CN113113114A - Personal plan management APP terminal interactive system based on cognitive behavioral therapy - Google Patents
Personal plan management APP terminal interactive system based on cognitive behavioral therapy Download PDFInfo
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Abstract
The invention relates to the field of personal plan management and improvement of self-cognition, in particular to a cognitive behavioral therapy-based personal plan management APP terminal interactive system, which comprises a plan making module, a plan management module, a self-cognition guidance module, a staged data analysis module and a personal health management module; the invention provides a cognitive behavior therapy-based personal plan management APP terminal interactive system, aiming at the current situations that patients with mild and moderate depression have low daily efficiency and poor self-cognition, the system is used for improving the daily efficiency of patients with mild and moderate depression, establishing achievement and improving self-cognition. The method combines the planning with the professional cognitive therapy, further improves the treatment specialty for mild and moderate depression patients, and enables users to establish more comprehensive and healthy self-cognition while improving the daily efficiency.
Description
Technical Field
The invention relates to the field of online plan management and improvement of self-cognition, in particular to a personal plan management APP terminal interactive system based on cognitive behavioral therapy
Background
According to statistics, the prevalence rate of the Chinese depression reaches 2.1 percent, and about 9600 ten thousand people suffer from the depression. Of these, mild to moderate depression patients are more prominent. The prominent clinical symptoms of mild and moderate depression patients are mainly reflected in changes of behavior volition, and most patients can insist on working and learning. But the behavior is obviously lack of initiative and aggressiveness and the memory and attention are declined. Meanwhile, in cognition, self evaluation is reduced, the defects and errors of the self evaluation are often exaggerated, and the self evaluation cannot be correctly realized.
However, most of the existing efficiency management type terminals in the market are single plan making modes, the design in the aspects of experience summary and emotion dispersion after plan completion is less, and the terminals lack the APP for mild and moderate depression patients, so that the users cannot timely evacuate negative emotions and cannot establish correct self-cognition, and the online process of the efficiency management type APP is incomplete. Therefore, the APP terminal interaction system based on the cognitive behavior therapy is provided, plan making and professional cognitive therapy are combined, the treatment specialty of mild and moderate depression patients can be further improved, and users can build more comprehensive and healthy self-cognition while improving daily efficiency.
Disclosure of Invention
In order to solve the problems, the invention provides a cognitive behavior therapy-based personal plan management APP terminal interactive system, aiming at the current situations that patients with mild and moderate depression have low daily efficiency and poor self-cognition, the system is used for improving the daily efficiency of patients with mild and moderate depression, and simultaneously establishing achievement and improving self-cognition. The method combines the planning with the professional cognitive therapy, further improves the treatment specialty for mild and moderate depression patients, and enables users to establish more comprehensive and healthy self-cognition while improving the daily efficiency.
In order to achieve the purpose, the invention adopts the technical scheme that:
an APP terminal interaction system based on cognitive behavioral therapy is characterized by comprising a plan making module, a plan management module, a self-cognition guidance module, a staged data analysis module and a personal health management module;
the plan making module is used for making a plan and comprises a crop selection unit, a label selection unit, a name setting unit and a date setting unit; the crop selection unit is used for selecting a virtual crop; the label selection unit is classified according to the attributes of the planned contents and is divided into learning, working, entertainment, sports and the like; the name setting unit is used for customizing the name of the plan; the date setting unit is used for setting a scheduled starting date and a scheduled finishing date;
the plan management module is used for managing a plan and comprises a state unit and a classification unit; the state unit is divided according to plan completion conditions, stores plans which are not started, are in progress and are completed, and can manually set plan states; the classification unit is used for dividing and storing the plan of the state unit according to different content attributes, and can manually set the plan category;
the self-cognition guiding module is used for helping to improve emotion management and self-cognition of a user after plan is finished and comprises a reason analyzing unit, an emotion description unit and a thought introspection unit; the reason analysis unit is used for providing possible internal and external reasons and helping a user to analyze the reason of failure or success of the plan; the emotion description unit is used for providing possible emotions and strength and helping a user to more comprehensively learn self emotions; the thinking introspection unit is used for providing possible thinking traps and corresponding solutions and helping a user to seek a correct thinking mode;
the stage data analysis module is used for overall planning and analyzing stage data and comprises a plan summarizing unit, an efficiency summarizing unit and an emotion summarizing unit; the plan summarizing unit is used for counting the types, the times of completion or failure and reasons of the user plans in the stage; the efficiency summarizing unit is used for counting the speed of completion of the user plan and daily driving force change in the stage; the emotion summarizing unit is used for counting emotion changes and common thought traps of the user in the phase;
the personal health management module is used for analyzing and storing mental health information of the user according to the data, wherein the mental health information comprises average mood index information, mood change information, mood content information and suggested measure information.
