JP2023104132A - Social participation status analyzer and program - Google Patents

Abstract

To realize social participation status analysis while keeping accuracy, with a simpler configuration.SOLUTION: A social participation status analysis server 114 which analyzes social participation status of a participant comprises: a communication unit 11 which receives behavior information indicating an action history in each of the plurality of participants; a social participation information identification unit 13 which identifies social participation information of the participant, on the basis of the behavior information; a reliability degree calculation unit 15 which calculates a reliability degree of the social participation information; an information collection planning unit 17 which performs additional information collection being update related processing for the social participation information, depending on the reliability degree; and a social participation status evaluation unit 21 which analyzes the social participation status of the participant, based on the social participation information updated on the basis of the additional information.SELECTED DRAWING: Figure 2

Description

The present invention relates to techniques for analyzing situations based on participant behavior. In particular, it relates to a technique for analyzing the state of social participation of participants based on their social participation behavior. Note that the participant includes various concepts related to people such as residents, customers, users, stakeholders, subjects, and subjects.

Currently, data analysis is performed in various fields. Among these, the analysis of behavior related to the movement of people for purchase trends, crime prevention, and logistics efficiency is attracting attention. In addition, as we enter an aging society, health problems of the elderly such as dementia and nursing care problems are becoming apparent. Here, it is becoming clear that it is possible to suppress the onset of dementia in the elderly and the transition to need of long-term care by activating the social participation behavior (including social participation activities) of the elderly. In other words, as a health index, it is important to visualize social participation behavior and social participation status based on this, in addition to conventional diet and exercise.

For example, Patent Literature 1 discloses a technology for preventive care. More specifically, it states that "acquisition of physical strength measurement and cognitive function measurement results, life information and social participation scores by an acquisition unit" (summary). It also discloses that the user's location information is used to calculate the social participation score (claim 2, etc.).

WO2018/100797

Here, in Patent Literature 1, the user's future physical strength value is predicted based on physical strength measurement and cognitive function measurement results. Thus, in Patent Document 1, it is necessary to prepare various data. Also, in physical fitness measurement, etc., it is necessary to prepare a place for the measurement and perform the measurement work. As described above, Patent Document 1 has a problem that it takes time and effort to calculate the social participation score.

Also, in order to reduce this trouble, it is conceivable to reduce the data for calculating the social participation score. However, reducing the data may reduce the reliability of social participation scores. As a result, there is a risk that the accuracy of the analysis of social participation will be reduced.

Accordingly, an object of the present invention is to realize an analysis of the state of social participation that maintains accuracy with a simpler configuration.

In order to solve the above problems, the present invention executes update-related processing according to the reliability of various types of information such as social participation information specified based on location information. Note that this update-related processing includes updating of information, collection of additional information for updating, and inquiry to participants for collection. The information includes social participation information and various master information.

A more specific configuration of the present invention is a social participation situation analysis device for analyzing social participation situations of participants. a social participation information identification unit for identifying social participation information of said participant; a reliability calculation unit for calculating reliability of said social participation information; and processing related to update of said social participation information according to said reliability. and a social participation situation evaluation unit that analyzes the social participation situation of the participant based on the social participation information on which the update-related process has been executed. 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.

Furthermore, the present invention includes a user terminal that is connected to a social participation status analysis device and collects behavior information and social participation information (additional information), a method using this, and a program for operating the user terminal. be The present invention also includes a social participation analysis system including a social participation analysis device and a user terminal.

ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to analyze a social participation state precisely.

The figure which shows the concept of one Example of this invention. 1 is a system configuration diagram of a social participation situation analysis system according to an embodiment of the present invention; FIG. 1 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; It is a figure which shows the terminal management information used by one Example of this invention. It is a figure which shows the social participation information used by one Example of this invention. FIG. 4 is a diagram showing stay location master information used in one embodiment of the present invention; It is a figure which shows the stay purpose master information used by one Example of this invention. It is a figure which shows social participation information verification information used by one Example of this invention. FIG. 4 is an overall processing sequence diagram showing overall processing in one embodiment of the present invention; 4 is a flow chart showing analysis processing of social participation information in one embodiment of the present invention. 4 is a flow chart showing processing for specifying social participation information in one embodiment of the present invention. 4 is a flow chart showing reliability calculation processing in one embodiment of the present invention. It is a flowchart which shows the calculation process of the risk influence degree in one Example of this invention. FIG. 10 is a diagram showing a social participation information collection notification screen in one embodiment of the present invention; FIG. 10 is a diagram showing a social participation information collection screen in one embodiment of the present invention; FIG. 4 is a diagram showing additional social participation information used in one embodiment of the present invention; FIG. 10 is a diagram showing a social participation status evaluation screen in one embodiment of the present invention;

An embodiment of the present invention will be described below in the order of <concept>, <configuration/information>, and <processing flow> with reference to the drawings.

<Thinking>
First, the concept of this embodiment will be described with reference to FIG. In regions A and B, participants (users) such as residents carry user terminals 101-1, 101-2, and 101-3, which are types of user terminals, and carry out social participation actions. there is For this reason, each of the user terminals 101-1, 101-2, and 101-3 uses the GPS function, etc., to acquire the position information associated with the social participation behavior of the participants (behavior information collection unit described later). 26). A region is a concept that includes a so-called district, and the unit can be arbitrarily set, such as a prefecture. A region is an example of a unit society in this embodiment. The unit society includes organizations such as companies and health insurance associations, and local communities.

