WO2023133573A1 - Méthodes et systèmes de traitement d'états de douleur chronique à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies - Google Patents

Méthodes et systèmes de traitement d'états de douleur chronique à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies Download PDF

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WO2023133573A1
WO2023133573A1 PCT/US2023/060353 US2023060353W WO2023133573A1 WO 2023133573 A1 WO2023133573 A1 WO 2023133573A1 US 2023060353 W US2023060353 W US 2023060353W WO 2023133573 A1 WO2023133573 A1 WO 2023133573A1
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patient
pain
disorder
chronic
digital
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PCT/US2023/060353
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English (en)
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Steven BASTA
Simon Levy
Ann Harriet Montgomery
Julie Miller
Kayla KRAICH
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Mahana Therapeutics, Inc.
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Definitions

  • a patient when a patient is diagnosed with one or more medical conditions, the patient may be referred to additional health professionals for further care and treatment.
  • a patient may be referred to a psychologist, psychiatrist, counselor, or other mental health professional.
  • a patient may also be directed to one or more support groups to assist with any psychological distress that the patient may be experiencing. While these traditional face-to-face options may be greatly beneficial to a patient, often times they do not provide enough psychological support.
  • a patient when a patient is alone, at home, or not otherwise engaged directly with their mental health professional or support group, they may experience a significant degree of one or more negative emotional states, such as fear, anxiety, panic, and depression. Additionally, left unidentified and untreated, these negative emotional states often exacerbate the physical symptoms associated with a patient’s diagnosis, which in turn can lead to greater psychological distress.
  • chronic pain health conditions have significant impact on the quality of life of patients worldwide.
  • current approaches typically focus on reducing or eliminating physiological symptoms, by implementation of medication regimens, supplement regimens, diet changes, and/or lifestyle changes.
  • chronic pain health conditions have other adverse effects on lives of patients due to the nature of symptoms, and current approaches to treatment fail to address such adverse effects.
  • current methods of improving patient states associated with chronic pain health conditions are limited in relation to: educating patients regarding standard and non-standard treatment options; detecting, in real or near-real time, states of symptom severity in non-invasive manners; and delivering therapy in a customized and adaptive manner.
  • Behavioral therapy is also a valuable tool for addressing a variety of mental health issues, including anxiety and depression, and improving an individual’s ability to manage and respond effectively to external stimuli, such as stress.
  • Treatments based on behavioral therapy have been successfully applied to the management of chronic pain, either delivered alone or as a component of an integrated, multimodal pain management system.
  • Evidence suggests that behavioral therapy improves the functioning and quality of life for a variety of chronic pain conditions (e.g., Hoffman et al., Health Psychol. 2007 Jan; 26(1); Morley et al., Pain 1999 Mar;80(l-2)).
  • CBT cognitive behavioral therapy
  • a mental health professional such as a therapist, for example through regular sessions between an individual and their therapist.
  • Such interactions can be time consuming, inconvenient, and costly, thereby limiting accessibility of behavioral therapy treatment.
  • behavioral therapy is recommended as a first-line treatment for chronic pain, there remains a general shortage of clinicians who are trained to competence to provide behavioral interventions for chronic pain nor are their standardized training curriculums to ensure the consistent quality of providers.
  • Cognitive-behavioral therapy for chronic pain (“CBT-CP”) is acknowledged to have strong evidence of effectiveness, and though protocols differ across organizations, generally includes three components: (i) cognitive restructuring for unhelpful thoughts; (ii) paced behavioral activation to increase movement and engagement; and (iii) relaxation training to improve sympathetic nervous system responses.
  • Other psychological approaches including acceptance and commitment therapy, mindfulness, biofeedback, hypnosis, and emotional-awareness and expression therapy, have also garnered varying degrees of evidence across multiple pain conditions. Mechanistic studies have identified multiple pathways by which these treatments may reduce the intensity and impact of pain. However, a significant gap exists between the evidence for the effectiveness of these psychological interventions and their routine availability and use in clinical care.
  • NPS National Pain Strategy
  • Chronic pain disorders include, but not limited to migraine disorders, chronic headache or maxillofacial pain, temporomandibular disorders (e.g., temporomandibular joint disorders), migraines, fibromyalgia, chronic primary pain, chronic post-traumatic pain, chronic neuropathic pain, chronic pelvic pain (e.g., endometriosis, vulvar pain, vulvodynia, interstitial cystitis, bladder pain syndrome) and chronic muscoskeletal pain.
  • temporomandibular disorders e.g., temporomandibular joint disorders
  • migraines fibromyalgia
  • chronic primary pain chronic post-traumatic pain
  • chronic neuropathic pain chronic pelvic pain
  • chronic pelvic pain e.g., endometriosis, vulvar pain, vulvodynia, interstitial cystitis, bladder pain syndrome
  • chronic muscoskeletal pain e.g., endometriosis, vulvar pain, vulvodyn
  • NSAIDs NSAIDs
  • OCPs OCPs
  • GnRH gonadotrophin releasing hormone
  • Another chronic pain disorder is chronic pelvic pain in women.
  • CPP chronic pelvic pain
  • monotherapy is often unsuccessful for chronic pelvic pain, and combinations of different classes of medications are frequently prescribed, with the expectation of improved outcomes.
  • This approach combines both pharmacological agents and nonpharmacological therapy (e.g., bladder training, mindfulness) or multiple pharmacological agents.
  • migraine disorders patients suffer from moderate to severe headaches, which in some cases may be variably associated with nausea, vomiting, and sensitivity to light and sounds. While many headaches can be self-managed with simple analgesics, their efficacy tends to decrease with frequent use and overuse can lead to more headaches. Other limitations of pharmacological therapies include the high cost associated with ongoing medication, contraindications and medication intolerance. Harris et al., British J of Pain 2015, Vol 9(4) 213-224, at p. 214.
  • Medication-overuse headache usually resolves on discontinuation of the medication(s); however, patients often require some combination of preventive treatment to reduce the frequency of acute treatment need, use of alternative treatment(s), and/or abstinence, which may result in suboptimal treatment of individual attacks. Journal of the American Association of Nurse Practitioners: June 2021 - Volume 33 - Issue 6 - p 419-428
  • fibromyalgia Another chronic pain condition is fibromyalgia with patients experiencing various symptoms and comorbidities, including pain and stiffness all over the body, fatigue, depression, anxiety, obsessive compulsive disorder (OCD), headaches (including migraines), irritable bowel syndrome (IBS), pain in the face or jaw (including TMJ), and insomnia.
  • OCD obsessive compulsive disorder
  • IBS irritable bowel syndrome
  • TMJ irritable bowel syndrome
  • insomnia Many options are available to treat fibromyalgia, but no single option is effective for its symptom constellation. Even though the majority of the diagnosed fibromyalgia population receives prescription drug treatment, most current therapies suffer from shortcomings in efficacy.
  • Patients with chronic pain disorders often suffer from other disorders, such as anxiety, depression, post-traumatic stress disorder, attention deficit hyperactivity disorder (ADHD), cardiovascular disease, insomnia, chronic fatigue, fibromyalgia, hypertension, asthma, migraines/chronic headaches, TMJ and IBS. What is needed is a combination therapy that addresses the holistic universe of symptoms. Patients suffering chronic pain disorders also often experience lower sexual function and satisfaction due to pain, fear of pain, or associated problems, such as anxiety, depression, and lower desire and arousal, orgasm and satisfaction (collectively, “Sexual function”).
  • Pain is not a psychological phenomenon, but a real somatosensory experience generated by the CNS, in which psychosocial aspects (e.g., anxiety, fear of pain, hypervigilance, catastrophism and depression) have a great influence.
  • psychosocial aspects e.g., anxiety, fear of pain, hypervigilance, catastrophism and depression
  • CGRP or RAMP1 inhibitors can lead to dysbiosis, an imbalance in the gut, that makes the individual more susceptible to functional GI conditions (e.g., colitis, inflammatory bowel disease (IBD) and irritable bowel disease (IBS)).
  • functional GI conditions e.g., colitis, inflammatory bowel disease (IBD) and irritable bowel disease (IBS)
  • Embodiments of the present disclosure provide a technical solution to the technical problem of effectively, efficiently, and remotely treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies, in order to ensure that patients receive adequate care, support, and treatment.
  • the invention described herein is an innovative way to deliver interactive psychotherapies concurrent with pain medications via a prescription digital therapeutic platform broadly available to all chronic pain patients and optimized to improve the effectiveness of these combination therapies, including tailoring to address individual differences, addressing cooccurring disorders (many pain conditions are overlapping) and associated symptoms and medication side effects, and incorporating other optimization strategies.
  • the systems and methods disclosed herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing a chronic pain disorder in a patient. Further, the systems and methods disclosed herein allow behavioral therapy to be remotely administered to patients suffering from chronic pain disorders in a convenient and flexible, yet structured fashion, via a prescription digital therapeutics (DTX) system in combination with one or more non-behavioral therapies. In some embodiments, the invention(s) disclosed herein can employ non-traditional systems and methods for providing services such as interventions to patients exhibiting symptoms associated with one or more chronic pain health conditions.
  • DTX prescription digital therapeutics
  • the invention(s) can deliver psychologicalbased interventions to patients, such as, but not limited to, cognitive behavioral therapy (CBT), mindfulness therapy, relaxation therapy, somatic anchoring therapy, hypnotherapy, and acceptance and commitment (ACT)-based interventions, as well as other types of interventions, which are described in more detail below, by way of a platform having components implemented in a mobile device environment and/or other computer or internet-based architecture.
  • CBT cognitive behavioral therapy
  • ACT acceptance and commitment
  • the invention(s) use components of the platform to process large amounts of user data, remotely deliver personalized interventions, and remotely monitor user interactions with such interventions in near real-time in a manner that cannot be practically implemented by the human mind.
  • digital therapeutics (DTx) technologies may be used to administer behavioral therapy treatments in combination with a variety of non-behavioral therapy treatments in a controlled fashion, as treatment for one or more conditions described herein.
  • provided technologies address physiological conditions (e.g., conditions with one or more physical symptoms, features, or manifestations) that may be affected by a subject’s mental health state, for example, presence of a mental health condition such as, but not limited to anxiety, depression, and/or stress.
  • mental health conditions and/or stress levels may be triggered and/or worsened by symptoms of a particular associated physiological condition, and/or may trigger and/or worsen the symptoms of the same particular physiological conditions, for example, in a feedback-like manner, which is often referred to as a ‘vicious cycle.’
  • the DTx technologies disclosed herein can be used to administer guided behavioral therapies in combination with a variety of non-behavioral therapies to treat individuals suffering from certain particular physiological conditions.
  • the DTx technologies can be used in combination with treatments utilizing one or more pharmaceutical compositions.
  • chronic pain health conditions are particularly relevant, thus, in certain embodiments, guided behavioral therapy approaches disclosed herein may be administered, in combination with non-behavioral therapies (e.g., medications), to individuals suffering from one or more chronic pain health conditions. In this manner, approaches described herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing one or more symptoms associated with a variety of chronic pain health conditions.
  • the DTx system disclosed herein may be used to improve efficacy of other types of therapies and/or ameliorate side effects of other types of therapies.
  • guided behavioral therapy tools provided by the DTx system disclosed herein may facilitate adherence to various treatment regimens (e.g., of pharmaceutical compositions), and/or management of dosing (e.g., providing insight and/or guidance relevant to dosage adjustments).
  • the DTX technologies described herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing one or more side effects associated with one or more non-behavioral therapies for a chronic pain disorder in a patient who is undergoing said one or more non-behavioral therapies.
  • the DTX systems and methods may be used to treat, prevent, ameliorate, or reduce likelihood of developing one or more side effects associated with one or more medications used to treat a variety of chronic pain health conditions.
  • the DTx systems and methods disclosed herein may be used to enhance the performance of a non-digital therapeutic intervention administered to a patient for the treatment, prevention, amelioration, or reduction in the likelihood of developing a chronic pain disorder, and/or for the treatment, prevention, amelioration, or reduction in the likelihood of developing one or more symptoms associated with the chronic pain disorder.
  • the DTX systems and methods described herein may be used to enhance performance of the therapeutic intervention for the treatment, prevention, amelioration, or reduction in the likelihood of developing one or more side effects associated with the therapeutic intervention.
  • the DTx systems and methods disclosed herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing one or more comorbidities associated with a variety of chronic pain health conditions.
  • a patient is provided with a user interface to a prescription digital therapeutics (PDT) system wherein the PDT system remotely administers guided behavioral therapy to the patient.
  • PDT prescription digital therapeutics
  • a pre-assessment of a patient exhibiting one or more chronic pain health condition symptoms is performed by the DTX system to generate patient profile and pre-assessment data.
  • the patient profile and pre-assessment data is processed by the DTX system to generate patient condition data, wherein the patient condition data includes an identification of the patient’s condition, condition sub-type, and/or condition severity.
  • the patient profile and pre-assessment data and the patient condition data are processed by the DTX system to identify one or more complementary non-behavioral therapy components to be administered to the patient in combination with behavioral therapy components.
  • the patient profile and pre-assessment data and the patient condition data are processed by the DTX system to generate a personalized intervention regimen for the patient, wherein the personalized intervention regimen defines both behavioral therapy components and non- behavioral therapy components to be administered to the patient.
  • the one or more behavioral therapy components are administered, through the user interface of the DTX system, to the patient according to the personalized intervention regimen generated for the patient.
  • the one or more non-behavioral therapy components are administered to the patient in combination with the one or more behavioral therapy components according to the personalized intervention regimen generated for the patient.
  • the patient’s interactions with the one or more behavioral therapy components and the one or more non-behavioral therapy components are monitored remotely in near real-time to generate patient interaction data.
  • the patient interaction data is processed by the DTX system to generate intervention modification data representing recommended modifications to the patient’s personalized intervention regimen.
  • aspects of the behavioral therapy and/or the non-behavioral therapy components defined by the patient’s personalized intervention regimen are dynamically modified.
  • the invention(s) can also provide interventions that are tailored to individual users/patients suffering from a variety of symptoms, such as, but not limited to, moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light, sensitivity to sounds, pelvic pain, abdominal pain, bladder pain, fatigue, nausea, gastrointestinal symptoms, jaw pain, tenderness of jaw, tenderness of temporomandibular joint, pain at temporomandibular joint, tenderness in ears, tenderness around ears, pain in ears, facial tenderness, difficulty chewing, pain while chewing, pain and/or stiffness all over the body, pain in a particular area of the body, headaches, facial pain, insomnia, social/interpersonal effects, emotional effects, cognitive effects, and behavioral effects, in a customized manner, with implementation of real-time or near real-time assessments of data from multiple sources, including, but not limited to, electronic health record sources, self-report sources, and sensor sources.
  • symptoms such as, but not limited to, moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light
  • the invention(s) can also be used for acquisition of user/patient data from multiple data sources, including, but not limited to, health data, biometric data, user demographic data, pain scale data, user mood data, and user behavior data.
  • the invention(s) can also be used for generation of training datasets, whereby the training datasets can be used fortraining machine learning models (e.g., neural networks, etc.) that take input data pertaining to users/patients and produce outputs that can be used to guide customization of interventions.
  • machine learning models e.g., neural networks, etc.
  • the invention(s) can also be used to provide automated delivery of health-promoting or improving interventions, automated tracking/monitoring of user interactions with such interventions, automated communications with users (e.g., through transmission of notifications), and/or automated delivery of modified interventions to users, through a mobile device application platform and/or other platform (e.g., web platform).
  • a mobile device application platform and/or other platform e.g., web platform
  • such interventions can also be delivered as digital therapeutics, alone as a monotherapy or in combination with other therapeutics, such as medications and/or medical devices, through technical systems intended to diagnose and/or treat and/or improve symptoms or health-related quality of life, in collaboration with healthcare providers, health insurers, and/or other entities in the healthcare system.
  • the invention(s) can also employ non-traditional systems and methods for delivering prescription digital therapeutics (DTX) for improving patient health (e.g., in relation to disease management), whereby digital therapeutics are prescribed through healthcare providers (e g., with associated billing codes).
  • DTX prescription digital therapeutics
  • the invention(s) can include systems and methods for improving patient states (e.g., in the context of health, symptoms, disease progression, quality of life, and other contexts). Additionally or alternatively, in some embodiments, the system and/or method can confer any other suitable benefit.
  • the present disclosure provides methods for remotely administering behavioral therapy to a user/patient via a controlled progression of interactive therapy modules, through a graphical user interface (GUI) of a prescription digital therapeutics (DTX) system.
  • GUI graphical user interface
  • DTX prescription digital therapeutics
  • technologies described herein allow an individual user/patient to access and take part in a series of guided lessons that provide training in various behavioral skills. In one embodiment, these guided lessons may be presented as a sequence of interactive lesson modules that provide training and practice via a graphical user interface (GUI) of a DTX system.
  • GUI graphical user interface
  • approaches described herein provide structured behavioral therapy that is targeted at managing triggers and/or symptoms associated with specific physical conditions. Accordingly, in some embodiments, a behavioral therapy toolkit as provided by the systems and methods described herein can be tailored for a particular physical condition.
  • the present disclosure provides methods for providing for interactive creation of a user personal model via a graphical user interface (GUI) of a DTX system, allowing a user to identify cycles of behaviors, thoughts, emotions, and stressors that influence the frequency and/or severity of symptoms associated with a particular physical condition from which the user is suffering,
  • GUI graphical user interface
  • technologies described herein can increase access to and/or facilitate effective administration of behavioral therapy, and moreover can achieve effective impact on physiological conditions through guided behavioral therapy in combination with other types of therapies.
  • the present disclosure provides improvements to technologies and methods for administering cognitive behavioral therapy (CBT), relaxation therapy, somatic anchoring therapy, hypnotherapy, education and communication/assertiveness training around sexual functioning and alternative intimacy techniques (SFT), acceptance and commitment (ACT) therapy, pelvic floor physical therapy, pelvic floor relaxation therapy, and/or mindfulness-based therapy.
  • CBT cognitive behavioral therapy
  • SFT sexual functioning and alternative intimacy techniques
  • ACT acceptance and commitment
  • pelvic floor physical therapy pelvic floor relaxation therapy
  • mindfulness-based therapy provides improvements to technologies for administering a wide variety of therapy modalities, individually, or in combination with other modalities.
  • embodiments of the present disclosure provide a technical solution to the technical problem of effectively, efficiently, and remotely treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies, in order to ensure that patients receive adequate care, support, and treatment.
  • FIG. 1A depicts a schematic of a system for treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • FIG. IB depicts a block diagram of a production environment for treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • FIG. 2A depicts a flowchart of a method for treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • FIG. 2B depicts a flowchart of a method for providing adaptive interventions for chronic pain health conditions, according to one or more embodiments.
  • FIG. 2C depicts a flowchart of a method for providing adaptive interventions for chronic pain health conditions, according to one or more embodiments.
  • FIG. 3 A depicts a schematic of architecture implemented for delivery of intervention regimen components and/or modules, according to one or more embodiments.
  • FIG. 3B depicts examples of individual sections that may make up an introduction and education module of an intervention regimen, according to one or more embodiments.
  • FIG. 3C depicts examples of individual sections that may make up a pain management module of an intervention regimen, according to one or more embodiments.
  • FIG. 4 depicts an example of formation of a personal disease model, according to one or more embodiments.
  • FIG. 5A depicts a flowchart of a process for determining severity of a chronic pain condition, according to one or more embodiments.
  • FIG. 5B depicts examples of a process for determining severity of a chronic pain health condition, according to one or more embodiments.
  • FIG. 6 depicts a flowchart of a pre-assessment and onboarding process of a method for providing adaptive interventions, according to one or more embodiments.
  • FIG. 7 depicts examples of behavioral therapy modules of a program for personalized chronic pain condition monitoring and improvement, according to one or more embodiments.
  • FIG. 8A, FIG. 8B, FIG. 8C, FIG. 8D, and FIG. 8E depict example schematics of conditional branching architecture implemented for delivery of intervention regimen components, according to one or more embodiments.
  • FIG. 9 A, FIG. 9B, FIG. 9C, FIG. 9D, FIG. 9E, FIG. 9F, FIG. 9G and FIG. 9H are screenshots of several portions of an exemplary pain assessment for a system for treating chronic pain conditions using digital therapeutics, according to one or more embodiments.
  • FIG. 10A, FIG. 10B, FIG. 10C, and FIG. 10D are screenshots of GUIs for example user interactions with an initial communication lesson module for content tailored for a patient with chronic pain.
  • FIG. HA, FIG. 1 IB, FIG. 11C, FIG. HD, FIG.11E, and FIG. 1 IF, and FIG. 11G are screenshots of GUIs for exemplary user interactions to practice behavioral therapy tools, for a system for treating chronic pain conditions using digital therapeutics, in accordance with one or more embodiments.
  • FIG. 12A, FIG. 12B, FIG. 12C, FIG. 12D and FIG.12E are screenshots of an exemplary GUI for a symptom diary lesson module, according to one or more embodiments.
  • FIG. 13A, FIG. 13B, FIG. 13C, FIG 13D, FIG. 13E, FIG. 13F, FIG 13G, FIG. 13H, FIG. 131, FIG. 13J, and FIG. 13K are screenshots of example user interactions with a symptom diary practice module, in accordance with one or more embodiments.
  • FIG. 14A, FIG. 14B, FIG. 14C, FIG. 14D, and FIG. 14E are screenshots of an exemplary GUI for introducing a personal model lesson module, in accordance with one or more embodiments.
  • FIG. 15 A, FIG. 15B, FIG. 15C, FIG. 15D, FIG. 15E, FIG. 15F, FIG. 15G, FIG. 15 H, FIG. 151, FIG. 15J and FIG. 15K are screenshots of an exemplary GUI for a personal model lesson module, according to one or more embodiments.
  • FIG. 16A is a screenshot of an exemplary personal model graphical representation, according to one or more embodiments.
  • FIG. 17A, FIG. 17B, FIG. 17C, FIG. 17D, FIG. 17E, FIG. 17F, FIG. 17G, FIG. UH and FIG. 171 are screenshots of an exemplary GUI for a reflections section of a personal model lesson module, according to one or more embodiments.
  • FIG. 18A, FIG. 18B, FIG. 18C, FIG. 18D and FIG. 181 are screenshots of an exemplary GUI for a pain management lesson module, according to one or more embodiments.
  • FIG. 19A, FIG. 19B, FIG. 19C, FIG 19D, FIG. 19E, FIG. 19F, FIG 19G, FIG. 19H, FIG. 191, FIG. 19J, FIG. 19K, and FIG. 19L are screenshots of an exemplary GUI for a sexual functioning lesson module, according to one or more embodiments.
  • FIG. 20A, FIG. 20B, FIG. 20C, and FIG. 20D are screenshots of an exemplary GUI for a pain management lesson module, according to one or more embodiments.
  • the systems and methods disclosed herein allow behavioral therapy to be administered to patients suffering from chronic pain health conditions in a convenient and flexible, yet structured fashion, via a digital therapeutics (DTX) system in combination with one or more non-behavioral therapies.
  • DTX digital therapeutics
  • behavioral therapy may include therapies such as, but not limited to, psychotherapy; cognitive behavioral therapy (CBT); education and communication/assertiveness training around sexual functioning and alternative intimacy techniques (SFT); acceptance and commitment (ACT) therapy; pelvic floor physical therapy; pelvic floor relaxation therapy; dialectical behavioral therapy (DBT); exposure therapy; mindfulness-based cognitive therapy (MCBT); hypnotherapy; somatic anchoring therapy, experiential therapy; psychodynamic therapy; relaxation therapy; biofeedback therapy; and combinations thereof.
  • therapies such as, but not limited to, psychotherapy; cognitive behavioral therapy (CBT); education and communication/assertiveness training around sexual functioning and alternative intimacy techniques (SFT); acceptance and commitment (ACT) therapy; pelvic floor physical therapy; pelvic floor relaxation therapy; dialectical behavioral therapy (DBT); exposure therapy; mindfulness-based cognitive therapy (MCBT); hypnotherapy; somatic anchoring therapy, experiential therapy; psychodynamic therapy; relaxation therapy; biofeedback therapy; and combinations thereof.
  • CBT cognitive behavioral therapy
  • SFT sexual functioning and alternative intimacy techniques
  • ACT acceptance and commitment
  • such guided behavioral therapy technologies are based at least in part on cognitive behavioral therapy (CBT), and provide structured modules and/or lessons via a graphical user interface (GUI) of a prescription digital therapeutics (DTX) system, for example to allow patients to develop a skillset for treating a physiological disease, disorder and/or condition, and for managing stress and/or other psychological symptoms associated with such disease, disorder and/or condition.
  • CBT cognitive behavioral therapy
  • GUI graphical user interface
  • DTX prescription digital therapeutics
  • a relevant disease, disorder or condition may be or comprise a chronic pain condition, such as, but not limited to migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic neuropathic pain, and combinations thereof.
  • a chronic pain condition such as, but not limited to migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic neuropathic pain, and
  • approaches described herein provide patients with structured behavioral therapy that is targeted at managing triggers and/or symptoms associated with specific physical and/or physiological conditions.
  • physiological conditions such as chronic pain conditions
  • symptoms and effects of these physiological conditions may trigger and/or worsen related mental health conditions and can be a source of significant stress for many patients.
  • This feedback loop can create a vicious cycle, in which symptoms of a particular physiological condition trigger and/or worsen mental health states, causing issues such as anxiety and/or depression, which, in turn, trigger and/or worsen physical/physiological symptoms. Feedback loops of this kind are particularly relevant to chronic pain health conditions.
  • symptoms associated with a chronic pain condition may be triggered by stress, and mental health conditions such as depression and/or anxiety can worsen such symptoms.
  • physical pain, as well as the many complexities of managing the chronic pain condition are themselves significant stressors and may contribute to attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), post-traumatic stress disorder (PTSD), depression and/or anxiety.
  • ADHD attention deficit hyperactivity disorder
  • OCD obsessive compulsive disorder
  • PTSD post-traumatic stress disorder
  • a behavioral therapy toolkit as provided by technologies (e.g., systems and methods) disclosed herein can be tailored for a particular physical/physiological condition.
  • particular behavioral therapy lesson modules can be designed to facilitate tracking of specific symptoms, tracking and elucidating specific stressors, and/or providing targeted exercises (e.g., breathing, progressive relaxation, etc.), which are well suited for managing specific triggers and symptoms of the particular physiological condition.
  • behavioral therapy lesson modules targeted at a chronic pain health condition such but not limited to migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic neuropathic pain, and combinations thereof, may include specially designed symptom diaries, trigger trackers, personal model interfaces and/or other types of therapy modules, which allow a user to discover and reflect upon combinations of stressors, triggers, thoughts, and symptoms that contribute to their own, personal, vicious cycle.
  • a chronic pain health condition such but not limited to migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain,
  • the technologies, methods, and systems disclosed herein provide a valuable complement to physician visits and recommendations (e.g., with regard to lifestyle changes) and standard of care therapies (e.g., administration of medication(s)). Furthermore, technologies disclosed herein can increase access to and/or facilitate effective administration of behavioral therapy to achieve effective impact on physiological conditions such as, but not limited to, chronic pain health conditions, through guided behavioral therapy.
  • the term “patient,” and/or “subject,” may include an individual who is suffering from a relevant disease, disorder or condition.
  • a patient/ subject is an individual who is susceptible to a disease, disorder, or condition.
  • a patient/ subject displays one or more symptoms or characteristics of a disease, disorder or condition.
  • a patient/subject does not display any symptom or characteristic of a disease, disorder, or condition.
  • a patient/subject is someone with one or more features characteristic of susceptibility to or risk of a disease, disorder, or condition.
  • a patient/subject is an individual to whom diagnosis and/or therapy is and/or has been administered.
  • a patient/subject is an individual who has been diagnosed with one or more diseases, disorders, and/or conditions and is the recipient of one or more therapies in a clinical or non- clinical setting. In some embodiments, a patient/subject is an individual who has not been diagnosed with a health condition, but is a recipient of one or more therapies in a clinical or non-clinical setting.
  • DTX digital therapeutics system
  • the term “therapeutics system” or “digital therapeutics system” is a software application that delivers psychoeducation and digital behavioral therapy to users with chronic pain conditions and, in some cases, concomitant health conditions.
  • the DTX system may require prior approval by a government agency before it is marketed or may be marketed to users without preapproval. It may be purchased by users “over the counter” (OTC), or recommended or prescribed by health care providers.
  • the term “prescription digital therapeutics (PDTs)” and/or “prescription digital therapeutics (PDT) system,” may include a system utilized for remotely administering a therapy to a patient, wherein the PDT system is required to be approved by a government agency before it can be marketed for administration to humans.
  • a PDT system requires FDA approval and rigorous clinical evidence to substantiate intended use and impact on disease state.
  • a PDT system is typically a system for which a medical prescription is required for administration to patients.
  • PDT systems are a sub category of DTX systems.
  • the term “user” may include a patient/subject who utilizes a therapeutics system or a prescription digital therapeutics system.
  • an individual who is “suffering from” a disease, disorder, and/or condition displays one or more symptoms of a disease, disorder, and/or condition and/or has been diagnosed with the disease, disorder, or condition.
  • the term “therapy,” “behavioral therapy,” and/or “guided behavioral therapy” may include psychological techniques, methodologies, and/or modalities intended or demonstrated to achieve impact on and/or alteration of one or more behaviors of a patient/subject.
  • therapies may include, but are not limited to, psychotherapy, cognitive behavioral therapy (CBT), education and communication/assertiveness training around sexual functioning and alternative intimacy techniques (SFT), acceptance and commitment (ACT) therapy, pelvic floor physical therapy, pelvic floor relaxation therapy, dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), relaxation therapy, biofeedback therapy, somatic anchoring therapy, hypnotherapy, experiential therapy, and psychodynamic therapy.
  • mind-body intervention may include one or more therapeutic practices that employ a variety of techniques designed to facilitate the mind’s capacity to affect bodily function and systems.
  • Examples of mind-body interventions may include, but are not limited to, relaxation, imagery, biofeedback, meditation, hypnosis, tai, chi, and yoga.
  • the phrase “administration” may include providing, delivering, and/or applying a therapy to a patient.
  • a therapy may be administered to a patient directly by a health practitioner.
  • a therapy may be administered to a patient remotely, for example, over the internet or through a computer system, without the direct involvement of a health practitioner.
  • the therapy may be self-administered by the patient.
  • a therapy may also be administered to a patient remotely with partial involvement of a health practitioner.
  • the therapy to be administered may be selected by a health practitioner, but the therapy may then be self-administered by the patient, utilizing a computer system, or the therapy may be administered to the patient by a computer system, but a health practitioner may monitor the patient’ s response data.
  • compositions may be administered by one or more routes such as ocular, oral, parenteral, topical, etc.
  • administration may involve dosing, application, or interaction that is intermittent (c.g, a plurality of doses separated in time) and/or periodic (e.g., individual doses separated by a common period of time) dosing.
  • administration may involve continuous dosing (e.g., perfusion), application or interaction for at least a selected period of time.