Compared with the prior art, the invention has the advantages and beneficial effects that: the APP terminal interaction system based on cognitive behavior therapy provided by the invention aims at the current situations that patients with mild and moderate depression have low daily efficiency and poor self-cognition, and establishes achievement feeling and improves self-cognition while the daily efficiency of patients with mild and moderate depression is improved by the system. The method combines the planning with the professional cognitive therapy, further improves the treatment specialty for mild and moderate depression patients, and enables users to establish more comprehensive and healthy self-cognition while improving the daily efficiency.
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Fig. 1 is a block diagram of an embodiment of an APP terminal interactive system based on cognitive therapy according to an embodiment of the present invention;
fig. 2 is a block diagram of another embodiment of an APP terminal interaction system based on cognitive therapy according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of the self-cognition guiding module according to the present invention.
Detailed Description
In order to facilitate an understanding of the invention, the invention will now be described more fully hereinafter with reference to the accompanying drawings, in which several embodiments of the invention are shown, but which may be embodied in many different forms and are not limited to the embodiments described herein, but rather are provided for the purpose of providing a more thorough disclosure of the invention.
The invention provides an APP terminal interaction system based on cognitive therapy, which comprises a plan making module, a plan management module, a self-cognition guiding module, a staged data analysis module and a personal health management module, as shown in figure 1;
the plan making module is used for making a plan; the plan may be a total plan for a period of time or a periodic plan divided into every day or every few days, and each plan may be divided into a study plan, a work plan, an entertainment plan, an exercise plan, and the like.
The plan management module is used for managing a plan and comprises a state unit and a classification unit; the state unit is divided according to the completion condition of each plan, and stores plans which are not started, are in progress, are completed and are failed, all states can be automatically judged by the system, the change of the states can be updated in real time along with the progress of time, and the states of the plans can also be manually set; it should be noted that each plan stored therein needs to contain some basic information of the plan, such as name, contents of the plan, content attribute, start date and end date, etc. The classification unit is used for dividing and storing the plan of the state unit according to different content attributes, or manually setting the plan category, and classifying and storing the existing plan after the existing plan is divided again to obtain a plan state table with different content attributes; and the related planning state and classification information is sent to the staged data analysis module and the personal health management module.
The self-cognition guiding module is used for helping to improve the emotion management and self-cognition of the user after plan is finished, such as analyzing failure reasons and giving solutions.
The stage data analysis module is used for overall planning and analyzing stage data and comprises a plan summarizing unit, an efficiency summarizing unit and an emotion summarizing unit; the plan summarizing unit is used for counting the types of user plans in the stage, the plan number of each type, the finishing or failure times and reasons according to the plan state tables with different content attributes; the efficiency summarizing unit is used for counting the finishing speed of the user plan and the daily driving force change in the stage according to the plan state table with different content attributes; the emotion summarizing unit is used for counting emotion changes and common thought traps of the user in the phase; in order to more intuitively display the stage data analysis module, the information can be classified and named as 'plan situation', 'driving force change', 'emotion change' and 'common thinking' on an interface of the APP terminal interaction system.
The personal health management module is used for generating and storing mental health information of a user by a statistical method according to an analysis result of the stage data analysis module, the mental health information comprises average mood index information, mood change information and mood content information, suggested measure information is generated by a keyword recommendation algorithm, and in order to display the personal health management module more visually, the information can be named as 'mood index', 'mood change', 'mood content' and 'suggested measure' in a classified mode on an interface of an APP terminal interaction system.
In another embodiment of the present invention, as shown in fig. 2, a specific implementation of the planning module and the self-cognition guidance module is provided.
Plan making module includes crop selection unit, label selection unit, name setting unit and date setting unit, for the function of more directly perceived show plan making module, can be with above-mentioned unit classification name and show for "select crop", "select the label", "set up the name", "set the date" respectively on APP terminal interaction system's interface.
The crop selection unit is stored with a virtual cartoon crop pattern, and a user can freely select the crop pattern; associating the selected crop with a new plan established, which can be planted in the virtual farm by moving the virtual crop when the status of the plan is updated to be completed, the user can manage the virtual farm; the virtual farm can be managed in a mode that a user freely moves, crops or ornaments in the virtual farm are deleted, and personalized and customized management is carried out.
The label selection unit is used for confirming the contents of the plan, classifying the contents into learning, working, entertainment, sports and the like according to the attributes of the contents of the plan;
the name setting unit is used for customizing the name of the plan;
the date setting unit is used for setting a scheduled start date and an end date.
In this embodiment, the self-cognition guiding module comprises a reason analyzing unit, an emotion describing unit and a thinking introspection unit;
the reason analysis unit is used for providing possible internal and external reasons and helping a user to analyze the reason of failure or success of the plan; the user can record words autonomously, and can also select possible reasons prompted by the system to generate a reason analysis table. More specifically, the reason analysis unit can display the common reason entries in the reason entry library for the user to select, and provide blank reason entries for the user to define; the self-defined reason entries can be automatically stored in the reason entry library after the occurrence frequency or frequency of the reason entries exceeds a threshold value.
The emotion description unit is used for providing possible emotion and strength, guiding the user to timely learn self emotion and performing comparison after thinking is in self-province; for example, it may screen out relevant emotion words from the emotion database according to the reason analysis table, and determine the emotion intensity corresponding to each emotion word to generate the emotion intensity table. The reason analysis table described here can also be applied to the plan summary unit in fig. 1, so that the plan summary unit can be used to combine the plan status table and reason analysis table with different content attributes, and count the categories of user plans, the number of plans in each category, the number of completions or failures, and the reasons in the phase after eliminating the plans that have not yet started and are in progress.
The thinking introspection unit is used for providing possible thinking traps and corresponding solutions and helping a user to self-check wrong thinking and seek a correct thinking mode; for example, it can screen out the thought traps existing in the user from the knowledge base according to the emotion intensity table and output the corresponding solutions. The emotion intensity table described herein can also be applied to the emotion summarizing unit in fig. 1, so that the emotion summarizing unit can be used to count the emotion changes of the user and common thought traps in this stage according to the emotion intensity table and thought traps corresponding to each plan.
In one specific implementation of the invention, the emotion description unit can be further divided into different emotion analysis platforms, including an emotion category platform and an emotion intensity platform, wherein the emotion category platform is used for providing different positive emotion and negative emotion vocabularies for a user to select; the emotion intensity platform is used for providing different emotion intensity values for the user to select, the emotion intensity values are selected once before and after the thought is self-saved, and the user can freely record the emotion intensity values or the emotion intensity values are automatically matched by the system. In the specific implementation, the emotion type platform is composed of an emotion screening model and an emotion database, wherein positive emotion words and negative emotion words are stored in the emotion database, labels are set for different emotion words, a classifier is trained by using pre-collected reason entries and corresponding emotion labels, and the pre-trained classifier is used as the emotion screening model; the emotion screening model can automatically generate matched emotion vocabulary and prediction probability according to each reason in the reason analysis table, and in the embodiment, a classifier can adopt an SVM (support vector machine) and a random forest;
the emotion intensity platform is used for converting the prediction probability into the intensity value of the corresponding emotion vocabulary, and is provided with an interactive manual correction frame for a user to manually delete, supplement or modify the intensity value of the emotion vocabulary, and finally generates an emotion intensity table.
In one embodiment of the invention, the information stored in the thinking introspection unit can be obtained by big data acquisition, relevant websites are accessed for information screening and extraction, and the data are continuously updated; the thinking introspection unit comprises different platforms, including a thinking trap platform and a solution platform, wherein the thinking trap platform comprises 16 common thinking traps for a user to select, and the solution platform provides a corresponding correct thinking mode according to the selection of the user on the thinking trap platform, so that the user is helped to improve the emotion and correctly recognize the self. More specifically, the thinking trap platform stores a knowledge base containing 16 common thinking traps, each thinking trap corresponds to one or more emotion vocabularies with different intensity values, and the thinking traps existing in the user are screened out through an emotion intensity table; the solution platform stores correct solutions corresponding to each thought trap, and when one or more thought traps in the thought trap platform are selected automatically or by means, the corresponding solutions can be matched automatically.
As shown in fig. 3, in the present embodiment, the self-cognition guidance module is based on the cognitive therapy psychologically directed to major depression patients, and the flow is as follows:
a: after the plan is successful or failed, firstly, reason analysis is carried out, a user autonomously records possible reasons prompted by a system and then selects the possible reasons, and preliminary self analysis is carried out;
b: selecting and combing the emotion according to the positive emotion vocabulary and the negative emotion vocabulary provided by the system;
c: respectively setting initial emotion intensity values according to the selected emotion vocabularies;
d: selecting possible trapped thought traps from 16 common thought traps provided by the system to perform self thought introspection;
e: learning the correct thinking mode corresponding to the thinking trap to perform self-treatment;
f: setting the emotional intensity value after the self-saving thinking;
g: the method is summarized, and causes, emotions and thinking are summarized in three aspects.
The invention refers to the professional cognitive therapy process, creatively provides the personal plan management APP terminal interactive system based on the cognitive behavioral therapy, standardizes each process, and can objectively provide psychological counseling for the user, so that the user can establish more comprehensive, professional and healthy self-cognition while improving the daily efficiency.
In the above embodiments provided by the present invention, it should be understood that the above-described system embodiments are merely illustrative, and for example, the self-learning bootstrap module may be a logic function division, and may have another division when being actually implemented, for example, a plurality of modules or units may be combined or may be integrated into another system, or some features may be omitted, or may not be executed. In addition, the connections between the modules or units shown or discussed may be communication connections via interfaces, electrical connections or in other forms.
The present invention is not limited to the above embodiments, and many variations are possible, for example, the unit structures described in fig. 1 and fig. 2 may be combined with each other, or may be further modified based on the combination.
For example, with reference to fig. 1 and fig. 2, an emotion category conversion unit is arranged in the staged data analysis module shown in fig. 1, the emotion vocabulary in the emotion database is divided into eight categories of anger, nausea, sadness, fear, nothing, surprise, goodness, and happiness, a single emotion index value corresponding to each category of emotion is assigned, wherein the emotion index value of anger is-100, the emotion index value of happiness is 100, and the rest of the emotion index values are between-100 and 100, the emotion and intensity corresponding to each item of plan are converted into eight categories of emotion ratios, an emotion vector composed of eight ratios is obtained, and the sum of the eight ratios is 1. In this embodiment, a single emotion index value may be assigned according to the dispersion coefficient of eight types of emotions, or may be simply assigned according to the numerical value of an arithmetic sequence or an unequal difference sequence (from small to large).
Acquiring an analysis result of the periodic data analysis module through the personal health management module to obtain plan types of the user at the period, plan contents and statistical information under each type, wherein the statistical information comprises plan number, completion or failure times and reasons under each type, plan completion progress, daily action power, emotion vectors corresponding to each plan and thinking traps;
calculating a weighted sum as a total emotion index of each plan according to the emotion vector and a preset single emotion index value; taking the average value of the total emotion indexes belonging to the same category plan to obtain the average emotion index of the category plan; averaging the total emotion indexes of all the plans to obtain an average emotion index of all the plans in the stage;
for example, the emotion vector of a user after completing a program is [0,0,0.1,0.1,0.5,0.2,0.1,0], the single emotion index value of eight categories of emotions is [ -100, -75, -50, -30,0,50,75,100], and then the emotion index obtained by the user on the program is:
X＝0*-100+0*-75+0.1*-50+0.1*-30+0.5*0+0.2*50+0.1*75+0*100＝9.5
arranging the total emotion indexes of each plan according to a time sequence to obtain emotion change information;
extracting the content corresponding to each plan, the reason for completion or failure, the schedule for completion of the plan, daily action power and thinking traps as emotional content information;
and outputting suggested measures with the matching value larger than 80% through a keyword recommendation algorithm according to the average emotion index, the emotion change information and the emotion content information at the stage. In this embodiment, the content is first converted into a keyword or referred to as a feature value, for example, the feature value is an average emotion index, an emotion change amplitude, a plan category, a failure cause category, a thinking trap category, or the like, and the recommendation algorithm may use a decision tree, a neural network, a logistic regression, a vector-based representation method or a combined recommendation method, or may implement recommendation based on an existing engine server.
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains. Unless specifically stated otherwise, the relative steps, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of the present invention.
In all examples shown and described herein, unless otherwise specified, any particular value should be construed as merely illustrative, and not restrictive, and thus other examples of example embodiments may have different values.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (8)
1. An APP terminal interactive system for personal plan management based on cognitive behavioral therapy is characterized by comprising a plan making module, a plan management module, a self-cognition guiding module, a staged data analysis module and a personal health management module;
the plan making module is used for making a plan and comprises a crop selection unit, a label selection unit, a name setting unit and a date setting unit; the crop selection unit is used for selecting a virtual crop; the label selection unit is used for confirming the contents of the plan, classifying the contents into learning, working, entertainment and sports according to the attributes of the contents of the plan; the name setting unit is used for customizing the name of the plan; the date setting unit is used for setting a scheduled starting date and a scheduled finishing date;
the plan management module is used for managing a plan and comprises a state unit and a classification unit; the state unit divides the state of each plan according to the completion condition of the plan, updates the state along with time, and obtains a total plan state table updated in real time, wherein each plan comprises a name, plan content, a content attribute label, a starting date, an ending date and a current state, the states are divided into a state which is not started yet, is in progress, is completed and fails, and the selection of the state types comprises an automatic mode and a manual mode; the classification unit is used for dividing plans in different states according to different content attributes to obtain and store a plan state table with different content attributes, and the classification unit is provided with an automatic mode and a manual mode;
the self-cognition guiding module is used for helping to improve emotion management and self-cognition of a user after plan is finished and comprises a reason analyzing unit, an emotion description unit and a thought introspection unit; the reason analysis unit is used for providing possible internal and external reasons, helping a user to analyze the reason of plan failure or success and generating a reason analysis table; the emotion description unit is used for screening out related emotion vocabularies from an emotion database according to the reason analysis table, determining the emotion intensity corresponding to each emotion vocabulary and generating an emotion intensity table; the thinking introspection unit is used for screening out thinking traps existing in the user from the knowledge base according to the emotion intensity table and outputting corresponding solutions;
the stage data analysis module is used for overall planning and analyzing stage data and comprises a plan summarizing unit, an efficiency summarizing unit and an emotion summarizing unit; the plan summarizing unit is used for combining a plan state table and a reason analysis table with different content attributes, eliminating the plans which are not started yet and are in progress, and then counting the types of the user plans, the plan number of each type, the finishing or failure times and reasons in the stage; the efficiency summarizing unit is used for counting the schedule finished by the user plan and the daily action power change in the stage according to the plan state table with different content attributes; the emotion summarizing unit is used for counting emotion changes and common thinking traps of the user in the stage according to the emotion intensity table and the thinking traps corresponding to each plan;
the personal health management module is used for generating and storing mental health information of the user by using a statistical method according to the analysis result of the staged data analysis module, wherein the mental health information comprises average mood index information, mood change information and mood content information, and suggested measure information is generated by using a keyword recommendation algorithm.