Here, this social participation behavior includes movement to various facilities such as home, factory (place of work), store, fitness club (gymnasium), office (place of work), and restaurant, and activities at the facility. In addition, participants are not limited to actions within the region, but are assumed to be taking actions across regions.

Then, the social participation status analysis server 114 installed in the data center collects behavior information from each of the user terminals 101-1, 101-2, and 101-3 (hereinafter referred to as user terminals 101), Identify participation information. The action information indicates the action history of the participant, and position information can be used. Then, the social participation status analysis server 114 analyzes the social participation status of the participant based on the social participation information. This analysis also includes assessing social participation. Also, the social participation status analysis server 114 can present such analysis results to various business systems. As a result, business systems are expected to be systems used by administrative agencies, insurance companies, nursing care facilities, fitness clubs and other facility management companies, and point management companies in regions A and B. Furthermore, the analysis results include environmental indicators that indicate the ease of participation for each unit society such as region, various aggregate information, policy plans using these, and information to support them. The analysis result may also be notified to the user terminal 101 . The social participation analysis server 114 is a kind of social participation analysis device.

Furthermore, the social participation status analysis server 114 notifies the user terminal 101 of an information collection request, which is a kind of update-related processing, according to the reliability of the specified social participation information. In response, the user terminal 101 notifies the social participation status analysis server 114 of the additional information. 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 social participation status analysis based on the social participation information. 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 indicating the participant's relationship with society based on this.

<Configuration/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 the social participation situation 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. connected. In FIG. 2, fitness clubs, insurance companies, nursing care facility operating companies, and point operating companies are exemplified as operators of the business systems 30-60. These operators can be realized by a computer system composed of servers and PCs.

Here, each of the business systems 30-60 can use the analysis results of the social participation status analysis server 114. FIG. For example, in the business system 30 of a fitness club, it is possible to formulate a menu for participants according to the analysis results. Further, in the business system 40 of the insurance company, it becomes possible to develop insurance products and calculate insurance premium rates for participants according to the analysis results. In addition, in the business system 50 of the nursing care facility management company, it is possible to develop nursing care menus, establish new facilities, and formulate plans for refurbishment according to the analysis results. Furthermore, in the business system 60 of the point management company, points may be given to the participants according to the analysis results. Incidentally, each of these business systems 30 to 60 may use behavior information or social participation information itself as an analysis result.

Each device constituting the social participation situation analysis system will be described below. The social participation status analysis server 114 is realized by a computer device provided in the data center. The social participation status analysis server 114 includes the communication unit 11, the input/output unit 12, the social participation information identification unit 13, the social participation information verification unit 14, the reliability calculation unit 15, the risk impact calculation unit 16, and the information collection plan formulation. It has a section 17 , a risk prediction model learning section 18 , a risk prediction section 19 , an information update section 20 , a social participation status evaluation section 21 and a storage section 22 . These configurations will be described below, and the details of the processing will be described later with reference to flowcharts.

The communication unit 11 has an interface function for connecting the network 113 . The input/output unit 12 has an interface function for connecting with the operation management terminals 10-1 and 10-2. Therefore, the communication unit 11 and the input/output unit 12 may be integrated.

The social participation information specifying unit 13 specifies social participation information from the action information notified from the user terminal 101 . This behavior information includes the location information of the corresponding user terminal 101, that is, the location information of the participants. Also, the social participation information includes details of activities of the participants. 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 reliability-based verification and risk-impact-based verification. For this reason, the social participation information verification unit 14 preferably 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 that indicates the deviation or closeness between the social participation information and the true information, and it is also possible to use accuracy and precision. In addition, the risk impact calculation unit 16 calculates a risk impact indicating the degree of impact on health risks predicted for the participant in the social participation information. This risk includes the risk of requiring nursing care in the future, the risk of being bedridden, and the like.

The information collection plan formulating unit 17 formulates a plan for notification of an information collection request, which is a kind of update-related processing, and notifies the information collection request accordingly. For example, the information collection plan formulating unit 17 formulates a plan for notifying the information collection request in a period of time when the traffic on the network 113 is low or when the behavior of the participants has settled down. In addition, it is desirable that the information collection plan formulation unit 17 output an information collection request. For this reason, the information collection plan formulating unit 17 of this embodiment does not formulate future plans or schedules, and requests information collection on a case-by-case basis.

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 health risks described above. This model is used by the risk prediction unit 19 . That is, the risk prediction unit 19 uses the risk prediction model to predict the above-described risks. Note that the risk prediction model learning unit 18 can be omitted.

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

Further, the information updating section 20 may be divided into a social participation information updating section for updating social participation information and a master information updating section for updating the place of stay master information 134 and the purpose of stay master information 135 . Furthermore, at least one of the social participation information updating unit and the master information updating unit may be provided. Based on the updated social participation information, the social participation status evaluation section 21 analyzes the participant's social participation status evaluation section and the like. The storage unit 22 stores various types of information used for processing by the social participation status analysis server 114 and information as processing results.

