A device for supporting social participation, and a method for supporting social participation.

Abstract

To encourage social participation of citizens.SOLUTION: A social participation support device 10 includes: a storage device which stores information about multiple items that indicate social activities performed by multiple users in a prescribed period, and information about a biological attribute value of each of the multiple users; and a control device which executes model creation processing of creating a numerical model that estimates the biological attribute value of the users from information about the multiple items that indicate the social activity performed by the users on the basis of the stored information about the items and information about the biological attribute value, attribute value estimation processing of estimating the biological attribute value of the specified user by inputting the information about the multiple items that indicate the social activity performed by the specified user to the numerical model, and output processing of outputting the estimated biological attribute value.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a social participation support device and a social participation support method.

Background Art

[0002] In recent years, along with the increasing health awareness of citizens, technologies for knowing one's own health condition have been developed. For example, Patent Document 1 describes an activity meter that calculates an activity age from the amount of physical activity (number of steps and activity intensity) obtained from an acceleration sensor such as a pedometer. Patent Document 2 describes a health condition determination device that calculates a health age, which is an index obtained by converting the health condition into age based on the measured values measured by an activity meter, a body composition meter, or a blood glucose or blood pressure meter. Patent Document 3 discloses a health condition diagnosis system that calculates an evaluation age for the health condition from a walking evaluation value, a physical strength evaluation value, and a cognitive evaluation value.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, one of the purposes of knowing the health condition is to continuously participate in society while maintaining the health condition well according to one's own attributes (for example, age).

[0005] From this perspective, for example, while Patent Documents 1 and 2 assess health status based on biological factors, they do not adequately address how this specifically connects to citizens' social participation. Furthermore, while Patent Document 3 is related to social participation in that it processes walking information, its content is not necessarily clear. For example, the number of steps does not necessarily correlate with age.

[0006] This invention has been made in view of these circumstances, and its purpose is to provide a social participation support device and a social participation support method that can encourage citizens' participation in society. [Means for solving the problem]

[0007] One of the present inventions for solving the above problems is to Okeru Each of multiple users involving movement Social activities Includes movement information and location information. Information on multiple items and each of the multiple users age A storage device that stores information and the information of the stored items and age Based on the information, the user performed The aforementioned Based on information from multiple items indicating the user's social activities, age The model creation process involves creating a numerical model to estimate the value, and the specified user performed The aforementioned By inputting information on multiple items representing social activities into the numerical model, the specified user age An attribute value estimation process that estimates the estimated age This is a social participation support device equipped with an output process that outputs a signal and a control device that performs such an output. [Effects of the Invention]

[0008] According to the present invention, it is possible to encourage citizens' participation in society. Other configurations and effects will be clarified by the following description of the embodiments. [Brief explanation of the drawing]

[0009] [Figure 1] It is a diagram showing an example of the configuration of the social participation support system according to the first embodiment. [Figure 2] It is a diagram explaining an example of the hardware possessed by the social participation support device and the functional units included in the social participation support device. [Figure 3] It is a diagram showing an example of basic information in social participation information. [Figure 4] It is a diagram showing an example of movement information in social participation information. [Figure 5] It is a diagram showing an example of stay information in social participation information. [Figure 6] It is a flowchart explaining the outline of the social participation support process. [Figure 7] It is a flowchart explaining an example of the social participation age estimation formula creation process. [Figure 8] It is a diagram showing an example of social participation shaping data. [Figure 9] It is a flowchart explaining an example of the unique stay location number process. [Figure 10] It is a diagram showing an example of the calculated score formula, the social participation age estimation formula BA, and the correction term Z. [Figure 11] It is a flowchart explaining an example of the input variable setting screen. [Figure 12] It is a diagram showing an example of the social participation age estimation process. [Figure 13] It is a diagram showing an example of the social participation age estimation result data. [Figure 14] It is a diagram showing an example of the social participation age estimation result screen. [Figure 15] It is a diagram showing an example of the transition screen. [Figure 16] It is a flowchart explaining an example of the social participation age estimation formula creation process according to the second embodiment. [Figure 17] It is a diagram showing an example of the shaped data for each period. [Figure 18] It is a diagram showing examples of the score formula, the social participation age estimation formula BAu, and the correction term Zu calculated for each aggregation period. [Figure 19]This flowchart illustrates an example of the social participation age estimation process according to the second embodiment. [Figure 20] This figure shows an example of the estimated social participation age data according to the second embodiment. [Figure 21] This figure shows an example of a social participation age estimation formula according to the third embodiment. [Figure 22] This figure illustrates an example of the hardware and functions of a social participation support device according to the fourth embodiment. [Figure 23] This flowchart illustrates an example of the process for creating a social participation age estimation formula according to the fourth embodiment. [Figure 24] This figure shows an example of data used to create a correction formula. [Figure 25] This figure shows an example of the correction formula that can be calculated. [Figure 26] This flowchart illustrates an example of the social participation age estimation process according to the fourth embodiment. [Figure 27] This figure shows an example of the estimated social participation age data according to the fourth embodiment. [Figure 28] This figure illustrates an example of the hardware and functions of a social participation support device according to the fifth embodiment. [Figure 29] This is a flowchart illustrating an example of social participation support processing according to the fifth embodiment. [Figure 30] This is a flowchart illustrating the details of the caregiving risk calculation process. [Figure 31] This figure shows an example of the social participation age estimation result data and long-term care certification result data that are obtained. [Figure 32] This figure shows an example of a formula for estimating the risk of needing long-term care. [Modes for carrying out the invention]

[0010] Hereinafter, embodiments of the present invention will be described with reference to the drawings. [First Embodiment] Figure 1 shows an example of the configuration of the social participation support system 1 according to the first embodiment. The social participation support system 1 is composed of a social participation support device 10 to which a database 30 is connected, and one or more user terminals 20.

[0011] User terminal 20 is an information processing device held by each user participating in society. User terminal 20 is a location acquisition device such as GPS (Global Positioning System) and user terminal The device is equipped with a pedometer that measures the number of steps taken by the user holding the terminal 20, and transmits the current location and step count information of the user terminal 20 to the social participation support device 10 at predetermined timings.

[0012] The social participation support device 10 creates a formula (hereinafter referred to as the social participation age estimation formula) for calculating the user's estimated (converted) age (hereinafter referred to as the social participation age; details will be described later) based on the information received from each user terminal 20. Then, when the social participation support device 10 receives a predetermined instruction from the user terminal 20, it calculates the user's social participation age based on the social participation age estimation formula and transmits the calculated social participation age information to the user terminal 20.

[0013] Furthermore, the connection between the social participation support device 10 and each user terminal 20 is via the Internet, LAN (Local Area Network), WAN (Wide Area Network), or wired or wireless connections such as dedicated lines. It is connected via communication network 5.