  • the term “treat,” “treatment,” or “treating” may include administration of therapy that has been established to partially or completely alleviate, ameliorate, relieve, inhibit, prevent, delay onset of, reduce severity of, and/or reduce incidence of one or more symptoms or features of a disease, disorder, and/or condition (e.g., when administered to a relevant population).
  • treatment may be administered to a patient who is not exhibiting (and/or has not exhibited) one or more signs of a relevant disease, disorder, and/or condition.
  • treatment may be administered to a patient who exhibits only early signs of the disease, disorder, and/or condition, for example for the purpose of decreasing risk of developing one or more features of pathology associated with the disease, disorder, and/or condition.
  • a treatment is termed “therapeutic” when administered to a patient who is displaying or has displayed one or more features, symptoms, or other characteristics of a relevant disease, disorder and/or condition.
  • a treatment is termed “prophylactic” when administered to a patient who has not displayed features, symptoms, or other characteristics of a relevant disease, disorder and/or condition.
  • the term “protocol” or “therapeutic protocol” may include procedures and/or systems of rules for administration of a therapy.
  • a therapeutic protocol defines the rules, syntax, semantics, and synchronization of communications with a patient.
  • a therapy may include a series of modules, lessons, questionnaires, and exercises, and a related protocol may dictate the order, speed, and/or frequency in which various modules, lessons, exercises and questionnaires are presented to a patient.
  • a protocol may also dictate the specific layout, content and general presentation of the various lessons, exercises and questionnaires.
  • a protocol can be as specific as to dictate each word or sequence of words selected for use in the therapy.
  • a therapy may be administered to a patient according to any number of protocols or any number of combinations of protocols.
  • a therapeutic regimen may include a therapy for administration to a patient as part of a therapeutic treatment, wherein the therapy is administered to the patient according to a specific set of therapeutic protocols.
  • a therapeutic/intervention regimen for a behavioral therapy may include a specific set of modules, lessons, questionnaires, exercises, and other content, which may be administered to a patient in a particular order, at a particular frequency, utilizing a particular layout, etc.
  • a therapeutic/intervention regimen for a non-behavioral therapy may include administration of a non-behavioral therapy, such as a pharmaceutical or nutraceutical composition, in a particular amount, according to a particular dosing schedule.
  • a therapeutic/intervention regimen may be correlated with a desired or beneficial therapeutic outcome.
  • a therapeutic/intervention regimen may be personalized or tailored to meet the needs of a specific patient.
  • the term “combination therapy” may include situations in which a subject is simultaneously exposed to two or more therapeutic regimens (e.g., two or more therapeutic modalities and/or agents).
  • the two or more regimens may be administered simultaneously; in some embodiments, such regimens may be administered sequentially (e.g., all “doses” of a first regimen are administered prior to administration of any doses of a second regimen); in some embodiments, such modalities and/or agents are administered in overlapping dosing regimens.
  • “administration” of combination therapy may involve administration of one or more agent(s) or modality(ies) to a subject receiving the other agent(s) or modality(ies) in the combination.
  • combination therapy does not require that individual agents be administered together in a single composition (or even necessarily at the same time), although in some embodiments, two or more agents, or active moieties thereof, may be administered together in a combination composition, or even in a combination compound (e.g., as part of a single chemical complex or covalent entity).
  • the term “therapeutic agent” may include any agent that elicits a desired effect when administered to an organism, e.g., in a pharmaceutical composition, via a digital therapeutics system, and/or according to a therapeutic regimen as described herein.
  • an agent is considered to be a therapeutic agent if it demonstrates a statistically significant effect across an appropriate population.
  • the appropriate population may be a population of model organisms.
  • an appropriate population may be defined by various criteria, such as a certain age group, gender, genetic background, preexisting conditions, etc.
  • a therapeutic agent can be used to alleviate, ameliorate, relieve, inhibit, prevent, delay onset of, reduce severity of, and/or reduce incidence of one or more symptoms or features of a disease, disorder, and/or condition.
  • the term “dosing regimen” and/or “dosing schedule” may include a set of unit doses (typically more than one) that are administered individually to a subject, typically separated by periods of time.
  • a given therapeutic agent or modality has a recommended dosing regimen, which may involve one or more doses.
  • a dosing regimen comprises a plurality of doses each of which is separated in time from other doses.
  • individual doses are separated from one another by a time period of the same length; in some embodiments, a dosing regimen comprises a plurality of doses and at least two different time periods separating individual doses.
  • all doses within a dosing regimen are of the same unit dose amount. In some embodiments, different doses within a dosing regimen are of different amounts. In some embodiments, a dosing regimen comprises a first dose in a first dose amount, followed by one or more additional doses in a second dose amount different from the first dose amount. In some embodiments, a dosing regimen comprises a first dose in a first dose amount, followed by one or more additional doses in a second dose amount same as the first dose amount In some embodiments, a dosing regimen is correlated with a desired or beneficial outcome when administered across a relevant population (i.e., is a therapeutic dosing regimen).
  • the term “pharmaceutical composition” may include a composition in which an active agent is formulated together with one or more pharmaceutically acceptable carriers.
  • the active agent is present in unit dose amount appropriate for administration in a therapeutic regimen that has been established a statistically significant probability of achieving a predetermined therapeutic effect when administered to a relevant population.
  • a pharmaceutical composition may be specially formulated for administration in a particular form (e.g., in a solid form or a liquid form), and/or may be specifically adapted for, for example: oral administration (for example, as a drenche [aqueous or non-aqueous solutions or suspensions], tablet, capsule, bolus, powder, granule, paste, etc., which may be formulated specifically for example for buccal, sublingual, or systemic absorption); parenteral administration (for example, by subcutaneous, intramuscular, intravenous or epidural injection as, for example, a sterile solution or suspension, or sustained-release formulation, etc.); topical application (for example, as a cream, ointment, patch or spray applied for example to skin, lungs, or oral cavity); intravaginal or intrarectal administration (for example, as a pessary, suppository, cream, or foam); ocular administration; nasal or pulmonary administration, etc.
  • oral administration for example, as a drenche
  • nutraceutical composition may include a composition comprising one or more food(s) and/or food component(s), and/or one or more microbiome components, that provide medical or health benefits.
  • a nutraceutical is or comprises a component selected from the group consisting of microorganisms, proteins, vitamins, herbs, and combinations thereof, such as bacteria.
  • nutraceutical compositions are dietary supplements.
  • nutraceutical compositions are medical foods.
  • the term “amelioration” may include prevention (e.g., delay), reduction (e.g., in frequency and/or intensity), improvement, and/or palliation of a state, or one or more features thereof, experienced by a patient. Amelioration may include, but does not require, complete recovery or complete prevention of a disease, disorder or condition (e.g., radiation injury).
  • an appropriate reference measurement may be or may comprise a measurement in a particular system (e.g., in a single individual) under otherwise comparable conditions absent (e.g., prior to and/or after addition of) a particular agent or treatment, or in presence of an appropriate comparable reference agent.
  • an appropriate reference measurement may be or may comprise a measurement in a comparable system known or expected to respond in a particular way, for example in presence of the relevant agent or treatment.
  • prevention when used in connection with the occurrence of a disease, disorder, and/or condition, may include reducing a risk of developing the disease, disorder and/or condition and/or to delaying onset of one or more characteristics or symptoms of the disease, disorder or condition. Prevention may be considered complete when onset of a disease, disorder or condition has been delayed for a predefined period of time.
  • patient illness narrative may include a narrative expressed by a patient regarding the patient’s personal experiences with a disease, disorder, and/or condition.
  • An illness narrative is typically a narrative solicited from a patient, which enables a healthcare practitioner to build a more complete picture of the patient’s past and present health state in the context of the patient’s life, while providing the patient with an opportunity for self-reflection and validation.
  • a personal model and/or “personal disease model” may include a construction built based on patient input, which enables the patient to identify stressors, counterproductive behaviors, unhelpful thoughts, and negative emotions as associated with the patient’s disease, disorder, and/or condition.
  • a personal model is constructed as a graphical representation, which comprises text corresponding to patient-selected counter-productive behavior(s), unhelpful thought(s), and negative emotion(s), superimposed on a flow diagram illustrating links between the patient’s behaviors, thoughts, and emotions.
  • a personal model graphical representation comprises text corresponding to causes and/or stressors of symptoms.
  • a personal model may be utilized to help a patient identify links between their behaviors, thoughts, and emotions, and to help a patient consider possible changes in their behavior that could be implemented to address their symptoms.
  • the term “ecological momentary assessment” may include repeatedly sampling a subject’s current behaviors and experiences in real time, in the subject’s natural environment, with the aim of minimizing recall bias and allowing study of microprocesses that influence behavior in real-world contexts.
  • machine learning module may include a computer implemented process that implements one or more particular machine learning algorithms, such as supervised, unsupervised, and semi-supervised systems, an artificial neural network (ANN), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values.
  • ANN artificial neural network
  • FIG. 1A depicts a schematic of a system 100A for treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • system 100A includes: an online system 110 for digital content associated with the adaptive interventions, one or more client devices including client device 120 for delivering the behavioral therapy and skills training to one or more users, one or more external systems including external system 130, and a network 140 for data transmission between the online system 110, the client device(s) 120, and the external system(s) 130.
  • the system 100A includes functionality for educating patients (e.g., patients, users of the platform, etc.) regarding treatment and therapy options in the context of improving symptoms associated with chronic pain health conditions; detecting, in real or near-real time, states of chronic pain health condition symptom severity in non-invasive manners; and delivering therapeutic interventions in a customized, and adaptive manner to one or more users/patients exhibiting chronic pain health condition symptoms.
  • patients e.g., patients, users of the platform, etc.
  • therapeutic interventions in a customized, and adaptive manner to one or more users/patients exhibiting chronic pain health condition symptoms.
  • the system 100A can provide tailored cognitive behavioral therapies (CBTs) and/or other therapeutic modalities, such as psychotherapy, acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), relaxation therapy, biofeedback therapy, exposure therapy, mindfulness-based cognitive therapy (MCBT), hypnotherapy, experiential therapy, and psychodynamic therapy for patients in an adaptive and customizable manner.
  • CBTs cognitive behavioral therapies
  • ACT acceptance commitment therapy
  • DBT dialectical behavioral therapy
  • MCBT mindfulness-based cognitive therapy
  • hypnotherapy hypnotherapy
  • experiential therapy and psychodynamic therapy
  • components of the above-listed therapeutic modalities may be combined to tailor a therapeutic intervention regimen to the needs of a particular patient.
  • variations of the system 100A can be adapted for generation and provision of interventions for systems associated with other health conditions.
  • the online system 110 functions to generate, store, and transmit digital content associated with the behavioral therapy and related adaptive interventions, according to algorithms that allow the online system 110 to administer (or guide administration) of interventions to patients in a timely and customized manner.
  • the online system 110 thus procures digital content associated with one or more therapeutic interventions and allows users/patients of the system 100A to access the digital content in an active or passive manner, in order to improve the patient(s)’ ability to manage chronic pain health condition symptoms.
  • the online system 110 can include content generation components 112, content storage components 114, content transmission components 116, communication elements 118, and/or analytic platform 119 elements, implemented in computer architecture.
  • the online system 110 can additionally or alternatively include any other suitable subsystems or components associated with administration of guided therapy, adaptive interventions, and/or monitoring of patient health condition states.
  • the online system 110 can include computing architecture configured for generation of interactive digital objects in computer-readable formats, where such interactive digital objects can be included in modules of therapeutic interventions provided to patients exhibiting one or more chronic pain health condition symptoms.
  • the content generation components 112 can include architecture for generation of content in one or more of: visual formats (e.g., with image objects, video objects, etc.), audible formats, haptic formats, and any other suitable formats.
  • Such content can be delivered through output devices of other components of the system 100A, such as display components (e.g., of a device, of an augmented reality device, of a virtual reality device, etc.), speaker components, haptic output device components, and/or any other suitable components.
  • the online system 110 can include architecture for storage and retrieval of computer-readable media associated with digital content and/or other objects.
  • Data storage systems can be associated with any suitable format, and include components configured for cloud and/or non-based cloud computing.
  • the information stored in the content storage components 114 can be organized according to specific data structures (e.g., with relational, columnar, correlation, or other suitable architecture).
  • Stored content can be associated with various digital objects (e.g., graphical/textual/audio/visual/haptic objects associated with content, and/or rearrangement of objects within particular environments, as associated with therapeutics and/or communications between entities, as described in more detail below).
  • the online system 110 can be configured to transmit content over wired and/or wireless interfaces, through network 140 (described in more detail below).
  • the content transmission components 116 of the online system 110 can include interfaces to the network 140, for content transmission to client devices 120 and/or external systems 130.
  • the online system 110 can include elements that enable communications between patients and other entities (e.g., care providers, coaches associated with health interventions, other patients, etc.) in text format, in audio format, and/or in any other suitable formats.
  • the online system 110 can support messaging, calling, and/or any other suitable communication types using web or other computer-based communication subsystems.
  • the online system 110 can include architecture for an analytics platform 119 for performing analytics in relation to generation of interventions (e.g., digital therapeutics as monotherapies, digital therapeutics as combinatorial therapies), evaluation of performance of interventions (e.g., in relation to performance, in relation to effectiveness, etc.), modification of interventions (e.g., in relation to content aspects, in relation to frequency aspects, etc.), provision of interventions (e.g., delivery method, etc.), generating and processing training data for refinement of models for intervention generation and provision, and other architecture for performing analytics.
  • interventions e.g., digital therapeutics as monotherapies, digital therapeutics as combinatorial therapies
  • evaluation of performance of interventions e.g., in relation to performance, in relation to effectiveness, etc.
  • modification of interventions e.g., in relation to content aspects, in relation to frequency aspects, etc.
  • provision of interventions e.g., delivery method, etc.
  • generating and processing training data for refinement of models for intervention generation and provision e.g., delivery method, etc.
  • one or more portions of the online system 110 can include processing subsystem components comprising non-transitory media storing instructions for executing one or more method operations described below.
  • the processing subsystem components can be distributed across the online system 110, client devices 120, and external systems 130, or organized in any other suitable manner.
  • the online system 110 can be implemented in a network-addressable computing system that can host one or more components for generating, storing, receiving, and sending data (e.g., content-related data, user-related data, data related to entities associated with various therapeutics, etc.).
  • the online system 110 can thus be accessed by the other components of the system 100A either directly or via network 140 described below.
  • the online system 110 can include one or more servers (e.g., unitary servers, distributed servers spanning multiple computers or multiple datacenters, etc.).
  • the servers can include one or more server types (e.g., web server, messaging servers, advertising servers, file servers, application servers, exchange servers, database servers, proxy servers, etc.) for performing functions or processes described.
  • each server can thus include one or more of: hardware, software, and embedded logic components for carrying out the appropriate functionalities associated with the method(s) described below.
  • the client device(s) 120 function to deliver the behavioral therapy and/or adaptive interventions generated and/or stored by the online system 110 to patients exhibiting chronic pain health condition symptoms in a timely manner.
  • the client device(s) 120 can include computing components, input devices, and/or output devices providing interfaces for receiving patient inputs and transmitting digital content data and/or sensor-derived data over the network 140 (described in more detail below).
  • the client device(s) 120 can include one or more of: mobile computing devices (e.g., a smartphone a personal digital assistant); a conventional computing system (e.g., desktop computer, laptop computer); a tablet computing device; a wearable computing device (e.g., a wrist-borne wearable computing device, a head-mounted wearable computing device, an apparel-coupled wearable computing device); a toilet-interfacing computing device; and any other suitable computing device.
  • mobile computing devices e.g., a smartphone a personal digital assistant
  • a conventional computing system e.g., desktop computer, laptop computer
  • a tablet computing device e.g., a wearable computing device (e.g., a wrist-borne wearable computing device, a head-mounted wearable computing device, an apparel-coupled wearable computing device); a toilet-interfacing computing device; and any other suitable computing device.
  • a wearable computing device e.g., a wrist-borne wearable computing device, a head-mounted wearable computing device
  • the client device(s) 120 can be configured to store and/or execute an application (e g., mobile application, web application) that allows a user of the client device 120 to interact with the online system 110 by way of the network 140, in order to receive digital content associated with one or more therapeutic interventions and/or provide data associated with survey responses, sensor-derived data associated with interactions with such interventions, and/or any other suitable data.
  • the client device(s) 120 can include operation modes for administering treatments to the user (e.g., in relation to providing prescription digital therapeutics upon diagnosis of the chronic pain health condition of the user, in relation to providing medications, in relation to providing pain management therapies, etc.).
  • the external system(s) 130 function to transmit data (e.g., 3 rd party data) and/or receive data (e.g., 3 rd party data) associated with therapeutic interventions and/or user data (e.g., patient data).
  • the external system(s) 130 can include systems associated with electronic health records (EHRs) of the patient(s), systems associated with collection and/or storage of patient data (e.g., biometric data, behavioral data, social network data, communication data, etc.), systems associated with care providers (e.g., health insurance providers, health care practitioners, etc.), and/or any other suitable systems.
  • EHRs electronic health records
  • care providers e.g., health insurance providers, health care practitioners, etc.
  • the external system(s) can provide applications for communicating data in a manner that is protective of personal health information (PHI) and/or other sensitive patient data. Additionally or alternatively, the external system(s) can be associated with 3 rd party content generators and generate digital content in visual formats, audible formats, haptic formats, and/or any other suitable formats.
  • PHI personal health information
  • the external system(s) can be associated with 3 rd party content generators and generate digital content in visual formats, audible formats, haptic formats, and/or any other suitable formats.
  • the external system(s) 130 and/or client device(s) 120 can be configured to interact with the online system 110 by way of an application programming interface (API) executing on a native operating system of the external system(s) 130 and/or client device(s), in order to access API-associated data associated with the therapeutic interventions, patient health records, and/or other data (e.g., biometric data, patient behavior data through social networks, communication data through communication subsystems, etc.).
  • API application programming interface
  • the external system(s) 130 and/or client devices 120 can further include sensing components configured to generate data from which patient biometrics and/or behaviors can be extracted.
  • the external system(s) 130 and/or client devices 120 can include sensing components associated with one or more of: activity of a patient (e.g., through accelerometers, gyroscopes, motion coprocessing devices, etc.); facial expressions of the patient (e.g., through eye tracking, through image/video processing) for determination of cognitive states (e.g., associated with depression, anxiety, emotions, etc.) and/or performance of activities and/or interacting with content provided through the intervention regimen; physiological and/or psychological stress of a patient (e.g., in relation to respiration parameters, in relation to cardiovascular parameters, in relation to galvanic skin response, in relation to neurological activity, in relation to other stress biometrics, etc.); sleep behavior of a patient (e.g., with a sleepmonitoring device);
  • activity of a patient e.g., through accelerometers
  • the external system(s) 130 and/or client devices 120 can include components for extracting behavioral data associated with communications and social behavior, which can be indicative of changes in patient health associated with different symptoms.
  • Such components can include location sensors (e.g., direct location sensors, location sensing modules based on connections to local networks, triangulation systems, etc.) for tracking user motility and/or other behavior patterns, components associated with API access to social networking data, components associated with messaging communication behavior (e.g., components for accessing SMS or other messaging application data of a patient, with respect to messaging entities, messaging content, etc.), components associated with calling communication behavior (e.g., in relation to inbound/outbound calls, in relation to call duration, in relation to call content, etc.), data from digital assistants (e.g., voice-activated digital assistants) and any other suitable components from which behavioral data can be extracted.
  • location sensors e.g., direct location sensors, location sensing modules based on connections to local networks, triangulation systems, etc.
  • components associated with API access to social networking data
  • the network 140 functions to enable data transmission between the online system 110, the client device(s) 120, and the external system(s) 130, in relation to detection of patient states of wellbeing (e.g. with respect to chronic pain health condition symptoms).
  • the network 140 can include a combination of one or more of local area networks and wide area networks, and/or can include wired and/or wireless connections to the network 140.
  • the network 140 can implement communication linking technologies including one or more of: Ethernet, worldwide interoperability for microwave access (WiMAX), 802.11 architecture (e.g., Wi-Fi, etc.), 3G architecture, 4G architecture, 5G architecture, long term evolution (LTE) architecture, code division multiple access (CDMA) systems, digital subscriber line (DSL) architecture, and any other suitable technologies for data transmission.
  • WiMAX worldwide interoperability for microwave access
  • 802.11 architecture e.g., Wi-Fi, etc.
  • 3G architecture 4G architecture
  • 4G architecture 5G architecture
  • long term evolution (LTE) architecture long term evolution
  • CDMA code division multiple access
  • DSL digital subscriber line
  • the network 140 can be configured for implementation of networking protocols and/or formats including one or more of: hypertext transport protocol (HTTP), multiprotocol label switching (MPLS), transmission control protocol/Intemet protocol (TCP/IP), file transfer protocol (FTP), simple mail transfer protocol (SMTP), hypertext markup language (HTML), extensive markup language (XML), and any other suitable protocol/format.
  • HTTP hypertext transport protocol
  • MPLS multiprotocol label switching
  • TCP/IP transmission control protocol/Intemet protocol
  • TCP/IP file transfer protocol
  • SMTP simple mail transfer protocol
  • HTML hypertext markup language
  • XML extensive markup language
  • the network 140 can also be configured for and/or provide, through communication links, encryption protocols for improving security of patient data transmitted over the network 140.
  • the system 100A can include or be configured to interface with other system components associated with generation and/or delivery of behavioral therapy and related adaptive interventions.
  • the system 100A can include or be associated with environmental control devices configured to affect patient states of wellbeing passively or actively, in relation to the intervention types described in more detail below.
  • such devices can include environmental control devices, including one or more of: lighting control devices, audio output devices, temperature control devices, and any other suitable environmental control devices.
  • the system 100A can coordinate operation of such devices with delivery of adaptive interventions to patients, such that aspects of the patient’s environment can be modulated in coordination with other therapeutic measures to improve patient wellbeing in relation to chronic pain health condition symptoms.
  • the system 100A can include and/or communicate control instructions for devices in the environment of the patient, in order to facilitate control of pain volume, in relation to magnitude of pain/intensity of pain (e.g., by focusing the user on real time environmental changes) and/or to cause improvements in lives of patients in another suitable manner.
  • the system 100A can include an output device (e.g., component of client device 120, component of external system 130, etc.) that functions as an environmental control device in an environment of the patient, where the processing subsystem further includes instructions for adjusting the operation mode in coordination with monitoring a change in symptoms (e.g., pain symptoms) of the patient. Modulation of output device operation modes can thereby produce an adjustment in symptoms (e.g., pain volume) associated with the condition of the patient.
  • the environmental control device can modulate one or more of: an audio output, a thermal parameter adjustment, a visually-observed output, a haptic output, and a light output in the environment.
  • the system 100A can include an output device (e.g., component of client device 120, component of external system 130, etc.) that functions as a communication device for transmitting communications between the patient and an entity associated with the patient, where the processing subsystem further includes instructions for generating a scripted communication for transmission to an entity associated with the patient, in coordination with monitoring a change in a physiological symptoms of the patient.
  • an output device e.g., component of client device 120, component of external system 130, etc.
  • the processing subsystem further includes instructions for generating a scripted communication for transmission to an entity associated with the patient, in coordination with monitoring a change in a physiological symptoms of the patient.
  • system 100A can be configured to interface or include any other suitable system components.
  • Embodiments, variations, and examples of one or more components of the system 100A described above can implement one or more embodiments, variations, and examples of the methods 200A, 200B, and/or 200C, as described below.
  • the system 100A can additionally or alternatively be configured to implement other methods.
  • FIG. IB depicts a block diagram of a production environment 100B for treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • production environment 100B includes DTX computing environment 141, patient 142, and patient computing systems 144.
  • production environment 100B optionally includes patient monitoring devices 146, health practitioner 148, and/or health practitioner computing systems 149.
  • production environment 100B includes communications channels 143, which facilitate communication between DTX computing environment 141 and one or more of patient computing systems 144, patient monitoring devices 146, and health practitioner computing systems 149.
  • DTX computing environment 141 includes DTX user interface 150, patient monitoring system 152, patient condition determination system 166, personalized regimen generation system 168, content selection system 170, and module gating system 172.
  • DTX computing environment 141 further includes patient database 156.
  • patient database 156 includes patient profde and pre-assessment data 158, patient condition data 162, patient personalized regimen data 164, and patient interaction data 154.
  • DTX computing environment 141 further includes therapeutic module database 174.
  • therapeutic module database 174 includes therapeutic module data 176, which further includes first therapeutic module 178, and second therapeutic module 184 through Nth therapeutic module 190.
  • first therapeutic module 178 includes module 1 content data 180 and module 1 protocol data 182
  • second therapeutic module 184 includes module 2 content data 186 and module 2 protocol data 188
  • Nth therapeutic module 190 includes module N content data 192 and module N protocol data 194.
  • DTX computing environment 141 further includes processor 196 and physical memory 198, which together coordinate the operation and interaction of the data and data processing systems associated with DTX computing environment 141.
  • processor 196 and physical memory 198 which together coordinate the operation and interaction of the data and data processing systems associated with DTX computing environment 141.
  • patient 142 is provided with a prescription digital therapeutics (DTX) system, wherein the DTX system remotely administers guided behavioral therapy through an adaptive intervention regimen including a plurality of interactive therapy modules.
  • DTX prescription digital therapeutics
  • the DTX computing environment 141 communicates with patient 142 via one or more communications channels 143 between patient computing systems 144 and a user interface of the DTX system, such as DTX user interface 150.
  • therapeutic module database 174 contains a repository of data related to each of the available therapy modules, including module content data and module protocol data.
  • a therapeutic protocol defines the rules, syntax, semantics, and synchronization of communications with a patient.
  • the therapeutic module database may be populated and/or updated periodically by health practitioner 148, for example, through health practitioner computing systems 150.
  • module gating system 172 is responsible for determining which parts of the intervention regimen patient 142 has already completed, if any, as well as determining which modules and/or module content should be gated, locked, and/or unlocked. The operation of module gating system 172 will be discussed in additional detail below.
  • content selection system 170 may select module 1 content data 180 from first therapeutic module 178 of therapeutic module database 174. Content selection system 170 may then administer module 1 content data 180 to patient 142 through DTX user interface 150. In one embodiment, module 1 content data 180 is administered to patient 142 according to one or more therapeutic protocols defined by module 1 protocol data 182.
  • first therapeutic module 178 may be an introduction and education module, which introduces the patient to the system features, and provides education to the patient relating to the methods utilized by the system and/or relating to the patient’ s particular disease, disorder, and/or condition.
  • first therapeutic module 178 also generates patient profile and pre-assessment data 158 by virtue of interaction between patient 142 and the content provided through DTX user interface 150 of the DTX system.
  • patient profile and pre-assessment data is generated independently of first therapeutic module 178. Additional details regarding first therapeutic module 178 (the introduction and education module) will be provided below.
  • content selection system 170 may select module 2 content data 186 from second therapeutic module 184 of therapeutic module database 174. Content selection system 170 may then administer module 2 content data 186 to patient 142 through DTX user interface 150. In one embodiment, module 2 content data 186 is administered to patient 142 according to one or more therapeutic protocols defined by module 2 protocol data 188.
  • second therapeutic module 184 may be a physical illness narrative module, which, in some embodiments, solicits narratives from the patient regarding the impact that the patient’s disease, disorder, and/or condition has had on their lifestyle, mental state, and overall well-being.
  • second therapeutic module 184 generates patient illness narrative data (not shown) by virtue of interaction between patient 142 and the content provided through DTX user interface 150 of the DTX system.
  • second therapeutic module 184 also introduces the patient to the concept of a personal disease model, and guides the user through the process of creating a personal model.
  • second therapeutic module 184 solicits additional data from the patient for use in creation of the personal model, such as data related to the patient’s counter-productive behaviors, unhelpful thoughts, and negative emotions. Additional details regarding second therapeutic module 184 (the physical illness narrative module) will be provided below.
  • patient profde and pre-assessment data 158 is processed by patient condition determination system 166 of the DTX system to generate patient condition data 162, as will be discussed in additional detail below.
  • personalized regimen generation system 168 utilizes patient profde and pre-assessment data 158 and patient condition data 162 to generate a personalized intervention regimen for the patient, which is represented in FIG. IB by patient personalized regimen data 164.
  • patient personalized regimen data 164 includes data representing regimen details such as, but not limited to, which of the available remaining therapy modules to administer to the patient, in what order to administer the therapy modules, a time schedule for when/how often to administer the therapy modules, what content to include in each of the therapy modules, and how to present the therapy module content to the patient.
  • personalized regimen generation system 168 may further process patient profile and pre-assessment data 158 and patient condition data 162 to identify one or more current or potential complementary therapies to be administered to patient 142 in combination with the behavioral therapy components represented by therapeutic module data 176.
  • complementary therapies may include one or more non-behavioral therapies, such as pharmaceutical and/or nutraceutical compositions, and personalized regimen generation system 168 may incorporate data related to administration of such therapies (e.g. therapy type, dosage amount, and dosage schedules) into patient personalized regimen data 164. Additional details regarding generation of a personalized intervention regimen for the patient will be discussed below.
  • patient personalized regimen data 164 is provided to module gating system 172 to determine which components of the intervention should be gated, locked, or unlocked, and content selection system 170 may then administer content data related to the appropriate therapeutic module to patient 142 through DTX user interface 150.
  • content selection system 170 may provide one or more options, notifications, alerts, and/or recommendations to patient 142 through DTX user interface 150, wherein the one or more options, notifications, alerts, and/or recommendations relate to current or potential complementary (non-behavioral) therapies to be administered in combination with the behavioral therapy modules/components.
  • the patient’s interactions with the behavioral therapy components and/or the patient’s interactions with and/or reactions to the non- behavioral therapy components of the personalized intervention regimen may be monitored remotely, either at fixed intervals, or in near real-time.
  • the patient’s interactions with the regimen components such as through a patient monitoring system 152 of the DTX system, or through external patient monitoring devices 146, such as sensors, etc., which may then transmit patient data and/or patient interaction data 154 over one or more communications networks 143.
  • the progression of the user through the through the therapeutic modules may be dynamically and remotely controlled, for example, though a system such as module gating system 172.
  • module gating system 172 may be programmed to gate, lock, or unlock various modules and module components at set intervals. If the patient interaction data 154 indicates that the user would benefit from shorter or longer intervals between lesson modules, module gating system 172 may dynamically adjust how often to unlock new content. A more detailed description of the module gating system used to dynamically and remotely control user progression through the modules will be provided below.
  • the patient’s personalized intervention regimen may be modified and/or updated. For example, user input in one module might change the recommendation for how to present subsequent modules, and a patient’s reactions to one more non-behavioral therapy components may change the recommendations for the dosing of that particular component. In the case where the patient is being remotely monitored in near real-time, this allows for the personalized intervention regimen to be dynamically adaptive, thus resulting in administration of the guided therapy in combination with other types of chronic pain therapies in a manner that is most efficient and effective for the patient. Additional details regarding dynamically modifying the patient’s personalized intervention regimen will be discussed in further detail below.