Next, operation management terminals 10-1 and 10-2 (hereinafter simply operation management terminal 10) will be described. The operation management terminal 10 can be realized by a computer and is used by the data center operator. 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 carried by the participant, collects behavior information, and notifies the social participation status analysis server 114 of the behavior information. Here, in this embodiment, position information of the user terminal 101, that is, position information of the participants is collected as behavior information. For this reason, the user terminal 101 can be realized by a portable information processing device such as a smart phone, a mobile phone, a tablet, or a portable GPS (Global Positioning System) transmitter. The user terminal 101 of this embodiment also has a communication unit 23 , an input/output unit 24 , an action information detection unit 25 , an action information collection unit 26 , a social participation information collection unit 27 and a storage unit 28 .

The communication unit 23 has an interface function for connecting the network 113 . The input/output unit 24 receives inputs from participants using the user terminals 101 and outputs processing results. Note that the input/output unit 24 may be configured by being divided into an input unit and an output unit.

The behavior information detection unit 25 has a function of detecting behavior information of participants. In this embodiment, since position information is used as action information, the position information is detected by the GPS function. The behavior information collection unit 26 collects behavior information detected by the behavior information detection unit 25 . Then, the social participation status analysis server 114 is notified of the collected behavior information 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 . Collecting the additional information includes receiving additional information input from the participant via the input/output unit 24, collecting behavior information from the behavior information detection unit 25, and the like. The storage unit 28 contains information used for processing in the user terminal 101 and information indicating processing results.

Various processes of the user terminal 101 and social participation status analysis server 114 can be realized by a computer program (software), dedicated hardware, or FPGA (Field-Programmable Gate Array). An example of this implementation will be described later.

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

Although the description of FIG. 2 ends above, the number of each device is only an example, and is not limited to these. Also, the operators of the business systems 30 to 60 are not limited to the illustrated examples.

Next, an implementation example 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. As shown in FIG. In this embodiment, the user terminal 101 is realized by a portable information processing device such as a program (application) smartphone. The social participation status analysis server 114 is also realized by a server, which is a type of computer that executes processing according to a program. Each configuration will be described below.

First, the user terminal 101 has an input/output device 102, an arithmetic device 103, a behavior information sensor 104, a communication I/F 106, a main storage device 107 and an auxiliary storage device 110. These have a communication channel 105 such as a bus. connected to each other through

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

The main storage device 107 can be realized by a memory, and programs and information used by the arithmetic device 103 are expanded. Programs developed in the main storage device 107 include a behavior information collection program 108 and a social participation information collection program 109 . Functions of the behavior information collection program 108 correspond to functions of the behavior information collection unit 26 . Also, functions of the social participation information collection program 109 correspond to functions of the social participation information collection unit 27 . These behavior information collection program 108 and social participation information collection program 109 may be realized by one program.

The auxiliary storage device 110 stores terminal information 111 and collected information 112 . Here, the terminal information 111 is information relating to the user terminal 101, and includes identification information thereof, user IDs of participants, and the like. Collected information 112 includes collected behavior information and social participation information. Note that 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), SSD (Solid State Drive). Further, auxiliary storage device 110 desirably stores the aforementioned program. Furthermore, it is desirable that these programs be distributed via network 113 or stored in a storage medium. Although not shown in FIG. 3, the user terminal 101 stores an OS (Operating System) that implements basic functions.

Communication I/F 106 corresponds to communication unit 23 and communicates with social participation status analysis server 114 via network 113 . Moreover, although it is desirable that the communication I/F 106 performs wireless communication, wired communication may 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, an arithmetic device 118, a main memory device 119 and an auxiliary memory device 130, which are connected via a communication path 138 such as a bus. connected to each other. The input device 116 and the output device 117 correspond to the input/output unit 12 in FIG. 2 and have the function of connecting to the operation management terminals 10-1 and 10-2.

Like the arithmetic device 103, the arithmetic device 118 can be realized by a processor such as a CPU, and executes arithmetic operations according to various programs described later. Also, the main storage device 119 can be realized by a memory, and programs and information used by the arithmetic device 118 are expanded. The programs developed in the main memory 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 assessment program 129 is included.

Here, the function realized by the social participation information identification program 121 corresponds to the function of the social participation information identification unit 13 . The correspondence between other programs and the units shown in FIG. 2 will be described below.
Social participation information verification program 122: social participation information verification unit 14
Information collection plan formulation program 125: Information collection plan formulation unit 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 Evaluation Program 129: Social Participation Evaluation Department 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 modules correspond to the functions of the reliability calculation unit 15 and the risk impact calculation unit 16, respectively. do. Each of these modules may be implemented by an independent program. Furthermore, each program may be aggregated to form one or more programs.

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 . These pieces of information will now be described. First, FIG. 4 is a diagram showing the user management information 131 used in this embodiment. The user management information 131 is information about participants who are users. User management information 131 has items of user ID 701, name 702, date of birth 703, sex 704, address 705, contact information 706, and family contact information 707 for each participant. Here, the user ID 701 is identification information that identifies a participant. Name 702, date of birth 703, sex 704, address 705, contact information 706, and family contact information 707 indicate the names of participants, respectively. Note 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 about the user terminal 101 . The terminal management information 132 has items of a user ID 701 , a used model 801 , an OS 802 and an OS version 803 for each user terminal 101 . User ID 701 is the same as that in FIG. 4, but information for identifying user terminal 101 may be provided. The used model 801 indicates the model of the corresponding user terminal 101, that is, the model used by the participant. Also, the OS 802 and OS version 803 are information for identifying the OS and its version used in the corresponding user terminal 101 . In addition to or instead of the model 801 used, the OS 802, and the OS version 803, information regarding the functions of the user terminal 101 may be used.

