Action support system, action support method, and action support program

Abstract

It is possible to more effectively support behavior modification of a target person using a nudge based on a behavior factor.SOLUTION: An action support system according to the present invention includes a storage unit 101 that stores a plurality of messages for promoting action modification in association with a plurality of action factors, respectively, a prediction unit 102 that predicts state information indicating a state of a target person for each of the plurality of action factors on the basis of target person information on the target person, a generation unit 103 that selects one or more messages from the storage unit 101 on the basis of the state information and generates a message set including the one or more messages, and a control unit 105 that controls output of the one or more messages in the message set to the target person.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an action support system, an action support method, and an action support program. [Background technology]

[0002] In recent years, efforts to utilize approaches based on theories of behavioral science, which is the scientific study of human behavior, in service development have been expanding in various fields, including public policy, medicine, retail, and education. Systems that technically support behavioral change and habit formation for subjects in these various fields are also being considered (for example, Patent Document 1).

[0003] The system described in Patent Document 1 analyzes behavioral data containing various data measured on the behavior of multiple subjects, and based on the results of the analysis of the behavioral data, defines a stage index, which is an index used as a standard for multiple stages that gradually lead to a behavior that is a goal for habituation, and each of the multiple stages according to the stage index. For each pair of adjacent stages, it identifies the gap between the two stages that make up the pair. For each stage pair, it identifies reasons / measures that are at least one of the reason for the identified gap and measures to cause a subject belonging to the lower stage to undergo behavioral change to transition to the higher stage from relationship information that defines the relationship between the gap and the reasons / measures, and executes processing related to the identified reasons / measures for each stage pair. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2020-140596 Summary of the Invention [Problem to be solved by the invention]

[0005] In order to encourage behavioral change in individuals, the use of nudges based on the individual's behavioral factors is being considered. Behavioral factors are the factors that cause people to take action. However, there is a risk that simply using nudges based on behavioral factors may not be effective in promoting behavioral change in individuals.

[0006] Therefore, one of the objects of the present invention is to provide a behavior support system, a behavior support method, and a behavior support program that utilize nudges based on behavioral factors to more effectively support behavioral change in a subject. [Means for solving the problem]

[0007] A behavioral support system according to one aspect of the present invention includes a memory unit that stores a plurality of messages for encouraging behavioral change, each associated with a plurality of behavioral factors; a prediction unit that predicts status information indicating the subject's status for each of the plurality of behavioral factors based on subject information about the subject; a generation unit that selects one or more messages from the memory unit based on the status information and generates a message set including the one or more messages; and a control unit that controls output of the one or more messages in the message set to the subject.

[0008] According to this aspect, status information indicating the subject's state for each of multiple behavioral factors is predicted, and a message set including one or more messages selected based on the status information is generated. This makes it possible to generate a message set (i.e., an information bundle) that is optimal for changing the subject's behavior, and to promote the subject's behavioral change by utilizing nudges based on behavioral factors.

[0009] In the above aspect, the generator may select from the storage unit the one or more messages associated with one or more behavioral factors indicating that the status information is not sufficient for the behavioral change. According to this aspect, a message set (i.e., information bundle) more appropriate for the behavioral change of the subject can be generated.

[0010] In the above aspect, the control unit may control the output of the one or more messages to the subject based on at least one of: RCT information on the results of an exploratory randomized controlled trial (RCT), environmental information on the environment for the behavior change, response information on responses from the subject, and a behavior change probability predicted by the prediction unit based on the subject information. According to this aspect, the output of messages is controlled from a message set (i.e., information bundle), thereby more effectively supporting the subject's behavior change.

[0011] In the above aspect, the RCT information may indicate at least one of a ranking of the time periods for outputting the one or more messages, a ranking of the frequency, a compatibility between the subject information and / or the status information and the message set, and a ranking of the order in which the one or more messages within the message set are output.

[0012] In the above aspect, the subject information may indicate at least one of the attributes of the subject, the behavioral history of the subject, the risk in the absence of the behavioral change of the subject, and a response from the subject.

[0013] In the above aspect, the plurality of behavioral factors may include at least two of experiential attitude, instrumental attitude, indicative norm, descriptive norm, sense of behavioral control, self-efficacy, knowledge, skill, importance of behavior, environmental constraints, and habituation.