  • FIG. 2A depicts a flowchart of a method 200A for treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • the method 200A can include operations for: providing a patient with a user interface to a digital therapeutics (DTX) system wherein the DTX system remotely administers guided behavioral therapy to the patient 204; performing, by the DTX system, a pre-assessment of a patient exhibiting one or more chronic pain health condition symptoms to generate patient profile and pre-assessment data 206; processing, by the DTX system, the patient profile and pre-assessment data to generate patient condition data, wherein the patient condition data includes an identification of the patient’s condition, condition sub-type and/or condition severity 208; processing, by the DTX system, the patient profile and pre-assessment data and the patient condition data to identify one or more complementary non-behavioral therapy components to be administered to the patient in combination with behavioral therapy components 210; processing, by the DTX system, the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient, where
  • DTX digital therapeutics
  • the pre-assessment (and/or subsequent monitoring assessments) comprise(s) a health-related quality of life metric, an emotional impact of pain metric, and a pain self- efficacy metric.
  • assessments can be measured against metrics from a database of patients with similar chronic pain conditions, or from the patient’s own baseline metric(s).
  • method 200A functions to educate users regarding treatment and therapy options in the context of improving symptoms associated with a variety of health conditions; detect, in real or near-real time, states of health condition symptom severity in non-invasive manners; and administer therapeutic interventions in a customized, and adaptive manner to one or more patients exhibiting health condition symptoms.
  • the method 200A can be used to provide tailored behavioral therapy to patients in an adaptive and customizable manner.
  • the method 200A can be used to provide behavioral therapy to patients in combination with other types of complementary, non-behavioral therapies. Method 200A will be discussed in additional detail below.
  • providing guided behavioral therapy and skills training includes providing adaptive interventions for patients with chronic pain health conditions.
  • FIG. 2B depicts a flowchart of a method 200B for providing adaptive interventions for chronic pain health conditions, according to one or more embodiments.
  • a method 200B can include operations for: performing a pre-assessment of a patient exhibiting one or more chronic pain health condition symptoms 226; generating an intervention regimen for the patient upon processing data from the preassessment with an intervention-determining model 228; delivering the intervention regimen to the patient 230; monitoring a set of interactions between the patient and modules of the intervention regimen and a health status progression of the patient contemporaneously with delivery of the intervention regimen 232; and in response to at least one of the set of interactions and the health status progression, performing an action configured to improve wellbeing of the patient with respect to the chronic pain health condition 234.
  • Method 200B will be discussed in additional detail below.
  • FIG. 2C depicts a flowchart of a method 200C for providing adaptive interventions for chronic pain health conditions, according to one or more embodiments.
  • a method 200C can include operations for: establishing an interface between a device and a user 240; from the interface, receiving a set of signals associated with a health condition of the user, wherein the set of signals encodes physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user 242; determining a characterization of the chronic pain health condition upon processing the set of signals with a model 244; based upon the characterization, modulating content of a treatment comprising a set of components, the set of components comprising a subset of cognitive behavioral therapy (CBT) components for improving a state of the user 246; and administering the treatment to the user 248.
  • CBT cognitive behavioral therapy
  • Methods 200B and 200C function to educate patients regarding treatment and therapy options in the context of improving symptoms associated with chronic pain health conditions; detect, in real or near-real time, states of chronic pain health condition symptom severity in non-invasive manners; and deliver interventions in a customized, and adaptive manner to one or more users exhibiting chronic pain health condition symptoms.
  • methods 200B and 200C can be used to provide tailored cognitive behavioral therapy (CBT) and/or other therapeutic modalities to patients in an adaptive and customizable manner. While Chronic pain health condition symptoms are described, variations of the methods 200B and 200C can be adapted for generation and provision of interventions for systems associated with other health conditions.
  • CBT cognitive behavioral therapy
  • aspects of methods 200A, 200B, and 200C can be performed at desired frequencies (e.g., weekly, more often than weekly, less often than weekly).
  • desired frequencies e.g., weekly, more often than weekly, less often than weekly.
  • the method can promote interactions more often than weekly (e.g., daily, 2 times a week, 3 times a week, four times a week, five times a week, six times a week, etc.) or less often than weekly, in relation to reinforcement of skills acquired by the patients.
  • received data can be processed in real time, or non-real time.
  • the methods 200A, 200B, and 200C can have delivery and processing aspects associated with other suitable frequencies.
  • the methods 200A, 200B, and 200C can be performed by an embodiment, variation, or example of the system 100A described in above (e.g., in relation to processing subsystem components with instructions stored in non-transitory media and other input/output devices); however, the methods 200A, 200B, and 200C can additionally or alternatively be performed using any other suitable system components.
  • FIG. 2A depicts a flowchart of a method 200A for treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • method 200A begins at BEGIN 202, and method flow proceeds to operation 204.
  • a patient is provided with a user interface to a digital therapeutics system wherein the DTX system remotely administers guided behavioral therapy to the patient.
  • a patient may consult with one or more healthcare practitioners regarding symptoms that the patient is experiencing, and the healthcare practitioner may determine that the patient is suffering from one or more health-related conditions.
  • therapies such as, but not limited to, psychotherapy; cognitive behavioral therapy (CBT); education and communication/assertiveness training around sexual functioning and alternative intimacy techniques (SFT); acceptance and commitment (ACT) therapy; pelvic floor physical therapy; pelvic floor relaxation therapy; dialectical behavioral therapy (DBT); exposure therapy; mindfulness-based cognitive therapy (MCBT); hypnotherapy; experiential therapy; psychodynamic therapy; relaxation therapy; biofeedback therapy; and combinations thereof.
  • components of the above listed modalities may be combined to form a hybrid type of therapy.
  • a hybrid therapy may utilize particular components taken from CBT, ACT, SFT and DBT, wherein the components are selected based on the specific needs of the patient.
  • behavioral therapies can also be combined with other types of non-behavioral therapies, as will be discussed in detail below.
  • behavioral therapy and in particular cognitive behavioral therapy (CBT) has traditionally been considered effective for treatment of psychological conditions such as, for example, alcohol and drug use problems, anxiety disorders, depression, chronic fatigue disorders, eating disorders, emotional trauma, grief or loss, marital or other relationship problems, mental illness, obsessive-compulsive disorder, (OCD) pain, phobias, post- traumatic stress disorder (PTSD), schizophrenia, sexual disorders, sleep disorders, etc.
  • CBT cognitive behavioral therapy
  • OCD obsessive-compulsive disorder
  • PTSD post- traumatic stress disorder
  • behavioral therapy has traditionally involved counseling by a mental health provider such as a psychiatrist, psychologist, or other provider; typically, behavioral therapy provides a structured format and a limited (i.e., finite) number of sessions.
  • the present disclosure provides new behavioral therapy technologies which may, in some embodiments, be provided to an individual via non-human interactions, such as via a computer-based system.
  • computer-based systems are designed to mimic portions of interactions, such as useful exercises, assessments, and techniques that may traditionally be carried out in the context of counseling sessions with a mental health provider and/or via exercises recommended thereby (e.g., ‘homework,’ such as values inventories, journaling exercises, self-assessments, and the like).
  • provided behavioral therapies may be useful in the treatment of certain physiological conditions, such as, but not limited to, chronic pain health conditions (e.g., migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic neuropathic pain, and combinations thereof.
  • chronic pain health conditions e.g., migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic n
  • the doctor may prescribe a therapeutics system to the patient.
  • the therapeutics system is a prescription digital therapeutics (PDT) system.
  • PDT prescription digital therapeutics
  • aPDT system differs from traditional computer-based wellness and digital therapeutics systems, in that the PDT system is required to be approved by a government agency before it can be marketed for administration to humans.
  • a PDT system requires FDA approval and rigorous clinical evidence to substantiate intended use and impact on disease state.
  • a PDT system is typically a system for which a medical prescription is required for administration to patients.
  • DTX digital therapeutics
  • an embodiment of the online system in coordination with the network and a client device, can perform the pre-assessment of operation 206 contemporaneously with executing an onboarding process with the patient with the online system.
  • Operation 206 functions to retrieve data describing characteristics of the patient, preferences of the patient, goals of the patient and/or any other suitable patient features that can be used to provide adaptive interventions through an intervention regimen associated with administration of guided behavioral therapy to the patient in a customized and personalized manner.
  • operation 206 can include pre-assessing and onboarding patients to generate patient profile and pre-assessment data, wherein the patient profile and pre-assessment data includes one or more of: demographics (e.g., genders, ages, familial statuses, residential location, ethnicities, nationalities, socioeconomic statuses, sexual orientations, etc.), household situations (e.g., living alone, living with family, living with a caregiver, etc.), relationship status (e.g., active intimate relationship), levels of activity, levels of pain severity, psychological symptom severity, pain triggers, medical history associated with area of pain, durations of mindfulness (e.g., mindful minutes), and any other suitable patient characteristic associated with chronic pain health conditions.
  • demographics e.g., genders, ages, familial statuses, residential location, ethnicities, nationalities, socioeconomic statuses, sexual orientations, etc.
  • household situations e.g., living alone, living with family, living with a caregiver, etc.
  • relationship status e.g., active intimate
  • patient profile and pre-assessment data generated at operation 206 includes data related to non-behavioral therapies that the patient is receiving and/or has received.
  • patient profile and pre-assessment data may include data such as, but not limited to, data indicating the type of non-behavioral therapy (e.g., pharmaceutical, nutraceutical, etc.), data indicating the class of non-behavioral therapy (e.g., almotriptan, eletriptan, frovatriptan, naratriptan, rizatriptan, sumatriptan, zolmitriptan, sumatriptan/naproxen, ergotamines, lasmiditan, acetaminophen, ibuprofen, aspirin, meloxicam, feldene, celocoxib, peroxicam, diclofenac, naproxen, ketorolac, opioids, gepants, ditans, topiramate,
  • the non-behavioral therapy comprises one or more pharmaceutical compositions each comprising at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, non-steroidal anti-inflammatories, opioids, gepants, ditans, barbiturate-containing analgesics, ergot alkaloids, ergotamines, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, anticonvulsants, antidepressants, a-blockers, 5-a-reductase inhibitors, beta blockers, ACE inhibitors, progestins, angiotensin II receptor antagonists, calcium channel blockers, CNS depressants, quinolones, tetracyclines, serotonin norepinephrine reuptake inhibitors, serotonin reuptake inhibitors, serotonin 5-HT receptor
  • the one or more pharmaceutical compositions may each comprise at least one compound independently selected from the list of medication for chronic pain disorders indicated in Table 1 below.
  • Table 1 Medications for various chronic pain disorders- Migraine, fibromyalgia, endometriosis/chronic pelvic pain, TMD/TMJ
  • patient profile and pre-assessment data includes data, such as, but not limited to, physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the patient.
  • the pre-assessment and/or onboarding process performed in operation 206 can identify mental health statuses of the patient, in relation to comorbid or non- comorbid conditions (e.g., associated with anxiety, associated with depression, associated with social behavior, etc.), where the intervention regimen described in more detail below can be configured to improve mental health states of the patient in a timely and adaptive manner.
  • related data can include psychological and/or disease symptom/clinical profile data that informs selection of high priority therapy components, where examples include data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia characteristics of the patient, promoting behavioral activation content by the system and response chaining, where response chaining involves linking of effortful avoided tasks to those that are neutral or slightly rewarding); sources of motivation; reward sensitivity (e.g., sensitivity associated with drive and reward responsiveness (e.g., using a BIS/BAS assessment tool); and threat sensitivity.
  • data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia
  • the method 200A can include receiving a reward sensitivity dataset characterizing motivation and reinforcement behavior of the patient, and modulating aspects of the treatment upon processing the reward sensitivity dataset with one or more models described herein.
  • Mental health, reward tendencies and sensitivity, and motivational aspect identification can, however, be assessed outside of the pre-assessment of operation 206.
  • the pre-assessment and/or onboarding process performed in operation 206 can identify user preferences associated with scheduling of content delivery (e.g., in relation to frequencies of content delivery described above) associated with one or more aspects of the intervention regimen, preferred formats (e.g., visual formats, audio formats, haptic formats, etc.) of content delivery, frequency of content delivery, location of user when content is delivered, specific device(s) to which content is delivered, and/or any other suitable user preferences.
  • preferred formats e.g., visual formats, audio formats, haptic formats, etc.
  • the pre-assessment and/or onboarding process performed in operation 206 can identify user goals for improving health, in relation to the intervention regimen.
  • Such goals can include one or more goals, such as, but not limited to: reduction of anxiety, reduction of negative emotions, reduction of depression symptoms, improvement of sleep behavior, improvement in socialization, improvement of chronic pain health condition symptoms, improvement of medication adherence, improvement in chronic pain-related quality of life, improvement of other health condition symptoms, and/or any other suitable goals.
  • Goals can be organized at a high level of abstraction (e.g., improve sleep behavior), and/or at lower levels of abstraction (e.g., improve quality of sleep, reduce number of symptom-induced disturbances to sleep, etc.).
  • the patient profde and pre-assessment data can be obtained through various mechanisms, including, but not limited to, from a pre-assessment module of the DTX system, from patient health records accessible by the DTX system, from API access of health monitoring systems through the DTX system, and/or from biometric sensor data obtained by the DTX system from various devices utilized by the patient.
  • patient profile and pre-assessment data can be collected repeatedly throughout performance of the methods described herein, as will be discussed in additional detail below.
  • the online system and/or other system components can implement surveying tools (e.g., to obtain self-report data from the patient) and/or non-survey-based tools for acquisition of data.
  • Survey tools can be delivered through an application associated with the DTX system executing on the client device of the patient and/or through another suitable method, where the survey tools can implement architecture for assessing the patient in relation to mental health, pain, chronic pain health symptom severity or disease activity, types of chronic pain health condition symptoms, and/or other statuses.
  • the surveying tools can be derived from one or more patient reported outcome instruments, such as, but not limited to: a Numbered Pain Scale (NPS); a Numbered Rating Scale (NRS); a Verbal Rating Scale (VRS); a Visual Analog Scale (VAS); a Categorical Scale; a Quantitative Scale; a Qualitative Scale; a COMFORT Scale; a McGill Pain Questionnaire; a Mankoski Pain Scale; a Brief Pain Inventory (BPI); a Descriptor Differential Scale of Pain Intensity (DDS-I); a Universal Pain Assessment Tool (UP AT); Pain Catastrophizing Scale (PCS), Pain Anxiety Symptom Scale (PASS-20), Patient-Reported Outcomes Measurement Information System (PROMIS), Vulvar Pain Assessment Questionnaire (VPAQ), Female Sexual Distress Scale (FSDS), Patient Health Questionnaire (PHQ), Duke Health Profile (DUKE), mHealth App Usability Questionnaire
  • NPS Numbered
  • the surveying tools comprise one or more patient reported data resulting in a health-related quality of life metric or score, an emotional impoact of pain metric or score, and a pain self efficacy metric or score. In one embodiment, these metrics is combined into a single pain impact score.
  • survey components can be implemented during pre-assessment of a patient and/or within modules of the intervention regimen, as described in more detail below.
  • the online system and/or other system components can implement data from devices (e.g., non-survey data).
  • embodiments of the system can perform pre-assessment with implementation of data from devices including one or more devices, such as, but not limited to: electronic health record-associated devices; wearable devices (e.g., wrist-borne wearable devices, head-mounted wearable devices, etc.) for monitoring behavior and activities (e.g., related to physiological/cognitive stress, related to respiration activity, related to sedentary and active states, etc.) of the user; non-invasive torso-coupled devices; ingestible smart-pill devices; smart toilet devices and/or other devices for analyzing stool and/or urine samples from the patient; and other devices.
  • devices including one or more devices, such as, but not limited to: electronic health record-associated devices; wearable devices (e.g., wrist-borne wearable devices, head-mounted wearable devices, etc.) for monitoring behavior and activities (e.g., related to physiological/cognitive stress, related to respiration activity, related to sedentary and active states, etc.) of the user; non-invasive torso
  • Non-survey-derived data can additionally or alternatively include data derived from API access of social networking platforms, other communication platforms (e.g., for extracting social behavior characteristics associated with text, voice, and other communications of the users), locationdetermining platforms, and/or other platforms, in order to assess social behaviors of the user.
  • multiple surveying tools may be combined in a single assessment module, or may be provided as distinct, separate, assessment modules.
  • Assessment modules may be based on, and used to solicit input for, a variety of diagnostic questionnaires, depending on a particular chronic pain health condition that a patient is to be evaluated for. Additionally or alternatively, assessment modules may be designed to evaluate any other physiological and/or psychological conditions of the patient.
  • data pertaining to patient symptoms, quality of life, and other medical information may be obtained via access to electronic health records (EHRs) and/or electronic medical records (EMRs).
  • EHRs electronic health records
  • EMRs electronic medical records
  • applications in accordance with technologies as described herein may provide for communication with a secure database in order to receive and/or access EHR and/or EMR data for the user.
  • data may be used to populate a patient profile, and as a basis for tailoring content, e.g., as described herein.
  • method flow proceeds to operation 208.
  • the DTX system processes the patient pre-assessment data to generate patient condition data, wherein the patient condition data includes an identification of the patient’s condition, condition sub-type, and/or condition severity.
  • processing of the patient pre-assessment data in operation 208 can result in identification of the patient as having chronic pain health condition symptoms associated with chronic pain, such as, but not limited to, one or more of: migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic neuropathic pain, and/or any other suitable symptoms.
  • chronic pain health condition symptoms associated with chronic pain such as, but not limited to, one or more of: migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulv
  • processing of the patient assessment data at 208 can result in identification of a subtype of a chronic pain health disorder.
  • a chronic pain health disorder This includes, but not limited to subtypes of migraine, fibromyalgia, endometriosis, chronic pelvic pain, temporomandibular disorders (including temporomandibular joint disorders), etc.
  • processing of the patient pre-assessment data in operation 208 can result in identification of the patient as having one or more comorbidities associated with chronic pain, such as, but not limited to, one or more of: a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, an attention deficit hyperactivity disorder, an obsessive compulsive disorder, a post-traumatic stress disorder, an eating disorder, a substance use disorder, an anhedonia disorder, a cardiovascular disease, a sleep disorder, chronic fatigue, inflammatory bowel syndrome, fibromyalgia, tinnitus, hypertension, asthma, gastroesophageal reflux disease, functional dyspepsia, and/or any other suitable comorbidities.
  • a generalized anxiety disorder such as, but not limited to, one or more of: a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, an attention deficit hyperactivity disorder, an obsessive compulsive disorder, a post-traumatic stress disorder, an eating disorder, a
  • operation 208 can further identify one or more sub-types of a chronic pain health condition, and/or one or more sub-types of comorbidities associated with the chronic pain health condition.
  • a type of chronic pain disorder is endometriosis, which can be further classified into a variety of subtypes.
  • the DTX system can be configured to receive, automatically detect, or automatically extract information regarding the particular subtype(s) of IBS that a patient has, based on a combination of patient health record data, data collected from health monitoring systems, data collected from biometric sensors, and data collected from patient-reported outcome instruments, in order to prioritize relevant content provided to the patient, in the interests of customizing the program.
  • subtypes of endometriosis include ovarian endometriosis (endometriomas), superficial peritoneal endometriosis, and deep infiltrating endometriosis. If the processing operation 208 identifies that the patient is predominantly subtype ovarian endometriosis, subsequent portions of the intervention regimen can prioritize content associated more highly with ovarian endometriosis. In some embodiments, however, subtype identification may be determined outside of the processing of operation 208.
  • operation 208 of method 200A includes a method of determining severity of the chronic pain health condition.
  • operation 208 can calculate levels of a chronic pain health condition-associated marker (e.g., from a sample from the patient, such as a stool sample or a breath sample, from interactions with the system, etc.) to identify the patient as having a certain state of severity (e.g., expression, phenotype, etc.) of the chronic pain health condition.
  • a chronic pain health condition-associated marker e.g., from a sample from the patient, such as a stool sample or a breath sample, from interactions with the system, etc.
  • operation 208 can be implemented through the DTX system executing on a mobile device or other device associated with the patient, where a user interface of the DTX system prompts inputs from the patient pertaining to various symptoms (e.g., moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light, sensitivity to sounds, pelvic pain, abdominal pain, bladder pain, fatigue, nausea, gastrointestinal symptoms, jaw pain, tenderness of jaw, tenderness of temporomandibular joint, pain at temporomandibular joint, tenderness in ears, tenderness around ears, pain in ears, facial tenderness, difficulty chewing, pain while chewing, pain and stiffness all over the body, pain in specific area, headaches, facial pain, insomnia, etc.), generates a report indicating severity of the chronic pain health condition (e.g., migraine, fibromyalgia, endometriosis, chronic pelvic pain, TMD/TMJ, etc.).
  • various symptoms e.g., moderate to severe headaches, headaches associated with nausea,
  • the DTX system disclosed herein can include architecture for receiving data derived from the patient (e.g., through sensor components, through survey components, associated with pain characteristics, motion limitation characteristics, digestive characteristics, cognitive function characteristics, and other characteristics), processing the data with one or more models, and returning scores (e.g., measures of symptom severity, etc.). Scores can also be used for tagging user data with symptom severity, in relation to model aspects and model training/refinement described below.
  • method flow proceeds to operation 210.
  • the patient profile and preassessment data and the patient condition data are processed to identify one or more complementary non-behavioral therapy components to be administered to the patient in combination with behavioral therapy components.
  • the digital therapeutics (DTX) system disclosed herein may utilize behavioral therapy components in combination with non-behavioral therapy components to provide treatment for various physiological conditions (e.g., conditions with one or more physical symptoms, features, or manifestations), such as those described herein.
  • the DTX system disclosed herein may administer behavioral therapies and associated components in combination with one or more non-behavioral therapies and associated components, such as those described herein.
  • behavioral therapy is administered to subject(s) who are receiving or have received non-behavioral therapy for a relevant disease, disorder, or condition.
  • behavioral therapies and non-behavioral therapies may be approved, and/or administered as a combination product.
  • digital therapeutics (DTX) systems and methods described herein are utilized to administer guided behavioral therapy to a patient undergoing treatment for one or more chronic pain health conditions via administration of one or more non-behavioral therapies.
  • non-behavioral therapies for chronic pain health conditions, including, for example, pharmaceutical compositions such as, but not limited to: triptans, non-opioid analgesics, non-steroidal anti-inflammatories, opioids, gepants, ditans, barbiturate-containing analgesics, ergot alkaloids, ergotamines, corticosteroids, calcitonin gene- related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, anticonvulsants, antidepressants, a-blockers, 5-a-reductase inhibitors, beta blockers, ACE inhibitors, progestins, angiotensin II receptor antagonists, calcium channel blockers, CNS depressants, quinolones, tetracyclines, serotonin norepinephrine reuptake inhibitor
  • pharmaceutical compositions such as, but not limited to: triptans, non-opioid analgesics, non
  • particular agents that may be utilized in therapy for chronic pain health conditions may include one or more of: almotriptan, el etriptan, frovatriptan, naratriptan, rizatriptan, sumatriptan, zolmitriptan, sumatriptan/naproxen, ergotamines, lasmiditan, acetaminophen, ibuprofen, aspirin, meloxicam, feldene, celocoxib, peroxicam, diclofenac, naproxen, ketorolac, opioids, gepants, ditans, topiramate, divalproex sodium, valproate sodium, metoprolol, propranolol, timolol, atenolol, nadolol, barbiturate containing analgesics, dihydroergotamine, ergotamine, corticosteroids, prednisone, dexamethas
  • DTX may be used in combination with one or more pharmaceutical compositions for the treatment, prevention, amelioration, or reduction in the likelihood of developing a chronic pain disorder in a patient.
  • the chronic pain disorder is migraine
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, non-steroidal anti-inflammatories, opioids, gepants, ditans, anticonvulsants, beta blockers, barbiturate-containing analgesics, ergot alkaloids, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, ACE inhibitors, angiotensin II receptor (ARBS) antagonists, calcium channel blockers, antidepressants, botulinum toxin, and combinations thereof.
  • CGRP calcitonin gene-related peptide
  • ARBS angiotensin II receptor
  • the chronic pain disorder is fibromyalgia
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of anticonvulsants, antidepressants, opioids, muscle relaxants, CNS depressants, and combinations thereof.
  • the chronic pain disorder is chronic pelvic pain
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of a-blockers, 5-a-reductase inhibitors, opioids, quinolones, tetracyclines, antidepressants, anticonvulsants, non-steroidal anti-inflammatory drugs, muscle relaxants, cannabinoids, progestins, anxiolytics, neuroleptics, calcium channel blockers, botulinum toxin, N- methyl-D-aspartate (NDMA) glutamate receptor antagonists, and combinations thereof.
  • a-blockers 5-a-reductase inhibitors
  • opioids quinolones, tetracyclines
  • antidepressants anticonvulsants
  • non-steroidal anti-inflammatory drugs muscle relaxants
  • cannabinoids progestins
  • anxiolytics neuroleptics
  • calcium channel blockers botulinum toxin
  • NDMA N-
  • the chronic pain disorder is a temporomandibular disorder
  • the temporomandibular disorder including temporomandibular joint disorder
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of non-steroidal anti-inflammatory drugs, corticosteroids, bioactive compounds, isolated compounds, anxiolytics, benzodiazepines, carbamates, barbiturates, barbiturate-like hypnotics, opioids, antidepressants, anticonvulsants, 5HT receptor agonists, botulinum toxin, corticosteroids, hyaluronic acid, dietary supplements, celecoxib, cannabis-related drugs, muscle relaxants, and combinations thereof.
  • one or more non-behavioral therapies utilized for treatment of chronic pain health conditions may include nutraceutical compositions such as supplements, probiotics, prebiotics, synbiotics, natural products, herbal therapies (e.g., feverfew, butterbur, curcumin, menthol/peppermint oil, etc.).
  • nutraceutical compositions such as supplements, probiotics, prebiotics, synbiotics, natural products, herbal therapies (e.g., feverfew, butterbur, curcumin, menthol/peppermint oil, etc.).
  • One or more non-behavioral therapies may further include nutritional therapies (e.g., enteral nutrition), acupuncture, mind-body interventions (e.g., relaxation, meditation, yoga), whole system medicine (e.g., Eastern Medicine, Ayurveda), and physical exercises.
  • One or more non-behavioral therapies may further include therapies utilizing a variety of medical devices, such as, but not limited to, the one or more medical devices are each independently selected from the group consisting of wearable devices, ingestible devices, implanted devices, biofeedback devices, Transcutaneous electrical nerve stimulation (TENS) and microcurrent nerve stimulation (MENS) devices, remote electrical neuromodulation (REN) device, non-invasive vagus nerve stimulation (nVNS) device, transcranial magnetic stimulator, pressure sensors, acupressure or motion sensor mat, phototherapy devices, compression devices, heat therapy devices, and combinations thereof.
  • a patient suffering from a chronic pain health condition may be treated using any combination of the above listed non-behavioral therapies.
  • the digital therapeutics (DTX) systems and methods disclosed herein collect patient medication information, for example in the pre-assessment operation discussed above, via interactive lesson modules such as a pre-assessment module, via modules specifically related to medication, etc., and/or via user entry into a user profile.
  • the digital therapeutics (DTX) systems and methods described herein may collect and offer recommendations regarding an amount and/or timing of dosage of particular medications. Such recommendations regarding amount and/or timing may be absolute and/or relative to other events and/or activities. For example, recommendations may comprise a particular schedule of dosage, e.g., a particular rate, timing (e.g., in a morning, afternoon, or evening), etc.
  • Timings and/or amounts relative to other activities may include timings and/or amounts relative to other activities, such as meal consumption, physical exercises, seasons, social gatherings, travel, work, etc.
  • recommendations may be based on data provided by the patient, for example in daily symptom diary entries, via assessment modules, personal model creation modules, etc., such as those described in more detail below.
  • such recommendations are generated via use of one or more machine learning modules that receive, as input, data corresponding to patient symptom and/or habits, as tracked by various modules such as those described herein. In some embodiments, this information is used as feedback, to refine and dynamically update parameters of machine learning modules. In some embodiments, dosage recommendations provided via the approaches described herein are restricted to fall within a pre-defined range, for example as specified by a physician.
  • dosage recommendations provided by technologies (e.g., systems and methods) described herein comprise an identification of one or more specific symptoms, so as to provide recommendation to discuss particular symptoms with a medical professional, such as a physician and/or therapist (e.g., to discuss particular changes to medication regimens and/or types of medication, so as to best manage particular symptoms).
  • a medical professional such as a physician and/or therapist (e.g., to discuss particular changes to medication regimens and/or types of medication, so as to best manage particular symptoms).
  • the non-behavioral therapy components are related to therapies that have previously been administered to the patient. In one embodiment, the non-behavioral therapy components are related to therapies that are currently being administered to the patient. In one embodiment, the non-behavioral therapy components are related to therapies that will be and/or are recommended to be administered to the patient.
  • method flow proceeds to operation 212.
  • the patient profile and pre-assessment data and the patient condition data are processed to generate a personalized intervention regimen for the patient, wherein the personalized intervention regimen defines both behavioral therapy components and non-behavioral therapy components to be administered to the patient.
  • the personalized intervention regimen provides, through client devices, an array of empirically-supported intervention options or actions delivered via a modular and flexible approach, whereby modules of the regimen (a set of overarching principles and evidence-based interventions) can be adaptively provided based on patient states assessed in real-time or near real-time. This allows for individualized treatment planning.
  • guided behavioral therapy technologies as provided herein provide a user with a sequence of interactive lesson modules that the user accesses and interacts with via a graphical user interface (GUI) of a DTX system, which may include a web-based application accessible via a web-browser of a user personal computer (e.g., desktop, laptop, etc.), and/or a mobile application, running, at least in part, on and/or accessible via a user mobile computing device.
  • GUI graphical user interface
  • Each interactive lesson module may represent a guided lesson in a particular behavioral therapy skill and includes specific graphical content and/or graphical widgets designed to introduce a user to a particular behavioral therapy skill, such as keeping a symptom diary, managing symptoms, setting goals, identifying and understanding thoughts (e.g. , unhelpful and/or irrational thoughts), and the like.
  • a user completes various interactive lesson modules, they are introduced to, and learn to practice, a specific behavioral therapy skill.
  • interactive lesson modules are arranged in a particular sequence.
  • a DTX system in accordance with approaches described herein may include controls that encourage and/or require a user to progress through a particular sequence of lesson modules in a prescribed order.
  • the DTX system may restrict access by the user to certain lesson modules, occurring later in the sequence, until others have been completed first.
  • the order of modules of the intervention regimen provided can vary from patient to patient and/or vary based on other factors (e.g., due to refinement and training of models, as described in further detail below); however, in some embodiments, all patients will have access to and be offered all of the skill modules through DTX systems executing on their respective client devices.
  • the skills- based interventions rely on skill acquisition (initial phase of learning the new skill), then skill practice before proceeding to learn the subsequent new skill (e g., in one’s natural home/social environment). Monitoring of task performance and practicing skills is described in further detail below.
  • the modules can allow users to develop and train core skills (e.g., 8 core skills, another suitable number of core skills, etc.) associated with understanding their disease, disorder, and/or condition, therapies available, brain-gut connections; relaxation skills; behavioral change, avoidance, and activation; problem solving and coping; pain management; cognitive flexibility; social problem solving and communication; and relapse prevention and skills maintenance.
  • core skills e.g. 8 core skills, another suitable number of core skills, etc.
