Cognitive behavioral therapy assistance device, cognitive behavioral therapy assistance system, and cognitive behavioral therapy assistance program

Abstract

The present invention comprises: a candidate presentation unit 11 that presents a plurality of target behavior candidates; and a target behavior setting unit 12 that sets, as a target behavior for a prescribed period, a target behavior candidate selected by a user. The plurality of target behavior candidates are presented with the allocation thereof being adjusted on the basis of the degree of implementability or non-implementability of a behavior by the user for each category set for the behavior such that the number of target behavior candidates corresponding to a category having a greater degree of non-implementablity becomes larger, thereby making it possible to prevent a situation in which an unachieved behavior is easily set as a target behavior from being created and prevent the unachieved behavior from remaining unachieved.

Description

Cognitive behavioral therapy support device, cognitive behavioral therapy support system, and cognitive behavioral therapy support program

[0001] The present invention relates to a cognitive behavioral therapy support device, a cognitive behavioral therapy support system, and a cognitive behavioral therapy support program that support the implementation of cognitive behavioral therapy.

[0002] Tinnitus is one of the most common complaints in daily medical practice. Tinnitus is an abnormal sound sensation felt despite the absence of any apparent external sound source. The number of tinnitus patients is expected to increase due to stress caused by aging and changes in the social environment. Severe tinnitus is likely to be accompanied by mental disorders such as depression, anxiety, and insomnia, and it has also been pointed out that it can affect the cognitive function of the elderly, making how to deal with this condition one of the important issues in otolaryngology clinical practice.

[0003] In response to this, the Tinnitus Treatment Guidelines (see Non-Patent Document 1) were published in 2019. These guidelines recommend the implementation of cognitive behavioral therapy. Cognitive behavioral therapy focuses on the fact that a person's mood and behavior are influenced by their way of thinking and perception, and aims to treat mental illness by correcting biases in cognition and behavior.

[0004] Conventionally, systems that support the implementation of cognitive behavioral therapy using information processing technology are known (see, for example, Patent Documents 1 to 3). In the information processing device described in Patent Document 1, after presenting a first task behavior to a user, the user is presented with options to complete, retake, or not complete the first task behavior. If the user selects the not complete option, a second task behavior that is less difficult than the first task behavior is set and presented to the user. This allows the user to easily improve their lifestyle habits.

[0005] In the information processing device described in Patent Document 2, a level of difficulty is set in advance for each behavioral goal, and the difficulty of the next behavioral goal presented to the user is adjusted depending on the achievement status of the predetermined goal determined based on the user's answers for the behavioral goal presented to the user. Specifically, if it is determined that the predetermined goal has been achieved for a behavioral goal, a behavioral goal with a higher difficulty level than the behavioral goal is presented to the user as the next behavioral goal to be performed by the user. Conversely, if it is determined that the predetermined goal has not been achieved for a behavioral goal, a behavioral goal with a lower difficulty level than the behavioral goal is presented to the user as the next behavioral goal to be performed by the user. This enables the patient's lifestyle to be improved.

[0006] In the lifestyle management system described in Patent Document 3, a server selects an action menu suitable for a user based on answers to questions for the user and transmits it to an information terminal device, receives the execution status of the sent action menu (execution frequency, execution time, whether or not it has been executed, etc.) from the information terminal device, and when the execution status reaches the achievement standard of the sent action menu, transmits the next level of action menu to the information terminal device. In this way, an action menu can be provided after the user's motivation has increased to a certain extent, allowing the user to work on improving their lifestyle with little resistance.

[0007] JP 2022-23756 A JP 2023 / 058378 A JP 2012-113393 A

[0008] Tinnitus Treatment Guidelines 2019 Edition (Japan Audiology Society)

[0009] In cognitive behavioral therapy for tinnitus, it is thought that behavioral training that encourages the user to perform actions that the user is unable to perform (or believes they cannot perform) due to tinnitus and gradually reduces the actions that the user is unable to perform is effective. However, the techniques described in Patent Documents 1 and 2 above have the problem that unaccomplished task actions remain unaccomplished.

[0010] On the other hand, in the technology described in Patent Document 3, when the execution status of the presented action menu reaches the achievement standard, the next action menu is presented, so there is a low possibility that the presented action menu will remain unachieved. However, Patent Document 3 only describes that an action menu suited to the user's physical condition and lifestyle habits, collected through questions and answers to the user, is selected and presented, and it is not clear how the action menu suited to the user is extracted.

[0011] The present invention has been made to solve such problems, and aims to use information processing technology to support the implementation of behavioral training that can effectively reduce behaviors that users are unable to perform due to tinnitus.