Next, FIG. 6 is a diagram showing social participation information 133 used in this embodiment. The social participation information 133 is information indicating behavior of participants. The social participation information 133 has items of user ID 701, social participation information ID 901, stay centroid coordinates 902, stay start 903, stay end 904, place of stay ID 905, and activity content 906 for each action. User ID 701 is the same item as those in FIGS. The social participation information ID 901 is information for identifying each record of the social participation information as a management unit, that is, the social participation information 133 .

Also, the stay barycentric coordinates 902 indicate the barycentric position in the position information group under predetermined conditions such as a predetermined time and position. Stay start 903 and stay end 904 indicate the start time and end time when a predetermined condition is satisfied. The place of stay ID 905 is an item for identifying a place of stay indicated by action information represented by position information, and can identify a facility or the like. Note that the place of stay ID 905 is an item that is specified using, for example, the place of stay master information 134, which will be described later, according to the action information represented by the position information.

Further, the activity content 906 is an item specified according to the place of stay ID 905 using, for example, the purpose of stay master information 135 described later. In this embodiment, the activity content 906 is exemplified by athletic activities, cultural activities, and volunteer activities, but is not limited to these. Also, in this embodiment, the type of activity is used as the activity content 906, but a quantified amount of activity may be used. The items of stay barycentric coordinates 902, stay start 903, stay end 904, stay place ID 905, and activity content 906 are items indicating the content of actions. It should be noted that these items may be items that indicate the actions of the participants, and some of the items may be omitted. It is also possible to replace it with another item.

FIG. 7 is a diagram showing the stay location master information 134 used in this embodiment. The place-of-stay master information 134 is information about places of stay such as facilities where participants can stay. The place of stay master information 134 has items of a place of stay ID 905, a place of stay name 1001, and coordinates of the center of stay 1002 for each place of stay.

Here, the stay location ID 905 is identification information for identifying the corresponding intervening location. The place of stay name 1001 indicates the name of the place of stay, but this item can be omitted. Furthermore, the stay place barycentric coordinates 1002 is an item indicating the barycentric position at the stay place.

FIG. 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 indicating the purpose of stay, that is, the content of activities, for each place of stay. For this reason, the stay purpose master information 135 has items of a stay place ID 905, a stay purpose No. 1101, an activity day 1102, an activity time 1103, an activity content 1104, and a user ID list 1105 for each stay place.

The place of stay ID 905 is similar to that of FIG. The purpose of stay No. 1101 is an item for specifying the purpose of stay (contents of activities) of the corresponding place of stay, and a number is used in this embodiment. The activity days 1102 and activity hours 1103 indicate the days of the week and time periods during which activities are possible at the relevant place of stay. Note that these can be omitted. Also, instead of or in addition to the activity day 1102, month and day may be used. Further, the activity content 1104 indicates the activity content possible at the corresponding place of stay. The using user ID list 1105 records the using user ID which is the user ID of the participant who used the corresponding place of stay.

FIG. 9 is a diagram showing 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 . Therefore, the social participation information verification information 136 includes, for each social participation information, a user ID 701, a social participation information ID 901, a terminal-dependent reliability 1201, a place-of-stay estimation reliability 1202, a user-specific reliability 1203, a stay purpose reliability 1204, It has items of integrated reliability 1205 , risk impact 1206 , verification score 1207 and verification result 1208 .

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

The terminal dependent reliability 1201 indicates the reliability corresponding to the terminal 101 used by the user. For example, it is an item calculated based on the length of time until the restart or start of position information measurement after the user terminal 101 starts moving, the performance of the action 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 dependent on software such as an OS or hardware such as a sensor. Therefore, it can be said that the higher these performances are, the higher the reliability is.

The place-of-stay estimation reliability 1202 indicates the degree of reliability according to locational requirements of the place of stay where the participant stayed. For example, the distance between the center of the place of stay and the center of position information, the degree of dispersion of position information during the stay, the time out of GPS range during the stay, the number of location information measurement points during the stay, the activity level of the amount of activity during the stay, the place of stay area, the number of adjacent stays, etc. This is because when the place of stay is large or when other places of stay are not densely located in the neighborhood, the probability of the place of stay is high, so the reliability tends to be high.

The user-specific confidence level 1203 indicates the confidence level according to the participant. For example, it is calculated based on the history of behavior information of the participants. More specifically, there is a tendency that the more frequently a participant stays, the higher the reliability. Furthermore, the stay purpose reliability 1204 indicates the reliability according to the stay purpose of the place where the participant stayed. For example, the reliability tends to be low in the following cases.
When the user ID of the corresponding participant is not registered in the user ID list 1105 of the stay purpose master information 135 When there are multiple stay purpose numbers 1101 or activity details 1104 Information registered in the stay purpose master information 135 When there is no integrated reliability 1205 indicates the integrated reliability calculated based on the terminal dependent reliability 1201 , the stay location estimation 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 estimation reliability 1202, the user-specific reliability 1203, and the stay purpose reliability 1204 may be used. Furthermore, you may use reliability other than these.

