JP7674282B2 - Social participation status analysis device and program - Google Patents

Description

The present invention relates to a technology for analyzing a situation based on the behavior of participants. In particular, the present invention relates to a technology for analyzing the social participation status of participants based on their social participation behavior. Note that the term "participant" includes various concepts related to people, such as residents, customers, users, related parties, subjects, and targets.

Currently, data analysis is being conducted in a variety of fields. Among these, analysis of people's movement behavior for purposes such as purchasing trends, crime prevention, and logistics efficiency is attracting attention. Furthermore, as we enter an aging society, health issues of the elderly, such as dementia and nursing care issues, are becoming apparent. It is becoming clear that by revitalizing the social participation behavior of the elderly (including social participation activities), it is possible to prevent the onset of dementia and the transition to nursing care among the elderly. In other words, in addition to the conventional diet and exercise, it will be important to visualize social participation behavior and the social participation status based on this as health indicators.

For example, Patent Document 1 discloses a technology for preventing the need for nursing care. More specifically, it describes how "physical fitness and cognitive function measurements, lifestyle information, and a social participation score are acquired by an acquisition unit" (abstract). It also discloses that the user's location information is used to calculate the social participation score (Claim 2, etc.).

International Publication No. 2018/100797

Here, in Patent Document 1, the user's future physical fitness value is predicted based on the results of physical fitness tests and cognitive function tests. In this way, Patent Document 1 requires the preparation of various data. Also, in physical fitness tests, etc., a place for the measurement must be prepared and the measurement work must be carried out. As described above, Patent Document 1 has the problem that it takes time and effort to calculate the social participation score.

To reduce this effort, it is possible to reduce the amount of data used to calculate the social participation score. However, reducing the amount of data may reduce the reliability of the social participation score. As a result, there is a risk that the accuracy of the analysis of social participation status may decrease.

The present invention aims to provide a simpler configuration for analyzing social participation status while maintaining accuracy.

To solve the above problem, the present invention executes update-related processing for various information, such as social participation information identified based on location information, according to its reliability. Note that this update-related processing includes updating the information, collecting additional information for the update, and making inquiries of participants for the collection. Note that the information includes social participation information and various master information.

A more specific configuration of the present invention is a social participation status analysis device that analyzes the social participation status of participants, the social participation status analysis device including a communication unit that receives behavioral information in which a position and time indicating the behavioral history of each of a plurality of participants are associated with each other, and the behavioral information is divided into predetermined units, a center of gravity of the stay of the participant and a time period of stay are identified, and for each stay location where the participant can stay, a stay location corresponding to the center of gravity of the stay is estimated using stay location master information having a stay location ID, stay location name, and stay location center coordinates, and activity content of the estimated stay location is estimated using stay purpose master information indicating activity content that is the purpose of stay for each stay location, thereby identifying social participation information including activity content of the participant. The social participation status analysis device includes a social participation information identification unit that determines the reliability of a plurality of viewpoints that indicate the accuracy of the social participation information , a reliability calculation unit that calculates reliability of each of a plurality of viewpoints that indicate the accuracy of the social participation information, performs an integration process of the calculated plurality of reliability, and calculates an integrated reliability, a social participation information verification unit that outputs an information collection plan formulation request if the integrated reliability is less than a predetermined threshold, an information collection plan formulation unit that outputs an information collection request to the communication unit in response to the information collection plan formulation request for collecting additional information, an information update unit that updates the social participation information using the additional information collected in response to the information collection request, and a social participation status evaluation unit that analyzes the social participation status of the participant based on the updated social participation information. The present invention also includes a method using the social participation status analysis device and a program for operating the social participation status analysis device.

The present invention also includes a user terminal that connects to the social participation status analysis device and collects behavioral information and social participation information (additional information), a method using the same, and a program for functioning the user terminal. The present invention also includes a social participation status analysis system that includes the social participation status analysis device and the user terminal.

The present invention makes it possible to analyze social participation status with high accuracy.

FIG. 1 is a diagram showing the concept of an embodiment of the present invention. FIG. 1 is a system configuration diagram of a social participation status analysis system according to an embodiment of the present invention. 2 is a configuration diagram of a user terminal and a social participation status analysis server in one embodiment of the present invention. FIG. FIG. 4 is a diagram showing user management information used in one embodiment of the present invention. FIG. 4 is a diagram showing terminal management information used in one embodiment of the present invention. FIG. 2 is a diagram showing social participation information used in one embodiment of the present invention. FIG. 11 is a diagram showing stay location master information used in one embodiment of the present invention. FIG. 2 is a diagram showing stay purpose master information used in one embodiment of the present invention. FIG. 13 is a diagram showing social participation information verification information used in one embodiment of the present invention. FIG. 2 is an overall processing sequence diagram showing the overall processing in one embodiment of the present invention. 11 is a flowchart showing an analysis process of social participation information in an embodiment of the present invention. 11 is a flowchart showing a process of identifying social participation information in an embodiment of the present invention. 11 is a flowchart showing a reliability calculation process according to an embodiment of the present invention. 11 is a flowchart showing a calculation process of a risk influence degree in an embodiment of the present invention. FIG. 13 is a diagram showing a social participation information collection notification screen in an embodiment of the present invention. FIG. 13 is a diagram showing a social participation information collection screen in an embodiment of the present invention. FIG. 11 is a diagram showing additional social participation information used in one embodiment of the present invention. FIG. 13 is a diagram showing a social participation status evaluation screen in one embodiment of the present invention.

Below, one embodiment of the present invention will be explained using drawings in the following order: Concept, Configuration and Information, Processing Flow.

<Principles>
First, the concept of this embodiment will be described with reference to FIG. 1. In regions A and B, each participant (user) such as a resident carries a user terminal 101-1, 101-2, or 101-3, which is a type of user terminal, and performs social participation behavior. For this reason, each user terminal 101-1, 101-2, or 101-3 uses a GPS function or the like to acquire location information associated with the social participation behavior of the participant (behavioral information collection unit 26, described later). Note that a region is a concept that includes so-called districts, and the unit can be set arbitrarily, such as a prefecture. Furthermore, a region is an example of a unit society in this embodiment. Furthermore, unit societies include organizations such as companies and health insurance associations, and local communities.

Here, social participation behavior includes travel to various facilities such as home, factories (workplaces), stores, fitness clubs (gyms), offices (workplaces), and restaurants, as well as activities at facilities. In addition, participants are not limited to activities within a local area, but are also considered to be engaged in activities across local areas.