[0014] A behavior support method according to another aspect of the present invention includes the steps of: a behavior support device predicting status information indicating the subject's state for each of a plurality of behavioral factors based on subject information about the subject; a behavior support device selecting one or more messages based on the status information from a memory unit that stores a plurality of messages for encouraging behavioral change, each associated with the plurality of behavioral factors; and a behavior support device controlling output of the one or more messages in the message set to the subject.

[0015] A behavioral support program according to another aspect of the present invention causes a computer to perform the following steps: predicting status information indicating the state of the subject for each of a plurality of behavioral factors based on subject information about the subject; selecting one or more messages based on the status information from a memory unit that stores a plurality of messages associated with the plurality of behavioral factors to encourage behavioral change, and generating a message set including the one or more messages; and controlling the output of the one or more messages in the message set to the subject. [Effects of the Invention]

[0016] According to the present invention, nudges based on behavioral factors can be used to more effectively support behavioral change in subjects. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a diagram illustrating an example of a schematic configuration of a behavior support system according to an embodiment of the present invention. [Figure 2] FIG. 1 is a diagram illustrating an example of the hardware configuration of devices in a behavior support system according to an embodiment of the present invention. [Figure 3] FIG. 2 is a diagram illustrating an example of the functional configuration of devices in the action support system according to the present embodiment. [Figure 4] FIG. 10 is a diagram illustrating an example of a nudge message according to the embodiment. [Figure 5] FIG. 10 is a diagram showing an example of subject information according to the present embodiment. [Figure 6] FIG. 4 is a diagram showing an example of state information according to the embodiment; [Figure 7] FIG. 10 is a diagram illustrating an example of a nudge message set according to the present embodiment. [Figure 8] FIG. 8 is a flowchart showing an example of the operation of the action support system according to this embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0018] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described with reference to the accompanying drawings, in which the same reference numerals denote the same or similar components.

[0019] (Configuration of behavior support system) <Outline configuration> 1 is a diagram showing an example of a schematic configuration of a behavior support system according to this embodiment. As shown in FIG. 1, the behavior support system 1 includes a behavior support device 10, a behavior analysis device 20, and a terminal 30.

[0020] The behavior support device 10 is an information processing device that provides a terminal 30 with a message using a nudge based on a behavioral factor (hereinafter referred to as a "nudge message"). The behavior analysis device 20 is an information processing device that generates a nudge message that is provided to the terminal 30 by the behavior support device 10. The terminal 30 is a terminal used by a person who is a target of behavioral change, and may be any of various information devices such as a smartphone, mobile phone, tablet, or personal computer. The terminal 30 is assumed to have a function for receiving messages such as short messages and e-mails, and to be capable of using various social networking services (SNS) such as LINE (registered trademark).

[0021] In the following, factors defined by the Integrated Behavioral Model (IBM) (also referred to as "IBM factors") are used as examples of the above-mentioned behavioral factors, but the behavioral factors may be any factors related to human behavioral intentions, such as factors defined by behavioral models other than IBM.

[0022] <Hardware configuration> Fig. 2 is a diagram showing an example of the hardware configuration of devices in the behavior support system according to this embodiment. As shown in Fig. 2, each device in the behavior support system 1 (e.g., the behavior support device 10, the behavior analysis device 20, and the terminal 30) has a processor 11 such as a CPU (Central Processing Unit) that corresponds to a computing device, a storage device 12, a communication device 13, and an input / output device 14. These components are connected via a bus so that they can send and receive data to and from each other.

[0023] In this example, the behavior support device 10 and the behavior analysis device 20 are shown as separate devices, but they may also be configured as an integrated device. Multiple devices configured as an integrated device may be realized, for example, as different operations of a PLC (Programmable Logic Controller). Furthermore, at least one of the behavior support device 10, the behavior analysis device 20, and the terminal 30 may be divided into multiple devices.