  • sizes of lesson modules - for example, a number of screens a user cycles through, a number of graphical widgets they interact with, an estimated approximate time they are expected to spend with various lesson module(s), etc. - may be tailored to remain relatively small, so as to provide a user ‘bite-sized’ lessons that can and/or are designed to facilitate retention.
  • lesson modules may be designed such that they may be completed with no more than about twenty minutes of continuous user interaction.
  • lesson modules may be designed such that they may be completed with no more than about fifteen minutes of continuous user interaction.
  • lesson modules may be designed such that they may be completed with no more than about ten minutes of continuous user interaction.
  • Disease, condition, and/or syndrome-specific components include content addressing one or more of: an illness narrative, symptom management for pain and other symptoms, disease-specific psychoeducation, social skills training, and emphasis on chronic pain health condition (e.g., migraine- related, fibromyalgia-related, endometriosis-related, TMD/TMJ-related, etc.) cognitions, beliefs, and behaviors.
  • Intervention modules can further include general cognitive behavioral components shared across psychological conditions/disorders such as behavioral activation, attentional processes, relaxation, problem solving, cognitive reframing, and other areas.
  • generating a personalized intervention regimen can include defining a type, amount, and/or dosing schedule of a non-behavioral therapy to be administered to the patient in combination with the behavioral therapy components.
  • a dosing schedule for administration of a non-behavioral therapy may be defined relative to a schedule for administration of the behavioral therapy.
  • generating a personalized intervention regimen can include adjusting (e.g., decreasing, increasing, maintaining) an amount of the non-behavioral therapy treatment administered to the patient, for example, based upon the state of the patient’s health condition symptom severity, and/or correspondingly adjusting (e.g., decreasing, increasing, maintaining) an amount of a behavioral therapy treatment provided to the patient, thereby titrating relative treatment types provided to the patient based upon returned outputs of models associated with the methods described.
  • a treatment cocktail can include prescription digital therapeutic aspects (e.g. behavioral therapy components) as well as non-prescription digital therapeutic aspects (e.g. non-behavioral therapy components).
  • FIG. 3A depicts a schematic of architecture 300 implemented for delivery of behavioral therapy intervention regimen components and/or modules, according to one or more embodiments.
  • architecture 300 includes introduction and education module 301, which in some embodiments, also includes symptom assessment module 302.
  • introduction and education module 301 is utilized to generate patient profile and pre-assessment data.
  • the patient profile and pre-assessment data is generated and/or obtained outside of the functioning of the introduction and education module 301.
  • architecture 300 further includes physical illness narrative module 304, which is utilized to generate patient illness narrative data, which in turn, may be utilized for personalization of an intervention regimen, as well as for constructing personal model 303.
  • the patient profile and pre-assessment data generated by introduction and education module 301, and the patient illness narrative data generated by physical illness narrative module 304 are processed through the DTX system to generate a personalized and adaptive intervention regimen for the patient, as will be discussed in additional detail below.
  • the personalized intervention regimen includes one or more additional interactive therapy modules, such as, but not limited to, relaxation module 306, behavioral change and avoidance module 308, problem solving and coping module 310, pain management module 312, cognitive restructuring and flexibility module 314, social problem-solving and communication module 316, relapse prevention and skills maintenance module 318, and adherence module 320.
  • additional interactive therapy modules such as, but not limited to, relaxation module 306, behavioral change and avoidance module 308, problem solving and coping module 310, pain management module 312, cognitive restructuring and flexibility module 314, social problem-solving and communication module 316, relapse prevention and skills maintenance module 318, and adherence module 320.
  • a symptom diary and trigger tracking module 321, and a medication adherence module 323 are also provided.
  • method flow proceeds to operation 214.
  • the one or more behavioral therapy components are administered to the patient through the user interface of the digital therapeutics (DTX) system according to the personalized intervention regimen generated for the patient.
  • DTX digital therapeutics
  • the behavioral and cognitive change interventions described below interrupt the problematic behaviors that are maintaining/perpetuating the targeted symptoms, provide new adaptive coping strategies, and improve perceived control of symptom management in a positive manner.
  • the ability to tailor ‘at the right time’ requires relevant information about the user that is used to decide under what conditions to provide an intervention and the appropriateness of the intervention.
  • the following interactive therapy modules will be discussed with reference to FIG. 3A. As noted above, inclusion of these therapy modules and/or the order of inclusion of these additional therapy modules, in various embodiments, is dependent on the personalized intervention regimen generated for a particular patient.
  • modules are described in a particular order, it should be noted that the modules can be performed in any other suitable sequence, omit operations, and/or include additional operations (e.g., based on refinement and training of models described below, and/or based on other factors). Furthermore, aspects of the modules can overlap with each other in any suitable manner.
  • introduction and education module 301 focuses on education about the patient’s disease and symptoms (e.g., more common symptoms, less common symptoms, etc.).
  • the introduction and education module is designed to create awareness about what matters to the patient (their reason for trying the program), introduce therapy concepts (e.g., related to CBT, related to other therapies), introduces skills that the user will build by interacting with the system, and assesses user’s level of commitment for change.
  • an overview of this program links to the patient’s specific psychological/disease management challenges.
  • the following points are emphasized: (1) the treatment is modular/flexible in nature and tailored for patient’s needs (2) the patient will learn skills, that if practiced, will help them manage their symptoms (e.g., with highlighting of red flag symptoms), improve their quality of life, and lessen the toll that the patient’s health conditions take on the patient.
  • Introduction and education module 301 thus can guide the patient to explore the influence that moods, attitudes, beliefs and behavior exert on health and the impact of illness.
  • Introduction and education module 301 can further function to provide tools for education, persuasion (e.g., regarding effectiveness of program completion), personalization, motivation enhancement, setting expectations, eliciting commitment by users, and establishing a relationship between users and the system (e.g., in lieu of a human coach, with supplementation of therapy by a human coach, etc.).
  • Delivery methods for introduction and education module 301 can include one or more of: graphics/animations, metaphorical digital content, interactive exercises provided in a DTX system environment, and a clinical vignette simulating patient-provider interactions.
  • introduction and education module 301 may include a variety of individual sections designed to lay a foundation for progression through later modules. While the sections described below are described in a particular order for illustrative purposes, variations of introduction and education module 301 can additionally or alternatively be arranged in another suitable order, omit sections as desired, and/or include additional sections as desired.
  • FIG. 3B depicts examples of individual sections that may make up an introduction and education module 301 of an intervention regimen, according to one or more embodiments.
  • introduction and education module 301 includes a First Section 322 configured to welcome the patient and introduce the patient to goals of the intervention regimen delivered through the online system and client device.
  • the First Section 322 is delivered by the system in an interactive format (e.g., with video and text content) that creates a feedback loop with users and processes user responses to tailor subsequent module delivery and content, in order to increase engagement.
  • goals can be set in coordination with user desires, with establishment of collaborative empirence. Goals can be specific, in terms of detailed planning of what users will do, including frequency, intensity, duration, and context (e.g., where, when, how, with whom, etc.) of the goal(s).
  • introduction and education module 301 can determine topics having greater relevance to the user’s current issues (e.g., in relation to comorbid conditions, such as anxiety and depression, in relation to health condition subtypes, such as subtypes of migraine, endometriosis, etc.).
  • the First Section 322 can include a description of how the program will involve regular practice (e.g., daily, every two days, every 3 days, etc.) of skills (e.g., core skills described above and below), with a guideline for program length (e.g., 8 weeks, less than 8 weeks, more than 8 weeks), and methods of identifying personal progress (e.g., feeling better with mastery of a subset of skills).
  • introduction and education module 301 includes a Second Section 324 configured to allow the patient to submit information, through a user interface of the DTX system, regarding personal aspects of his/her health condition as an initial physical illness narrative, along with video content to which the patient can compare his/her experiences.
  • Second Section 324 has goals of facilitating emotional awareness, establishing a physical illness narrative that can be revisited as the user gains mastery of skills, and helping the user to articulate and track his/her experiences.
  • introduction and education module 301 includes a Third Section 326 configured for personalization of subsequent portions of the intervention regimen to the patient, by allowing the patient to indicate, through a user interface of the DTX system, which symptoms (e.g., moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light, sensitivity to sounds, pelvic pain, abdominal pain, bladder pain, fatigue, nausea, gastrointestinal symptoms, jaw pain, tenderness of jaw, tenderness of temporomandibular joint, pain at temporomandibular joint, tenderness in ears, tenderness around ears, pain in ears, facial tenderness, difficulty chewing, pain while chewing, pain and stiffness all over the body, headaches, facial pain, insomnia, medication side effects, other symptoms, etc.) are most bothersome.
  • symptoms e.g., moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light, sensitivity to sounds, pelvic pain, abdominal pain, bladder pain, fatigue, nausea, gastrointestinal symptoms, jaw pain, tenderness of jaw, tenderness of temporomand
  • Third Section 326 can also include architecture for mapping the user’s symptoms and health condition-induced factors to various impacts associated with the user’s values.
  • one or more of the mappings can be created, such as, but not limited to: symptoms associated with diarrhea, abdominal pain, urgency, tenesmus, nocturnal bowel movements, rectal bleeding, physical fatigue, and other physical symptoms with mappings to aspects of life (e.g., relationships, work, school, hobbies, daily activities, etc.) that have been affected by such symptoms and the reason such aspects have been affected; medication side effects with mappings to aspects of life (e.g., relationships, work, school, hobbies, daily activities, etc.) that have been affected by such symptoms and the reason such aspects have been affected; social/relationship issues (e.g., stress on loved ones, impacts on friendships, etc.) with mappings to behaviors (e.g., relationships, work, school, hobbies, daily activities, etc.) that have been affected by such symptoms and the reason such aspects have been affected; and behavioral, mental, and emotional factors (
  • Third Section 326 has goals for providing education about health condition symptoms and psychological consequences (e.g., behavioral psychological consequences), as well as generating data for future personalization of the intervention regimen.
  • introduction and education module 301 includes a Fourth Section 328 configured for personalization and values identification, with tools for allowing the user to provide data related to positive and negative changes in his/her life that are attributed to having the health condition, in relation to changes in relationships, levels of embarrassment, curiosity, being understood, stress to self and loved ones, confidence, energy levels, senses of lack of control, worry (e.g., about health issues experienced outside of a comfortable environment, about disease progression, and symptoms, about medication effects, about ability to conduct daily activities, about dietary constraints, about travel, etc.), and other aspects.
  • worry e.g., about health issues experienced outside of a comfortable environment, about disease progression, and symptoms, about medication effects, about ability to conduct daily activities, about dietary constraints, about travel, etc.
  • Fourth Section 328 can also revisit aspects of the user’s initial physical illness narrative, with ranking of: symptoms (e.g., moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light, sensitivity to sounds, pelvic pain, abdominal pain, bladder pain, fatigue, nausea, gastrointestinal symptoms, jaw pain, tenderness of jaw, tenderness of temporomandibular joint, pain at temporomandibular joint, tenderness in ears, tenderness around ears, pain in ears, facial tenderness, difficulty chewing, pain while chewing, pain and stiffness all over the body, headaches, facial pain, etc.); social/interpersonal factors (e.g., changes to relationships, embarrassment, stress to loved ones, dealing with constant questions about illness, not being understood, etc ); emotional factors (e.g., lack of confidence, mental exhaustion, lack of control, etc.); cognitive factors (e.g., worry about health issues outside of places of comfort, worry about disease progression, catastrophizing, depression, anxiety, other comorbid conditions, etc.);
  • introduction and education module 301 includes a Fifth Section 330 configured for allowing further customization, by providing the patient with interactive elements that allow the patient to prioritize the order in which content associated with interventions is received.
  • introduction and education module 301 also includes a Sixth Section 332 configured for introducing subsequent portions/modules of the intervention according to user preferences indicated from outputs of the Fifth Section 330, where the goals of Sixth Section 332 include promotion of treatment credibility (e.g., through presentation of video content by patients having experiences similar to those of the user(s)).
  • introduction and education module 301 includes a Seventh Section 334 configured for delivery of content for educating the patient about their condition, where the content includes an animated element and audio format content configured to actively interact with the user.
  • the interactive elements function to gauge how well the patient understands the content provided, and to provide additional content to engage and inform the patient depending upon responses of the patient.
  • the Seventh Section 334 has goals of shaping knowledge of symptoms and treatment components of the intervention regimen and enhancing motivation.
  • Seventh Section 334 can teach users of the system regarding the brain’s role in proper gut functioning, and the connection between the mind and the gut. As such, the user can be primed to gain skills related to affecting gut functioning and regulation by changing behaviors, attentional biases, and automatic thought patterns. Seventh Section 334 can further gage internalization and understanding of the user, with provision of further content in this section and/or the eighth section to promote further understanding.
  • introduction and education module 301 includes an Eighth Section 336 configured for delivery of content for educating the patient in a manner personalized to the patient, where the content includes video and audio format content configured to actively interact with the user, in order to aid the user in understanding influences on the perception of symptoms, based on symptom severity (e.g., related to a threshold level of severity of symptoms, related to fight- or-flight responses, etc.).
  • Eighth Section 336 also provides interactive exercises for learning about physiological-cognitive pathways for perceiving and responding to experienced symptoms and implements architecture for assessing stress and other disease aspects, with implementation of therapeutic techniques for changing reactivity of the brain, thereby decreasing symptom severity.
  • introduction and education module 301 includes a Ninth Section 338 configured for eliciting commitment from the patient, in relation to different set goals of the patient.
  • the digital content of Ninth Section 338 includes interactive elements for creating a reminder system (according to personalized user preferences and formats for receiving reminders), and interactive elements for setting goals to improve one or more aspects of dealing with the patient’s health condition (e.g., with a menu of choices as well as a field for custom user inputs and a field for prompting the user to confirm chosen goals, where example choices can include repeating of tasks, reviewing content, reflecting, identifying entities for social accountability, relocation of application icons on a home screen of a device in a manner that promotes regular use, identifying factors that may obstruct progress, etc.), where the interactive elements allow the patient to confirm when (e.g., specific times), how often, and where the patient will perform activities to meet such goals.
  • Ninth Section 338 includes a brief introduction to subsequent modules of the intervention regimen that are customized to the patient.
  • Ninth Section 338 has goals including setting of expectations, promoting therapeutic persuasiveness, eliciting commitment, increasing user engagement, providing reminders, providing instruction for performing behaviors (e.g., SMART goals).
  • goals including setting of expectations, promoting therapeutic persuasiveness, eliciting commitment, increasing user engagement, providing reminders, providing instruction for performing behaviors (e.g., SMART goals).
  • the term “physical illness narrative,” “personal illness narrative,” and/or “patient illness narrative” may include a narrative expressed by a patient regarding the patient’s personal experiences with a disease, disorder, and/or condition.
  • An illness narrative is typically a narrative solicited from a patient, which enables a healthcare practitioner to build a more complete picture of the patient’s past and present health state in the context of the patient’s life, while providing the patient with an opportunity for self-reflection and validation.
  • physical illness narrative module 304 provides a form of validation (being heard), highlights cognitive distortions/attentional biases and other clinically relevant processes to address, as well as begins the work of emotional exposure. It also provides a point of reference for reflection throughout and at the end of the program. Physical illness narrative module 304 promotes formation of a “personal disease model,” or “personal model” for users, such that they can identify patterns and/or cycles in their disease expression and/or progression, in relation to biology, behaviors, environment, stressors, emotions, and thoughts.
  • the term “personal model,” and/or “personal disease model” may include a construction built based on patient input, which enables the patient to identify stressors, counter-productive behaviors, unhelpful thoughts, and negative emotions as associated with the patient’s disease, disorder, and/or condition.
  • a personal model may be utilized to help a patient identify such links, and to consider possible changes in their behavior that could be implemented to address their symptoms.
  • second patient response data representing the patient’s responses to content provided to the patient through the second interactive therapy module is obtained, for example, through the user interface of the DTX system, or from a variety of patient devices, such as, but not limited to, sensors and/or biometric devices.
  • the DTX system then processes the second patient response data to generate physical illness narrative data, which can then be used for a variety of purposes.
  • the patient illness narrative data can be utilized to personalize an intervention regimen for the patient, as will be discussed in additional detail below.
  • the patient illness narrative data generated by physical illness narrative module 304 can also be utilized as the basis for formation of a personal model, such as personal model 303 of FIG. 3 A, which can then be graphically represented to the user to aid in progression through the intervention regimen.
  • a personal model such as personal model 303 of FIG. 3 A
  • key functions of physical illness narrative module 304 can include creation of a patient’s personal model 303, validation of a patient’s experience, enhancement of self-understanding and illness comprehension, setting the stage for application of behavioral therapy skills to accept uncontrollable elements of physical illness and/or or increase proactivity to address controllable elements of physical illness, and generation of interest for patient engagement.
  • physical illness narrative module 304 introduces a patient to a process for creating a personal model 303, for example so as to orient them and provide content designed to offer helpful motivation.
  • graphical content representing educational material is displayed to a patient, for example to introduce them to concept of vicious cycles, and explain how symptoms, stress, and pain can create a feedback loop.
  • graphical content corresponding to shared patient experiences and/or testimonials is displayed.
  • viewing shared experiences from other patients may help prime a patient to be receptive to therapy, provide motivation, and foster a particular sense of therapy.
  • such content can serve to reinforce skills that lesson modules present to a patient, by allowing the patient to hear benefits of various lessons and/or skill practice from real patients.
  • testimonial content can comprise stories from patients describing their experiences living with a particular health condition and which behavioral therapy skills and/or lesson they found particularly helpful.
  • patients providing videos may be loosely coached, e.g., to structure, direct, etc. their stories in a particular way, while still allowing them to provide authentic, ‘from the heart’ descriptions of their experiences. Additionally or alternatively, among other things, viewing relatable experiences from real patients (e.g., and not actors) can provide a patient with a helpful sense of not being alone in their experiences.
  • a patient may be prompted to read about another patient’ s experiences with their condition and guided behavioral therapy approaches such as those described herein.
  • a patient may view exemplary personal models created by and shared by others.
  • screens comprising graphical content providing helpful encouragement are displayed within a GUI of the DTX system.
  • Other lesson modules for example any lesson modules described herein and/or additional lesson modules, providing for development of other behavioral therapy skills provided via the technologies described herein may also include content comprising patient experiences and/or testimonials.
  • FIG. 4 depicts an example of formation of a personal disease model, according to one or more embodiments.
  • physical illness narrative module 304 can receive patient report data (or other data) regarding the patient’s illness history (e.g., painful experiences in a clinical setting, such as with a clinician or hospital environment), thoughts (e.g., thoughts of guilt or responsibility for condition and behaviors, etc.), emotions (e.g., in relation to helplessness, feeling worthless, in relation to embarrassment, etc.), and behaviors (e.g., avoidance, communications) in order to address cognitive distortions for emotional exposure throughout subsequent interactions with the system.
  • patient report data or other data regarding the patient’s illness history
  • thoughts e.g., thoughts of guilt or responsibility for condition and behaviors, etc.
  • emotions e.g., in relation to helplessness, feeling worthless, in relation to embarrassment, etc.
  • behaviors e.g., avoidance, communications
  • physical illness narrative module 304 is used to implement, via a GUI of the DTX system, a structured process for conveniently soliciting patient input of specific counter-productive behaviors, unhelpful thoughts, and negative emotions that they identify, e.g., in their life and/or as associated with their particular condition for use in creating a patient’s own personal model 303.
  • physical illness narrative module 304 and/or other related modules can include architecture for prompting the patient to provide data and/or automatically receiving data (e.g., through API access of health monitoring systems, through receiving of sensor signals of devices of the patient, etc.) pertaining to one or more of: biological aspects (e.g., physiological symptoms); behavioral aspects (e.g., in relation to skipping meals, in relation to exercise avoidance, in relation to social event behavior, in relation to locating restrooms, in relation to straining, in relation to checking stools, in relation to other aspects); environmental aspects (e.g., in relation to stress, in relation to temperatures, in relation to diet, etc.); emotional aspects; and thoughts linked to behaviors (e.g., regarding anxiety around diet, regarding to anxiety around performing various activities, etc.), [0249]
  • physical illness narrative module 304 can include architecture for prompting the patient to provide data and/or automatically receiving data (e.g., through API access of health monitoring systems, through receiving of sensor signals of devices of the patient, etc.
  • physical illness narrative module 304 may automatically return an analysis summarizing the personal model 303 of the patient (e.g., in a visual format, etc.). Such personalization thus promotes interruption of vicious cycles for patients.
  • the method 200A can include returning a mapping with a network of flows between a set of behaviors specific to the patient, a set of thought patterns specific to the patient, a set of physiological symptoms specific to the patient, a set of emotions specific to the patient, and environmental triggers specific to the patient, where returned outputs of models described can be configured to disrupt flows of the network contributing to deterioration of symptoms of the patient.
  • a personal model is constructed as a graphical representation, which comprises text corresponding to patient-selected counter-productive behavior(s), unhelpful thought(s), and negative emotion(s), superimposed on a flow diagram illustrating links between each other.
  • a personal model graphical representation comprises text corresponding to causes and/or stressors of symptoms. Examples of personal model graphical representations will be provided below in the discussion of the DTX user interface.
  • generation of a visual or graphical representation of a personal model 303 may include, retrieving, by the illness narrative module 304, stored information previously input by a patient.
  • a patient may have previously provided input identifying causes and/or stressors that impact their particular condition.
  • a patient provides input corresponding to causes and/or stressors associated with their particular condition via the physical illness narrative module 304.
  • a graphical representation of a partially completed personal model 303 is rendered, showing the patient identified causes and stressors superimposed on a flow diagram, with portions allocated for graphical representations of additional information such as counter-productive behaviors, unhelpful thoughts, and negative emotions, to be displayed.
  • the physical illness narrative module 304 includes graphical content prompting a patient to review their personal model 303.
  • a series of questions e.g., from a predefined list of questions, e.g., based on a therapeutic protocol
  • graphical content including passages of rendered text, mimicking conversation with a therapist can be displayed.
  • encouraging graphical content is displayed, and the patient is returned to a home screen.
  • delivery methods for the physical illness narrative module 304 can include audio format content and/or textual content for guiding exercises.
  • physical illness narrative module 304 may be a subcomponent of multiple modules, such that its content can be revisited. For instance, upon development of core skills associated with the modules, the system can trigger revisitation of aspects of physical illness narrative module 304 within the DTX system, such that patients can solidify new skills, reflect on their initial versions of their physical illness narrative and what has changed, generalize skills, maintain skills, and implement cognitive flexibility.
  • a relaxation module 306 provides a patient with understanding of what physiological stress feels like (e.g., with education on fight or flight responses) and recognition of the importance of actively optimizing their stress response, particularly because of the connection between stress reactivity, stress hormones and autonomic arousal, and flares in symptoms.
  • Relaxation module 306 informs the patient that (1) stress is a natural reaction and it causes its own physical symptoms (2) the brain does not differentiate between an event that is actually happening to us and an event that we only think is happening, and (3) the connection between stress and flares and symptoms.
  • relaxation module 306 provides the patient with a rationale for each type of relaxation and how it is tailored for their specific stress symptoms, and provides guided relaxation exercises (e.g., through an application associated with the DTX system executing at the client device).
  • Relaxation module 306 promotes mastery of at least one relaxation technique.
  • Key functions of relaxation module 306 can include decreasing physiological reactivity associated with stress, worry, anxiety, and pain, activation (for depression symptoms), and pain management.
  • Delivery methods for relaxation module 306 can include audio format and/or visual content for guiding exercises associated with targeted muscle groups for progressive muscle relaxation, video-guided demonstration of diaphragmatic breathing, and haptic feedback for exercise guidance.
  • relaxation module 306 can include video format content that introduces the general concept of relaxation; educates the patient on the applicability of stressreduction exercises to specific health conditions, with active text boxes that promote user engagement and personalization of the module to the patient’s specific symptoms and contexts; addresses common doubts or concerns about relaxation; promotes a guided breathing exercise with a diaphragmatic breathing demonstration and corresponding animated graphic; promotes guided exercises for muscle relaxation using progressive muscle relaxation (PMR) techniques using graphical animations (e.g., of targeted muscle groups); provides information on how relaxation practices can be used (e.g., for abdominal pain, for anxiety, for other stressors, etc.), and encourages practice of exercises by including active interactive elements that the patient can use for scheduling and/or accountability in practicing exercises.
  • PMR progressive muscle relaxation
  • behavior change and avoidance module 308 provides content covering the importance of activation and approaching avoided situations/experiences in breaking the cycle of persistent pain symptoms and depressive and/or anxious mood.
  • Specific action plans are developed for decreasing avoidance behavior.
  • Key functions of this module can include linking behaviors and mood, mood monitoring (e.g. self-monitoring), activity scheduling, identifying and counteracting avoidance behavior, action planning, activity scheduling, creating anxiety hierarchies, self-monitoring, behavioral experiments, exposure (e.g., imaginal exposure, actual exposure to counteract anxiety) and systematic desensitization for anxiety, coping performance, confidence building, and routine building.
  • Delivery methods for behavior change and avoidance module 308 can include use of automated tailoring for choosing topics that have greater relevance to a patient's current problems (e.g., if a patient reports anxiety, information about physiological responses of anxiety and their relationship with thoughts and behaviors would be more appropriate than information about the physiological symptoms of depression or generic stress).
  • Problem Solving and Coping Module 310 e.g., if a patient reports anxiety, information about physiological responses of anxiety and their relationship with thoughts and behaviors would be more appropriate than information about the physiological symptoms of depression or generic stress.
  • problem solving and coping module 310 provides content covering how to differentiate controllable vs. uncontrollable stressors, problem- focused coping (e.g., with problem identification, solution brainstorming, evaluation of solution options, etc.) vs. emotion-focused coping (e.g., with grounding exercises), as well as types of adaptive and maladaptive coping. Mood/anxiety/stress may be managed/ameliorated by using externally- focused coping to distressing and modifiable conditions and internally-focused coping to adjust one’s expectations and interpretations for unmodifiable conditions.
  • problem solving and coping module 310 can include architecture and instructions for promoting practicing of problem solving and coping methods by the patient, such that the patient is better able to handle stronger symptoms (and milder symptoms).
  • Delivery methods for problem solving and coping module 310 can include digital content with explanations and testimonials of other patients and their uses of problem solving skills, peer support groups facilitated by the DTX system, and other delivery methods.
  • pain management module 312 focuses on awareness of the pain experience, discusses how pain influences mood and vice versa, promotes recognition of certain behaviors (e.g., penetration, avoidance) and automatic thoughts that may influence pain as well as how to feel more in control of pain by also improving physical and role functioning though increasing adaptive behaviors/coping (e.g. mindfulness) and decreasing avoidance/maladaptive behaviors.
  • Key functions of pain management module 312 can include behavioral experimentation, behavior substitution, acceptance of pain, and self-monitoring, with one or more disease-or-syndrome-specific targets.
  • pain management module 312 can include architecture and content for educating patients regarding re-directing attention away from pain symptoms by focusing on parts of the body that are not in pain, and other methods (e.g. pacing).
  • the system can include a processor with instructions stored in non-transitory media that when executed, perform operations for identifying when a patient is in a state of pain, and triggering a response (e.g., verbal cues and instructions to modify attention and/or engage in various pain observation exercises, a change in the environment of the patient, by playing music, by activating a display and providing video or image content, by providing haptic stimulation to the patient, etc.).
  • delivery methods for pain management module 312 can include audio format content and/or textual content for managing pain (e.g., with music, exercise, etc.) and/or for promoting attention restructuring.
  • FIG. 3C depicts examples of individual sections that may make up a pain management module of an intervention regimen, according to one or more embodiments.
  • pain management module 312 can include a First Section 340 that includes content focused on common types of pain (e.g., vulvar pain) associated with the patient’s health condition.
  • pain management module 312 can include a First Section 340 that includes content focused on common types of pain (e.g., vulvar pain) associated with the patient’s health condition.
  • pain management module 312 can include a Second Section 342 focusing on facts about chronic pain associated with the patient’s health condition, in relation to constant pain, flare ups of pain, pain signals for people with health conditions vs. without health conditions, factors affecting pain strength, and other factors.
  • Second Section 342 can also include image and video content (e.g., including testimonials of patients similar to the user) and other interactive exercises.
  • pain management module 312 can include a Third Section 344 describing differences between acute pain and chronic pain associated with health conditions, and therapies associated with each type of pain.
  • pain management module 312 can include a Fourth Section 346 focused on pain volume attributed to specific nerves of the brain, with interactive exercises and content for re-training the brain to adjust pain volume (i.e., pain modulation).
  • pain management module 312 can include a Fifth Section 348 focusing on factors that affect pain intensity/perceived pain intensity (e.g., loss of sleep, tense muscles, anxiety, worry, etc.) and methods for modulating pain intensity and duration (e.g., relaxation, distraction, positivity, exercise, medicine, etc.).
  • factors that affect pain intensity/perceived pain intensity e.g., loss of sleep, tense muscles, anxiety, worry, etc.
  • methods for modulating pain intensity and duration e.g., relaxation, distraction, positivity, exercise, medicine, etc.
  • pain management module 312 can include a Sixth Section 350 describing the importance of relaxation in modulating pain volume and creation of a pain management plan.
  • pain management module 312 can include a Seventh Section 352 focused on the effects of pain on negative emotions, with architecture for including customized content from the patient’ s illness narrative (associated with other modules), in a textual, audio, and/or visual format, and allowing the patient to update his/her illness narrative.
  • pain management module 312 can include an Eighth Section 354 focused on development of automatic habitual thinking patterns to interrupt and break these negative cycles.
  • pain management module 312 can include a Ninth Section 356 with architecture for presenting a patient testimonial regarding a personal experience of catastrophizing thoughts and the effects on worsening mood, pain, and perpetuation of biased attend onal processing.
  • pain management module 312 can include a Tenth Section 358 focused on promoting a healthy lifestyle to protect the body against stress, pain flares, and other health condition symptoms.
  • pain management module 312 can include an Eleventh Section 360, which provides architecture for helping the patient establish goals in various activities in his/her daily life (e.g., school, friendship, sports, etc.), as they relate to pain management.
  • Eleventh Section 360 provides architecture for helping the patient establish goals in various activities in his/her daily life (e.g., school, friendship, sports, etc.), as they relate to pain management.
  • pain management module 312 can include a Twelfth Section 362 focused on activity pacing to prevent increases in pain, with interactive content (e g., derived from patient testimonials, etc.).
  • pain management module 312 can include a Thirteenth Section 364 focused on providing examples of activity pacing (e.g., taking breaks during physical exercise, setting limits in relation to pain thresholds, etc.), with interactive modules for setting goals specific to activities that the patient values and/or enjoys.
  • activity pacing e.g., taking breaks during physical exercise, setting limits in relation to pain thresholds, etc.
  • pain management module 312 can also include a Fourteenth Section 366 focused on helping the patient to generate a pain management plan with respect to relaxation skills gained (e.g., diaphragmatic breathing, progressive muscle relaxation, etc.), cognitive flexibility skills (e.g., catastrophizing avoidance, etc.), eating and drinking habits (e.g., with respect to regular meals with respect to caffeine limitation, etc.), with respect to activity performing, and with respect to activity pacing.
  • relaxation skills gained e.g., diaphragmatic breathing, progressive muscle relaxation, etc.