Then, the social participation status analysis server 114 installed in the data center collects behavioral information from each user terminal 101-1, 101-2, 101-3 (hereinafter, user terminal 101) and identifies the social participation information of the participants. The behavioral information indicates the behavioral history of the participants, and location information can be used. The social participation status analysis server 114 then analyzes the social participation status of the participants based on the social participation information. This analysis also includes evaluating the social participation status. The social participation status analysis server 114 can also present such analysis results to various business systems. As a result, the business systems are assumed to be systems used by administrative agencies in regions A and B, insurance companies, nursing care facilities, facility management companies such as fitness clubs, and point management companies. Furthermore, the analysis results include environmental indicators that indicate the ease of participation for each unit society such as a region, various aggregated information, policy plans using these, and information to support these. The analysis results may also be notified to the user terminal 101. This social participation status analysis server 114 is a type of social participation status analysis device.

Furthermore, the social participation status analysis server 114 notifies the user terminal 101 of an information collection request, which is a type of update-related process, according to the reliability of the identified social participation information. Then, the user terminal 101 notifies the social participation status analysis server 114 of additional information in response to this. As a result, the social participation status analysis server 114 can update the social participation information more appropriately. Therefore, the social participation status analysis server 114 can improve the accuracy of the analysis of the social participation status based on the social participation information. Note that, as the social participation information in this embodiment, a social participation index calculated by taking into account the diversity and complexity of behavior may be used. More specifically, it is also possible to determine the social participation category of the behavior based on the behavior information, and use a social participation index that indicates the participant's social involvement status based on this.

<Configuration and Information>
Next, the configuration and information of this embodiment for realizing the concept shown in Fig. 1 will be described. Fig. 2 is a system configuration diagram of a social participation status analysis system in this embodiment. The social participation status analysis system includes user terminals 101-1, 101-2, 101-3, a social participation status analysis server 114, and business systems 30 to 60, which are connected via a network 113 such as the Internet. Fig. 2 shows a fitness club, an insurance company, a care facility management company, and a point management company as examples of operators of the business systems 30 to 60. These operators can be realized by a computer system consisting of a server and a PC.

Here, each of the business systems 30 to 60 can use the analysis results of the social participation status analysis server 114. For example, the fitness club business system 30 can formulate a menu for participants based on the analysis results. Also, the insurance company business system 40 can develop insurance products and calculate insurance rates for participants based on the analysis results. Also, the care facility management company business system 50 can develop care menus and formulate plans for new construction and renovation of facilities based on the analysis results. Furthermore, the point management company business system 60 may award points to participants based on the analysis results. Note that each of these business systems 30 to 60 may use behavioral information or social participation information itself as the analysis results.

The devices that make up the social participation status analysis system are described below. The social participation status analysis server 114 is realized by a computer device installed in a data center. The social participation status analysis server 114 has a communication unit 11, an input/output unit 12, a social participation information identification unit 13, a social participation information verification unit 14, a reliability calculation unit 15, a risk impact calculation unit 16, an information collection plan formulation unit 17, a risk prediction model learning unit 18, a risk prediction unit 19, an information update unit 20, a social participation status evaluation unit 21, and a memory unit 22. The configuration of these components is described below, and the details of the processing are described later using a flowchart.

The communication unit 11 has an interface function for connecting to the network 113. The input/output unit 12 has an interface function for connecting to each of the operation management terminals 10-1 and 10-2. For this reason, the communication unit 11 and the input/output unit 12 may be configured as an integrated unit.

The social participation information identification unit 13 identifies social participation information from the behavioral information notified from the user terminal 101. This behavioral information includes location information of the corresponding user terminal 101, i.e., location information of the participant. The social participation information also includes the content of the participant's activities. Details of the social participation information will be described later.

The social participation information verification unit 14 verifies the social participation information of the participants. This verification includes at least one of verification based on reliability and verification based on risk impact. For this purpose, it is preferable that the social participation information verification unit 14 has a reliability calculation unit 15 and a risk impact calculation unit 16. Here, the reliability calculation unit 15 calculates the reliability of the identified social participation information. This reliability is an index showing the deviation or closeness of the social participation information from the true information, and it is also possible to use accuracy or precision. In addition, the risk impact calculation unit 16 calculates the risk impact indicating the degree of impact on health risks predicted for the participant in the social participation information. Note that this risk includes future risks of needing nursing care and risks of becoming bedridden.

The information collection plan formulation unit 17 formulates a plan for notifying information collection requests, which is a type of update-related processing, and notifies information collection requests accordingly. For example, the information collection plan formulation unit 17 formulates a plan to notify information collection requests during times of low communication volume on the network 113 or when participants' activities have settled down. It is also desirable for the information collection plan formulation unit 17 to output information collection requests. For this reason, the information collection plan formulation unit 17 in this embodiment also includes making information collection requests each time, without formulating future plans or schedules.

The risk prediction model learning unit 18 learns a risk prediction model in machine learning and AI (Artificial Intelligence) technology. Here, the risk prediction model is a model for calculating the above-mentioned health risks. This model is used by the risk prediction unit 19. In other words, the risk prediction unit 19 predicts the above-mentioned risks using the risk prediction model. Note that the risk prediction model learning unit 18 can be omitted.

The information update unit 20 updates related information according to the reliability. The information to be updated includes social participation information, and the stay location master information 134 and stay purpose master information 135 stored in the memory unit 22. The information update unit 20 and the information collection plan formulation unit 17 can be realized as an example of an update-related processing unit that executes update-related processing on information. Therefore, the update-related processing includes the updating of information itself and the processing of collecting additional information for updating.

The information updating unit 20 may also be divided into a social participation information updating unit for updating the social participation information and a master information updating unit for updating the stay location master information 134 and the stay purpose master information 135. Furthermore, at least one of the social participation information updating unit and the master information updating unit may be provided. The social participation status evaluation unit 21 performs analysis such as evaluation of the social participation status of the participants based on the updated social participation information. The memory unit 22 stores various information used for processing in the social participation status analysis server 114 and information that is the processing result.

Next, the operation management terminals 10-1 and 10-2 (hereinafter simply referred to as the operation management terminal 10) will be described. The operation management terminal 10 can be realized by a computer, and is used by the operator of the data center. For this purpose, it connects to the social participation status analysis server 114 via the input/output unit 12, outputs various instructions, and receives processing results.

Next, the user terminal 101 will be described. The user terminal 101 is a device brought by the participant, which collects behavioral information and notifies the social participation status analysis server 114. In this embodiment, location information of the user terminal 101, that is, location information of the participants, is collected as behavioral information. For this purpose, the user terminal 101 can be realized by a portable information processing device such as a smartphone, mobile phone, or tablet, or a portable GPS (Global Positioning System) transmitter. The user terminal 101 in this embodiment also has a communication unit 23, an input/output unit 24, a behavioral information detection unit 25, a behavioral information collection unit 26, a social participation information collection unit 27, and a memory unit 28.

