Information processing methods, methods for creating prediction models, information processing devices, information processing systems, control programs for information processing devices, control programs for target terminals

Abstract

To output information having effectiveness for solving mental and physical problems caused by stress of an object person.SOLUTION: An intervener terminal device (1) acquires a first answer group of an object person to a plurality of questions of inquiring brain fatigue states, and a second answer group of the object person to a plurality of problems of inquiring cognitive and behavioral characteristics, classifies the brain fatigue states of the object person from the first answer group to determine a first segment representing brain fatigue characteristics of the object person, and classifies the cognitive and behavioral characteristics to determine a second segment representing the cognitive and behavioral characteristics of the object person from the second answer group. The intervener terminal device (1) outputs information related to the determined first segment and second segment.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an information processing method, an information processing apparatus, a system, a control program for an information processing apparatus, and a control program for a target person terminal that output effective information for solving physical and mental problems caused by stress of a target person.

Background Art

[0002] Stress has various effects on the physical and mental health of a target person. In the industrial field, in order to widely capture the stress of a target person, a simple occupational stress survey form is used. By using the simple occupational stress survey form, it is possible to check the stress of a target person in the workplace and measure the stress factors in the workplace.

Prior Art Documents

Non-Patent Documents

[0003]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a stress check using a simple occupational stress survey form, a target person with a high score is determined as a highly stressed person, and recommendations for interview guidance by an industrial physician are made. However, the proportion of target persons who actually receive interview guidance even after receiving a recommendation for interview guidance is low (it is said to be 0.5% of the target persons who received a recommendation for interview guidance). In order to solve the physical and mental problems caused by the stress of a target person, a stress check using a simple occupational stress survey form is insufficient.

[0005] One aspect of this disclosure aims to realize an information processing method, a method for creating a predictive model, an information processing device, and an information processing system that output effective information for resolving mental and physical problems caused by stress in the subject. [Means for solving the problem]

[0006] To solve the above problems, an information processing method according to one aspect of the present disclosure is an information processing method for obtaining information necessary for presenting information useful for improving the mental health of a subject, and includes the steps of: obtaining a first group of responses from a subject to a plurality of questions asking about their brain fatigue state; obtaining a second group of responses from the subject to a plurality of questions asking about their cognitive behavioral characteristics; classifying the subject's brain fatigue state from the first group of responses to determine a first segment representing the characteristics of the subject's brain fatigue; classifying the subject's cognitive behavioral characteristics from the second group of responses to determine a second segment representing the characteristics of the subject's cognitive behavioral characteristics; and outputting information relating to the determined first and second segments, wherein the cognitive behavioral characteristics are characteristics relating to the subject's behavioral patterns when recognizing and processing things that are to be processed.

[0007] Furthermore, a method for creating a predictive model according to one aspect of this disclosure includes the steps of: obtaining a third response group, which is a group of responses from multiple respondents to multiple questions asking about their state of brain fatigue; obtaining a fifth response group, which is a group of responses from the multiple respondents to multiple questions asking about their cognitive behavioral characteristics; extracting respondents as eligible individuals whose total score on the brain fatigue scale calculated from the third response group for each of the multiple respondents is equal to or greater than a predetermined value; creating a first predictive model using a fourth response group, which is a group of responses from the eligible individuals extracted from the third response group, as an explanatory variable, and a cluster of brain fatigue states obtained by cluster extraction from the fourth response group as the dependent variable; and creating a second predictive model using a sixth response group, which is a group of responses from the eligible individuals extracted from the fifth response group, as an explanatory variable, and a cluster of cognitive behavioral characteristics obtained by cluster extraction from the sixth response group as the dependent variable.

[0008] Furthermore, a method for creating a predictive model according to one aspect of this disclosure includes the steps of: obtaining a third response group, which is a group of responses from multiple respondents to multiple questions asking about brain fatigue status; obtaining a fifth response group, which is a group of responses from the same multiple respondents to multiple questions asking about cognitive behavioral characteristics; creating a first predictive model using the third response group as explanatory variables and clusters of brain fatigue status obtained by cluster extraction from the third response group as the objective variable; and creating a second predictive model using the fifth response group as explanatory variables and clusters of cognitive behavioral characteristics obtained by cluster extraction from the fifth response group as the objective variable. The multiple questions regarding cognitive fatigue include at least one each of the following: Question 1 concerning the ability to perform an assigned role, Question 2 concerning fatigue or activity in daily life, Question 3 concerning sleep patterns, and Question 4 concerning mental state. The multiple questions regarding cognitive behavioral characteristics include at least one each of the following: Question 5 concerning the ability to solve problems, Question 6 concerning tendencies in taking in and understanding information, Question 7 concerning tendencies in approaching things, Question 8 concerning the ability to process things, and Question 9 concerning self-assessment when viewing oneself objectively.

[0009] An information processing device according to one aspect of the present disclosure is an information processing device for obtaining information necessary for presenting information useful for improving the mental health of a subject, comprising: a first acquisition unit that acquires a first group of answers from a subject to a plurality of questions asking about the state of brain fatigue; a second acquisition unit that acquires a second group of answers from the subject to a plurality of questions asking about cognitive behavioral characteristics; a first determination unit that classifies the state of brain fatigue of the subject from the first group of answers and determines a first segment that represents the characteristics of the subject's brain fatigue; a second determination unit that classifies the cognitive behavioral characteristics of the subject from the second group of answers and determines a second segment that represents the characteristics of the subject's cognitive behavioral characteristics; and an output unit that outputs information relating to the determined first segment and the second segment, wherein the cognitive behavioral characteristics are characteristics relating to the behavioral patterns of the subject when recognizing and processing things that are to be processed.

[0010] An information processing system according to one aspect of the present disclosure is a system including an information processing device for obtaining information necessary for presenting information useful for improving the mental health of a subject, and a subject terminal operated by the subject, which is communicably connected to the information processing device, wherein the information processing device includes a first acquisition unit for obtaining a first group of answers from the subject to a plurality of questions asking about the state of brain fatigue, a second acquisition unit for obtaining a second group of answers from the subject to a plurality of questions asking about cognitive behavioral characteristics, a first determination unit for classifying the state of brain fatigue of the subject from the first group of answers and determining a first segment representing the characteristics of the subject's brain fatigue, a second determination unit for classifying the cognitive behavioral characteristics of the subject from the second group of answers and determining a second segment representing the characteristics of the subject's cognitive behavioral characteristics, and the determined the The device comprises: a transmission unit that transmits information relating to the first segment and the second segment to the subject terminal, wherein the cognitive behavioral characteristics are characteristics relating to the behavioral patterns of the subject when recognizing and processing things to be processed, and the subject terminal comprises: a first output control unit that presents a plurality of questions inquiring about the state of brain fatigue and a plurality of questions inquiring about the cognitive behavioral characteristics; an input control unit that receives input of a first group of answers and a second group of answers to the plurality of questions inquiring about the state of brain fatigue and a plurality of questions inquiring about the cognitive behavioral characteristics; a transmission unit that transmits the received first group of answers and second group of answers to the information processing device; and a second output control unit that presents information relating to the first segment and the second segment received from the information processing device.

[0011] Each aspect of the information processing device, information processing system, and target terminal relating to this disclosure may be implemented by a computer. In this case, the control programs for the information processing device, information processing system, and target terminal, and the computer-readable recording medium on which they are recorded, which enable the computer to implement the information processing device, information processing system, and target terminal by operating the computer as each part (software element) of the information processing device, information processing system, and target terminal, are also included in the scope of this disclosure. [Effects of the Invention]

[0012] According to one aspect of this disclosure, it is possible to output effective information for resolving mental and physical problems caused by stress in the subject. [Brief explanation of the drawing]

[0013] [Figure 1] This is a block diagram showing an example of the configuration of an intervener terminal device according to one aspect of this disclosure. [Figure 2] This figure shows an example of the content of several questions used to assess the state of brain fatigue. [Figure 3] This figure shows an example of the content of multiple questions that assess cognitive and behavioral characteristics. [Figure 4] This figure shows an example of the content of multiple questions that assess cognitive and behavioral characteristics. [Figure 5] This flowchart shows an example of the processing flow performed by the intervention terminal device. [Figure 6] This figure shows a description of different brain fatigue types categorized by brain fatigue cluster, along with an example of how to address them. [Figure 7] This figure shows an example of recommended themes for each brain fatigue state cluster. [Figure 8] This figure shows an example of a description of cognitive behavioral trait types and coping methods for each cognitive behavioral trait cluster. [Figure 9] This figure shows the characteristics of each cognitive behavioral trait cluster. [Figure 10] This figure shows examples of recommended themes for each cognitive behavioral characteristics cluster. [Figure 11] This figure shows the number of subjects in each combination of the brain fatigue state segment and the cognitive behavioral characteristics segment. [Figure 12] This flowchart shows an example of the pre-training process flow, including the method for creating brain fatigue state cluster prediction models and cognitive behavioral characteristic cluster prediction models. [Figure 13] This figure shows the schematic configuration of an information processing system relating to one aspect of this disclosure. [Figure 14]It is a diagram showing an example of presenting information regarding a brain fatigue state segment and a cognitive behavior characteristic segment. [Figure 15] It is a diagram showing another example of presenting information regarding a brain fatigue state segment and a cognitive behavior characteristic segment. [Figure 16] It is a diagram showing an example of a recommended theme.