[0014] Next, Figure 2 is a diagram illustrating an example of the hardware and functional components of the social participation support device 10.

[0015] First, the social participation support device 10 includes a control unit 1 such as a CPU (Central Processing Unit). 04, memory 105 such as RAM (Random Access Memory) or ROM (Read Only Memory), storage device 106 such as HDD (Hard Disk Drive) or SSD (Solid State Drive), input device 102 such as keyboard, mouse or touch panel, output device 103 such as display or touch panel, NIC (Network Interface Card), wireless communication module, USB (Universal Serial Interface) module, or serial communication module It includes a communication device 107 composed of wires, etc.

[0016] Next, the social participation support device 10 comprises the following functional units: a model creation unit 111, a social participation age estimation unit 112 (attribute value estimation unit), and a real age difference calculation unit 113.

[0017] The model creation unit 111 creates a numerical model that estimates the user's biological attribute values ​​from information on multiple items indicating the social activities the user has performed, based on the information on each item (hereinafter referred to as social participation parameters) that indicate the social activities the user has performed, as well as the user's biological attribute values, as described later in the social participation information 200.

[0018] Social participation information 200 includes information on multiple items indicating each social activity performed by each user during a specified period, as well as information on each user's biological attribute values.

[0019] In this embodiment, the above items include the number of times the user went out during a predetermined period, the number of places the user visited, and the number of steps the user took. Details of the social participation information 200 will be described later.

[0020] Furthermore, in this embodiment, the biological attribute value is defined as the user's age (social participation age) calculated from the perspective of social participation.

[0021] Furthermore, in this embodiment, the numerical model is assumed to be a social participation age estimation formula for calculating the social participation age, as described above (details will be described later).

[0022] The model creation unit 111 creates a composite variable (first principal component) of each variable representing each of the multiple items of multiple users, and combines the created composite variable with the biological attribute values ​​(age) of the multiple users. A social participation age estimation formula is created based on the average value of ) and the standard deviation of the biological attribute values ​​(age) of multiple users.

[0023] Specifically, the model creation unit 111 includes a data formatting unit 114, an input variable setting unit 115, and a social participation age estimation formula creation unit 116.

[0024] The data formatting unit 114 processes the social participation information data 200 into data for creating the first principal component of the social participation parameter (hereinafter referred to as formatted data).

[0025] The input variable setting unit 115 sets variables (hereinafter referred to as input variables) that correspond to the items (social participation parameters) to be entered into the social participation age estimation formula.

[0026] The social participation age estimation formula creation unit 116 creates a first principal component based on the input variable data set in the input variable setting unit 115 from the formatted data created by the data formatting unit 114. Then, the social participation age estimation formula creation unit 116 creates a social participation age estimation formula based on the created first principal component.

[0027] Next, the social participation age estimation unit 112 calculates the biological attribute value (social participation age) of the specified user by inputting information from multiple items indicating the social activities performed by the specified user into the social participation age estimation formula.

[0028] The actual age difference calculation unit 113 calculates the difference between the social participation age calculated by the social participation age estimation unit 112 and the user's actual age (hereinafter referred to as the actual age difference).

[0029] Next, the social participation support device 10 is connected to the database 30. The database 30 includes a social participation information storage unit 311, a social participation age estimation formula storage unit 312, and an estimation result storage unit 313.

[0030] The social participation information storage unit 311 stores social participation information 200. This social participation information 200 includes basic information 210, movement information 220, and stay information 230. Details of this information will be described later.

[0031] The social participation age estimation formula memory unit 312 stores the social participation age estimation formula 300 created by the model creation unit 111.

[0032] The estimation result storage unit 313 stores information such as the social participation age and the difference between the user's actual age and the estimated social participation age of each user (social participation age estimation result data 400), which are estimated by the social participation age estimation unit 112.

[0033] (Social participation information) Here, Figure 3-5 shows an example of social participation information 200.

[0034] (Social participation information - basic information) First, Figure 3 shows an example of basic information 210 in social participation information 200. For each user, the basic information 210 includes the user's ID (personal ID 211), the user's gender 212, the user's age 213, and the user's home location 214. In this embodiment, the home location 214 is represented by latitude and longitude, but it may be represented using any other information.

[0035] (Social participation information - mobility information) Figure 4 shows an example of mobility information 220 in social participation information 200. Mobility information 220 contains, for each user, the following information: user ID (personal ID 221), data recording date 222, data recording month 223, the user's steps for that day 224, information indicating whether the user went out on that day (outing 225), the user's distance traveled on that day 226, and the user's travel time for that day 227.

[0036] (Social participation information - Accommodation information) Figure 5 shows an example of the stay information 230 in the social participation information 200. For each user, the stay information 230 includes the user's ID (personal ID 231), the latitude and longitude of the user's location 232, the date and time the user started their stay at that location (start date and time 233), the date and time the user ended their stay at that location (end date and time 234), the stay location code 235 which is the identifier of that location, and the distance 236 from the user's home to that location. In this embodiment, the location is represented by latitude and longitude, but it may be represented using any other information.

[0037] In this embodiment, the location code is an identifier for one of several pre-defined areas (represented by latitude and longitude) and indicates the user's current location. The location code is set for each municipality or facility, for example.

[0038] The functions of each information processing unit in the social participation support system 1 described above are realized by the control device 104 reading programs from the memory 105 or storage device 106. Each program can be recorded and distributed, for example, on a portable or fixed recording medium. Furthermore, all or part of these programs may be realized using virtual information processing resources provided using virtualization technology, process space isolation technology, etc., such as virtual servers provided by a cloud system. Also, all or part of these programs may be realized by services provided by a cloud system via an API (Application Programming Interface), etc. Next, we will explain the processes performed by the social participation support system 1.

[0039] Figure 6 is a flowchart illustrating the overview of the processing (social participation support processing) performed by the social participation support system 1. First, the social participation support device 10 executes a data collection process s1 to collect data related to social participation from the user terminal 20.

[0040] For example, each user terminal 20 transmits location information obtained from GPS, step count information obtained from a pedometer, and user attribute information to the social participation support device 10 at a predetermined time (for example, at a predetermined time, at a predetermined time interval, or at a time specified by the user). The social participation support device 10 converts each of the received pieces of information into social participation information 200 (basic information 210, movement information 220, and stay information 230), stores it, and accumulates it.

[0041] Subsequently, the social participation support device 10 executes a social participation age estimation formula creation process s2, which is a process of creating a social participation age estimation formula based on the data collected in the data collection process s1.

[0042] Subsequently, when the social participation support device 10 receives a predetermined instruction from the user terminal 20, it executes a social participation age estimation process s3 to calculate the user's social participation age based on the social participation age estimation formula created in the social participation age estimation formula creation process s2.