  • cognitive flexibility skills e.g., catastrophizing avoidance, etc.
  • eating and drinking habits e.g., with respect to regular meals with respect to caffeine limitation, etc.
  • cognitive restructuring and flexibility module 314 targets one’s interpretations of events/ experiences (e.g., how core thoughts influence our feelings and behavior). Cognitive restructuring and flexibility module 314 emphasizes connections between thoughts and physical sensations due to a variety of symptoms.
  • the aim of cognitive restructuring and flexibility module 314 is to teach patients how to identify unhelpful automatic thinking patterns and develop a new pattern of realistic, balanced, and flexible thinking.
  • a health behavior change is targeted in the area of sleep and worry by providing education about worry and how it might interfere with sleep.
  • Strategies to manage worry before bedtime e.g., use a relaxation practice) are provided as well as basic sleep hygiene.
  • Cognitive restructuring and flexibility module 314 can include resetting of cognitive distortions (e.g., about self, others, and the world), identification of unhelpful thoughts, challenging of automatic thoughts, creating more balanced thoughts, reattribution, appraisals of moods, and improving cognitive flexibility.
  • Delivery methods for cognitive restructuring and flexibility module 314 can include a tool providing digital content for reassembling a traditional thought record in which patients enter an unhelpful automatic thought and select from a list of negative thoughts that best matched. After selecting from a list of most common automatic thoughts, the tool can generate a list of possible challenge/alternative thoughts. The patient can then input their own personalized challenge/alternative thought.
  • social problem solving and communication module 316 provides content promoting effective social behaviors in the context of a variety of health conditions.
  • Social problem solving and communication module 316 can provide tools for one or more of: action planning, social skills training, social support, exposure, and activation, with identification of oneself as a role model, and presentation of information regarding vicarious consequences.
  • social problem solving and communication module 316 is intended to assist interactions between patients and their social environment in the context of their health condition(s), and how to communicate effectively about the medical condition/disease. Some examples include how pain impacts sexual functioning, ways to navigate dating and relationships, redefining sexual intimacy, and communicating to others about your pain.
  • Key functions of social problem solving and communication module 316 can include activation and action planning, problem solving by analysis of factors influencing the behavior and generating strategies to overcome barriers, demonstrating one’s ability to cope and communicate about pain and sexual functioning, decreasing avoidance behaviors, ensuring practice of new coping skills, when symptoms are more severe (e.g., with behavioral rehearsal, etc.).
  • Delivery methods for social problem solving and communication module 316 can include digital content with testimonials of other patients and their uses of problem solving, peer support groups facilitated by the DTX system, and other delivery methods.
  • social problem solving and communication module 316 can include architecture for triggering actions based on detected changes in symptoms. For instance, in one example, social problem solving and communication module 316 can process data generated by interactions between the user and the system (e.g., with sensor-based monitoring of symptom progression, with user input-based monitoring of symptom progression, etc.), and based upon the data, generate control instructions for recommended actions that would improve social problem solving ability.
  • Examples of recommended actions can include one or more of: guidance for conducting a conversation regarding symptoms (e.g., example language for communicating pain, intimacy, or other-related symptoms, so that the user can experience relief, etc.); triggering automatic communications between the patient and another person (e.g., communications with one’s partner regarding how sexual intimacy impacts pain); and performing other suitable actions.
  • symptoms e.g., example language for communicating pain, intimacy, or other-related symptoms, so that the user can experience relief, etc.
  • triggering automatic communications between the patient and another person e.g., communications with one’s partner regarding how sexual intimacy impacts pain
  • performing other suitable actions e.g., guidance for conducting a conversation regarding symptoms (e.g., example language for communicating pain, intimacy, or other-related symptoms, so that the user can experience relief, etc.); triggering automatic communications between the patient and another person (e.g., communications with one’s partner regarding how sexual intimacy impacts pain); and performing other suitable actions.
  • relapse prevention and skills maintenance module 318 encourages maintenance/continuation of treatment gains and reinforces positive changes in thoughts and behavior that were accomplished during the active treatment time.
  • Key functions of relapse prevention and skills maintenance module 318 can include skills generalization, skills maintenance, and adaptive monitoring to refresh skills learned. Additionally, relapse prevention and skills maintenance module 318 can perform one or more of: informing patients of signs of relapse into old patterns, development of specific proactive coping tools for future challenges, encouragement of proactive coping for mood regulation, explaining perseverance, education regarding sequential coping strategies, and identification of skills/techniques that were most effective for the user, based on analysis of user outcomes. Delivery methods for relapse prevention and skills maintenance module 318 can include digital content and/or notifications related to monitored states of the patient (e.g., related to relapse) as described in further detail below.
  • an intervention regimen may include a symptom diary module that introduces and familiarizes a patient with techniques for tracking their chronic pain condition symptoms and identifying pain triggers.
  • technologies described herein provide a convenient interface that facilitates patient tracking and/or monitoring of their chronic pain health condition symptoms on a regular basis.
  • a patient may use utilize the DTX system disclosed herein to rate pain and stress on a scale and provide information characterizing their daily routines.
  • symptom diary and trigger tracking module 321 may include features providing options for setting goals, for example, goals pertaining to a regular timing and/or type of non-triggering alternative (e.g., finding activities that you enjoy) and/or activity (e.g, physical exercise, meditation, breathing and/or relaxation exercises, reflection exercise, e.g., including skills introduced via lesson modules and/or practicable via interaction with one or more other practice modules, such as keeping a regular symptom diary, etc.).
  • goals pertaining to a regular timing and/or type of non-triggering alternative e.g., finding activities that you enjoy
  • activity e.g, physical exercise, meditation, breathing and/or relaxation exercises, reflection exercise, e.g., including skills introduced via lesson modules and/or practicable via interaction with one or more other practice modules, such as keeping a regular symptom diary, etc.
  • daily activities with associated pain may be characterized via use of a streamlined tracking interface.
  • conventional tracking tools typically allow users to input a wide array of information, including detailed information characterizing types of activities that may trigger pain episodes.
  • approaches described herein provide a streamlined tracking interface that expressly limits a range of user input and avoids allowing a user to input detailed information regarding daily activities and known/potential pain associations.
  • information may be relevant to, for example, identifying pain triggers or stressors, and ensuring adherence to specific programs, in some embodiments it may not necessarily be of utmost importance for chronic pain health condition symptom tracking.
  • less finely grained information such as a broad categorization of activity (e.g., intimacy, sleep, exercise, interactions, moods, stressors), and a particular time at which the activity occurred mapped against pain histories can provide sufficient information for tracking pain triggers and/or evaluating chronic pain health condition symptoms, in the context of daily activities and/or identifying patterns.
  • this approach may facilitate user input of activities information, and can improve adherence to treatment protocols.
  • this approach encompasses recognition that patients suffering from certain chronic pain health conditions and associated mental health conditions, such anxiety and/or depression, can suffer from unhelpful thoughts and compulsive behavior, which conventional, overly complex activity trackers may exacerbate. Accordingly, among other things, by providing, in some embodiments, a streamlined activity tracking approach, technologies described herein can address unique challenges associated with a particular patient population.
  • the present disclosure provides methods for facilitating activity and pain tracking by a subject suffering from a chronic health condition, for example including steps of: causing, by a processor of a computing device, display of a streamlined trigger-tracking user interface comprising one or more trigger tracking features, wherein, for each of one or more particular triggers, the trigger tracking features provide for user input of trigger data.
  • the trigger data input by the user via the trigger tracking features is received by the processor and stored for display and/or further processing, by the processor, of the trigger input data.
  • the digital therapeutics (DTX) system described herein can include mechanisms to facilitate a patient’s adherence to one or more particular non-behavioral therapies, such as dosing regimens of pharmaceutical compositions, nutraceutical compositions, and/or therapies involving use of medical devices.
  • various lesson modules and/or practice modules, as described herein may include features that allow a patient to track their adherence to medication.
  • medication adherence module 323 may include features that provide for patient input (e. , via one or more graphical widgets) of when and what medication the patient took. Tracking features such as these may serve as a helpful reminder to the patient to actually take their medication.
  • tracking features may allow identification of patterns related to a patient’s medication regimens, such as benefits with respect to symptom improvement conferred by adherence to a regimen and/or symptoms and/or activities that are associated with degree to which the patient adheres to a medication regimen.
  • medication adherence module 323 may provide features for setting goals pertaining to adherence to medication.
  • goals pertaining to medication adherence may include goals relating to a timing and/or particular type of medication, such as adherence to a regular schedule and/or timing of a particular medication.
  • medication adherence goals may include timing of a particular medication in relation to symptoms (e.g., of a user physiological condition) and/or other events, such as relative to meal consumption, physical exercises, seasons, social gatherings, travel, work, etc.
  • guided behavioral therapy technologies described herein may provide alerts, such as in-app pop up messages, push notifications, digital calendar integration, email/text message reminders, and the like, that facilitate medication adherence. Such notifications may include, for example, reminders to take particular medications.
  • the DTX systems and methods as described herein may provide for communication between a patient and one or more external medication tracking devices, as will be discussed in additional detail below.
  • guided behavioral therapy technologies described herein may also provide content (e.g., graphical content, e.g., presented within a GUI, such as those described herein) that explains and/or educates a user about one or more particular medications that they are taking.
  • medication adherence module 323 may be a standalone module, or may be included in the DTX system as part of another module, such a daily symptom and side effect diary and trigger tracking module 321 discussed above.
  • exercises associated with the intervention regimen can include one or more of: a card sorting task to identify a patient’s reinforcers/motivators (e.g., in relation to social reinforcers, reminders, accountability, gaming/competition, responsiveness to quantitative summary feedback, monetary incentives, altruism, learning, elimination of symptoms, etc.); computerized performance tasks (e.g., delayed discounting) to measure/identify salient reinforcers and/or learning style; and performance tasks (e.g., validated distress tolerance computer tasks, tasks associated with mimicked social interactions, etc.) to measure emotional awareness and ability to tolerate various types of distress (psychological, physical, etc.).
  • a card sorting task to identify a patient’s reinforcers/motivators (e.g., in relation to social reinforcers, reminders, accountability, gaming/competition, responsiveness to quantitative summary feedback, monetary incentives, altruism, learning, elimination of symptoms, etc.); computerized performance tasks (e.g., delayed discounting) to measure/identify salient reinforcer
  • modules are described in a particular order, it should be noted that the modules can be performed in any other suitable sequence, omit operations, and/or include additional operations (e.g., based on refinement and training of models described below, and/or based on other factors). Furthermore, aspects of the modules can overlap with each other in any suitable manner.
  • method flow proceeds to operation 215.
  • the one or more non-behavioral therapy components are administered to the patient in combination with the one or more behavioral therapy components according to the personalized intervention regimen generated for the patient.
  • administering therapies according to an intervention regimen can further include administration of other types of interventions, such as those including non-behavioral therapy components, in combination with interventions that include behavioral therapy components, by way of the online system in coordination with other devices, where monitoring of performance of activities with such interventions is described below.
  • non-behavioral therapy components can include one or more of: pharmaceutical compositions, nutraceutical compositions, nutritional therapies, whole system medicine, mind-body interventions, physical exercise, and biofeedback.
  • some therapies can be administered via a variety of routes, such as, but not limited to, ocular, oral, parenteral, topical, bronchial (e.g., by bronchial instillation), buccal, dermal (which may be or comprise, for example, one or more of topical to the dermis, intradermal, interdermal, transdermal, etc.), enteral, intra-arterial, intradermal, intragastric, intramedullary, intramuscular, intranasal, intraperitoneal, intrathecal, intravenous, intraventricular, within a specific organ (e.g., intrahepatic), mucosal, nasal, oral, rectal, subcutaneous, sublingual, topical, tracheal (e.g., by intratracheal instillation), vaginal, and vitreal.
  • routes such as, but not limited to, ocular, oral, parenteral, topical, bronchial (e.g., by bronchial instillation), buccal,
  • administration may be performed via a medical device such as, for example, a wearable device, an implanted device, and/or an ingestible device.
  • wearable devices may be designed and/or demonstrated to stimulate peristalsis.
  • ingestible devices can be designed and/or demonstrated to aid to trigger contractions in a colon of the patient.
  • therapies can be self-administered by patients, for example, in the case of therapies involving physical exercise or mind-body interventions.
  • method flow proceeds to operation 216.
  • the patient at operation 216, the patient’s interactions with the one or more behavioral therapy components and the one or more non-behavioral therapy components are monitored remotely in near real-time to generate patient interaction data.
  • an embodiment of the online system in coordination with the network and a client device, can monitor the patient’s interactions with the behavioral and non-behavioral therapy components contemporaneously with administration of the intervention regimen.
  • Monitoring patient interactions functions to provide intimate understanding of progress of the patient in achieving health goals, and to provide further personalization of and administration of intervention content at appropriate times, in order to maintain or improve progress of the patient.
  • Monitoring is preferably performed in near-real time or real time, such that actions can be taken to adjust interventions to patient states according to just-in-time adaptive intervention (JITAI) protocols.
  • JITAI just-in-time adaptive intervention
  • monitoring can be performed with any suitable delay (e.g., in relation to achieving better accuracy of assessed states of the patient).
  • monitoring can be performed using survey components, such as the patient reported outcome instruments described above, which may be delivered with interactive interventions of the intervention regimen, where the patient is prompted and provided with interactive elements that allow the patient to provide self-report data indicating progress statuses.
  • Monitoring can additionally or alternatively be performed with processing of other non-survey data streams, where the non-survey data streams are associated with system or device usage metrics, social networking behavior extracted from usage of social networking platforms and communication platforms, sensor-derived data, and/or other data. Monitoring can thus occur with any frequency and/or level of intrusiveness.
  • operation 216 can process monitoring data (e.g., real time data, non- real time data, dynamic data, static data) with a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • monitoring data e.g., real time data, non- real time data, dynamic data, static data
  • a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • ecological momentary assessments of the patient can be used for monitoring.
  • client device usage parameters can be used for monitoring. Examples of client device usage parameters can include frequency of application switching, duration of time spent in association with each application login, screen time parameters, data usage associated with different applications and/or types of applications (e.g., social networking, creative, utility, travel, activity-related, etc.) executing on the client device of the patient, time of day of application usage, location of device usage, and other client device usage parameters.
  • the system can process voice data and/or text communication data of the patient for monitoring and modifying interventions and program aspects.
  • voice data can include voice sampling data from which emotional states can be extracted using voice processing models.
  • natural language processing of textual data e.g., from communication platforms, from social networking platforms
  • the client device can be used to provide context for behaviors of the patient and/or assess emotional or cognitive states of the patient.
  • electronic health record data can be used for monitoring.
  • the online system can be configured to receive a notification providing information regarding the type of care the patient has received, and to use this data for monitoring statuses of the patient.
  • the system can include architecture for processing data from other sensors of the client device, devices in the environment of the patient, and/or wearable computing devices can be used for monitoring.
  • device data can include activity data, location data, motion data, biometric data, and/or other data configured to provide context to behaviors associated with the health condition of the patient.
  • motion data from motion of sensors of the client device can indicate that the user is sedentary, and may be experiencing symptoms that can be addressed with components of the intervention regimen.
  • device usage data can indicate that the patient has been using a particular device (e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient), in a fixed location (e.g., from GPS data), and in a prone position (e.g., from motion chip data), and may be experiencing health condition symptoms that can be addressed with components of the intervention regimen.
  • a particular device e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient
  • a fixed location e.g., from GPS data
  • a prone position e.g., from motion chip data
  • the DTX systems and methods as described herein may provide for communication between a patient and one or more external medication tracking devices, such as a smart pill packet, smart pill bottle, etc.
  • external medication tracking devices such as a smart pill packet or smart pill bottle may communication with and provide data to a cloud-based system to indicate, for example, if/when/how often a patient takes their medication.
  • technologies described herein may receive updates from the cloud-based system to track the patient’s taking of their medication.
  • An application may, for example, use received updates to check that a patient is adhering to their medication schedule, goals, etc., and present reminders accordingly.
  • technologies described herein may provide for other approaches of communication, e.g, directly, with external medication devices, for example wirelessly, e.g, over a wireless network, via Bluetooth®, and the like.
  • monitoring the patient’s interactions with the behavioral and non-behavioral therapy components includes obtaining one or more of: patient physiological health data; patient psychological health data; patient condition data; patient symptoms data; patient medications data; patient medication adherence data; patient medication side effect data; patient progress report data; patient system usage data; patient device usage data; patient social networking behavior data; patient voice data; patient textual data; patient activity data; patient location data; patient motion data; and patient biometric data.
  • active monitoring of patient states can be used to adjust administration of intervention regimen modules in order to appropriately meet the needs of the patient.
  • Other data and combinations of data can, however, be used for monitoring.
  • method flow proceeds to operation 218.
  • the patient interaction data is processed by the DTX system to generate intervention modification data representing recommended modifications to the patient’s personalized intervention regimen.
  • the recommended modifications to the patient’s personalized intervention regimen include recommended modifications to aspects of the behavioral therapy components of the regimen, based on processing of patient interaction data representing patient interactions with the behavioral therapy components of the regimen, wherein the patient interaction data is generated by the monitoring operation 216, as discussed above.
  • operation 218 functions to generate recommendations for further customization of the behavioral therapy components of the intervention regimen, in order to improve personalization of delivered content to meet the needs of the patient, in an adaptive manner.
  • Operation 218 can also function to generate recommendations for increasing engagement between the patient and the intervention regimen, in order to improve effectiveness of provided treatments and increase the chances of success of the patient in achieving their goals.
  • behavioral therapy components of the intervention regimen may include a plurality of interactive therapy modules.
  • recommendations for modifying aspects of the behavioral therapy components of the patient’s personalized intervention regimen can include one or more recommendations, such as, but not limited to: adjusting the order of administration of the behavioral therapy components; adjusting the frequency of administration of the behavioral therapy components; adjusting the mode of administration of the behavioral therapy components; adjusting the content of the behavioral therapy components; adjusting the content size of the behavioral therapy components; adjusting the presentation of the behavioral therapy components; adjusting the layout of the behavioral therapy components; updating the patient’s electronic health records (EHRs); updating the patient’s personal health records (PHRs); updating the patient’s open medical records, for instance by writing to or modifying records whenever new information is generated regarding the user/patient.
  • EHRs electronic health records
  • PHRs personal health records
  • recommendations for modifying aspects of the behavioral therapy components of the patient’s personalized intervention regimen can include recommendations for providing features for increasing engagement and optimal learning.
  • specific descriptions self-reported by the patient can be used in subsequent portions of the intervention regimen to increase personalization of the intervention to drive engagement.
  • features for increasing engagement and optimal learning can include features that mimic therapist/healthcare provider, or social group interactions (e.g., patient testimonials, clinician video content, etc.).
  • features for increasing engagement and optimal learning can include features that link the patient’s specific current problems and/or challenges faced by the patient as a trigger to notify the patient to interact with content of the intervention regimen and recommend appropriate skill for improving health states.
  • the recommended modifications to the patient’s personalized intervention regimen include recommended modifications to aspects of the non-behavioral therapy components of the regimen, based on processing of patient interaction data representing patient interactions with the non-behavioral therapy components of the regimen, wherein the patient interaction data is generated by the monitoring operation 216, as discussed above.
  • recommendations for modifying aspects of the non-behavioral therapy components of the patient’s personalized intervention regimen can include one or more recommendations, such as, but not limited to: adjusting the order of administration of the non- behavioral therapy components; adjusting the frequency of administration of the non-behavioral therapy components; adjusting the mode of administration of the non-behavioral therapy components; adjusting the content of the non-behavioral therapy components; adjusting the dosage amount of the non-behavioral therapy components; and adjusting the dosage schedule of the non-behavioral therapy components.
  • a dosage amount of the non-behavioral therapy treatment may be based upon the state of the patient’s health condition symptom severity.
  • a dosing schedule for administration of a non-behavioral therapy may be relative to a schedule for administration of the behavioral therapy.
  • Such recommendations regarding amount and/or dosing may be absolute and/or relative to other events and/or activities.
  • recommendations may comprise a particular schedule of dosage, e.g., a particular rate, timing (e.g., in a morning, afternoon, or evening), etc.
  • Recommendations regarding timing may include timings and/or amounts relative to other activities, such as meal consumption, physical exercises, seasons, social gatherings, travel, work, etc.
  • adjusting an amount of the non-behavioral therapy can include correspondingly adjusting an amount of a behavioral therapy treatment provided to the patient, thereby titrating relative treatment types provided to the patient based upon returned outputs of models associated with the methods described.
  • dosage recommendations provided via the approaches described herein are restricted to fall within a pre-defined range, for example as specified by a physician.
  • dosage recommendations provided by technologies (e.g., systems and methods) described herein comprise an identification of one or more specific symptoms or medication side effects, so as to provide recommendation to discuss particular symptoms with a medical professional, such as a physician and/or therapist (e.g., to discuss particular changes to medication regimens and/or types of medication, so as to best manage particular symptoms).
  • recommendations may be generated via use of one or more machine learning modules that receive, as input, data corresponding to patient symptom and/or habits, as tracked by various modules such as those described herein. In some embodiments, this information is used as feedback, to refine and dynamically update parameters of machine learning modules.
  • one or more notifications are issued to a computing device accessible to one or more health practitioners associated with the patient (e.g., nurses, physicians, dieticians, therapists, etc., who may be registered to view patient updates with a secure hub).
  • one or more notifications are issued to a patient computing device, for example, through the DTX system disclosed herein, and/or via an out-of-app notification, such as text message, push notification, email, calendar reminder, etc.
  • the one or more notifications include options and/or recommendations for modifications to the patient’s personalized intervention regimen, for the patient to discuss with their healthcare practitioner
  • the one or more notifications include identification of activities, behaviors, and/or symptoms of the patient.
  • the one or more notifications include options and/or recommendations for new therapies and/or potential adjustments to current therapies being administered to the patient.
  • the options and/or recommendations are based on potential compatibility of new and/or modified therapies with the identified activities, behaviors, and/or symptoms of the patient.
  • options and/or recommendations may include adjusting aspects of the patient’s intervention regimen, such that it is compatible with the patient’s physical exercise, travel, work, etc.
  • the one or more notifications include options and/or recommendations for one or more tests for the patient to complete (e.g., blood test, ultrasound.)
  • the one or more notifications include alerts and/or reminders to the patient to self-administer at least a portion of a therapy.
  • a notification may be a reminder to take a particular pharmaceutical composition and/or a particular nutraceutical composition and/or a notification may be a reminder to use a wearable device for a prescribed period of time according to a particular therapeutic regimen.
  • method flow proceeds to operation 220.
  • aspects of the behavioral therapy and/or the non-behavioral therapy components defined by the patient’s personalized intervention regimen may be modified based on the intervention modification data.
  • an embodiment of the online system in coordination with the network and a client device can, based on the intervention modification data, perform one or more actions to dynamically modify aspects of the behavioral therapy and/or the non- behavioral therapy components defined by patient’s personalized intervention regimen.
  • dynamically modifying aspects of the behavioral and non- behavioral therapy components of the patient’s personalized intervention regimen includes one or more of: adjusting the order of administration of the behavioral therapy components; adjusting the order of administration of the non-behavioral therapy components; adjusting the frequency of administration of the behavioral therapy components; adjusting the frequency of administration of the non-behavioral therapy components; adjusting the mode of administration of the behavioral therapy components; adjusting the mode of administration of the non-behavioral therapy components; adjusting the content of the behavioral therapy components; adjusting the content of the non- behavioral therapy components; adjusting the content size of the behavioral therapy components; adjusting the dosage amount of the non-behavioral therapy components; adjusting the dosage schedule of the non-behavioral therapy components; adjusting the presentation of the behavioral therapy components; adjusting the layout of the behavioral therapy components; updating the patient’s electronic health records; updating the patient’s personal health records; updating the patient’s open medical records; and increasing personalization of the intervention regimen.
  • dynamically modifying aspects of the patient’s personalized intervention regimen to promote patient engagement can be done using one or more of: artificial reality tools (e.g., augmented reality platforms, virtual reality platforms) for reducing depression, anxiety, pain, and/or other symptoms; artificial intelligence-based coaching elements for driving interactions with the patient; smart assistants (e.g., AlexaTM, SiriTM, GoogleTM Assistant, etc.) for assisting the patient in relation to task management, gamification elements within intervention regimen-associated applications executing on the client device; gamification elements of other devices (e.g., smart toilet devices having interactive elements, such as buttons that control flushing and other subsystems, for promoting triggering of stool sample tracking in relation to various symptoms); smart pill devices and/or medication-dispensing devices that provide insights in an engaging manner in coordination with intervention regimen modules; adjustment of reinforcement schedules (e.g., in relation to reward sensitivity, positive reinforcement, negative reinforcement, etc.) for providing intervention regimen content to the patient; and other elements for increasing engagement.
  • artificial reality tools e.g., augmented
  • features for modifying, updating, and/or personalizing the intervention regimen, as well as for promoting engagement with the intervention regimen can be delivered within modules of the intervention regimen before, during and/or after monitoring of the patient at operation 216.
  • the patient’s personalized intervention regimen is modified dynamically, in near-real time, based on the intervention modification data generated at operation 218.
  • method flow may return to operation 214 to continue administering the intervention according to the modified personalized intervention regimen.
  • method flow proceeds to END operation 222, and the method 200A for treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies is exited to await new instructions.
  • FIG. 2B depicts a flowchart of a method 200B for providing adaptive interventions for chronic pain health conditions, according to one or more embodiments.
  • method 200B begins at BEGIN 224, and method flow proceeds to operation 226.
  • operation 226 a pre-assessment of a patient exhibiting one or more chronic pain health condition symptoms is performed.
  • an embodiment of the online system in coordination with the network and a client device, can perform operation 226, performing a pre-assessment of a patient exhibiting one or more chronic pain health condition symptoms, contemporaneously with executing an onboarding process with the patient with the online system.
  • Operation 226 functions to retrieve data describing characteristics of the patient, preferences of the patient, goals of the patient and/or any other suitable patient features that can be used to provide adaptive interventions in a customized and personalized manner, in order to promote user engagement with the intervention regimen(s) described in subsequent operations of the method 200B.
  • operation 226 can include pre-assessing and onboarding patients and assessing characteristics including one or more of demographics (e.g., genders, ages, familial statuses, residential location, ethnicities, nationalities, socioeconomic statuses, sexual orientations, etc.), household situations (e.g., living alone, living with family, living with a caregiver, etc.), relationship status (e.g., sexually active), levels of activity, levels of pain medication usage, psychological symptom severity, levels of mobility (e.g., in relation to distance traveled in a period of time), sexual functioning, durations of mindfulness (e.g., mindful minutes), and any other suitable characteristic associated with chronic pain health conditions.
  • demographics e.g., genders, ages, familial statuses, residential location, ethnicities, nationalities, socioeconomic statuses, sexual orientations, etc.
  • household situations e.g., living alone, living with family, living with a caregiver, etc.
  • relationship status e.g., sexually active
  • levels of activity e.g.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify the patient as having chronic pain health condition symptoms such as, but not limited to, one or more of: moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light, sensitivity to sounds, pelvic pain, vulvar pain, vaginal pain, abdominal pain, bladder pain, fatigue, nausea, gastrointestinal symptoms, jaw pain, tenderness of jaw, tenderness of temporomandibular joint, pain at temporomandibular joint, tenderness in ears, tenderness around ears, pain in ears, facial tenderness, difficulty chewing, pain while chewing, pain and stiffness all over the body, headaches, facial pain, insomnia, and/or any other suitable symptoms.
  • chronic pain health condition symptoms such as, but not limited to, one or more of: moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light, sensitivity to sounds, pelvic pain, vulvar pain, vaginal pain, abdominal pain, bladder pain, fatigue, nausea, gastrointestinal symptoms, jaw pain, tenderness
  • a set of signals can encode physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user, from the pre-assessment, health record access, API access of health monitoring systems, and/or biometric sensors. Furthermore, such signals can be collected repeatedly throughout performance of the methods described, as will be discussed in additional detail below.
  • the pre-assessment can be configured to receive information regarding (or automatically detect, or automatically extract, based upon symptoms, etc.) the subtype(s) of a chronic pain disorder (e.g., subtypes of migraine such as hemiplegic migraine, retinal migraine, vestibular migraine, etc.) a patient has, in order to prioritize relevant content provided to the patient, in the interests of customizing the program. For instance, if the pre-assessment operation 226 identifies that the patient is predominantly subtype hemiplegic migraine, subsequent portions of the method 200B can prioritize content associated more highly with hemiplegic migraine. Subtype identification can, however, be assessed outside of the pre-assessment of operation 226.
  • a chronic pain disorder e.g., subtypes of migraine such as hemiplegic migraine, retinal migraine, vestibular migraine, etc.
  • complementary therapies for migraine can include one or more therapies, such as, but not limited to: triptans, non-opioid analgesics, non-steroidal anti-inflammatories, opioids, gepants, ditans, anticonvulsants, beta blockers, barbiturate-containing analgesics, ergot alkaloids, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, ACE inhibitors, angiotensin II receptor (ARBS) antagonists, calcium channel blockers, antidepressants, botulinum toxin, and other therapies.
  • Complementary therapies can further include one or more of: psychological treatments, hypnotherapy, acupuncture, herbal therapies, oils, and other therapies.
  • operation 226 of method 200B includes a method of determining severity of an associated gastrointestinal (GI) and/or chronic pain condition.
  • GI gastrointestinal
  • FIG. 5A depicts a flowchart of a process for determining severity of a an associated gastrointestinal and/or chronic pain condition, according to one or more embodiments.
  • FIG. 5B depicts examples of a process for determining severity of a chronic pain condition, according to one or more embodiments.
  • the process 500 can include operation 501 for calculating levels of a chronic pain health condition-associated marker (e.g., from a sample from the user, such as a blood sample or a saliva sample, from interactions with the system, etc.) to identify the user (e.g. the patient), as having a certain state of severity (e.g., expression, phenotype, etc.) of the chronic pain health condition.
  • a chronic pain health condition-associated marker e.g., from a sample from the user, such as a blood sample or a saliva sample, from interactions with the system, etc.
  • a certain state of severity e.g., expression, phenotype, etc.
  • 5 A can be implemented through a DTX system executing on a mobile device or other device associated with the user, where a user interface of the DTX system prompts inputs from the user pertaining to various symptoms (e.g., pain location, pain severity, energy levels, digestive issues, cognitive symptoms, behavioral effects, etc.) and generates a report indicating severity of the chronic pain health condition as shown in FIG. 5B.
  • various symptoms e.g., pain location, pain severity, energy levels, digestive issues, cognitive symptoms, behavioral effects, etc.
  • the process 500 shown in FIG. 5A can then include operation 502, administering a treatment (e.g., monotherapy, complementary therapy) to the user having the state of severity, where the treatment comprises one or more of the therapies described.
  • a treatment e.g., monotherapy, complementary therapy
  • the process 200B can include adjusting (e.g., decreasing, increasing, maintaining) an amount of a non-behavioral therapy treatment provided to the user based upon the state of severity, and/or correspondingly adjusting (e.g., decreasing, increasing, maintaining) an amount of a behavioral therapy treatment provided to the user, thereby titrating relative treatment types provided to the user based upon returned outputs of models associated with the methods described.