Mode for Carrying Out the Invention

[0014] 〔Embodiment 1〕 Hereinafter, an embodiment of the present disclosure will be described in detail.

[0015] An information processing method according to one aspect of the present disclosure includes steps of obtaining a first response group of a subject to a plurality of questions asking about the brain fatigue state, and obtaining a second response group of the subject to a plurality of questions asking about cognitive behavior characteristics.

[0016] Furthermore, this information processing method includes the following steps (1) and (2).

[0017] (1) A step of classifying the brain fatigue state of the subject from the first response group and determining a first segment representing the characteristics of the subject's brain fatigue.

[0018] (2) A step of classifying the cognitive behavior characteristics of the subject from the second response group and determining a second segment representing the characteristics of the subject's cognitive behavior characteristics.

[0019] The information processing method then outputs information regarding the first and second segments determined in steps (1) and (2) above. The information regarding the first segment is based on the results of patterning the characteristics of the subject's brain fatigue, and the information regarding the second segment is based on the results of patterning the subject's cognitive behavioral characteristics. Therefore, the information regarding the first segment and the information regarding the second segment are effective information for solving mental and physical problems caused by stress for each of the subjects. In addition, a predictive model created by predetermined machine learning may be applied in the process of classifying the subject's brain fatigue state from the first group of responses in (1) above, and in the process of classifying the subject's cognitive behavioral characteristics from the second group of responses in (2) above. Such predictive models (brain fatigue state cluster prediction model 112 and cognitive behavioral characteristic cluster prediction model 113) will be explained later.

[0020] Here, cognitive behavioral characteristics refer to the behavioral patterns of the subject when perceiving and processing things that need to be processed. On the other hand, brain fatigue refers to the characteristics of the subject's decline in brain function related to a decrease in role performance function, decline in social daily functioning, sleep insufficiency, maladaptive cognition, and behavioral responses.

[0021] In this disclosure, "Subject" may be a professional with an occupation, a student, or a full-time housewife or other person whose role is to perform household chores. In this disclosure, "Intervener" refers to a person who provides various interventions to the Subject based on their professional knowledge. For example, the Intervener may be a psychiatrist who provides medical intervention to the Subject, or an industrial physician or mental health professional who provides counseling, etc. Mental health professionals may include those with qualifications such as psychologist and certified psychologist. Alternatively, the Intervener may be a company that provides counseling, etc., to resolve the mental and physical problems of the Subject caused by stress. Such a company may be one that is affiliated with or contracted by the employer who employs the Subject.

[0022] The following explanation will use as an example a case in which the intervener terminal device 1 (information processing device) used by the intervener performs an information processing method according to one aspect of this disclosure.

[0023] (Intervenor terminal device 1) Figure 1 is a block diagram showing an example of the schematic configuration of the intervener terminal device 1. The intervener terminal device (information processing device) 1 may be a computer and tablet terminal used by the intervener terminal device 1.

[0024] As shown in Figure 1, the intervener terminal device 1 comprises a control unit 10 that centrally controls all parts of the intervener terminal device 1, and a storage unit 11 that stores various data used by the intervener terminal device 1. The intervener terminal device 1 also comprises an input unit 12 that receives input operations to the intervener terminal device 1, a communication unit 13 for the intervener terminal device 1 to communicate with other devices, and a display unit 14 which is a display device that displays images. The input unit 12 may be a touch panel, in which case the display surface of the display unit 14 functions as the input surface of the input unit 12.

[0025] [Storage section 11] The memory unit 11 stores question data 111, a brain fatigue state cluster prediction model (first prediction model) 112, a cognitive behavioral characteristics cluster prediction model (second prediction model) 113, a brain fatigue state type description and coping method 114, a cognitive behavioral characteristics type description and coping method 115, recommended content 116, and a correspondence table 117.

[0026] Question data 111 includes multiple questions regarding brain fatigue levels and multiple questions regarding cognitive behavioral characteristics. The brain fatigue level cluster prediction model 112 is used to predict brain fatigue level clusters, and the cognitive behavioral characteristics cluster prediction model 113 is used to predict cognitive behavioral characteristics clusters.

[0027] Brain fatigue state type description and coping method 114 may be information describing the types of brain fatigue state segments (first segment) and information describing coping methods. Cognitive behavioral characteristic type description and coping method 115 may be information describing the types of cognitive behavioral characteristic segments (second segment) and information describing coping methods. Recommended content 116 may be recommended content corresponding to recommended themes that help improve the mental and physical health of the subject due to stress. Recommended content 116 may include multiple recommended contents corresponding to multiple recommended themes. Here, the recommended content may be a booklet containing effective advice, etc., to solve the mental and physical problems of the subject due to stress, or it may be a video.

[0028] Here, a "brain fatigue state segment" refers to each brain fatigue state cluster determined by the brain fatigue state cluster prediction model 112, to which experts have pre-assigned corresponding interpretations or meanings. In other words, a brain fatigue state segment is an interpretable representation of the brain fatigue characteristics of individuals classified into a brain fatigue state cluster.

[0029] On the other hand, a "cognitive behavioral characteristics segment" is a segment to which experts have pre-assigned corresponding interpretations or meanings to each cognitive behavioral characteristics cluster determined by the cognitive behavioral characteristics cluster prediction model 113. In other words, a cognitive behavioral characteristics segment is an interpretable representation of the characteristics of the cognitive behavioral characteristics of individuals classified into cognitive behavioral characteristics clusters.

[0030] Correspondence Table 117 stores correspondences between brain fatigue clusters and brain fatigue segments, between cognitive behavioral characteristic clusters and cognitive behavioral characteristic segments, between brain fatigue segments and recommended content, between cognitive behavioral characteristic segments and recommended content, and between combinations of brain fatigue segments and cognitive behavioral characteristic segments and recommended content. Each correspondence stored in Correspondence Table 117 may have been pre-assigned by a specialist such as a psychiatrist, industrial physician, or counselor.

[0031] [Control Unit 10] The control unit 10 includes a first acquisition unit 101, a second acquisition unit 102, a first prediction unit 103, a second prediction unit 104, a first determination unit 105, a second determination unit 106, and an output unit 107.

[0032] The first acquisition unit 101 acquires a group of initial responses from the subject to a series of questions regarding their state of brain fatigue. The method by which the first acquisition unit 101 acquires the group of initial responses is not particularly limited. For example, the subject may input their answers using the input unit 12 to a series of questions regarding their state of brain fatigue, which are read from the question data 111 and displayed on the display unit 14, thereby acquiring the group of initial responses from the first acquisition unit 101. Alternatively, the series of questions regarding their state of brain fatigue may be output to paper via the communication unit 13, and the answers written by the subject on the paper may be input by the intervener using the input unit 12.

[0033] The second acquisition unit 102 acquires a second set of responses from the subject to multiple questions about cognitive and behavioral characteristics. The method by which the second acquisition unit 102 acquires the second set of responses is not particularly limited. For example, the subject may input their answers using the input unit 12 to multiple questions about cognitive and behavioral characteristics read from the question data 111 and displayed on the display unit 14, thereby acquiring the second set of responses from the second acquisition unit 102. Alternatively, multiple questions about brain fatigue status may be output to paper via the communication unit 13, and the intervener may input the answers written by the subject on the paper using the input unit 12.

[0034] The first prediction unit 103 predicts the brain fatigue state cluster of a subject using a brain fatigue state cluster prediction model 112, based on the first response group, which is a group of the subject's answers to multiple questions regarding their brain fatigue state. Specifically, the first prediction unit 103 classifies the subject's brain fatigue from the first response group into one of the five brain fatigue state clusters (1) to (5) shown in Figure 6. Brain fatigue state clusters (1) to (5) will be explained later.

[0035] The second prediction unit 104 predicts the cognitive behavioral characteristic cluster of a subject from the second response group, which is the subject's response to multiple questions about cognitive behavioral characteristics, using the cognitive behavioral characteristic cluster prediction model 113. Specifically, the second prediction unit 104 classifies the subject's cognitive behavioral characteristics from the second response group into one of the five cognitive behavioral characteristic clusters (I) to (V) shown in Figure 8. Cognitive behavioral characteristic clusters (I) to (V) will be explained later.