The communication unit 23 has an interface function for connecting to the network 113. The input/output unit 24 receives input from participants using the user terminal 101 and outputs processing results. Note that the input/output unit 24 may be configured as separate input and output units.

The behavioral information detection unit 25 has a function of detecting behavioral information of participants. In this embodiment, location information is used as the behavioral information, and the location information is detected by the GPS function. The behavioral information collection unit 26 collects the behavioral information detected by the behavioral information detection unit 25. The collected behavioral information is then notified to the social participation status analysis server 114 via the communication unit 23.

The social participation information collection unit 27 collects additional information in response to an information collection request from the social participation status analysis server 114. The collection of additional information includes accepting additional information input by participants via the input/output unit 24 and collecting behavioral information from the behavioral information detection unit 25. The memory unit 28 contains information used for processing in the user terminal 101 and information indicating the processing results.

The various processes of the user terminal 101 and the social participation status analysis server 114 can be realized by computer programs (software), dedicated hardware, or an FPGA (Field-Programmable Gate Array). Examples of this implementation will be described later.

Next, the business systems 30 to 60 are computer systems used in the business of fitness clubs, insurance companies, nursing care facility management companies, etc. In this embodiment, behavioral information may be notified from these to the social participation status analysis server 114. For example, at a fitness club, it is expected that when a participant enters the facility, the position information and the participant's identification information (user ID) will be notified from the business system 30 to the social participation status analysis server 114.

This concludes the explanation of Figure 2, but the number of devices is merely an example and is not limited to this. Furthermore, the operators of business systems 30 to 60 are not limited to the example shown.

Next, an example of the implementation of the user terminal 101 and the social participation status analysis server 114 that execute the main processing of this embodiment will be described. FIG. 3 is a configuration diagram of the user terminal 101 and the social participation status analysis server 114. In this embodiment, the user terminal 101 is implemented as a program (app) or a portable information processing device such as a smartphone. The social participation status analysis server 114 is also implemented as a server, which is a type of computer that executes processing according to a program. The configuration of each will be described below.

First, the user terminal 101 has an input/output device 102, a computing device 103, a behavioral information sensor 104, a communication I/F 106, a main memory device 107, and an auxiliary memory device 110, which are connected to each other via a communication path 105 such as a bus.

The input/output device 102 corresponds to the input/output unit 24 in FIG. 2, and can be realized by a touch panel. The input/output device 102 may be realized by an input device such as a keyboard, and an output device such as a monitor. The calculation device 103 can be realized by a processor such as a CPU, and executes calculations according to various programs (applications) described below. The behavior information sensor 104 has a function of detecting behavior information of participants, and corresponds to the behavior information detection unit 25. Therefore, the behavior information sensor 104 can be realized by a sensor that detects location information or information indicating the movements of participants, such as a GPS sensor or an acceleration sensor. The behavior information sensor 104 is not limited to these.

The main memory device 107 can be realized by a memory, and programs and information used by the computing device 103 are deployed on it. The programs deployed on the main memory device 107 include a behavioral information collection program 108 and a social participation information collection program 109. The functions of the behavioral information collection program 108 correspond to the functions of the behavioral information collection unit 26. Furthermore, the functions of the social participation information collection program 109 correspond to the functions of the social participation information collection unit 27. The behavioral information collection program 108 and the social participation information collection program 109 may be realized by a single program.

The auxiliary storage device 110 stores terminal information 111 and collected information 112. Here, the terminal information 111 is information about the user terminal 101, and includes its identification information and the user ID of the participant. The collected information 112 includes collected behavioral information and social participation information. The auxiliary storage device 110 may be realized by an internal storage, or may be realized by an external storage such as a memory card, HDD (Hard Disk Drive), or SSD (Solid State Drive). Furthermore, it is preferable that the auxiliary storage device 110 stores the above-mentioned programs. Furthermore, it is preferable that these programs are distributed via a network 113 or stored in a storage medium. Although not shown in FIG. 3, the user terminal 101 stores an OS (Operating System) that realizes basic functions.

The communication I/F 106 corresponds to the communication unit 23, and communicates with the social participation status analysis server 114 via the network 113. In addition, it is preferable that the communication I/F 106 executes wireless communication, but wired communication may also be used.

Next, the social participation status analysis server 114 will be described. The social participation status analysis server 114 has a communication I/F 115, an input device 116, an output device 117, a computing device 118, a main memory device 119, and an auxiliary memory device 130, which are connected to each other via a communication path 138 such as a bus. The input device 116 and the output device 117 correspond to the input/output unit 12 in Figure 2, and have the function of connecting to the operation management terminals 10-1 and 10-2.

Like the computing device 103, the computing device 118 can be realized by a processor such as a CPU, and executes calculations according to various programs described below. The main storage device 119 can be realized by a memory, and the programs and information used by the computing device 118 are deployed in it. The programs deployed in the main storage device 119 include a social participation information identification program 121, a social participation information verification program 122, an information collection plan formulation program 125, a risk prediction model learning program 126, a risk prediction program 127, an information update program 128, and a social participation status evaluation program 129.

Here, the functions realized by the social participation information identification program 121 correspond to the functions of the social participation information identification unit 13. The correspondence between the other programs and each unit shown in FIG.
Social participation information verification program 122: Social participation information verification unit 14
Information collection plan formulation program 125: Information collection plan formulation section 17
Risk prediction model learning program 126: risk prediction model learning unit 18
Risk Prediction Program 127: Risk Prediction Unit 19
Information update program 128: Information update unit 20
Social Participation Status Assessment Program 129: Social Participation Status Assessment Unit 21
The social participation information verification program 122 has a reliability calculation module 123 and a risk impact calculation module 124, and the functions realized by these correspond to the functions of the reliability calculation unit 15 and the risk impact calculation unit 16, respectively. Each of these modules may be realized by an independent program. Furthermore, each of these programs may be aggregated to constitute each program by one or more programs.

The auxiliary storage device 130 stores user management information 131, terminal management information 132, social participation information 133, stay location master information 134, stay purpose master information 135, social participation information verification information 136, and risk prediction model 137. Here, these pieces of information will be explained. First, FIG. 4 is a diagram showing user management information 131 used in this embodiment. User management information 131 is information about participants who are users. And, for each participant, user management information 131 has the following items: user ID 701, name 702, date of birth 703, gender 704, address 705, contact information 706, and family contact information 707. Here, user ID 701 is identification information that identifies the participant. And, name 702, date of birth 703, gender 704, address 705, contact information 706, and family contact information 707 indicate the name, etc., of the participant. It should be noted that these can be omitted.