[0043] The social participation support device 10 executes a result display process s4 that outputs information about the social participation age calculated in the social participation age estimation process s3. The above process is repeated as needed. The details of each process are explained below.

[0044] <Process for creating an estimated age for social participation> Figure 7 is a flowchart illustrating an example of the social participation age estimation process s2. First, the data formatting unit 114 obtains each user's social participation information 200 (basic information 210, movement information 220, and stay information 230) (s201).

[0045] The data formatting unit 114 creates data (hereinafter referred to as formatted data) by aggregating the social participation information 200 of each user over the entire period of the social participation information 200, based on the social participation information 200 acquired in s201, and records the created formatted data in the social participation formatted data 800 (s202).

[0046] (Social participation in cosmetic surgery data) Figure 8 shows an example of social participation formatting data 800. For each user, the social participation formatting data 800 includes the user's ID (personal ID 801), the data year 802, the user's gender 803, the user's age in that year 804, the user's average number of steps in that year 805, the user's average number of days out in that year 806, the average number of unique places the user has stayed in that year (hereinafter referred to as unique places stayed) 807, the user's average travel distance in that year 808, the user's average travel time in that year 809, and the average of the user's maximum travel distance for each month in that year (average maximum travel distance 810).

[0047] Here, Figure 9 is a flowchart illustrating an example of the process for calculating the number of unique places of stay, which is performed in the process s202 of the social participation age estimation formula creation process s2.

[0048] First, the data formatting unit 114 obtains time-series data of a user's latitude and longitude 232, start date and time 233, and end date and time 234 from the stay information 230 of the social participation information 200 (s2021).

[0049] The data formatting unit 114 identifies the location code and time period for each area where the user stayed, based on the time-series data acquired in s2021 (s2022).

[0050] Then, the data formatting unit 114 calculates the unique areas (locations) by removing duplicate locations from the location codes obtained in s2021 (s2023). This completes the process of calculating the number of unique locations.

[0051] Next, as shown in Figure 7, the input variable setting unit 115 sets the social participation parameters (input variables) (s203). For example, the input variable setting unit 115 displays the input variable setting screen 1100, which will be described later, and accepts input from the administrator of social participation parameters (input variables) that will be used as input values ​​for the social participation age estimation formula to be created.

[0052] Next, the data formatting unit 114 standardizes the formatted data related to the social participation parameters set in s203 (average number of steps 805, number of days out 806, average number of places stayed 807, average distance traveled 808, average travel time 809, and average maximum distance traveled 810 of the social participation formatted data 800).

[0053] Then, the social participation age estimation formula generation unit 116 performs principal component analysis on the standardized input variables to determine the composite parameter (first principal component) of the social participation parameters that most determines the degree of social participation (s205). For example, the social participation age estimation formula generation unit 116 calculates the score formula PCS (equation (1)) related to each input variable Xj and its weight coefficient wj.

[0054] PCS=(w1X1+···+wjXj+···+wnXn) / Standard deviation SD···( 1)

[0055] In this process, we determine the weight coefficients wj and standard deviation SD such that the variance of the score PCS is maximized and the mean is 0 (w1^2 + w2^2 + ... + wn^2 = 1).

[0056] Meanwhile, the social participation age estimation formula generation unit 116 calculates the average age and standard deviation of all users based on the social participation formatted data 800 (s206).

[0057] The social participation age estimation formula generation unit 116 creates a social participation age estimation formula BA (formula (2)) for calculating the social participation age, based on the first principal component calculated in s205 and the mean age and standard deviation calculated in s206.

[0058] BA = PCS × (Standard deviation of age) + (Mean of age) ... (2)

[0059] The social participation age estimation formula generation unit 116 calculates the regression coefficient a related to age by performing a regression analysis between the social participation age BAi of each user i, calculated by formula (2) created in s206, and the age of each user i (s208).

[0060] Then, the social participation age estimation formula generation unit 116 calculates a correction term Zi (equation (3)) for calculating user i's social participation age based on the average age calculated in s206 and the regression coefficient a calculated in s208 (s209). This correction term provides a numerical correction when user i's age lies at the extreme end of the age distribution of all users.

[0061] Zi = (User i's age - Average age) × (1-a) ... (3)

[0062] This concludes process s2 for creating the social participation age estimation formula. Figure 10 shows an example of the calculated score formula, the social participation age estimation formula BA, and the correction term Z.

[0063] (Input variable settings screen) Figure 11 shows an example of the input variable setting screen 1100. The input variable setting screen 1100 includes a display field 1101 for each social participation parameter, a display field 1102 for the correlation coefficient between the value of the social participation parameter and age, and a setting field 1103 for receiving input from the administrator to set the social participation parameter as an input variable.

[0064] <Estimation of age for social participation> Figure 12 is a flowchart illustrating an example of the social participation age estimation process s3. The social participation age estimation process s3 is initiated, for example, when the social participation support device 10 receives an instruction to calculate the social participation age from a user terminal 20 of a certain user (hereinafter referred to as the target user).

[0065] The social participation age estimation unit 112 obtains social participation information 200 (basic information 210, movement information 220, and stay information 230) of the target user x (s301).

[0066] The social participation age estimation unit 112 creates data (hereinafter referred to as user formatted data) by aggregating the movement information 220 and stay information 230 of the target user x for each predetermined aggregation period (in this case, monthly) based on the social participation information 200 acquired in s301 (s302).

[0067] Next, the social participation age estimation unit 112 inputs the user formatted data created in s302 into the social participation age estimation formula (formula (1)) created in the social participation age estimation formula creation process s2. Therefore, the social participation age BAx,t for each aggregation period t of the target user x is calculated (s303).

[0068] Furthermore, the social participation age estimation unit 112 extracts the age of the target user x for each aggregation period t from the user formatting data created in s302, and inputs each extracted age into the correction formula (formula (2)) created in the social participation age estimation formula creation process s2, thereby calculating the values ​​of the correction terms Zx,t for each aggregation period of the target user x (s304).

[0069] The social participation age estimation unit 112 calculates the corrected social participation age BA2x,t by adding the correction term Zx,t calculated in s304 to the social participation age BAx,t calculated in s303 (s305).

[0070] Then, the social participation age estimation unit 112 calculates the age difference Dx, t by subtracting the actual age of the target user x in each aggregation period t from the calculated social participation age BA2x, t (s306). The social participation age estimation unit 112 registers the social participation age BA2x, t and the age difference Dx, t calculated in s305 and s306 into the social participation age estimation result data 400. This completes the social participation age estimation process s3.