[0036] The first decision unit 105 classifies the subject's brain fatigue state from the first group of responses using the brain fatigue state cluster prediction model 112 and determines a brain fatigue state segment that represents the characteristics of the subject's brain fatigue. For example, the first decision unit 105 may refer to the correspondence table 117 and determine a brain fatigue state segment that corresponds to the brain fatigue state cluster predicted by the first prediction unit 103.

[0037] As shown in Figures 6 and 11, "insomnia" is associated with the brain fatigue state segment in brain fatigue state cluster (1). "Moderate fatigue" is associated with the brain fatigue state segment in brain fatigue state cluster (2). "Over-adapted state / overwork (general fatigue)" is associated with the brain fatigue state segment in brain fatigue state cluster (3). "High stress sensitivity (blaming oneself) (emotional change-centered, maladaptive cognition / behavioral response)" is associated with the brain fatigue state segment in brain fatigue state cluster (4). "High stress sensitivity (blaming oneself) and high fatigue (emotional change / decreased executive function, decreased executive function + maladaptive cognition / behavioral response)" is associated with the brain fatigue state segment in brain fatigue state cluster (5).

[0038] The second decision unit 106 classifies the cognitive behavioral characteristics of the subject from the second group of responses using the cognitive behavioral characteristics cluster prediction model 113 and determines a cognitive behavioral characteristics segment that represents the characteristics of the subject's cognitive behavioral characteristics. For example, the second decision unit 106 may refer to the correspondence table 117 and determine a cognitive behavioral characteristics segment that corresponds to the cognitive behavioral characteristics cluster predicted by the second prediction unit 104.

[0039] As shown in Figures 8 and 11, the cognitive behavioral characteristics cluster (I) is associated with the cognitive behavioral characteristics segment "hyperactive and prone to overload (hyperactive, overloaded)". The cognitive behavioral characteristics cluster (II) is associated with the cognitive behavioral characteristics segment "few fluctuations, but greatly influenced by environmental factors (few fluctuations, large environmental factors)". The cognitive behavioral characteristics cluster (III) is associated with the cognitive behavioral characteristics segment "easily influenced by others". The cognitive behavioral characteristics cluster (IV) is associated with the cognitive behavioral characteristics segment "highly inattentive, easily believes what others say". The cognitive behavioral characteristics cluster (V) is associated with the cognitive behavioral characteristics segment "has obsessions, is capable at work but has difficulty controlling things (has obsessions, is capable at work, lacks control)".

[0040] The output unit 107 outputs information regarding the determined brain fatigue state segment (first segment) and cognitive behavioral characteristics segment (second segment). The output may be presented by displaying it on the display unit 14 of the intervention terminal device 1, or by printing it onto paper via the communication unit 13. If the intervention terminal device 1 is equipped with an audio output unit such as a speaker, the information may also be presented via audio output.

[0041] For example, the output unit 107 may output the determined brain fatigue state segment and cognitive behavioral characteristic segment as information regarding the determined brain fatigue state segment and cognitive behavioral characteristic segment. That is, for example, if the brain fatigue state cluster is (3) and the cognitive behavioral characteristic cluster is (III), it will present "Over-adapted state / overwork (general fatigue)" and "Easily influenced by others."

[0042] Furthermore, the output unit 107 may also provide information regarding the determined brain fatigue state segment and cognitive behavioral characteristic segment, including a description of the brain fatigue state type and coping method corresponding to the brain fatigue state segment (first type description and first coping method), and a description of the cognitive behavioral characteristic type and coping method corresponding to the cognitive behavioral characteristic segment (second type description and second coping method).

[0043] Specifically, the output unit 107 may refer to the brain fatigue state type description / coping method 114 to present a brain fatigue state type description and a coping method corresponding to the brain fatigue state segment. Similarly, the output unit 107 may refer to the cognitive behavioral characteristic type description / coping method 115 to present a cognitive behavioral characteristic type description and a coping method corresponding to the cognitive behavioral characteristic segment.

[0044] Furthermore, the output unit 107 may present recommended content corresponding to the brain fatigue state segment and recommended content corresponding to the cognitive behavioral characteristics segment as information regarding the determined brain fatigue state segment and cognitive behavioral characteristics segment. Specifically, the output unit 107 may refer to the correspondence table 117 to present recommended content corresponding to the brain fatigue state segment and recommended content corresponding to the cognitive behavioral characteristics segment.

[0045] Furthermore, the output unit 107 may also present recommended content corresponding to the combination of brain fatigue state segments and cognitive behavioral characteristics segments, based on the combination of brain fatigue state segments and cognitive behavioral characteristics segments, as information regarding the determined brain fatigue state segments and cognitive behavioral characteristics segments. Specifically, the output unit 107 may refer to the correspondence table 117 to present recommended content corresponding to the combination of brain fatigue state segments and cognitive behavioral characteristics segments.

[0046] (Question data) <Multiple questions to assess the state of mental fatigue> The multiple questions assessing brain fatigue include at least one of each of the following: a first question concerning the ability to perform a given role, a second question concerning fatigue or activity in daily life, a third question concerning sleep patterns, and a fourth question concerning mental state. The first acquisition unit 101 acquires the subject's responses to the first, second, third, and fourth questions as a first response group. The responses to the questions may be numerical values ​​corresponding to, for example, four-point scale options. The numerical values ​​corresponding to the four-point scale options may be, for example, "0" for "strongly disagree," "1" for "somewhat agree," "2" for "agree," and "3" for "very agree."

[0047] Figure 2 shows an example of the content of multiple questions used to assess brain fatigue. As shown in Figure 2, the multiple questions used to assess brain fatigue have four representative items corresponding to questions 1 through 4.

[0048] The first question regarding the ability to perform an assigned role is designated as the representative item "Decreased Role Performance Function." "Decreased Role Performance Function" is further divided into detailed items: "Decreased Work Efficiency" and "Decreased Attention Function," with at least one question item for each detailed item. In Figure 2, questions Q1 to Q3 are included as questions for "Decreased Role Performance Function - Decreased Work Efficiency," and questions Q3 to Q6 are included as questions for "Decreased Role Performance Function - Decreased Attention Function." "Decreased Work Efficiency" asks whether the respondent feels their work efficiency is reduced when performing an assigned role, and "Decreased Attention Function" asks whether the respondent feels their attention function is reduced when performing an assigned role.

[0049] As the second question regarding fatigue or activity in daily life, the representative item "Decreased Social and Daily Functioning" is set. "Decreased Social and Daily Functioning" is further divided into detailed items "Accumulated Fatigue" and "Decreased Daily Activity," with at least one question item for each detailed item. In Figure 2, Q7 to Q9 are included as questions for "Decreased Social and Daily Functioning - Accumulated Fatigue," and Q10 to Q12 are included as questions for "Decreased Social and Daily Functioning - Decreased Daily Activity." "Accumulated Fatigue" asks whether the person feels that fatigue is accumulating in their daily life. "Decreased Daily Activity" asks whether the person feels that their activity level is decreasing in their daily life.

[0050] The third question regarding sleep quality is a representative item, "sleep insufficiency," which includes four questions, Q13 to Q16. Questions Q13 to Q16 ask whether the respondent feels their sleep quality has deteriorated, and inquire about factors such as sleep duration, time to fall asleep, and time of waking during sleep.

[0051] The fourth question regarding mental state is a representative item called "maladaptive cognitive and behavioral responses," which includes four questions, Q17 to Q20. Questions Q17 to Q20 ask whether the person feels their mental state is deteriorating. They ask about things like being easily irritated, speaking harshly, being concerned about what others think, and often becoming pessimistic.

[0052] <Multiple questions to assess cognitive and behavioral characteristics> The multiple questions assessing cognitive behavioral characteristics include at least one of each of the following: Question 5 concerning problem-solving ability, Question 6 concerning tendencies in taking in and understanding information, Question 7 concerning tendencies in approaching things, Question 8 concerning ability to process things, and Question 9 concerning self-assessment when viewing oneself objectively. The second acquisition unit 102 acquires the subject's responses to Questions 5, 6, 7, 8, and 9 as a second group of responses. The responses to the questions may be numerical values ​​corresponding to, for example, four-point scale options. The numerical values ​​corresponding to the four-point scale options may be, for example, "0" for "strongly disagree," "1" for "somewhat agree," "2" for "agree," and "3" for "very agree."

[0053] Figures 3 and 4 show examples of the content of multiple questions that assess cognitive behavioral characteristics. In Figures 3 and 4, five representative items corresponding to questions 5 through 9 are set.