Next, FIG. 5 is a diagram showing the terminal management information 132 used in this embodiment. The terminal management information 132 is information related to the user terminal 101. The terminal management information 132 has the following items for each user terminal 101: user ID 701, model used 801, OS 802, and OS version 803. The user ID 701 is the same as that in FIG. 4, but information for identifying the user terminal 101 may also be provided. The model used 801 indicates the model of the user terminal 101 in question, that is, the model used by the participant. The OS 802 and OS version 803 are information for identifying the OS and its version used by the user terminal 101 in question. Note that in addition to or instead of the model used 801, OS 802, and OS version 803, information related to the functions of the user terminal 101 may be used.

Next, FIG. 6 is a diagram showing the social participation information 133 used in this embodiment. The social participation information 133 is information that indicates the actions of participants. For each action, the social participation information 133 has the following items: user ID 701, social participation information ID 901, stay center coordinates 902, stay start 903, stay end 904, stay location ID 905, and activity details 906. The user ID 701 is the same item as in FIG. 4 and FIG. 5. The social participation information ID 901 is information that identifies the social participation information that serves as the management unit, that is, each record of the social participation information 133.

The stay center coordinates 902 indicate the center position in a group of location information under specified conditions such as a specified time or location. Stay start 903 and stay end 904 indicate the start and end times when the specified conditions are met. Stay location ID 905 is an item that identifies the stay location indicated by the behavior information represented by the location information, and can identify facilities, etc. The stay location ID 905 is an item that is specified according to the behavior information represented by the location information, for example, using the stay location master information 134 described below.

The activity details 906 are items that are specified according to the stay location ID 905, for example, using the stay purpose master information 135 described below. In this embodiment, the activity details 906 are exemplified by athletic activities, cultural activities, and volunteer activities, but are not limited to these. In this embodiment, the type of activity is used as the activity details 906, but a quantified amount of activity may also be used. The items of the stay center coordinates 902, stay start 903, stay end 904, stay location ID 905, and activity details 906 are items that indicate the content of the action. These items only need to indicate the action of the participant, and some items can be omitted. They can also be replaced with other items.

Figure 7 is a diagram showing the stay location master information 134 used in this embodiment. The stay location master information 134 is information on stay locations, such as facilities, where participants can stay. The stay location master information 134 has the following items for each stay location: stay location ID 905, stay location name 1001, and stay location center coordinates 1002.

Here, the stay location ID 905 is identification information that identifies the relevant intervening location. The stay location name 1001 indicates the name of the relevant stay location, but this item can be omitted. Furthermore, the stay location center coordinates 1002 is an item that indicates the center position of the relevant stay location.

Figure 8 is a diagram showing the purpose of stay master information 135 used in this embodiment. The purpose of stay master information 135 is information that indicates the purpose of stay for each place of stay, that is, the activity details. For this reason, the purpose of stay master information 135 has the following items for each place of stay: place of stay ID 905, purpose of stay No. 1101, day of activity 1102, time of activity 1103, activity details 1104, and user ID list 1105.

The stay location ID 905 is the same as that in FIG. 7. The stay purpose No. 1101 is an item for specifying the stay purpose (activity content) of the corresponding stay location, and in this embodiment, a number is used. The activity day of the week 1102 and activity time 1103 indicate the day of the week and time period during which the activity is possible at the corresponding stay location. These can be omitted. Also, instead of or in addition to the activity day of the week 1102, the month and date may be used. The activity content 1104 indicates the activity content that is possible at the corresponding stay location. The user ID list 1105 records the user IDs that are the user IDs of the participants who used the corresponding stay location.

Figure 9 is a diagram showing the social participation information verification information 136 used in this embodiment. The social participation information verification information 136 is information for verifying the social participation information 133. For this reason, the social participation information verification information 136 has the following items for each social participation information: a user ID 701, a social participation information ID 901, a terminal-dependent reliability 1201, an estimated stay location reliability 1202, a user-specific reliability 1203, a stay purpose reliability 1204, an integrated reliability 1205, a risk impact 1206, a verification score 1207, and a verification result 1208.

The user ID 701 and the social participation information ID 901 are the items described above. The terminal-dependent reliability 1201, the stay location estimation reliability 1202, the user-specific reliability 1203, the stay purpose reliability 1204, and the integrated reliability 1205 are each items that indicate the reliability of the social participation information 133.

The terminal-dependent reliability 1201 indicates the reliability according to the user terminal 101. For example, it is an item calculated based on the length of time until the location information measurement is resumed or started after the user terminal 101 starts moving, the performance of the behavior information detection unit 25 such as a GPS sensor, and the like. Therefore, the terminal-dependent reliability 1201 can also be expressed as an item that depends on software such as an OS and hardware such as a sensor. Therefore, it can be said that the higher the performance of these, the higher the reliability tends to be.

The estimated reliability of stay locations 1202 indicates the reliability according to the locational requirements of the stay locations where the participant stayed. For example, it is calculated based on the distance between the center of the stay location and the center of gravity of the location information, the distribution of location information during the stay time, the time outside of GPS range during the stay time, the number of location information measurement points during the stay, the activity level during the stay, the area of the stay location, the number of adjacent stay locations, etc. This is because the reliability tends to be higher when the stay location is large or there are not many other stay locations nearby, since the reliability of the stay location is higher.

The user-specific reliability 1203 indicates the reliability according to the participant. For example, it is calculated based on the history of the participant's behavioral information. More specifically, the reliability tends to be higher the more frequently the participant stays at a particular location. Furthermore, the stay purpose reliability 1204 indicates the reliability according to the stay purpose of the location where the participant stayed. For example, the reliability tends to be lower in the following cases:
When the user ID of the relevant participant is not registered in the user ID list 1105 of the stay purpose master information 135 When multiple stay purpose numbers 1101 or activity details 1104 exist When there is no information registered in the stay purpose master information 135 And, the integrated reliability 1205 indicates an integrated reliability calculated based on the terminal-dependent reliability 1201, the stay location estimated reliability 1202, the user-specific reliability 1203, and the stay purpose reliability 1204. Note that at least one of the terminal-dependent reliability 1201, the stay location estimated reliability 1202, the user-specific reliability 1203, and the stay purpose reliability 1204 may be used. Furthermore, a reliability other than these may be used.

