JP7133207B2 - Information processing device and program - Google Patents

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to healthcare support technology, and more particularly to support technology capable of optimizing the content of support for each individual.

According to Patent Literature 1, a system has been developed for standardizing and improving the efficiency of creating an expert's advice message in creating and transmitting a message for guidance. The purpose is to select advice suitable for the client's health condition, etc. from the client's biological information, diet, health condition, etc., and to improve the accuracy of the health guidance service itself by providing feedback.

According to Patent Document 2, there is provided a health care server capable of generating an appropriate advice message based on the diet and health condition of a person subject to health care, and improving the motivation to implement the health care curriculum. At this time, an expert selects images for improving motivation.

Japanese Patent No. 6010719 JP 2017-1154 A

In the conventional approaches such as those described in Patent Documents 1 and 2, although it is possible to propose health behaviors according to need based on biometric information and the person's consciousness, the method of conveying them is almost uniform. It does not take into consideration that the same explanation can have a big difference in how it is conveyed by people. Essentially, the person's intrinsic motivation should be provided, but existing individual optimization does not consider individualization of cognition. At present, the actual situation is that it is not possible to dramatically change the probability in behavior modification without depending on counseling by some professionals. This is because there are many variables such as individual preferences and experiences, and it is very complicated to unravel individual characteristics.

In addition, in the case where the subject is a person who is in poor health and needs some kind of professional help, or when the subject is a person who is highly interested in health, health itself becomes the purpose. There is a way of thinking that is systematized to some extent as the motivation of the person subject to health care. However, when targeting people who do not have any particular problems with their health, there is no systematized method for motivating them, and they are treated individually.

SUMMARY OF THE INVENTION Accordingly, the object of the present invention is to optimize the content of support in the health care of the person and the timing of transmission thereof for each individual subject to health care whose health itself is not the goal.

With the development of brain science, the processes of human thought and emotion have been scientifically elucidated. On the other hand, in the academic field as well, over the last 100 years, it has been proven that five human characteristics are elements with universality (the so-called Big Five). In addition to the knowledge of conventional public health, we will apply the above-mentioned knowledge of brain science, knowledge of characteristic analysis such as individual cognitive and behavioral characteristics based on the Big Five, knowledge of healthcare marketing, knowledge of coaching, etc. By using them in combination and systematizing them, it is possible to analyze the "characteristics related to healthcare decision-making" for each person subject to health management. By analyzing "characteristics involved" and "appropriate timing", we support individual optimization of intrinsic motivation in healthcare, and present guidance patterns of communication tailored to the target person at appropriate timing. It can be so.

It can dramatically increase the probability of behavior change compared to existing approaches. In the existing approach, it was not possible to optimize for each individual until whether or not it was communicated, but it was a uniform way of communicating. This is because by analyzing the "timing", it is possible to support individual optimization of intrinsic motivation in healthcare, and to present guidance patterns for communicating according to the target person at the appropriate timing. Therefore, according to the present invention, it is possible to optimize the content of support in health care for the person in question for each individual, taking into consideration the manner of communication.

FIG. 1 is an overall schematic diagram of a healthcare support system. FIG. 2 is a sequence diagram of the entire healthcare support system shown in FIG. FIG. 3 is a functional configuration diagram of the healthcare support server 100 shown in FIG. FIG. 4 is a data conceptual diagram (individual information) showing a data configuration example of the storage unit 1300 shown in 3. FIG. FIG. 5 is a data conceptual diagram (common basic information) showing a data configuration example of the storage unit 1300 shown in FIG. FIG. 6 is a flowchart of account-related processing A shown in FIG. FIG. 7 is a flow chart of the “characteristics related to decision-making in healthcare” judgment process P shown in FIG. FIG. 8 is a flow chart of the transmission method optimization process T shown in FIG. FIG. 9 is a flow chart of the learning process G shown in FIG. FIG. 10 is a specific example of the “characteristics related to decision-making in healthcare” determination process P shown in FIG. FIG. 11 is a specific example of the “characteristics related to decision-making in healthcare” determination process P shown in FIG. FIG. 12 is a specific analysis example of the communication optimization process T shown in FIG. FIG. 13 shows specific examples of guidance patterns and timing.

The healthcare support system of the present invention will be described below with reference to the drawings.

FIG. 1 is an overall schematic diagram of a healthcare support system.
<Overview>
As shown in FIG. 1, the healthcare support system includes a healthcare support server 100, a plurality of user terminals 200 to 800, and customer companies that provide services to health care recipients through the user terminals 200 to 800 of the health care recipients. includes a customer enterprise terminal 900 of Healthcare support server 100 is connected to customer company terminal 900 and user terminals 200 to 800 via network 1 .

A user terminal 200 shown in FIG. 1 refers to a mobile terminal such as a smart phone, and is mainly responsible for input and output from the screen. The user terminal 200 has an application program for receiving and displaying information exchanged with the customer company terminal 900 and the healthcare support server 100 . In the user terminal 200 , the information received by the application from the person subject to health care is transmitted to the customer company terminal 900 via the network 1 or transmitted to the healthcare support server 100 via the network 1 . The information transmitted from the user terminal 200 and the customer company terminal 900 to the healthcare support server 100 is, for example, answer data and answer voice to a questionnaire sent from the healthcare support server 100 to the user terminal 200 via the network 1. data, an activity log that measures activity, image information such as complexion and pupils, and position information that indicates the results of running and walking. Alternatively, it is similar information obtained by the customer company terminal 900 from the user terminal 200 .

A user terminal 300 shown in FIG. 1 is a body measurement device that can be connected to the network 1, and is provided by a customer company to a person subject to health management. The information acquired by the user terminal 300 is vital data such as body weight, body fat, bone density, etc., and is transmitted to the customer company terminal 900 or the healthcare support server 100 via the network 1 . The data acquired by the healthcare support server 100 is used not only for processing to measure the current health level, but also for "healthcare ("healthcare") defined by WHO (World Health Organization), physical, Analysis of decision-making characteristics of health behaviors to promote mental and social health and patternization of necessary elements for guidance patterns (motivational information to promote health care decision-making) It is also used to calculate the timing for providing

The user terminal 400 is an audio device provided by a client company to a person subject to health management, and can exchange input and output mainly by voice. Since the two-way voice communication itself can be deployed in the cloud, the stationary voice device shown here is just one example, and some are equipped with a screen. Information input from the user terminal 400 is transmitted to the customer company terminal 900 or the healthcare support server 100 via the network 1 .

The information transmitted from the user terminal 400 to the client company terminal 900 or the healthcare support server 100 includes responses to various questions and requests as well as voice itself. It is divided into data that can measure emotions such as voice tone and speed, and is used not only for judgment processing of "characteristics related to decision-making in healthcare" but also to provide guidance patterns. It is also used to calculate the timing for

The user terminal 500 is a personal computer used by a health care subject to receive services from a customer company, and may contain a program for the customer company to provide services to the health care subject. The information transmitted from the user terminal 500 to the client company terminal 900 or the healthcare support server 100 includes response data and voice response to questionnaires transmitted from the healthcare support server 100 to the user terminal 500 via the network 1, This includes image information such as complexion and pupils.

The user terminal 600 refers to a wearable device for providing services from a client company to a person subject to health management, and is of a type worn on the user's body. Specifically, there are various forms such as a bracelet-shaped activity meter, a watch type, a pedometer type, and a wearable type. In addition to the amount of physical activity, various vital data such as body temperature and blood sugar level can be measured. Data transmitted from the user terminal 600 to the customer enterprise terminal 900 or to the healthcare support server 100 is used to calculate the current "characteristics involved in healthcare decision-making" analysis and timing for providing guidance patterns. used for

A user terminal 700 is a high-performance mirror for providing services from client companies to persons subject to health management, and incorporates a camera, an audio device, a touch sensor, and the like. It detects facial expressions, heartbeats, blood pressure, body temperature, perspiration, etc. reflected in the high-performance mirror. It is also possible to use a half-mirror to display images, so it is possible to convey information using images. You can also know the unconscious emotional reaction such as whether it is a target or not. The information transmitted from the user terminal 700 to the client company terminal 900 or the healthcare support server 100 is the data of the responses to the questionnaire output from the healthcare support server 100 to the user terminal 700 via the network 1 and the responses. voice data, image information such as complexion and pupils, and the like.

The user terminal 800 is a device mainly for acquiring specialized vital data, such as a sphygmomanometer, a blood test device, an electroencephalograph, a swallowing gastroscope, etc., for providing services from client companies to persons subject to health management. The data transmitted from the user terminal 800 to the customer enterprise terminal 900 and the healthcare support server 100 is also used to calculate the timing for providing guidance patterns.

In FIG. 1, only seven user terminals are shown to simplify the explanation, but it goes without saying that there may be more. Moreover, the specific devices of the user terminals 200 to 800 are not limited to those illustrated. It refers to all network-connected devices that are part of the entire healthcare support system of the present invention and that lead to enhancement of motivational functions related to healthcare. The user terminals 200 to 800 have both or one of the functions of acquiring information from users and outputting them.

The customer company terminal 900 is a terminal for providing services to persons subject to health management, and exchanges various information with the user terminals 200 to 800 described above. Information obtained from user terminals 200 to 800 is also transmitted to healthcare support server 100 .

The healthcare support server 100 analyzes “characteristics related to healthcare decision-making” and “appropriate timing” for each individual based on information acquired from the client company terminal 900 or the user terminals 200-800. Then, the “optimum guidance pattern” and the “appropriate timing” of intrinsic motivation in healthcare are transmitted to the client company terminal 900 .

Here, in order to facilitate understanding of the outline, FIG. 2 shows a sequence diagram of the entire healthcare support system.

Main data exchange is from the user terminals 200 to 800 to the customer company terminal 900 via the network 1, and the customer company terminal 900 goes through the network 1 to the healthcare support server 100, or the healthcare support server 100 communicates directly with user terminals 200-800 via network 1.

In the sequence diagram shown in FIG. 2, account-related processing A, “characteristics related to healthcare decision-making” determination processing P, communication style optimization processing T, and learning processing G proceed in this order. In addition, by performing the account-related processing A prior to the “characteristics related to healthcare decision-making” determination processing P, the same health care subject intermittently receives data via a plurality of user terminals 200 to 800. Appropriate analysis can be done even if you exchange As a result, the survey and analysis are divided into multiple times according to the convenience and mood of the person subject to health care.

In account-related processing A, user terminals 200, 500, and 700 transmit the account information of the person subject to health management to customer company terminal 900 (step S01).
0 transmits the received account information to the healthcare support server 100 (step S02). Healthcare support server 100 transmits an attribute information input form for acquiring attribute information from a person subject to health management to customer company terminal 900 (step S03). , 500 and 700 (step S04). In response to this, the user terminals 200, 500 and 700 display the attribute input form on the screen and receive the attribute information from the health care subject. User terminals 200, 500, and 700 transmit the received attribute information to customer company terminal 900 (step S05), and customer company terminal 900 transmits the attribute information described above to healthcare support server 100 (step S06). In response to this, the healthcare support server 100 associates the attribute information with the account information and registers it.

In the "characteristics related to decision-making in healthcare" determination process P, the healthcare support server 100 performs the "characteristics related to decision-making in healthcare" for analyzing the "characteristics related to decision-making in healthcare" of the customer management subject. ' information input form to the customer company terminal 900 (step S07), and the customer company terminal transmits the received 'characteristics related to decision-making of healthcare' information input form to the user terminals 200, 500, and 700 (step S08). ). In response to this, the user terminals 200, 500, and 700 display the "characteristics related to decision-making in healthcare" information input form on the screen, and the survey information of the "characteristics related to decision-making in healthcare" is received from the person subject to health management. (Survey information related to habits of the head, habits of the mind, the scale of the head, and the scale of the heart, which will be described later) is accepted. User terminals 200, 500, and 700 transmit the received survey information of "characteristics related to decision-making in healthcare" to client company terminal 900 (step S09), and customer company terminal 900 sends the above-mentioned "characteristics related to decision-making in healthcare." The survey information of "characteristics involved" is transmitted to the healthcare support server 100 (step S10). In response to this, the healthcare support server 100 analyzes the “characteristics related to healthcare decision-making” of the subject of health management based on the survey information of the “characteristics related to healthcare decision-making”, and links them to the account information. and stored in the storage unit 1300 of the healthcare support server 100 .

In the communication method optimization process T, when the content to be conveyed to the person subject to health management is transmitted from the customer company terminal 900 to the healthcare support server 100 (step S11), the healthcare support server 100 receives the above-mentioned content to be conveyed. Analyze what kind of content it is, and then analyze and judge the "optimal guidance pattern" according to the "characteristics related to decision-making in healthcare" of the person subject to health care. Furthermore, the healthcare support server 100 transmits a data request command necessary for determining the "optimum guidance pattern" to the customer company terminal 900 (step S12). The customer company terminal 900 transmits the above command to the user terminals 200 to 800 (step S13). Among the user terminals 200 to 800, the terminal that receives the above-described command stores data necessary for timing determination (for example, log data for measuring the timing when the weight exceeds a certain threshold in the user terminal 300, log data for the user terminal 600 , log data for measuring the timing when the amount of activity has decreased significantly) is transmitted to the customer company terminal 900 (step S14). The customer company terminal 900 transmits the data necessary for the timing determination described above to the healthcare support server 100 (step S15). The healthcare support server 100 analyzes the received data necessary for timing determination, and determines "appropriate timing" for motivating the subject of health management. The healthcare support server 100 transmits the above-mentioned "optimum guidance pattern" and "appropriate timing" information to the customer company terminal 900 (step S16). In response to this, the customer company receives specific "optimal motivation information" ("optimal motivation "Information" is optimized by taking into account the "characteristics related to decision-making in healthcare" of the person subject to health management, and the "optimal motivational information" is sent from the customer company terminal 900 to the "appropriate timing." ' to the user terminals 200 to 800 (step S17).

It should be noted that the communication method optimization processing T is assumed to be automated by artificial intelligence. become. In this case, the healthcare support server 100 will transmit the above-mentioned “optimal motivational information” to the user terminals 200 to 800 or the customer company terminal 900 .

In the learning process G, the customer company terminal 900 transmits to the server 100 the same information as the "optimal motivational information" transmitted to the user terminals 200 to 800 (step S18). Further, when the user terminals 200 to 800 receive the "optimal motivation information", the user terminals 200 to 800 display changes in behavior caused by displaying the above-mentioned motivation information to the person subject to health management as a time-series behavior log data transition. Send to the company terminal 900 . The customer company terminal 900 transmits the received action log data to the healthcare support server 100 . The healthcare support server 100 stores the received "optimal motivational information" and the behavior log data analyzed as learning information.
<Configuration>
The healthcare support server 100 will be described below with reference to FIG. FIG. 3 is a system functional configuration diagram of the healthcare support server 100. As shown in FIG. The healthcare support server 100 includes a communication section 110 , a processing section 1200 , a storage section 1300 and an information output section 140 .

The communication unit 110 transmits and receives video/image/audio information and message information to/from the user terminals 200 to 800 and the customer company terminal 900 via the network 1 .

The information output section 140 sends the information processed by the processing section 1200 to the communication section 110 .

A storage unit 1300 mainly stores data, and is divided into an individual information storage unit and a common basic information storage unit. The individual information storage section has an account information storage section 1310 , an attribute information storage section 1311 and an integrated personality information storage section 1330 . The common basic information storage section has a guidance/pattern information storage section 1340 , health information storage section 1350 , behavior change story information storage section 1360 , user-provided information storage section 1370 , bias information storage section 1380 and survey information storage section 1390 .

As shown in FIG. 4, the account information storage unit 1310 stores account information (ID, name, information disclosure setting information, contracted company information, used terminal information, etc.) of the health care subject.

As shown in FIG. 4, the attribute information storage unit 1311 stores the attribute information of the subject of health care (meaning information unique to an individual, such as age information, gender information, hobby information, and five senses memory information related to motivation) as account information. It is stored in association with an ID.

As shown in FIG. 4, integrated personality information storage unit 1330 stores integrated personality information, which is "characteristics related to healthcare decision-making", in a state of being associated with an ID of account information. "Integrated personality information" is mainly composed of "habits" that are genetic and difficult to change, and "measures" that can be changed by adding knowledge or training, etc. , there is something by "heart". Furthermore, in addition to these four "head habits", "mind habits", "brain scales" and "mind scales" (these will be described later), "weighting information" necessary for integrated calculations ” is called integrated personality information, and all five pieces of information are stored in a state of being associated with the ID of the account information.

As shown in FIG. 5, the health information storage unit 1350 mainly stores various medically verified data related to health (numerical information on diet, exercise, sleep, smoking, alcohol consumption, oral hygiene, information related to disease, etc.). For example, an appropriate intake amount of vegetables recommended per day, an appropriate amount of exercise recommended per day, etc.) are stored.

As shown in FIG. 5, the user-provided information storage unit 1370 stores "optimal motivational information" and "appropriate provision timing" actually provided to the person subject to health management. Concrete examples provided to persons subject to health management based on the "optimal guidance pattern" and "appropriate timing" that take into account the individual's "characteristics related to healthcare decision-making" are kept as user-provided information. In addition to using it to correct the weight of the individual's "characteristics related to healthcare decision-making," in the future, it will be possible to use the recorded images and texts to determine the "characteristics related to healthcare decision-making" of the person subject to health management. It is also possible to automatically create "optimal motivational information" according to the situation.

The bias information storage unit 1380 stores algorithm information for various illusions and biases (confirmation bias, heuristic bias, halo effect, mental shotgun, etc.) as bias information as shown in FIG.

