Behavior support system, behavior support method, and behavior support program

Abstract

To effectively support behavioral change of a subject using nudge based on a behavioral factor.SOLUTION: A behavior support system includes: a storage unit 101 which stores a plurality of messages for urging behavioral change, in association with a plurality of behavioral factors, respectively; a prediction unit 102 which predicts state information indicating a state of a subject for each of the behavioral factors, based on subject information on the subject; a generation unit 103 which selects one or more messages based on the state information from the storage unit 101, and generates a message set including the one or more messages; and a control unit 105 which controls outputting the one or more messages in the message set to the subject.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 are spreading in various fields such as public policy, medicine, retail, education, etc. Systems that technically realize support for behavioral change and habit formation of 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 including 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 that serves as a standard for multiple stages that gradually lead to a behavior that is a goal of habit formation, and each of the multiple stages according to the stage index, identifies a gap between the two stages that make up each pair of adjacent stages, and for each stage pair, identifies a reason / measure that is at least one of the reason for the existence of the identified gap and a measure to cause a subject belonging to the lower stage to change his / her behavior to transition to the higher stage from relationship information that defines the relationship between the gap and the reason / measure, and executes processing related to the reason / measure identified for each stage pair. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-140596 A Summary of the Invention [Problem to be solved by the invention]

[0005] In order to promote behavioral change in subjects, the use of nudges based on the subjects' behavioral factors is being considered. Behavioral factors are factors that cause people to take action. However, there is a risk that simply using nudges based on behavioral factors will not effectively promote behavioral change in subjects.

[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 behavior support system according to one embodiment of the present invention includes a memory unit that stores a plurality of messages for encouraging behavioral change, each corresponding to 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 a number of 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., information bundle) that is optimal for changing the subject's behavior, and to promote behavioral change in the subject by utilizing nudges based on the 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 state information is not sufficient for the behavioral change. According to this aspect, a message set (i.e., an 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 from a message set (i.e., information bundle) is controlled, so that the subject's behavior change can be more effectively supported.

[0011] In the above aspect, the RCT information may indicate 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 the order in which the one or more messages are output within the message set.

[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 attitudes, instrumental attitudes, indicative norms, descriptive norms, sense of behavioral control, self-efficacy, knowledge, skills, importance of behavior, environmental constraints, and habituation.

[0014] A behavior support method according to another aspect of the present invention includes a step 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 regarding the subject; a step of the 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 in correspondence with each of the plurality of behavioral factors, and generating a message set including the one or more messages; and a step of the 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 steps of predicting status information indicating the subject's state 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 for encouraging behavioral change, each associated with the plurality of behavioral factors; 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. Effect of the Invention

[0016] According to the present invention, it is possible to more effectively support a subject's behavioral change by utilizing a nudge based on behavioral factors. [Brief description 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. [Diagram 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of an apparatus in the action support system according to the present embodiment. [Diagram 3] FIG. 2 is a diagram illustrating an example of the functional configuration of an apparatus in the action support system according to the present embodiment. [Figure 4] FIG. 13 is a diagram illustrating an example of a nudge message according to the embodiment. [Diagram 5] FIG. 11 is a diagram showing an example of subject information according to the embodiment; [Figure 6] FIG. 4 is a diagram showing an example of state information according to the embodiment; [Figure 7] FIG. 2 is a diagram illustrating an example of a nudge message set according to the 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 PREFERRED EMBODIMENTS

[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 configurations.

[0019] (Configuration of the behavior support system) <Outline configuration> 1 is a diagram showing an example of a schematic configuration of a behavior support system according to the present 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 message using a nudge based on a behavioral factor (hereinafter referred to as a "nudge message") to the terminal 30. The behavior analysis device 20 is an information processing device that generates a nudge message provided to the terminal 30 by the behavior support device 10. The terminal 30 is a terminal used by a subject of behavioral change, and may be, for example, any of various information devices such as a smartphone, a mobile phone, a tablet, or a personal computer. The terminal 30 is assumed to have a function for receiving messages such as short messages and e-mails, and to have access to various social network services (SNS) such as LINE (registered trademark).