[0012] In order to solve the above-mentioned problems, in the present invention, one or more target behavior candidates selected by a user from among a plurality of target behavior candidates are set as target behaviors for a predetermined period. When presenting the plurality of target behavior candidates to the user, the distribution is adjusted based on the degree of feasibility or impossibility of the user's behavior for each classification set for the behavior, so that the number of target behavior candidates corresponding to a classification with a low feasibility or a high impossibility is greater than the number of target behavior candidates corresponding to a classification with a high feasibility or a low impossibility.

[0013] According to the present invention configured as described above, the multiple candidate target actions presented to the user when setting a target action are adjusted so as to increase the number of actions that the user is unable to perform due to tinnitus, thereby creating a situation in which unachieved actions are more likely to be set as target actions and preventing unachieved actions from remaining unachieved.As a result, according to the present invention, it is possible to use information processing technology to support the implementation of behavioral training that can effectively reduce the number of actions that the user is unable to perform due to tinnitus.

[0014] 1 is a block diagram showing an example of the functional configuration of a cognitive behavioral therapy support device according to this embodiment; FIG. 2 is a diagram showing an example of the hardware configuration of a cognitive behavioral therapy support device according to this embodiment; FIG. 3 is a diagram showing an example of a plurality of behavioral data stored in a behavior storage unit of this embodiment; FIG. 4 is a diagram showing an example of the processing content of a behavior analysis unit and a candidate presentation unit of this embodiment; FIG. 5 is a flowchart showing an example of the operation of a cognitive behavioral therapy support device according to this embodiment; FIG. 6 is a diagram showing an example of behavior classification and decomposition element properties; FIG. 7 is a block diagram showing a specific example of the functional configuration of a behavior analysis unit according to a modified example; FIG. 8 is a diagram showing an example for explaining the processing content of a behavior analysis unit according to a modified example.

[0015] An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing an example of the functional configuration of a cognitive behavioral therapy support device 1 according to this embodiment. FIG. 2 is a diagram showing an example of the hardware configuration of the cognitive behavioral therapy support device 1 according to this embodiment. The cognitive behavioral therapy support device 1 is configured by a terminal such as a personal computer, a tablet, or a smartphone. A cognitive behavioral therapy support program (hereinafter referred to as a cognitive behavioral therapy support app) is installed in the cognitive behavioral therapy support device 1.

[0016] 2, the cognitive behavioral therapy support device 1 includes, as its hardware configuration, a control unit 101, a storage unit 102, an input unit 103, and a display unit 104. The control unit 101 is configured by a processor such as a microcomputer equipped with a CPU, RAM, and ROM, and operates in accordance with an operating system and a cognitive behavioral therapy support application stored in the storage unit 102, and executes information processing using various data stored in the storage unit 102. In addition to the microcomputer, the device may also include a DSP (Digital Signal Processor) or the like.

[0017] The storage unit 102 is configured with a computer-readable storage medium. For example, the storage unit 102 is configured to include a ROM, a RAM, a hard disk, or a semiconductor memory. The storage unit 102 stores various programs executed by the control unit 101. The various programs include a cognitive behavioral therapy support program.

[0018] The storage unit 102 also stores various data including data used in the processing of the control unit 101 and data generated by the processing. The various data include data on candidate target behaviors to be presented to the user, data input by the user indicating whether or not the candidate target behaviors can be performed, etc. The storage unit 102 also stores data on a target behavior selection screen used when presenting candidate target behaviors to the user and prompting them to select one, and data on an achievement status input screen used when obtaining information from the user regarding the achievement status of the target behavior selected by the user.

[0019] The input unit 103 is configured with, for example, a keyboard, a mouse, or a touch panel, and supplies data according to user operation input to the control unit 101. The display unit 104 is configured with, for example, a liquid crystal display, and displays information according to instructions input from the control unit 101.

[0020] 1, the cognitive behavioral therapy support device 1 of this embodiment includes, as functional components of a control unit 101, a candidate presentation unit 11, a target behavior setting unit 12, an implementation status recording unit 13, a response input unit 14, an achievement status input unit 15, and a behavior analysis unit 16. The cognitive behavioral therapy support device 1 of this embodiment also includes, as a memory unit 102, a behavior memory unit 21 and an implementation status memory unit 22. The processing of the functional blocks 11 to 16 is executed by operating a program including a cognitive behavioral therapy support app stored in the memory unit 102 under the control of the control unit 101 shown in FIG.