Risk impact level 1206 is an item that indicates the degree of impact on health risks predicted for the participant. This is an item that is calculated by the risk impact level calculation unit 16, and is calculated based on the social participation information. Furthermore, verification score 1207 is an item that indicates the degree to which collection of additional information is necessary, calculated based on integrated reliability 1205. In this embodiment, the higher the value of this score, the more necessary it is to collect additional information, i.e., to conduct an investigation. Finally, verification result 1208 is information that indicates whether collection of additional information is necessary based on verification score 1207. In this embodiment, in the second record in FIG. 9, it is recorded that "additional information collection is necessary" because verification score 1207 is greater than a predetermined threshold.

Note that the risk prediction model 137 can use a known machine learning model, so a detailed description of its contents will be omitted. This concludes the description of the information stored in the auxiliary storage device 130.

It is also preferable that the auxiliary storage device 130 stores the above-mentioned programs. Furthermore, it is also preferable that these programs are distributed via the network 113 or stored in a storage medium.

The auxiliary storage device 130 can be realized by a hard disk drive (HDD) or a solid state drive (SSD). Furthermore, the auxiliary storage device 130 may be realized as a database provided outside the social participation status analysis server 114.

<Processing flow>
Next, the process flow in this embodiment will be described. In this case, the processing subject of each process will be described using the configuration (each unit) shown in FIG. 2. First, FIG. 10 is an overall process sequence diagram showing the overall process in this embodiment. First, in step S11, the user terminal 101 notifies the social participation status analysis server 114 of a user registration application. For this purpose, the user terminal 101 accepts a registration application instruction from the participant via the input/output unit 24. In response to this, the user management information such as the user ID is read from the terminal information 111 in the storage unit 28 by a function of the OS or the like. Then, the user registration application including the user management information is notified to the social participation status analysis server 114 using the communication unit 23. The user management information has each item shown in FIG. 4.

Next, in step S21, the social participation information identification unit 13 of the social participation status analysis server 114 performs user registration in response to the registration application. In other words, the social participation information identification unit 13 registers the user management information included in the notified registration application in the memory unit 22.

Then, in step S22, the social participation information identification unit 13 uses the communication unit 11 to notify the user terminal 101 that the registration in step S21 has been completed. These steps S11 to S22 are preliminary steps in the social participation status analysis, and may be executed using the operation management terminal 10. It is also desirable that the user terminal 101 be configured to start the behavior information collection unit 26 in response to the registration management notification in step S22. In other words, a start-up is performed to start the processing from step S12 onwards.

Next, the behavioral information collection unit 26 collects the behavioral information detected by the behavioral information detection unit 25. As described above, in this embodiment, location information is collected as behavioral information. However, hereinafter, location information will be referred to as behavioral information. In addition, the behavioral information detection unit 25, which is realized by a GPS sensor or an acceleration sensor, acquires the location of the user terminal 101, i.e., the location of the participant, according to predetermined conditions. Here, the acquired behavioral information includes timestamp information, and the location and time are associated.

The predetermined conditions also include periodic acquisition, acquisition when movement of the user terminal 101 is detected, and the like. More preferably, the behavioral information detection unit 25 is activated when movement of the user terminal 101 is detected, and thereafter acquires behavioral information periodically. Then, if there is no movement for a certain period of time, the behavioral information detection unit 25 suspends position detection in a sleep mode or the like. Then, the behavioral information collection unit 26 stores the collected behavioral information in the memory unit 28 as collected information 112.

In addition, in step S13, the communication unit 23 notifies the social participation status analysis server 114 of the behavioral information and user ID contained in the collected information 112. This notification is performed periodically or in accordance with a predetermined condition. When performed periodically, the unit of time can be any number of days, minutes, or the like. The notification may also be performed in conjunction with the movement of the user terminal 101. In other words, this notification may be performed when any distance has been moved per unit time.

Next, in step S22, the social participation status analysis server 114 executes an analysis process for the social participation information identified based on the notified behavioral information. Details of this step are explained below with reference to FIG. 11. FIG. 11 is a flowchart showing the analysis process for social participation information in the embodiment.

First, as a prerequisite process for the analysis process (step S22), in step S13, the communication unit 23 of the user terminal 101 notifies the social participation status analysis server 114 of the user ID and behavioral information. Then, in step S22-1, the communication unit 11 of the social participation status analysis server 114 outputs the behavioral information and user ID received to the social participation information identification unit 13.

In addition, in step S22-2, the social participation information identification unit 13 identifies social participation information from the behavioral information and the user ID. Details of this social participation information identification process will be explained using FIG. 12. FIG. 12 is a flowchart showing the social participation information identification process in the embodiment. First, in step S22-21, the social participation information identification unit 13 accepts the behavioral information output in step S22-1.

Next, in step S22-22, the social participation information identification unit 13 uses the received behavioral information to determine the stay of the participant. This stay determination means dividing the behavioral information into predetermined units. For example, the social participation information identification unit 13 applies a method such as clustering to the behavioral information based on the timestamp information to divide it into stay information for each stay, which is one of the predetermined units. For this reason, the social participation information identification unit 13 identifies information on the center of gravity of the stay and the time period of the stay as each piece of stay information.

Next, in step S22-23, the social participation information identification unit 13 estimates the stay location corresponding to the center of gravity of the stay identified in step S22-22 from the stay location master information 134. In other words, the stay locations of the participants are estimated. For this purpose, it is desirable for the social participation information identification unit 13 to identify the stay location center of gravity coordinates 1002 that are closest to the identified center of gravity of the stay, and estimate the stay of the corresponding stay location ID 905.

Next, in step S22-24, the social participation information identification unit 13 estimates the activity content of the participant based on the stay location estimated in step S22-23. To this end, the social participation information identification unit 13 identifies the activity content 1104 corresponding to the stay location ID 905 of the estimated stay location from the stay purpose master information 135. Here, as shown in FIG. 8 (second record and third record), there are cases where the activity content differs even for the same stay location. Therefore, in addition to identifying the activity content 1104 corresponding to the stay location ID 905 of the estimated stay location as described above, the activity content may be estimated as follows.

(1) The social participation information identification unit 13 identifies the activity content 1104 corresponding to the stay location ID 905 of the estimated stay location from the stay purpose master information 135. In other words, the social participation information identification unit 13 searches for the activity content 1104 in the stay purpose master information 135 using the stay location ID 905 of the estimated stay location as a key.

(2) The social participation information identification unit 13 identifies the user ID list 1105 that corresponds to the notified user ID. In other words, the social participation information identification unit 13 searches the user ID list 1105 of the stay purpose master information 135 using the user ID as a key.

(3) If at least (1) is found, the social participation information identification unit 13 determines the activity content 1104 found in (1) as the activity content. Note that if only (1) is found, there is a tendency for multiple estimated activity contents to be found.

(4) If neither (1) nor (2) is found, it is desirable to transition to step S22-12 and collect additional information. Note that the order of (1) and (2) can vary, and parallel processing is also possible, but in consideration of processing efficiency, it is desirable to perform (1) first and then execute (2) on the results of (1).