  • a treatment cocktail can include prescription digital therapeutic aspects and nonprescription digital therapeutic aspects.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify mental health statuses of the patient, in relation to comorbid or non-comorbid conditions (e.g., associated with anxiety, associated with depression, associated with social behavior, etc.), where the intervention regimen described in more detail above can be configured to improve mental health states of the patient in a timely and adaptive manner.
  • the DTX systems and methods described herein may be used to treat, ameliorate, prevent, or reduce the likelihood of developing one or more comorbidities associated with a chronic pain disorder in a patient.
  • the one or more comorbidities associated with the chronic disorder and treated using the DTX systems and methods described herein include, but not limited to a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, an attention deficit hyperactivity disorder, an obsessive compulsive disorder, a post-traumatic stress disorder, an eating disorder, a substance use disorder, an anhedonia disorder, a cardiovascular disease, a sleep disorder, chronic fatigue, inflammatory bowel syndrome, fibromyalgia, tinnitus, hypertension, asthma, gastroesophageal reflux disease, functional dyspepsia, and/or any other suitable comorbidities.
  • related data can include psychological and/or disease symptom/clinical profile data that informs selection of high priority therapy components, where examples include data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia characteristics of the patient, promoting behavioral activation content by the system and response chaining, where response chaining involves linking of effortful avoided tasks to those that are neutral or slightly rewarding); sources of motivation; reward sensitivity (e.g., sensitivity associated with drive and reward responsiveness (e.g., using a BIS/BAS assessment tool); and threat sensitivity.
  • data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia
  • the method 200B can include receiving a reward sensitivity dataset characterizing motivation and reinforcement behavior of the user, and modulating aspects of the treatment upon processing the reward sensitivity dataset with one or more models described.
  • Mental health, reward tendencies and sensitivity, and motivational aspect identification can, however, be assessed outside of the pre-assessment of operation 226.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify user preferences associated with scheduling of content delivery (e.g., in relation to frequencies of content delivery described above) associated with one or more aspects of the intervention regimen, preferred formats (e.g., visual formats, audio formats, haptic formats, etc.) of content delivery, frequency of content delivery, location of user when content is delivered, specific device(s) to which content is delivered, and/or any other suitable user preferences.
  • preferred formats e.g., visual formats, audio formats, haptic formats, etc.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify user goals for improving health, in relation to the intervention regimen.
  • Such goals can include one or more goals, such as, but not limited to: reduction of anxiety, reduction of negative emotions, reduction of depression symptoms, improvement of sleep behavior, improvement in socialization, improvement of chronic pain health condition symptoms, improvement of medication adherence, improvement in chronic pain-related quality of life, improvement of other health condition symptoms, and/or any other suitable goals.
  • Goals can be organized at a high level of abstraction (e.g., improve sleep behavior), and/or at lower levels of abstraction (e.g., improve quality of sleep, reduce number of symptom-induced disturbances to sleep, etc.).
  • the online system and/or other system components can implement surveying tools (e.g., for self-report of data from the patient) and/or non-survey-based tools for acquisition of data.
  • Survey tools can be delivered through an application associated with the DTX system executing on the client device of the patient and/or through another suitable method, where the survey tools can implement architecture for assessing the patient in relation to mental health, pain, chronic pain health symptom severity or disease activity, types of chronic pain health condition symptoms, and/or other statuses.
  • the surveying tools can be derived from one or more tools such as, but not limited to a Numbered Pain Scale (NPS); a Numbered Rating Scale (NRS); a Verbal Rating Scale (VRS); a Visual Analog Scale (VAS); a Categorical Scale; a Quantitative Scale; a Qualitative Scale; a COMFORT Scale; a McGill Pain Questionnaire; a Mankoski Pain Scale; a Brief Pain Inventory (BPI); a Descriptor Differential Scale of Pain Intensity (DDS-I) a Universal Pain Assessment Tool (UP AT); an IMMPACT evaluation; Multidimensional Pain Inventory (MPI); Global Impression of Change Scale; other psychometric testing; a GAD-7 anxiety disorder questionnaire; a Beck Depression Inventory; a profile of mood states; a pain assessment questionnaire; and any other tool or instrument.
  • NPS Numbered Pain Scale
  • NRS Numbered Rating Scale
  • VRS Verbal Rating Scale
  • VAS
  • Survey components can be implemented during pre-assessment of a patient and/or within modules of the intervention regimen, as described in more detail above.
  • the assessment may also entail patient- reported data on health related quality of life, emotional impact of pain and pain self-efficacy metrics.
  • the system can include architecture for receiving data derived from the patient (e.g., through sensor components, through survey components, associated with pain characteristics, digestive characteristics, cognitive characteristics, and other characteristics), processing the data with one or more models, and returning scores (e.g., measures of symptom severity, etc.). Scores can also be used for tagging user data with symptom severity, in relation to model aspects and model training/refinement described below.
  • the online system and/or other system components can implement data from devices (e.g., non-survey data).
  • devices e.g., non-survey data
  • embodiments of the system can perform pre-assessment with implementation of data from devices including one or more devices, such as, but not limited to: electronic health record-associated devices; torso-coupled devices; wearable devices; cardiovascular monitoring; implanted devices; sleep monitoring devices; location monitoring devices; social networking tracking devices; and combinations thereof, and other devices.
  • Non-survey-derived data can additionally or alternatively include data derived from API access of social networking platforms, other communication platforms (e.g., for extracting social behavior characteristics associated with text, voice, and other communications of the users), location-determining platforms, and/or other platforms, in order to assess social behaviors of the user.
  • FIG. 6 depicts a flowchart of a pre-assessment and onboarding process of a method for providing adaptive interventions, according to one or more embodiments.
  • the pre-assessment and onboarding process 600 can include operation 611, which facilitates downloading of an application associated with the system and/or using of a non-downloadable version of the system (e.g., via web application, etc.) for delivering the intervention regimen by a client device of the patient; operation 612, which renders a welcome/introduction screen within the application associated with the system; operation 613, which delivers content within the application for educating the patient regarding the purpose of the system and provides an overview of the intervention regimen; operation 614, which creates a patient profile within the online system, resulting in a first tier of personalization by implementing survey and nonsurvey based tools (e.g., to assess gender, age, preferences for scheduling of content delivery, specific chronic pain health condition symptoms of the patient, etc.); and operation 615, which, within the application associated with the system, assesses goals of the patient, resulting in a second tier of personalization.
  • operation 611 which facilitates downloading of an application associated with the system and/or using of a non
  • the second tier of personalization can operate by assessing goals related to anxiety reduction, depression reduction, reduction of chronic pain disease or syndrome symptoms, improvement of sleep, improvement of socialization, and other goals.
  • FIG. 6 further depicts operation 616, which, in one embodiment, processes the data from operations 614 and 615 with an intervention-determining model to output a personalized intervention regimen with adaptive behavioral therapy tools and exercises for improving health and wellbeing of the patient, in relation to his/her specific goals.
  • FIG. 6 also depicts operation 617 where a first module of the intervention regimen is delivered to the patient within the application associated with the system, and operation 618, which provides further adaptation of modules of the intervention regimen as the patient progresses through the intervention regimen and interacts with content.
  • FIG. 6 While the operations of FIG. 6 are shown in a particular order, the operations can be performed in another suitable sequence, omit operations, and/or include additional operations (e.g., based on refinement and training of models, as described below, as well as based on other factors).
  • FIG. 7 depicts examples of behavioral therapy modules of a program for personalized chronic pain condition monitoring and improvement, according to one or more embodiments.
  • process flow proceeds to operation 228.
  • an intervention regimen for the patient is generated upon processing data from the preassessment with an intervention-determining model.
  • one embodiment of the online system in coordination with the network and a client device, can process data from the pre-assessment with an intervention-determining model.
  • Operation 228 functions to generate an intervention regimen for the patient upon processing pre-assessment data, in order to design a customized intervention regimen to address specific symptoms and needs of the patient. While operation 228 is described in relation to pre-assessment data, model architecture and associated algorithms can additionally or alternatively be applied to assessment of patient data as the patient interacts with content of the intervention regimen, in order to adaptively modify delivery of intervention regimen components to the patient, with processing of incoming data.
  • the intervention-determining model contemporaneously processes data associated with patient goals, user chronic pain health condition symptoms, patient mental health states, other characteristics, and interactions with content of the DTX system, providing the intervention regimen as inputs, in order to output a customized and modulatable intervention regimen to improve the health and/or wellbeing of the patient.
  • the intervention-determining model can include architecture for one or more of conditional decision making (e.g., with conditional branching structure that processes input data in stages and determines an output at each node of the branching structure); ranking (e.g., with ranking algorithms configured to rank candidate intervention regimen components according to appropriateness, based on the input data); matching (e.g., with performance of best match operations between input data and different groups representing modules of the intervention regimen, with centroid-based approaches, etc.); correlation (e.g., correlation functions that process input data to generate outputs associated with different intervention regimen components); and/or any other suitable architecture. Training of models is further described below.
  • conditional decision making e.g., with conditional branching structure that processes input data in stages and determines an output at each node of the branching structure
  • ranking e.g., with ranking algorithms configured to rank candidate intervention regimen components according to appropriateness, based on the input data
  • matching e.g., with performance of best match operations between input data and different groups representing modules of the intervention regimen, with centroid
  • method flow proceeds to operation 230.
  • the online system in coordination with other system components (e.g., the client device, external systems, network, etc.) delivers the intervention regimen to the patient, for instance, through an application associated with the DTX system executing at the client device of the patient.
  • content associated with the intervention regimen can be of visual (e.g., image format, video format), textual, audio, haptic, and/or other formats, through connected devices (e.g., mobile computing devices, wearable devices, audio output devices, displays, temperature control devices, lighting control devices, etc.) and generated in a manner that promotes user engagement.
  • connected devices e.g., mobile computing devices, wearable devices, audio output devices, displays, temperature control devices, lighting control devices, etc.
  • the system in providing the interventions (e.g., such as interventions described in more detail below), can coordinate with and/or provide instructions for control of other devices, for intervention delivery.
  • the system can coordinate with environmental control devices (e.g., connected audio output devices, connected temperature control devices, connected lighting control devices, connected pill dispensing devices, connected smart pill devices, etc.) to change aspects of the patient’s environment in association with provision of the intervention regimen.
  • environmental control devices e.g., connected audio output devices, connected temperature control devices, connected lighting control devices, connected pill dispensing devices, connected smart pill devices, etc.
  • the intervention regimen can provide a grounding exercise to reduce anxiety regarding chronic pain health condition symptoms, where the user is prompted to observe aspects of the environment with multiple senses, and the system can coordinate with environmental control devices to adjust one or more of lighting (e.g., colors, intensity, etc.), sounds (e.g., through audio output devices), and/or temperature in the patient’s environment.
  • the intervention regimen can provide a relaxation exercise to reduce pain associated with chronic pain health condition symptoms, and coordinate with an audio output device to play music pleasing to the patient.
  • the intervention regimen can provide an exercise activity involving movements or dancing, to reduce bloating and depression associated with chronic pain health condition symptoms, and coordinate with an audio output device to play dance music to the user, while reducing environmental temperature with a smart thermostat device.
  • the system can provide coordinated interventions, however, in any other suitable manner, where details of interventions are provided in more detail above.
  • DTX for use in the improvement of non-digital therapeutic interventions for chronic pain disorders.
  • a method of enhancing the performance of a therapeutic intervention administered to a patient for the treatment, prevention, amelioration, or reduction in the likelihood of developing a chronic pain disorder and/or one or more side effects associated with the therapeutic intervention comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic includes: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the therapeutic intervention for the chronic pain condition includes treatments utilizing one or more pharmaceutical compositions.
  • the one or more side effects associated with the one or more pharmaceutical compositions are each independently selected from the group consisting of constipation, nausea, vomiting, fatigue, stomach ache, diarrhea, headaches, drowsiness, dizziness, confusion, tiredness, insomnia, nervousness, dizziness, abdominal pain, muscle pain, itching, rapid heartbeat, hypertension, mood swings, upset stomach, paresthesia, vision disturbances, indigestion, tinnitus, restlessness, anxiety, difficulty sleeping, feeling sick, dry cough, increased heartbeat, rash, insomnia, loss of libido, erectile dysfunction, GI dysfunction, confusion, depression, ringing or buzzing in ears, itching, tiredness, reduced libido, stomach pain, heartbum, vaginal itching, fatigue, loss of libido, low libido, ringing or buzzing in ears, itching, increased heart rate, sexual dysfunction, cardiac arrhythmia, fatigue,
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, nonsteroidal anti-inflammatories, opioids, gepants, ditans, barbiturate-containing analgesics, ergot alkaloids, ergotamines, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, anticonvulsants, antidepressants, a-blockers, 5-a- reductase inhibitors, beta blockers, ACE inhibitors, progestins, angiotensin II receptor antagonists, calcium channel blockers, CNS depressants, quinolones, tetracyclines, serotonin norepinephrine reuptake inhibitors, serotonin reuptake inhibitors
  • adjusting the dosage of the one or more pharmaceutical composition comprises increasing the dosage to increase effectiveness of the therapeutic intervention without increasing the associated side effects.
  • adjusting dosage of the one or more pharmaceutical composition comprises increasing the dosage of the one or more pharmaceutical compositions without increasing the associated side effects to a higher amount that is therapeutically effective in a patient who is not responsive to lower amounts of the one or more pharmaceutical compositions.
  • adjusting dosage of the one or more pharmaceutical composition comprises reducing the dosage of the one or more pharmaceutical compounds responsive to treatment or amelioration of one or more symptoms of the chronic pain disorder using the digital therapeutics; and wherein the reduced dosage is therapeutically effective.
  • enhancing performance of the therapeutic intervention comprises reducing, ameliorating, or preventing the one or more side effects associated with the therapeutic intervention.
  • enhancing performance of the therapeutic intervention comprises increasing bioavailability of the one or more pharmaceutical compositions by reducing, ameliorating, or preventing one or more of side effects associated with the therapeutic intervention and/or by reducing, ameliorating, or preventing one or more symptoms associated with the chronic pain disorder.
  • a method of treating, preventing, ameliorating, or reducing the likelihood of developing a chronic pain disorder in a patient comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic includes: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the patient is undergoing or has undergone a therapeutic intervention for said condition.
  • the therapeutic intervention comprises one or more non-digital treatments selected from the group consisting of: treatments utilizing one or more pharmaceutical compositions; treatments utilizing one or more nutraceutical compositions; treatments utilizing one or more medical devices; treatments utilizing one or more physical activities; treatments utilizing one or more mind-body interventions; treatments utilizing whole system medicine; treatments utilizing one or more surgeries; and combinations thereof.
  • the therapeutic intervention comprising one or more non-digital treatments is provided prior to, contemporaneously with, and/or after administering the digital therapeutic to the patient.
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, nonsteroidal anti-inflammatories, opioids, gepants, ditans, barbiturate-containing analgesics, ergot alkaloids, ergotamines, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, anticonvulsants, antidepressants, a-blockers, 5-a- reductase inhibitors, beta blockers, ACE inhibitors, progestins, angiotensin II receptor antagonists, calcium channel blockers, CNS depressants, quinolones, tetracyclines, serotonin norepinephrine reuptake inhibitors, serotonin reuptake inhibitors,
  • the one or more nutraceutical compositions each comprise at least one nutraceutical component independently selected from the group consisting of microorganisms, proteins, vitamins, herbs, dietary supplements, and combinations thereof.
  • the one or more medical devices are each independently selected from the group consisting of wearable devices, ingestible devices, implanted devices, biofeedback devices, Transcutaneous electrical nerve stimulation (TENS) and microcurrent nerve stimulation (MENS) devices, remote electrical neuromodulation (REN) device, non-invasive vagus nerve stimulation (nVNS) device, transcranial magnetic stimulator, pressure sensors, acupressure or motion sensor mat, phototherapy devices, compression devices, heat therapy devices, and combinations thereof.
  • the chronic pain disorder is selected from the group consisting of migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic neuropathic pain, and combinations thereof.
  • the chronic pain disorder is migraine
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, non-steroidal anti-inflammatories, opioids, gepants, ditans, anticonvulsants, beta blockers, barbiturate-containing analgesics, ergot alkaloids, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, ACE inhibitors, angiotensin II receptor (ARBS) antagonists, calcium channel blockers, antidepressants, botulinum toxin, and combinations thereof.
  • CGRP calcitonin gene-related peptide
  • ARBS angiotensin II receptor
  • the chronic pain disorder is fibromyalgia
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of anticonvulsants, antidepressants, opioids, muscle relaxants, CNS depressants, and combinations thereof.
  • the chronic pain disorder is chronic pelvic pain
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of a-blockers, 5-a-reductase inhibitors, opioids, quinolones, tetracyclines, antidepressants, anticonvulsants, non-steroidal anti-inflammatory drugs, muscle relaxants, cannabinoids, progestins, anxiolytics, neuroleptics, calcium channel blockers, botulinum toxin, N- methyl-D-aspartate (NDMA) glutamate receptor antagonists, NGF inhibitors, and combinations thereof.
  • a-blockers 5-a-reductase inhibitors
  • opioids quinolones, tetracyclines
  • antidepressants anticonvulsants
  • non-steroidal anti-inflammatory drugs muscle relaxants
  • cannabinoids progestins
  • anxiolytics neuroleptics
  • calcium channel blockers botulinum toxin
  • the chronic pain disorder is a temporomandibular disorder
  • the temporomandibular disorder including temporomandibular joint disorder
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of non-steroidal anti-inflammatory drugs, corticosteroids, bioactive compounds, isolated compounds, anxiolytics, benzodiazepines, carbamates, barbiturates, barbiturate-like hypnotics, opioids, antidepressants, anticonvulsants, 5HT receptor agonists, botulinum toxin, corticosteroids, dietary supplements, celecoxib, cannabis-related drugs, muscle relaxants, and combinations thereof.
  • the digital therapeutic treatment components include components of therapies selected from the group of therapies consisting of: psychotherapy; cognitive behavioral therapy (CBT); education and communication/assertiveness training around sexual functioning and alternative intimacy techniques (SFT), acceptance and commitment (ACT) therapy; pelvic floor physical therapy; pelvic floor relaxation therapy; dialectical behavioral therapy (DBT); exposure therapy; mindfulness-based cognitive therapy (MCBT); somatic anchoring therapy, hypnotherapy; experiential therapy; relaxation therapy; biofeedback therapy; psychodynamic therapy; and combinations thereof.
  • therapies selected from the group of therapies consisting of: psychotherapy; cognitive behavioral therapy (CBT); education and communication/assertiveness training around sexual functioning and alternative intimacy techniques (SFT), acceptance and commitment (ACT) therapy; pelvic floor physical therapy; pelvic floor relaxation therapy; dialectical behavioral therapy (DBT); exposure therapy; mindfulness-based cognitive therapy (MCBT); somatic anchoring therapy, hypnotherapy; experiential therapy; relaxation therapy; biofeedback therapy; psychodynamic therapy; and combinations thereof.
  • remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components includes obtaining patient data including one or more of: patient physiological health data; patient psychological health data; patient condition data; patient pain data; patient symptoms data; patient medications data; patient medication adherence data; patient progress report data; patient system usage data; patient device usage data; patient social networking behavior data; patient voice data; patient textual data; patient activity data; patient location data; patient motion data; and patient biometric data.
  • remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components includes utilizing surveying tools derived from one or more patient reported outcome instruments selected from the group of patient reported outcome instruments consisting of: a Numbered Pain Scale (NPS); a Numbered Rating Scale (NRS); a Verbal Rating Scale (VRS); a Visual Analog Scale (VAS); a Categorical Scale; a Quantitative Scale; a Qualitative Scale; a COMFORT Scale; a McGill Pain Questionnaire; a Mankoski Pain Scale; a Brief Pain Inventory (BPI); a Descriptor Differential Scale of Pain Intensity (DDS-I) a Universal Pain Assessment Tool (UP AT); an IMMPACT evaluation; Multidimensional Pain Inventory (MPI); Global Impression of Change Scale; other psychometric testing; a GAD-7 anxiety disorder questionnaire; a Beck Depression Inventory
  • remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components includes utilizing non-survey data obtained from one or more devices selected from the group of devices consisting of: electronic health record- associated devices; torso-coupled devices; wearable devices; cardiovascular monitoring; implanted devices; medication tracking and/or delivery device; sleep monitoring devices; location monitoring devices; social networking tracking devices; and combinations thereof.
  • dynamically modifying one or more of the digital therapeutic treatment components includes one or more of: adjusting the order of administration of the digital therapeutic components; adjusting the order of administration of the non-digital treatment; adjusting the frequency of administration of the digital therapeutic components; adjusting the frequency of administration of the non-digital treatments; adjusting the mode of administration of the digital therapeutic components; adjusting the mode of administration of the non-digital treatments; adjusting the content of the digital therapeutic components; adjusting the content of the non-digital treatments; adjusting the content size of the digital therapeutic components; adjusting the dosage amount of the non-digital treatments; adjusting the dosage schedule of the non-digital treatments; adjusting the presentation of the digital therapeutic components; adjusting the layout of the digital therapeutic components; and increasing personalization of the digital therapeutic components.
  • a method of treating, preventing, ameliorating, or reducing the likelihood of developing one or more symptoms associated with a chronic pain disorder in a patient comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic comprises: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the one or more symptoms are each independently selected from the group consisting of moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light, sensitivity to sounds, pelvic pain, vaginal pain, vulvar pain, abdominal pain, bladder pain, fatigue, nausea, gastrointestinal symptoms, jaw pain, tenderness of jaw, tenderness of temporomandibular joint, pain at temporomandibular joint, tenderness in ears, tenderness around ears, pain in ears, facial tenderness, difficulty chewing, pain while chewing, pain and stiffness all over the body, headaches, facial pain, insomnia, and combinations thereof.
  • the patient is undergoing or has undergone one or more non-digital therapeutic interventions for said condition.
  • the one or more non-digital therapeutic interventions is provided prior to, contemporaneously with, and/or after administering the digital therapeutic to the patient.
  • the one or more non-digital therapeutic interventions are each independently selected from the group consisting of: treatments utilizing one or more pharmaceutical compositions; treatments utilizing one or more nutraceutical compositions; treatments utilizing one or more medical devices; treatments utilizing one or more physical activities; treatments utilizing one or more mindbody interventions; treatments utilizing whole system medicine; treatments utilizing one or more surgeries; and combinations thereof.
  • the chronic pain disorder is selected from the group consisting of migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic neuropathic pain, and combinations thereof.
  • the chronic pain disorder is migraine
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, non-steroidal anti-inflammatories, opioids, gepants, ditans, anticonvulsants, beta blockers, barbiturate-containing analgesics, ergot alkaloids, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, ACE inhibitors, angiotensin II receptor (ARBS) antagonists, calcium channel blockers, antidepressants, botulinum toxin, and combinations thereof.
  • CGRP calcitonin gene-related peptide
  • ARBS angiotensin II receptor
  • the chronic pain disorder is fibromyalgia
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of anticonvulsants, antidepressants, opioids, muscle relaxants, CNS depressants, and combinations thereof.
  • the chronic pain disorder is chronic pelvic pain
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of a-blockers, 5-a-reductase inhibitors, opioids, quinolones, tetracyclines, antidepressants, anticonvulsants, non-steroidal anti-inflammatory drugs, muscle relaxants, cannabinoids, progestins, anxiolytics, neuroleptics, calcium channel blockers, botulinum toxin, N- methyl-D-aspartate (NDMA) glutamate receptor antagonists, NGF inhibitors, and combinations thereof.
  • a-blockers 5-a-reductase inhibitors
  • opioids quinolones, tetracyclines
  • antidepressants anticonvulsants
  • non-steroidal anti-inflammatory drugs muscle relaxants
  • cannabinoids progestins
  • anxiolytics neuroleptics
  • calcium channel blockers botulinum toxin
  • the chronic pain disorder is a temporomandibular disorder
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of non-steroidal anti-inflammatory drugs, corticosteroids, bioactive compounds, isolated compounds, anxiolytics, benzodiazepines, carbamates, barbiturates, barbiturate-like hypnotics, opioids, antidepressants, anticonvulsants, 5HT receptor agonists, botulinum toxin, corticosteroids, dietary supplements, celecoxib, cannabis-related drugs, muscle relaxants, and combinations thereof.
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, nonsteroidal anti-inflammatories, opioids, gepants, ditans, barbiturate-containing analgesics, ergot alkaloids, ergotamines, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, anticonvulsants, antidepressants, a-blockers, 5-a- reductase inhibitors, beta blockers, ACE inhibitors, progestins, angiotensin II receptor antagonists, calcium channel blockers, CNS depressants, quinolones, tetracyclines, serotonin norepinephrine reuptake inhibitors, serotonin reuptake inhibitor
  • CGRP calcitonin gene-related peptide
  • the chronic pain disorder is migraine, and the one or more symptoms are each independently selected from the group consisting of moderate to severe headaches, headaches associated with nausea, vomiting, sensitivity to light and sounds, and combinations thereof.
  • the chronic pain disorder is chronic pelvic pain, and the one or more symptoms are each independently selected from the group consisting of pelvic pain, abdominal pain, bladder pain, fatigue, nausea, gastrointestinal symptoms, depression, and combinations thereof.
  • the chronic pain disorder is a temporomandibular disorder
  • the one or more symptoms are each independently selected from the group consisting of jaw pain, tenderness of jaw, tenderness and/or pain of temporomandibular joint, tenderness and/or pain in and around the ear(s) and face, difficulty chewing, pain while chewing, and combinations thereof.
  • the chronic pain disorder is fibromyalgia
  • the one or more symptoms are each independently selected from the group consisting of body pain, stiffness all over the body, fatigue, headaches, migraines, facial pain, jaw pain, insomnia, and combinations thereof.
  • a method of treating, preventing, ameliorating, or reducing the likelihood of developing one or more side effects associated with a therapeutic intervention for a chronic pain disorder in a patient who is undergoing said therapeutic intervention comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic includes: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the therapeutic intervention for the chronic pain disorder includes treatments utilizing one or more pharmaceutical compositions.
  • the one or more side effects associated with the one or more pharmaceutical compositions are each independently selected from the group consisting of constipation, nausea, vomiting, fatigue, Stomach ache, diarrhea, headaches, drowsiness, dizziness, confusion, tiredness, insomnia, nervousness, dizziness, abdominal pain, muscle pain, itching, rapid heartbeat, Hypertension, mood swings, upset stomach, paresthesia, vision disturbances, indigestion, tinnitus, restlessness, anxiety, difficulty sleeping, feeling sick, dry cough, increased heartbeat, rash, insomnia, loss of libido, erectile dysfunction, GI dysfunction, confusion, Depression, ringing or buzzing in ears, itching, tiredness, Reduced libido, stomach pain, heartbum, vaginal itching, fatigue, loss of libido, low libido, ringing or buzzing in ears, itching, increased heart rate, sexual dysfunction, cardiac arrhythmia, fatigue
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, nonsteroidal anti-inflammatories, opioids, gepants, ditans, barbiturate-containing analgesics, ergot alkaloids, ergotamines, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, anticonvulsants, antidepressants, a-blockers, 5-a- reductase inhibitors, beta blockers, ACE inhibitors, progestins, angiotensin II receptor antagonists, calcium channel blockers, CNS depressants, quinolones, tetracyclines, serotonin norepinephrine reuptake inhibitors, serotonin reuptake inhibitors
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of almotriptan, eletriptan, frovatriptan, naratriptan, rizatriptan, sumatriptan, zolmitriptan, sumatriptan/naproxen, ergotamines, lasmiditan, acetaminophen, ibuprofen, aspirin, meloxicam, feldene, celocoxib, peroxicam, diclofenac, naproxen, ketorolac, opioids, gepants, ditans, topiramate, divalproex sodium, valproate sodium, metoprolol, propranolol, timolol, atenolol, nadolol, barbiturate containing analgesics, dihydroergotamine, ergotamine, cor
  • the chronic pain disorder is selected from the group consisting of migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, temporomandibular joint disorder, chronic facial pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, cancer pain, post-operative pain, stress-induced chronic pain, diabetic neuropathic pain, chronic fatigue syndrome, and combinations thereof.
  • the chronic pain disorder is a migraine disorder
  • the therapeutic intervention for the migraine disorder comprises one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of triptans, nonopioid analgesics, non-steroidal anti-inflammatories, opioids, gepants, ditans, anticonvulsants, beta blockers, barbiturate-containing analgesics, ergot alkaloids, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, ACE inhibitors, angiotensin II receptor (ARBS) antagonists, calcium channel blockers, antidepressants, botulinum toxin, and combinations thereof; and wherein the one or more side effects associated with the one or more pharmaceutical compositions for the migraine disorder are each independently selected from the group consisting of constipation, nausea, vomiting,
  • the chronic pain disorder is a fibromyalgia disorder
  • the therapeutic intervention for the fibromyalgia disorder includes one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of anticonvulsants, antidepressants, opioids, muscle relaxants, CNS depressants, and combinations thereof; and wherein the one or more side effects associated with the one or more pharmaceutical compositions are each independently selected from the group consisting of dizziness, drowsiness, headache, anxiety, fatigue, insomnia, headache, GI dysfunction, Constipation, nausea, confusion, Depression, ringing or buzzing in ears, itching, tiredness, diarrhea, muscle pain, insomnia and combinations thereof.
  • the chronic pain disorder is a chronic pelvic pain disorder; wherein the therapeutic intervention for the chronic pelvic pain disorder includes one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of a-blockers, 5-a-reductase inhibitors, opioids, quinolones, tetracyclines, antidepressants, anticonvulsants, non-steroidal anti-inflammatory drugs, muscle relaxants, cannabinoids, progestins, anxiolytics, neuroleptics, calcium channel blockers, botulinum toxin, N-methyl-D-aspartate (NDMA) glutamate receptor antagonists, NGF inhibitors, and combinations thereof; and wherein the one or more side effects associated with the one or more pharmaceutical compositions include drowsiness, headaches, dizziness, reduced libido, depression, anxiety, constipation, nausea, confusion, nausea, vomiting, stomach pain
  • the chronic pain disorder is a temporomandibular disorder
  • the therapeutic intervention for the temporomandibular disorder includes one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of non-steroidal anti-inflammatory drugs, corticosteroids, bioactive compounds, isolated compounds, anxiolytics, benzodiazepines, carbamates, barbiturates, barbiturate-like hypnotics, opioids, antidepressants, anticonvulsants, 5HT receptor agonists, botulinum toxin, corticosteroids, dietary supplements, celecoxib, cannabis-related drugs, muscle relaxants, and combinations thereof; and wherein the one or more side effects associated with the one or more pharmaceutical compositions are each independently selected from the group consisting of stomach ache, nausea, diarrhea, headaches, drowsiness, dizziness, hypertension, mood swings, vomiting, digestive disturbance
  • DTX for use in improvement of adherence to non-digital therapeutic interventions for chronic pain disorders
  • a method of improving patient adherence to a treatment regimen of a therapeutic intervention administered to said patient for the treatment, prevention, amelioration, or reduction in the likelihood of developing a chronic pain disorder and/or one or more side effects associated with said therapeutic intervention comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic includes: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the therapeutic intervention for the chronic pain disorder includes treatments utilizing one or more pharmaceutical compositions.