[0054] The fifth question, concerning the ability to solve problems, is the representative item "Problem-solving ability." "Problem-solving ability" is further divided into detailed items: "Logical analytical ability," "Rational decision-making," "Creative thinking," "Abstraction ability," and "Concretization ability," with at least one question for each detailed item. In Figure 3, Q1 is the question for "Logical analytical ability," Q2 is the question for "Rational decision-making," Q3 is the question for "Creative thinking," Q4 is the question for "Abstraction ability," and Q5 is the question for "Concretization ability."

[0055] The sixth question, which concerns tendencies when taking in and understanding information, is a representative item called "Cognitive Characteristics of Input." "Cognitive Characteristics of Input" is further divided into detailed items: "Visual," "Auditory," "Social," and "Things," with at least one question for each detailed item. In Figure 3, questions Q6 and Q7 are included as "Visual" questions, and questions Q8 and Q9 are included as "Auditory" questions. Additionally, questions Q10 to Q13 are included as "Social" questions, and questions Q14 and Q15 are included as "Things" questions.

[0056] "Visual" includes questions about whether you tend to take in information from diagrams rather than text. "Auditory" includes questions about whether you tend to take in information from text rather than diagrams. "Social" includes questions about your ability to read the atmosphere, or "social cues," when taking in information in relation to others. "Things" includes questions about your behavioral characteristics for taking in and understanding information.

[0057] The seventh question, which concerns tendencies in approaching tasks, is a representative item called "Cognitive Characteristics of Output." "Cognitive Characteristics of Output" is further divided into detailed items: "Hunting," "Farming," and "Assertion Ability," with at least one question for each detailed item. In Figure 3, Q16 is the question for "Hunting," Q17 is the question for "Farming," and Q18 is the question for "Assertion Ability."

[0058] "Hunting" questions assess whether you act before thinking when tackling tasks. "Farming" questions assess whether you approach tasks by steadily building things up step by step. "Assertion ability" questions assess your assertiveness when tackling tasks.

[0059] As shown in Figure 4, the eighth question concerning the ability to process things is the representative item "Basic Cognitive Functions." "Basic Cognitive Functions" is further divided into detailed items: "Executive Function: Inhibitory Function (Cognition)," "Executive Function: Inhibitory Function (Emotion)," "Executive Function: Shifting," "Executive Function: Working Memory," "Executive Function: Planning," "Attention Function: Selection," "Attention Function: Segmentation," "Attention Function: Retention," "Memory," and "Processing Speed," with at least one question for each detailed item. In Figure 4, Q19 is the question for "Executive Function: Inhibitory Function (Cognition)," Q20 is the question for "Executive Function: Inhibitory Function (Emotion)," Q21 is the question for "Executive Function: Shifting," and Q22 and Q23 are the questions for "Executive Function: Working Memory." Additionally, questions Q24 and Q25 are related to "Executive Function: Planning," Q26 to "Attention Function: Selection," Q27 to "Attention Function: Splitting," Q28 to "Attention Function: Retention," Q29 to "Memory," and Q30 to "Processing Speed."

[0060] "Executive Function: Inhibitory Function (Cognitive)" consists of questions that assess whether you can recognize and concentrate on what needs to be done when performing multiple tasks. "Executive Function: Inhibitory Function (Emotional)" consists of questions that assess whether you tend to procrastinate on tasks. "Executive Function: Shifting" consists of questions that assess whether you can effectively switch between multiple tasks when you have several to do. "Executive Function: Working Memory" includes questions that assess your processing ability when handling multiple tasks. "Executive Function: Planning" includes questions that assess whether you can plan and handle multiple tasks. "Attention Function: Selection" consists of questions that assess how easily you are distracted. "Attention Function: Division" consists of questions that assess how often you forget things. "Attention Function: Retention" consists of questions that assess how long you can concentrate on one thing. "Memory" consists of questions that assess your memory. "Processing Speed" consists of questions that assess how quickly you process things.

[0061] The ninth question, which concerns self-assessment when viewing oneself objectively, is the representative item "metacognition." "Metacognition" is further divided into detailed items: "self-monitoring: cognition," "self-monitoring: emotion," and "self-efficacy," with at least one question item for each detailed item. In Figure 4, Q31 and Q32 are questions for "self-monitoring: cognition," Q33 and Q34 are questions for "self-monitoring: emotion," and Q35 and Q36 are questions for "self-efficacy."

[0062] "Self-monitoring: Cognition" includes questions that ask whether you try to objectively observe yourself and recognize your own state. "Self-monitoring: Emotion" includes questions that ask about your emotions by objectively observing yourself. "Self-efficacy" consists of questions that ask about your self-efficacy by objectively observing yourself.

[0063] (Process flow) Figure 5 is a flowchart showing an example of the processing flow performed by the Intervention Terminal Device 1. First, the Intervention Terminal Device 1 presents the subject with several questions regarding brain fatigue and several questions regarding cognitive behavioral characteristics (Step S1). The order in which the questions regarding brain fatigue and cognitive behavioral characteristics are presented to the subject may be arbitrary.

[0064] Next, the intervener terminal device 1 obtains a first group of answers, which are responses to a series of questions about brain fatigue (step S2). The intervener terminal device 1 obtains a second group of answers, which are responses to a series of questions about cognitive behavioral characteristics (step S3). Figure 5 shows an example in which the intervener terminal device 1 performs S3 after step S2, but the order of these processes is not particularly limited. For example, if the series of questions about cognitive behavioral characteristics are presented to the subject before the series of questions about brain fatigue, the process in step S3 may be performed before the process in step S2. The intervener terminal device 1 may also present the first group of answers obtained in step S2 and the third group of answers obtained in step S3 to the intervener.

[0065] Next, the intervention terminal device 1 classifies the subject's brain fatigue state from the first response group using the brain fatigue state cluster prediction model 112 and determines a brain fatigue state segment that represents the characteristics of the subject's brain fatigue (steps S4, S6). Furthermore, the intervention terminal device 1 classifies the subject's cognitive behavioral characteristics from the second response group using the cognitive behavioral characteristics cluster prediction model 113 and determines a cognitive behavioral characteristics segment that represents the characteristics of the subject's cognitive behavioral characteristics (steps S5, S7).

[0066] Next, the intervener terminal device 1 outputs information regarding the brain fatigue state segment determined in steps S4 and S6, and information regarding the cognitive behavioral characteristics segment determined in steps S5 and S7 (step S8). The information regarding the brain fatigue state segment and the information regarding the cognitive behavioral characteristics segment may include, as described above, a description of the brain fatigue state type and its coping methods, a description of the cognitive behavioral characteristics type and its coping methods, recommended content, etc.

[0067] Each piece of information output in step S8 may be presented to the intervener, or to both the intervener and the subject. Additionally, the brain fatigue state segment corresponding to the subject determined in S6, and the cognitive behavioral characteristic segment corresponding to the subject determined in S7, may be presented to the intervener, or to both the intervener and the subject. Based on this information, the intervener can determine and implement an effective psychological intervention (e.g., cognitive behavioral therapy) to resolve the subject's stress-related physical and mental problems.

[0068] In Figure 5, the intervener terminal device 1 may, but is not limited to, determining the brain fatigue state segment and the cognitive behavioral characteristics segment in parallel. For example, the intervener terminal device 1 may determine either the brain fatigue state segment or the cognitive behavioral characteristics segment first, and then determine the other.

[0069] (Explanation of different types of brain fatigue and how to deal with them) Figure 6 shows an example of a description of brain fatigue state types and coping methods for each brain fatigue state cluster. In the graph labeled 601, the vertical axis represents the aggregated values ​​for each item in Figure 2, obtained as numerical values ​​corresponding to the four-point scale options for questions about brain fatigue state. Each graph shows the average value for the entire population surveyed in advance, and the average value for the subset classified into brain fatigue state clusters (1) to (5). In the figure, "A: I-I_Decreased work efficiency)" is the aggregated value of the responses to questions Q1 to Q3 of "Decreased role performance function_Decreased work efficiency" shown in Figure 2. In the figure, "B: I-II_Decreased attention function" is the aggregated value of the responses to questions Q4 to Q6 of "Decreased role performance function_Decreased attention function" shown in Figure 2. In the figure, "C: II-I_Accumulated fatigue" is the aggregated value of the responses to questions Q7 to Q8 of "Decreased social and daily functioning_Accumulated fatigue" shown in Figure 2. In the figure, "D:II-I_Decreased Daily Activity" is the aggregated value of the responses to questions Q10-Q12, which are questions from "Decreased Social and Daily Functioning_Decreased Daily Activity" shown in Figure 2. In the figure, "E:III_Sleep Disorder" is the aggregated value of the responses to questions Q13-Q16, which are questions from "Sleep Disorder" shown in Figure 2. In the figure, "F:IV_Maladaptive Cognitive and Behavioral Reactions" is the aggregated value of the responses to questions Q17-Q20, which are questions from "Maladaptive Cognitive and Behavioral Reactions" shown in Figure 2.

[0070] From the graph labeled 601, for example, the brain fatigue state cluster (1) has a higher value for "E:III_Sleep Disorder" compared to the overall trend. This allows us to understand the characteristics of the five brain fatigue state clusters (1) to (5), which can be helpful when assigning interpretations or meanings to each cluster.

[0071] The table labeled 602 in Figure 6 shows the brain fatigue state segment, brain fatigue state type description, and countermeasures corresponding to each of the brain fatigue state clusters (1) to (5). The table labeled 602 is an example of the data structure of the brain fatigue state type description and countermeasures 114 stored in the memory unit 11. As shown in the table labeled 602, the description of the type and the countermeasures are set for each brain fatigue state segment (brain fatigue state cluster).

[0072] For example, the brain fatigue state segment "insomnia" (brain fatigue state cluster (1)) has the following description: "It appears that you are getting insufficient sleep or the quality of your sleep is poor. As a result, your brain may be a little tired." Furthermore, the suggested solution is: "Understand the mechanisms of brain fatigue, ensure you get enough sleep, get good quality sleep, and live your daily life with a refreshed mind and body."

[0073] (Brain fatigue cluster and recommended themes) Figure 7 shows an example of recommended themes for each brain fatigue cluster. In the example in Figure 7, five themes have been selected from the list of recommended themes shown in Figure 16: "How to cope with stress," "About brain fatigue," "For good sleep," "How to take notes," and "How to relax." Depending on the brain fatigue segment (brain fatigue cluster), a recommended theme is selected from these five themes. In the figure, themes marked with "○" are recommended themes, and themes marked with "△" are recommended themes with a lower recommendation level than those marked with "○." For example, brain fatigue cluster (1) has "About brain fatigue," "For good sleep," and "How to relax" as recommended themes.

[0074] (Description of cognitive behavioral trait types and coping strategies) Figure 8 shows an example of a description of cognitive behavioral trait types and coping methods for each cognitive behavioral trait cluster. In the graph labeled 801, the vertical axis represents the numerical values ​​obtained as corresponding to the four-point scale of responses to questions about cognitive behavioral traits. Each graph shows the average value of the entire population surveyed in advance, and the average value of the subset classified into cognitive behavioral trait clusters (I) to (V). In the figure, "H: Trait 1_Logical analytical ability" is the response value to Q1, a question item in "Problem-solving ability_Logical analytical ability" shown in Figure 3. In the figure, "I: Trait 18_Assertion ability" is the response value to Q18, a question item in "Cognitive trait of output_Assertion ability" shown in Figure 3. In the figure, "J: Trait 25_Planning 2_Schedule setting" is the response value to Q25, a question item in "Basic cognitive function_Executive function planning" shown in Figure 4. In the figure, "K: Trait 26_Attentional Selection" is the response value to Q26, a question from "Basic Cognitive Functions_Attention Function: Selection" shown in Figure 4. In the figure, "L: Trait 29_Memory" is the response value to Q29, a question from "Basic Cognitive Functions_Memory" shown in Figure 4. In the figure, "M: Trait 34_Self-Monitoring (Emotion) 2_Anxiety / Worry" is the response value to Q34, a question from "Metacognition_Self-Monitoring (Emotion): Emotion" shown in Figure 4.

[0075] From the graph labeled 801, for example, the cognitive behavioral characteristic cluster (I) has a higher value for "J: Characteristic 25_Planning 2_Schedule Making" compared to the overall trend. This allows us to understand the characteristics of the five cognitive behavioral characteristic clusters (I) to (V), which can be helpful when assigning interpretations or meanings to each cluster.

[0076] The table labeled 802 in Figure 8 shows cognitive behavioral characteristic segments, cognitive behavioral characteristic type descriptions, and coping methods. The table labeled 802 is an example of the data structure of the cognitive behavioral characteristic type descriptions and coping methods 115 stored in the memory unit 11. As shown in the table labeled 802, the description of each type and the coping method are set for each cognitive behavioral characteristic segment (cognitive behavioral characteristic cluster).

[0077] For example, in the cognitive behavioral characteristics segment "Hyperactive and prone to overload" (Cognitive Behavioral Characteristics Cluster (I)), the type description is set as, "You may often find yourself looking at many things at once and taking on too much work." Furthermore, the suggested coping mechanism is, "Try to be mindful of how to politely decline tasks according to your own abilities and capacity."

[0078] (Cognitive behavioral trait clusters and their characteristics) Figure 9 shows the characteristics of each cognitive behavioral trait cluster. As shown in Figure 9, each cognitive behavioral trait cluster has its own characteristics, and cognitive behavioral trait segments are assigned based on these characteristics. In the example in Figure 9, five items are listed as characteristics: "dispersion of attention," "inattention, weakness in WM (working memory)," "systematic / autistic," "problem-solving ability," and "anxiety." In Figure 9, "◎" indicates a strong and prominent degree, and "×" indicates a weak degree. The degree decreases in the order of "◎" → "○" → "△" → "×".

[0079] (Cognitive behavioral characteristics clusters and recommended themes) Figure 10 shows an example of recommended themes for each cognitive behavioral characteristics cluster. In the example in Figure 10, five themes have been selected from the list of recommended themes shown in Figure 16: "Understanding Brain Habits," "Note-Taking Techniques," "Planning Your Daily Time," "Relaxation Methods," and "Communicating Effectively." Depending on the cognitive behavioral characteristics segment (cognitive behavioral characteristics cluster), a recommended theme is selected from these five themes. Note that "○" and "△" are the same as in Figure 7. For example, for cognitive behavioral characteristics cluster (I), the recommended themes are "Understanding Brain Habits," "Planning Your Daily Time," and "Communicating Effectively."

[0080] (Combination of brain fatigue state segment and cognitive behavioral characteristics segment) Figure 11 shows the number of subjects in each combination of the brain fatigue state segment and the cognitive behavioral characteristics segment. As shown in Figure 11, both the brain fatigue state segment and the cognitive behavioral characteristics segment consist of 5 segments, so combining them yields a total of 25 segments. In this way, recommended themes may be set according to the segments obtained by the combination, and recommended content may be presented and provided accordingly.

[0081] (Creation of a brain fatigue state cluster prediction model and a cognitive behavioral characteristics cluster prediction model) <Brain fatigue state cluster prediction model> Figure 12 is a flowchart showing an example of the processing flow for the pre-training stage, including the method for creating the brain fatigue state cluster prediction model 112 and the cognitive behavioral characteristics cluster prediction model 113. Note that the cluster extraction method, multiple regression analysis method, regression analysis method, etc., exemplified in Figure 12 are those used in one embodiment, but are not limited to these.

[0082] Here, we will explain using the example where the intervener terminal device 1 creates the brain fatigue state cluster prediction model 112 and the cognitive behavioral characteristics cluster prediction model 113, but we are not limited to this. For example, any computer other than the intervener terminal device 1 may create the brain fatigue state cluster prediction model 112 and the cognitive behavioral characteristics cluster prediction model 113. In this case, by installing the created brain fatigue state cluster prediction model 112 and cognitive behavioral characteristics cluster prediction model 113 into the intervener terminal device 1, the intervener terminal device 1 will be able to execute the process shown in Figure 5.

[0083] First, in step S10, the intervener terminal device 1 extracts respondents for the pre-learning stage. Here, the target subjects may or may not be included among the respondents for the pre-learning stage. Next, in step S11, the intervener terminal device 1 presents the extracted respondents with several questions regarding brain fatigue status, specifically for the pre-learning stage. Furthermore, in step S21, the intervener terminal device 1 presents the respondents for the pre-learning stage with several questions regarding cognitive behavioral characteristics.

[0084] Next, in step S22, the intervener terminal device 1 obtains a third group of responses from the respondents for the pre-learning stage, which consists of answers to several questions regarding brain fatigue. Also in step S22, the intervener terminal device 1 obtains a fifth group of responses from the respondents for the pre-learning stage, which consists of answers to several questions regarding cognitive behavioral characteristics.

[0085] Next, in step S13, the intervention terminal device 1 calculates the total score of the brain fatigue scale (numerical values ​​corresponding to the answers to questions about brain fatigue) for each of the multiple respondents calculated from the third response group. In step S14, the intervention terminal device 1 extracts respondents whose total score on the brain fatigue scale is above a predetermined value as highly brain-fatigued individuals (eligible individuals). If the answers to the questions about brain fatigue are, for example, numerical values ​​corresponding to a 4-point scale (not at all applicable: 0, somewhat applicable: 1, applicable: 2, very applicable: 3), the total score will be in the range of 0 to 60. In this case, the predetermined value for extracting eligible individuals may be set to 21 points. Note that, below, only the response groups of eligible individuals (fourth response group and sixth response group) are extracted to perform steps such as cluster extraction and creation of cluster prediction models, but the same steps may be performed on the response groups of all respondents (third response group and fifth response group). In other words, in Figure 12, steps S13, S14, S15, and S23, which are included in the area enclosed by the dashed line 1102, are not essential steps.

[0086] Next, in step S15, the intervention terminal device 1 extracts the fourth response group, which consists of the responses of the relevant individuals, from the third response group. Furthermore, in step S16, the intervention terminal device 1 clusters the fourth response group to create brain fatigue state clusters. Known methods such as Ward's method can be used for cluster extraction. Figure 12 shows an example where the intervention terminal device 1 extracted five brain fatigue state clusters. This is just one example, and the number of clusters extracted by the intervention terminal device 1 is not limited (and there are no upper or lower limits).

[0087] Next, in step S17, the intervention terminal device 1 performs a multinomial logistic regression analysis using the fourth response group as the explanatory variable and the brain fatigue state cluster extracted in S16 as the dependent variable to create a brain fatigue state cluster prediction model 112. In addition, in step S18, the intervention terminal device 1 associates the five extracted brain fatigue state clusters with the separately created brain fatigue state type explanations and coping methods 114 and recommended content 116.

[0088] Thus, the brain fatigue state cluster prediction model 112 is created by using the fourth response group, which is the group of responses from eligible respondents extracted from the third response group, as the explanatory variable, and the brain fatigue state clusters obtained by cluster extraction from the fourth response group as the dependent variable. The fourth response group is the group of responses from eligible respondents extracted from the third response group, which is the group of responses from eligible respondents, which is the dependent variable.

[0089] <Cognitive Behavioral Characteristics Cluster Prediction Model> Next, in step S23, the intervener terminal device 1 extracts the sixth response group, which consists of the responses of the relevant individuals extracted in step S14, from the fifth response group obtained in step S22. Alternatively, as shown in Figure 12, steps S24 and S25 may be performed to extract responses of the significant cognitive behavioral characteristics "H" to "M" mentioned above from the fifth response group, and this may also be used as the sixth response group. In step S24, a multiple regression analysis was used with the sixth response group as the explanatory variable and the total score of the brain fatigue scale as the dependent variable. Known methods such as the Stepwise method can be used for the multiple regression analysis. In Figure 12, steps S24 and S25, which are included in the area enclosed by the dashed line 1101, are not mandatory steps.

[0090] Next, in step S26, the intervention terminal device 1 extracts clusters from the sixth response group to create cognitive behavioral characteristic clusters. Known methods such as Ward's method can be used for cluster extraction. Figure 12 shows an example in which the intervention terminal device 1 extracted five cognitive behavioral characteristic clusters. This is just one example, and the number of clusters extracted by the intervention terminal device 1 is not limited (and there is no upper or lower limit).

[0091] Next, in step S27, the intervention terminal device 1 performs a multinomial logistic regression analysis using the sixth response group as the explanatory variable and the cognitive behavioral characteristic cluster extracted in S26 as the dependent variable to create a cognitive behavioral characteristic cluster prediction model 113. Furthermore, in step S28, the intervention terminal device 1 associates the five extracted cognitive behavioral characteristic clusters with the separately created cognitive behavioral characteristic type explanations / coping methods 115 and recommended content 116.

[0092] Thus, the cognitive behavioral characteristics cluster prediction model 113 is created using the following as its explanatory variable: the sixth response group, which is the group of responses extracted from the fifth response group, which is the group of responses to multiple questions asking about cognitive behavioral characteristics obtained from multiple respondents, as the explanatory variable; and the clusters of cognitive behavioral characteristics obtained by cluster extraction from the sixth response group as the dependent variable. The model uses the third response group, which is the group of responses from multiple respondents, as the explanatory variable.

[0093] The brain fatigue state cluster prediction model 112 may be constructed using a third response group, which is a group of responses to multiple questions about brain fatigue states obtained from multiple respondents, as the explanatory variable, and clusters of brain fatigue states obtained by cluster extraction from the third response group as the dependent variable. Here, the multiple questions about brain fatigue states may include at least one of each of the following: a first question regarding the ability to perform a given role, a second question regarding fatigue or activity in daily life, a third question regarding sleep status, and a fourth question regarding mental state.

[0094] Furthermore, the cognitive behavioral characteristics cluster prediction model 113 may be constructed using a fifth response group, which is a group of responses to multiple questions asking about cognitive behavioral characteristics obtained from multiple respondents, as the explanatory variable, and clusters of cognitive behavioral characteristics obtained by cluster extraction from the fifth response group as the dependent variable. Here, the multiple questions asking about cognitive behavioral characteristics may include at least one of each of the following: a fifth question concerning the ability to solve problems, a sixth question concerning tendencies when taking in and understanding information, a seventh question concerning tendencies in how to approach things, an eighth question concerning the ability to process things, and a ninth question concerning self-assessment when viewing oneself objectively.

[0095] The brain fatigue state cluster prediction model 112 created as described above can classify the brain fatigue state of a subject from a set of responses to multiple questions about their brain fatigue state and output brain fatigue state clusters that represent the characteristics of the subject's brain fatigue. Similarly, the cognitive behavioral characteristic cluster prediction model 113 created as described above can classify the cognitive behavioral characteristics of a subject from a set of responses to multiple questions about their cognitive behavioral characteristics and output cognitive behavioral characteristic clusters that represent the characteristics of the subject's cognitive behavioral characteristics.

[0096] [Embodiment 2] Other embodiments of the present invention are described below. For the sake of clarity, components having the same function as those described in the above embodiments will be denoted by the same reference numerals, and their descriptions will not be repeated.

[0097] (Information Processing System 50) Figure 13 shows a schematic configuration of the information processing system 50. As shown in Figure 1, the information processing system 50 includes a provider server 51, a target terminal 2 operated by the target person, and an intervener terminal device 3 operated by the intervener. The provider server 51 is a computer owned by the service provider.

[0098] The service provider will provide services that offer information to help improve the mental health of the target individuals. As one example of how the service provider will provide this service, it will distribute a stress manager application (hereinafter referred to as the stress manager app) to the target individuals and the interveners. The distribution of the stress manager app may be free of charge or on a paid basis. The stress manager app may have different specifications for the target individuals and the interveners.

[0099] The storage device (not shown) of the service provider connected to the provider server 51 stores predetermined information that was stored in the storage unit 11 of the intervener terminal device 1 described in Embodiment 1. The predetermined information is, in other words, the question data 111, the brain fatigue state cluster prediction model 112, the cognitive behavioral characteristics cluster prediction model 113, the brain fatigue state type description and coping method 114, the cognitive behavioral characteristics type description and coping method 115, the recommended content 116, and the correspondence table 117, as shown in Figure 1.

[0100] Furthermore, the control unit (not shown) of the provider server 51 is equipped with predetermined functions that were provided by the control unit 10 of the intervener terminal device 1 described in Embodiment 1. These predetermined functions are, in other words, the first acquisition unit 101, the second acquisition unit 102, the first prediction unit 103, the second prediction unit 104, the first decision unit 105, the second decision unit 106, and the output unit 107, as shown in Figure 1.

[0101] The provider server 51, the subject terminal 2, and the intervener terminal device 3 are all connected to each other in a way that allows for communication. The subject terminal 2, which has the stress manager application provided by the provider server 51 installed, can retrieve question data read from the storage device provided by the service provider and present it to its own terminal device so that the subject can answer it. The subject terminal 2 generates answer data (a group of answers) based on the answers entered by the subject and sends it to the provider server 51.

[0102] Similarly, an intervener terminal device 3, which has installed the stress manager application provided by the provider server 51, can acquire question data read from the storage device provided by the service provider and present it to its terminal device so that the subject can answer it. The intervener terminal device 3 generates answer data (a group of answers) based on the answers entered by the subject and sends it to the provider server 51.

[0103] (Target user terminal 2) As shown in Figure 13, the user terminal 2 includes a control unit 30 and a storage unit 31 for storing various data used by the user terminal 2. The user terminal 2 also includes an input unit 32 for receiving input operations from the user, a communication unit 33 for the user terminal 2 to communicate with other devices, and a display unit 34 which is a display device for displaying images. The input unit 32 may be a touch panel, in which case the display surface of the display unit 34 functions as the input surface of the input unit 32.

[0104] The control unit 30 comprises a first output control unit 301, an input control unit 302, a transmission control unit (transmission unit) 303, and a second output control unit 304.

[0105] The first output control unit 301 presents multiple questions regarding the state of brain fatigue and multiple questions regarding cognitive behavioral characteristics. The first output control unit 301 presents the multiple questions regarding the state of brain fatigue and multiple questions regarding cognitive behavioral characteristics, which are transmitted from the provider server 51 and received by the communication unit 33, for example by displaying them on the display unit 34.

[0106] The input control unit 302 receives input of a first group of answers and a second group of answers to multiple questions asking about the state of brain fatigue and multiple questions asking about cognitive behavioral characteristics. For example, when the subject is asked to answer multiple questions asking about the state of brain fatigue displayed on the display unit 34 using the input unit 32, the input control unit 302 receives input of a first group of answers and a second group of answers.

[0107] The transmission control unit 303 transmits the received first and second response groups to the provider server 51. The transmission control unit 303 controls the communication unit 33 to transmit the received first and second response groups to the provider server 51.

[0108] The second output control unit 304 receives the brain fatigue state segment from the provider server 51. Information regarding the first segment and the cognitive behavioral characteristics segment (second segment) is presented. The second output control unit 304 presents the information regarding the brain fatigue state segment and the cognitive behavioral characteristics segment, which is transmitted from the provider server 51 and received by the communication unit 33, for example by displaying it on the display unit 34.

[0109] Although a detailed explanation will be omitted, the intervener terminal device 3 has the same configuration as the target terminal device 2.

[0110] (Example of information to be sent to target user's terminal 2) Figures 14 and 15 show examples of information presentation for the brain fatigue state segment and the cognitive behavioral characteristics segment. Figure 1401 is an email sent from the intervener to the participant's terminal 2, briefly explaining the actions to be taken based on the survey results. The intervener is the "Home-Based / Remote Work Stress Effect Verification Survey Secretariat."

[0111] Figure 1402 is an email sent from the intervener to the subject's terminal 2, notifying the subject of the type of brain fatigue, the type of specific cognitive behavioral characteristics (characteristic type), and methods for dealing with brain fatigue, as well as methods for dealing with specific cognitive behavioral characteristics.

[0112] Figure 1501 is an email sent from the intervener to the subject's terminal 2, recommending that the subject view content that takes into account the combination of brain fatigue type and specific cognitive behavioral trait type (trait type).

[0113] Figure 1502 shows an email sent from the intervener to the subject's terminal 2, containing the results of two brain fatigue surveys and recommending that the subject view recommended content based on their brain fatigue score (a score based on their state of brain fatigue).

[0114] This configuration makes it possible to help resolve mental and physical problems caused by stress in the subjects, leading to the maintenance of their health. This can contribute to achieving Sustainable Development Goal (SDG) 3, "Ensure healthy lives and promote well-being for all."

[0115] [Examples of implementation using software] The functions of the intervener terminal device 1 and the target terminal device 2 (hereinafter referred to as "devices") can be realized by programs that cause the devices to function as computers, and by programs that cause each control block of the devices (especially each part included in the control unit 10) to function as a computer.

[0116] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., memory) as hardware for executing the program. By executing the program using this control device and storage device, the functions described in each of the embodiments are realized.

[0117] The above program may be recorded on one or more computer-readable recording media, not temporary ones. These recording media may or may not be provided by the above device. In the latter case, the program may be supplied to the above device via any wired or wireless transmission medium.

[0118] Furthermore, some or all of the functions of each of the above-mentioned control blocks can also be realized by logic circuits. For example, an integrated circuit in which logic circuits that function as each of the above-mentioned control blocks are formed is also included in the scope of the present invention.

[0119] Furthermore, each process described in the above embodiments may be performed by AI (Artificial Intelligence). In this case, the AI ​​may operate on the control device described above, or it may operate on other devices (for example, an edge computer or a cloud server).

[0120] The present invention is not limited to the embodiments described above, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention. [Explanation of Symbols]

[0121] 1. Intervener terminal device (information processing device) 2. Target user's device 50 Information Processing Systems 101 First acquisition part 102 Second acquisition part 103 First Prediction Section 104 Second Prediction Section 105 First Decision Section 106 Second Decision Section 107 Output section 112 Brain Fatigue State Cluster Prediction Model (First Prediction Model) 113. Cognitive Behavioral Characteristics Cluster Prediction Model (Second Prediction Model) 301 First Output Control Unit 302 Input Control Unit 304 Second Output Control Unit

Claims

1. An information processing method for obtaining information necessary for presenting information useful for improving the mental health of a subject, which is performed by a computer having at least one processor and at least one memory, The processor obtains a group of first responses from the subject to multiple questions regarding their state of brain fatigue, The processor obtains a second set of responses from the subject to a series of questions regarding cognitive behavioral characteristics, The processor classifies the brain fatigue state of the subject from the first group of responses using a first predictive model and determines a first segment that represents the characteristics of the subject's brain fatigue. The processor classifies the cognitive behavioral characteristics of the subject from the second group of responses using a second predictive model, and determines a second segment that represents the characteristics of the subject's cognitive behavioral characteristics. The processor includes the step of outputting information relating to the first segment and the second segment that it has determined, The aforementioned cognitive behavioral characteristics are features relating to the behavioral patterns of the subject when perceiving and processing the things that are to be processed. The first prediction model described above is: A third response group, which is a group of responses to multiple questions regarding the state of brain fatigue obtained from multiple respondents, is used as the explanatory variable. The fourth response group, which is a group of responses from the selected respondents extracted from the third response group, is used as the explanatory variable. Clusters of brain fatigue states obtained by cluster extraction from the fourth response group are used as the dependent variable. The second prediction model described above is: The sixth response group, which is the group of responses from the relevant individuals extracted from the fifth response group, which is the group of responses from the aforementioned multiple respondents to multiple questions regarding cognitive behavioral characteristics, is used as the explanatory variable, and the clusters of cognitive behavioral characteristics obtained by cluster extraction from the sixth response group are used as the dependent variable. Information processing methods.

2. As a step of outputting information regarding the first segment and the second segment determined above, The processor provides a first type description and a first handling method corresponding to the determined first segment. The information processing method according to claim 1, comprising the step of the processor presenting a second type description and a second handling method corresponding to the determined second segment.

3. As a step of outputting information regarding the first segment and the second segment determined above, The processor determines and presents recommended content corresponding to the first segment based on the first segment it has determined, The information processing method according to claim 1 or 2, comprising the step of the processor determining and presenting recommended content corresponding to the second segment based on the determined second segment.

4. As a step of outputting information regarding the first segment and the second segment determined above, The information processing method according to claim 1 or 2, comprising the step of the processor determining and presenting recommended content corresponding to the combination of the determined first segment and the determined second segment.

5. The aforementioned multiple questions regarding the state of brain fatigue are, The first question concerns the ability to perform the assigned role. The second question concerns fatigue or activity levels in daily life. Third question regarding sleep patterns, and the fourth question regarding mental state, Each of these must contain at least one, The information processing method according to claim 1, wherein in the step of obtaining the first set of answers, the processor obtains the answers of the subject to the first question, the second question, the third question, and the fourth question as the first set of answers.

6. The aforementioned set of questions regarding cognitive and behavioral characteristics is: The fifth question regarding problem-solving ability, Question 6 regarding tendencies when taking in and understanding information, Question 7 regarding tendencies in how you approach things, Question 8 regarding the ability to handle things, and, Question 9 regarding self-assessment when viewing oneself objectively, Each of these must contain at least one, The information processing method according to claim 1 or 5, wherein in the step of obtaining the second set of answers, the processor obtains the answers of the subject to the fifth question, the sixth question, the seventh question, the eighth question, and the ninth question as the second set of answers.

7. An information processing method for obtaining information necessary for presenting information useful for improving the mental health of a subject, which is performed by a computer having at least one processor and at least one memory, The processor obtains a group of first responses from the subject to multiple questions regarding their state of brain fatigue, The processor obtains a second set of responses from the subject to a series of questions regarding cognitive behavioral characteristics, The processor classifies the brain fatigue state of the subject from the first group of responses using a first predictive model and determines a first segment that represents the characteristics of the subject's brain fatigue. The processor classifies the cognitive behavioral characteristics of the subject from the second group of responses using a second predictive model, and determines a second segment that represents the characteristics of the subject's cognitive behavioral characteristics. The processor includes the step of outputting information relating to the first segment and the second segment that it has determined, The aforementioned cognitive behavioral characteristics are features relating to the behavioral patterns of the subject when perceiving and processing the things that are to be processed. In the step of determining the first segment, the processor classifies the brain fatigue state of the subject from the first group of responses using the first predictive model, In the step of determining the second segment, the processor classifies the cognitive behavioral characteristics of the subject from the second group of responses using a second predictive model. The first predictive model is constructed using a third response group, which is a group of responses to multiple questions about the state of brain fatigue obtained from multiple respondents, as the explanatory variable, and clusters of brain fatigue obtained by cluster extraction from the third response group as the dependent variable. The second predictive model is constructed using a fifth response group, which is a set of responses to multiple questions asking about cognitive behavioral characteristics obtained from multiple respondents, as the explanatory variable, and clusters of cognitive behavioral characteristics obtained by cluster extraction from the fifth response group as the dependent variable. The aforementioned multiple questions regarding the state of brain fatigue are, The first question concerns the ability to perform the assigned role. The second question concerns fatigue or activity levels in daily life. Third question regarding sleep patterns, and the fourth question regarding mental state, Each of these must contain at least one, The aforementioned set of questions regarding cognitive and behavioral characteristics is: The fifth question regarding problem-solving ability, Question 6 regarding tendencies when taking in and understanding information, Question 7 regarding tendencies in how you approach things, Question 8 regarding the ability to handle things, and, Question 9 regarding self-assessment when viewing oneself objectively, An information processing method that includes at least one of each of the following.

8. A method for creating a predictive model to be executed by a computer having at least one processor and at least one memory, The processor obtains a third set of responses, which is a set of responses from multiple respondents to multiple questions regarding their state of brain fatigue. The processor obtains a fifth set of responses, which is a set of responses from the multiple respondents to a set of questions asking about cognitive behavioral characteristics. The processor performs the step of extracting respondents as applicable if the total score of each of the multiple respondents calculated from the third group of responses is equal to or greater than a predetermined value. The process involves the processor creating a first predictive model using a fourth response group, which is the group of responses from the relevant individuals extracted from the third response group, as an explanatory variable, and clusters of brain fatigue states obtained by cluster extraction from the fourth response group as the dependent variable. A method for creating a predictive model, comprising the step of creating a second predictive model using a sixth group of responses, which is the group of responses of the relevant persons extracted from the fifth group of responses, as an explanatory variable, and clusters of cognitive behavioral characteristics obtained by cluster extraction from the sixth group of responses as the dependent variable.

9. A method for creating a predictive model to be executed by a computer having at least one processor and at least one memory, The processor obtains a third set of responses, which is a set of responses from multiple respondents to multiple questions regarding their state of brain fatigue. The processor obtains a fifth set of responses, which is a set of responses from the multiple respondents to a set of questions asking about cognitive behavioral characteristics. The processor creates a first predictive model using the third group of responses as explanatory variables and the clusters of brain fatigue states obtained by cluster extraction from the third group of responses as the target variable. The processor includes the step of creating a second predictive model using the fifth group of responses as explanatory variables and clusters of cognitive behavioral characteristics extracted from the fifth group of responses as the dependent variable. The aforementioned multiple questions regarding the state of brain fatigue are, The first question concerns the ability to perform the assigned role. The second question concerns fatigue or activity levels in daily life. Third question regarding sleep patterns, and the fourth question regarding mental state, Each of these must contain at least one, The aforementioned set of questions regarding cognitive and behavioral characteristics is: The fifth question regarding problem-solving ability, Question 6 regarding tendencies when taking in and understanding information, Question 7 regarding tendencies in how you approach things, Question 8 regarding the ability to handle things, and, Question 9 regarding self-assessment when viewing oneself objectively, A method for creating a predictive model that includes at least one of each of the following.

10. An information processing device for obtaining information necessary to present information that is useful for improving the mental health of the target person, A first acquisition unit that acquires the first group of responses from subjects to multiple questions regarding their state of brain fatigue, A second acquisition unit that acquires a second set of responses from the subject to multiple questions regarding cognitive behavioral characteristics, A first determination unit classifies the brain fatigue state of the subject using a first prediction model from the first group of responses and determines a first segment that represents the characteristics of the subject's brain fatigue, A second determination unit classifies the cognitive behavioral characteristics of the subject using a second prediction model from the second set of responses and determines a second segment that represents the characteristics of the subject's cognitive behavioral characteristics. The system includes an output unit that outputs information relating to the determined first segment and the second segment, The aforementioned cognitive behavioral characteristics are features relating to the behavioral patterns of the subject when recognizing and processing the things that are to be processed. The first prediction model described above is: A third response group, which is a group of responses to multiple questions regarding the state of brain fatigue obtained from multiple respondents, is used as the explanatory variable. The fourth response group, which is a group of responses from the selected respondents extracted from the third response group, is used as the explanatory variable. Clusters of brain fatigue states obtained by cluster extraction from the fourth response group are used as the dependent variable. The second prediction model described above is: The sixth response group, which is the group of responses from the relevant individuals extracted from the fifth response group, which is the group of responses from the aforementioned multiple respondents to multiple questions regarding cognitive behavioral characteristics, is used as the explanatory variable, and the clusters of cognitive behavioral characteristics obtained by cluster extraction from the sixth response group are used as the dependent variable. Information processing device.

11. An information processing system including an information processing device for obtaining information necessary to present information useful for improving the mental health of a subject, and a subject terminal operated by the subject, which is communicably connected to the information processing device, The aforementioned information processing device is A first acquisition unit that acquires a first group of responses from the subject to multiple questions regarding the state of brain fatigue, A second acquisition unit that acquires a second set of responses from the subject to multiple questions regarding cognitive behavioral characteristics, A first determination unit classifies the brain fatigue state of the subject using a first prediction model from the first group of responses and determines a first segment that represents the characteristics of the subject's brain fatigue, A second determination unit classifies the cognitive behavioral characteristics of the subject using a second prediction model from the second set of responses and determines a second segment that represents the characteristics of the subject's cognitive behavioral characteristics. The system includes a transmission unit that transmits information regarding the determined first segment and the second segment to the target user terminal, The aforementioned cognitive behavioral characteristics are features relating to the behavioral patterns of the subject when perceiving and processing the things that are to be processed. The aforementioned target user terminal is A first output control unit presents a plurality of questions regarding the state of brain fatigue and a plurality of questions regarding the cognitive behavioral characteristics, An input control unit that receives input of a first group of answers and a second group of answers to a plurality of questions asking about the state of brain fatigue and a plurality of questions asking about cognitive behavioral characteristics, A transmission unit that transmits the received first group of answers and second group of answers to the information processing device, The system includes a second output control unit that displays information about the first segment and the second segment received from the information processing device, The first prediction model described above is: A third response group, which is a group of responses to multiple questions regarding the state of brain fatigue obtained from multiple respondents, is used as the explanatory variable. The fourth response group, which is a group of responses from the selected respondents extracted from the third response group, is used as the explanatory variable. Clusters of brain fatigue states obtained by cluster extraction from the fourth response group are used as the dependent variable. The second prediction model described above is: The sixth response group, which is the group of responses from the relevant individuals extracted from the fifth response group, which is the group of responses from the aforementioned multiple respondents to multiple questions regarding cognitive behavioral characteristics, is used as the explanatory variable, and the clusters of cognitive behavioral characteristics obtained by cluster extraction from the sixth response group are used as the dependent variable. Information processing system.

12. A control program for causing a computer to function as an information processing device according to claim 10, wherein the control program causes the computer to function as the first acquisition unit, the second acquisition unit, the first determination unit, the second determination unit, and the output unit.

13. A control program for causing a computer to function as a target terminal that communicates with an information processing device to obtain information necessary for presenting information that is useful for improving the mental health of the target, The aforementioned user terminal is equipped with: A first output control unit presents multiple questions regarding the state of brain fatigue and multiple questions regarding cognitive behavioral characteristics, An input control unit that receives input of a first group of answers and a second group of answers to multiple questions regarding the state of brain fatigue and multiple questions regarding cognitive behavioral characteristics, A transmission unit that transmits the received first group of answers and second group of answers to the information processing device, A control program for a computer to function as a second output control unit that receives and presents the following information from the information processing device: (1) a first prediction model created using a third response group, which is a group of responses from multiple respondents to multiple questions asking about the state of brain fatigue, where the total score of each of the multiple respondents' brain fatigue scales calculated from the third response group is equal to or greater than a predetermined value, with the fourth response group, which is a group of responses from the multiple respondents to the multiple respondents to the multiple questions asking about the state of brain fatigue, as the explanatory variable, and the fourth response group, which is a group of responses from the multiple respondents to the multiple respondents to the multiple questions asking about the state of brain fatigue, as the dependent variable, and classifying the brain fatigue state of the subjects from the first response group to determine information regarding the first segment representing the characteristics of the subjects' brain fatigue; and (2) a second prediction model created using a second prediction model created using a second response group, which is a group of responses from the multiple respondents to the multiple respondents to the multiple respondents to the multiple questions asking about the cognitive behavioral characteristics, where the sixth response group, which is a group of responses from the multiple respondents to the multiple respondents to the multiple respondents to the multiple questions asking about the cognitive behavioral characteristics, as the explanatory variable, and the sixth response group, which is a group of cognitive behavioral characteristics, is clustered and classifying the cognitive behavioral characteristics of the subjects from the second response group to determine information regarding the characteristics of the subjects' cognitive behavioral characteristics.

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