The degree of risk impact 1206 is an item that indicates the degree of impact on health risks predicted for the participant. This is an item calculated by the risk impact calculator 16, and is calculated based on the social participation information. Furthermore, the verification score 1207 is an item that indicates the degree of necessity of collecting additional information calculated based on the integrated reliability 1205 . In this example, a higher value of this score indicates a need for additional information gathering, ie, investigation. Finally, the verification result 1208 is information indicating whether the verification score 1207 requires collection of additional information. In this embodiment, the second record in FIG. 9 records that the verification score 1207 is greater than a predetermined threshold, so that "additional information collection is required".

Since the risk prediction model 137 can use a known machine learning model, the description of its contents is omitted. This concludes the description of the information stored in the auxiliary storage device 130. FIG.

Also, the auxiliary storage device 130 desirably stores the above-described program. Furthermore, it is desirable that these programs be distributed via network 113 or stored in a storage medium.

Incidentally, the auxiliary storage device 130 can be realized by an HDD (Hard Disk Drive) or an SSD (Solid State Drive). Furthermore, the auxiliary storage device 130 may be implemented as a database provided outside the social participation status analysis server 114 .

<Processing flow>
Next, the processing flow in this embodiment will be described. At this time, the processing subject of each process will be described using the configuration (each part) shown in FIG. First, FIG. 10 is an overall processing sequence diagram showing overall processing 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 receives registration application instructions from the participants 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 of the storage unit 28 by the function of the OS. Then, using the communication unit 23, the social participation status analysis server 114 is notified of the user registration application including the user management information. The user management information has items shown in FIG.

Next, in step S21, the social participation information specifying unit 13 of the social participation status analysis server 114 performs user registration in response to the registration application. That is, the social participation information specifying unit 13 registers the user management information included in the notified registration application in the storage unit 22 .

Then, in step S22, the social participation information specifying 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 preparations for social participation status analysis, and may be executed using the operation management terminal 10. FIG. Further, it is desirable that the user terminal 101 is configured to activate the action information collection unit 26 with the notification for registration management in step S22 as a trigger. In other words, activation is executed for starting the processes after step S12.

Next, the behavior information collection unit 26 collects behavior information detected by the behavior information detection unit 25 . As described above, in this embodiment, position information is collected as action information. However, below, position information is described as action information. Also, the behavior information detection unit 25 implemented by a GPS sensor or an acceleration sensor acquires the position of the user terminal 101, that is, the position of the participant, according to predetermined conditions. Here, the acquired action information includes time stamp information, and positions and times are associated with each other.

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

Also, in step S13, the communication unit 23 notifies the social participation status analysis server 114 of the behavior information and the user ID included in the collected information 112 . This notification is executed according to predetermined conditions such as periodically. In addition, when performing periodically, the unit such as day unit or minute unit does not matter. Also, it may be executed when the user terminal 101 is moved. In other words, this notification may be executed when an arbitrary distance is moved per unit time.

Next, in step S22, the social participation status analysis server 114 executes analysis processing for the social participation information specified based on the notified behavior information. The details of this step will be described below with reference to FIG. FIG. 11 is a flow chart showing analysis processing of social participation information in the embodiment.

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

Also, in step S22-2, the social participation information specifying unit 13 specifies social participation information from the behavior information and the user ID. The details of this social participation information specifying process will be described with reference to FIG. FIG. 12 is a flowchart showing processing for identifying social participation information in the embodiment. First, at step S22-21, the social participation information specifying unit 13 receives the behavior information output at step S22-1.

Next, in step S22-22, the social participation information specifying unit 13 uses the received behavior information to determine whether the participant stays. This stay determination means dividing the action information into predetermined units. For example, the social participation information identifying unit 13 applies a technique such as clustering to the behavior information based on the time stamp information, and divides the behavior information into stay information for each stay, which is one of predetermined units. For this reason, the social participation information specifying unit 13 specifies the center of gravity of stay and the information of the stay time period as each piece of stay information.

Next, in step S22-23, the social participation information specifying unit 13 estimates, from the stay place master information 134, the place of stay corresponding to the center of gravity of the stay specified in step S22-22. In other words, the place of stay of the participant is estimated. For this reason, it is desirable that the social participation information specifying unit 13 specifies the stay place barycentric coordinates 1002 closest to the barycenter of the specified stay, and estimates the stay of the stay place ID 905 corresponding thereto.

Next, at step S22-24, the social participation information specifying unit 13 estimates the activity content of the participant based on the place of stay estimated at step S22-23. For this purpose, the social participation information specifying unit 13 specifies the activity content 1104 corresponding to the place of stay ID 905 of the estimated place of stay from the stay purpose master information 135 . Here, as shown in FIG. 8 (second record and third record), even the same place of stay may have different activity contents. Therefore, in addition to specifying the activity content 1104 corresponding to the place of stay ID 905 of the place of stay estimated as described above, the activity content may be estimated as follows.