[0024] The processor 11 is, for example, a CPU (Central Processing Unit), and is a control unit that controls the execution of programs stored in the storage device 12 and calculates and processes data. The processor 11 receives various input data from the input / output device 14 and / or the communication device 13, and outputs (for example, displays) the calculation results of the input data to the input / output device 14, stores the calculation results in the storage device 12, or transmits the calculation results via the communication device 13.

[0025] The storage device 12 is at least one of a memory, a hard disk drive (HDD), and a solid state drive (SSD). The storage device 12 of the action support device 10 may store the action support program executed by the processor 11. The storage device 12 may be called a "storage unit" or the like.

[0026] The communication device 13 is a device that communicates via a wired and / or wireless network, and may include, for example, a network card, a communication module, a chip, an antenna, etc. When the behavior support device 10 and the behavior analysis device 20 are configured as an integrated device, the communication device 13 may include inter-process communication between a process operating as the behavior support device 10 and a process operating as the behavior analysis device 20. The communication device 13 may be referred to as a "transmitter" or a "receiver", etc.

[0027] The input / output device 14 includes input devices such as a keyboard, a touch panel, a mouse, and / or a microphone, and output devices such as a display and / or a speaker. The input / output device may be called an "input unit" or an "output unit," etc.

[0028] The hardware configuration described above is merely an example. Each device in the action support system 1 may omit some of the hardware shown in Figure 2, or may include hardware not shown in Figure 2. Furthermore, the hardware shown in Figure 2 may be configured from one or more chips.

[0029] <Functional configuration> Fig. 3 is a diagram showing an example of the functional configuration of devices in the action support system according to this embodiment. Note that Fig. 3 is merely an example, and each device in the action support system 1 may of course have functions not shown.

[0030] ≪Behavior analysis device≫ As shown in FIG. 3 , the behavior analysis apparatus 20 includes an acquisition unit 201 and a generation unit 202. At least some of the functions realized by the acquisition unit 201 can be realized using the communication device 13. At least some of the functions realized by the acquisition unit 201 and the generation unit 202 can be realized by the processor 11 executing a program stored in the storage device 12. The program can be stored in a storage medium. The storage medium storing the program may be a non-transitory computer-readable medium. The non-transitory storage medium is not particularly limited, and may be, for example, a storage medium such as a USB memory or a CD-ROM.

[0031] The acquisition unit 201 acquires information on the process for behavioral change (hereinafter referred to as "behavioral process information"). The behavioral process information includes information indicating at least one of the following: the field in which behavioral change is encouraged, the range of intervention for the behavioral change, the success rate of behavioral change, and the failure rate of behavioral change. For example, if the field in which behavioral change is encouraged is "use of medical examinations or health checkups," the success rate of behavioral change may be the rate of people attending medical examinations or health checkups, and the failure rate of behavioral change may be the rate of people dropping out of medical examinations or health checkups. The acquisition unit 201 may acquire the behavioral process information from another device via the communication device 13, or may acquire it via the above-mentioned storage medium.

[0032] The generation unit 202 generates a plurality of nudge messages associated with a plurality of IBM factors, respectively, based on the behavioral process information acquired by the acquisition unit 201. The nudge messages are generated to encourage behavioral change for each IBM factor. For example, the generation unit 202 may generate the plurality of nudge messages using a trained machine learning model. The machine learning model is trained to output nudge messages when the behavioral process information acquired by the acquisition unit 201 is input. Such a machine learning model may be realized as a neural network and trained by supervised learning using pairs of behavioral process information and nudge messages as training data.

[0033] 4 is a diagram showing an example of a nudge message according to this embodiment. As shown in FIG. 4, a nudge message is associated with each of a plurality of IBM factors. The plurality of IBM factors may include, for example, at least two of experiential attitude, instrumental attitude, injunctive norm, descriptive norm, perceived control, self-efficacy, knowledge, skills, salience of the behavior, environmental constraints, and habit.

[0034] Note that the IBM factors shown in FIG. 4 are merely examples and are not limited to those shown. At least two IBM factors shown in FIG. 4 may be subsumed and defined as a higher-level IBM factor. For example, the experiential attitude and instrumental attitude may be subsumed under "Attitude," the indicative norm and descriptive norm may be subsumed under "Perceived Norm," the sense of behavioral control and self-efficacy may be subsumed under "Personal Agency," the knowledge and skills may be subsumed under "Knowledge," the importance of the behavior may be subsumed under "Importance," and environmental constraints may be subsumed under "Friction." Alternatively, one IBM factor shown in FIG. 4 may be divided to define multiple lower-level IBM factors. A nudge message may be associated with an IBM factor at any level.