[0071] (Data on estimated age of social participation) Figure 13 shows an example of the estimated social participation age data 400. This estimated social participation age data 1300 contains the following information for each target user: the target user's identifier (personal ID 1301), the aggregation period (year and month 1302), the target user's gender 1303, the target user's age during that aggregation period 1304, the target user's average number of steps taken during that aggregation period 1305, the target user's average number of days spent out during that aggregation period 1306, the target user's average number of unique places visited during that aggregation period 1307, the target user's social participation age during that aggregation period 1308, and the target user's age difference during that aggregation period 1309 (difference from actual age).

[0072] (Screen showing estimated age for social participation) Next, Figure 14 shows an example of a screen (social participation age estimation result screen 1400) displayed in the result display process s3. The social participation age estimation result screen 1400 is displayed, for example, when the social participation support device 10 receives an instruction from the target user's user terminal 20 to display the social participation age for a specified year and month from the aggregation period.

[0073] The estimated social participation age results screen 1400 includes a target year and month display field 1401 that displays the specified year and month, a corrected social participation age display field 1402 that displays the target user's social participation age in the specified year and month, an age difference display field 1403 that displays the difference between that social participation age and the target user's actual age in the specified year and month, and an input variable display field 1404 that displays a list of the specified input variables and their values ​​(aggregated values ​​in the specified year and month).

[0074] Furthermore, the social participation age estimation results screen 1400 is provided with a trend screen display area 1405 for displaying a trend screen 1500 that shows the trends of each data for each aggregation period for the target user.

[0075] (Transition screen) Figure 15 shows an example of the trend screen 1500. The trend screen 1500 includes a first graph 1501 that shows the trend of the target user's age of social participation in each aggregation period, and second graphs 1502 and 1503 that show the trend of the values ​​of each input variable in each aggregation period for the target user.

[0076] As described above, the social participation support device 10 of this embodiment uses the social participation information 200, Based on information from multiple items (social participation parameter items) indicating the social activities performed by multiple users over a predetermined period, and information from the user's biological attribute values ​​(social participation age), a numerical model (social participation age estimation formula 300) is created to estimate the user's biological attribute values ​​from the user's social participation parameter information. By inputting information from the social participation parameter items related to the social activities performed by the target user into the numerical model (social participation age estimation formula 300), the target user's biological attribute values ​​(social participation age) are estimated, and the estimated biological attribute values ​​are output.

[0077] Thus, the social participation support device 10 of this embodiment estimates the biological attribute values ​​of a target user by creating a numerical model that estimates the user's biological attribute values ​​using information on the social participation activities performed by the user. As a result, the user can easily find out what biological attributes they have from the perspective of social participation (what age they correspond to), and can make decisions about social participation from that perspective.

[0078] As described above, the social participation support device 10 of this embodiment can encourage citizens to participate in society.

[0079] Furthermore, in the social participation support device 10 of this embodiment, in the social participation age estimation formula creation process s2, a composite variable (first principal component) of each variable of the social participation parameter is created, and a social participation age estimation formula is created based on the created first principal component, the mean value of each user's biological attribute value (age), and the standard deviation of each user's age.

[0080] In this way, by determining the first principal component based on multiple social participation parameters and combining it with age statistics, the characteristics of a user's social participation can be accurately converted into biological attribute values ​​(social participation age).

[0081] Furthermore, in the social participation support device 10 of this embodiment, in the social participation age estimation process s2, the device creates a social participation age estimation formula that estimates the user's social participation age from the number of times the user has gone out, the number of places they have visited, and the number of steps taken.

[0082] By creating a social participation age estimation formula using elements that have a high correlation with age and are considered to accurately represent the state of social participation, it is possible to create a social participation age estimation formula that can accurately calculate the social participation age.

[0083] [Second Embodiment] In the second embodiment of the social participation support system 1, the social participation support device 10 creates a social participation age estimation formula at predetermined intervals. This section will focus on the differences from the first embodiment.

[0084] The configuration of the social participation support system in the second embodiment is the same as in the first embodiment. On the other hand, the model creation unit 111 of the social participation support device 10 in the second embodiment performs the following processing. That is, based on the information of each item of the social participation parameter and the user's biological attribute value (social participation age) in the social participation information 200, the model creation unit 111 creates a numerical model (social participation age estimation formula) for each of several periods that estimates the user's biological attribute value from the information of multiple items indicating the social activities performed by the user. In this embodiment, these periods are assumed to be each month (social participation age estimation formula for January, social participation age estimation formula for February, ...).

[0085] Furthermore, the social participation age estimation formula creation unit 116 of the social participation support device 10 in the second embodiment performs the following processing. That is, the social participation age estimation formula creation unit 116 takes the period information and The target user's social participation age is calculated by inputting information on multiple items indicating the social activities the user undertook during that period into a social participation age estimation formula corresponding to the aforementioned period.

[0086] Next, the social participation support process of the second embodiment will be described. In the social participation support processing of the second embodiment, the data collection process s1 is the same as in the first embodiment. The social participation age estimation formula creation process s2 and the social participation age estimation process s3 in the second embodiment will be described below.

[0087] <Process for creating an estimated age for social participation> Figure 16 is a flowchart illustrating an example of the social participation age estimation formula creation process s2 according to the second embodiment. First, the data formatting unit 114 acquires social participation information 200 (basic information 210, movement information 220, and stay information 230) for each user, similar to s201 in the first embodiment (s221).

[0088] The data formatting unit 114 creates data (hereinafter referred to as period-specific formatted data) by aggregating the social participation information 200 for each user over the entire period of the social participation information 200 acquired in s221 (s222).

[0089] (Formatted data by period) Figure 17 shows an example of formatted data for each period. The formatted data for each period 1700 contains the following information for each user: personal ID 1701, aggregation period (year and month 1702), user's gender 1703, user's age during that aggregation period 1704, average number of steps taken by the user during that aggregation period 1705, average number of days the user was out during that aggregation period 1706, average number of unique places the user stayed during that aggregation period 1707, average distance traveled by the user during that aggregation period 1708, average travel time during that aggregation period 1709, and the average of the maximum distance traveled by the user during that aggregation period (average maximum distance traveled 1710).

[0090] Next, as shown in Figure 16, the input variable setting unit 115 sets each input variable (s223), similar to s203 in the first embodiment.

[0091] Next, the social participation age estimation formula generation unit 116 selects one of the aggregation periods (s224).

[0092] The data formatting unit 114, for the aggregation period selected in s224 (hereinafter referred to as the selected aggregation period), standardizes the data of the period-specific formatted data 1700 created in s222 (average number of steps 1705, number of days out 1706, average number of places stayed 1707, average distance traveled 1708, average travel time 1709, and average maximum distance traveled 1710) in the same manner as in the first embodiment (s225).

[0093] Then, the social participation age estimation formula generation unit 116 determines the first principal component for the selected aggregation period, similar to s225 in the first embodiment. For example, the social participation age estimation formula generation unit 116 determines the score formula (4) for each input variable Xj,u and their weight coefficients wj,u for the selected aggregation period u.

[0094] PCSu = (w1, u × X1, u + ... + wj, u × Xj, u + ... + wn, u × Xn, u) / Standard Deviation SDu ... (4)

[0095] In this process, we determine the weight coefficients wj,u and standard deviation SD such that the variance of the score PCSu is maximized and the mean is 0 (w1,u^2+w2,u^2+···+wn,u^2=1 ).

[0096] Meanwhile, the social participation age estimation formula creation unit 116 calculates the average age and standard deviation for all users during the selection aggregation period, similar to s205 in the first embodiment (s226).

[0097] The social participation age estimation formula generation unit 116 creates a social participation age estimation formula BAu (formula (5)) for calculating the social participation age in the selected aggregation period u, based on the first principal component calculated in s225 and the mean age and standard deviation calculated in s226 (s227).

[0098] BAu = PCSi, u × (standard deviation of age in the selected aggregation period u) + (mean age in the selected aggregation period u) ... (5)

[0099] The social participation age estimation formula generation unit 116 calculates the regression coefficient au for age in the selected aggregation period u by performing a regression analysis between the social participation age BAi,u for each user i in the selected aggregation period u, calculated by formula (5) created in s227, and the age of each user in the selected aggregation period (s228).

[0100] Then, the social participation age estimation formula generation unit 116 calculates a correction term Zu (equation (6)) for calculating the social participation age during the aggregation period u, based on the average age calculated in s226 and the regression coefficient a calculated in s228 (s229).

[0101] Zu = (Age during the aggregation period u - Average age) × (1 - au) ... (6)

[0102] The social participation age estimation formula creation unit 116 repeats the processes from s224 to s229 above for all aggregation periods (s230), and thereafter the social participation age estimation formula creation process s2 is completed. Figure 18 shows examples of the score formula, the social participation age estimation formula BAu, and the correction term Zu calculated for each aggregation period.

[0103] <Estimation of age for social participation> Next, Figure 19 is a flowchart illustrating an example of the social participation age estimation process s3 according to the second embodiment. The social participation age estimation unit 112 acquires social participation information 200 (basic information 210, movement information 220, and stay information 230) of the target user x, similar to s301 in the first embodiment (s321).

[0104] The social participation age estimation unit 112, similar to s302 in the first embodiment, creates user formatted data by aggregating the movement information 220 and stay information 230 of the target user x for each predetermined aggregation period (in this case, monthly) based on the social participation information 200 acquired in s331 (s322).

[0105] Next, the social participation age estimation unit 112 calculates the social participation age BAx,t for each aggregation period t of the target user x by inputting the user formatted data created in s322 into the social participation age estimation formula BAu (formula (5)) created in the social participation age estimation formula creation process s2, similar to s303 in the first embodiment (s323).

[0106] Furthermore, the social participation age estimation unit 112, similar to s304 in the first embodiment, extracts the age of the target user x for each aggregation period t from the user formatted data created in s322, and applies each extracted age to the correction term Zu (formula (6)) created in the social participation age estimation formula creation process s2, thereby calculating the values ​​of the correction terms Zx,t for each aggregation period of the target user x (s3 twenty four).

[0107] The social participation age estimation unit 112 calculates the corrected social participation age BA2x,t by adding the correction term Zx,t to the social participation age BAx,t calculated in s324, similar to s305 in the first embodiment (s325). The social participation age estimation unit 112 registers the social participation age BA2x,t calculated in s325 in the social participation age estimation result data 400. The social participation age estimation unit 112 may also calculate the age difference Dx,t by subtracting the actual age of the target user x in each aggregation period t from the calculated social participation age BA2x,t.

[0108] (Data on estimated age of social participation) Figure 20 shows an example of the estimated social participation age data 400 according to the second embodiment. The social participation age BAx,t in this estimated social participation age data 2000 is a different value from the social participation age BAx,t in the estimated social participation age data 1300 of the first embodiment, depending on the changes in each user's social activities characterized by each aggregation period.

[0109] In the second embodiment, as in the first embodiment, the screen showing the estimated social participation age results and the progress screen are displayed.

[0110] As described above, the social participation support device 10 of this embodiment stores information on multiple social participation parameters for each user and information on each user's biological attribute value (social participation age) as social participation information 200 for each of multiple aggregation periods within a predetermined period. Based on this social participation information 200, it creates a social participation age estimation formula for each aggregation period, and estimates the biological attribute value (social participation age) of the target user by inputting the period information and the target user's social participation parameters during that period into the social participation age estimation formula corresponding to that period.

[0111] It is believed that the patterns of citizens' social participation are influenced by external environmental factors that change depending on the timing (period), such as temperature, weather, or social conditions. Therefore, as in the social participation support device 10 of this embodiment, by creating a social participation age estimation formula for each such period, it is possible to calculate a social participation age that reflects the actual situation of the user or society.

[0112] [Third Embodiment] In the third embodiment of the social participation support system 1, the social participation support device 10 creates a social participation age estimation formula for each predetermined category to which the user belongs. The differences from the first embodiment will be explained here.

[0113] The configuration of the social participation support system 1 in the third embodiment is the same as in the first embodiment. The functions of the social participation support device 10 are as follows.

[0114] First, in the third embodiment, the model creation unit 111 creates a numerical model (social participation age estimation formula) for each category, which estimates the user's biological attribute value (social participation age) from information on multiple items indicating the social activities performed by the user, based on the information on the social participation parameter items and the user's biological attribute value (social participation age) in the social participation information 200. In this embodiment, this category is assumed to be the gender (male or female) registered in the social participation information 200 (a social participation age estimation formula for males and a social participation age estimation formula for females are created, respectively), but this is not intended to limit the information that can be set as a category. The category may be, for example, the region where the user lives, their occupation, etc.

[0115] Furthermore, the social participation age estimation formula generation unit 116 in the third embodiment uses information about the category to which the target user belongs (male or female) and information about multiple items indicating the social activities performed by the target user. By inputting the information into the social participation age estimation formula corresponding to that category, the social participation age of the target user is calculated.

[0116] Next, we will describe the processes performed in the social participation support system 1 of the third embodiment. In the third embodiment, the data collection process s1 is the same as in the first embodiment. The social participation age estimation formula creation process s2 and the social participation age estimation process s3 in the second embodiment will be described below.

[0117] <Process for creating an estimated age for social participation> In the third embodiment, the social participation support device 10 creates separate social participation age estimation formulas for men and women in the social participation age estimation formula creation process s2. For example, the social participation age estimation formula creation unit 116 creates separate score formulas for men and women (formula (7))

[0118] PCSM=(w1,M×X1,M+···+wj,M×Xj,M+···+wn,M×Xn,M) / Standard deviation SDM···(7)

[0119] The function creates a formula (M: male or female). Similarly, the social participation age estimation formula generation unit 116 generates separate social participation age estimation formulas BAM (formula (8)) for men and women.

[0120] BAM = PCSM × (Standard deviation of age in the male population) + (Mean age in the male population) ... (8)

[0121] Furthermore, the social participation age estimation formula generation unit 116 calculates the correction term ZM (equation (9)) separately for men and women.

[0122] ZM = (Age - Mean age in the male population) × (1 - aM) ... (9)

[0123] Here, equations (7)-(9) cover the entire period, but by combining them with the second embodiment, they may be expressed separately for men and women and on a monthly basis. Figure 21 shows an example of a social participation age estimation equation according to the third embodiment.

[0124] Subsequently, in the social participation age estimation process s3, the social participation support device 10 receives input of the target user's gender and calculates the social participation age corresponding to that user's gender.

[0125] As described above, the social participation support device 10 of this embodiment stores, as social participation information 200, multiple social participation parameters for each user and information on each user's biological attribute values ​​(social participation age), for each category to which each user belongs (e.g., by gender). Based on this social participation information 200, it creates a social participation age estimation formula for each category, and estimates the biological attribute values ​​(age) of the target user by inputting the target user's category information (e.g., by gender) and the target user's social participation parameters into the social participation age estimation formula corresponding to that category.

[0126] It is believed that the patterns of citizens' social participation differ depending on the category to which they belong. Therefore, as in the social participation support device 10 of this embodiment, by creating a social participation age estimation formula for each user category, it is possible to calculate a social participation age that reflects the user's actual situation. In particular, since the manner of social participation is thought to differ greatly between men and women, by using separate social participation age estimation formulas for men and women, it is possible to calculate a social participation age that better reflects the user's actual situation.

[0127] [Fourth Embodiment] In the second embodiment, the social participation support device 10 created a social participation age estimation formula BAu for each aggregation period u. However, as the aggregation period increases, the social participation age estimation formula BAu occupies a large amount of resources in the social participation support device 10.

[0128] Therefore, the social participation support device 10 of the fourth embodiment consolidates the social participation age estimation formula BAu, which is created for each aggregation period, into a single formula. Here, we will explain the differences from the first and second embodiments.

[0129] Figure 22 is a diagram illustrating an example of the hardware and functions of the social participation support device 10 according to the fourth embodiment. The social participation support device 10 has the same hardware configuration as the first and second embodiments. In addition to the same data formatting unit 114, input variable setting unit 115, social participation age estimation formula creation unit 116, social participation age estimation unit 112, and actual age difference calculation unit 113 as in the first and second embodiments, the social participation support device 10 also includes a newly added correction formula creation unit 117.

[0130] Furthermore, the social participation support device 10 includes a social participation information storage unit 311, a social participation age estimation formula storage unit 312, and an estimation result storage unit 313, similar to those in the first and second embodiments, as well as a correction formula storage unit 314.

[0131] The correction formula creation unit 117 creates a first numerical model (i.e., a social participation age estimation formula created using the method of the first embodiment), which is a numerical model for a predetermined period (in this case, the period of data for social participation information 200), and a second numerical model (i.e., a social participation age estimation formula created using the method of the second embodiment), which is a numerical model for each of the multiple periods within the predetermined period.

[0132] Then, the correction formula creation unit 117 identifies the correlation between the age of social participation calculated by the first numerical model and the age of social participation for each period calculated by the second numerical model. Based on the information about the period and the information about multiple items indicating the social activities the user performed during that period, the unit creates a new numerical model (a new age of social participation estimation formula; hereinafter also referred to as the correction formula 500) that estimates the user's biological attribute values ​​during that period.

[0133] The social participation age estimation unit 112 calculates the social participation age of a specified user by inputting information about a period and information about multiple items indicating the social activities performed by the specified user during that period into a new social participation age estimation formula.

[0134] The correction formula storage unit 314 stores the above correction formula 500.

[0135] Next, we will describe the processes performed in the social participation support system of the fourth embodiment. In the fourth embodiment, the data collection process s1 is the same as in the first and second embodiments. The social participation age estimation formula creation process s2 and the social participation age estimation process s3 in the fourth embodiment will be described below. <Process for creating an estimated age for social participation> Figure 23 is a flowchart illustrating an example of the social participation age estimation formula creation process s2 according to the fourth embodiment.

[0136] The data formatting unit 114 acquires each user's social participation information 200 (basic information 210, travel information 220, and stay information 230) in the same manner as in s201 and s221 of the first and second embodiments (s241).

[0137] The data formatting unit 114, in the same manner as in s202 and s222 of the first and second embodiments, in s241 Based on the acquired social participation information 200, data (formatted data) is created by aggregating the social participation information 200 for each user over the entire period of social participation information 200 (s242).

[0138] The input variable setting unit 115 uses all social participation parameters as input variables and standardizes the data of each input variable, similar to the first and second embodiments. Then, the social participation age estimation formula creation unit 116 creates a social participation age estimation formula BA and a correction term Z related to user i's social participation age, using the same processing as in s205 to s209 of the first embodiment. Then, the social participation age estimation formula creation unit 116 calculates each user's social participation age by inputting the input variables related to each user into the social participation age estimation formula BA2 (first numerical model) based on the created social participation age estimation formula BA and correction term Z (s243). In this way, the social participation age is calculated using the first numerical model.

[0139] Furthermore, the social participation age estimation formula creation unit 116 takes all social participation parameters as input variables and, in the same processing as in s224~s230 of the second embodiment, creates a social participation age estimation formula BAu for calculating the social participation age of user i in each aggregation period u, and a correction term Zu related to the social participation age of user i. Then, the social participation age estimation formula creation unit 116 calculates the social participation age of each user in each aggregation period by inputting the input variables for each user in each aggregation period to the social participation age estimation formula BA2u (second numerical model) based on the created social participation age estimation formula BAu and correction term Zu (s243). In this way, the social participation age is calculated using the second numerical model.

[0140] Next, the correction formula creation unit 117 creates correction formula creation data for creating the correction formula 500 based on the processing results of s243 and s244 (s245).

[0141] (Data for creating correction formulas) Figure 24 shows an example of the correction formula data 2400. The correction formula data 2400 includes the following data items: each user's personal ID 2401, aggregation period (month 2402), each user's gender 2403, each user's age in each aggregation period 2404, each user's social participation age 2405 calculated by s243, and each user's social participation age 2406 calculated by s244.

[0142] Next, as shown in Figure 23, the correction formula creation unit 117 creates a correction formula (s246) based on the correction formula creation data 2400 created in s245. For example, the correction formula creation unit 117 performs a multiple regression analysis with the explanatory variables being the social participation age 2405 of each user calculated in s243, the aggregation period (dummy data), and the actual age, and the dependent variable being the social participation age 2406 of each user for each aggregation period calculated in s344. In this way, the magnitude of the influence of each factor that affects social participation age (here, the user's social participation age, the user's actual age, and each aggregation period) is calculated. For example, the correction formula creation unit 117 creates a correction formula BAH (formula (10)) for period H, as shown below.

[0143] BAH = b0 + (BA+Z)×b1 + Age×b2 + February×b3 + March×b4 + April×b5 + May×b6 + June×b7 + July×b8 + August x b9 + September x b10 + October x b11 + November x b12 + December x b13...Formula (10)

[0144] Here, (BA+Z) is the age of social participation BA from the first numerical model, 02 to 12 are dummy variables for each month, b0 is the intercept, and b1 to b13 are the regression coefficients. This completes the process s2 for creating the age of social participation estimation formula. Figure 25 shows an example of the calculated correction formula 500.

[0145] <Estimation of age for social participation> Next, Figure 26 is a flowchart illustrating an example of the social participation age estimation process s4 according to the fourth embodiment. The social participation age estimation unit 112 acquires social participation information 200 (basic information 210, movement information 220, and stay information 230) of the target user x, similar to s301 in the first embodiment (s341).

[0146] The social participation age estimation unit 112, similar to s322 in the second embodiment, creates data (user formatted data) by aggregating the movement information 220 and stay information 230 of the target user x for each predetermined aggregation period (in this case, monthly) based on the social participation information 200 acquired in s341 (s342).

[0147] The social participation age estimation unit 112 calculates the social participation age BAx,t for each aggregation period t of the target user x by inputting the user formatted data created in s342 into the first numerical model created in the social participation age estimation formula creation process s2, similar to s303 in the first embodiment (s343).

[0148] Furthermore, the social participation age estimation unit 112, similar to s304 in the first embodiment, extracts the age of the target user x for each aggregation period t from the user formatted data created in s342, and inputs each extracted age into the second model created in the social participation age estimation formula creation process s2, thereby calculating the values ​​of the correction terms Zx,t for each aggregation period of the target user x (s344).

[0149] The social participation age estimation unit 112 calculates the corrected social participation age BA2x,t by adding the correction term Zx,t calculated in s344 to the social participation age BAx,t calculated in s343, similar to s305 in the first embodiment (s345).

[0150] The social participation age estimation unit 112 then inputs the social participation ages BA2x and t calculated in s345, the period H (in this case, months) for which the social participation age of the target user x is to be calculated, and the actual age of the target user x into the correction formula 500 created in the social participation age estimation formula creation process s2, thereby calculating the social participation age BAH of the target user x for the month H (s346). The social participation age estimation unit 112 then registers the calculated social participation age BAH in the social participation age estimation result data 400. The social participation age estimation unit 112 may also calculate age differences Dx and t by subtracting the actual age of the target user x in each aggregation period t from the calculated social participation age BAH.

[0151] (Data on estimated age of social participation) Figure 27 shows an example of the estimated social participation age data 400 according to the fourth embodiment. The social participation support device 10 can create estimated social participation age data 2700 showing the same results as in the second embodiment using only the correction formula 500, without having to manage a large number of second numerical models.

[0152] As described above, the social participation support device 10 of this embodiment identifies the correlation between the social participation age calculated by a first numerical model for a predetermined period and the social participation age for each period calculated by a second numerical model for each aggregation period. Based on the aggregation period information and information on the user's multiple social participation parameters during the aggregation period, it creates a new social participation age estimation formula to estimate the attribute value (social participation age) of the target user during the aggregation period. By inputting the aggregation period information and information on the target user's multiple social participation parameters during that aggregation period into the new social participation age estimation formula, it estimates the target user's biological attribute value (age).

[0153] This allows us to represent the relationship between social participation parameters and biological attribute values ​​(age) for each aggregation period, which are represented by numerous second numerical models, as a single model (equation). This will significantly reduce the resources required to manage numerical models.

[0154] <Fifth Embodiment> Actively participating in society may improve future health. Therefore, from this perspective, the social participation support device 10 according to the fifth embodiment presents future caregiving risks based on the age of social participation calculated in the first to fourth embodiments. The differences from the first to fourth embodiments will be explained below.

[0155] Figure 28 is a diagram illustrating an example of the hardware and functions of the social participation support device 10 according to the fifth embodiment.

[0156] The social participation support device 10 includes a care risk estimation unit 118. The care risk estimation unit 118 creates a third numerical model (hereinafter referred to as the care risk estimation formula) that estimates the user's future health status (referred to here as care risk) from the user's age, based on the biological attribute values ​​(social participation age) of each user output by the social participation age estimation process s3 and the care certification result data 3150 described later. The care risk estimation unit 118 then estimates the target user's future health status (care risk) by inputting the target user's age into the care risk estimation formula.

[0157] Furthermore, the social participation support device 10 includes a care certification result storage unit 315. The care certification result storage unit 315 stores care certification result data 600, which is information that has been accumulated regarding each user's current or past health status (in this case, information regarding each user's care certification history).

[0158] Next, we will describe the processes performed in the social participation support system 1 of the fifth embodiment. Figure 29 is a flowchart illustrating an example of the social participation processing support process according to the fifth embodiment. Of the social participation processing support processes, the data collection process s1, the social participation age estimation formula creation process s2, and the social participation age estimation process s3 may be the same as in any of the first to fourth embodiments.

[0159] Next, the social participation support device 10 executes a care risk calculation process s6 to calculate the care risk of the target user based on the social participation age of each user calculated in the social participation age estimation process s3 and the care risk estimation formula.

[0160] Subsequently, the social participation support device 10 performs the same result display process s4 as in the first to fourth embodiments. At this time, the social participation support device 10 displays the care risk calculated in the care risk calculation process s6 on the screen. This completes the social participation support process.

[0161] <Calculation process for long-term care risk> Figure 30 is a flowchart illustrating the details of the caregiving risk calculation process s6. The care risk estimation unit 118 acquires the social participation age estimation result data 400 and the care certification result data 600 created in the social participation age estimation process s3 (s601). Figure 31 shows an example of the acquired social participation age estimation result data 400 and care certification result data 600.

[0162] Next, as shown in Figure 30, the care risk estimation unit 118 identifies the correlation between age of social participation and the risk of needing care, based on the data acquired in s601, thereby estimating the care risk. Prepare the formula (s602).

[0163] For example, the care risk estimation unit 118 creates a care risk estimation formula that calculates the probability of a user receiving future care based on their age at social participation by performing logistic regression analysis. In addition to logistic regression, the care risk estimation unit 118 may also calculate the care risk estimation formula using any method that estimates the correlation between the user's age at social participation and the probability (or necessity) of receiving care. Figure 32 shows an example of a care risk estimation formula.

[0164] Subsequently, the care risk estimation unit 118 receives the specified age of social participation for the target user and calculates the care risk for the target user by inputting the specified age of social participation into the care risk estimation formula (s603). This completes the care risk calculation process s6.

[0165] As described above, the social participation support device 10 of this embodiment creates a care risk estimation formula that estimates the future health status (care risk) of a user from the user's biological attribute values ​​(social participation age) based on the biological attribute values ​​(social participation age) of each user output by the social participation age estimation process s3 and the care certification result data 600 (information on the current or past care certification of each user). By inputting the biological attribute values ​​of the target user into the care risk estimation formula, the device estimates the future health status (care risk) of the target user.

[0166] In this way, by using the age at which users participate in society to estimate their future health status (risk of needing care), it is possible to encourage users to actively participate in society.

[0167] The present invention is not limited to the embodiments described above, and can be implemented using any components without departing from its spirit. The embodiments and modifications described above are merely examples, and the present invention is not limited to these as long as the features of the invention are not impaired. Furthermore, although various embodiments and modifications have been described above, the present invention is not limited to these. Other embodiments conceivable within the scope of the technical idea of ​​the present invention are also included within the scope of the present invention.

[0168] For example, some of the hardware provided by each device in each embodiment may be provided in other devices. Also, each program (functional unit) of each device may be provided in other devices, a program may consist of multiple programs, or multiple programs may be integrated into a single program.

[0169] Furthermore, in each embodiment, the conversion formulas shown in equations (1)-(9) were used as numerical models for calculating the age of social participation, but other models (equations) may also be used. For example, a trained model may be created using machine learning.

[0170] Furthermore, the items of the social participation parameters in the social participation information 200 described in each embodiment are just examples, and other arbitrary items related to social activities may be included, such as walking speed, maximum distance traveled in a day, and type of destination for outings.

[0171] Furthermore, the age of social participation as a biological attribute value described in each embodiment is just one example, and numerical models may be created to determine other attribute values ​​(such as age group).

[0172] Furthermore, while the second embodiment describes the creation of a monthly social participation age estimation formula, other periods such as seasons may also be used. Also, while the third embodiment describes the case where categories are separated by gender, other categories such as residential area or race may also be used.

[0173] Furthermore, the long-term care certification (long-term care risk) as health status information described in the fifth embodiment is just one example, and other health status information may also be used. [Explanation of Symbols]

[0174] 1 Social participation support system, 10 Social participation support device, 111 Model creation unit, 112 Social participation age estimation unit, 113 Actual age difference calculation unit

Claims

1. A storage device that stores information on multiple items, including movement information and location information, representing the social activities involving movement of multiple users during a predetermined period, and information on the age of each of the multiple users, and A model creation process that creates a numerical model to estimate the user's age from information on multiple items indicating the social activities the user has performed, based on the information on the stored items and the user's age. An attribute value estimation process that estimates the age of a specified user by inputting information on multiple items representing the social activities performed by the specified user into the numerical model, A control device that performs output processing to output the estimated age. A social participation support device equipped with the following features.

2. The control device, in the model creation process, creates a composite variable of each variable corresponding to the multiple items of the multiple users, and creates a numerical model based on the created composite variable, the mean age of the multiple users, and the standard deviation of the age of the multiple users. The social participation support device according to claim 1.

3. The storage device stores information on multiple items indicating the social activities performed by each of the multiple users during each of the multiple periods within the predetermined period, and information on the age of each of the multiple users. The control device is In the aforementioned model creation process, a numerical model is created for each of the aforementioned multiple periods that estimates the user's age from information on multiple items representing the social activities performed by the user, based on the stored item information and age information. In the attribute value estimation process described above, the age of the specified user is estimated by inputting information about a period and information about multiple items indicating the social activities performed by the specified user during that period into a numerical model corresponding to that period. The social participation support device according to claim 1.

4. The storage device stores information on multiple items indicating the social activities performed by each of the multiple users, and information on the age of each of the multiple users, categorized according to the category to which the user belongs. The control device is In the aforementioned model creation process, a numerical model is created for each category that estimates the user's age from information on multiple items representing the social activities performed by the user, based on the stored item information and age information. In the attribute value estimation process, the age of the specified user is estimated by inputting information about the category to which the specified user belongs and information about multiple items indicating the social activities performed by the specified user into a numerical model corresponding to that category. The social participation support device according to claim 1.

5. The storage device stores information on multiple items representing each of the social activities performed by multiple users, and information on the age of each of the multiple users, separately for each user's gender. The control device is In the aforementioned model creation process, based on the stored item information and age information, numerical models are created separately for males and females to estimate the user's age from information on multiple items indicating the social activities the user has performed. In the attribute value estimation process, the age of the specified user is estimated by inputting the gender information of the specified user and information on multiple items indicating the social activities performed by the specified user into a numerical model corresponding to that gender. The social participation support device according to claim 4.

6. The control device, in the model creation process, A first numerical model, which is a numerical model for the predetermined period, and a second numerical model, which is a numerical model for each of the plurality of periods, are created. By identifying the correlation between the age calculated by the first numerical model and the age for each period calculated by the second numerical model, a new numerical model is created to estimate the user's age during a given period, based on the period information and information on multiple items indicating the social activities the user performed during that period. In the attribute value estimation process, the age of the designated user is estimated by inputting information about the period and information about multiple items indicating the social activities performed by the designated user during that period into the new numerical model. The social participation support device according to claim 3.

7. The storage device stores information on the number of times each of the multiple users went out during the predetermined period, the number of places each of the multiple users went to, and the number of steps each of the multiple users took, as well as information on the age of each of the multiple users. The control device is In the aforementioned model creation process, a numerical model is created that estimates the user's age from the number of times the user has gone out, the number of places they have visited, and the number of steps taken, based on the stored number of times the user has gone out, the number of places they have visited, and the number of steps taken. In the attribute value estimation process, the age of the specified user is estimated by inputting information such as the number of times the specified user has gone out, the number of places they have visited, and the number of steps taken into the numerical model. The social participation support device according to claim 1.

8. The aforementioned storage device stores information about each user's current or past health status. The control device is Based on the age of each user output by the attribute value estimation process and the health status information, a third numerical model is created to estimate the future health status of the user from the user's age. By inputting the age of the specified user into the third numerical model, the future health status of the specified user is estimated. The social participation support device according to claim 1.

9. Information processing device, The system stores information on multiple items, including movement information and location information, representing the social activities involving movement of each of the multiple users during a predetermined period, and information on the age of each of the multiple users. Based on the stored information and age information, a numerical model is created to estimate the user's age from information on multiple items indicating the social activities the user has performed. By inputting information on multiple items representing the social activities performed by the designated user into the numerical model, the age of the designated user is estimated. Output the estimated age as described above. How to support social participation.

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