JP2022163957A - Behavior support system, behavior support method, and behavior support program - Google Patents

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

The present invention relates to an action support system, an action support method, and an action support program.

In recent years, efforts to utilize approaches based on the theory of behavioral science, which is a scientific study of human behavior, in service development have spread in various fields such as public policy, medical care, retail, and education. Also, a system that technically realizes support for behavioral change and habituation of subjects in the various fields is being studied (for example, Patent Literature 1).

In the system described in Patent Document 1, behavior data including various data measured on the behavior of a plurality of subjects is analyzed, and based on the results of the analysis of the behavior data, the behavior as the goal of habituation is stepped. defining a stage index, which is an index as a reference for a plurality of stages toward a target, and each of the plurality of stages according to the stage index; Identifying gaps, for each stage pair, why the identified gaps exist, and actions to induce behavioral change in subjects belonging to the lower stages to transition to the higher stages. It is described that at least one reason/measure is specified from the relational information defining the relationship between the gap and the reason/measure, and the process related to the specified reason/measure is executed for each stage pair.

Japanese Patent Application Laid-Open No. 2020-140596

By the way, in order to encourage behavioral change of the subject, the use of nudges based on behavioral factors of the subject is under consideration. A behavioral factor is a factor that causes a person to act. However, it may not be possible to effectively promote the behavioral change of the subject only by using nudges based on behavioral factors.

Accordingly, one object of the present invention is to provide an action support system, an action support method, and an action support program that more effectively support behavioral change of a subject using nudges based on behavioral factors.

A behavior support system according to an aspect of the present invention includes a storage unit that stores a plurality of messages for prompting behavior modification in association with a plurality of behavior factors, respectively; a predicting unit that predicts state information indicating the state of the subject for each of the behavioral factors; one or more messages selected from the storage unit based on the state information; and a message set containing the one or more messages a generator for generating; and a controller for controlling output of the one or more messages in the message set to the target person.

According to this aspect, the state information indicating the state of the subject for each of the plurality of behavior factors is predicted, and the message set including one or more messages selected based on the state information is generated. It is possible to generate a message set (ie, information bundle) that is optimal for behavior modification of , and use nudges based on behavioral factors to promote behavior modification of the subject.

In the above aspect, the generation unit may select from the storage unit the one or more messages respectively associated with one or more behavior factors indicating that the state information is not sufficient for the behavior modification. . According to this aspect, it is possible to generate an appropriate message set (that is, information bundle) by subject's behavior modification.

In the above aspect, the control unit includes RCT information about the results of an exploratory randomized controlled trial (RCT), environmental information about the environment for behavior modification, response information about the response from the subject, and the prediction The output of the one or more messages to the target person may be controlled based on at least one behavior change probability predicted by the unit based on the target person information. According to this aspect, since the output of the message is controlled from among the message set (that is, information bundle), it is possible to more effectively support the subject's behavior modification.

In the above aspect, the RCT information includes ranking of the time period for outputting the one or more messages, ranking of frequency, compatibility between the target person information and/or the status information and the message set, within the message set and a ranking of the output order of the one or more messages.

In the above aspect, the subject information indicates at least one of the attributes of the subject, the behavior history of the subject, the risk when the subject does not change the behavior, and the response from the subject. may

In the above aspect, the plurality of behavioral factors are empirical attitudes, instrumental attitudes, directive norms, descriptive norms, sense of control over behavior, self-efficacy, knowledge, skills, importance of behavior, environmental constraints, habits may include at least two of the

An action support method according to another aspect of the present invention is a step of predicting, by an action support device, state information indicating the state of the subject for each of a plurality of behavior factors based on subject information about the subject; The action support device selects one or more messages based on the state information from a storage unit that stores a plurality of messages for prompting behavioral change in association with the plurality of behavior factors, and selects the one or more messages generating a message set containing messages; and controlling, by the action support device, output of the one or more messages in the message set to the subject.

An action support program according to another aspect of the present invention provides a computer with a step of predicting state information indicating the state of the subject for each of a plurality of behavior factors based on subject information about the subject; selects one or more messages based on the state information from a storage unit that stores a plurality of messages for promoting behavioral change associated with each of the behavior factors, and generates a message set containing the one or more messages and controlling the output of the one or more messages in the message set to the subject.