[0035] As shown in FIG. 4, each of the multiple IBM factors may be associated with an IBM factor identifier (hereinafter referred to as an "IBM ID") and a nudge message. Note that FIG. 4 shows a nudge message assuming, for example, that the subject is a "resident of XX city" and the behavioral change is "recommended to undergo a specific health checkup (hereinafter referred to as a "specific health checkup")." The nudge message associated with each IBM factor is generated to encourage the subject to change their behavior, taking each IBM factor into consideration. Note that, although one nudge message is associated with each IBM factor in FIG. 4, multiple nudge messages may be associated with each IBM factor. Furthermore, the IBM ID identifying each IBM factor is not limited to that shown in the figure.

[0036] The nudge message generated by the generation unit 202 may be transmitted to the action support device 10 by the communication device 13. Alternatively, the nudge message may be output to the storage medium and input to the action support device 10 via the storage medium.

[0037] ≪Behavior support device≫ As shown in Fig. 3, the action support device 10 includes a storage unit 101, a prediction unit 102, a generation unit 103, an acquisition unit 104, and a transmission control unit 105. At least a part of the functions realized by the acquisition unit 104 can be realized using a communication device 13. The prediction unit 102, the generation unit 103, and the transmission control unit 105 can be realized by the processor 11 executing an action support program stored in the storage device 12. The action support program can be stored in the storage medium. The storage unit 101 can be realized using the storage device 12.

[0038] The storage unit 101 stores a plurality of nudge messages (e.g., FIG. 4) in association with a plurality of IBM factors. The plurality of nudge messages may be generated by the behavior analysis device 20, or may be input from the input / output device 14 of the behavior support device 10.

[0039] The memory unit 101 stores at least one of information about the subject (hereinafter referred to as "subject information"), information about the environment for behavioral change (hereinafter referred to as "environmental information"), and information about the results of an exploratory randomized controlled trial (RCT) (hereinafter referred to as "RCT information").

[0040] Here, the subject information stored in the memory unit 101 may include at least one of the subject's identification information, information about the subject's attributes (hereinafter referred to as "attribute information"), information about the subject's behavioral history (hereinafter referred to as "behavioral history information"), information about the risks in the event that the subject's behavior does not change (hereinafter referred to as "risk information"), and information about the subject's responses (hereinafter referred to as "response information").

[0041] Fig. 5 is a diagram showing an example of subject information according to this embodiment. For example, Fig. 5 illustrates subject information assuming that the subject is a "resident of XX city" and the behavioral change is "attending a specific health checkup (e.g., a medical checkup)."

[0042] The subject information in Figure 5 may include, as identification information of the subject, for example, information indicating the subject's ID; as attribute information of the subject, for example, information indicating the subject's age and gender; as behavioral history information, for example, information indicating the subject's history of undergoing specific health checkups; as risk information, for example, information indicating the subject's risk of contracting a specific disease (hereinafter referred to as "morbidity risk"); and as response information, for example, information indicating the subject's responses to a questionnaire (hereinafter referred to as "questionnaire responses").

[0043] Note that the subject information is not limited to that shown in Figure 5. For example, in Figure 5, the behavioral history information shows the history of specific health checkups for the most recent predetermined number of years, but any information related to the behavioral history of the subject may be used. Furthermore, the attribute information is not limited to the age and gender of the subject, and may be any information related to the subject's attributes. Furthermore, it is not necessary to include at least some of the information shown in Figure 5, or it may include information about the subject that is not shown.

[0044] Furthermore, the environmental information stored in the storage unit 101 may be, for example, information indicating the date and time of the specific health checkup, information indicating medical institutions that can receive the specific health checkup, etc., when the target is a resident of a specific administrative unit (e.g., city X) and the behavioral change is taking a specific health checkup. Furthermore, the environmental information may include information regarding the maximum number of times a nudge message can be sent to the target, information regarding rewards for behavioral change (hereinafter referred to as "reward information"), etc. For example, when the target is "a resident of a certain administrative unit" and the behavioral change is "taking a specific health checkup," the reward information may be the lifespan extension effect expected of the target, the expected amount of tax payment, etc.