[0021] The behavior storage unit 21 stores data indicating a plurality of behaviors to be presented to the user as target behavior candidates. The plurality of behaviors are assigned classifications according to their properties. FIG. 3 is a diagram schematically illustrating a plurality of behavior data stored in the behavior storage unit 21. In the example of FIG. 3, one of four classifications CL1 to CL4 is assigned to each of the plurality of behavior data according to the properties of the behaviors.

[0022] As shown in Figure 3, the behavior memory unit 21 stores data indicating a plurality of behaviors 1 to i (i is any number) assigned to a first classification CL1, data indicating a plurality of behaviors i+1 to j (j is any number) assigned to a second classification CL2, data indicating a plurality of behaviors j+1 to k (k is any number) assigned to a third classification CL3, and data indicating a plurality of behaviors k+1 to L (L is any number) assigned to a fourth classification CL4.

[0023] For example, actions belonging to the first category CL1 are "actions performed alone indoors," actions belonging to the second category CL2 are "actions performed alone outdoors," actions belonging to the third category CL3 are "actions performed indoors with others," and actions belonging to the fourth category CL4 are "actions performed outdoors with others." Note that the categories shown here are merely examples and are not limiting. For example, "indoors" may be replaced with "quiet surroundings," and "outdoors" may be replaced with "noisy surroundings." Furthermore, "other people" may be replaced with "two or more people."

[0024] The candidate presentation unit 11 reads out a plurality of pieces of behavioral data to be used as target behavior candidates from the behavior storage unit 21, and displays the data on the display unit 104 in a target behavior selection screen, thereby presenting the plurality of target behavior candidates and prompting the user to select one. At this time, the candidate presentation unit 11 reads out a plurality of pieces of behavioral data to be presented as target behavior candidates from the behavior storage unit 21 in accordance with a predetermined selection algorithm. Details of this selection algorithm will be described later.

[0025] The target behavior setting unit 12 sets one or more target behavior candidates selected by the user from the plurality of target behavior candidates presented by the candidate presentation unit 11 as a target behavior for a predetermined period. As an example, the number of target behavior candidates presented by the candidate presentation unit 11 is assumed to be 12, and the number of target behaviors selected and set by the user from among them is assumed to be three. The predetermined period is assumed to be one week. That is, the user selects three target behavior candidates from the 12 target behavior candidates presented by the candidate presentation unit 11, and the target behavior setting unit 12 sets the selected target behavior candidates as target behaviors for one week. Note that the numerical values ​​shown here are merely examples and are not limited to these.

[0026] In this embodiment, the candidate presentation unit 11 presents a plurality of target behavior candidates and prompts the user to select a target behavior candidate that the user has already performed among them, and to select a target behavior from among the target behavior candidates that the user has not yet performed. The user responds with an action that the user has already performed among the plurality of target behavior candidates (e.g., 12) presented on the target behavior selection screen, and selects one or more (e.g., three) target behavior candidates that the user has not yet performed, and sets them as target behaviors for a predetermined period (e.g., one week).

[0027] The implementation status recording unit 13 acquires implementation status information indicating whether or not the user can perform some or all of the actions indicated by the multiple target action candidates presented by the candidate presentation unit 11, and records the information in the implementation status storage unit 22. Here, the implementation status recording unit 13 acquires the implementation status information indicating whether or not the actions can be performed from the answer input unit 14 and the achievement status input unit 15.

[0028] The answer input unit 14 inputs answer information input through the target behavior selection screen displayed on the display unit 104 by the candidate presentation unit 11, i.e., information on the target behavior candidates that the user has answered as being able to implement. The implementation status recording unit 13 acquires the answer information by the user from the answer input unit 14 as implementation status information regarding some or all of the multiple target behavior candidates presented by the candidate presentation unit 11, and records the information in the implementation status storage unit 22. For example, if the user answers that they have already implemented some of the 12 target behavior candidates, the implementation status recording unit 13 records implementation status information indicating "implementable" for those some target behavior candidates in the implementation status storage unit 22.

[0029] The achievement status input unit 15 displays an achievement status input screen on the display unit 104 after a predetermined period has elapsed since the goal setting, prompting the user to input the achievement status. The user reflects on their actions during the predetermined period and inputs the achievement status, indicating whether or not they were able to perform the target behavior set by the target behavior setting unit 12, into the achievement status input screen. The achievement status input unit 15 acquires achievement status information input by the user through the achievement status input screen. The implementation status recording unit 13 acquires achievement status information indicating the achievement status of the target behavior set by the target behavior setting unit 12 from the achievement status input unit 15 as implementation status information regarding some of the multiple target behavior candidates presented by the candidate presentation unit 11, and records the information in the implementation status storage unit 22. Here, for target behaviors that the user was able to perform during the predetermined period, the implementation status information indicating "implementable" is recorded in the implementation status storage unit 22, and for target behaviors that the user was not able to perform, the implementation status information indicating "unimplementable" is recorded in the implementation status storage unit 22.

[0030] Here, if the number of target behavior candidates that the user has already answered that they have been able to perform on the target behavior selection screen is, for example, less than nine out of twelve, the implementation status recording unit 13 combines the answer information for the less than nine target behavior candidates and the achievement status information for the three target behaviors, and records implementation status information indicating “implementable” or “unimplementable” for some of the twelve target behavior candidates presented by the candidate presentation unit 11 in the implementation status storage unit 22. On the other hand, if the number of target behavior candidates that the user has already answered that they have been able to perform on the target behavior selection screen is nine, the implementation status recording unit 13 records implementation status information indicating “implementable” or “unimplementable” for all of the twelve target behavior candidates presented by the candidate presentation unit 11 in the implementation status storage unit 22.

[0031] Note that if the number of target behavior candidates that the user has already responded that they have performed on the target behavior selection screen is, for example, more than 9 out of 12, the number of target behaviors that can be set as target behaviors will be 2 or less. In this case, the candidate presentation unit 11 may present additional target behavior candidates to prompt further selection. Alternatively, if the number of target behaviors that can be set as target behaviors is 1 or 2, the one or two target behavior candidates may be set as target behaviors without presenting additional target behavior candidates.

[0032] The cognitive behavioral therapy support app operates to repeat the processes of the candidate presentation unit 11, the target behavior setting unit 12, and the implementation status recording unit 13 n times (n≧2) in units of a predetermined period. For example, assuming that the predetermined period is one week and n=10, the processes of the candidate presentation unit 11, the target behavior setting unit 12, and the implementation status recording unit 13 are repeated once a week for 10 weeks. As a result, implementation status information regarding some or all of the behaviors indicated by the target behavior candidates presented by the candidate presentation unit 11 every week, 12 at a time, is sequentially recorded in the implementation status storage unit 22 every week for 10 weeks.

[0033] The behavior analysis unit 16 analyzes the degree of feasibility or impossibility of an action for each of the categories CL1 to CL4 set according to the nature of the action, based on the implementation status information stored in the implementation status storage unit 22 (including the answer information acquired by the implementation status recording unit 13 from the answer input unit 14 and the achievement status information acquired from the achievement status input unit 15). For example, the behavior analysis unit 16 counts the number of actions recorded as "possible to implement" in the implementation status information for each of the categories CL1 to CL4, and ranks the categories CL1 to CL4 in descending order of the number of possible actions.

[0034] As described above, the cognitive behavioral therapy support app may repeatedly execute the processing of the candidate presentation unit 11, the target behavior setting unit 12, and the implementation status recording unit 13 n times (n≧2) in units of a predetermined period, while repeatedly executing the processing of the behavior analysis unit 16 in units of a predetermined period from the first week to the n-1th week.

[0035] Here, the implementation status information counted by the behavior analysis unit 16 may be only information recorded in the implementation status storage unit 22 for the most recent predetermined period, or may be information recorded by repeatedly executing the processes of the candidate presentation unit 11, the target behavior setting unit 12, and the implementation status recording unit 13 over multiple predetermined periods. In the former case, for example, when setting a target behavior for the wth cycle (2≦w≦n), the number of behaviors recorded as "implementable" is counted for each of the categories CL1 to CL4 using only the implementation status information for the most recent w-1 cycle. In the latter case, for example, when setting a target behavior for the wth cycle (2≦w≦n), the number of behaviors recorded as "implementable" is counted for each of the categories CL1 to CL4 using the implementation status information from the first cycle to the most recent w-1 cycle.

[0036] The candidate presentation unit 11 presents multiple target behavior candidates for the next predetermined period by adjusting the distribution so that the number of target behavior candidates corresponding to a category with a low degree of feasibility is greater than the number of target behavior candidates corresponding to a category with a high degree of feasibility, based on the degree of feasibility for each of the categories CL1 to CL4 analyzed by the behavior analysis unit 16 in response to the end of one predetermined period. This is an example of a selection algorithm when reading multiple behavior data to be presented as target behavior candidates from the behavior storage unit 21.

[0037] For example, for the category with the largest number of executable actions, the number of presented target action candidates is set to 1, for the category with the second largest number, the number of presented target action candidates is set to 2, for the category with the third largest number, the number of presented target action candidates is set to 4, and for the category with the fewest, the number of presented target action candidates is set to 5. By adjusting the number of presented target action candidates for each of categories CL1 to CL4 in this way, it is possible to create a situation in which target action candidates that the user is unable to perform due to tinnitus are more likely to be set as target actions.

[0038] 4 is a diagram schematically illustrating an example of the processing details of the behavior analysis unit 16 and the candidate presentation unit 11. As shown in FIG. 4, the behavior analysis unit 16 counts the number of behaviors recorded as "possible" for each of the categories CL1 to CL4 based on the implementation status information stored in the implementation status storage unit 22, and ranks the categories CL1 to CL4 in descending order of the number of possible behaviors. FIG. 4 illustrates a state in which the ranking is performed in descending order of the number of possible behaviors: fourth category CL4 > second category CL2 > first category CL1 > third category CL3.

[0039] The candidate presentation unit 11 presents multiple target behavior candidates for the next predetermined period by adjusting the distribution so that the number of presented target behavior candidates corresponding to higher ranked categories is less than the number of presented target behavior candidates corresponding to lower ranked categories, according to the ranking of the categories CL1 to CL4 analyzed by the behavior analysis unit 16. That is, the number of presented target behavior candidates is one for the fourth category CL4 in first place, two for the second category CL2 in second place, four for the first category CL1 in third place, and five for the third category CL3 in fourth place.

[0040] When the implementation status recording unit 13 records the implementation status information in the implementation status storage unit 22, the implementation status recording unit 13 may assign points to actions that are executable or not executable and record the information. The behavior analysis unit 16 may calculate the total points for each of the categories CL1 to CL4 to analyze the degree of executableness of the actions for each of the categories CL1 to CL4. For example, a point of "+1" may be assigned to an action recorded as "executable," while no point may be assigned to an action recorded as "not executable" (the point may be set to "0"). In this case, the candidate presentation unit 11 ranks the categories CL1 to CL4 based on the total points calculated for each of the categories CL1 to CL4 by the behavior analysis unit 16, and determines the number of target behavior candidates to present for each of the categories CL1 to CL4 according to the ranking.

[0041] Here, points assigned to actions recorded as "possible to implement" based on the answer information acquired from the answer input unit 14 may be different from points assigned to actions recorded as "possible to implement" based on the achievement status information acquired from the achievement status input unit 15. Furthermore, for actions that are "impossible to implement," the degree to which the action cannot be implemented may be input from the achievement status input screen, and different points may be assigned depending on the degree. For example, one of "completely impossible to implement," "difficult to implement," or "not implemented" may be selected and input from the achievement status input screen, and different points may be assigned depending on which is input.

[0042] While the example described here ranks the categories CL1 to CL4 and determines the number of target behavior candidates to be presented based on a predetermined number in accordance with the ranking, this method is not limiting. For example, the ratio of the total number of "possible" behaviors or the total points calculated for each category CL1 to CL4 may be calculated, and the number of target behavior candidates to be presented for each category CL1 to CL4 may be determined based on the inverse ratio. For example, if the ratio of the total number of "possible" behaviors calculated for each category CL1 to CL4 is 1:2:5:3, the number of target behavior candidates to be presented for each category CL1 to CL4 may be determined based on the inverse ratio of 3:5:2:1. Here, if the value calculated based on the ratio does not become an integer, it may be converted to an integer by rounding, rounding down, rounding up, or other adjustments.

[0043] In addition, when the behavior analysis unit 16 analyzes the degree of feasibility of each of the categories CL1 to CL4 for all of the implementation status information stored in the implementation status memory unit 22 (implementation status information from the first week to the most recent week), the algorithm for selecting target behavior candidates may be different for the first m (1≦m<n) predetermined periods when the process is repeatedly executed over n (n≧2) predetermined periods and for the m+1th and subsequent predetermined periods.

[0044] For example, during the first m predetermined periods, the behavior analysis unit 16 does not perform processing, and only the candidate presentation unit 11, the target behavior setting unit 12, and the implementation status recording unit 13 perform processing, and the candidate presentation unit 11 presents multiple target behavior candidates corresponding to multiple categories CL1 to CL4 in an even distribution. For example, when m=3, the behavior analysis unit 16 does not perform processing until the third week, and when setting target behaviors for the first to third weeks, multiple target behavior candidates corresponding to multiple categories CL1 to CL4 are presented in an even distribution. That is, during the first three predetermined periods, the candidate presentation unit 11 presents three target behavior candidates each corresponding to categories CL1 to CL4.

[0045] Meanwhile, for a predetermined period from the m+1th time onward among the n times, the candidate presentation unit 11, the target behavior setting unit 12, the implementation status recording unit 13, and the behavior analysis unit 16 are processed, and the candidate presentation unit 11 presents multiple target behavior candidates corresponding to multiple categories CL1 to CL4 in a distribution adjusted based on the feasibility or impossibility of each category CL1 to CL4. For example, if m=3, the behavior analysis unit 16 executes processing when setting a target behavior from the fourth week onward, and the candidate presentation unit 11 presents multiple target behavior candidates in a distribution adjusted based on the feasibility or impossibility of each category CL1 to CL4. At this time, the behavior analysis unit 16 analyzes the feasibility or impossibility of each category CL1 to CL4 for all of the implementation status information stored in the implementation status storage unit 22 at the time of analysis.

[0046] As described above, in the specified period from the m+1th time onwards, the number of presented target behavior candidates corresponding to the classification with the highest degree of feasibility will be 1, the number of presented target behavior candidates corresponding to the classification with the second highest degree of feasibility will be 2, the number of presented target behavior candidates corresponding to the classification with the third highest degree of feasibility will be 4, and the number of presented target behavior candidates corresponding to the classification with the lowest degree of feasibility will be 5.

[0047] The candidate presentation unit 11 may change the distribution ratio of the number of presented target behavior candidates during the processing for a predetermined period from the (m+1)th to the (n)th time. For example, the number of presented target behavior candidates may be distributed evenly from the first week to the third week, and the distribution ratio may be 2:3:3:4 in descending order of feasibility from the fourth week to the sixth week, and the distribution ratio of the target behavior candidates may be changed to 1:2:4:5 from the seventh week onwards.

[0048] 5 is a flowchart showing an example of the operation of the cognitive behavioral therapy support device 1 according to this embodiment configured as described above. The flowchart in FIG. 5 shows the flow of processing from the time when the target behavior for the first week is set.

[0049] First, the candidate presentation unit 11 presents 12 candidate target actions on a target action selection screen, with the number of actions corresponding to the multiple categories CL1 to CL4 adjusted to be evenly distributed, and prompts the user to answer which candidate target actions the user has been able to perform and to select a target action from among the candidate target actions the user has not been able to perform (step S1). Of the 12 candidate target actions presented on the target action selection screen, the user answers which actions the user has already performed and selects three candidate target actions the user has not been able to perform.

[0050] The answer input unit 14 inputs the answer information (information on the candidate target behaviors that the user has answered as being implemented) input by the user through the target behavior selection screen as described above (step S2), and the implementation status recording unit 13 acquires the answer information from the answer input unit 14 and records it in the implementation status storage unit 22 (step S3). Furthermore, the target behavior setting unit 12 sets the three candidate target behaviors selected by the user through the target behavior selection screen as target behaviors for the first week (step S4).

[0051] The achievement status input unit 15 then determines whether one week has passed since the target behavior was set by the target behavior setting unit 12 (step S5). If it determines that one week has passed, it presents an achievement status input screen to prompt the user to input the achievement status. In response, the user inputs the achievement status indicating whether the target behavior for the first week was performed within the specified period into the achievement status input screen, and the achievement status input unit 15 acquires the achievement status information (step S6). The implementation status recording unit 13 acquires the achievement status information from the achievement status input unit 15 and records it in the implementation status storage unit 22 (step S7).

[0052] Next, the candidate presentation unit 11 determines whether the predetermined period that has elapsed since the achievement status information was recorded in the implementation status storage unit 22 is less than three weeks (step S8). If the predetermined period has elapsed less than three weeks, the process returns to step S1. Initially, the predetermined period is one week, so the process returns to step S1, where the answer information entered through the target behavior selection screen is recorded in the implementation status storage unit 22, and the target behavior for the second week is set (steps S1 to S4). Then, one week after the target behavior for the second week was set, the achievement status information entered through the achievement status input screen is recorded in the implementation status storage unit 22 (steps S5 to S7).

[0053] At this stage, two weeks have passed since the predetermined period, so the process returns from step S8 to step S1, where the response information entered through the target behavior selection screen is recorded in the implementation status storage unit 22, and the target behavior for the third week is set (steps S1 to S4). Then, one week after the target behavior for the third week was set, the achievement status information entered through the achievement status input screen is recorded in the implementation status storage unit 22 (steps S5 to S7). At this stage, three weeks have passed since the predetermined period, so the process proceeds from step S8 to step S9, where the target behavior for the fourth week is set by the following process.

[0054] In step S9, the behavior analysis unit 16 determines whether the predetermined period that has elapsed since the achievement status information was recorded in the implementation status storage unit 22 in step S7 has reached the final 10 weeks. If the period has not reached 10 weeks, the behavior analysis unit 16 analyzes the degree to which the behavior can be implemented for each of the categories CL1 to CL4 based on the implementation status information stored in the implementation status storage unit 22 (step S11).

[0055] The candidate presentation unit 11 presents multiple target behavior candidates by adjusting the distribution so that the number of target behavior candidates corresponding to categories with a low degree of feasibility is greater than the number of target behavior candidates corresponding to categories with a high degree of feasibility based on the feasibility level for each of the categories CL1 to CL4 analyzed by the behavior analysis unit 16 (step S11). After that, the process returns to step S2, where the response information input through the target behavior selection screen is recorded in the implementation status storage unit 22 and the target behavior for the fourth week is set (steps S2 to S4).

[0056] Then, one week after the fourth week's target behavior was set, the progress status information entered through the progress status input screen is recorded in the implementation status storage unit 22 (steps S5 to S7). At this stage, four weeks have passed since the predetermined period, so the process proceeds from step S8 to step S9, and then from step S9 to step S10. This process flow is repeated until the predetermined period reaches the final ten weeks, at which point the process of the flowchart shown in FIG. 5 ends.

[0057] As described above in detail, in this embodiment, one or more target behavior candidates selected by the user from among multiple target behavior candidates presented on the target behavior selection screen are set as target behaviors for a predetermined period, and implementation status information (answer information and achievement status information) indicating whether or not the user can perform some or all of the behaviors represented by the multiple target behavior candidates is obtained and recorded in the implementation status storage unit 22. Then, when multiple target behavior candidates for the next predetermined period are presented to the user upon the end of one predetermined period, the system adjusts the distribution based on the degree of feasibility for each of the categories CL1 to CL4 analyzed based on the implementation status information recorded in the implementation status storage unit 22 so that the number of target behavior candidates corresponding to a category with a low degree of feasibility is greater than the number of target behavior candidates corresponding to a category with a high degree of feasibility, and presents the multiple target behavior candidates for the next predetermined period.

[0058] According to this embodiment configured as described above, the multiple candidate target actions presented to the user when setting a target action for a given period are adjusted to increase the number of actions that the user is unable to perform due to tinnitus, thereby creating a situation in which unachieved actions are more likely to be set as target actions and preventing unachieved actions from remaining unachieved. As a result, this embodiment can use information processing technology to support the implementation of behavioral training that can effectively reduce the number of actions that the user is unable to perform due to tinnitus.

[0059] The algorithm for selecting target behavior candidates described in the above embodiment is merely an example, and the present invention is not limited to this method. For example, the number of target behavior candidates to be presented may be determined as in the following modified example.

[0060] <Modification> For example, the behavior analysis unit 16 may calculate the proportion of possible actions or impossible actions for each of the decomposition element properties that define the nature of the actions, based on the implementation status information recorded in the implementation status memory unit 22 by the implementation status recording unit 13, and determine the number of candidate target actions to be presented for each of the categories CL1 to CL4 based on the calculated proportions.

[0061] Here, the decomposition element properties that define the behavioral characteristics refer to individual element properties obtained by decomposing the behavioral characteristics defined in the categories CL1 to CL4. In other words, the four decomposition element properties related to the categories CL1 to CL4 are "alone," "other people," "indoors," and "outdoors." Note that, while the above embodiment describes an example in which behavioral data is assigned to one of the four categories CL1 to CL4, this is not limiting. For example, as shown in FIG. 6 , the decomposition element properties related to the number of people may be "one person," "two people," and "three or more people," and the decomposition element properties related to the location may be "home," "indoors other than home," and "outdoors," and the behavioral data may be assigned to one of nine categories CL1 to CL9.

[0062] For the sake of explanation, the three decomposition element properties related to the number of people will be represented by the symbols A1 to A3, and the three decomposition element properties related to the location will be represented by the symbols B1 to B3. In this case, the properties can be expressed mathematically as follows: CL1 = A1 x B1, CL2 = A2 x B1, CL3 = A3 x B1, CL4 = A1 x B2, CL5 = A2 x B2, CL6 = A3 x B2, CL7 = A1 x B3, CL8 = A2 x B3, CL9 = A3 x B3.

[0063] Fig. 7 is a block diagram showing a specific example of the functional configuration of the behavior analysis unit 16 in a modified example. As shown in Fig. 7, the behavior analysis unit 16 includes, as specific functional configurations, an element-specific executable ratio calculation unit 16a, an element-specific presentation ratio calculation unit 16b, and a category-specific presentation ratio calculation unit 16c. Fig. 8 is a diagram showing an example for explaining the processing contents of the element-specific presentation ratio calculation unit 16b and the category-specific presentation ratio calculation unit 16c.

[0064] The element-specific feasibility ratio calculation unit 16a calculates the feasibility ratio for each of the decomposition element properties A1 to A3 and B1 to B3, for example. For example, when implementation status information of "feasible" is recorded for an action corresponding to the first category CL1, the element-specific feasibility ratio calculation unit 16a recognizes that the decomposition element property A1 related to the number of people and the decomposition element property B1 related to the location for that action have been recorded as "feasible." Conversely, when implementation status information of "not feasible" is recorded for an action corresponding to the first category CL1, the element-specific feasibility ratio calculation unit 16a recognizes that the decomposition element property A1 related to the number of people and the decomposition element property B1 related to the location for that action have been recorded as "not feasible." The same applies to the other categories CL2 to CL9.

[0065] The element-specific executable ratio calculation unit 16a counts the number of executable and infeasible actions for each decomposition element property recognized as above, and calculates the executable ratio (hereinafter referred to as the element-specific executable ratio) for each decomposition element property. For example, for decomposition element property A1, the element-specific executable ratio is calculated by dividing the number of executable actions by (the number of executable actions + the number of infeasible actions) by 100. The element-specific executable ratios are calculated in the same manner for the other decomposition element properties A2 to A3 and B1 to B3.

[0066] The element-specific presentation ratio calculation unit 16b calculates the presentation ratio of the target behavior candidate for each of the decomposition element properties A1 to A3 and B1 to B3 (hereinafter referred to as "element-specific presentation ratio") based on the element-specific implementation ratio calculated by the element-specific implementation ratio calculation unit 16a. For example, the element-specific presentation ratio calculation unit 16b assigns a predetermined coefficient to the decomposition element properties A1 to A3 and B1 to B3 depending on whether the element-specific implementation ratio is equal to or greater than a threshold, and calculates the element-specific presentation ratio based on the assigned coefficient.

[0067] First, the element-specific executable ratio calculation unit 16a assigns a predetermined coefficient to the decomposition element properties A1 to A3, B1 to B3 depending on whether the element-specific executable ratio is equal to or greater than a threshold. For example, if the element-specific executable ratio is equal to or greater than the threshold, a coefficient x1 is assigned, and if the element-specific executable ratio is less than the threshold, a coefficient x2 (where x1<x2, x1+x2=1) is assigned. As an example, the threshold is 80%, the coefficient x1=0.2, and the coefficient x2=0.8. Figure 8(a) shows an example of assigning coefficients to the decomposition element properties A1 to A3, B1 to B3.

[0068] Furthermore, the element-specific presentation rate calculation unit 16b calculates the ratio of the coefficient of each of the decomposition element properties A1 to A3 to the sum of the coefficients of the decomposition element properties A1 to A3 related to the number of people, for each of the decomposition element properties A1 to A3, and calculates the ratio of the coefficient of each of the decomposition element properties B1 to B3 to the sum of the coefficients of the decomposition element properties B1 to B3 related to the location, for each of the decomposition element properties B1 to B3, thereby calculating the element-specific presentation rate. FIG. 8B shows an example of a calculation of the element-specific presentation rate. In the example shown in FIG. 8B, the sum of the coefficients of the decomposition element properties A1 to A3 related to the number of people is 0.8 + 0.8 + 0.2 = 1.8. For example, for the decomposition element property A1, the coefficient 0.8 is divided by the sum of the coefficients 1.8 × 100, resulting in an element-specific presentation rate of 44%.

[0069] The category-specific presentation ratio calculation unit 16c calculates the presentation ratio of the target behavior candidates for each of the categories CL1 to CL9 (hereinafter referred to as the category-specific presentation ratio) based on the element-specific presentation ratios calculated by the element-specific presentation ratio calculation unit 16b. For example, for the category-specific presentation ratio for the first category CL1 defined by the formula CL1 = A1 × B1, the category-specific presentation ratio calculation unit 16c calculates the category-specific presentation ratio by multiplying the element-specific presentation ratio of the decomposition element property A1 related to the number of people by the element-specific presentation ratio of the decomposition element property B1 related to the location. