Intervention output device, intervention output method, program for intervention output device and intervention output system

Abstract

To provide an intervention output device, a method and a program, capable of offering an intervention appropriate to an object person.SOLUTION: A method includes: acquiring (S30) an object person answer point obtained by scoring each answer by the object person to each question in a second question group having a question number smaller then a first question number, including questions in a first question group having the first question number; classifying (S34) the object person according to the object person answer point to one of classes clustering other persons other than the object person, based on an other person answer point obtained by scoring each answer by an other person to each question in the first question group; and outputting (S36) an intervention according to a priority of an intervention of a class classified through referring to intervention-class storage means summing by class the priority of intervention supporting fitness in accordance with the other person answer point to a psychological question, in which the first question group includes the psychological question related to a psychological characteristic.SELECTED DRAWING: Figure 22

Description

Technical Field

[0001] The present invention relates to an intervention output device, an intervention output method, a program for an intervention output device, and an intervention output system for a subject in healthcare. It relates to the technical field of

Background Art

[0002] In the field of healthcare, systems for supporting health have been developed to improve health. For example, in Patent Document 1, health information of candidates for implementing an intervention is acquired, and time-series health information acquired from the start of the intervention of an individual who has implemented the intervention is acquired from a storage unit as a health transition with the intervention. Based on the candidate's health information and the health transition with the intervention, the time-series health information of the candidate when the candidate starts the intervention is predicted as a predicted transition with the intervention, and the predicted transition with the intervention is stored in the storage unit. A health transition prediction unit, a processor uses the predicted transition with the intervention to predict, as an effect of the intervention, a duration indicating a period during which the candidate's health improves, and stores the duration in the storage unit. A duration prediction unit, and a processor selects, based on the duration, a subject to whom the intervention is to be performed from the candidates. An analysis system having a support target selection unit is disclosed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the prior art such as Patent Document 1, the determination of the intervention to be implemented was determined by experience or the like, and thus it may not be an intervention suitable for the subject.

[0005] Therefore, an example of the problem of the present invention is to provide an intervention output device or the like that can provide an intervention suitable for a target person.

Means for Solving the Problem

[0006] In order to solve the above problems, the invention according to claim 1 includes a subject response score acquisition means for acquiring a subject response score obtained by scoring each response of a target person to each question in a second question group having a smaller number of questions than the first number of questions, the second question group including questions in a first question group having a first number of questions; a classification means for classifying the target person according to the subject response score into any one of classes obtained by clustering others based on other response scores obtained by scoring each response of others other than the target person to each question in the first question group; and an intervention output means for outputting an intervention according to the priority of the intervention for the classified class with reference to an intervention-class storage means that totals the priority of an intervention for supporting health according to the other response scores for the psychological questions included in the first question group for each class.

[0007] The invention according to claim 9 includes a subject data acquisition means for acquiring data of subject intervention indicating an intervention for supporting health received by a target person and subject response data obtained by measuring the response of the target person to the subject intervention; an evaluation means for evaluating the subject response data; and an intervention output means for outputting an intervention according to the priority of the intervention with reference to an intervention storage means that totals the priority of the intervention based on other response scores obtained by scoring each response of others other than the target person to a question group including psychological questions regarding psychological characteristics, according to the evaluation.

[0008] The invention according to claim 12 includes: a subject response score acquisition step in which a subject response score acquisition means acquires subject response scores obtained by scoring each response of a subject to each question in a second question group having a smaller number of questions than the first number of questions, the second question group including questions in a first question group having a first number of questions; a classification step in which a classification means classifies the subject according to the subject response scores into any one of classes obtained by clustering others based on other response scores obtained by scoring each response of others other than the subject to each question in the first question group; and an intervention output step in which an intervention output means outputs an intervention according to the priority of the intervention for the classified class, with reference to an intervention-class storage means in which the priority of an intervention for supporting health is aggregated for each class according to the other response scores for psychological questions included in the first question group regarding psychological characteristics.

[0009] The invention according to claim 13 includes: a subject data acquisition step in which a subject data acquisition means acquires data on subject interventions indicating interventions received by a subject for supporting health and subject response data obtained by measuring the subject's response to the subject intervention; an evaluation step in which an evaluation means evaluates the subject response data; and an intervention output step in which an intervention output means outputs an intervention according to the priority of the intervention, with reference to an intervention storage means in which the priority of the intervention is aggregated based on other response scores obtained by scoring each response of others other than the subject to a question group including psychological questions regarding psychological characteristics, according to the evaluation. It is characterized by including the above.

[0010] The invention described in claim 14 is characterized in that the computer functions as a subject answer score acquisition means for acquiring a subject answer score obtained by scoring each answer of the subject to each question of a second group of questions having a number of questions less than the first number of questions, including questions of a first group of questions having a first number of questions; a classification means for classifying the subject into one of classes obtained by clustering others based on an other person's answer score obtained by scoring each answer of others other than the subject to each question of the first group of questions, according to the subject answer score; and an intervention output means for outputting an intervention according to the priority of the intervention for the classified class, by referring to an intervention / class storage means which aggregates the priority of interventions to support health for each class according to the other person's answer scores to the psychological questions, wherein the first group of questions includes psychological questions related to psychological characteristics.

[0011] The invention described in claim 15 is characterized in that it functions as an intervention output means that references subject data acquisition means that acquires subject intervention data indicating interventions that support health received by a subject and subject response data that measures the subject's response to the subject intervention, evaluation means that evaluates the subject response data, and intervention storage means that tally up the priority of the intervention based on other person's answer scores that score each answer of others other than the subject to a group of questions including psychological questions about psychological characteristics, and outputs an intervention in accordance with the priority of the intervention in accordance with the evaluation.

[0012] The invention according to claim 16 is an intervention output system comprising a terminal device of a subject who answers questions to receive an intervention for supporting health, and an intervention output device that outputs the intervention presented to the subject based on the answer transmitted from the terminal device. In the intervention output system, the intervention output device has: a subject response score acquisition means for acquiring a subject response score obtained by scoring each answer of the subject to each question in a second question group having a number of questions less than the first number of questions, the second question group including questions in a first question group having a first number of questions; a classification means for classifying the subject according to the subject response score into any of classes obtained by clustering others based on other response scores obtained by scoring each answer of others other than the subject to each question in the first question group; and an intervention output means for outputting an intervention according to the priority of the intervention for the classified class with reference to an intervention-class storage means in which the priority of the battle record intervention is totaled for each class according to the other response scores for the psychological questions included in the first question group.

[0013] The invention according to claim 17 is an intervention output system comprising a terminal device of a subject who answers questions to receive an intervention for supporting health, and an intervention output device that outputs the intervention presented to the subject based on the answer transmitted from the terminal device. In the intervention output system, the intervention output device has: a subject data acquisition means for acquiring data of subject intervention indicating the intervention received by the subject and subject response data measuring the response of the subject to the subject intervention; an evaluation means for evaluating the subject response data; and an intervention output means for outputting an intervention according to the priority of the intervention with reference to an intervention storage means in which the priority of the intervention is totaled based on other response scores obtained by scoring each answer of others other than the subject to a question group including psychological questions related to psychological characteristics, according to the evaluation.

Advantages of the Invention

[0014] According to the present invention, a subject's answer score is obtained by scoring each of the subject's answers to each question in a second group of questions, which has a number of questions less than the first number of questions and includes questions in a first group of questions having a first number of questions; the subject is classified into one of classes obtained by clustering others based on other's answer scores, which are obtained by scoring each answer of others other than the subject to each question in the first group of questions, according to the subject's answer score; the first group of questions includes psychological questions regarding psychological characteristics; and an intervention is output according to the intervention priority of the classified class by referring to an intervention / class storage means which tallys up the priority of interventions to support health for each class according to the other's answer scores to the psychological questions.By outputting an intervention that is appropriate for the subject, since it is the class to which the subject belongs and the intervention is according to the intervention priority of that class, it is possible to provide an intervention that is appropriate for the subject. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a schematic diagram illustrating an example of a general configuration of an information processing system according to an embodiment. [Figure 2] FIG. 10 is a schematic diagram showing an example of classification of question types. [Figure 3] 2 is a block diagram showing an example of a schematic configuration of the information processing server device of FIG. 1. FIG. [Figure 4] FIG. 4 is a diagram showing an example of data stored in the question database of FIG. 3. [Figure 5] FIG. 4 is a diagram showing an example of data stored in the outcome database of FIG. 3. [Figure 6] FIG. 4 is a diagram showing an example of data stored in the intervention information database of FIG. 3. [Figure 7] FIG. 1 is a schematic diagram illustrating an example of classification of types of intervention. [Figure 8] FIG. 4 is a diagram showing an example of data stored in the response database of FIG. 3. [Figure 9] FIG. 4 is a diagram showing an example of data stored in a correlation information database of FIG. 3. [Figure 10] FIG. 10 is a schematic diagram showing an example of correlation between questions. [Figure 11]FIG. 4 is a diagram showing an example of data stored in a class information database of FIG. 3. [Figure 12] FIG. 4 is a diagram showing an example of data stored in a user information database of FIG. 3. [Figure 13] FIG. 4 is a diagram showing an example of data stored in the reaction history database of FIG. 3. [Figure 14] 2 is a block diagram showing an example of a schematic configuration of the mobile terminal device of FIG. 1. FIG. [Figure 15] FIG. 2 is a block diagram showing an example of a schematic configuration of the wearable terminal device of FIG. [Figure 16] 10 is a flowchart illustrating an example of an operation of correlation data calculation. [Figure 17] 10 is a flowchart illustrating an example of a clustering operation. [Figure 18] 10 is a flowchart showing an example of an operation for calculating a second group of questions. [Figure 19] 10 is a flowchart showing an example of an operation for determining the priority of intervention for each class. [Figure 20] FIG. 10 is a schematic diagram showing an example of the priority of intervention for each class. [Figure 21] FIG. 10 is a schematic diagram illustrating an example of a screen displayed on a mobile terminal device. [Figure 22] 10 is a flowchart showing an example of an intervention determination operation. [Figure 23] 10 is a flowchart illustrating an example of an operation for evaluating an intervention. [Figure 24] 10 is a flowchart illustrating a variation of the operation of evaluating an intervention. DETAILED DESCRIPTION OF THE INVENTION

[0016] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Note that the embodiment described below is an embodiment in which the present invention is applied to an information processing system.

[0017] [1. Information processing system configuration and functional overview] First, the configuration of an information processing system 1 according to this embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the general configuration of the information processing system 1 according to this embodiment. The figure is a schematic diagram showing an example of classification of question types.

[0018] As shown in FIG. 1, the information processing system 1 includes an information processing server device 10 (an example of an intervention output device) that classifies a target user T (an example of a subject) and determines an intervention to support health according to the target user T's answers to healthcare questions, a mobile terminal device 20 that transmits the target user T's answers, etc. to the information processing server device 10, a wearable terminal device 30 worn by the target user T, and a supporter terminal device 40 used by a support user S that gives health advice to the target user T. The information processing system 1 is an example of a classification system. The information processing system 1 is also an example of a determination system.

[0019] As shown in FIG. 2 , health-related questions are broadly categorized into questions about the user's personal attributes, environmental factors, psychological characteristics, and physical and mental conditions. The personal attribute questions are further subdivided into questions about age, gender, height, weight, place of residence, occupation, whether or not the user has children, and marital status. The environmental factor questions are subdivided into questions about social support, the exercise environment (e.g., the physical environment for exercise, the environment for exercise near the home, etc.), and the home environment, such as family support for exercise. The psychological characteristics questions are subdivided into personality, service preferences, values, and cognitive function. The physical and mental conditions questions are subdivided into exercise volume, stages of behavioral change, motivation for exercise, health status, lifestyle habits, and medical history. Each of the subcategories contains one or more specific questions. In addition, questions about food preferences and questions about eating habits such as chewing and eating speed may be included in the questions about mental and physical conditions.

[0020] Here, "intervention" means to digitally influence through an app or the like, or to influence by a person such as an expert, with the intention of causing a change in health-related behaviors or lifestyle habits. For example, digital influence includes the display of the number of steps and weight on a smartphone or web app, support for setting goals, formulating exercise plans, and evaluating the degree of achievement. Support for setting goals includes, for example, having the user decide the daily achievement steps on the app. Formulating an exercise plan includes having the user input a plan such as "walk more on weekends". Evaluation of the degree of achievement displays, for example, a one-week review on the display unit of the portable terminal device 20 or the like. Influence by a person includes, for example, health guidance during a medical check-up, personal training at a gym, and health support workshops in companies and local governments. Examples of workshops include prevention of frailty and healthy diet lectures.

[0021] These influences cause changes in the behaviors and lifestyle habits of the target user T. Changes in behaviors and lifestyle habits are observed by measuring the outcome, that is, the variable that is desired to be changed by the intervention. Outcome variables are variables such as physical activity level, nutritional status level, physical condition level, sleep quality, and mental state level. More specifically, in the case of physical activity level, it is the number of steps, the number of stair climbs, in the case of nutritional status level, the number of calories, the number of meals, meal times, chewing times, in the case of physical condition level, the weight value, heart rate, blood pressure value, in the case of sleep quality, the level indicating the depth of sleep and its time, and in the case of mental state level, the stress level, etc.

[0022] The intervention is planned to cause a particular behavior to appear or decrease. A numerical change occurs in the outcome due to the change in that behavior.

[0023] The information processing server device 10, the portable terminal device 20, the supporter terminal device 40, etc. can transmit and receive data to and from each other via the network N, for example, using a communication protocol such as TCP / IP. The network N is constructed by, for example, the Internet.

[0024] Note that the network N may be constructed by a dedicated communication line, a mobile communication network, a gateway, etc. Further, the network N may have an access point Ap. The mobile terminal device 20, the wearable terminal device 30, etc. may be connected to the network N via the access point Ap.

[0025] The information processing server device 10 has the functions of a computer. The information processing server device 10 acquires the subject response scores obtained by scoring each response of the target user T to each question, classifies the target user T, and determines the intervention to be presented to the target user T. The information processing server device 10 is an example of an intervention output device that outputs an intervention to support the health of the subject based on the response transmitted from the terminal device.

[0026] The initial database of the information processing server device 10 is constructed based on basic data and the like obtained from the results of a questionnaire survey for a plurality of users P (an example of others other than the subject). The questionnaire survey includes all the questions shown in FIG. 2.

[0027] Here, the basic data is data digitized from the responses to the questions shown in FIG. 2. Depending on the questionnaire items, the responses to the questions are set to be answerable on a 5-point scale, 7-point scale, etc. and can be scored.

[0028] The mobile terminal device 20 has the functions of a computer. The mobile terminal device 20 is, for example, a smartphone or a tablet terminal. The target user T uses the mobile terminal device 20 to input responses to questionnaire questions and the like. The mobile terminal device 20 transmits the data measured by the wearable terminal device 30 and the data input by the target user T to the information processing server device 10.

[0029] The wearable terminal device 30 has the functions of a computer. The wearable terminal device 30 is, for example, a wristband-type wearable computer. The wearable terminal device 30 has various sensors and measures the number of steps, heart rate, body temperature, etc. The portable terminal device 20 and the wearable terminal device 30 can communicate with each other via wireless communication.

[0030] The supporter terminal device 40 has the functions of a computer. The supporter terminal device 40 is, for example, a personal computer, a laptop computer, a tablet terminal, etc. The supporting user S uses the supporter terminal device 40 to input data such as the basic data of the target user T and the results of the medical interview with the target user T. For example, the supporting user S is a nurse, a health counselor (in a health insurance association, etc.), or a gym trainer. Note that if the target user T inputs or attempts to change behavior alone without the support of the supporting user S, the information processing system 1 may not include the supporter terminal device 40.

[0031] The portable terminal device 20, the wearable terminal device 30, and the supporter terminal device 40 are examples of the terminal devices of the person who answers the questions. Also, the portable terminal device 20, the wearable terminal device 30, and the supporter terminal device 40 are examples of the terminal devices of the person who answers the questions in order to receive an intervention for health support.

[0032] [2. Configuration and Functions of the Information Processing Server Device and Each Terminal Device] (2.1 Configuration and Functions of the Information Processing Server Device 10) Next, the configuration and functions of the information processing server device 10 will be described with reference to the drawings.

[0033] FIG. 3 is a block diagram showing an example of the schematic configuration of the information processing server device 10. FIG. 4 is a diagram showing an example of the data stored in the question database of FIG. 3. FIG. 5 is a diagram showing an example of the data stored in the outcome database of FIG. 3. FIG. 6 is a diagram showing an example of the data stored in the intervention information database of FIG. 3. FIG. 7 is a schematic diagram showing an example of the classification of the types of intervention. FIG. 8 is a diagram showing an example of the data stored in the answer database of FIG. 3. FIG. 9 is a diagram showing an example of the data stored in the correlation information database of FIG. 3. FIG. 10 is a schematic diagram showing an example of the correlation between questions. FIG. 11 is a diagram showing an example of the data stored in the class information database of FIG. 3. FIG. 12 is a diagram showing an example of the data stored in the user information database of FIG. 3. FIG. 13 is a diagram showing an example of the data stored in the reaction history database of FIG. 3.

[0034] As shown in FIG. 3, the information processing server device 10 includes a communication unit 11, a storage unit 12, an output unit 13, an input unit 14, an input / output interface unit 15, and a control unit 16. The control unit 16 and the input / output interface unit 15 are electrically connected via a system bus 17. Also, the information processing server device 10 has a clock function.

[0035] The communication unit 11 is electrically or electromagnetically connected to the network N to control the communication state with the mobile terminal device 20 and the like.

[0036] The storage unit 12 is configured by, for example, a hard disk drive, a solid state drive, or the like. The storage unit 12 stores data related to questions, answer data for questions, classification of interventions, data related to the content of outcomes which are variables to be changed by the interventions, and the like. Also, the storage unit 12 stores various programs such as an operating system and server programs, and various files. Note that the various programs may be acquired, for example, from another server device or the like via the network N, or may be recorded on a recording medium and read via a drive device.

[0037] In addition, the memory unit 12 has constructed therein a question database 12a (hereinafter referred to as "question DB12a"), an outcome database 12b (hereinafter referred to as "outcome DB12b"), an intervention information database 12c (hereinafter referred to as "intervention information DB12c"), an answer database 12d (hereinafter referred to as "answer DB12d"), a correlation information database 12e (hereinafter referred to as "correlation information DB12e"), a class information database 12f (hereinafter referred to as "class information DB12f"), a user information database 12g (hereinafter referred to as "user information DB12g"), a response history database 12h (hereinafter referred to as "response history DB12h"), etc.

[0038] As shown in FIG. 4 , the question DB 12a stores a question ID identifying each question, along with a major category, a question type ID identifying a minor category, and question content. For example, questions about personality, which is a psychological trait, include questions about extroversion, openness, conscientiousness, agreeableness, neuroticism, etc. Questions about service preferences, which are psychological traits, include questions about recording health status data, recording exercises, goal setting, such as what to achieve and what exercises to do, approval from others, exercise preferences, such as whether exercise itself is enjoyable, efficiency, such as being able to exercise while commuting or doing housework, relationships, such as being able to exercise while working hard with others, and rewards, such as receiving points for exercising or being able to send messages. Some questions also include specific examples to make answering easier. These questions are examples of questions in the first question group. The number of these questions is about 200, which is an example of the first number of questions in the first question group. Note that the question DB 12a may have questions in the second question group, the number of questions of which is less than the first number of questions.

[0039] As shown in FIG. 5, the outcome DB 12b stores an outcome type ID, the content of the outcome, etc. in association with an outcome ID indicating each outcome variable. When the outcome ID of the outcome variable indicates "number of steps", the type of the outcome is "physical activity level", and the content of the outcome is "number of steps". When the outcome ID of the outcome variable indicates "body weight", the type of the outcome is "physical activity level", and the content of the outcome is "number of steps". The outcome type ID may be placed in the upper digits of the outcome ID of the outcome variable.

[0040] The intervention information DB 12c stores information regarding the classification of interventions, etc. For example, as shown in FIG. 6, the intervention information DB 12c stores an outcome type ID, an intervention classification ID, the content of the intervention, the question ID of the question related to the intervention, etc. in association with an intervention ID indicating each intervention. As shown in FIG. 7, the interventions are divided into a plurality of hierarchies such as a major classification and a minor classification. The major classification of the intervention is, for example, "self-monitoring" in which the target user T monitors the outcome by himself / herself, "goal setting" in which the target of the outcome of the target user T is set, "reward and threat" in which an incentive or a penalty is given to the target user T according to the outcome, etc. Other examples of the major classification of the intervention include an intervention of "game nature" incorporating competitiveness into the intervention, an intervention of "efficiency" using idle time, etc., an intervention of "social nature" related to others, an intervention of "outcome prediction" providing future health status, etc.

[0041] Furthermore, "Self-monitoring" in major category A is further classified into "behavior monitoring," which monitors outcomes that appear when target user T is taking action, and "result monitoring," which monitors outcomes that appear as a result of target user T's action. Major category B's "goal setting" is further classified into "goal setting," which sets outcome goals for target user T, and "action plan," which sets a plan for achieving outcome goals for target user T. Major category C's "rewards and threats" is further classified into "physical rewards," which give points or the like when outcome goals are achieved, and "social rewards," which send messages or the like when outcome goals are achieved. Note that the intervention category ID may have the part indicating the major category at the top and the part indicating the minor category at the bottom. Separate major category IDs, such as major category ID and minor category ID, may also be used.

[0042] Furthermore, at a higher level than this classification, there is the type of outcome, which is indicated by an outcome type ID. Note that the classification system for interventions does not depend on the type of outcome, so each type of outcome is classified into major categories such as A, B, C, etc., and major category A is further subdivided into A1, A2, etc., and major category B is subdivided into B1, B2, etc.

[0043] More specifically, if the outcome type is "amount of physical activity," examples of interventions for "monitoring behavior" in A1 include "recording daily steps" and "recording number of stairs climbed." Examples of interventions for "monitoring results" in A2 include "recording weight (as an exercise outcome)." Examples of interventions for "setting goals" in B1 include "achieving 10,000 steps." Examples of interventions for "action plans" in B2 include "making a training plan." Examples of interventions for "physical rewards" in C1 include "redeeming points for every 1,000 steps walked." Examples of interventions for "social rewards" in C2 include "sending a message of appreciation when the step goal is achieved." Furthermore, in the intervention information DB 12c, as in the case of "recording daily steps," the intervention ID of this intervention may be associated with the outcome ID of the outcome for the "step count."

[0044] When the outcome type is "nutritional status", the intervention content of subcategory A1 is "let the user record their daily diet", the intervention content of subcategory A2 is "record the skin condition (the result of diet improvement)", the intervention content of subcategory B1 is "achieve a low-carb diet for one week", the intervention content of subcategory B2 is "decide the daily menu", the intervention content of subcategory C1 is "point reduction every time a diet record is entered", the intervention content of subcategory C2 is "a congratulatory message every time fat is reduced", etc.

[0045] Each intervention is particularly associated with a questionnaire on the preference for the service, which is a psychological characteristic. For example, the "self-monitoring" intervention corresponds to a questionnaire on the recording of health status data and a questionnaire on the recording of the exercise or diet performed. The "goal setting" intervention corresponds to a questionnaire on goal setting. The "reward and threat" intervention corresponds to a questionnaire on rewards. The "gamification" intervention corresponds to a questionnaire on the preference for exercise or diet. The "efficiency" intervention corresponds to a questionnaire on efficiency. The "sociality" intervention corresponds to a questionnaire on the approval from the surroundings for exercise or diet, a questionnaire on the relationship with others, etc. The relationship between the intervention and the questionnaire may be an association at the level of major categories of interventions such as "self-monitoring", "goal setting", "reward and threat", "gamification", "efficiency", "sociality", etc., rather than the content of individual specific interventions. That is, the relationship between the intervention and the questionnaire may include the relationship between the type of intervention and the questionnaire. Note that the relationship between the questionnaire and the intervention may be common or have different associations for each outcome type such as "physical activity level" and "nutritional status". As a questionnaire related to the intervention, a questionnaire other than the questionnaire on the preference for the service may also be used. For example, for the questionnaire "Do you have no time to exercise at work?" in the lifestyle questionnaire, an "efficiency" intervention may be corresponded, and for the questionnaire "Do you have a spouse?", a "sociality" intervention may be corresponded. From the questionnaire on the preference for the service, the major category of the intervention is determined, and then the individual specific intervention belonging to that major category may be obtained from the scores of other questionnaires.

[0046] As shown in FIG. 8, the response DB 12d stores, in association with the user ID of user P, question IDs, response contents, response scores, and the like. The response score is calculated from the responses to each question in the questionnaire, that is, values selected on a 5-point scale, 7-point scale, or the like. These response scores indicate basic data such as an individual's attributes (an example of human attributes), the user's environmental factors, the user's psychological characteristics, and the user's physical and mental state. Regarding environmental factors, psychological characteristics, and physical and mental state, the total score calculated from each item may be stored in the response DB 12d. The total score of environmental factors is calculated from the response scores of each question regarding "social support", the response scores of each question regarding "physical environment for exercise implementation", and the like. Note that basic data regarding the target user T is also added to the response DB 12d. When added in this way, this target user T also becomes an example of others other than the target person for other target users T.

[0047] As shown in FIG. 9, the correlation information DB 12e stores correlation information in association with two question IDs indicating between questions. The correlation information is a correlation coefficient (an example of correlation data between questions in the first question group) calculated from the response scores of the two questions indicated by the two question IDs for all users P. As shown in FIG. 10, when each node is associated with each question, the strength of the correlation can be schematically shown by the thickness of the arc connecting each node. As shown in FIG. 10, each question has a network structure of each question via the correlation information. Note that the color of the question node indicates, for example, the category of the question.

[0048] As shown in FIG. 11, the class information DB 12f stores intervention IDs of a plurality of interventions related to a class in association with a class perspective ID and a class ID. A class is a group clustered from a certain perspective based on the number of response points. As a certain perspective, in the case of the personality of psychological characteristics, the class perspective ID indicates "personality", and the class ID indicates "extroversion", "openness", "honesty", "harmony", or "neurotic tendency". Also, when a certain perspective is the exercise environment of environmental factors, Class 1: "Living in the suburbs, there are no exercise facilities such as gyms in the vicinity, but there is an outdoor exercise environment for jogging and walking", Class 2: "Living in the suburbs, there are abundant exercise facilities such as gyms and an outdoor exercise environment", Class 3: "Living in the city center, there are abundant exercise facilities such as gyms, while the outdoor exercise environment is not well - equipped", Class 4: "Living in the city center, neither exercise facilities such as gyms nor the outdoor exercise environment are well - equipped", etc. can be cited. When a certain perspective is the motivation for exercise in terms of physical and mental state, Class 1: "Exercising because exercising itself is fun", Class 2: "Exercising because people around (family, friends, doctors, etc.) are satisfied by exercising", Class 3: "Exercising because physical and mental health is improved by exercising", Class 4: "Exercising because appearance becomes better and more attractive by exercising", etc. can be cited. Also, as a class perspective, a class perspective that crosses human attributes, psychological characteristics, environmental factors, and physical and mental states such as personality × exercise environment, environment × attribute, etc. may be used. For example, in the case of personality × environmental factors, classes may be created by combinations such as Class 1: High extroversion and a well - equipped exercise environment, Class 2: High extroversion and an ill - equipped exercise environment. The intervention IDs of a plurality of interventions are set, for example, for each priority order of the interventions, the first - ranked intervention is the first intervention ID, the second - ranked intervention is the second intervention ID, the third - ranked intervention is the third intervention ID, etc. Note that the intervention IDs of a plurality of interventions related to a class may also be intervention classification IDs such as the first - ranked intervention classification ID, the second - ranked intervention classification ID, and the third - ranked intervention classification ID.

[0049] As described above, the class information DB 12f is an example of intervention-class storage means that associates interventions for supporting health with classes. The class information DB 12f is an example of intervention storage means that aggregates the priority of the intervention based on the other person's response scores obtained by scoring each response of others other than the subject to a questionnaire group including a psychological questionnaire regarding psychological characteristics.

[0050] As shown in FIG. 12, the user information DB 12g stores, in association with the user ID of the target user T, the questionnaire ID, response content, response score, class ID of the classified class, intervention ID of the determined intervention, date and time when the response was made, etc. of the questionnaires in the second questionnaire group. The user information DB 12g may store outcome information due to the intervention received by the target user T.

[0051] As shown in FIG. 13, the response history DB 12h stores, in association with the user ID of the user P, the intervention ID of the applied intervention, the intervention classification ID indicating the type of intervention, the start time of the intervention, the latest time of the intervention, the value of the outcome variable (outcome data), etc. As the value of the outcome variable, values such as the number of steps, heart rate, body temperature, stress level, body weight, etc. are stored in the response history DB 12h together with the measurement time. Note that the measurement time is, for example, a date, and in the case of the number of steps, it is the cumulative value for one day, in the case of the heart rate, it is the average heart rate, in the case of the body temperature, it is the body temperature at the time of waking up, and in the case of the stress level, it is the average stress level. The plot of the value of each outcome variable with respect to the measurement time (day) is the response curve data of each outcome. Note that the intervention classification ID may be absent, or the intervention classification ID may be specified from the intervention ID and the intervention information DB 12c.

[0052] Note that a predetermined value for evaluating the intervention may be stored in the intervention information DB 12c in association with the intervention ID. The predetermined value is, for example, a value obtained by referring to the response history DB 12h, reading out the outcome data, and averaging the outcome data of the user P who received the intervention for each intervention among all the users P who received the intervention. The predetermined value is, in the case of the number of steps, the population average of the number of steps per day, the population average of the cumulative number of steps over a predetermined period, etc.

[0053] When the output unit 13 outputs video, it has, for example, a liquid crystal display element or an EL (Electro Luminescence) element, etc. When the output unit 13 outputs sound, it has a speaker.

[0054] The input unit 14 has, for example, a keyboard and a mouse, etc.

[0055] The input / output interface unit 15 is configured to perform interface processing between the communication unit 11, the storage unit 12, etc. and the control unit 16.

[0056] The control unit 16 has a CPU (Central Processing Unit) 16a, a ROM (Read Only Memory) 16b, a RAM (Random Access Memory) 16c, etc. And the control unit 16 calculates the predicted response curve of each target user T by the CPU 16a reading out and executing the codes of various programs stored in the ROM 16b and the storage unit 12.

[0057] (2.2 Configuration and Functions of the Portable Terminal Device 20) Next, the configuration and functions of the portable terminal device 20 will be described with reference to FIG. 14.

[0058] FIG. 14 is a block diagram showing an example of the schematic configuration of the portable terminal device 20.

[0059] As shown in FIG. 14, the portable terminal device 20 has an output unit 21, a storage unit 22, a communication unit 23, an input unit 24, a sensor unit 25, an input / output interface unit 26, and a control unit 27. And the control unit 27 and the input / output interface unit 26 are electrically connected via a system bus 28. Also, a portable terminal ID is assigned to each portable terminal device 20.

[0060] The output unit 21 has, for example, a liquid crystal display element or an EL element, etc. as a display function. The output unit 32 has a speaker for outputting sound.

[0061] The memory unit 22 is composed of, for example, a hard disk drive, a solid state drive, etc. The memory unit 22 stores various programs such as an operating system and applications for the mobile terminal device 20. Note that the various programs may be acquired from another server device or the like via the network N, or may be recorded on a recording medium and read via a drive device. Further, the memory unit 22 may have information of a database such as the memory unit 12 of the information processing server device 10.

[0062] The communication unit 23 is electrically or electromagnetically connected to the network N and controls the communication state with the information processing server device 10 and the like. Further, the communication unit 23 has a function of wireless communication for communicating with the wearable terminal device 30 by radio waves or infrared rays.

[0063] The input unit 24 has, for example, a touch switch type display panel such as a touch panel. The input unit 24 acquires the position information of the output unit 21 where the user's finger touches or approaches. The input unit 24 has a microphone for inputting voice.

[0064] The sensor unit 25 has various sensors such as a GPS (Global Positioning System) sensor, an azimuth sensor, an acceleration sensor, a gyro sensor, a pressure sensor, a temperature sensor, and a humidity sensor. The sensor unit 25 has imaging elements such as a CCD (Charge Coupled Device) image sensor and a CMOS (Complementary Metal Oxide Semiconductor) image sensor of a digital camera. The mobile terminal device 20 acquires the current position information of the mobile terminal device 20 by the GPS sensor. Note that a unique sensor ID is assigned to each sensor.

[0065] The input / output interface unit 26 performs interface processing between the output unit 21, the memory unit 22, etc. and the control unit 27.

[0066] The control unit 27 is configured with a CPU 27a, a ROM 27b, a RAM 27c, etc. In the control unit 27, the CPU 27a reads out and executes various programs stored in the ROM 27b and the storage unit 22.

[0067] The supporter terminal device 40 has the same configuration and functions as the information processing server device 10 or the mobile terminal device 20 .

[0068] If the supporter terminal device 40 is a personal computer, it has a similar configuration and functions to the information processing server device 10. If the supporter terminal device 40 is a tablet terminal, it has almost the same configuration and functions as the mobile terminal device 20. In addition, each supporter terminal device 40 is assigned a terminal ID.

[0069] 2.3 Configuration and Function of the Wearable Terminal Device 30 Next, the configuration and functions of the wearable terminal device 30 will be described with reference to FIG.

[0070] FIG. 15 is a block diagram showing an example of a schematic configuration of the wearable terminal device 30. As shown in FIG.

[0071] 15, the wearable terminal device 30 includes an output unit 31, a storage unit 32, a communication unit 33, an input unit 34, a sensor unit 35, an input / output interface unit 36, and a control unit 37. The control unit 37 and the input / output interface unit 36 are electrically connected via a system bus 38. A terminal ID is assigned to each wearable terminal device 30. The wearable terminal device 30 has a clock function.

[0072] The output unit 31 has, for example, a liquid crystal display element or an EL element as a display function, a speaker for outputting sounds such as notifications, and the like.

[0073] The memory unit 32 is constituted by, for example, a solid state drive or the like. The memory unit 32 stores various programs such as an operating system and applications for the wearable terminal device 30. Note that the various programs may be acquired from other server devices or the like via the network N through the connected portable terminal device 20, for example.

[0074] The communication unit 33 controls communication with the portable terminal device 20 by wireless communication. The communication unit 33 may be electrically or electromagnetically connected to the network N to control the communication state with the information processing server device 10 or the like.

[0075] The input unit 34 has, for example, a touch switch type display panel such as a touch panel. The input unit 34 acquires the position information of the output unit 31 where the user's finger has touched or is in proximity. The input unit 34 has a microphone for inputting voice.

[0076] The sensor unit 35 includes an acceleration sensor, a gyro sensor, a body temperature (temperature) sensor, a pressure sensor, an ultrasonic sensor, an optical sensor, an electrical sensor, a magnetic sensor, an image sensor, and the like. Note that a unique sensor ID is assigned to each sensor.

[0077] The acceleration sensor measures the acceleration of the wearable terminal device 30. From the measurement data of the acceleration sensor, the movement of the arm of the target user T and the up and down movement of the target user T are measured. The gyro sensor measures the angular acceleration of the wearable terminal device 30. The wearable terminal device 30 measures the number of steps, the posture during sleep, the number of turns in bed, etc. of the target user T using the acceleration sensor and the gyro sensor.

[0078] The body temperature sensor measures the temperature of the contacted part. The pressure sensor measures, for example, the pulse wave. The optical sensor detects the response to the irradiation of electromagnetic waves on the skin or the like, that is, at least one of the reflected wave and the transmitted wave. By the optical sensor, components of blood such as the blood flow velocity and the oxygen concentration of the blood flow are measured. The ultrasonic sensor detects the response to the irradiation of ultrasonic waves, that is, at least one of the reflected wave and the transmitted wave.

[0079] The electrical sensor measures voltage, current, impedance, etc. The electrical sensor measures the electric field generated by muscle activity, blood flow, nerve excitation, etc. The electrical sensor also functions as a chemical sensor, a pH sensor, etc. by detecting components of sweat in combination with electrodes.

[0080] The magnetic sensor measures the magnetic field generated by muscle activity, blood flow, nerve excitation, etc.

[0081] The image sensor detects the skin color, surface temperature, surface movement, blood flow, sweating state, etc.

[0082] Also, the sensor unit includes a GPS sensor, an azimuth sensor, a barometric pressure sensor, etc. The wearable terminal device 30 may measure the moving distance, momentum, etc. by these sensors.

[0083] Also, the microphone of the input unit may capture the snoring or breathing sound of the target user T during sleep.

[0084] The input / output interface unit 36 is configured to perform interface processing between the output unit 31, the storage unit 32, etc. and the control unit 37.

[0085] The control unit 37 is composed of a CPU 37a, a ROM 37b, a RAM 37c, etc. And the control unit 37 causes the CPU 37a to read and execute various programs stored in the ROM 37b and the storage unit 32.

[0086] The wearable terminal device 30 may be of a wristband type, a glasses type, a ring type, a shoe type, a pocket type, a necklace type, a clothing type, etc. The wearable terminal device 30 may be a combination of a wristband type wearable terminal device and a wearable terminal device other than a wristband type, or multiple wearable terminal devices of the same type may be worn.

[0087] [3. Example of operation of information processing system 1] An example of the operation of the information processing system 1 will be described with reference to FIGS.

[0088] (3.1 Example of correlation data calculation) The operation of calculating correlation data will be described with reference to Fig. 16. Fig. 16 is a flowchart showing an example of the operation of calculating correlation data.

[0089] First, a questionnaire survey is conducted on a large number of users P, approximately 20,000 people, for questions in a first question group consisting of approximately 200 questions. For example, the information processing server device 10 transmits an app for answering a questionnaire including each question in the first question group to the mobile terminal device 20 of each user P. Each user P answers the questions on the mobile terminal device 20. The mobile terminal device 20 transmits to the information processing server device 10 the user ID of the user P, each question ID, and answer data of the answer content associated with each question ID. Here, the answer content may be an age value in the case of age, a numerical value representing male or female in the case of gender, a value selected from 1 to 7 in the case of a 7-point answer, etc.

[0090] As shown in FIG. 16, the information processing system 1 acquires answer data for the first set of questions (step S1). Specifically, the information processing server device 10 receives the answer data from the mobile terminal device 20 of each user P. The information processing server device 10 stores, in the answer DB 12d, the answer content and the answer score corresponding to each question ID in association with the user ID. Note that in the case of a seven - level answer, the answer score is “−0.5” for level “1”, “−0.166” for level “2”, “−0.333” for level “3”, “0” for level “4”, “0.166” for level “5”, “0.333” for level “6”, and “0.5” for level “7”. In the case of gender, the answer score is “0.5” for male and “−0.5” for female, etc. In this way, for each question, the answer score is set to a normalized value with 0 in the middle.

[0091] Next, the information processing system 1 calculates correlation data (step S2). Specifically, the information processing server device 10 calculates the correlation coefficient between two questions from the answer scores of the questions, and stores each correlation coefficient in the correlation information DB 12e in association with the combination of question IDs. More specifically, the information processing server device 10 calculates the product of the answer scores for each combination of all questions, totals them for all users P, and calculates the correlation coefficient.

[0092] Next, the information processing system 1 stores the correlation data (step S4). Specifically, the information processing server device 10 stores the value of each correlation coefficient in the correlation information DB 12e in association with each pair of question IDs.

[0093] (3.2 Operation Example of Clustering) The operation of clustering will be described with reference to FIG. 17. FIG. 17 is a flowchart showing an operation example of clustering.

[0094] As shown in FIG. 17, the information processing system 1 acquires response data for the first question group (step S5). Specifically, the information processing server device 10 acquires response data for the first question group as in step S1.

[0095] Next, the information processing system 1 performs clustering (step S6). Specifically, the information processing server device 10 applies a method such as hierarchical clustering or non-hierarchical clustering to the response data to classify each user P into classes and extract feature quantities. Examples of hierarchical clustering include the group average method and the shortest distance method. Examples of non-hierarchical clustering include the k-means method.

[0096] In the case of the perspective of personality, clustering is performed based on the response data of each user P, using "extroversion", "openness", "honesty", "harmony", or "neurotic tendency" as feature quantities. In particular, each user P is classified based on the response scores for the questions regarding personality.

[0097] Next, the information processing system 1 stores class data (step S4). Specifically, the information processing server device 10 stores class data necessary for classification, such as feature vectors in the feature space by the questions of the first question group, center vectors of each class in the feature space (an example of the center coordinates of the class), distances from the center, and data indicating the boundaries of the class regions, in the class information DB12f in association with class IDs. The center coordinates of the class are the average value, median value, etc. of those belonging to the class. Examples of methods for representing the distance from the center coordinates of the class include Euclidean distance and Mahalanobis distance. Also, the class data may be stored in the class information DB12f in association with a class perspective ID indicating differences in the perspectives of personality, exercise environment, and motivation for exercise. Further, after clustering, the class perspective ID and class ID may be stored in the response DB12d, etc. in association with the user ID of each user P.

[0098] (3.3 Operation Example of Calculation of the Second Question Group) An operation example of calculating the second question group will be described with reference to FIG. 18. FIG. 18 is a flowchart showing an operation example of calculating the second question group.

[0099] As shown in FIG. 18, the information processing system 1 acquires data of the first question group (step S10). Specifically, the information processing server device 10 refers to the question DB 12a and acquires data of the first question group.

[0100] Next, the information processing system 1 acquires correlation data (step S11). Specifically, the information processing server device 10 refers to the correlation information DB 12e and acquires correlation data.

[0101] Next, the information processing system 1 acquires class data (step S12). Specifically, the information processing server device 10 refers to the class information DB 12f and acquires class data.

[0102] Next, the information processing system 1 extracts the second question group (step S13). Specifically, the information processing server device 10 calculates the second question group based on the correlation data and / or class data. Questions such as gender and age are included as essential questions in the second question group.

[0103] As an example of calculating the second question group based on class data, from the perspective of personality, questions with high relevance are extracted from each class of "extroversion", "openness", "honesty", "harmony", or "neurotic tendency". And as an example of calculating the second question group based on correlation data and class data, when there are multiple questions with high relevance to a class, in order to further narrow down the questions, based on the correlation data, questions having a correlation coefficient of a predetermined value or more in relation to other questions of the first question group may be selected. In FIG. 10, it is a question with a large number of arcs of a predetermined thickness or more. In particular, when there are multiple questions in one class and some of them are to be selected, this criterion based on correlation data is used.

[0104] Furthermore, in the chain of arcs of correlation with the questions thus extracted, questions with weak links may be extracted and added to the second question group. As a result, a question group that is close to the first question group and has a good balance can be obtained.

[0105] As an example of calculating the second question group based on the correlation data, as shown in FIG. 10, the questions in the first question group are divided among the islands Is of nodes linked with a correlation coefficient equal to or greater than a predetermined value, and some questions are extracted from each island Is to form the second question group. Also, if the total number of questions in the second question group is less than the number of first questions in the first question group, questions other than those extracted from the first question group may be added. For example, additionally, there may be questions that did not exist in the first question group and that one wishes to ask user P or target user T.

[0106] Next, the information processing system 1 stores the second question group (step S14). Specifically, the information processing server device 10 stores the class perspective ID and the class ID in the question DB12a in association with the question ID of the questions in the second question group. Note that the database of the second question group may be separate from the question DB12a. A question group ID may be assigned to the second question group. The question IDs of the questions belonging to the second question group are stored in association with the question group ID.

[0107] (3.4 Operation Example of Intervention Decision for Each Class) An operation example of the intervention decision for each class will be described with reference to FIGS. 19 and 20. FIG. 19 is a flowchart showing an operation example of determining the priority order of intervention for each class. FIG. 20 is a schematic diagram showing an example of the priority order of intervention for each class.

[0108] As shown in FIG. 19, the information processing system 1 acquires answer data for the first question group (step S20). Specifically, the information processing server device 10 acquires answer data for the first question group as in step S1.

[0109] Next, the information processing system 1 acquires class data (step S21). Specifically, the information processing server device 10 acquires class data as in step S12.

[0110] Next, the information processing system 1 totals the scores of the questions about service preferences for each class (step S22). Specifically, the information processing server device 10 divides all users P into classes determined by clustering, and calculates the total score of each question about service preferences for the users P belonging to each class. Note that the information processing server device 10 may total the total scores of each question about service preferences for all users P separately from each class.

[0111] Next, the information processing system 1 determines the priority order of interventions for each class (step S23). Specifically, the information processing server device 10 refers to the intervention information DB 12c including the question IDs of the questions related to the interventions, and obtains the scores of each intervention for each class from the total scores of the questions about service preferences corresponding to each intervention. When a plurality of questions correspond to an intervention, the information processing server device 10 calculates the average of the total scores as the score of the intervention. Note that instead of the intervention ID, an intervention classification ID may be used. In this case, the priority order of the types of interventions is determined for each class, rather than the content of individual specific interventions. As the priority of the intervention, in addition to the priority order of the interventions, the score of the intervention or a value obtained by normalizing the score of the intervention may be used. The information processing server device 10 may total the total scores of each question about service preferences for all users P and determine the priority order of the interventions for the entire user P.

[0112] As shown in Fig. 20, the information processing server device 10 determines the priority of interventions for each class in descending order of intervention scores according to the priority of the interventions. Fig. 20 shows the priority of the types of interventions. For example, the priority of the types of interventions is as follows: for class A, "reward and threat", "efficiency", "game-like", etc.; for class B, "self-monitoring", "efficiency", "game-like", etc.; and for class C, "efficiency", "reward and threat", "game-like", etc. In addition, the priority of an intervention may be calculated down to the level of a subcategory of the intervention, such as "behavior monitoring" or "result monitoring." The priority of an intervention may also be calculated down to the level of individual, specific intervention content, such as "recording the number of steps taken daily" or "recording the number of stairs climbed." After the information processing server device 10 has determined the major category of intervention, "self-monitoring," it may calculate which of the minor categories of intervention, "behavior monitoring" or "result monitoring," to prioritize, and / or the ranking of individual, specific interventions, such as "recording the number of steps taken daily," from the scores of questions other than the question regarding service preference, which is a psychological characteristic. For interventions in a major category, such as "self-monitoring," an individual, specific intervention, such as "recording the number of steps taken daily," may be predetermined as a default to be presented.

[0113] Next, the information processing system 1 stores the results (step S24). Specifically, the information processing server device 10 stores the intervention IDs corresponding to the upper-level questions of each class in the class information DB12f in association with the class perspective ID and the class ID in descending order of the total score. The first intervention corresponds to the first intervention ID, the second intervention corresponds to the second intervention ID, the third intervention corresponds to the third intervention ID, and so on. In this way, the intervention IDs are stored in order as the priorities of the interventions. Note that, as the priorities stored in the class information DB12f, the scores of the interventions and the values obtained by normalizing the scores of the interventions may also be stored in association with the intervention IDs such as the first intervention ID, the second intervention ID, and the third intervention ID. As an example of the intervention storage means that aggregates the priorities of the interventions based on the other person answer scores obtained by scoring each answer of a person other than the subject for the question group including the psychological questions regarding the psychological characteristics, the priority order of the interventions for the entire user P may be stored in the storage unit 12.

[0114] (3.5 Operation Example of Intervention Determination) An operation example of the operation of the information processing server device 10 according to the present embodiment in response to a request from the mobile terminal device 20 will be described with reference to the drawings. FIG. 21 is a schematic diagram showing an example of a screen displayed on the mobile terminal device 20. FIG. 22 is a flowchart showing an operation example of intervention determination.

[0115] The target user T who answers the questions in the second question group activates the dedicated application. As shown in FIG. 21, the questions in the second question group are sequentially displayed on the display of the output unit 21 of the mobile terminal device 20 of the target user T. The target user T answers according to the questions in the second question group. Note that the support user S who provides health advice may input the answers of the target user T using the supporter terminal device 40 while asking questions to the target user T. Further, the second question group may be extracted by the information processing server device 10 with reference to the question DB12a based on the class perspective or the like and incorporated into the dedicated application in advance, or may communicate with the mobile terminal device 20 to transmit the second question group to the mobile terminal device 20.

[0116] The mobile terminal device 20 transmits the input answer data to the information processing server device 10 together with the question group ID of the second question group and the user ID of the target user T. When the supporting user S inputs to the supporter terminal device 40, the supporter terminal device 40 transmits the input answer data to the information processing server device 10 together with the user ID of the target user T.

[0117] As shown in FIG. 22, the information processing system 1 acquires the answer data of the target person (step S30). Specifically, the information processing server device 10 acquires the user ID of the target user T, the answer data as an example of the target person's answer score, and the question group ID of the second question group from the mobile terminal device 20. The information processing server device 10 stores the answer data in the answer DB 12d or the like together with the received user ID of the target user T. In this way, the information processing server device 10 functions as an example of a target person answer score acquisition means for acquiring the target person answer score obtained by scoring each answer of the target person to each question of the second question group having a question number less than the first question number, including the questions of the first question group having the first question number.

[0118] Next, the information processing system 1 acquires class data (step S31). Specifically, the information processing server device 10 refers to the class information DB 12f to acquire class data.

[0119] Next, the information processing system 1 acquires correlation data (step S32). Specifically, the information processing server device 10 refers to the correlation information DB 12e and acquires the correlation coefficient between one question not belonging to the second question group and each question belonging to the second question group among the first question groups based on the question ID of one question not belonging to the second question group and the question ID of each question belonging to the second question group. This is repeated until the correlation coefficient is acquired for all questions not belonging to the second question group.

[0120] Next, the information processing system 1 estimates the response scores (step S33). Specifically, the information processing server device 10 calculates the estimated response scores of the questions in the first question group from the response scores of the questions in the second question group and the correlation coefficients between the questions in the first question group and the questions in the second question group. For example, p = A px1 ×x1 + A px2 ×x2 + A px3 ×x3 + ··· (Equation 1) From this, the information processing server device 10 calculates the estimated response scores of a predetermined question in the first question group. Here, p is the estimated response score of the predetermined question in the first question group to be estimated, x1, x2, x3 ··· are the response scores of the questions in the second question group, and A px1 , A px2 , A px3 , ··· are the correlation coefficients between the predetermined question in the first question group and each question in the second question group. The information processing server device 10 calculates the estimated response scores for all questions in the first question group other than the questions in the second question group according to Equation 1. Note that the estimated response scores may be corrected so that the range of the estimated response scores falls within a predetermined range.

[0121] In this way, the information processing server device 10 functions as an example of a response score estimation means for estimating the estimated response scores of the subject for each question in the first question group based on the subject response scores according to the correlation data between the questions in the first question group calculated from the other person's response scores. The information processing server device 10 functions as an example of a response score estimation means for calculating the estimated response scores of the subject for the questions in the first question group to be estimated from the correlation coefficients between the questions in the first question group to be estimated and each question in the second question group and the subject response scores.

[0122] Next, the information processing server device 10 stores the estimated response scores in the user information DB12g in association with the user ID and question ID of the target user T.

[0123] Next, the information processing system 1 classifies according to the estimated response score (step S34). Specifically, the information processing server device 10 refers to the class data in the class information DB12f, and based on a predetermined class perspective ID, determines the class to which the target user T belongs from the response scores and estimated response scores of each question in the second question group of the target user T. The information processing server device 10 stores the class perspective ID and the class ID of the classified class in the user information DB12g together with the date, in association with the user ID of the target user T.

[0124] In this way, the information processing server device 10 functions as an example of classification means for classifying the target person according to the target person's response score and the estimated response score of the target person into one of the classes obtained by clustering the others according to the other person's response score. The information processing server device 10 functions as an example of classification means for determining the class to which it belongs from the center coordinates of the class, the target person's response score, and the estimated response score of the target person in the feature space by the questions of the first question group.

[0125] Next, the information processing system 1 determines the intervention to be presented to the target person according to the classified class (step S35). Specifically, the information processing server device 10 refers to the class information DB12f that stores the priority order of intervention for each class determined in step S23, reads the corresponding intervention ID based on the class perspective ID and the class ID of the classified class, and refers to the intervention information DB12c with this intervention ID to obtain the intervention to be presented to the target person (including the type of intervention). The information processing server device 10 stores the read intervention ID in the user information DB12g together with the date, in association with the user ID of the target user T. Note that the information processing server device 10 may also read the intervention score and the value obtained by normalizing the intervention score. The intervention to be presented to the target person may be only the intervention corresponding to the first intervention ID, or a plurality of upper-level interventions.

[0126] Next, the information processing system 1 outputs the result (step S36). Specifically, the information processing server device 10 transmits the classification result of the class viewpoint ID and the class information of the classified class, and the intervention ID of the determined intervention to the mobile terminal device 20 of the target user T. The mobile terminal device 20 of the target user T displays the class viewpoint, the class, and the intervention on the display of the output unit 21 by means of a dedicated application. For example, when the target user T is classified into class B, the mobile terminal device 20 displays on the display of the output unit 21 that "Your personality class is B, the recommended type of intervention is 'Self-monitoring', and please record your daily steps." Note that a plurality of specific interventions belonging to "Self-monitoring" may be displayed with priorities. Further, the information processing server device 10 may transmit health care advice or the like according to the determined class to the mobile terminal device 20 of the target user T.

[0127] In this way, the information processing server device 10 functions as an example of an intervention output means that refers to the intervention-class storage means in which the first questionnaire group includes psychological questionnaires related to psychological characteristics and the priorities of interventions for supporting health are aggregated for each class according to the other-person response scores for the psychological questionnaires, and outputs an intervention according to the priority of the intervention of the classified class.

[0128] Next, according to the display of the dedicated application, the target user T selects an intervention to receive. For example, when aiming to improve health by walking, the intervention of "recording the daily number of steps" is selected. The mobile terminal device 20 transmits the intervention ID or outcome ID of the selected intervention together with the user ID of the target user T to the information processing server device 10. The information processing server device 10 stores the intervention ID and the date of the intervention start time in the reaction history DB12h together with the received user ID of the target user T.

[0129] Next, the mobile terminal device 20 connects to the wearable terminal device 30 at a predetermined interval and acquires information such as the number of steps and heart rate from the wearable terminal device 30. The mobile terminal device 20 may calculate the number of steps from information such as acceleration from an acceleration sensor or the like of the wearable terminal device 30.

[0130] The target user T receives the intervention by viewing the daily step count displayed on the mobile terminal device 20 for an initial measurement period of one week, and inputting the number of steps walked each day into an app or recording it on a record sheet. If the intervention is to "record the number of steps every day," it is preferable to have the target user T consciously do the task. The mobile terminal device 20 may be configured to notify the target user T of the number of steps taken yesterday and the current day at a predetermined time at least once a day. Daily weight may also be input. The intervention does not have to be once a day, and the current number of steps may be notified or input at predetermined intervals, such as every hour, every two hours, or every three hours.

[0131] The mobile terminal device 20 transmits information such as the cumulative number of steps taken in a day and the average heart rate together with the user ID of the target user T to the information processing server device 10. The information processing server device 10 stores the received information such as the number of steps taken and the heart rate together with the user ID of the target user T as the subject's response curve data together with the date in the response history DB 12h. The data at the latest intervention point in the response history DB 12h is updated.

[0132] (3.6 Example of Intervention Evaluation) Next, an example of an operation for evaluating an intervention after an intervention is implemented for a target user T will be described with reference to Fig. 23. Fig. 23 is a flowchart showing an example of an operation for evaluating an intervention.

[0133] As shown in FIG. 23, the information processing system 1 acquires subject response data (step S40). Specifically, the information processing server device 10 reads out user data such as the class ID of the class to which the target user T belongs, the intervention ID of the subject intervention indicating the intervention received by the target user T, etc. from the user information DB 12g based on the user ID of the target user T. The information processing server device 10 acquires the subject response data of the target user T from the response history DB 12h based on the user ID of the target user T, that is, the time-series data of the outcome variables during a specific measurement period from the start time of the intervention, which is the outcome data of the intervention. In this way, the information processing server device 10 functions as an example of subject data acquisition means for acquiring the data of the subject intervention indicating the intervention received by the subject and the subject response data measuring the response of the subject to the subject intervention.

[0134] Next, the information processing system 1 evaluates the intervention (step S41). Specifically, the information processing server device 10 refers to the intervention information DB 12c, reads out a predetermined value of the outcome data corresponding to the intervention based on the intervention ID, and compares it with the subject response data of the target user T to evaluate the intervention. More specifically, when the subject response data is data on the number of steps, the information processing server device 10 compares statistical values such as the number of steps per day, the cumulative number of steps, and the trend of the number of steps of the target user T with the corresponding predetermined values. Note that cases where the evaluation is poor include not reaching the target value, having no improvement trend, having the opposite change direction, etc. Cases where the evaluation is good include reaching the target value, having a change in the improvement direction of a certain amount or more, etc. Whether the change amount of the outcome data is equal to or greater than a predetermined value, whether the direction of the change of the outcome data is positive or negative as a predetermined value, etc. are evaluated. In this way, the information processing server device 10 functions as an example of evaluation means for evaluating the subject response data. The information processing server device 10 functions as an example of evaluation means for performing the evaluation according to the comparison between the value of the subject response data and a predetermined value.

[0135] Next, the information processing system 1 determines whether it is equal to or greater than a predetermined value (step S42). Specifically, when the target person response data is the number of steps data, the information processing server device 10 compares the number of steps in a day or the cumulative number of steps of the target user T with a corresponding predetermined value to determine whether it is equal to or greater than the predetermined value. When the outcome data is the weight and the purpose is weight loss, it is determined whether it is equal to or less than the predetermined value.

[0136] When the evaluation is not equal to or greater than the predetermined value (step S42: NO), the information processing system 1 selects the intervention of the next priority (step S43). Specifically, the information processing server device 10 refers to the class information DB12f based on the class ID of the class to which the target user T is classified, obtains the intervention ID of the next intervention with a lower priority than the current intervention, and selects the intervention of the next priority. For example, when the target user T is classified into class B and the major classification of the previous intervention is "self-monitoring", the intervention of the next major classification "efficiency" is selected. Further, an intervention belonging to "efficiency" is selected.

[0137] Next, the information processing system 1 outputs the result (step S44). Specifically, the information processing server device 10 transmits the intervention ID and / or the intervention classification ID of the next priority intervention to the mobile terminal device 20 of the target user T. The mobile terminal device 20 of the target user T displays the intervention of the next priority on the display of the output unit 21 by a dedicated application. For example, the major classification "efficiency" of the next priority intervention and the interventions belonging to "efficiency" are displayed. Note that a plurality of interventions belonging to "efficiency" which is the next priority may be displayed and the target user T may select the intervention to be implemented. In this way, the information processing server device 10 functions as an example of an intervention output means that refers to the intervention / class storage means and outputs an intervention according to the priority of the intervention according to the evaluation.

[0138] When the evaluation is equal to or greater than the predetermined value (step S42: YES), the information processing system 1 outputs the result (step S44). Specifically, the information processing server device 10 displays that the evaluation of the result of the intervention is good.

[0139] Note that, according to the evaluation, the values of the intervention IDs of the first intervention ID, the second intervention ID, and the third intervention ID in the class information DB12f may be changed. The information processing server device 10 may aggregate the results of interventions for various target users T, increase the intervention priority if the evaluation is good, and decrease the priority if it is bad. For example, in the class information DB12f, the information processing server device 10 changes the intervention scores associated with the intervention IDs such as the first intervention ID, the second intervention ID, and the third intervention ID, and the priorities of the values obtained by normalizing the intervention scores according to the evaluation. If the priorities are reversed, the intervention order is swapped. In this way, the information processing server device 10 functions as an example of a priority change means for changing the intervention priority in the class to which the target person belongs in the intervention / class storage means according to the evaluation.

[0140] As described above, according to the present embodiment, by obtaining the target person's response scores obtained by scoring each response of the target user T to each question in the second question group having a smaller number of questions than the first question group including the questions in the first question group having the first number of questions, and classifying the target user T according to the target person's response scores into any of the classes obtained by clustering the user P based on the other person's response scores obtained by scoring each response of the user P other than the target user T to each question in the first question group, and referring to the class information DB12f which is an example of the intervention / class storage means that aggregates the priorities of interventions for supporting health according to the other person's response scores for the psychological questions included in the first question group for each class, and outputting an intervention according to the intervention priority of the classified class, since it is the class to which the target user T belongs and the intervention is according to the intervention priority of that class, an intervention suitable for the target user T can be provided. When the intervention to be presented is of the type of intervention, a plurality of interventions belonging to the same type can be displayed for the target user T to select. Since there is a priority order, if the result of the intervention does not occur, the next intervention can be output and proposed to the target user T.

[0141] Also, it is possible to know the intervention to be presented from the class to which the target user T belongs. Also, since it is possible to provide interventions unified by class, the analysis of the outcomes due to the interventions can be analyzed at the class level. Also, since each question in the second question group with a smaller number of questions than the first question number is answered, the burden on the target user T to answer can be reduced.

[0142] An example of an intervention storage means that acquires data on the target person's intervention indicating the intervention for supporting the health received by the target user T and target person response data measuring the response of the target user T to the target person's intervention, evaluates the target person response data, and aggregates the priority of the intervention based on the scores of each answer of the other user P other than the target user T to a question group including psychological questions regarding psychological characteristics. By referring to the class information DB12f and outputting an intervention according to the priority of the intervention according to the evaluation, it is the class to which the target user T belongs, and it is an intervention according to the priority of the intervention of that class. Therefore, an intervention suitable for the target user T can be provided.

[0143] When acquiring data on the target person's intervention indicating the intervention received by the target user T and target person response data measuring the response of the target user T to the target person's intervention, evaluating the target person response data, referring to the class information DB12f, and outputting an intervention according to the priority of the intervention according to the evaluation, an intervention suitable for the target user T can be provided based on the evaluation. In particular, even when the evaluation is poor, an intervention more suitable for the target user T can be provided by indicating the next priority order.

[0144] When evaluating according to the comparison between the value of the target person response data and a predetermined value, the evaluation can be quantitative.

[0145] When changing the priority of the intervention in the class to which the target user T belongs in the class information DB12f or the like according to the evaluation, the actual effect of the intervention can be measured, the DB can be improved, and the accuracy of the intervention for other target persons can be improved.

[0146] When the subject's answer score is used to estimate the estimated answer score of the target user T for each question in the first group of questions, based on the correlation data between the questions in the first group of questions calculated from the answer scores of others, and the subjects are classified according to the subject's answer score and the estimated answer score of the target user T, in addition to the subject's answer scores for a relatively small number of questions, the estimated answer scores for unanswered questions are also used, thereby improving the accuracy of information processing such as classifying the target user T based on the answers, and also improving the accuracy of information processing such as determining the intervention of the target user T based on the answers.

[0147] When calculating the subject's estimated answer score for the questions in the first group of questions to be estimated from the correlation coefficient between the questions in the first group of questions to be estimated and each question in the second group of questions, and the subject's answer score, the estimated answer score for unanswered questions can be accurately calculated from the product sum of each subject's answer score and each correlation coefficient, which can improve the accuracy of information processing such as classifying subjects based on their answers.In addition, the accuracy of classification can be improved, and the accuracy of information processing such as determining the intervention of target user T can be improved.

[0148] In the feature space based on the questions in the first group of questions, when determining the class to which the subject belongs based on the class center coordinates and the subject's answer score, the class is determined by calculating the distance from the class center coordinates not only from the subject's answer score but also from the estimated answer score, thereby improving accuracy and class classification accuracy, and also improving the accuracy of information processing such as determining the intervention of the target user T.

[0149] If the questions in the first group of questions include questions about a person's attributes, psychological characteristics, environmental factors, and physical and mental state, and the classes are based on the perspective of a person's attributes, psychological characteristics, environmental factors, and / or physical and mental state, in addition to the subject's answer scores for a relatively small number of questions, estimated answer scores for unanswered questions are also used, thereby making it possible to more accurately classify the target user T into a healthcare-related class.

[0150] When the questions in the second question group include at least questions related to human attributes and questions related to psychological characteristics, it is advantageous for information processing such as classification of psychological characteristics.

[0151] (Modification example of the operation for evaluating intervention) Next, a modification example of the operation for evaluating intervention will be described with reference to FIG. 24. In addition, for the same or corresponding parts as those in the above-described embodiment, only different configurations and operations will be described using the same reference numerals. The same applies to other embodiments and modification examples.

[0152] FIG. 24 is a flowchart showing a modification example of the operation for evaluating intervention.

[0153] The target user T who answers the questions in the second question group again starts a dedicated application for re-implementation. The target user T answers again according to the questions in the second question group. The mobile terminal device 20 transmits the input answer data to the information processing server device 10 together with the question group ID of the second question group and the user ID of the target user T.

[0154] As shown in FIG. 24, the information processing system 1 acquires the answer data of the subject as in step S30 (step S50). In this way, the information processing server device 10 functions as an example of a subject answer score acquisition means for acquiring the subject answer scores for each question in the second question group that has been re-implemented.

[0155] Next, the information processing system 1 acquires the subject response data of the target user T, which is the outcome data of the intervention result, as in step S40 (step S51).

[0156] Next, the information processing system 1 evaluates the intervention from the subject response data of the target user T as in step S41 (step S52).

[0157] Next, the information processing system 1 reclassifies the target user T based on the response data (step S53). Specifically, the information processing server device 10 performs the processes of steps S31, S32, S33, and S34 on the acquired response data to determine the class of the target user T again based on the response data. The information processing server device 10 associates the class viewpoint ID and the class ID of the classified class with the user ID of the target user T and stores them in the user information DB 12g together with the date of reclassification. In this way, the information processing server device 10 functions as an example of a classifying means for classifying the target user T according to the target user's response score of the re-execution.

[0158] Next, the information processing system 1 determines whether or not the statistical value of the subject response data of the target user T is equal to or greater than a predetermined value, as in step S42 (step S54).

[0159] If the evaluation is equal to or greater than a predetermined value (step S54: YES), the information processing system 1 determines whether the class has changed (step S55). Specifically, the information processing server device 10 refers to the user information DB 12g and compares the class into which the target user T was previously classified with the reclassified class based on the user ID of the target user T. The information processing server device 10 compares the class into which the target user T was previously classified with the reclassified class, and determines that there has been no change in the class if the class IDs are the same, and that there has been a change in the class if the class IDs are different.

[0160] If the evaluation is equal to or greater than a predetermined value and the class has not changed (step S55: NO), the information processing system 1 outputs the result (step S56). Specifically, the information processing server device 10 transmits information to the mobile terminal device 20 of the target user T that the evaluation of the intervention result was good and that the class has not changed. The mobile terminal device 20 displays on the display of the output unit 21 that the evaluation of the intervention result was good and that the class has not changed.

[0161] When the evaluation is equal to or higher than a predetermined value and the class has changed (step S55: YES), the information processing system 1 selects the intervention of the higher order of the changed class (step S57) and outputs the result (step S56). Specifically, the information processing server device 10 refers to the class information DB12f that stores the priority order of intervention for each class, and reads the first intervention ID based on the class ID of the reclassified class. When the read first intervention ID is the same as the class ID of the reclassified class, the second intervention ID is read. In this way, the intervention of the higher order of the changed class is selected. In this way, the information processing server device 10 functions as an example of an intervention output means that outputs an intervention according to the priority of the intervention of the classified class by the re - execution.

[0162] Next, the information processing server device 10 refers to the intervention information DB12c based on the read first intervention ID, and obtains the intervention to be presented to the target person. The information processing server device 10 transmits information indicating that the evaluation of the result of the intervention was good and that a new intervention is also recommended because the class has changed, to the mobile terminal device 20 of the target user T. The mobile terminal device 20 displays on the display of the output unit 21 that the evaluation of the result of the intervention was good and that a new intervention is also recommended because the class has changed.

[0163] When the evaluation is not equal to or higher than the predetermined value (step S54: NO), the information processing system 1 determines whether the class has changed as in step S55 (step S58).

[0164] When the evaluation is not equal to or higher than the predetermined value and the class has not changed (step S58: NO), the information processing system 1 selects the intervention of the next priority order as in step S43 (step S59), and outputs the result as in step S44 (step S56).

[0165] If the evaluation is not equal to or greater than the predetermined value and the class has changed (step S58: YES), the information processing system 1 selects the next-priority intervention and / or selects a higher-ranked intervention for the changed class (step S58) and outputs the result (step S56). Specifically, the information processing server device 10 selects the next-priority intervention as in step S43 and / or, as in step S58, refers to the class information DB 12f and reads out the first intervention ID based on the class ID of the reclassified class. The information processing server device 10 transmits information to the mobile terminal device 20 of the target user T indicating that a new intervention is also recommended because the evaluation of the intervention result was poor and / or that a new intervention is also recommended because the class has changed, and the mobile terminal device 20 displays this information on the display of the output unit 21. In this way, the information processing server device 10 functions as an example of an intervention output means that outputs an intervention according to the priority of the intervention for the class classified by the re-implementation.

[0166] The information processing system 1 may determine whether the time has passed for a predetermined period or more, and if so, may send a re-answer notification. Specifically, the information processing server device 10 refers to the user information DB 12g and reads out the date and time of the previous classification into a class and the date and time of the previous intervention determination based on the user ID of each target user T. The information processing server device 10 determines whether a predetermined period or more has passed since the read out date and time. Because personal attributes and environmental factors often change over the course of several years due to factors such as transfers and marriage, the predetermined period is preferably set to one year. The predetermined period does not have to be uniform for each target user T. For example, the predetermined period may be set after the next health check or may be changed depending on the frequency of access to a healthcare app. If the frequency of access to a healthcare app is high, the predetermined time is shortened.

[0167] As described above, according to this modified example, by obtaining the respondent answer scores for each question in the second question group that has been implemented again, classifying the target user T according to the respondent answer scores of the repeated implementation, and outputting an intervention according to the priority of the intervention for the class classified by the repeated implementation, even if factors such as job transfer and marriage cause changes in personal attributes and environmental factors, it is possible to present an intervention suitable for the target user T at that time.

[0168] When obtaining the respondent answer scores for each question in the second question group that has been implemented again after a predetermined period, and classifying the target user T into any class according to the respondent answer scores and the estimated answer scores of the target user T in the results of the repeated implementation, after several years, due to factors such as job transfer and marriage, personal attributes and environmental factors often change. However, by notifying after a predetermined period, it is possible to detect changes in the class to which the target user T belongs.

[0169] When obtaining the respondent answer scores for each question in the second question group that has been implemented again after a predetermined period, classifying the target user T into any class according to the respondent answer scores and the estimated answer scores of the target user T in the results of the repeated implementation, and determining the intervention to be presented to the target user T according to the class classified by the results of the repeated implementation, after several years, due to factors such as job transfer and marriage, personal attributes and environmental factors often change. However, by notifying after a predetermined period, it is possible to present an intervention suitable for the target user T at that time.

[0170] When obtaining the respondent answer scores for each question in the second question group that has been implemented again after a predetermined period, and determining the intervention to be presented to the target user T according to the respondent answer scores and the estimated answer scores of the target user T in the results of the repeated implementation, after several years, due to factors such as job transfer and marriage, personal attributes and environmental factors often change. However, by notifying after a predetermined period, it is possible to present an intervention suitable for the target user T at that time.

[0171] Furthermore, the present invention is not limited to the above-described embodiments. The above-described embodiments are examples, and any configuration that has substantially the same configuration as the technical idea described in the claims of the present invention and exhibits the same operational effects is included in the technical scope of the present invention.

Explanation of Reference Numerals

[0172] 1: Information processing system (intervention input / output system) 10: Information processing server device (intervention input / output device) 12: Storage unit (intervention storage means) 12f: Class information database (intervention / class storage means, intervention storage means) 20: Portable terminal device (terminal device) 30: Wearable terminal device (terminal device) 40: Supporter terminal device (terminal device) T: Target user (target person) P: Other user (other person)

Claims

1. Subject response score acquisition means for acquiring subject response scores obtained by scoring each response of a subject to each question in a second question group having a smaller number of questions than the first number of questions, including questions in the first question group having the first number of questions; Classification means for classifying the subject according to the subject response scores into any one of the classes obtained by clustering others based on the other response scores obtained by scoring each response of others other than the subject to each question in the first question group; Intervention output means for outputting an intervention according to the priority of the intervention for the classified class with reference to the intervention / class storage means that totals the priority of the intervention for health support according to the other response scores for the psychological questions included in the first question group for each class; An intervention output device characterized by comprising the above.

2. In the intervention output device according to Claim 1, Subject data acquisition means for acquiring data on subject intervention indicating the intervention received by the subject and subject response data measuring the subject's response to the subject intervention; Evaluation means for evaluating the subject response data; further comprising, The intervention output means outputs an intervention according to the priority of the intervention with reference to the intervention / class storage means according to the evaluation. An intervention output device characterized by this.

3. In the intervention output device according to Claim 2, The evaluation means evaluates according to the comparison between the value of the subject response data and a predetermined value. An intervention output device characterized by this.

4. In the intervention output device according to Claim 2 or Claim 3, According to the evaluation, a priority change means for changing the priority of the intervention in the class to which the subject belongs in the intervention / class storage means is further provided. An intervention output device characterized by this.

5. In the intervention output device according to Claim 1 or Claim 2, The subject response score acquisition means acquires the subject response scores for each question in the second question group that has been implemented again, The classification means classifies the subject according to the subject response scores of the re-implementation, The intervention output means outputs an intervention according to the priority of the intervention for the class classified by the re-implementation. An intervention output device characterized by this.

6. In the intervention output device according to Claim 1 or Claim 2, Answer score estimation means for estimating the estimated answer score of the subject for each question in the first question group based on the subject answer score according to the correlation data between the questions in the first question group calculated from the other person's answer scores is further provided. The classification means classifies the subject according to the subject answer score and the estimated answer score of the subject. An intervention output device characterized by this.

7. In the intervention output device according to claim 6, The answer score estimation means calculates the estimated answer score of the subject for the question in the first question group to be estimated from the correlation coefficient between the question in the first question group to be estimated and each question in the second question group, and the subject answer score. An intervention output device characterized by this.

8. In the intervention output device according to claim 1 or claim 2, The classification means determines the class to which the subject belongs from the center coordinates of the class and the subject answer score in the feature space defined by the questions in the first question group. An intervention output device characterized by this.

9. Subject data acquisition means for acquiring data on subject intervention indicating an intervention for supporting the health received by the subject and subject response data measuring the subject's response to the subject intervention, Evaluation means for evaluating the subject response data, Intervention output means for outputting an intervention according to the evaluation according to the priority of the intervention, referring to the intervention storage means that aggregates the priority of the intervention based on the other person's answer scores obtained by scoring each answer of others other than the subject to a question group including psychological questions regarding psychological characteristics. An intervention output device characterized by comprising:

10. In the intervention output device according to claim 9, The evaluation means evaluates according to the comparison between the value of the subject response data and a predetermined value. An intervention output device characterized by this.

11. In the intervention output device according to claim 9 or claim 10, According to the evaluation, the intervention output device further comprises a priority change means for changing the priority of the intervention in the class to which the subject belongs in the intervention / class storage means.

12. A subject answer score acquisition step of acquiring subject answer scores obtained by scoring each answer of the subject to each question in a second question group having a smaller number of questions than the first question group, including questions in the first question group having a first number of questions. A step of classifying the subject according to the subject response score into any one of the classes obtained by clustering others based on the other response scores obtained by scoring each response of others other than the subject to each question in the first question group; An intervention output step of the intervention output means referring to the intervention / class storage means that totals the priority of interventions for supporting health according to the other response scores for the psychological questions, where the first question group includes psychological questions related to psychological characteristics, for each class, and outputs an intervention according to the priority of the intervention for the classified class; An intervention output method characterized by including the above.

13. A subject data acquisition step of the subject data acquisition means for acquiring data on subject interventions indicating interventions for supporting the health received by the subject and subject response data measuring the subject's response to the subject intervention; An evaluation step of the evaluation means for evaluating the subject response data; An intervention output step of the intervention output means referring to the intervention storage means that totals the priority of the intervention based on the other response scores obtained by scoring each response of others other than the subject to a question group including psychological questions related to psychological characteristics, and outputs an intervention according to the priority of the intervention according to the evaluation; An intervention output method characterized by including the above.

14. A computer is made to function as a subject response score acquisition means for acquiring subject response scores obtained by scoring each response of a subject to each question in a second question group having a smaller number of questions than the first question group, the second question group including questions in a first question group having a first number of questions, a classification means for classifying the subject according to the subject response score into any one of the classes obtained by clustering others based on the other response scores obtained by scoring each response of others other than the subject to each question in the first question group, and an intervention output means for referring to the intervention / class storage means that totals the priority of interventions for supporting health according to the other response scores for the psychological questions, where the first question group includes psychological questions related to psychological characteristics, for each class, and outputting an intervention according to the priority of the intervention for the classified class. A program for an intervention output device characterized by this.

15. Subject data acquisition means for acquiring data on subject interventions indicating interventions for supporting the health received by the subject and subject response data measuring the subject's response to the subject intervention; Evaluation means for evaluating the subject response data, and An intervention output device program, characterized in that it functions as intervention output means for outputting an intervention according to the evaluation, with reference to intervention storage means that aggregates the priority of the intervention based on the other person's response scores obtained by scoring each response of a person other than the subject to a questionnaire group including a psychological questionnaire regarding psychological characteristics.

16. In an intervention output system comprising a terminal device of a subject who answers a questionnaire to receive an intervention for health support, and an intervention output device that outputs the intervention presented to the subject based on the response transmitted from the terminal device, wherein the intervention output device Subject response score acquisition means for acquiring subject response scores obtained by scoring each response of the subject to each question in a second question group having a smaller number of questions than the first number of questions, including the questions in the first question group having the first number of questions; Classification means for classifying the subject according to the subject response scores into any of the classes obtained by clustering the other persons based on the other person response scores obtained by scoring each response of a person other than the subject to each question in the first question group; Intervention output means for outputting an intervention according to the priority of the intervention for the classified class, with reference to intervention / class storage means that aggregates the priority of the war record intervention for each class according to the other person response scores for the psychological questionnaire, where the first question group includes a psychological questionnaire regarding psychological characteristics; An intervention output system, characterized by comprising the above.

17. In an intervention output system comprising a terminal device of a subject who answers a questionnaire to receive an intervention for health support, and an intervention output device that outputs the intervention presented to the subject based on the response transmitted from the terminal device, wherein the intervention output device Subject data acquisition means for acquiring data on subject intervention indicating the intervention received by the subject and subject response data measuring the subject's response to the subject intervention; Evaluation means for evaluating the subject response data; Intervention output means for outputting an intervention according to the priority of the intervention, with reference to intervention storage means that aggregates the priority of the intervention based on the other person response scores obtained by scoring each response of a person other than the subject to a questionnaire group including a psychological questionnaire regarding psychological characteristics, according to the evaluation; An intervention output system, characterized by comprising the above.

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