[0045] The RCT information may also include information indicating at least one of the following: ranking of sending dates (e.g., weekdays, Monday to Sunday, holidays, etc.), ranking of sending times (e.g., morning, afternoon, night, etc.), ranking of sending frequencies (e.g., monthly, biweekly, monthly, etc.), compatibility between subject information and nudge message set, and sending order of nudge messages within the nudge message set.

[0046] The prediction unit 102 predicts information indicating the state of the subject for each of the plurality of IBM factors (hereinafter referred to as "state information") based on the subject information about the subject. Fig. 6 is a diagram showing an example of the state information according to this embodiment. As shown in Fig. 6, the state information may indicate whether the state of the subject is sufficient for behavioral modification for each IBM factor.

[0047] For example, the status information shown in Figure 6 indicates whether or not each subject's status is sufficient for behavioral change (e.g., undergoing a specific health checkup) for each of multiple IBM factors (here, experiential attitude, instrumental attitude, indicative norm, descriptive norm, sense of behavioral control, self-efficacy, knowledge and skills, importance of behavior, environmental constraints, and habituation). For example, the status information for the subject with subject ID "3" in Figure 6 (hereinafter referred to as "subject #3") indicates that the three IBM factors "experiential attitude," "knowledge and skills," and "environmental constraints" are insufficient for behavioral change, and indicates that the other IBM factors are sufficient for behavioral change. Note that status information indicating that the subject's status is insufficient for behavioral change may be referred to as insufficient information. Also, Figure 6 is merely an example, and some items (e.g., IMB ID, major items, medium items, etc.) may be omitted.

[0048] The prediction unit 102 may predict the above-mentioned state information based on at least one of information on a response from the subject (hereinafter referred to as "response information") acquired by the acquisition unit 104, environmental information, and RCT information, in addition to the subject information. The prediction unit 102 may also generate the above-mentioned state information using a trained machine learning model. The machine learning model is trained to output the above-mentioned state information when the subject information (and at least one of the response information, environmental information, and RCT information) is input. Such a machine learning model may be realized as a neural network and trained by supervised learning using pairs of the subject information (and at least one of the response information, environmental information, and RCT information) and state information as training data.

[0049] Furthermore, the prediction unit 102 may predict the probability of a behavioral change of the subject (hereinafter referred to as "behavioral change probability") based on the subject information about the subject. The behavioral change probability may be, for example, the probability that the subject will achieve a behavioral change without intervention for the subject's behavioral change (hereinafter referred to as "non-intervention behavior probability"). For example, the non-intervention behavior probability of subject #3 in FIG. 6 is 70%, meaning that if no intervention for behavioral change is made, there is a 70% chance that the behavioral change will be achieved. Note that the behavioral change probability is not limited to this, and may also be the probability that the subject will not achieve a behavioral change without the above intervention, the probability that the subject will achieve or not achieve a behavioral change with the above intervention, etc.

[0050] Furthermore, the prediction unit 102 may predict the above-described behavior change probability based on at least one of the response information, environmental information, and RCT information acquired by the acquisition unit 104 in addition to the subject information. Furthermore, the prediction unit 102 may generate the above-described behavior change probability using a trained machine learning model. The machine learning model is trained to output the above-described behavior change probability when the subject information (and at least one of the response information, environmental information, and RCT information) is input. Such a machine learning model may be realized as a neural network and trained by supervised learning using pairs of the subject information (and at least one of the response information, environmental information, and RCT information) and the behavior change probability as training data.

[0051] The generation unit 103 selects a set including one or more nudge messages to be delivered to the target person (hereinafter referred to as a "nudge message set") from the storage unit 203 based on the state information predicted by the prediction unit 102. Specifically, the generation unit 103 generates a nudge message set including at least a nudge message associated with an IBM factor indicating that the state information is insufficient for behavioral modification.