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

(2) The social participation information specifying unit 13 specifies the using user ID list 1105 corresponding to the notified user ID. That is, the social participation information specifying 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 retrieved, the social participation information specifying unit 13 determines the activity content 1104 retrieved in (1) as the activity content. Note that when only (1) is retrieved, there is a tendency for a plurality of activities to be estimated.

(4) If neither (1) nor (2) is found, it is desirable to proceed to step S22-12 and collect additional information. The order of (1) and (2) is not the same, and parallel processing is also possible. should be performed.

Next, in step S22-25, the social participation information specifying unit 13 merges the results of steps S22-22 to S22-24 to create social participation information. In other words, the social participation information identifying unit 13 identifies the social participation information by merging the following items.
The barycenter of stay and stay time period in the stay information in step S22-22 are the stay barycenter coordinates 902, stay start 903, and stay end 904.
- The place of stay ID 905 estimated in step S22-23 becomes the place of stay ID 905 as it is.
• The activity content estimated in step S22-24 becomes the activity content 906;
・On top of that, the social participation information ID 901 for identifying the social participation information is created using the accepted user ID as the user ID 701 .

With this, the description of FIG. 12 is completed, and the description of the analysis processing in this embodiment is continued by returning to FIG. 11 . In step S22-3, the social participation information specifying unit 13 outputs the specified social participation information to the social participation information verifying unit . Then, from step 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 reliability calculation request to the reliability calculation unit 15 to calculate the reliability of the relevant social participation information. Then, in step S22-5, the reliability calculation unit 15 calculates the reliability of the received social participation information social participation information. Here, the details of the reliability calculation processing in this step will be described with reference to FIG. 13 . FIG. 13 is a flow chart showing reliability calculation processing in this embodiment.

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

In step S22-52, the reliability calculation unit 15 calculates a terminal-dependent reliability indicating a reliability corresponding to the terminal 101 used by the user. For this purpose, the reliability calculation unit 15 calculates the reliability based on the corresponding user terminal 101 and the OS installed therein. Also, in step S22-53, the reliability calculation unit 15 calculates the estimated reliability of the place of stay, which indicates the reliability of the place of stay where the participant has stayed, according to the locational requirements. Also, in step S22-54, the reliability calculation unit 15 calculates a user-specific reliability indicating the reliability corresponding to the participant. Furthermore, in step S22-55, the reliability calculation unit 15 calculates the reliability of stay purpose indicating the reliability of the place where the participant stayed according to the purpose of stay.

Here, the details of the calculation of each reliability are as described above in the explanation of the social participation information verification information 136 in FIG.

Next, in step S22-56, the reliability calculation unit 15 integrates the reliability calculated in each of steps S22-52 to S22-55, and calculates the reliability by integrating the reliability. do. This integration processing includes calculation of representative values such as the average value of each reliability (arithmetic mean, geometric mean, median, etc.), median value, sum, and mode, and extraction of maximum and minimum values. Furthermore, if one of steps S22-52 to S22-55 does not satisfy a predetermined reliability such as being less than a threshold value, calculations in the other steps may be omitted.

At least one of steps S22-52 to S22-55 may be executed. This includes the use of stay feature confidence in terms of stay location estimation confidence and stay purpose confidence. The reliability of stay characteristics corresponds to the characteristics of the stay included in the behavior information, and is particularly based on the accuracy of the behavior information (for example, location information) in the stay. Therefore, it is possible to use at least one of the stay location estimation reliability and the stay purpose reliability as the stay characteristic reliability. Furthermore, the processing may be performed in parallel regardless of the processing order. 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.

With this, the description of FIG. 13 is completed, and the description of the analysis processing in this embodiment is continued by returning to FIG. 11 . At step S22-6, the reliability calculation unit 15 outputs the reliability calculated at step S22-56 to the social participation information verification unit .

Also, in step S22-7, the social participation information verification unit 14 outputs to the risk impact calculation unit 16 a request to calculate the degree of risk impact for the social participation information output in step S22-3. Then, in step S22-8, the degree of risk impact of the output social participation information is calculated in response to the calculation request. Here, the details of the calculation processing of the risk impact level in this step will be described using FIG. 14 . FIG. 14 is a flow chart showing the calculation processing of the degree of risk impact in this embodiment.

First, in step S22-81, the risk impact calculator 16 reads the risk prediction model 137. FIG. A statistical model and a machine learning model can be used as the risk prediction model 137 . Here, the statistical model and machine learning model include linear regression, logistic regression, proportional hazards 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 degree of contribution using more explanatory variables may be additionally prepared. Social participation information is used as explanatory variables 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 calculator 16 uses the risk prediction model 137 to calculate the risk impact. Two calculation examples are shown below.
Example 1: A coefficient (weight) corresponding to each explanatory variable is used as the degree of influence of each piece of social participation information. Example 2: Using so-called xAI technology such as SHAP and LIME, the influence on each social participation information in the nursing care risk prediction analysis result for each participant is calculated and used as the risk influence degree. Note that the calculation of the degree of risk impact is not limited to these. Further, the risk impact calculator 16 records the calculated risk impact in the corresponding item of the social participation information verification information 136 . With this, the description of FIG. 14 is completed, and the description of the analysis processing in this embodiment is continued by returning to FIG. 11 .