Next, in step S22-25, the social participation information identification unit 13 merges the results of steps S22-22 to S22-24 to create social participation information. In other words, the social participation information identification unit 13 identifies the social participation information by merging the following items.
The center of stay and the time period of stay of the stay information in step S22-22 become the center of stay coordinates 902, the start of stay 903, and the end of stay 904.
The stay location ID 905 estimated in step S22-23 becomes the stay location ID 905 as it is.
The activity details estimated in step S22-24 become the activity details 906.
Then, the accepted user ID is used as the user ID 701 to create a social participation information ID 901 that identifies the social participation information.

This concludes the explanation of FIG. 12, and we will return to FIG. 11 to continue the explanation of the analysis process in this embodiment. In step S22-3, the social participation information identification unit 13 outputs the identified social participation information to the social participation information verification unit 14. Then, in steps S22-4 onwards, the social participation information verification unit 14 verifies the social participation information.

First, in step S22-4, the social participation information verification unit 14 outputs a request to calculate the reliability of the relevant social participation information to the reliability calculation unit 15. Then, in step S22-5, the reliability calculation unit 15 calculates the reliability of the accepted social participation information. Here, the details of the reliability calculation process in this step will be explained using FIG. 13. FIG. 13 is a flowchart showing the reliability calculation process in this embodiment.

First, in step S22-51, the reliability calculation unit 15 receives a reliability calculation request. Then, the reliability calculation unit 15 calculates the reliability from multiple perspectives in each of steps S22-52 to S22-55.

In step S22-52, the reliability calculation unit 15 calculates a terminal-dependent reliability indicating the reliability according to the user terminal 101. To this end, the reliability calculation unit 15 calculates the reliability based on the user terminal 101 in question and the OS installed therein. In addition, in step S22-53, the reliability calculation unit 15 calculates a stay location estimation reliability indicating the reliability according to the location requirements of the stay location where the participant stayed. In addition, in step S22-54, the reliability calculation unit 15 calculates a user-specific reliability indicating the reliability according to the participant. Furthermore, in step S22-55, the reliability calculation unit 15 calculates a stay purpose reliability indicating the reliability according to the stay purpose of the stay location where the participant stayed.

Note that the details of the calculation of each of these reliability levels are as described above in the explanation of the social participation information verification information 136 in Figure 9.

Next, in step S22-56, the reliability calculation unit 15 performs an integration process for each reliability calculated in each of steps S22-52 to S22-55, and calculates a reliability obtained by integrating each reliability. This integration process includes calculating representative values such as the average (arithmetic mean, geometric mean, median, etc.), median, sum, and mode of each reliability, and extracting maximum and minimum values. Furthermore, if one of steps S22-52 to S22-55 does not satisfy the specified reliability because it is below a threshold, the calculations in the other steps may be omitted.

Furthermore, at least one of steps S22-52 to S22-55 may be executed. This includes using stay characteristic reliability related to stay location estimation reliability and stay purpose reliability. This stay characteristic reliability corresponds to the characteristics of the stay contained in the behavior information, and is particularly a reliability based on the accuracy of the behavior information (e.g., location information) during the stay. Therefore, at least one of the stay location estimation reliability and the stay purpose reliability can be used as the stay characteristic reliability. Furthermore, the order of processing these is not important, and processing may be performed in parallel. Note that the reliability calculation unit 15 records each reliability calculated in steps S22-52 to S22-56 in the corresponding item of the social participation information verification information.

This concludes the explanation of Figure 13, and we will return to Figure 11 to continue the explanation of the analysis process in this embodiment. In step S22-6, the reliability calculation unit 15 outputs the reliability calculated in step S22-56 to the social participation information verification unit 14.

In addition, in step S22-7, the social participation information verification unit 14 outputs a request to calculate the risk impact level for the social participation information output in step S22-3 to the risk impact level calculation unit 16. Then, in step S22-8, the risk impact level of the output social participation information is calculated in response to the calculation request. Here, the details of the risk impact level calculation process in this step will be explained using FIG. 14. FIG. 14 is a flowchart showing the risk impact level calculation process in this embodiment.

First, in step S22-81, the risk influence degree calculation unit 16 reads the risk prediction model 137. A statistical model and a machine learning model can be used as the risk prediction model 137. Here, the statistical model and the machine learning model include linear regression, logistic regression, proportional hazard model, generalized linear model, SVM (Support-Vector Machine), random forest, gradient decision tree, deep learning, and the like. In addition to the risk prediction model 137, a model for calculating the contribution degree using more explanatory variables may be additionally prepared. Furthermore, social participation information is used as an explanatory variable in these risk prediction models 137. For example, when the risk prediction model 137 is linear, it can be expressed as follows.
Y=a1*Social Participation A1 + a2*Social Participation A2 + a3*Social Participation A3 + …+ b1*Basic Information B1 + b2*Basic Information B2 + b3*Basic Information B3 + ….

Next, in step S22-82, the risk impact degree calculation section 16 calculates the risk impact degree using the risk prediction model 137. Two calculation examples will be described below.
Example 1: The coefficient (weight) corresponding to each explanatory variable is used as the influence of each piece of social participation information. Example 2: Using so-called xAI technology such as SHAP or LIME, the influence on each piece of social participation information in the nursing care risk prediction analysis results for each participant is calculated and used as the risk influence. Note that the calculation of the risk influence is not limited to this. In addition, the risk influence calculation unit 16 records the calculated risk influence in the corresponding item of the social participation information verification information 136. This concludes the explanation of Figure 14, and we will return to Figure 11 to continue the explanation of the analysis process in this embodiment.

Next, in step S22-9, the risk impact calculation unit 16 outputs the calculated risk impact to the social participation information verification unit 14. Then, in step S22-10, the social participation information verification unit 14 verifies the social participation information. To this end, the risk impact calculation unit 16 uses at least one of the reliability calculated in step S22-56 and the risk impact calculated in step S22-8. For example, the social participation information verification unit 14 applies a predetermined calculation formula to the reliability and risk impact to calculate a verification score. Then, as the verification score, a representative value of the reliability and risk impact may be used, or one of the values may be used. The social participation information verification unit 14 records the calculated verification score in the corresponding item of the social participation information verification information 136.