As shown in FIG. 5, the behavior modification story information storage unit 1360 stores behavior modification stage information (information for discriminating indifference period, interest period, preparatory period, execution period, and maintenance period). It stores reference values of various data (for example, information on intention to cause behavioral change, changes in body weight by the user terminal 300, changes in the amount of activity by the user terminal 600, etc.) for each stage. ) and story information (pattern information on what kind of decision-making pattern the person subject to health management changes the behavioral change stage according to their “characteristics related to decision-making in healthcare”. For example, intuitive Information that it is effective for a man in his 40s who has a figurative head habit and is in the indifference period to emphasize the importance of healthy behavior in maintaining relationships with his children and his partner. ) is remembered.

As shown in FIG. 5, the guidance/pattern information storage unit 1340 stores "integrated personality classification information" (integrated personality classification information is information obtained by comprehensively analyzing and classifying integrated personality information, behavior change story information, and attribute information). ) and corresponding output pattern information (an image pattern of 'something to be shown' and a character pattern of 'words to be conveyed') are stored.

The survey information storage unit 1390 stores survey items necessary for the “characteristics related to decision-making in healthcare” determination process. Questions in questionnaires, animations in a video survey method (described later), etc. are stored.

The processing unit 1200 includes, as shown in FIG. , a guidance updating unit 1290 and the like. Based on information such as videos, images, characters, and sounds received from the user terminals 200 to 800 or the customer company terminal 900, it is compared with various judgment materials stored in the storage unit 1300, By analyzing the "characteristics related to decision-making", it creates and processes the "optimal guidance pattern" and "appropriate timing" for each person subject to health care. The processing unit 1200 performs the account-related processing A, the “characteristics related to healthcare decision-making” determination processing P, the communication method optimization processing T, and the learning processing G shown in FIG.

The data judgment unit 1211 judges the contents of the information received from the communication unit 110 and distributes it to the necessary processing units. Mainly information related to account-related processing A, information related to "characteristics related to healthcare decision-making" determination processing P, information related to communication optimization processing T, and information related to learning processing G. Allocate.

The account information processing unit 1212 is where the account-related processing P is performed. The "account information storage unit 1310" and the "attribute information storage unit 1311" for personal identification are queried, newly established, name identification, updated, deleted, and the like.

The 'characteristics involved in decision-making in healthcare' analysis unit 1220 is where the 'characteristics involved in decision-making in healthcare' determination processing P is performed. The axis that divides the "habit", which is a trait that is mainly hereditary and difficult to change, and the "measure", which is a trait that can be changed by adding knowledge or training, etc. Four quadrants are divided by the axis that divides (mainly conscious functions) and "mind" (mainly unconscious functions), which is the characteristic of emotions, and each of them is divided into "head habits", "mind habits", and "heads". After analyzing the decision-making characteristics of health care with respect to the scale of the heart and the scale of the heart (details of each will be described later), we are finally analyzing the integrated characteristics of individuals.

Regarding the structure of the detailed survey, the reliability (retest reliability, internal consistency) and validity (content validity, comorbid validity, predictive validity) were evaluated by the Big Five with academic evidence and brain science. and construct validity) are used as a basis.

Guidance pattern creation section 1270 creates an “optimal guidance pattern” in accordance with the target health care subject in the communication method optimization process P. FIG. Analyzing the integrated personality classification information from the information stored in the above-mentioned integrated personality information storage unit 1330, attribute information storage unit 1311, and behavior change story information storage unit 1360 of the subject of health care, and according to the integrated personality classification information A guidance pattern is selected from the guidance pattern information storage unit 1340 . In the future, the information in the user-provided information storage unit 1370 can be used to perform individual correction processing in accordance with the person subject to health care by means of artificial intelligence, so that instead of guidance patterns, motivation information can be created directly.

The guidance provision timing analysis unit 1280 provides specific “optimal motivational information” created from the “optimal guidance pattern” sent by the customer company terminal 900 from the healthcare support server 100 to the person subject to health management. It analyzes and judges whether it is appropriate to convey one.

Guidance updating unit 1290 is where learning processing G is performed, and finally "motivational information" and "appropriate timing" displayed on user terminals 200, 400, 500, and 700, and logs of behavioral changes that have changed accordingly. This is for analyzing data and updating the weighting data of behavior change story information and integrated personality information.
<Action>
FIG. 6 is a flowchart of account-related processing A shown in FIG. Data is received by the communication unit 110 of the healthcare support server 100 via the network 1 by inputting data together with account information from the user terminals 200 to 800 or the customer company terminal 900 or the like. The data received by the communication unit 110 is distributed to the account information processing unit 1212 by the data judgment unit 1211 (step A01). In response to this, the account information processing unit 1212 refers to the account information storage unit 1310 and inquires about the presence of account information (step A02). If there is no account information, the account information is acquired and stored in the account information storage unit (step A06), and the process proceeds to step A07. If there is account information, the process immediately proceeds to step A07.

Next, the account information processing unit 1212 inquires about the attribute information (memory of five senses, age, family composition, hobby, vital data, etc.) linked to the registered account information ID and stored in the attribute information storage unit 1311. (Step A07). By this inquiry, the information output unit 140 and the communication unit 110 are sent to the information output unit 140 and the communication unit 110 to specify the information that has not been acquired and the information that needs to be updated (for example, weight, blood pressure, etc.). to the user terminals 200 to 800 or the customer company terminal 900 (step A08). The customer company terminal 900 transmits the above-described question information or information acquisition command to the user terminals 200-800. The user terminals 200, 400, 500, and 700 display the received question information on the screen, or execute the information acquisition command if it is.