  • the chronic pain disorder is selected from the group consisting of migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic neuropathic pain, and combinations thereof.
  • the one or more side effects associated with the one or more pharmaceutical compositions are each independently selected from the group consisting of constipation, nausea, vomiting, fatigue, Stomach ache, diarrhea, headaches, drowsiness, dizziness, confusion, tiredness, insomnia, nervousness, dizziness, abdominal pain, muscle pain, itching, rapid heartbeat, hypertension, mood swings, upset stomach, paresthesia, vision disturbances, indigestion, tinnitus, restlessness, anxiety, difficulty sleeping, feeling sick, dry cough, increased heartbeat, rash, insomnia, loss of libido, erectile dysfunction, GI dysfunction, confusion, depression, ringing or buzzing in ears, itching, tiredness, reduced libido, stomach pain, heartburn, vaginal itching, fatigue, loss of libido, low libido, ringing or buzzing in ears, itching, increased heart rate, sexual dysfunction, cardiac ar
  • the one or more pharmaceutical compositions each include at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, nonsteroidal anti-inflammatories, opioids, gepants, ditans, barbiturate-containing analgesics, ergot alkaloids, ergotamines, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, anticonvulsants, antidepressants, a-blockers, 5-a- reductase inhibitors, beta blockers, ACE inhibitors, progestins, angiotensin II receptor antagonists, calcium channel blockers, CNS depressants, quinolones, tetracyclines, serotonin norepinephrine reuptake inhibitors, serotonin reuptake inhibitors,
  • improving patient adherence to the therapeutic intervention comprises: receiving, via one or more of the digital therapeutic treatment components, patient adherence data; identifying patterns related to said patient’s treatment regimen based on symptom changes associated adherence to the treatment regimen and/or symptoms and/or activities that are associated with degree to which said patient adheres to the treatment regimen; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on the patient adherence data and the identified patterns; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • a sixth example of the method which optionally includes one or more of the first through fifth examples, further comprises: performing, by the therapeutics system, a pre-assessment of the patient; generating, by the therapeutics system, patient profile and pre-assessment data based on the results of the patient pre-assessment; processing, by the therapeutics system, the patient profile and pre-assessment data to generate patient condition data; processing, by the therapeutics system, the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient wherein the personalized intervention regimen defines a combination of first therapeutic treatment components and second therapeutic treatment components; administering one or more of the first therapeutic treatment components to the patient through the user interface of the therapeutics system according to the personalized intervention regimen generated for the patient; administering one or more of the second therapeutic treatment components to the patient in combination with the one or more first therapeutic treatment components according to the personalized intervention regimen generated for the patient; monitoring the patient’ s interactions with the first therapeutic treatment components and the second therapeutic treatment components to generate
  • DTX for use in the treatment of comorbidities associated with chronic pain disorders
  • a method of treating, preventing, ameliorating, or reducing the likelihood of developing one or more comorbidities associated with a chronic pain disorder in a patient comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic comprises: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the one or more comorbidities are each independently selected from the group consisting of a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, an attention deficit hyperactivity disorder, an obsessive compulsive disorder, a post-traumatic stress disorder, an eating disorder, a substance use disorder, an anhedonia disorder, a cardiovascular disease, a sleep disorder, chronic fatigue, inflammatory bowel syndrome, fibromyalgia, tinnitus, hypertension, asthma, gastroesophageal reflux disease, functional dyspepsia, and combinations thereof.
  • the patient is undergoing or has undergone one or more non-digital therapeutic interventions for said condition.
  • the one or more non-digital therapeutic interventions is provided prior to, contemporaneously with, and/or after administering the digital therapeutic to the patient.
  • the one or more non-digital therapeutic interventions are each independently selected from the group consisting of: treatments utilizing one or more pharmaceutical compositions; treatments utilizing one or more nutraceutical compositions; treatments utilizing one or more medical devices; treatments utilizing one or more physical activities; treatments utilizing one or more mindbody interventions; treatments utilizing whole system medicine; treatments utilizing one or more surgeries; and combinations thereof.
  • the chronic pain disorder is selected from the group consisting of migraine, chronic headache, chronic tension-type headache, chronic low back pain, fibromyalgia, temporomandibular disorder, chronic maxillofacial pain, temporomandibular joint disorder, chronic facial pain, chronic pelvic pain, endometriosis, vulvodynia, vulvar pain, interstitial cystitis, bladder pain syndrome, stress-induced chronic pain, diabetic neuropathic pain, and combinations thereof.
  • the chronic pain disorder is migraine
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, non-steroidal anti-inflammatories, opioids, gepants, ditans, anticonvulsants, beta blockers, barbiturate-containing analgesics, ergot alkaloids, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, ACE inhibitors, angiotensin II receptor (ARBS) antagonists, calcium channel blockers, antidepressants, botulinum toxin, and combinations thereof.
  • CGRP calcitonin gene-related peptide
  • ARBS angiotensin II receptor
  • the chronic pain disorder is migraine
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of Seratonin 5-HT receptor agonists, Triptans, Almotriptan, Eletriptan, Frovatriptan, Naratriptan, Rizatriptan, Sumatriptan, Zolmitriptan, Sumatriptan/Naproxen, Ergotamines, Ditans, including Lasmiditan, Non-opioid analgesics and non-steroidal anti-inflammatories, Acetaminophen, Ibuprofen, Aspirin, Diclofenac, Naproxen, Ketorolac, Opioids/Narcotics, codeine, hydrocodone, oxycodone [hydrochloride], meperidine, morphine, propoxyphene, tramadol, Anti-convulsants, topiramate, di
  • the chronic pain disorder is fibromyalgia
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of anticonvulsants, antidepressants, opioids, muscle relaxants, CNS depressants, and combinations thereof.
  • the chronic pain disorder is fibromyalgia
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of Anticonvulsants, pregabalin, gabapentin, Antidepressants, amitriptyline, cyclobenzaprine, venlafaxine, duloxetine, milnacipran, nortripyline, fluoxetine, paroxetine, citalopram, escitalopram, fluvoxamine, sertraline, Opioids/Narcotics, codeine, hydrocodone, oxycodone [hydrochloride], meperidine, morphine, propoxyphene, tramadol, Muscle relaxants, cyclobenzaprine, tizanidine, diazepam, metaxalone, cyclobenzaprine, carisoprodol, methocarbamol, orphenadrine,
  • the chronic pain disorder is chronic pelvic pain
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of a-blockers, 5-a-reductase inhibitors, opioids, quinolones, tetracyclines, antidepressants, anticonvulsants, non-steroidal anti-inflammatory drugs, muscle relaxants, cannabinoids, progestins, anxiolytics, neuroleptics, calcium channel blockers, botulinum toxin, N- methyl-D-aspartate (NDMA) glutamate receptor antagonists, NGF Inhibitors, and combinations thereof.
  • a-blockers 5-a-reductase inhibitors
  • opioids quinolones, tetracyclines
  • antidepressants anticonvulsants
  • non-steroidal anti-inflammatory drugs muscle relaxants
  • cannabinoids progestins
  • anxiolytics neuroleptics
  • calcium channel blockers botulinum toxin
  • the chronic pain disorder is chronic pelvic pain
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of a-blockers, tamsulosin, alfuzosin, doxazosin, prazosin, terazosin, 5-a-reductase inhibitors, finasteride, dutasteride, Opioids/Narcotics, codeine, hydrocodone, oxycodone [hydrochloride], meperidine, morphine, propoxyphene, tramadol, tapentadol, quinolones/tetracyclines, ciprofloxacin, levofloxacin, Muscle relaxants, cyclobenzaprine, tizanidine, diazepam, metaxalone, cyclobenzaprine, carirsoprodol, methocarbamol,
  • the chronic pain disorder is a temporomandibular disorder
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of non-steroidal anti-inflammatory drugs, corticosteroids, bioactive compounds, isolated compounds, anxiolytics, benzodiazepines, carbamates, barbiturates, barbituratelike hypnotics, opioids, antidepressants, anticonvulsants, 5HT receptor agonists, botulinum toxin, corticosteroids, hyaluronic acid, dietary supplements, celecoxib, cannabis-related drugs, muscle relaxants, and combinations thereof.
  • the chronic pain disorder is a temporomandibular disorder
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of Anti-inflammatories, non-steroidal anti-inflammatories (NSAIDs), meloxicam, feldene, celocoxib, peroxicam, corticosteroids, bioactive compounds, lectins, sulfated polysaccharides (SPs), isolated compounds, terpene, Anxiolytics, benzodiazepines, alprazolam, chlordiazepoxide, clonazepam, diazepam, lorazepam, zolpidem, zaleplon, Carbamates, Glutethimide, Meprobamate, Barbiturates, secobarbital, Barbiturate-like hypnotics, glutethimide, me
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of triptans, non-opioid analgesics, non-steroidal anti-inflammatories, opioids, gepants, ditans, barbiturate-containing analgesics, ergot alkaloids, ergotamines, corticosteroids, calcitonin gene-related peptide (CGRP) receptor antagonists, CGRP monoclonal antibodies, antiemetics, anticonvulsants, antidepressants, a-blockers, 5-a- reductase inhibitors, beta blockers, ACE inhibitors, progestins, angiotensin II receptor antagonists, calcium channel blockers, CNS depressants, quinolones, tetracyclines, serotonin norepinephrine reuptake inhibitors, serotonin reuptake
  • CGRP calcitonin gene-related peptide
  • the chronic pain disorder is migraine
  • the one or more comorbidities are each independently selected from the group consisting of a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, an eating disorder, a substance use disorder, an anhedonia disorder, a chronic fatigue, inflammatory bowel syndrome, tinnitus, gastroesophageal reflux disease, functional dyspepsia, and combinations thereof.
  • the chronic pain disorder is chronic pelvic pain
  • the one or more comorbidities are each independently selected from the group consisting of a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, an eating disorder, a substance use disorder, an anhedonia disorder, a chronic fatigue, inflammatory bowel syndrome, tinnitus, gastroesophageal reflux disease, functional dyspepsia, and combinations thereof.
  • the chronic pain disorder is a temporomandibular disorder
  • the one or more comorbidities are each independently selected from the group consisting of a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, an eating disorder, a substance use disorder, an anhedonia disorder, a chronic fatigue, inflammatory bowel syndrome, tinnitus, gastroesophageal reflux disease, functional dyspepsia, and combinations thereof.
  • the chronic pain disorder is fibromyalgia
  • the one or more comorbidities are each independently selected from the group consisting of a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, an eating disorder, a substance use disorder, an anhedonia disorder, a chronic fatigue, inflammatory bowel syndrome, tinnitus, gastroesophageal reflux disease, functional dyspepsia, and combinations thereof.
  • Tables 2 - 7 below show side effects caused by medications used in the treatment of various disorders, and chronic pain disorder symptoms and side effects that may be treated with the digital therapeutics systems described herein.
  • FIG. 8A, FIG. 8B, FIG. 8C, FIG. 8D, and FIG. 8E depict example schematics of conditional branching architecture implemented for delivery of intervention regimen components, according to one or more embodiments.
  • the intervention-determining model includes architecture for processing input data (e.g., from the pre-assessment and in real-time as the patient interacts with content of the intervention regimen), with a conditional branching model (e.g., with if-then branches coupled to nodes associated with outputs) that processes input data to tailor individual psychological interventions to the patient in an individualized manner.
  • the conditional branching model thus includes decision rules linking characteristics of the patient (e.g., clinical and symptom presentation, demographics, etc.) to different components of the intervention regimen, as an adaptive intervention.
  • FIG. 8A depicts architecture of the conditional branching model for a generalized pathway where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the DTX system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the order of modules can vary from patient to patient. Decisions (within app) about which modules to prioritize first are based on patient’s presentation and needs (e.g., symptom patterns, etc.). For example, if abdominal pain is what is most bothersome to the patient, the digital therapeutic will recommend the pain management module after completing one of the modules (e.g. the relaxation module).
  • the conditional branching model shown in FIG. 8A selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to GI health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the behavioral therapy techniques implemented in the selected intervention can address problem-focused coping tools and/or emotion-focused coping tools, with additional tailoring for different mental health issues associated with the chronic pain or co-morbid condition symptoms of the patient.
  • conditional branching model outputs behavioral activation exercises, cognitive reframing techniques, talent practicing and reinforcement exercises, and/or other exercises to mitigate depression symptoms.
  • conditional branching model outputs exposure-based exercises associated with anxiety sources, anxiety tolerance skill-building exercises, grounding exercises, and/or other exercises to mitigate anxiety symptoms.
  • the conditional branching model outputs problem-solving exercises with respect to controllable vs. uncontrollable stressors, and other exercises to mitigate problem-solving issues.
  • the conditional branching model further receives inputs (e.g., rankings of symptom severity) related to symptoms that the patient wishes to improve (e.g., related to pain management, related to sleep, related to adherence, related to communication, related to social problem solving, related to relapse prevention, etc.), and then based upon the inputs, guides the user through additional cognitive skills tailored to improve symptoms in the manner that the patient desires.
  • inputs e.g., rankings of symptom severity
  • related to symptoms that the patient wishes to improve e.g., related to pain management, related to sleep, related to adherence, related to communication, related to social problem solving, related to relapse prevention, etc.
  • FIG. 8B depicts architecture of the conditional branching model for an anxiety-specific pathway where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the DTX system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to chronic pain health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8B further receives inputs (e.g., rankings of symptom severity) related to sleep and/or other symptoms (e.g., fatigue, sleep hygiene, worry, etc.) that the patient wishes to improve, and then based upon the inputs, guides the user through additional cognitive skills, problem-solving exercises, and behavior change exercises, tailored to improve sleep symptoms related to his/her chronic pain health condition.
  • inputs e.g., rankings of symptom severity
  • other symptoms e.g., fatigue, sleep hygiene, worry, etc.
  • FIG. 8C depicts architecture of the conditional branching model for a depression-specific pathway where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the DTX system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to chronic pain health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8C outputs behavioral activation exercises, cognitive refraining techniques, and reinforcement exercises, and/or other exercises to mitigate depression symptoms.
  • the conditional branching model of FIG. 8C further receives inputs (e.g., rankings of symptom severity) related to sleep and/or other symptoms (e.g., fatigue, sleep hygiene, worry, etc.) that the patient wishes to improve, and then based upon the inputs, guides the user through additional cognitive skills, problem-solving exercises, and behavior change exercises, tailored to improve sleep symptoms related to his/her chronic pain health condition.
  • FIG. 8D depicts architecture of the conditional branching model for a pathway targeted to anxiety and depression (e.g., with a GAD-7 score greater than or equal to 11) where, the model guides (e.g., through an application associated with the DTX system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to chronic pain health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8D outputs exposure-based desensitization exercises associated with anxiety sources, anxiety tolerance skill-building exercises, grounding exercises, and/or other exercises to mitigate anxiety symptoms.
  • the model also determines if the patient is suffering from pain symptoms, and provides the patient with pain management exercises.
  • the model also then sequentially determines if the user is exhibiting symptoms of depression (e.g., if PHQ-9 score is greater than or less than 10), and addresses depression symptoms sequentially relative to other symptoms (e.g., sleep, communication, medication adherence) based upon symptom severity.
  • FIG. 8E depicts architecture of the conditional branching model for a pathway that is not specific to anxiety or depression where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the DTX system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to chronic pain health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8E For a patient having no initial anxiety/depression symptoms, the conditional branching model of FIG. 8E outputs problem-solving exercises with respect to controllable vs. uncontrollable stressors, and other exercises to mitigate problem-solving issues.
  • the conditional branching model of FIG. 8E further receives inputs (e.g., rankings of symptom severity) related to sleep and/or other symptoms (e.g., fatigue, sleep hygiene, worry, etc.) that the patient wishes to improve, and then based upon the inputs, guides the user through additional cognitive skills, problem-solving exercises, and behavior change exercises, tailored to improve sleep symptoms related to his/her chronic pain health condition.
  • inputs e.g., rankings of symptom severity
  • other symptoms e.g., fatigue, sleep hygiene, worry, etc.
  • method flow proceeds to operation 232.
  • operation 232 a set of interactions between the patient and modules of the intervention regimen and a health status progression of the patient are monitored contemporaneously with delivery of the intervention regimen.
  • an embodiment of the online system in coordination with the network and a client device, can monitor a set of interactions between the patient and modules of the intervention regimen and a health status progression of the patient contemporaneously with delivery of the intervention regimen.
  • Monitoring interactions functions to provide intimate understanding of progress of the patient in achieving health goals, and to provide further personalization of and delivery of intervention content at appropriate times, in order to maintain or improve progress of the patient.
  • Monitoring is preferably performed in near-real time or real time, such that actions can be taken to adjust interventions to user states according to just-in time adaptive intervention (IITAI) protocols.
  • IITAI just-in time adaptive intervention
  • monitoring can be performed with any suitable delay (e.g., in relation to achieving better accuracy of assessed states of the patient).
  • Monitoring can be performed using survey components delivered with interactive interventions of the intervention regimen, where the user is prompted and provided with interactive elements that allow the patient to provide self-report data indicating progress statuses. Monitoring can additionally or alternatively be performed with processing of other data streams, where the data streams are associated with system or device usage metrics, social networking behavior extracted from usage of social networking platforms and communication platforms, sensor-derived data, and/or other data. Monitoring can thus occur with any frequency and/or level of intrusiveness.
  • operation 232 can process monitoring data (e.g., real time data, non- real time data, dynamic data, static data) with a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • monitoring data e.g., real time data, non- real time data, dynamic data, static data
  • a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • ecological momentary assessments of the patient can be used for monitoring.
  • client device usage parameters can be used for monitoring. Examples of client device usage parameters can include frequency of application switching, duration of time spent in association with each application login, screen time parameters, data usage associated with different applications and/or types of applications (e.g., social networking, creative, utility, travel, activity-related, etc.) executing on the client device of the patient, time of day of application usage, location of device usage, and other client device usage parameters.
  • the system can process voice data and/or text communication data of the patient for monitoring and modifying interventions and program aspects.
  • voice data can include voice sampling data from which emotional states can be extracted using voice processing models.
  • natural language processing of textual data e.g., from communication platforms, from social networking platforms
  • the client device can be used to provide context for behaviors of the patient and/or assess emotional or cognitive states of the patient.
  • electronic health record data can be used for monitoring.
  • the online system can be configured to receive a notification providing information regarding the type of care the patient has received, and to use this data for monitoring statuses of the patient.
  • the system can include architecture for processing data from other sensors of the client device, devices in the environment of the patient, and/or wearable computing devices can be used for monitoring.
  • device data can include activity data, location data, motion data, biometric data, and/or other data configured to provide context to behaviors associated with the health condition of the patient.
  • motion data from motion of sensors of the client device can indicate that the user is sedentary, and may be experiencing symptoms that can be addressed with components of the intervention regimen.
  • device usage data can indicate that the patient has been using a particular device (e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient), in a fixed location (e.g., from GPS data), and in a prone position (e.g., from motion chip data), and may be experiencing GI health condition symptoms that can be addressed with components of the intervention regimen.
  • a particular device e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient
  • a fixed location e.g., from GPS data
  • a prone position e.g., from motion chip data
  • active monitoring of patient states can be used to adjust delivery of intervention regimen modules in order appropriately meet the needs of the patient.
  • Other data and combinations of data can, however, be used for monitoring.
  • process flow proceeds to operation 234.
  • operation 234 in response to at least one of the set of interactions and the health status progression, an action configured to improve wellbeing of the patient with respect to the chronic pain health condition is performed.
  • an embodiment of the online system in coordination with the network and a client device can, in response to at least one of the set of interactions and the health status progression, perform an action configured to improve health and wellbeing of the patient with respect to the chronic pain health condition.
  • Operation 234 functions to provide further customization of the intervention regimen, in order to improve personalization of delivered content to needs of the patient, in an adaptive manner.
  • Operation 234 can also function to increase engagement between the patient and the intervention regimen, in order to improve effectiveness of provided treatments and increase success of the patient in achieving his/her goals.
  • the action performed according to operation 234 can include one or more of: adjusting order of and/or content of intervention modules provided, where intervention types and content are described above; updating electronic health records (EHRs), personal health records (PHRs), and/or open medical records, for instance by writing to or modifying records whenever new information is generated regarding the user/patient/patient; providing and/or facilitating provision of supplemental interventions (e.g., hypnotherapy, physical exercises, medications, supplements, etc.) beyond standard content of the intervention regimen, for instance, under physician-guidance or treatment recommendations; generating and/or providing notifications to the patient regarding changes in behavior or health statuses; generating and/or providing notifications to entities (e.g., relatives, acquaintances having permission of the patient, health care providers, etc.) associated with the patient regarding changes in behavior or health statuses; and/or any other suitable action.
  • operation 234 can additionally or alternatively include functionality for increasing engagement of the patient with respect to interactions with content of the intervention regimen
  • features for increasing engagement and optimal learning can include text-based functionality for self-monitoring and symptom tracking, where the system can process real time text interactions with provision of interactive tasks, which increases likelihood of patient responses.
  • specific descriptions self-reported by the patient can be used in subsequent portions of the intervention regimen to increase personalization of the intervention to drive engagement.
  • features for increasing engagement and optimal learning can include features that mimic therapist/healthcare provider, or social group interactions (e.g., patient testimonials, clinician video content, etc.).
  • features for increasing engagement and optimal learning can include features that link the patient’ s specific current problems (e.g., from operation 232) and/or challenges faced by the patient as a trigger to notify the patient to interact with content of the intervention regimen and recommend appropriate skill for improving health states.
  • engagement can be promoted using one or more of: artificial reality tools (e.g., augmented reality platforms, virtual reality platforms) for reducing depression, anxiety, pain, and/or other symptoms; artificial intelligence-based coaching elements for driving interactions with the patient; smart assistants (e.g., AlexaTM, SiriTM, GoogleTM Assistant, etc.) for assisting the patient in relation to task management, gamification elements within intervention regimen-associated applications executing on the client device; gamification elements of other devices (e.g., smart toilet devices having interactive elements, such as buttons that control flushing and other subsystems, for promoting triggering of stool sample tracking in relation to various symptoms); smart pill devices and/or medication-dispensing devices that provide insights in an engaging manner in coordination with intervention regimen modules; adjustment of reinforcement schedules (e.g., in relation to reward sensitivity, positive reinforcement, negative reinforcement, etc.) for providing intervention regimen content to the patient; and other elements for increasing engagement.
  • artificial reality tools e.g., augmented reality platforms, virtual reality platforms
  • artificial intelligence-based coaching elements for driving
  • features for personalization and promoting engagement can be delivered within modules of the intervention regimen before and/or after monitoring of the patient according to operation 232.
  • method flow proceeds to END operation 236, and the method 200B for providing adaptive interventions for chronic pain health conditions is exited to await new instructions
  • FIG. 2C is a flowchart depicting a method 200C for providing adaptive interventions for chronic pain health conditions, in accordance with one embodiment.
  • method 200C begins at BEGIN 238, and method flow proceeds to operation 240.
  • operation 240 an interface between a device and a user is established.
  • method flow proceeds to operation 242.
  • a set of signals associated with a chronic pain or co-morbid condition of the user is received from the interface, wherein the set of signals encodes physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user.
  • a characterization of the chronic pain health condition is determined upon processing the set of signals with a model.
  • method flow proceeds to operation 246.
  • content of a treatment comprising a set of components is modulated, wherein the set of components comprises a subset of cognitive behavioral therapy (CBT) components for improving a state of the user.
  • CBT cognitive behavioral therapy
  • method flow proceeds to operation 248.
  • the treatment is administered to the user.
  • method flow proceeds to END operation 250, and the method 200C for providing adaptive interventions for chronic pain health conditions is exited to await new instructions ADDITIONAL METHOD ASPECTS
  • the methods 200A, 200B, and/or 200C can further include operations for detecting performance of activities associated with the intervention regimen, by the patient; reinforcing user performance or engagement with the intervention regimen; determining undesired levels of performance or engagement with the intervention regimen; and driving improved engagement with the intervention.
  • the methods 200A, 200B, and/or 200C can include functionality for detecting performance or non-performance of activities (e.g., based on system engagement, based upon sensor-detected measures of activity, etc.).
  • the methods 200A, 200B, and/or 200C can include functionality for reinforcing performance through provision of various rewards (e.g., rests, rewards of monetary value, etc.). If the patient does not perform activities appropriately, the methods 200A, 200B, and/or 200C can include functionality for determining causes of non-performance (e.g., nonengaging content, external factors associated with the patient’s life, etc.) and adjust content delivery, provide modified interventions, and/or adjust reinforcement schedules accordingly.
  • causes of non-performance e.g., nonengaging content, external factors associated with the patient’s life, etc.
  • the methods 200A, 200B, and/or 200C can include functionality for developing and training predictive models for predicting states of the patient during the course of the intervention regimen, in order to improve chances of success in outcomes.
  • the methods 200A, 200B, and/or 200C can thus include functionality for aggregation of training datasets from various data sources described above, and processing training datasets with one or more types of model architecture in order to improve predictions and/or selection of appropriate modules of the intervention regimen for delivery to the patient.
  • Models associated with the methods 200A, 200B, and/or 200C can be defined within architecture of computing systems described above, and include elements for statistical analysis of data and/or machine learning.
  • input to a machine learning module comprises one or more textual words, phrases, or lengthier strings.
  • the input comprises various data elements, such as numerical values corresponding to user responses to a series of questions in a questionnaire (e.g., ranking various symptom severities on a scale).
  • one or more output values of a machine learning module comprise values representing a classification of a particular condition of a user.
  • machine learning modules implementing machine learning techniques are trained, for example using curated and/or manually annotated datasets. Such training may be used to determine various parameters of machine learning algorithms implemented by a machine learning module, such as weights associated with layers in neural networks.
  • machine learning module may receive feedback, e.g., based on user review of accuracy, and such feedback may be used as additional training data, for example to dynamically update the machine learning module.
  • a trained machine learning module is a classification algorithm with adjustable and/or fixed (e.g., locked) parameters, e.g., a random forest classifier.
  • two or more machine learning modules may be combined and implemented as a single module and/or a single software application.
  • two or more machine learning modules may also be implemented separately, e.g., as separate modules or applications.
  • a machine learning module may be software and/or hardware.
  • a machine learning module may be implemented entirely as software, or certain functions of a ANN module may be carried out via specialized hardware (e.g., via an application specific integrated circuit (ASIC)).
  • ASIC application specific integrated circuit
  • the method can include: generating a combined dataset upon applying a first set of transformations to an aggregate dataset including physiological data, behavioral data, environmental stress data, emotional data, and cognitive data from a set of users exhibiting a form of the chronic pain health condition; collecting a treatment dataset comprising treatment outcome labels (e.g., quantitative or qualitative labels describing efficacy of individual treatment components) associated with the subset of behavioral therapy components applied to the set of users; creating a first training dataset comprising the combined dataset and the treatment dataset; and training the model with the first training dataset.
  • treatment outcome labels e.g., quantitative or qualitative labels describing efficacy of individual treatment components
  • the model can be structured and ultimately refined for receiving data objects associated with at least one of: physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user, and returning a set of outputs comprising a selection of treatment subcomponents tagged with efficacy indicators.
  • Statistical analyses and/or machine learning algorithm(s) can be characterized by a learning style including any one or more of: supervised learning (e.g., using back propagation neural networks), unsupervised learning (e.g., K-means clustering), semi-supervised learning, reinforcement learning (e.g., using a Q-learning algorithm, using temporal difference learning, etc.), and any other suitable learning style.
  • supervised learning e.g., using back propagation neural networks
  • unsupervised learning e.g., K-means clustering
  • semi-supervised learning e.g., reinforcement learning (e.g., using a Q-learning algorithm, using temporal difference learning, etc.), and any other suitable learning style.
  • any algorithm(s) can implement any one or more of: a regression algorithm, an instance-based method (e.g., k-nearest neighbor, learning vector quantization, self-organizing map, etc ), a regularization method, a decision tree learning method (e.g., classification and regression tree, chi-squared approach, random forest approach, multivariate adaptive approach, gradient boosting machine approach, etc.), a Bayesian method (e.g., naive Bayes, Bayesian belief network, etc.), a kernel method (e.g., a support vector machine, a linear discriminate analysis, etc.), a clustering method (e.g., k-means clustering), an associated rule learning algorithm (e.g., an Apriori algorithm), an artificial neural network model (e.g., a back-propagation method, a Hopfield network method, a learning vector quantization method, etc.), a deep learning algorithm (e.g., a Boltzmann machine, a Boltzmann
  • FIG. 9 A, FIG. 9B, FIG. 9C, FIG. 9D, FIG. 9E, FIG. 9F, FIG. 9G and FIG. 9H are screenshots of several portions of an exemplary GUI for a system for treating chronic pain conditions using digital therapeutics, according to one or more embodiments.
  • Screenshots in FIG. 9A, FIG. 9B, and FIG. 9C show a GUI sharing content about measuring the impact of pain, corresponding to a starting point for a user that has just begun to use the system.
  • FIG. 9A shows a home screen 901 that provides user access to an initial, first, lesson module.
  • a selectable icon 902 representing the initial lesson module may be displayed, which a user may select to begin.
  • FIG. 9B shows another screen of a GUI 903 explaining aspects of the program to the user, and allowing the user to progress through the lesson by selecting the ‘next’ button 904.
  • assessments are built into the program to identify how pain impacts the user’ s everyday life.
  • the screen of a GUI 905 explains that the impact of pain will be measured using self-reported metrics on the user’s ability to cope with pain, its emotional impact on the user, and how much pain affect the user’s quality of life.
  • a user may initiate a pain assessment by selecting the ‘start’ button 906.
  • FIG. 9D shows another screen of a GUI 907 explaining aspects of the program to the user, and allowing the user to progress through the lesson and see the results of its pain assessment by selecting the ‘next’ button 908.
  • FIG. 9E, FIG. 9F and FIG. 9G each show a screen of a GUI (909, 911 and 913, respectively) with different examples of scores from pain assessments, with scores of 10, 56 and 105, respectively, along with corresponding information for the user.
  • a user may proceed to the next screen by selecting the ‘next’ button 910, 912 or 914, respectively.
  • the GUI may present the assessment score, either each metric separately or as a combined score.
  • FIG. 9E, FIG. 9F and FIG. 9G each provide context for why participating in pain assessments during the course of the treatment are valuable.
  • a combined score (three different examples provided in these figures) may be presented along with context on how that score relates to the user’s current pain impact.
  • the user’s score may be compared to their initial pain assessment or pain assessment data for others with the same or similar health conditions.
  • the user’s data may be tracked over time to identify triggers, show progress of treatment, demonstrate impact of concomitant therapies, or provide emotional support.
  • FIG. 9H demonstrates a GUI 915 presenting emotional support and summarizing pain management techniques and psychoeducation intended to encourage the user to focus on problem-solving; then, a user may exit this lesson by selecting the ‘done’ button 916.
  • FIG. 10A, FIG. 10B, FIG. 10C, and FIG. 10D are screenshots of example user interactions with an initial lesson module for communicating with your partner about sexual functioning and pain support, according to one or more embodiments.