Next, in step S22-11, the social participation information verification unit 14 outputs an information collection plan formulation request including the verification result for the social participation information and the social participation information ID. This information collection plan formulation request may be a formulation request for multiple pieces of social participation information. Then, in step S22-12, the information collection plan formulation unit 17 formulates an information collection plan for collecting additional information to improve reliability. To this end, the information collection plan formulation unit 17 formulates a plan based on the verification score of each piece of social participation information in the information collection plan formulation request. In other words, the lower the reliability or the higher the risk, the higher the priority of the collection of additional information is given to the plan formulated. Here, priority includes being notified of the request to collect additional information earlier. Furthermore, if the reliability or risk is higher than a threshold in the verification score, the processing may end at this step.

Furthermore, the information collection plan formulation unit 17 may skip formulation of the information collection plan and execute step S22-13 each time the verification score 1207 satisfies a predetermined condition. The information collection plan formulation request in step S22-11 is a type of request for update-related processing. Therefore, the information collection plan formulation in step S22-12 is also a type of update-related processing. Therefore, an information update request may be executed in step S22-11, and information update may be executed in step S22-12 if a predetermined condition is satisfied. In this way, when information update is executed, "additional information collection required" is recorded in the verification result 1208 of the social participation information verification information 136. The predetermined condition includes whether the reliability is lower or the risk is higher than a threshold in the verification score 1207. Furthermore, the social participation information verification unit 14 may determine whether such a predetermined condition is satisfied, and if not, a request for update-related processing may be notified.
If the reliability is used in step S22-10, step S22-7 may be skipped and the process may proceed to step S22-10. Then, the social participation information verification unit 14 calculates the reliability as a verification score. As a result, if the verification score or the reliability satisfies a predetermined condition, the social participation information verification unit 14 may execute step S22-11. For example, if the verification score or the reliability is less than a predetermined threshold, that is, if there is a high possibility that the social participation information is not true information, step S22-11 is executed. This makes it possible to bring the social participation information closer to the true value.

Next, in step S22-13, the information collection plan formulation unit 17 outputs an information collection request to the communication unit 11 to collect additional information. Then, in step S23, the communication unit 11 notifies the communication unit 23 of the user terminal 101 of the information collection request. Various aspects are possible for the timing of step S23. For example, it may be executed each time a plan is formulated in step S22-12, or it may be batch processed for each unit period. Furthermore, when a predetermined number of request units are reached, the information may be notified collectively.
This completes the explanation of FIG. 11. Returning to FIG. 10, the overall processing in this embodiment will now be explained.

After step S23 described above, step S13 is executed. In step S13, the social participation information collection unit 27 of the user terminal 101 collects additional information. To this end, the social participation information collection unit 27 outputs the various screens of Figs. 15 to 16 to the input/output unit 24. The social participation information collection unit 27 first outputs a social participation information collection notification screen 1401. Fig. 15 is a diagram showing the social participation information collection notification screen 1401 in this embodiment. This social participation information collection notification screen 1401 is a screen for inquiring whether collection is possible, and contains text requesting the input of additional information.

The example in FIG. 15 describes an example of providing new functions. However, specific explanations regarding enhancements to functions already provided may also be given. For example, these include an expansion of prediction target items, higher accuracy, and an expansion of advice items. Furthermore, the social participation information collection notification screen 1401 includes a button 1402 for allowing the input of additional information and a button 1403 for not allowing it. Of these, when button 1402 is selected by a participant, the screen transitions to a screen for collecting additional information. Furthermore, when button 1403 is selected, the processing in FIG. 10 ends. In this case, it is desirable for the communication unit 23 to notify the social participation status analysis server 114 that it is not possible to collect additional information.

Here, we will explain the screen to which the screen transitions when button 1402 is selected. FIG. 16 is a diagram showing a social participation information collection screen 1501 in this embodiment. The social participation information collection screen 1501 has a social participation status area 1502, each piece of behavioral information, i.e., verification score areas 1503 to 1505 for each place of stay, a selected place of stay information area 1506, and a correction area 1507. A social participation status that summarizes the social participation information is output in the social participation status area 1502. Note that the social participation status is not limited to information that summarizes the social participation information.

In addition, in the verification score areas 1503 to 1505, the verification score for each piece of social participation information is output in association with the place of stay. Of these, the verification score area 1503 is in an active state, and additional information can be input, that is, corrections can be made. Information on the place of stay related to the verification score area 1503 that is in an active state is output in the place of stay information area 1506. In the example of Figure 16, a map of stay 1 is output, but the name of the place of stay may be clearly indicated.

Furthermore, in the correction area 1507, information corresponding to the corresponding social participation information item is output, and a correction button is output for each of them. Here, the stay date and time corresponds to the stay start 903 and stay end 904 of the social participation information. Furthermore, the stay location corresponds to the stay location name 1001 corresponding to the stay location ID 904. Furthermore, the purpose of the stay corresponds to the activity content 906. Here, if there are multiple activity contents 906, a correction button is output for each. Then, when the correction button is selected by the participant, corrections can be made to each item. As a result, the social participation information collection unit 27 identifies the corrected social participation information as additional information.

Next, in step S14, the communication unit 23 notifies the social participation status analysis server 114 of the additional information collected in step S13. The communication unit 11 of the social participation status analysis server 114 then accepts this.

As described above, the information collection plan formulation unit 17 of the social participation status analysis server 114 uses the communication unit 11 to notify an information collection request to collect additional information for social participation information that meets a specified condition, such as a reliability level that is less than a predetermined threshold. The information collection plan formulation unit 17 then collects the additional information from the user terminal 101 in response to this.

Next, in step S24, the information update unit 20 updates the social participation information identified in step S22 using the additional information. In this embodiment, the social participation information identified in step S22 is replaced with the additional information. Here, the replaced additional information, that is, additional social participation information 133', is shown in FIG. 17. The additional social participation information 133' is the social participation information 133
It has the same items as those in the above. However, a branch number (-01) indicating that it has been updated is added to the social participation information ID 901. This update may involve replacement (overwriting) or the addition of additional social participation information 133'. In this case, it is desirable to record that the social participation information 133 before the update is invalid.

Furthermore, in step S24, the information update unit 20 may update the stay location master information 134 and the stay purpose master information 135 based on the additional information. For example, the stay location name 1001, the activity day 1102, the activity time 1103, and the activity content 1104 can be updated.

Next, in step S25, the social participation status evaluation unit 21 identifies the social participation status of the participant based on the social participation information, and evaluates this social participation status. Here, the social participation status includes the results of collating the social participation information for a specified period of time and the social participation information itself. Furthermore, the evaluation of the social participation status includes identifying the participant's care risks and advice on those risks. Note that the evaluation is one type of analysis in this embodiment, and other analyses may also be performed.

The social participation status assessment unit 21 can use AI technology or big data analysis technology to identify, analyze or evaluate the social participation status. These can be realized using publicly known technologies, so a detailed description of the details will be omitted. Next, in step S26, the communication unit 11 notifies the user terminal 101 of the identified social participation status and the social participation status assessment result including the assessment result. The social participation status assessment result may include at least one of the social participation status and the social participation status assessment result including the assessment result.