Attribute information that has not yet been acquired or attribute information whose data needs to be updated, which has been input from the user terminal, is transmitted to the healthcare support server 100 via the customer company terminal 900 or directly. The attribute information received by healthcare support server 100 is received by account information processing section 1212 via communication section 110 and data judgment section 1211 (step A09). The account information processing unit 1212 stores the attribute information described above in the attribute information storage unit 1311 (step A10). Next, the account information processing unit 1212 inquires whether there is insufficient attribute information in the attribute information storage unit 1311, and if there is attribute information that has not yet been acquired or attribute information that needs to be updated, the health management unit 1212 Question information asking whether the target person will cooperate with information collection is transmitted to the user terminal 200 , 400 , 500 , 700 or the client company terminal 900 via the information output unit 140 and the communication unit 110 . The customer company terminal 900 transmits the above question information to the user terminals 200 , 400 , 500 and 700 . The user terminals 200, 400, 500 and 700 display the received question information on the screen. User terminals 200 , 400 , 500 , and 700 transmit the answer information of the person subject to health care to the above-described question information to healthcare support server 100 via customer company terminal 900 or directly. The answer information received by the healthcare support server 100 is received by the account information processing section 1212 via the communication section 110 and the data judgment section 1211 . Based on the received answer, the account information processing unit 1212 proceeds to step A08 if additional acquisition of attribute information is possible, and proceeds to end if additional acquisition of attribute information is not possible (step A11). Through the series of processes from step A01 to step A11, the account information storage unit 1310 is gradually supplemented, and the account information sufficiency (the sufficiency is the number of frameworks initially assigned as attribute information). (refers to the ratio of the number of people who are able to take health care).

FIG. 7 shows a flow chart of the “characteristics related to healthcare decision-making” determination process P shown in FIG. By receiving a signal for starting determination processing of "characteristics related to decision-making in healthcare" together with account information via user terminals 200, 400, 500, 700 and customer company terminal 900, "decision-making in healthcare "characteristics related to" determination process P is started. As a premise for this, it is assumed that consent has been obtained from the subject of health care to determine the "characteristics related to decision-making in healthcare."

The “characteristics related to decision-making in healthcare” analysis unit 1220 extracts and creates questions/survey items from the survey information storage unit 1390 (step P03). The questions/survey items created in step P03 are transmitted to the customer company terminal 900 or the user terminals 200, 400, 500, 700 via the information output unit 140 and the communication unit 110 (step P04). The user terminals 200, 400, 500, and 700 output the received questions/survey items on the screen, and the health care subject answers the above-mentioned questions/survey items. In addition, since the above account-related processing A is functioning, analysis can be performed intermittently from multiple user terminals used by the same person subject to health care. In addition, non-verbal information is utilized (step P05). The survey information of the “characteristics related to decision-making in healthcare” obtained in step P05 (answer information to questions for investigating “characteristics related to decision-making in healthcare”) is sent from the user terminal via the customer company terminal 900. or directly to the healthcare support server 100 . The attribute information received by the healthcare support server 100 is sent to the “characteristics related to healthcare decision-making” analysis unit 1220 via the communication unit 110 and the data determination unit 1211 . The ``characteristics related to decision-making in healthcare'' analysis unit 1220 performs ``mental habit determination processing'', ``mind habit determination processing'', ``head scale determination processing'', and ``mental scale determination processing'' depending on the question/survey item. It is done by each algorithm. Which question/survey item corresponds to which survey item is designed in advance. Each will be explained below.

The "characteristics related to decision-making in healthcare" analysis unit 1220 analyzes the "mental habit determination process" of the survey information of the "characteristics related to decision-making in healthcare" received in step P05. There are various biases (bias is mainly unconscious movement, so we usually don't notice it, but when humans use their five senses to collect external information, they have a big impact, such as unconsciously shutting down information. Here, it specifically refers to biases that are inherent in genetics.To give a concrete example, for example, humans have a bias to maintain physical safety, and they tend to react to things that are unfamiliar or difficult to understand. The conscious layer recognizes the situation based on the information gathered with directionality by the function of the conscious layer. However, because they go through the decision-making process, they do not know the bias themselves.To put it simply, it is easy to understand the example of getting nervous when you are with a stranger.In healthcare, if there is a motivation to promote social health, it is easy to understand. When it comes to labeling, people with strong and weak biases take different approaches.This trait manifests itself in the Big Five study of extroversion, so it's called "comparing yourself with others." I like to talk with people." It can be quantified by having them select from 6 points that "hardly agree" and 7 points that "strongly disagree."Because it is also a means to investigate unconscious reactions, it is not a questionnaire, but sweating, pupil dilation, heart rate, milliseconds. It is predicted that a survey method based on unconscious biological reactions, such as changes in facial expressions of the unit and changes in tone of voice due to the presence or absence of tension, will be more efficient and more accurate. For such phenomena, it is possible to change the approach considering the bias in advance.For example, there is a "monogatari".By first daring to tell that the "monogatari" is fiction and not about yourself, Because the bias is suppressed, the content comes in. Through the "story", how the frame of understanding the main character and the events that occur around him changes depending on the main character's decisions. By repeating it, it will be remembered as a causal relationship. ) and five-sensory memory (The five-sensory memory is the memory experienced through the five senses during life after birth. Especially, the five-sensory memory in childhood builds a framework in one's unconscious layer as an original experience, and appears as a characteristic in decision-making. There are many things.Since this is also remembered in the unconscious layer, there are things that we do not understand.Because people try to abstract and recognize what they see and experience, they are also abstracted and remembered to some extent in memory. The degree of abstraction differs from person to person, but in terms of five-sensory memory, causality is constructed and remembered at the level of whether it is good for you (whether you like it or not) in light of the framework of your past. In later life, decisions are made based on the above-mentioned directional information gathering, so the behavior becomes a pattern.In this five-sensory memory, the unconscious becomes conscious, and the abstract causal relationship is established. Impressions can be changed by changing the framework.The primary experience categories that are important in healthcare include learning, diet management, exercise, life rhythm, parent-child relationships, friendships, and emotional control. For example, the impressions of "learning things you don't know" are "image you hate" 1 point, "image you don't like" 2 points, "image you don't like or dislike" 3 points, "image you like" 4 points, It can be quantified by having them select from 5 "favorite images".For example, if you have a negative impression of dietary management, you can approach the person subject to health management with just words to convey. The survey information is statistically processed and the distribution is quantified by percentile to judge characteristics. Therefore, the information in the attribute information storage unit 1311 and the bias information storage unit 1380 is used for calculation in the analysis (step P06).

Among the survey information of the “characteristics related to decision-making in healthcare” received in step P05, the “characteristics related to decision-making in healthcare” analysis unit 1220 determines the “head habits” by each individual. Originally possessed cognitive characteristics (cognitive characteristics are the characteristics of how to perceive information obtained from the outside using the five senses, and the habits are quantified and statistically processed. Right-handedness and left-handedness As you can see, the characteristics of cognition differ depending on the person.There are two axes: whether you perceive things abstractly or concretely, and whether you perceive things intuitively or logically. Statistically process the survey information in the four divided quadrants and quantify the distribution by percentile to make a characteristic judgment. To the question "I am searching for a method", the scores were 1 point for ``not at all applicable'', 2 points for ``not applicable'', 3 points for ``somewhat not applicable'', 4 points for ``neither'', and 4 points for ``somewhat applicable''. 5 points, 6 points for "Applicable", and 7 points for "Exactly applicable". ) and behavioral characteristics (behavioral characteristics refer to behavioral characteristics, and the degree to which one's emotions are communicated to others and the world) "Self-expression," which is the degree of wanting others to accept one's thoughts and opinions By statistically processing the survey information on the three axes and quantifying the distribution by percentile, we make a characteristic judgment.Specifically, as a question to measure self-expression, we ask questions such as "I have a very positive personality." In response, they were asked to choose from the following: 1 point for “strongly disagree”, 2 points for “somewhat disagree”, 3 points for “neither agree”, 4 points for “somewhat agree”, and 5 points for “strongly agree”. In order to promote physical health in health care, if there is a health care subject who wants to exercise, the approach will change depending on the degree of self-expression of the health care subject. People with low self-expression are not good at putting their feelings into action, so they take the method of persuading them over and over again. It will be ), and the algorithm is designed taking into account attribute information such as memory of the five senses. Therefore, the information in the attribute information storage unit 1311 is also used for calculation (step P07).

Of the survey information on the “characteristics related to decision-making in healthcare” received in step P05, the “characteristics related to decision-making in healthcare” analysis unit 1220 selects healthcare (WHO’s By statistically processing the presence or absence of literacy and the degree of understanding of health behaviors to promote physical, mental, and social health (definition, physical, mental, and social health) through a survey, character judgment can be made by quantifying the distribution by percentile. conduct. According to the recent definition of health literacy, it is the ability to obtain, understand, evaluate, and utilize health information, and is used in the three areas of health care, disease prevention, and health promotion. are now included. Comprehensive and wide-ranging measures of ability have also been developed to match it. To date, many health literacy scales have been developed as measurement tools, and there are already more than 100. The National Library of Medicine in the United States and the Boston University School of Medicine have created and released the Health Literacy Tool Shed, a database that collects them, so that you can search by selecting the measurement content, number of questions, measurement method, acquisition method, language, etc. . Specifically, if we refer to the HLS-EU-Q47, one of the health literacy evaluation scales, the question to measure the ability to obtain information is, ”, choose from 1 point for “very easy”, 2 points for “somewhat easy”, 3 points for “somewhat difficult”, 4 points for “very difficult”, and 5 points for “don’t know/not applicable”. can be quantified. In health care, the presence or absence of literacy is very effective for intrinsic motivation. Figure out where you are stuck in the framework and take the appropriate approach for each. Therefore, in the analysis, the health information storage unit 1350 is also used for calculation (step P08).
The ``characteristics related to decision-making in healthcare'' analysis unit 1220, among the survey information of the ``characteristics related to decision-making in healthcare'' received in step P05, in the ``measure of mind'' determination processing, Survey information that takes into account the presence or absence of emotional literacy (emotional perception ability, emotional digestion ability, emotional understanding ability, emotional management ability) and the degree of utilization (how much the above emotional literacy is used) is statistically processed, and the distribution is quantified by percentile to determine characteristics. Specifically, self-efficacy, which is used in EQ, etc., is given to the question "I can put my current feelings into words." It can be quantified by having them select from 3 points, 3 points that "apply well", and 4 points that "apply very well". In healthcare, whether a person has a strong sense of self-efficacy or not has a significant impact on decision-making. Conveying images is effective. Therefore, in the analysis, the health information storage unit 1350 is also used for calculation (step P09).

The ``characteristics related to decision-making in healthcare'' analysis unit 1220 analyzes the ``head habits'', the ``mind habits'', the ``head scale'', and the ``mind Algorithms are designed to learn how relevant each factor is to decision-making in care. The method for obtaining the value that motivates specific health behavior is as follows: decision-making predictor (“head habit” value + “heart habit” value) × decision-making support factor (“head ruler” value + “mental habit” value) "measure" value). In addition, weighting is set for each of the decision-making predictor and the decision-making support factor. In the ``characteristics related to decision-making in healthcare'' analysis unit 1220, the integrated personality information is analyzed by performing calculations with these weights taken into consideration (step P10), and stored in integrated personality information storage unit 1330. (Step P11).

Here, the ``characteristics related to decision-making in healthcare'' analysis unit 1220 determines how much the survey information of the ``characteristics related to decision-making in healthcare'' from the health management subject is satisfied, The degree of sufficiency of the survey items of "characteristics related to decision" is calculated, and judgment is made as accuracy of the survey (step P12). The “characteristics related to decision-making in healthcare” analysis unit 1220 sends survey accuracy and A question is sent as to whether or not it is possible to continue the survey of "characteristics related to decision-making in healthcare" (step P13). The user terminal 200, 400, 500, 700 displays questions about the accuracy of the received survey and survey continuation, and the health care subject answers the displayed questions. Information input from the user terminal is transmitted to the healthcare support server 100 via the customer company terminal 900 or directly. The attribute information received by the healthcare support server 100 is sent to the “characteristics related to healthcare decision-making” analysis unit 1220 via the communication unit 110 and the data determination unit 1211 . If the "characteristics related to decision-making in health care" analysis unit 1220 receives the above-mentioned answer "survey can be continued", the process returns to step P03. In the case of "impossible to continue survey", the "characteristics related to decision-making in healthcare" determination process P ends.

FIG. 8 is a flow chart of the transmission method optimization T shown in FIG. When a customer company wants to provide some motivation to a person subject to health care, the customer company terminal 900 transmits the account information of the person subject to health care to be motivated and the content to be conveyed to the healthcare support server 100 ( step T01). The account information and “contents to be conveyed to the user” received by healthcare support server 100 are sent to guidance/pattern creation section 1270 via data determination section 1211 via communication section 110 . Guidance/pattern generating unit 1270 recognizes the received "contents to be conveyed to the user" as a pattern of information of "things to be shown" and "words to be conveyed" (step T02). Next, the guidance/pattern creating unit 1270 comprehensively stores the integrated personality information storage unit 1330, the behavior change story information storage unit 1360, and the attribute information storage unit 1311 based on the account information of the health care subject to whom information is to be provided. Analyze and calculate the individual's "Integrated Personality Classification Information". An appropriate guidance pattern is extracted from the guidance pattern information storage unit 1340 based on the guidance pattern processed in step T02 and the above-mentioned "integrated personality classification information". Guidance pattern creation unit 1270 corrects the wording used in the guidance pattern extracted from guidance pattern information storage unit 1340 to the wording stored in integrated personality information storage unit 1330. An “optimal guidance pattern” is created (step T03) and transmitted to guidance provision timing analysis section 1280 .

The guidance provision timing analysis unit 1280 analyzes which timing is appropriate for the received "optimal guidance pattern" to be given to the target health care recipient. Specifically, there are cases where “characteristics related to decision-making in healthcare” are important, and there are cases where behavior logs of health care recipients are important. Therefore, in order to analyze the "optimal timing", intermittent data from the user-provided information storage unit 1370, the behavior change story information storage unit 1360, the integrated personality information storage unit 1330, and the plurality of user terminals 200 to 800 used by the user are required. The linguistic and non-linguistic information that is obtained is analyzed and judged (step T04). Guidance provision timing analysis unit 1280 sends the “optimal guidance pattern” created in step T03 and the “appropriate timing” created in step T04 to customer company terminal 900 via information output unit 140 and communication unit 110. (step T06).

FIG. 9 is a flow chart of the learning process G shown in FIG. The customer company terminal 900 provides the user terminals 200, 400, 500, and 700 used by the persons subject to health care with "optimal motivational information", and at the same time, provides the same "optimal motivational information" and "providing timing". It also transmits to the healthcare support server 100 . (At this time, a command is also sent to the user terminals 200 to 800 used by the person subject to health care to take a behavior change log and send the data directly to the customer company terminal or the healthcare support server 100. ) The “optimal motivational information” and the “timing of provision” received by healthcare support server 100 are sent to guidance updating section 1290 via communication section 110 and data determining section 1211 (step G01). Guidance updating unit 1290 stores the received “optimal motivational information” and “providing timing” in user-provided information storage unit 1370 . User terminals 200 to 800 transmit log data of behavioral changes of health care recipients via customer company terminal 900 or to healthcare support server 100 based on commands received from customer company terminal 900 . The log data of behavioral change of the person subject to health care received by the healthcare support server 100 is sent to the guidance updating section 1290 via the communication section 110 and the data determination section 1211 . The guidance updating unit 1290 finally updates the “optimal motivational information” displayed on the user terminals 200, 400, 500, and 700, the provision timing, and the log data of the change in behavior of the person subject to health management that has changed accordingly. Analyze and update the behavior change story information storage unit 1360 (step G03). Next, the weighting data in the information in integrated personality information storage section 1330 is recalculated and updated (step G04).

FIG. 10 shows specific exchanges of the “characteristics related to decision-making in healthcare” determination process P, and shows output display on the screens of the user terminals 200 , 500 and 700 . The top two questions (J01-J02) show the process in step P13 of FIG. The third and subsequent questions (J03 to J05) indicate the state in which the survey of "characteristics related to healthcare decision-making" shown in step P04 of FIG. 7 is being conducted. Not only the answers themselves to the questions starting from Question 1, but also the answer times to the questions, etc. are used as survey information for "characteristics related to decision-making in healthcare."

As shown in FIG. 11, the survey information of the “characteristics related to decision-making in healthcare” obtained in the exchange shown in FIG. It is digitized (J06), statistically processed in comparison with the percentile in the database table for each survey item (lower factor) such as "intuition A", "abstraction", "logic", "concrete", and characteristic judgment By doing so, digitization is performed (J07 to J10). Each survey item has a set of high-level factors (“head habits,” “heart habits,” “brain scale,” “heart scale”). Quantification is performed by performing statistical processing and characteristic determination in comparison with percentiles in the hierarchy of "measure" and "measure of mind".

As shown in FIG. 12, the decision-making predictor (J11) derived from the "head habit" value + "mind habit" value quantified by the above process, and the "brain scale" value + The decision support factor (J12) derived by the "measure of mind" value is multiplied by a weight (J13) in each. Furthermore, by multiplying the decision-making predictive factor and the decision-making support factor after the above-mentioned weight correction, statistical processing is performed in comparison with the percentile in the database table in this hierarchy, and the integrated personality information is quantified. (J14). The weight (J13) used here changes as needed according to the learning process G shown in FIG. The above-mentioned integrated personality information (J14) is further combined with attribute information (e.g. marital status, smoking status, etc.) (J15), and decision-making patterns related to behavior change stage transitions that differ for each "characteristic related to healthcare decision-making." For the behavior change story information (J16), each is weighted (J17) and digitized, and the overall variation in the three axes of integrated personality information, attribute information, and behavior change stage information is classified into "integration personality classification information” (J18). The weights used here also change at any time according to the learning process G shown in FIG.

Guidance pattern creation unit 1270 stores wordings used in guidance patterns extracted from guidance pattern information storage unit 1340 (J19) based on the above-described “integrated personality classification information” into integrated personality information storage unit 1330. ``optimal guidance pattern'' is created by correcting the wording stored in .

For example, in the example shown in FIG. 12, the target health care subject is weighted by the weight modified by the past learning process, and the mental characteristic weight is slightly strong. It is determined that the person has "characteristics" and is quantified as integrated personality information (J14). Considering that the attribute information and the behavior change story have a higher weight than the integrated personality information of the health care subject, it is quantified as the integrated personality classification information 7266 (J17). Guidance patterns matching the above-described integrated personality classification information 7266 are extracted in the category of the indifference period as the behavior modification stage and the category of having children as the attribute. The guidance pattern derived from it is the analytical type 11 (shown in Fig. 13) as "what to show (video / image)", and as "words to convey", "first", "efficient", It can be seen that the words "moreover" and "children" are suitable.

FIG. 13 shows a specific output example of "optimal guidance pattern" and "appropriate timing" derived by the above calculation. Analysis type 11 (J20) is shown for display. Analytical type 11 people tend to think abstractly and logically as cognitive traits, and since they have children, it tends to be more effective to mix emotional approaches. As a guidance pattern that shows them, it is busy to do exercise, parent-child communication, and couple communication separately (J21), and shopping with children can solve everything efficiently (J22). are shown graphically. The words you want to convey are selected (J23), and sentence examples corresponding to them are also specified.

In addition, appropriate timing is determined by comparing the timing stored in the behavior modification story information storage unit 1360 and the actual examples stored in the user-provided information storage unit 1370. A close one is selected (J24).
<Supplement>
In addition, in the “characteristics related to healthcare decision-making” determination process P, the processing unit 1200 analyzes not only the survey information of the “characteristics related to healthcare decision-making” but also the received video/image/audio information. Based on this, it also has a function to comprehensively analyze "characteristics related to decision-making in healthcare." Here, video information analysis is to read emotions that are unconsciously dominated from video. It refers to utilizing the tone of voice, flushing of the face, and the degree of sweating due to tension. In addition, the analysis of image information is to analyze the “characteristics related to decision-making in healthcare” of the person subject to health management. Analysis based on Character information is to analyze the "characteristics related to decision-making in healthcare" of persons subject to health management. It is something to do. The analysis of voice information is divided into the one in which voice is converted into characters and analyzed as character information, and the other in which elements are analyzed. The other elements are those that read the unconsciously dominated emotions from the speed of speech, intonation, voice tone due to tension of the vocal cords, and the like. This enables a survey method with a low error rate that does not rely on questionnaires and does not rely on video and audio.

DESCRIPTION OF SYMBOLS 100... Healthcare support server, 110... Communication part, 140... Information output part, 200, 300, 400, 500, 600, 700, 800... User terminal, 900... Customer company terminal, 1200... Processing part, 1211... Data judgment Unit 1212 Account information processing unit 1220 Analysis unit 1270 Guidance/pattern creation unit 1280 Guidance provision timing analysis unit 1290 Guidance update unit 1300 Storage unit 1310 Account information storage unit 1311 Attribute information storage unit 1330 Integrated personality information storage unit 1340 Guidance/pattern information storage unit 1350 Health information storage unit 1360 Behavior change story information storage unit 1370 User provided information storage unit 1380 Bias information storage unit, 1390: investigation information storage unit;

Claims (4)

a storage unit for storing attribute information of a person subject to health care;
a storage unit that stores conscious decision-making characteristic information based on the health management subject's thoughts and unconscious decision-making characteristic information based on the health management subject's emotions;
a storage unit that stores stage information representing the stage in which the person subject to health care currently exists;
a storage unit that stores information about a plurality of guidance patterns that combine images and text to facilitate healthcare decision-making;
a pattern selection processing unit that selects one guidance pattern from the plurality of guidance patterns based on the attribute information, the conscious decision-making characteristic information, the unconscious decision-making characteristic information, and the stage information;
Timing analysis for analyzing timing for transmitting the image and text of the selected guidance pattern to the health care subject based on the conscious decision-making characteristic information, the unconscious decision-making characteristic information, and the stage information. An information processing device comprising a processing unit. Attribute information of a health management subject, conscious decision-making characteristic information based on thinking of the health management subject, unconscious decision-making characteristic information based on emotions of the health management subject, an indifference period of the health management subject, means for selecting one guidance pattern from a plurality of guidance patterns based on stage information indicating whether the current stage is one of the interest stage, the preparation stage, the execution stage, and the maintenance stage;
means for analyzing the timing of transmitting the image and text of the guidance pattern selected based on the conscious decision-making characteristic information, the unconscious decision-making characteristic information, and the stage information to the health care subject; A program for realizing on a computer. a storage unit for storing attribute information of a person subject to health care;
a storage unit that stores health information related to medically verified health;
A storage unit that stores bias information related to various illusions and biases clarified by brain science,
a storage unit that stores information on question survey items for the health care subject;
a determination processing unit that determines mental habits of the health care subject based on answer information from the health care subject to the question survey item, the attribute information, and the bias information;
a determination processing unit that determines the mental habits of the health care subject based on the attribute information and the answer information;
a determination processing unit that determines a scale of the health care subject's head based on the health information and the response information;
a determination processing unit that determines a measure of the health care recipient's mind based on the health information and the answer information;
a determination processing unit that determines the "characteristics related to healthcare decision-making" of the health care subject based on the mental habit, the mental habit, the mental scale, and the mental scale; An information processing device comprising: Based on the health management subject's attribute information, bias information on various illusions and biases clarified by brain science, and answer information from the health management subject to question survey items for the health management subject a means for determining mental habits of a person to be managed;
means for determining the mental habits of the person subject to health care based on the attribute information and the answer information;
means for determining the scale of the health care subject's head based on medically verified health information about health and the answer information;
means for determining the mental scale of the health care subject based on the health information and the answer information;
means for judging the "characteristics related to decision-making in healthcare" of the subject of health care based on the habit of mind, the habit of mind, the scale of the mind, and the scale of the mind; A program to make it happen.

Images