ADVANTAGE OF THE INVENTION According to this invention, a subject's behavioral change can be assisted more effectively using the nudge based on a behavioral factor.

It is a figure showing an example of the schematic structure of the action support system concerning this embodiment. It is a figure which shows an example of the hardware constitutions of the apparatus in the action assistance system which concerns on this embodiment. It is a figure which shows an example of the functional structure of the apparatus in the action support system which concerns on this embodiment. It is a figure which shows an example of the nudge message which concerns on this embodiment. It is a figure which shows an example of the target person information which concerns on this embodiment. It is a figure which shows an example of the state information which concerns on this embodiment. It is a figure which shows an example of the nudge message set which concerns on this embodiment. FIG. 8 is a flow chart showing an example of the operation of the action support system according to this embodiment.

Embodiments of the present invention will be described with reference to the accompanying drawings. It should be noted that, in each figure, the same reference numerals have the same or similar configurations.

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

The action support device 10 is an information processing device that provides the terminal 30 with messages using nudges based on action factors (hereinafter referred to as “nudge messages”). 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 person targeted for behavior modification, and may be, for example, various information devices such as a smart phone, a mobile phone, a tablet, and a personal computer. It is assumed that the terminal 30 is capable of receiving messages such as short messages and e-mails, and various social network services (SNS) such as LINE (registered trademark).

Below, as the behavioral factors, the factors defined by the Integrated Behavioral Model (IBM) (also called "IBM factors" etc.) will be exemplified, but the behavioral factors are the factors defined by behavioral models other than IBM. It may be any factor related to human action will.

<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) includes a processor 11 such as a CPU (Central Processing Unit) corresponding to an arithmetic device. , a storage device 12 , a communication device 13 , and an input/output device 14 . These components are connected to each other via a bus so that data can be sent and received.

Although the action support device 10 and the action analysis device 20 are shown as separate devices in this example, they may be configured as an integrated device. A plurality of devices configured as an integrated device may be implemented as different operations of a PLC (Programmable Logic Controller), for example. At least one of the action support device 10, the action analysis device 20, and the terminal 30 may be divided into a plurality of devices.

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 performs calculation and processing of data. The processor 11 receives various input data from the input/output device 14 and/or the communication device 13, outputs (for example, displays) the calculation results of the input data to the input/output device 14, stores them in the storage device 12, Alternatively, it may be transmitted via the communication device 13 .

The storage device 12 is at least one of memory, HDD (Hard Disk Drive), and SSD (Solid State Drive). 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.

The communication device 13 is a device that communicates via a wired and/or wireless network, and may include, for example, network cards, communication modules, chips, antennas, and the like. When the action support device 10 and the action analysis device 20 are configured as an integrated device, the communication device 13 performs inter-process communication between the process operating as the action support device 10 and the process operating as the action analysis device 20. may contain. The communication device 13 may also be called a "transmitter", a "receiver", or the like.

The input/output device 14 includes, for example, an input device such as a keyboard, touch panel, mouse and/or microphone, and an output device such as a display and/or speaker. An input/output device may be called an "input unit" or an "output unit" or the like.

The hardware configuration described above is merely an example. Each device in the action support system 1 may omit part of the hardware shown in FIG. 2, or may include hardware not shown in FIG. Moreover, the hardware shown in FIG. 2 may be configured by one or a plurality of chips.

<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.

≪Behavior analysis device≫
As shown in FIG. 3 , the behavior analysis device 20 has an acquisition unit 201 and a generation unit 202 . At least part of the functions realized by the acquisition unit 201 can be realized using the communication device 13 . At least 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 . Also, 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-temporary storage medium is not particularly limited, but may be a storage medium such as a USB memory or CD-ROM, for example.

The acquisition unit 201 acquires information about a process for behavior modification (hereinafter referred to as “behavior process information”). The behavioral process information includes, for example, information indicating at least one of a field that encourages behavioral modification, a range of intervention for the behavioral modification, a success rate of behavioral modification, a failure rate of behavioral modification, and the like. For example, if the field that encourages behavior change is “use of medical examinations or medical examinations,” the success rate of behavior change is the participation rate of medical examinations or medical examinations, and the failure rate of behavior change is the dropout rate of medical examinations or medical examinations. rate. The acquisition unit 201 may acquire the behavior process information from another device via the communication device 13 or via the storage medium.