2. The APP terminal interaction system for personal plan management based on cognitive behavioral therapy (CR) according to claim 1, characterized in that the crop selection unit is used for selecting a virtual crop, associating the selected crop with a new plan established, and when the status of the plan is updated to be completed, the virtual crop can be planted in a virtual farm by moving the virtual crop, and the user can manage the virtual farm.
3. The system of claim 2, wherein the virtual farm for management is: the user can freely move and delete crops or ornaments in the virtual farm, and personalized user-defined management is carried out.
4. The APP terminal interaction system for personal plan management based on cognitive behavioral therapy according to claim 1, wherein the emotion description unit in the self-cognition guidance module comprises an emotion category platform and an emotion intensity platform;
the emotion classification platform is composed of an emotion screening model and an emotion database, positive emotion vocabularies and negative emotion vocabularies are stored in the emotion database, labels are set for different emotion vocabularies, a classifier is trained by using pre-collected reason vocabulary entries and corresponding emotion labels, and the pre-trained classifier is used as the emotion screening model; the emotion screening model can automatically generate matched emotion words and prediction probability according to each reason in the reason analysis table;
the emotion intensity platform is used for converting the prediction probability into the intensity value of the corresponding emotion vocabulary, and is provided with an interactive manual correction frame for a user to manually delete, supplement or modify the intensity value of the emotion vocabulary, and finally generates an emotion intensity table.
5. The APP terminal interaction system for personal plan management based on cognitive behavioral therapy (COF) as claimed in claim 1, wherein the thought introspection unit in the self-cognition guidance module comprises a thought trap platform and a solution platform;
the thinking trap platform is stored with a knowledge base containing 16 common thinking traps, each thinking trap corresponds to one or more emotion vocabularies with different intensity values, and the thinking traps existing in the user are screened out through an emotion intensity table;
the solution platform stores correct solutions corresponding to each thought trap, and when one or more thought traps in the thought trap platform are selected automatically or by means, the corresponding solutions can be matched automatically.
6. The APP terminal interaction system is characterized in that a reason analysis unit in the self-cognition guidance module displays common reason entries in a reason entry library for a user to select and provides blank reason entries for the user to customize; the self-defined reason entries can be automatically stored in the reason entry library after the occurrence frequency or frequency of the reason entries exceeds a threshold value.
7. The APP terminal interaction system of personal plan management based on cognitive behavioral therapy as claimed in claim 1, further comprising an emotion category transformation unit in the staged data analysis module, dividing emotion vocabularies in the emotion database into eight categories of anger, nausea, sadness, fear, nothing, fright, good and happiness, assigning a single emotion index value corresponding to each category of emotion, wherein the emotion index value of anger is-100, the emotion index value of happiness is 100, and the rest of emotion index values are between-100 and 100, transforming emotion and intensity corresponding to each plan into eight categories of emotion ratios, obtaining an emotion vector composed of eight ratios, and the sum of the eight ratios is 1.
8. The APP terminal interaction system of personal plan management based on cognitive behavioral therapy as claimed in claim 7, wherein the personal health management module obtains the analysis result of the staged data analysis module to obtain the plan type of the user at the stage, the plan content and statistical information of each type, the statistical information includes the plan number, completion or failure times and reasons of each type, plan completion progress, daily behavior power, emotion vector corresponding to each plan, thinking trap;
calculating a weighted sum as a total emotion index of each plan according to the emotion vector and a preset single emotion index value; taking the average value of the total emotion indexes belonging to the same category plan to obtain the average emotion index of the category plan; averaging the total emotion indexes of all the plans to obtain an average emotion index of all the plans in the stage;
arranging the total emotion indexes of each plan according to a time sequence to obtain emotion change information;
extracting the content corresponding to each plan, the reason for completion or failure, the schedule for completion of the plan, daily action power and thinking traps as emotional content information;
and outputting suggested measures with the matching value larger than 80% through a keyword recommendation algorithm according to the average emotion index, the emotion change information and the emotion content information at the stage.
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