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

[0022] <Hardware configuration> Fig. 2 is a diagram showing an example of the hardware configuration of devices in the action support system according to this embodiment. As shown in Fig. 2, each device in the action support system 1 (for example, each of the action support device 10, the action analysis device 20, and the terminal 30) has a processor 11 such as a CPU (Central Processing Unit) equivalent to a computing device, a storage device 12, a communication device 13, and an input / output device 14. Each of these components is connected via a bus so as to be able to transmit 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 be configured as an integrated device. A plurality of devices configured as an integrated device may be realized as different operations of a PLC (Programmable Logic Controller), for example. At least one of the behavior support device 10, the behavior analysis device 20, and the terminal 30 may be divided into a plurality of 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 results of calculations on the input data to the input / output device 14, stores the results in the storage device 12, or transmits the 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 called a "transmitter" or a "receiver", etc.

[0027] The input / output device 14 includes, for example, 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 Fig. 2, or may include hardware not shown in Fig. 2. Furthermore, the hardware shown in Fig. 2 may be configured with 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 a function not shown.

[0030] ≪Behavior analysis device≫ As shown in FIG. 3, the behavior analysis device 20 includes an acquisition unit 201 and a generation unit 202. At least a part of the functions realized by the acquisition unit 201 can be realized using the communication device 13. At least a part 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 acquiring 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 attendance rate of medical examinations or health checkups, and the failure rate of behavioral change may be the dropout rate of medical examinations or health checkups. The acquiring unit 201 may acquire the behavioral process information from another device via the communication device 13, or via the above-mentioned storage medium.

[0032] The generating unit 202 generates a plurality of nudge messages respectively associated with a plurality of IBM factors based on the behavioral process information acquired by the acquiring unit 201. The nudge message is generated so as to encourage behavioral change for each IBM factor. For example, the generating unit 202 may generate the plurality of nudge messages using a trained machine learning model. The machine learning model is trained to output a nudge message when the behavioral process information acquired by the acquiring 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] Fig. 4 is a diagram showing an example of a nudge message according to the present 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 at least two of, for example, an experiential attitude, an instrumental attitude, an injunctive norm, a descriptive norm, a perceived control, a self-efficacy, knowledge, skills, salience of the behavior, environmental constraints, and habit.

[0034] Note that each IBM factor shown in FIG. 4 is merely an example and is not limited to those shown in the figure. At least two IBM factors shown in FIG. 4 may be included and defined as a higher level IBM factor. For example, the experiential attitude and the instrumental attitude may be included in "Attitude", the directive norm and the descriptive norm may be included in "Perceived norm", the sense of behavioral control and self-efficacy may be included in "Personal Agency", the knowledge and skills may be included in "Knowledge", the importance of the behavior may be included in "Importance", and the environmental constraints may be included in "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 any level of IBM factor.

[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 so as to encourage the subject's behavioral change in consideration of each IBM factor. 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. Also, 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, respectively. 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 regarding the subject (hereinafter referred to as "subject information"), information regarding the environment for behavioral change (hereinafter referred to as "environmental information"), and information regarding the results of an exploratory randomized controlled trial (RCT) (hereinafter referred to as "RCT information").

[0040] Here, the subject information stored in memory unit 101 may include at least one of the subject's identification information, information regarding the subject's attributes (hereinafter referred to as "attribute information"), information regarding the subject's behavioral history (hereinafter referred to as "behavioral history information"), information regarding the risks in the event that there is no change in the subject's behavior (hereinafter referred to as "risk information"), and information regarding the response from the subject (hereinafter referred to as "response information").

[0041] Fig. 5 is a diagram showing an example of subject information according to the present 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., medical examination)."