The generation unit 202 generates a plurality of nudge messages each associated with a plurality of IBM factors based on the behavioral process information acquired by the acquisition unit 201 . Nudge messages are generated to encourage behavioral change for each IBM factor. For example, the generator 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 acquisition unit 201 is input. Such machine learning models may be implemented as neural networks and trained by supervised learning using pairs of behavioral process information and nudge messages as training data.

FIG. 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. Multiple IBM factors include, for example, Experiential attitude, Instrumental attitude, Injunctive norm, Descriptive norm, Perceived control, Self-efficacy May include at least two of Self-efficacy, Knowledge, Skills, Salience of the behavior, Environmental constraints, and Habit .

Note that each IBM factor shown in FIG. 4 is merely an example, and is not limited to what is shown. At least two IBM factors shown in FIG. 4 may be subsumed and defined as higher level IBM factors. For example, the empirical attitude and instrumental attitude are included in "attitude", the referential norm and descriptive norm are included in "perceived norm", and the sense of behavioral control and self-efficacy are The above knowledge and skills are subsumed in "Knowledge", the importance of behavior is subsumed in "Importance", and environmental constraints are subsumed in "Importance". Friction”. Alternatively, the single IBM factor shown in FIG. 4 may be split to define multiple lower level IBM factors. A nudge message may be associated with any level of IBM factor.

As shown in FIG. 4, each of a plurality of IBM factors may be associated with an IBM factor identifier (hereinafter referred to as "IBM ID") and a nudge message. Note that FIG. 4 shows a nudge message assuming, for example, "residents of ○○ city" as a target person and "recommendation to undergo a specific health checkup (hereinafter referred to as "specific health checkup")" as a behavioral change. A nudge message associated with each IBM factor is generated to encourage behavioral change in the subject in consideration of each IBM factor. Although one nudge message is associated with each IBM factor in FIG. 4, a plurality of nudge messages may be associated with each IBM factor. Also, the IBM ID for identifying each IBM factor is not limited to the illustrated one.

The nudge message generated by the generator 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.

≪Action 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 . Note that at least part of the functions realized by the acquisition unit 104 can be realized using the communication device 13 . Also, the prediction unit 102 , the generation unit 103 and the transmission control unit 105 can be realized by the processor 11 executing the action support program stored in the storage device 12 . Further, the action support program can be stored in the storage medium. Also, the storage unit 101 can be realized using the storage device 12 .

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

The storage unit 101 stores information about the subject (hereinafter referred to as "subject information"), information about the environment for behavior modification (hereinafter referred to as "environmental information"), and results of exploratory randomized controlled trials (RCTs). (hereinafter referred to as "RCT information").

Here, the target person information stored in the storage unit 101 includes identification information of the target person, information on the attribute of the target person (hereinafter referred to as “attribute information”), information on the action history of the target person (hereinafter referred to as “action history information"), information on the risk in the case where the subject's behavior is not changed (hereinafter referred to as "risk information"), and information on the response from the subject (hereinafter referred to as "response information"). may contain.

FIG. 5 is a diagram showing an example of subject information according to this embodiment. For example, FIG. 5 illustrates target person information assuming that the target person is "a resident of ○○ city" and the behavior change is "a specific health checkup (for example, medical checkup)".

The target person information in FIG. Information indicating the subject's specific medical examination history, risk information, for example, information indicating the risk of the subject suffering from a specific disease (hereinafter referred to as "morbidity risk"), and response information, such as , information indicating responses to the questionnaire for the subject (hereinafter referred to as “questionnaire responses”).

Note that the target person information is not limited to that shown in FIG. For example, in FIG. 5, the reception history of specific medical examinations in the last predetermined number of years is shown as action history information, but any information may be used as long as it relates to the action history of the subject. Also, the attribute information is not limited to the subject's age and sex, and may be any information related to the subject's attributes. Also, at least part of the information shown in FIG. 5 may not be included, and information (not shown) related to the subject may be included.