[0052] FIG. 7 is a diagram showing an example of a nudge message set according to this embodiment. As shown in FIG. 7, the nudge message set for subject #3 includes nudge messages #1 to #4. Nudge messages #2 to #4 are associated with three IBM factors, "experiential attitude," "knowledge and skills," and "environmental constraints," respectively, that are indicated by the status information of subject #3 as being insufficient for behavioral change. On the other hand, nudge message #1 is not associated with these IBM factors. In this way, the nudge message set may include not only nudge messages associated with IBM factors that indicate that the status information is insufficient for behavioral change, but also other nudge messages.

[0053] The acquisition unit 104 acquires response information from the subject. Here, the response information is, for example, information indicating a response from the subject who viewed the nudge message, and may be information such as whether or not a short message (SM) or email containing the nudge message was viewed, a status regarding behavioral change (e.g., reservation status for a specific health checkup), or a result of behavioral change (e.g., results of the specific health checkup). The acquisition unit 104 may acquire the response information from the subject's terminal 30 in real time.

[0054] The transmission control unit 105 controls the transmission to the subject of one or more nudge messages in the nudge message set selected by the generation unit 103. Under the control of the transmission control unit 105, the communication device 13 of the action support device 10 transmits the nudge message to the terminal 30 of the subject.

[0055] Specifically, the transmission control unit 105 controls the transmission of the one or more nudge messages to the target person based on at least one of the RCT information, environmental information stored in the storage unit 101, and response information acquired by the acquisition unit 104. Here, the control of the transmission of the nudge messages may include, for example, control of the order in which multiple nudge messages in a nudge message set are sent, the date of sending each nudge message, the time period in which each nudge message is sent, the time interval (transmission frequency) for sending the multiple nudge messages, stopping the sending of each nudge message, the number of times each nudge message is sent, etc.

[0056] For example, in the case of the nudge message set for target person #3 shown in Figure 7, the transmission control unit 105 determines to send nudge messages to target person #3 in the order of nudge messages #1, #2, #3, and #4 based on at least one of the RCT information, environmental information, and response information. In addition, the transmission control unit 105 determines at least one of the sending date, sending time zone, sending interval, sending suspension, and number of sending times of nudge messages #1 to #4 based on at least one of the RCT information, environmental information, and response information.

[0057] For example, if the acquisition unit 104 acquires positive response information for behavioral change after transmitting each of the nudge messages #1 to #3 in Fig. 7, the transmission control unit 105 may cancel the transmission of the subsequent nudge message. On the other hand, if negative response information is acquired in response to a nudge message, the transmission control unit 105 may resend the nudge message or may send the subsequent nudge message.

[0058] In this way, instead of sending the nudge message set for subject #3 all at once, multiple nudge messages included in the nudge message set can be sent to subject #3 in multiple separate transmissions. Even if a single nudge message contains a lot of information, humans may overlook it, so it can be said that multiple nudge messages are more effective at promoting behavioral change. Therefore, by sending nudge messages in multiple transmissions, it is possible to increase the effectiveness of promoting behavioral change for subjects who are not likely to change their behavior with a single nudge message.

[0059] Furthermore, the transmission control unit 105 may transmit a subsequent nudge message that has been updated based on the response information acquired by the acquisition unit 104. Specifically, the prediction unit 102 may update the status information based on the response information, and the generation unit 103 may update the nudge message set based on the updated status information. Furthermore, by updating the nudge message to be sent to the subject based on the response information of the subject, it is possible to send a nudge message that is more effective in promoting behavioral change in the subject.

[0060] Furthermore, the transmission control unit 105 may control the transmission of one or more nudge messages in the nudge message set generated by the generation unit 103, based on the behavior change probability predicted by the prediction unit 102. For example, the transmission control unit 105 may increase the number of times each nudge message is transmitted or increase the transmission frequency for a subject whose non-intervention behavior probability satisfies a predetermined condition (e.g., equal to or less than a predetermined threshold). On the other hand, the transmission control unit 105 may decrease the number of times each nudge message is transmitted or decrease the transmission frequency for a subject whose non-intervention behavior probability satisfies a predetermined condition (e.g., greater than or equal to a predetermined threshold).