Next, in step S22-9, the risk impact calculation unit 16 outputs the calculated risk impact to the social participation information verification unit . Then, in step S22-10, the social participation information verification unit 14 verifies the social participation information. For this purpose, the risk impact calculator 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 the risk impact to calculate the verification score. Then, as the verification score, the representative values of the reliability and the risk impact may be used, or one of them 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 social participation information verification result and the social participation information ID. This information collection plan formulation request may be a formulation request for a plurality of pieces of social participation information. Then, in step S22-12, the information collection plan formulating unit 17 formulates an information collection plan for collecting additional information for improving reliability. For this reason, the information collection plan formulation unit 17 formulates a plan based on the verification score of each social participation information in the information collection plan formulation request. In other words, a plan is developed that prioritizes the collection of additional information for lower confidence or higher risk. Here, the term "priority" includes earlier notification of the additional information collection request. Also, if the verification score is higher in reliability or lower in risk than the threshold, the process may end at this step.

Furthermore, the information collection plan formulation unit 17 may skip the formulation of the information collection plan and execute step S22-13 each time the verification score 1207 satisfies a predetermined condition. Note that the information collection plan formulation request in step S22-11 is a kind of update-related processing request. Therefore, the information collection plan formulation in step S22-12 is also a kind 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 when a predetermined condition is satisfied. In this way, when information is updated, "additional information collection required" is recorded in the verification result 1208 of the social participation information verification information 136. FIG. This predetermined condition includes whether the verification score 1207 is lower in reliability or higher in risk than the threshold. Furthermore, the social participation information verifying unit 14 may determine whether such a predetermined condition is satisfied, and if not, a request for update-related processing may be sent. Furthermore, in step S25, when 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 and reliability satisfy predetermined conditions, the social participation information verification unit 14 may execute step S22-11. For example, if the verification score or 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 for collecting additional information. Then, in step S23, the communication unit 11 notifies the communication unit 23 of the user terminal 101 of an information collection request. Here, various modes are conceivable for the timing of step S23. For example, it may be executed for each formulation in step S22-12, or batch processing may be performed for each unit period. Furthermore, when the number of request units reaches a predetermined number, the notifications may be collectively sent.
With this, the explanation of FIG. 11 is completed, and returning to FIG. 10, the overall processing in this embodiment will 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. For this purpose, the social participation information collection unit 27 outputs various screens shown in FIGS. The social participation information collection unit 27 first outputs the social participation information collection notification screen 1401 . FIG. 15 is a diagram showing a social participation information collection notification screen 1401 in this embodiment. This social participation information collection notification screen 1401 is a screen for inquiring about whether or not collection is possible, and contains text requesting input of additional information.

The example of FIG. 15 describes an example of providing a new function. However, it may also be a specific explanation regarding the sophistication of the functions already provided. For example, these include expansion of prediction target items, improvement of accuracy, expansion of advice items, and the like. The social participation information collection notification screen 1401 also includes a button 1402 for accepting the input of additional information and a button 1403 for not accepting it. When the participant selects button 1402 among these, the screen transitions to a screen for collecting additional information. Also, when the button 1403 is selected, the processing in FIG. 10 is terminated. In this case, it is desirable to notify the social participation status analysis server 114 from the communication unit 23 that the additional information cannot be collected.

Here, a screen that transitions when the button 1402 is selected will be described. 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 action information, that is, verification score areas 1503 to 1505 for each place of stay, a selected place of stay information area 1506, and a correction area 1507. The social participation status area 1502 outputs the social participation status obtained by summarizing the social participation information. The social participation status is not limited to information obtained by summarizing the social participation information.

Further, in verification score areas 1503 to 1505, a 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, allowing input of additional information, that is, correction. Information about the place of stay related to the verification score area 1503 in the active state is output to the place of stay information area 1506 . In the example of FIG. 16, the map of Stay 1 is output, but the name of the place of stay may be specified.

Furthermore, in the correction area 1507, information corresponding to the corresponding item of social participation information is output, and a correction button is output for each of these items. Here, the stay date and time correspond to the start of stay 903 and the end of stay 904 of the social participation information. Also, the place of stay corresponds to the place of stay name 1001 corresponding to the place of stay ID 904 . Furthermore, the purpose of stay corresponds to the activity content 906 . Here, if there are a plurality of activity details 906, a correction button is output for each. When the participant selects the correction button, each item can be corrected. 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. Then, the communication section 11 of the social participation status analysis server 114 receives 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 collect additional information for social participation information that satisfies a predetermined condition, such as the reliability being less than a predetermined threshold. Notify the information collection request of Then, the information collection plan formulation unit 17 collects the additional information from the user terminal 101 accordingly.

Next, in step S24, the information updating section 20 updates the social participation information specified in step S22 using the additional information. In this embodiment, the social participation information identified in step S22 is replaced with additional information. Here, FIG. 17 shows the additional social participation information 133', which is the replaced additional information. The additional social participation information 133' is the social participation information 133
has the same items as However, the social participation information ID 901 is added with a branch number (-01) indicating that it has been updated. In addition to replacing (overwriting), additional social participation information 133' may be added for this update. In this case, it is desirable to record that the social participation information 133 before update is invalid.

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

Next, in step S25, the social participation status evaluation unit 21 specifies the social participation status of the participant based on the social participation information and evaluates the social participation status. Here, the social participation status includes the result of counting the social participation information for a predetermined period and the social participation information itself. In addition, assessment of social participation status includes identifying caregiver risks and risk advice for participants. Note that the evaluation is one type of analysis in this embodiment, and other analyzes may be performed.

In order to identify, analyze, or evaluate the social participation status, the social participation status evaluation unit 21 can use AI technology and big data analysis technology. Since these can be realized by known techniques, the description of their contents is omitted. Next, in step S26, the communication unit 11 notifies the user terminal 101 of the specified social participation status and the social participation status evaluation result including the evaluation result. Note that the social participation status evaluation result may include at least one of the social participation status and the social participation status evaluation result including the evaluation 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. FIG. FIG. 18 shows the social participation status evaluation screen 1601 output in step S15. In FIG. 18, social participation status evaluation screen 1601 has total result area 1602 , risk area 1603 and advice area 1604 . The content output to each of these areas is the result of the evaluation in step S25.

The tally result area 1602 is an area showing the result of tallying the social participation information of the corresponding participant. A risk area 1603 outputs the risk calculated based on the social participation information of the participant. In FIG. 18, care risk is used as the risk. Also, in an advice area 1604, advice for reducing risk is output based on the social participation information.

This is the end of the description of this embodiment. The present invention is not limited to this embodiment, and includes various applications and modifications. The present invention also includes information processing for various services by the business systems 30 to 60 based on social participation status analysis results 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 Action information detection unit 26 Action information collection unit 27 Social participation information collection unit 28 Storage unit 30 to 60 Business system 101 User terminal 102 Input/output device 103 Arithmetic device , 104... action information sensor, 105... communication path, 106... communication I/F, 107... main storage device, 108... action information collection program, 109... social participation information collection program, 110... auxiliary storage device, 111... terminal information , 112... Collected information, 113... Network, 114... Social participation status analysis server, 115... Communication I/F, 116... Input device, 117... Output device, 118... Arithmetic 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 Location of stay master information 135 Purpose of stay master information , 136... social participation information verification information, 137... risk prediction model

Claims (13)

In a social participation situation analysis device for analyzing the social participation situation of participants,
a communication unit that receives action information indicating the action history of each of the plurality of participants;
a social participation information identifying unit that identifies social participation information of the participant based on the behavior information;
a reliability calculation unit that calculates the reliability of the social participation information;
an update-related processing unit that executes update-related processing for the social participation information according to the reliability;
A social participation status analysis device having a social participation status evaluation unit that analyzes the social participation status of the participant based on the social participation information on which the update-related processing has been performed. In the social participation situation analysis device according to claim 1,
The update-related processing unit updates the social participation information as the update-related processing. In the social participation situation analysis device according to claim 2,
The update-related processing unit, as the update-related processing, outputs an information collection request for collecting additional information with respect to the social participation information whose reliability is a predetermined condition, and the social participation situation analysis device for collecting the additional information. . In the social participation situation analysis device according to claim 1,
Furthermore, the social participation status analysis device has a risk impact level calculation unit that calculates a risk impact level indicating the degree of impact on the health risk of the participant based on the social participation information. The social participation situation analysis device according to any one of claims 1 to 4,
The social participation situation analysis device, wherein the reliability calculation unit calculates, as the reliability, the reliability of stay characteristics according to the characteristics of stay included in the behavior information. In the social participation situation analysis device according to claim 5,
The reliability calculation unit calculates, as the reliability of the stay characteristics, at least one of a stay place estimation reliability according to the location requirements of the stay place of the participant and a stay purpose reliability according to the stay purpose of the stay place. Social participation analysis device that calculates. In the social participation situation analysis device according to claim 6,
The social participation situation analysis device, wherein the reliability calculation unit further calculates at least one of terminal-dependent reliability according to the user terminal detecting the behavior information and participant-specific reliability according to the participant. A user terminal, which is a computer, is connected to a social participation status analysis device that analyzes the social participation status of participants,
a behavior information collecting unit that collects behavior information indicating the behavior history of the participant;
Notifying the social participation status analysis device of the collected behavior information,
Communication for accepting, from the social participation status analysis device, an information collection request for collecting additional information for the social participation information specified based on the behavior information, the reliability of the social participation information of the participant meeting a predetermined condition. Department and
function as a social participation information collection unit that collects social participation information, which is the additional information, from the participant;
A program for analyzing the social participation status of the participant based on the social participation information collected by the social participation status analysis device. In the program according to claim 8,
moreover,
A program that causes the user terminal to function as an action information detection unit that detects position information of the participant as the action information. In the program according to claim 8,
A program for calculating, in the social participation status analyzer, a degree of risk impact indicating the degree of impact on the health risk of the participant based on the collected social participation information. In the program according to any one of claims 8 to 10,
A program for calculating, as the reliability, a stay characteristic reliability according to a stay characteristic included in the behavior information in the social participation status analysis device. The program according to claim 11,
In the social participation status analysis device, as the stay characteristic reliability, at least a stay place estimation reliability according to the location requirements of the stay place of the participant and a stay purpose reliability according to the stay purpose of the stay place A program in which one is calculated. The program according to claim 12,
A program for calculating at least one of a terminal-dependent reliability degree according to the user terminal and a participant-specific reliability degree according to the participant in the social participation situation analysis device.

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