In addition, the environmental information stored in the storage unit 101 is, for example, targeted at residents in a specific administrative unit (for example, ___ city), and when taking a specific health checkup is a behavioral change, the date and time of the specific health checkup , information indicating a medical institution that can receive the specific health checkup, or the like. The environment information may also include the maximum number of transmissions of nudge messages to the target person, information on rewards for behavior modification (hereinafter referred to as “reward information”), and the like. For example, if the target person is "a resident of a certain administrative unit" and the behavior change is "participation in a specific health checkup," the remuneration information may include the expected effect of extending the life span of the target person, the expected tax payment amount, etc. may

In addition, the RCT information includes ranking of transmission dates (eg, weekdays, Monday to Sunday, national holidays, etc.), ranking of transmission time zones (eg, morning, afternoon, nighttime, etc.), and ranking of transmission frequency (eg, monthly , biweekly, monthly, etc.), compatibility between the target person information and the nudge message set, and the transmission order of the nudge messages in the nudge message set.

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

For example, the state information shown in FIG. , environmental constraints and habituation), indicate whether or not the condition of each subject is sufficient for behavioral modification (for example, taking a specific health checkup). For example, the status information of the subject with subject ID "3" (hereinafter referred to as "subject #3") in FIG. Constraints” are not sufficient for behavior modification, and other IBM factors are sufficient for behavior modification. In addition, the state information indicating that the subject's state is not sufficient for behavior modification may be called insufficient information. Also, FIG. 6 is merely an example, and some items (eg, IMB ID, major items, medium items, etc.) may be omitted.

The prediction unit 102 obtains the state information as described above, in addition to the subject information, information on the response from the subject acquired by the acquisition unit 104 (hereinafter referred to as “response information”), environment information and RCT A prediction may be made based on at least one of the information. Also, the prediction unit 102 may generate the state information as described above using a trained machine learning model. The machine learning model is trained to output the state information when the subject information (and at least one of response information, environment information and RCT information) is input. Such a machine learning model is realized as a neural network, and supervised learning using pairs of the subject information (and at least one of response information, environmental information, and RCT information) and state information as training data. may be trained.

Also, the prediction unit 102 may predict a probability of behavior change of the target person (hereinafter referred to as “behavior change probability”) based on the target person information about the target person. The behavior modification probability may be, for example, the probability that the subject will achieve behavior modification without intervention for behavior modification of the subject (hereinafter, “non-intervention behavior probability”). For example, the non-interventional behavior probability of subject #3 in FIG. 6 is 70%, and behavior modification is achieved with a probability of 70% if intervention for behavior modification is not performed. In addition, the behavior change probability is not limited to this, and may be the probability that the subject does not achieve behavior change without the above intervention, the probability that the subject achieves or does not achieve behavior change with the above intervention, or the like. .

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

Based on the state information predicted by the prediction unit 102, the generation unit 103 selects a set (hereinafter referred to as a "nudge message set") containing one or more nudge messages that are distribution candidates for the target person from the storage unit 203. . Specifically, the generation unit 103 generates a nudge message set including at least a nudge message associated with the IBM factor indicating that the state information is not sufficient for behavior modification.

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-#4. Nudge messages #2-#4 are based on the three IBM factors "empirical attitude", "knowledge and skills" and " "Environmental Constraints". On the other hand, nudge message #1 is not associated with the IBM factor. Thus, the nudge message set may include other nudge messages, as well as nudge messages associated with IBM factors indicating that state information is not sufficient for behavior modification.

Acquisition unit 104 acquires response information from a subject. Here, the response information is, for example, information indicating a response from the target person who viewed the nudge message, whether or not the short message (SM) containing the nudge message or e-mail was viewed, the situation regarding behavior change (for example, specific health examination reservation status), the result of behavioral change (for example, the result of a specific medical examination), and the like. The acquisition unit 104 may acquire the response information from the terminal 30 of the subject in real time.

The transmission control unit 105 controls transmission of one or more nudge messages in the nudge message set selected by the generation unit 103 to the target person. 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 target person.

Specifically, the transmission control unit 105 generates the one or more nudge messages based on at least one of the RCT information and the environment information stored in the storage unit 101 and the response information acquired by the acquisition unit 104. Control sending to target audience. Here, the transmission control of the nudge messages includes, for example, the transmission order of the multiple nudge messages in the nudge message set, the transmission date of each nudge message, the transmission time period of each nudge message, and the time to transmit the multiple nudge messages. Controls such as intervals (sending frequency), stopping sending each nudge message, and the number of times each nudge message is sent may be included.