  • FIG. 10A a user may select icon 1002 on a GUI 1001 to explore communication strategies for exploring sexual functioning between a chronic pain patient and their sexual partner.
  • FIG. 10B provides an exemplary GUI 1003 with tips on how to save the content, and allowing a user to progress to the next screen by selecting the ‘next’ button 1004.
  • a user in an active sexual relationship can step through conversation guides 1005 and 1007, respectively, on communicating on sexual functioning and redefining intimacy.
  • a user may progress to the next screen by selecting the ‘next’ button 1006 and 1008, respectively.
  • FIG. 11A shows an interactive GUI 1101, according to one or more embodiments, allowing the user to select behavioral aspects of their pain journey.
  • a user may select icons 1101 A, 1101B and/or 1101C representing multiple common behavioral responses to pain that the user has learned about in earlier modules.
  • FIG. 11B, FIG. 11C, FIG. HD, and FIG. HE in some embodiments, a user may step through content of a lesson module by tapping selectable graphical buttons (here, each is labeled ‘next’) until they have viewed all screens (1102, 1103, 1104, 1105, and 1106) comprising all graphical content and widgets of the lesson module associated with the items selected in FIG.l 1A.
  • the user may also enter free text in space 110 ID.
  • a user may be presented with a final screen 1107 that provides an indication that they have completed a particular lesson module.
  • FIG. 11G is a screen 1107 showing gate features of an exemplary GUI for a system for treating chronic pain conditions using digital therapeutics, in accordance with one or more embodiments.
  • the user may select a graphical button 1008 to confirm completion of the particular lesson module.
  • progression onto a next lesson module is not necessarily instantaneous and/or direct. Instead, as described above, gate features may be used to introduce friction and/or to control a rate of progression from one lesson module to a next.
  • a soft-gate is used, wherein a user is not fully prevented from beginning a second lesson module, but is encouraged to delay moving on, and required to provide additional input to do so.
  • An inter-lesson gate screen may include graphical content prompting the user to delay progressing onto the second lesson until the next day.
  • a soft-gate is based on time-relationship criteria with respect to a user’s time of completion of the first lesson module.
  • a soft-gate is used to encourage a user to wait to begin the next lesson module.
  • gates may be used to encourage user practice of particular behavioral skills.
  • an inter-lesson gate screen may not allow for continued user progression onto the next lesson module (hard gate).
  • the hard gate may include graphical content that encourages the user to take a break and practice particular behavioral skills via a practice module.
  • a gate is a graphical widget - e.g., a selectable graphical button. Accordingly, in some embodiments, a gate provides a link to a particular practice module, such that user selection of the graphical icon causes initiation (e.g., display) of a particular practice module to which it links (e.g., a symptom diary practice module or other practice modules).
  • an inter-lesson gate screen may comprise a graphical widget that returns a user to a home screen.
  • inter-lesson gate screen 1007 comprises the message “That’s it for now” and a graphical widget 1108, displaying text “Done,” whereupon a user selection of graphical widget 1108, they are returned to a home screen.
  • FIG. 12A, FIG. 12B, FIG. 12C, FIG. 12D and FIG. 12E are screenshots (1201, 1202, 1203, 1204 and 1205, respectively) of an exemplary GUI for a symptom diary lesson module, according to one or more embodiments.
  • a sequence of interactive lesson modules may include a symptom diary lesson module that introduces and familiarizes a user with techniques for tracking their chronic pain or co-morbid condition symptoms and/or medication side effects.
  • technologies described herein provide a convenient GUI that can (e.g., be demonstrated and/or designed to) facilitate user tracking and/or monitoring of their chronic pain or co-morbid condition symptoms and/or medication side effects on a regular basis.
  • a tracking GUI may be included within a same system that provides, and controls user progression through interactive lesson modules, for example as a symptom diary practice module associated with a symptom diary lesson module.
  • access to a symptom diary practice module may be unlocked by clicking on a widget to open a symptom diary lesson module by the user, for example, as shown in FIG. 12A.
  • a selectable icon 1205 A representing, and providing access to, the symptom diary practice module may be displayed on a user home-screen.
  • FIG. 13A, FIG. 13B, FIG. 13C, FIG. 13D, FIG. 13E, FIG. 13F, FIG. 13G, FIG. 13H, FIG. 131, FIG. 13J and FIG. 13K are screenshots (1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310 and 1311, respectively) of example user interactions with a symptom diary practice module, in accordance with one or more embodiments.
  • a symptom diary practice module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the introduction and education module discussed above.
  • a user may use graphical widgets to provide input associated with one or more aspects of their disease, disorder, and/or condition.
  • patient input include, but are not limited to, rating patterns between pain and stress (FIG. 13C, FIG. 13D, FIG. 13E), patterns between daily activities and pain (FIG. 13F), providing information characterizing their daily triggers (FIG. 13G) and impact on daily life (FIG. 13H, FIG. 131, FIG. 13J, and FIG. 13K).
  • FIG. 14A, FIG. 14B, FIG. 14C, FIG. 14D and FIG. 14E are screenshots (1401, 1402, 1403, 1404 and 1405, respectively) of an exemplary GUI for introducing a personal model lesson module, in accordance with one or more embodiments.
  • a personal model lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the thoughts, behaviors and emotions narrative module discussed above.
  • a sequence of interactive lesson modules includes a personal model lesson module that allows a user to identify cycles of behaviors, thoughts, emotions, and stressors that influence symptoms associated with their particular condition (e.g., from which they are suffering).
  • a personal model lesson module is used to implement, via a GUI, a structured process for conveniently soliciting user input of specific counter-productive behaviors, unhelpful thoughts, and negative emotions that they identify, e.g., in their life and/or as associated with their particular condition.
  • a particular condition from which the user is suffering is a chronic pain condition, such as, but not limited to, migraine, chronic headache, fibromyalgia, chronic pelvic pain, endometriosis, vulvar pain, vulvodynia, interstitial cystitis, bladder pain syndrome.
  • a chronic pain condition such as, but not limited to, migraine, chronic headache, fibromyalgia, chronic pelvic pain, endometriosis, vulvar pain, vulvodynia, interstitial cystitis, bladder pain syndrome.
  • a personal model lesson module prior to soliciting user input and creating a user’ s own personal model, introduces a user to other examples of a personal model, for example so as to orient them and provide content designed to offer helpful motivation.
  • the user can select among different buttons (1405 A, 1405B) to see two exemplary personal models.
  • buttons 1405 A, 1405B
  • graphical content representing educational material is displayed to a user, for example to introduce them to concept of vicious cycles, and explain how symptoms, stress, and pain can create a feedback loop.
  • graphical content corresponding to shared user experiences and/or testimonials is displayed. For example, as shown in FIG. 14C, a user may be prompted to read about another user’s experiences with their chronic pain condition and guided behavioral therapy approaches such as those described herein.
  • a user may view exemplary personal models created by and shared by others.
  • Other lesson modules for example any lesson modules described herein and/or additional lesson modules, providing for development of other behavioral therapy skills provided via the technologies described herein may also include content comprising patient experiences and/or testimonials.
  • FIG. 15 A, FIG. 15B, FIG. 15C, FIG. 15D, FIG. 15E, FIG. 15F, FIG. 15G, FIG. 15H, FIG. 151, FIG. 15J and FIG. 15K are screenshots (1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510 and 1511, respectively) of an exemplary GUI for a personal model lesson module, according to one or more embodiments.
  • a personal model lesson module may be a standalone module, or it may be part of a different module, such as, but not limited to, the physical illness narrative module discussed above.
  • a personal model lesson module may retrieve stored information, previously input by a user. For example, in various embodiments, a user may have previously provided input identifying causes and/or stressors that impact their particular chronic pain condition, and previously input user identifications of causes and stressors that impact the user’s chronic pain condition may be retrieved and displayed. In some embodiments, a user provides input corresponding to causes and/or stressors associated with their particular chronic pain condition via a personal model lesson module. In some embodiments, a user may be provided with a graphical list of selectable elements.
  • the user is prompted to select a pre-defined number of counterproductive behaviors (1502A, 1502B, 1502C, 1502D, 1502E, 1502F, 1502G, 1502H), as shown in FIG. 15B.
  • a user may provide free-form textual input, for example via a text box 15021.
  • the user is prompted to select one or more unhelpful thoughts related to the counter-productive behavior (1504A, 1504B, 1504C, 1504D, 1504E).
  • unhelpful thoughts are selected from a list of pre-defined thoughts.
  • a user may provide free-form textual input, for example via a text box 1504F.
  • a user following a user selection of one or more unhelpful thoughts, as shown in FIG. 15F, a user is prompted to select one or more negative emotions.
  • negative emotions are selected from a list of pre-defined emotions (1506A, 1506B, 1506C, 1506D, 1506E, 1506F, 1506G, 1506H, 15061).
  • a user may provide free-form textual input, for example via a text box 1506J.
  • FIG. 16 is a screenshot 1601 of an exemplary personal model graphical representation, according to one or more embodiments.
  • a personal model graphical representation comprises text corresponding to user selected counterproductive behavior(s), unhelpful thought(s), and negative emotion(s), superimposed on a flow diagram illustrating links between each other, as shown in FIG. 16.
  • a personal model graphical representation comprises text corresponding to causes and/or stressors of symptoms, previously input by the user and retrieved via the personal model lesson module and/or input within the personal model lesson module, as described herein.
  • a personal model graphical representation is rendered to have a form factor fitting one or more mobile device screens.
  • a personal model graphical representation can be rendered in a narrow, rectangular format, allowing a user to scroll through the rendered diagram to view its content.
  • a personal model graphical representation can be displayed as a zoom-able diagram, such that a user may zoom in and out to view portions of the diagram.
  • a personal model graphical representation can be displayed so as to allow a user to navigate through its content by panning, for example in a two-dimensional fashion.
  • FIG. 17A, FIG. 17B, FIG. 17C, FIG. 17D, FIG. 17E, FIG. 17F, FIG. 17G, FIG. 17H and FIG. 171 are screenshots (1701, 1702, 1703, 1704, 1705, 1706, 1707, 1708 and 1709, respectively) of an exemplary GUI for a reflections section of a personal model lesson module, according to one or more embodiments.
  • a personal model lesson module includes graphical content prompting a user to review their personal model.
  • a series of questions e.g., from a predefined list of questions, e.g., based on a therapeutic protocol
  • a series of questions are displayed and presented to the user along with their personal model graphical representation, prompting the user to consider their selections, identify links, consider possible changes in their behavior that could be implemented to address their symptoms, and the like.
  • FIG. 17C and FIG. 17D a sequence of user questions are presented.
  • FIG. 17E, FIG. 17F, FIG. 17G, FIG. 17H, FIG. 171, FIG. 17J and FIG. 17K graphical content, including passages of rendered text, mimicking conversation with a therapist can be displayed.
  • encouraging graphical content is displayed, and the user is returned to a home screen.
  • FIG. 18 A, FIG. 18B, FIG. 18C, FIG. 18D, FIG. 18E, FIG. 18F, FIG. 18G, FIG. 18H and FIG. 181 are screenshots (1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808 and 1809, respectively) of an exemplary GUI for a pain management lesson module, according to one or more embodiments.
  • a symptom management lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the pain management module discussed above.
  • FIG. 18 A, FIG. 18B, FIG. 18C, FIG. 18D, FIG. 18E, FIG. 18F, FIG. 18G, FIG. 18H and FIG. 181 show an example symptom (pain) management lesson module and an associated symptom management goals practice module.
  • a symptom management goals practice module can be unlocked and made accessible to the user, as shown in FIG. 18A, FIG. 18B and FIG. 18C.
  • a user may access a symptom management strategy module to create goals to manage their chronic pain condition symptoms.
  • a user may, e.g., regularly, use a goals module to set goals such as practicing pain management strategies consistently, incorporating rest activities between pain management tools (e.g., pacing), prioritize pain management goals and get needed rest.
  • a goals module may provide for setting goals pertaining to medication adherence.
  • the user can opt to take a break from the digital therapeutic system or return to complete the days’ scheduled activities.
  • FIG. 19A, FIG. 19B, FIG. 19C, FIG 19D, FIG. 19E, FIG. 19F, FIG 19G, FIG. 19H, FIG. 191, FIG. 19J, FIG. 19K and FIG. 19L are screenshots (1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911 and 1912, respectively) of an exemplary GUI for physical therapy module for a chronic pelvic pain (including vulvar/vaginal pain and vulvodynia) management lesson module, according to one or more embodiments.
  • a physical therapy lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the pain management module discussed above.
  • FIG. 19A, FIG. 19B, FIG. 19C, FIG. 19D, FIG. 19E, FIG. 19F, FIG. W and FIG. 19H show an example physical therapy lesson module (pelvic floor exercises) and an associated activity practice module.
  • a physical therapy module upon user completion of pain assessment module, can be unlocked and made accessible to the user.
  • a user may choose certain behavioral or physical therapy options to focus their chronic pain management treatment.
  • FIG. 20 A, FIG. 20B, FIG. 20C and FIG. 20D are screenshots (2001, 2002, 2003 and 2004, respectively) of an exemplary GUI for a symptom (pain) management lesson module and an associated symptom management goals practice module.
  • a symptom management goals practice module can be unlocked and made accessible to the user, as shown in FIG. 20A, FIG. 20B and FIG. 20C.
  • FIG. 20D in some embodiments, as shown in FIG. 20D, the user can return to symptom management routines in the Toolkit section of the DTX system.
  • completed sessions may be indicated visually to a user.
  • completion of certain lesson modules unlocks various associated practice modules, which are then made accessible to the user via a screen of a GUI.
  • completion of lesson modules may cause population of portions of a user profile, which a user may review via a GUI.
  • completion of a user personal model module as described herein provides for creation of a personal model that identifies a particular user’s individual vicious cycle of related stressors, behaviors, emotions, and thoughts.
  • the data corresponding to a previously created personal model is stored and may be rendered for review and reflection by a user, via a profile screen.
  • interactive lesson modules, associated practice modules, user profile content, and the like may include a variety of other lesson modules, additionally or alternatively to those described herein.
  • various lesson modules and content thereof as described herein may be combined with other content, for example from other lesson modules described herein.
  • embodiments of the present disclosure provide a technical solution to the technical problem of effectively, efficiently, and remotely treating chronic pain health conditions using digital therapeutics in combination with other therapies in order to ensure that patients receive adequate care, support, and treatment for their chronic pain health condition.
  • the inventions covered by the system and method disclosed herein can confer several benefits over conventional systems and methods, and such inventions are further implemented into many practical applications related to improvement of user health and management of chronic pain.
  • a computing system implemented method for treating chronic pain health conditions using prescription digital therapeutics in combination with other therapies comprises: providing a patient with a user interface to a therapeutics system; performing, by the therapeutics system, a pre-assessment of a patient exhibiting one or more health condition symptoms; generating, by the therapeutics system, patient profile and pre-assessment data based on the results of the patient pre-assessment; processing, by the therapeutics system, the patient profile and pre-assessment data to generate patient condition data; and processing, by the therapeutics system, the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient wherein the personalized intervention regimen defines a combination of first therapeutic treatment components and second therapeutic treatment components.
  • the computing system implemented method further comprises administering one or more of the first therapeutic treatment components to the patient through the user interface of the therapeutics system according to the personalized intervention regimen generated for the patient; administering one or more of the second therapeutic treatment components to the patient in combination with the one or more first therapeutic treatment components according to the personalized intervention regimen generated for the patient; monitoring the patient’ s interactions with the first therapeutic treatment components and the second therapeutic treatment components to generate patient interaction data representing the patient’s interactions with the first and second therapeutic treatment components; processing, by the therapeutics system, the patient interaction data to generate intervention modification data representing recommended modifications to the patient’s personalized intervention regimen; at least partly based on the intervention modification data, dynamically modifying aspects of the patient’s personalized intervention regimen to generate a modified personalized intervention regimen for the patient; and administering one or more of the first therapeutic treatment components in combination with one or more of the second therapeutic treatment components according to the modified personalized intervention regimen for the patient.
  • the therapeutics system is a prescription digital therapeutics (PDT) system.
  • the patient health condition symptoms are associated with one or more of: a chronic pain condition; and a co-morbid condition.
  • performing a pre-assessment of a patient includes utilizing surveying tools derived from one or more patient reported outcome instruments selected from the group of patient reported outcome instruments consisting of: a Numbered Pain Scale (NPS); a Numbered Rating Scale (NRS); a Verbal Rating Scale (VRS); a Visual Analog Scale (VAS); a Categorical Scale; a Quantitative Scale; a Qualitative Scale; a COMFORT Scale; a McGill Pain Questionnaire; a Mankoski Pain Scale; a Brief Pain Inventory (BPI); a Descriptor Differential Scale of Pain Intensity (DDS-I) a Universal Pain Assessment Tool (UP AT); an IMMPACT evaluation; Multidimensional Pain Inventory (MPI); Global Impression of Change Scale; other psychometric testing; a GAD-7 anxiety disorder questionnaire; a Beck Depression Inventory; a profile of mood states; a pain assessment questionnaire.
  • the user enters data on a Numbered Pain Scale (NP
  • performing a pre-assessment of a patient includes utilizing non-survey data obtained from one or more devices selected from the group of devices consisting of: electronic health record-associated devices; torso-coupled devices, wearable devices; ingestible devices; implanted devices; smart-pill devices; medication tracking and/or delivery devices; location or activity monitoring devices; and social networking tracking devices.
  • devices selected from the group of devices consisting of: electronic health record-associated devices; torso-coupled devices, wearable devices; ingestible devices; implanted devices; smart-pill devices; medication tracking and/or delivery devices; location or activity monitoring devices; and social networking tracking devices.
  • generating the patient profile and pre-assessment data includes obtaining one or more of: patient demographics data; patient electronic health record data; patient physiological health data; patient psychological health data; patient condition data; patient pain data, patient symptoms data; patient medications data; patient illness narrative data; patient goals data; and patient preferences data.
  • generating the patient condition data includes of one or more of: identifying the patient’s condition as a chronic pain condition; identifying a co-morbid condition; identifying symptoms of the patient’s chronic pain and/or co-morbid condition; identifying a severity of the patient’s pain and other symptoms of the chronic pain and/or co-morbid condition(s); identifying the patient’s medication for the chronic pain and/or co-morbid condition(s); identifying the patient’s side effects from medication; identifying the patient’s dosage information for medications; and identifying a severity of the patient’s medication side effects.
  • generating a personalized intervention regimen includes one or more of: processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to determine a first therapeutic treatment to be administered to the patient; defining a first plurality of therapeutic components associated with the first therapeutic treatment; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the first plurality of therapeutic components to be administered to the patient; generating first therapeutic treatment component data representing the selected one or more of the first plurality of therapeutic components; defining a first plurality of therapeutic protocols to be utilized in administration of the components represented by the first therapeutic treatment component data; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the first plurality of therapeutic protocols to utilize in administration of the components represented by the first therapeutic treatment component data; and generating first therapeutic treatment protocol data representing the selected one or more of the first plurality of therapeutic protocols to utilize in administration of the components represented by the first
  • generating a personalized intervention regimen further includes one or more of: processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to determine a second therapeutic treatment to be administered to the patient in combination with the first therapeutic treatment; defining a second plurality of therapeutic components associated with the second therapeutic treatment; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the second plurality of therapeutic components to be administered to the patient; generating second therapeutic treatment component data representing the selected one or more of the second plurality of therapeutic components; defining a second plurality of therapeutic protocols to be utilized in administration of the components represented by the second therapeutic treatment component data; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the second plurality of therapeutic protocols to utilize in administration of the components represented by the second therapeutic treatment component data; and generating second therapeutic treatment protocol data representing the selected one or more of the second plurality of therapeutic protocols to utilize in
  • generating a personalized intervention regimen further includes one or more of: generating, by the therapeutics system, a personalized intervention regimen for the patient, wherein the personalized intervention regimen for the patient defines the first therapeutic treatment component data to be administered to the patient according to the first therapeutic treatment protocol data in combination with the second therapeutic treatment component data to be administered to the patient according to the second therapeutic treatment protocol data.
  • the first therapeutic treatment is a guided behavioral therapeutic treatment, further wherein the guided behavioral therapeutic treatment is administered remotely through a user interface of the therapeutics system.
  • the guided behavioral therapeutic treatment includes components of therapies selected from the group of therapies consisting of: psychotherapy; cognitive behavioral therapy (CBT); education and communication/assertiveness training around sexual functioning and alternative intimacy techniques (SFT); acceptance and commitment (ACT) therapy; pelvic floor physical therapy; pelvic floor relaxation therapy; dialectical behavioral therapy (DBT); exposure therapy; mindfulness-based cognitive therapy (MCBT); somatic anchoring therapy, hypnotherapy; experiential therapy; and psychodynamic therapy.
  • therapies selected from the group of therapies consisting of: psychotherapy; cognitive behavioral therapy (CBT); education and communication/assertiveness training around sexual functioning and alternative intimacy techniques (SFT); acceptance and commitment (ACT) therapy; pelvic floor physical therapy; pelvic floor relaxation therapy; dialectical behavioral therapy (DBT); exposure therapy; mindfulness-based cognitive therapy (MCBT); somatic anchoring therapy, hypnotherapy; experiential therapy; and psychodynamic therapy.
  • the second type of therapeutic treatment is a non-behavioral therapeutic treatment including components of non-behavioral therapeutic treatments selected from the group of non-behavioral therapeutic treatments consisting of: treatments utilizing one or more pharmaceutical compositions; treatments utilizing one or more nutraceutical compositions; treatments utilizing one or more medical devices; treatments utilizing one or more physical activities; treatments utilizing one or more mind-body interventions; and treatments utilizing whole system medicine.
  • monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components includes utilizing surveying tools derived from one or more patient reported outcome instruments selected from the group of patient reported outcome instruments consisting of: a Numbered Pain Scale (NPS); a Numbered Rating Scale (NRS); a Verbal Rating Scale (VRS); a Visual Analog Scale (VAS); a Categorical Scale; a Quantitative Scale; a Qualitative Scale; a COMFORT Scale; a McGill Pain Questionnaire; a Mankoski Pain Scale; a Brief Pain Inventory (BPI); a Descriptor Differential Scale of Pain Intensity (DDS-I) a Universal Pain Assessment Tool (UP AT); an IMMPACT evaluation; Multidimensional Pain Inventory (MPI); Global Impression of Change Scale; other psychometric testing; a GAD-7 anxiety disorder questionnaire; a Beck Depression Inventory; a profile of mood states; a pain assessment questionnaire.
  • NPS Numbered Pain Scale
  • monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components includes utilizing non-survey data obtained from one or more devices selected from the group of devices consisting of: electronic health record-associated devices; torso-coupled devices; wearable devices; ingestible devices; implanted devices; smart-pill devices; medication tracking and/or delivery devices; location and/or activity monitoring devices; and social networking tracking devices.
  • devices selected from the group of devices consisting of: electronic health record-associated devices; torso-coupled devices; wearable devices; ingestible devices; implanted devices; smart-pill devices; medication tracking and/or delivery devices; location and/or activity monitoring devices; and social networking tracking devices.
  • monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components includes obtaining patient data including one or more of: patient physiological health data; patient psychological health data; patient condition data; patient symptoms data; patient pain data, patient medications data; patient medication adherence data; patient progress report data; patient system usage data; patient device usage data; patient social networking behavior data; patient voice data; patient textual data; patient activity data; patient location data; patient motion data; and patient biometric data.
  • the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components are monitored remotely, in near-real time, contemporaneously with administration of one or more of: the first therapeutic treatment; and the second therapeutic treatment.
  • a request for approval of the intervention modification data is communicated remotely to one or more of: a health care practitioner associated with the patient; the patient; a relative of the patient; a caregiver of the patient; and a third party associated with the patient.
  • dynamically modifying aspects the patient’s personalized intervention regimen includes one or more of: adjusting the order of administration of the behavioral therapy components; adjusting the order of administration of the non-behavioral therapy components; adjusting the frequency of administration of the behavioral therapy components; adjusting the frequency of administration of the non-behavioral therapy components; adjusting the mode of administration of the behavioral therapy components; adjusting the mode of administration of the non-behavioral therapy components; adjusting the content of the behavioral therapy components; adjusting the content of the non-behavioral therapy components; adjusting the content size of the behavioral therapy components; adjusting the dosage of the non-behavioral therapy components; adjusting the presentation of the behavioral therapy components; adjusting the layout of the behavioral therapy components; updating the patient’s electronic health records; updating the patient’s personal health records; updating the patient’s open medical records; and increasing personalization of the intervention regimen.
  • the patient’s personalized intervention regimen is modified remotely, in near-real time, contemporaneously with administration of one or more of: the first therapeutic treatment; and the second therapeutic treatment.
  • a method for providing a digital therapeutics (DTX) system for remotely administering guided behavioral therapy in combination with other types of chronic pain conditions comprises: providing a patient with a therapeutics system; performing a pre-assessment of a patient exhibiting one or more health condition symptoms; generating patient profile and pre-assessment data based on the results of the patient pre-assessment; processing the patient profile and pre-assessment data to generate patient condition data; processing the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient wherein the personalized intervention regimen defines a combination of first therapeutic treatment components and second therapeutic treatment components; administering one or more of the first therapeutic treatment components to the patient according to the personalized intervention regimen generated for the patient; administering one or more of the second therapeutic treatment components to the patient in combination with the one or more first therapeutic treatment components according to the personalized intervention regimen generated for the patient; monitoring the patient’ s interactions with the first therapeutic treatment components and the second therapeutic treatment components to generate patient interaction data representing the patient
  • a system comprises one or more processors and one or more physical memories, the one or more physical memories having stored therein data; a patient computing system; a user interface provided to the patient computing system, the user interface providing access to a therapeutics system; a therapeutics system which provides remotely located patients and caretakers access to the therapeutics system, the therapeutics system using the one or more processors and one or more physical memories to perform the above described methods/processes.
  • the systems and methods disclosed herein allow behavioral therapy to be administered to patients suffering from chronic pain conditions in a convenient and flexible, yet structured fashion, via a prescription digital therapeutics (DTX) system in combination with one or more non-behavioral therapies.
  • the invention(s) can employ non-traditional systems and methods for providing interventions to patients exhibiting symptoms associated with one or more health conditions.
  • the invention(s) can deliver psychological-based interventions, such as behavioral therapy-based interventions and other interventions (described in more detail above) to users/patients, by way of a platform having components implemented in a mobile device environment and/or other computer or internet-based architecture.
  • digital therapeutics (DTX) technologies may be used to administer behavioral therapies in combination with a variety of non-behavioral therapies in a controlled fashion, as treatment for one or more conditions described herein.
  • the invention(s) use components of the platform to process large amounts of user data, create individual user baselines (e.g., health, pain, mood, symptoms, medication side effects, etc. over time), remotely deliver personalized interventions, and remotely monitor user interactions with such interventions in near real-time, i.e. dynamically, in a manner that cannot be practically implemented by the human mind.
  • the disclosed method and system for effectively, efficiently, and remotely administering guided behavioral therapy in combination with other types of chronic pain therapies requires specific processes that utilize components of the platform disclosed herein to process user data, deliver interventions, and monitor user interactions with such interventions, and as such, does not encompass, embody, or preclude other forms of innovation in the area of healthcare technologies. Further, the disclosed embodiments of systems and methods for dynamically, efficiently, and remotely treating chronic pain health conditions using digital therapeutics are not abstract ideas for at least several reasons.
  • the method and system for effectively, efficiently, and remotely treating chronic pain health conditions using digital therapeutics in combination with other therapies provides a tool that significantly improves the fields of medical and mental health care for patients suffering from a wide variety of diseases and/or conditions.
  • health practitioners are provided with a tool to help them generate personalized and adaptive intervention regimens for use in treating chronic pain health conditions using digital therapeutics in combination with other therapies, which ensures that patients are provided with personalized and effective assistance, treatment, and care.
  • the method and system disclosed herein is not an abstract idea, and also serves to integrate the ideas disclosed herein into practical applications of those ideas.
  • the present invention also relates to an apparatus or system for performing the operations described herein.
  • This apparatus or system may be specifically constructed for the required purposes, or the apparatus or system can comprise a system selectively activated or configured/reconfigured by a computer program stored on a non-transitory computer readable medium for carrying out instructions using a processor to execute a process, as discussed or illustrated herein that can be accessed by a computing system or other device.
  • a computer program stored on a non-transitory computer readable medium for carrying out instructions using a processor to execute a process, as discussed or illustrated herein that can be accessed by a computing system or other device.
  • the present invention is well suited to a wide variety of computer network systems operating over numerous topologies.
  • the configuration and management of large networks comprise storage devices and computers that are communicatively coupled to similar or dissimilar computers and storage devices over a private network, a LAN, a WAN, a private network, or a public network, such as the Internet.

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Abstract

L'invention concerne des systèmes et des méthodes pour traiter, améliorer, prévenir ou réduire la probabilité de développer un trouble de douleur chronique, un ou plusieurs symptômes et comorbidités associés au trouble de douleur chronique, et/ou un ou plusieurs effets secondaires associés à des interventions thérapeutiques pour traiter le trouble de douleur chronique à l'aide d'agents thérapeutiques numériques. L'invention concerne en outre des systèmes et des méthodes pour améliorer l'adhésion aux interventions thérapeutiques et améliorer les performances des interventions thérapeutiques à l'aide d'agents thérapeutiques numériques.
PCT/US2023/060353 2022-01-10 2023-01-10 Méthodes et systèmes de traitement d'états de douleur chronique à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies WO2023133573A1 (fr)

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Citations (6)

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US20210057056A1 (en) * 2019-08-19 2021-02-25 Apricity Health LLC System and Method for Developing Artificial Intelligent Digital Therapeutics with Drug Therapy for Precision and Personalized Care Pathway
US20210144058A1 (en) * 2017-11-03 2021-05-13 Vignet Incorporated Systems and methods for managing operation of devices in complex systems and changing environments
US20210174919A1 (en) * 2017-02-09 2021-06-10 Cognoa, Inc. Platform and system for digital personalized medicine
US20210183482A1 (en) * 2019-12-17 2021-06-17 Mahana Therapeutics, Inc. Method and system for remotely monitoring the psychological state of an application user based on historical user interaction data

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Publication number Priority date Publication date Assignee Title
US20080014272A1 (en) * 2006-07-11 2008-01-17 Phil Skolnick Compositions and Methods for Treatment of Chronic Pain Conditions
US20210174919A1 (en) * 2017-02-09 2021-06-10 Cognoa, Inc. Platform and system for digital personalized medicine
US20210144058A1 (en) * 2017-11-03 2021-05-13 Vignet Incorporated Systems and methods for managing operation of devices in complex systems and changing environments
US20200411185A1 (en) * 2019-06-27 2020-12-31 Mahana Therapeutics, Inc. Adaptive interventions for gastrointestinal health conditions
US20210057056A1 (en) * 2019-08-19 2021-02-25 Apricity Health LLC System and Method for Developing Artificial Intelligent Digital Therapeutics with Drug Therapy for Precision and Personalized Care Pathway
US20210183482A1 (en) * 2019-12-17 2021-06-17 Mahana Therapeutics, Inc. Method and system for remotely monitoring the psychological state of an application user based on historical user interaction data

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