[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 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] The subject information is not limited to that shown in Fig. 5. For example, in Fig. 5, the behavior history information shows the history of specific health checkups for a certain number of years in the most recent period, but any information related to the behavior history of the subject may be used. In addition, the attribute information is not limited to the age and sex of the subject, and may be any information related to the attributes of the subject. In addition, it is not necessary to include at least some of the information shown in Fig. 5, and it may include information not shown related to the subject.

[0044] Furthermore, the environmental information stored in the memory unit 101 may be, for example, information indicating the date and time of the specific health check, information indicating medical institutions that can receive the specific health check, etc., when the subjects are residents of a specific administrative unit (e.g., XX city) and the behavioral change is taking a specific health check. Furthermore, the environmental information may include the maximum number of times a nudge message is sent to the subjects, information regarding rewards for behavioral change (hereinafter referred to as "reward information"), etc. For example, when the subjects are "residents of a certain administrative unit" and the behavioral change is "taking a specific health check," the reward information may be the life extension effect expected of the subjects, the expected amount of tax paid, 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 the subject information and the nudge message set, and the sending order of nudge messages in 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 on 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 FIG. 6 indicates whether or not the status of each subject is sufficient for behavioral change (e.g., undergoing a specific health check) for each of a number of 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 of the subject with subject ID "3" in FIG. 6 (hereinafter referred to as "subject #3") indicates that the three IBM factors "experiential attitude," "knowledge and skills," and "environmental constraints" are not sufficient 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 not sufficient for behavioral change may be referred to as insufficient information. Also, FIG. 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 acquired by the acquisition unit 104 (hereinafter referred to as "response information"), environmental information, and RCT information in addition to the subject information. The prediction unit 102 may 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 behavior change of the subject (hereinafter referred to as "behavior change probability") based on the subject information on the subject. The behavior change probability may be, for example, the probability that the subject achieves a behavior change without intervention for the subject's behavior change (hereinafter referred to as "non-intervention behavior probability"). For example, the non-intervention behavior probability of subject #3 in FIG. 6 is 70%, and if no intervention for behavior change is made, there is a 70% probability that behavior change will be achieved. Note that the behavior change probability is not limited to this, and may be the probability that the subject will not achieve a behavior change without the above intervention, the probability that the subject will achieve or not achieve a behavior change with the above intervention, etc.

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

[0051] The generating unit 103 selects a set including one or more nudge messages (hereinafter referred to as a "nudge message set") that are candidates for delivery to the target person from the storage unit 203 based on the state information predicted by the predicting unit 102. Specifically, the generating unit 103 generates a nudge message set that includes at least a nudge message associated with an IBM factor that indicates 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 the present embodiment. As shown in FIG. 7, the nudge message set for subject #3 includes nudge messages #1 to #4. The nudge messages #2 to #4 are respectively associated with the three IBM factors "experiential attitude," "knowledge and skills," and "environmental constraints" that are indicated to be insufficient for behavioral change by the state information of subject #3. On the other hand, the nudge message #1 is not associated with the IBM factor. In this way, the nudge message set may include not only the nudge message associated with the IBM factor indicating that the state 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 whether or not a short message (SM) or email containing the nudge message was viewed, a situation regarding behavioral change (for example, a reservation status for a specific health checkup), a result of behavioral change (for example, a result of taking the specific health checkup), etc. 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, the environmental information stored in the storage unit 101, and the response information acquired by the acquisition unit 104. Here, the control of the transmission of the nudge message may include, for example, control of the order of transmission of multiple nudge messages in the nudge message set, the transmission date of each nudge message, the transmission time period of each nudge message, the time interval (transmission frequency) for transmitting the multiple nudge messages, the suspension of transmission of each nudge message, the number of times each nudge message is transmitted, and the like.

[0056] For example, in the case of the nudge message set for subject #3 shown in Fig. 7, the transmission control unit 105 determines to transmit nudge messages to subject #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 transmission date, transmission time zone, transmission interval, transmission suspension, and transmission count of nudge messages #1 to #4 based on at least one of the RCT information, environmental information, and response information.