For example, in the case of the nudge message set for subject #3 shown in FIG. 3 and #4 decide to send a nudge message to subject #3. Further, the transmission control unit 105, based on at least one of the RCT information, the environment information, and the response information, sets at least the transmission date, transmission time period, transmission interval, transmission stop, and number of transmissions of the nudge messages #1 to #4. Decide on one.

For example, if the acquisition unit 104 acquires positive response information for behavior modification after each of the nudge messages #1 to #3 in FIG. 7 is transmitted, the transmission control unit 105 stops transmission of subsequent nudge messages. You may On the other hand, when negative response information is acquired in response to a nudge message, the transmission control unit 105 may resend the nudge message or may transmit a subsequent nudge message.

Thus, instead of sending the set of nudge messages for target person #3 all at once to target person #3, multiple nudge messages included in the set of nudge messages can be distributed and sent to target person #3 multiple times. Even a single nudge message with a large amount of information may be overlooked by humans, so it can be said that multiple nudge messages are more effective in promoting behavioral change. Therefore, by dispersing and transmitting the nudge message a plurality of times, it is possible to enhance the effect of promoting behavior modification for the target person who does not cause behavior modification with a single nudge message.

Also, 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. Further, by updating the nudge message to be sent to the target person based on the response information of the target person, it is possible to send an effective nudge message by promoting behavioral change of the target person.

Also, the transmission control unit 105 may control 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 increases the number of transmissions of each nudge message or increases the transmission frequency for a target person whose non-intervention behavior probability satisfies a predetermined condition (for example, equal to or less than a predetermined threshold). You can On the other hand, the transmission control unit 105 reduces the number of transmissions of each nudge message or reduces the transmission frequency for a target person whose non-intervention action probability satisfies a predetermined condition (for example, greater than or equal to a predetermined threshold value). You may let

Further, transmission control section 105 controls transmission of one or more nudge messages in the nudge message set generated by generation section 103 based on information that changes due to various factors (hereinafter referred to as “change information”). may For example, the change information may be the arrival status of a specific vaccine, the availability of appointments for health checkups or medical examinations, the availability of time, and the like. In addition, the transmission control unit 105 controls the nudge message generated by the generation unit 103 based on information about the convenience of the target person (for example, whether or not the time and/or place is highly convenient for the target person). It may control the sending of one or more nudge messages in the set.

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 is initialized using at least one of the state information and behavior change probability predicted by the prediction unit 102, the environment information stored in the storage unit 101, and the nudge message set generated by the generation unit 103. may be In addition, the transmission control unit 105 uses all the nudge messages and all target persons stored in the storage unit 101 as an environment, all the nudge messages as a solution space, the maximum number of times of transmission of nudge messages to each target person as a budget, and the target The above transmission control may be implemented by solving the resource allocation problem with the sum of the rewards obtained during the period as the cumulative reward.

(Operation of action support system)
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 what is illustrated.

As shown in FIG. 8, in step S101, the action support device 10 predicts the target person's state information (for example, FIG. 6) based on the target person information. Also, the action support device 10 may predict a behavior change probability (for example, a non-intervention behavior probability) based on the subject information. Further, the action support device 10 predicts or updates the state information and/or the behavior change probability based on at least one of the response information, the environment information, and the RCT information for the nudge message transmitted by the transmission control in step S103. good too.

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

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

According to the action support system 1 according to the present embodiment, nudges based on action factors can be used to more effectively support the behavior change of the subject. More specifically, in the action support system 1, state information indicating a subject's state for each of a plurality of IBM factors is predicted, and nudge messages including one or more nudge messages selected based on the state information are generated. Generates a set. Therefore, it is possible to generate a nudge message set (that is, a bundle of information) that is optimal for behavior modification of the subject.

In addition, in the action support system 1, instead of transmitting a set of nudge messages as exemplified in FIG. By transmitting, it is possible to enhance the effect of promoting behavior modification of the subject. Further, by controlling the transmission of the subsequent nudge message and/or updating the content based on the response information to the nudge message, it is possible to more effectively assist the subject's behavioral change.

The embodiments described above are for facilitating understanding of the present invention, and are not intended to limit and interpret the present invention. Each element included in the embodiment and its arrangement, materials, conditions, shape, size, etc. are not limited to those illustrated and can be changed as appropriate. Also, it is possible to partially replace or combine the configurations shown in different embodiments.

For example, in the above-described embodiment, for example, it is assumed that the target person is "a resident of XX city" and the behavior change is "a specific medical checkup (for example, medical checkup)", but the present invention is not limited to this. The target person is not limited to users of administrative services, but may be users of various services such as English conversation and qualification tests. Behavioral change is not limited to the use of administrative services, but may be continued learning, use of various services, and the like.

Further, in the above embodiment, it was assumed to control the transmission of one or more messages to the subject based on the RCT information on the results of the exploratory randomized controlled trial (RCT), but it is used to control the transmission of the message Causal inference techniques are not limited to exploratory RCT. As the causal inference method, for example, other methods such as propensity score matching may be used. The exploratory RCT can also be called a trial and/or small-scale RCT, and may be any pilot for setting parameters used for transmission control of the message.

Further, 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 voice, video, image, or the like. In the above embodiment, the transmission control unit 105 of the action support device 10 controls the transmission of the nudge message, but the action support device 10 is not limited to this. (including display, audio output, etc.) may be provided. In other words, "transmission" of the nudge message in the above embodiment may be rephrased as display, audio output, output, or the like. Moreover, the terminal 30 is not limited to a terminal used by a specific target person, and may be a signage, an electronic bulletin board, a speaker, or the like that outputs information for an unspecified target person.

For example, the action support device 10 sends a nudge message "disperse people" to the terminal 30 (for example, , signage, electronic bulletin board, speaker, etc.) and output from the terminal 30 (for example, display, audio output, etc.). Further, the action support device 10 and the terminal 30 that outputs the nudge message to the target person may be provided as an integrated device, and the action support device 10 transmitting the nudge message to the terminal 30 is It may be internal communication within an integrated device.

1 action support system 10 action support device 20 action 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 (8)

a storage unit that stores a plurality of messages associated with a plurality of behavioral factors to encourage behavioral change;
a prediction unit that predicts state information indicating the 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;
action support system. The generation unit selects from the storage unit the one or more messages respectively associated with one or more behavioral factors indicating that the state information is not sufficient for the behavioral change.
The action support system according to claim 1. The control unit includes RCT information about the results of an exploratory randomized controlled trial (RCT), environment information about the environment for behavior modification, response information about the response from the subject, and the subject by the prediction unit controlling the output of the one or more messages to the target person based on at least one of the behavior change probabilities predicted based on the person information;
The action support system according to claim 1 or 2. The RCT information includes the ranking of time zones for outputting the one or more messages, the ranking of frequency, compatibility between the target person information and/or the status information and the message set, and the one or more in the message set indicating at least one of the ordering of the output order of messages in
The action support system according to claim 3. The subject information indicates at least one of the attributes of the subject, the behavior history of the subject, the risk in the absence of the behavioral change of the subject, and the response from the subject.
The action support system according to any one of claims 1 to 4. The plurality of behavioral factors includes at least two of experiential attitude, instrumental attitude, directive norm, descriptive norm, sense of control over behavior, self-efficacy, knowledge, skills, importance of behavior, environmental constraints, and habituation. including one
The action support system according to any one of claims 1 to 5. a step in which an action support device predicts state information indicating the state of the subject for each of a plurality of behavior factors based on subject information about the subject;
The action support device selects one or more messages based on the state information from a storage unit that stores a plurality of messages for prompting behavioral change in association with the plurality of behavior factors, and selects the one or more messages generating a message set containing messages;
the activity support device controlling output of the one or more messages in the message set to the subject;
An action support method having to the computer,
Predicting state information indicating the state of the subject for each of a plurality of behavioral factors based on subject information about the subject;
One or more messages are selected based on the state information from a storage unit that stores a plurality of messages for prompting behavioral change in correspondence with the plurality of behavior factors, and a message set including the one or more messages is generated. a step of generating;
controlling the output of the one or more messages in the message set to the subject;
An action support program to carry out.

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