Then, in step S15, the social participation information collection unit 27 of the user terminal 101 outputs the social participation status evaluation result notified to the input/output unit 24. The social participation status evaluation screen 1601 output in step S15 is shown in FIG. 18. In FIG. 18, the social participation status evaluation screen 1601 has a summary result area 1602, a risk area 1603, and an advice area 1604. The contents output in each of these areas are the results of the evaluation in step S25.

The aggregation result area 1602 is an area showing the results of aggregating the social participation information of the relevant participant. In addition, the risk area 1603 outputs the risk calculated based on the social participation information of the relevant participant. In FIG. 18, nursing care risk is used as the risk. In addition, the advice area 1604 outputs advice for reducing the risk based on the social participation information.

This concludes the explanation of this embodiment. The present invention is not limited to this embodiment, but includes various applications and modifications. The present invention also includes information processing for various services by business systems 30 to 60 based on the analysis results of social participation status and social participation information.

10...operation management terminal, 11...communication unit, 12...input/output unit, 13...social participation information identification unit, 14...social participation information verification unit, 15...reliability calculation unit, 16...risk impact calculation unit, 17...information collection plan formulation unit, 18...risk prediction model learning unit, 19...risk prediction unit, 20...information update unit, 21...social participation status evaluation unit, 22...storage unit, 23...communication unit, 24...input/output unit, 25...behavioral information detection unit, 26...behavioral information collection unit, 27...social participation information collection unit, 28...storage unit, 30-60...business system, 101...user terminal, 102...input/output device, 103...computing device, 104...behavioral information sensor, 105...communication path, 106...communication I/F, 107...main storage unit, 108...behavioral information collection program, 109...social participation information collection program, 110...auxiliary storage unit, 111...terminal information, 11 2...Collected information, 113...Network, 114...Social participation status analysis server, 115...Communication I/F, 116...Input device, 117...Output device, 118...Calculation device, 119...Main storage device, 121...Social participation information identification program, 122...Social participation information verification program, 123...Reliability calculation module, 124...Risk impact calculation module, 125...Information collection plan formulation program, 126...Risk prediction model learning program, 127...Risk prediction program, 128...Information update program, 129...Social participation status evaluation program, 130...Auxiliary storage device, 131...User management information, 132...Terminal management information, 133...Social participation information, 134...Stay location master information, 135...Stay purpose master information, 136...Social participation information verification information, 137...Risk prediction model

Claims (11)

In a social participation status analysis device that analyzes the social participation status of participants,
A communication unit that receives behavior information indicating a behavior history in which a position and a time of each of the plurality of participants are associated with each other;
a social participation information identification unit that identifies social participation information including the activity details of the participant by dividing the behavioral information into predetermined units, identifying a center of gravity of the participant's stay and a time period of stay, estimating a stay location corresponding to the center of gravity of the stay using stay location master information having a stay location ID, stay location name, and stay location center coordinate for each stay location where the participant can stay, and estimating activity details of the estimated stay location using stay purpose master information indicating activity details that are the stay purpose for each stay location;
a reliability calculation unit that calculates reliability of each of a plurality of viewpoints indicating the accuracy of the social participation information , integrates the calculated reliability, and calculates an integrated reliability ;
a social participation information verification unit that outputs an information collection plan formulation request when the integration reliability is less than a predetermined threshold;
an information collection plan formulation unit that outputs an information collection request for collecting additional information to the communication unit in response to the information collection plan formulation request;
an information updating unit that updates the social participation information by using additional information collected in response to the information collection request;
A social participation status analysis device comprising a social participation status evaluation unit that analyzes the social participation status of the participant based on the updated social participation information. 2. The social participation status analysis device according to claim 1,
The social participation status analysis device further comprises a risk influence calculation unit that calculates a risk influence level indicating the degree of influence on the health risk of the participant based on the social participation information. 3. The social participation status analysis device according to claim 1 ,
The reliability calculation unit calculates, as the reliability, a stay characteristic reliability according to a characteristic of a stay included in the behavioral information. 4. The social participation status analysis device according to claim 3 ,
The reliability calculation unit calculates, as the stay characteristic reliability, at least one of a stay location estimation reliability according to the locational requirements of the participant's stay locations and a stay purpose reliability according to the stay purpose of the stay locations. 5. The social participation status analysis device according to claim 4 ,
The reliability calculation unit further calculates, as the reliability, at least one of a terminal-dependent reliability corresponding to the user terminal that detects the behavioral information and a participant-specific reliability corresponding to the participant. The user terminal is connected to a social participation status analysis device that analyzes the social participation status of participants,
a behavior information collection unit that collects behavior information indicating a behavior history in which a location and a time of the participant are associated with each other;
notifying the social participation status analysis device of the collected behavioral information;
a communication unit that receives an information collection request for collecting additional information from the social participation status analysis device when an integrated reliability obtained by integrating reliability of multiple perspectives indicating accuracy of social participation information including the activity content of the participant, the integrated reliability being less than a predetermined threshold value, the communication unit that divides the behavioral information into predetermined units, identifies a center of gravity and a time period of stay of the participant, estimates a stay location corresponding to the center of gravity of the stay using stay location master information having a stay location ID, a stay location name, and a stay location center coordinate for each stay location where the participant can stay, and estimates the activity content of the estimated stay location using stay purpose master information indicating the activity content that is the purpose of stay for each stay location;
a social participation information collection unit that collects the social participation information, which is the additional information, from the participants;
A program for analyzing the social participation status of the participants based on the collected social participation information by the social participation status analysis device. The program according to claim 6 ,
moreover,
A program that causes the user terminal to function as a behavior information detection unit that detects location information of the participants as the behavior information. The program according to claim 6 ,
A program in which the social participation status analysis device calculates a risk impact level indicating the degree of impact on the participant's health risk based on the collected social participation information. The program according to any one of claims 6 to 8 ,
A program in which the social participation status analysis device calculates, as the reliability, a stay characteristic reliability according to the characteristics of the stay included in the behavioral information. The program according to claim 9 ,
A program in which the social participation status analysis device calculates, as the stay characteristic reliability, at least one of a stay location estimation reliability according to the locational requirements of the participant's stay locations and a stay purpose reliability according to the stay purpose of the stay locations. The program according to claim 10 ,
A program for causing the social participation status analysis device to further calculate, as the trustworthiness, at least one of a terminal-dependent trustworthiness corresponding to the user terminal and a participant-specific trustworthiness corresponding to the participant.

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