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

[0058] In this way, instead of sending the nudge message set for subject #3 all at once, multiple nudge messages contained in the nudge message set can be sent to subject #3 in a distributed manner multiple times. 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 multiple nudge messages in a distributed manner, it is possible to increase the promotion effect of 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 updated based on the response information acquired by the acquisition unit 104. Specifically, the prediction unit 102 may update the state information based on the response information, and the generation unit 103 may update the nudge message set based on the updated state information. Furthermore, by updating a nudge message to be sent to a subject based on the response information of the subject, a nudge message that is more effective in promoting behavioral change of the subject can be sent.

[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, etc.). 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, etc.).

[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 arrival status of a specific vaccine, 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 place 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. The transmission control unit 105 may also implement the above-mentioned transmission control by solving the resource allocation problem with all nudge messages and all subjects stored in the storage unit 101 as the environment, all the nudge messages as the solution space, the maximum number of times the nudge messages are transmitted to each subject as the budget, and the sum of rewards obtained during the target period as the accumulated reward.

[0063] (Behavioral Support System Operation) Fig. 8 is a flow chart 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 the one shown in the figure.

[0064] As shown in Fig. 8, in step S101, the action support apparatus 10 predicts state information of the subject (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 (eg, 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 for a previously transmitted nudge message.

[0067] According to the behavior support system 1 of this embodiment, it is possible to more effectively support the behavior change of a subject by using nudges based on behavioral factors. More specifically, in the behavior support system 1, state information indicating the state of the subject for each of a plurality of IBM factors is predicted, and a nudge message set including one or more nudge messages selected based on the state information is generated. Therefore, it is possible to generate a nudge message set (i.e., information bundle) optimal for the behavior change of the subject.

[0068] Moreover, in the above-mentioned behavior support system 1, instead of transmitting a nudge message set as exemplified in Fig. 7 to the subject all at once, multiple nudge messages in the nudge message set are distributed and transmitted to the subject multiple times, thereby enhancing the effect of promoting behavioral change in the subject. Also, by controlling the transmission of subsequent nudge messages and / or updating the contents based on response information to the nudge messages, it is possible to more effectively support the behavioral change of the subject.

[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 arrangements, materials, conditions, shapes, sizes, etc., are not limited to those illustrated, and can be changed as appropriate. In addition, 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., medical examination)", but this is not limited to this. The subject is not limited to users of government services, but may be users of various services such as English conversation or qualification exams. Furthermore, the behavioral change is not limited to the use of government services, but may be continued learning, use of various services, etc.

[0071] 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), but the causal inference method used to control the transmission of messages is not limited to the exploratory RCT. As the causal inference method, other methods such as propensity score matching may be used. Note that the exploratory RCT may be called a trial and / or small-scale RCT, and may be any type of pilot for setting parameters used to control the transmission of the message.

[0072] Furthermore, the nudge message in the above embodiment is not limited to a text format including character strings and symbols, and 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, and may be a signage, electronic bulletin board, speaker, etc. that outputs information for unspecified targets.

[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 (e.g., a signage, electronic bulletin board, or speaker, etc.) and output (e.g., 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 transmitting 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 in association with a plurality of behavioral factors; a prediction unit that predicts state information indicating a state of the subject with respect to each of the plurality of behavioral factors based on subject information regarding 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 for controlling 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 state 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 attributes of the subject, the behavioral history of the subject, the risk of the subject not changing his / her behavior, 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, directive 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 of predicting, by the action support device, state information indicating a state of the subject for each of a plurality of behavioral factors based on subject information regarding the subject; a step of the behavior support device 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; The action support device controls output of the one or more messages in the message set to the subject; A behavioral support method having the above-mentioned features.

8. On the computer, predicting state information indicating a state of the subject with respect to each of a plurality of behavioral factors based on subject information regarding the subject; 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 subject; A behavioral support program to help people achieve these goals.

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