[0061] Furthermore, the transmission control unit 105 may control the transmission of one or more nudge messages in the nudge message set generated by the generation unit 103 based on information that changes due to various factors (hereinafter referred to as "change information"). For example, the change information may be, for example, the stock availability of a particular vaccine, the availability of appointments for health checkups or medical examinations, available time, etc. Furthermore, the transmission control unit 105 may control the transmission of one or more nudge messages in the nudge message set generated by the generation unit 103 based on information regarding the subject's convenience (for example, whether or not the time and / or location is convenient for the subject, etc.).

[0062] The transmission control by the transmission control unit 105 as described above may be implemented by solving a resource allocation problem. For example, the resource allocation problem may be initially set using at least one of the state information and behavior change probability predicted by the prediction unit 102, the environmental information stored in the storage unit 101, and the nudge message set generated by the generation unit 103. Furthermore, the transmission control unit 105 may implement the transmission control by solving the resource allocation problem using all nudge messages and all target persons stored in the storage unit 101 as the environment, all the nudge messages as a solution space, the maximum number of times that nudge messages are transmitted to each target person as a budget, and the total sum of rewards obtained during a target period as a cumulative reward.

[0063] (Behavioral support system operation) Fig. 8 is a flowchart showing an example of the operation of the action support system according to this embodiment. Note that the operation of the action support system shown in Fig. 8 is merely an example and is not limited to what is shown in the figure.

[0064] As shown in Fig. 8, in step S101, the action support apparatus 10 predicts the subject's state information (e.g., Fig. 6) based on the subject information. The action support apparatus 10 may also predict a behavior change probability (e.g., a non-intervention behavior probability) based on the subject information. The action support apparatus 10 may also predict or update the state information and / or the behavior change probability based on at least one of response information, environmental information, and RCT information in response to the nudge message transmitted by the transmission control in step S103.

[0065] In step S102, the action support apparatus 10 generates a nudge message set (for example, FIG. 7) for the subject based on the state information predicted in step S101.

[0066] In step S103, the action support device 10 controls the transmission of one or more nudge messages in the nudge message set generated in step S102. The action support device 10 may control the transmission of the one or more nudge messages based on at least one of response information, environmental information, and RCT information in response to a previously transmitted nudge message.

[0067] The behavior support system 1 according to this embodiment can more effectively support a subject's behavioral change by utilizing nudges based on behavioral factors. More specifically, the behavior support system 1 predicts state information indicating the subject's state for each of a plurality of IBM factors, and generates a nudge message set including one or more nudge messages selected based on the state information. This makes it possible to generate a nudge message set (i.e., information bundle) optimal for the subject's behavioral change.

[0068] Furthermore, in the behavior support system 1, instead of sending a nudge message set such as that shown in Fig. 7 to the subject all at once, multiple nudge messages in the nudge message set are sent to the subject multiple times, thereby enhancing the effect of promoting behavioral change in the subject. Furthermore, by controlling the sending of subsequent nudge messages and / or updating their contents based on response information to the nudge messages, behavioral change in the subject can be more effectively supported.

[0069] The above-described embodiments are intended to facilitate understanding of the present invention and are not intended to limit the present invention. The elements of the embodiments, as well as their arrangement, materials, conditions, shapes, sizes, etc., are not limited to those illustrated and can be modified as appropriate. Furthermore, configurations shown in different embodiments can be partially substituted or combined with each other.

[0070] For example, in the above embodiment, the subject is assumed to be a "resident of XX city" and the behavioral change is assumed to be "attending a specific health checkup (e.g., a medical examination)," but this is not limited to this. The subject is not limited to users of government services, but may also be users of various services such as English conversation classes or qualification exams. Furthermore, the behavioral change is not limited to the use of government services, but may also be continued learning, use of various services, etc.

[0071] Furthermore, in the above embodiment, the transmission of one or more messages to subjects is controlled based on RCT information related to the results of an exploratory randomized controlled trial (RCT). However, the causal inference method used to control the transmission of messages is not limited to an exploratory RCT. Other methods, such as propensity score matching, may also be used as the causal inference method. Note that an exploratory RCT may also be considered a trial and / or small-scale RCT, and may be any type of pilot for setting parameters used to control the transmission of the messages.

[0072] Furthermore, the nudge message in the above embodiment is not limited to a text format including character strings and symbols, but may be predetermined information including audio, video, images, or the like. Furthermore, in the above embodiment, the transmission control unit 105 of the action support device 10 controls the transmission of the nudge message, but this is not limited thereto, and the action support device 10 may be provided with a control unit that controls the output of the nudge message (including, for example, not only transmission but also display, audio output, etc.). That is, the "transmission" of the nudge message in the above embodiment may be rephrased as display, audio output, output, etc. Furthermore, the terminal 30 is not limited to a terminal used by a specific target person, but may be a signage, electronic bulletin board, speaker, etc. that outputs information for an unspecified target person.

[0073] For example, in a situation where the population density in a specific space (inside a train station or a restaurant) exceeds a certain level and the probability of non-intervention behavior is high, the action support device 10 may transmit a nudge message to "disperse people" to a terminal 30 (for example, a signage, electronic bulletin board, or speaker, etc.) and output (for example, display, audio output, etc.) from the terminal 30. Furthermore, the action support device 10 and the terminal 30 that outputs the nudge message to the subject may be provided as an integrated device, and the action support device 10 sending the nudge message to the terminal 30 may be internal communication within the integrated device. [Explanation of symbols]

[0074] 1...Behavior support system, 10...Behavior support device, 20...Behavior analysis device, 30...Terminal, 11...Processor, 12...Storage device, 13...Communication device, 14...Input / output device, 101...Storage unit, 102...Prediction unit, 103...Generation unit, 104...Acquisition unit, 105...Transmission control unit, 201...Acquisition unit, 202...Generation unit, 203...Storage unit

Claims

1. a storage unit that stores a plurality of messages for encouraging behavioral change, each of the messages being associated with a plurality of behavioral factors; a prediction unit that predicts state information indicating a state of the subject for each of the plurality of behavioral factors based on subject information about the subject; a generation unit that selects one or more messages from the storage unit based on the state information and generates a message set including the one or more messages; a control unit that controls output of the one or more messages in the message set to the target person; A behavioral support system comprising:

2. the generation unit selects, from the storage unit, the one or more messages each associated with one or more behavioral factors indicating that the status information is not sufficient for the behavioral modification; The behavior support system according to claim 1 .

3. The control unit controls the output of the one or more messages to the subject based on at least one of: RCT information on the results of an exploratory randomized controlled trial (RCT); environmental information on the environment for the behavior change; response information on a response from the subject; and a behavior change probability predicted by the prediction unit based on the subject information. The behavior support system according to claim 1 or 2.

4. The RCT information indicates at least one of a ranking of time periods for outputting the one or more messages, a ranking of frequency, a compatibility between the subject information and / or the status information and the message set, and a ranking of an output order of the one or more messages in the message set. The behavior support system according to claim 3 .

5. The subject information indicates at least one of the subject's attributes, the subject's behavioral history, the risk in the absence of the subject's behavioral change, and a response from the subject. The behavior support system according to any one of claims 1 to 4.

6. The plurality of behavioral factors include at least two of experiential attitudes, instrumental attitudes, indicative norms, descriptive norms, sense of behavioral control, self-efficacy, knowledge, skills, importance of behavior, environmental constraints, and habituation. The behavior support system according to any one of claims 1 to 5.

7. a step in which the behavior support device predicts state information indicating a state of the subject for each of a plurality of behavioral factors based on subject information about the subject; a step in which the behavior support device selects one or more messages based on the state information from a storage unit that stores a plurality of messages for encouraging behavioral change in association with the plurality of behavioral factors, and generates a message set including the one or more messages; a step of controlling output of the one or more messages in the message set to the subject by the behavior support device; A behavioral support method having the above.

8. On the computer, predicting state information indicating a state of the subject for each of a plurality of behavioral factors based on subject information about the subject; a step of selecting one or more messages based on the state information from a storage unit that stores a plurality of messages for encouraging behavioral change in association with the plurality of behavioral factors, and generating a message set including the one or more messages; controlling output of the one or more messages in the message set to the target person; A behavioral support program to help people achieve this.

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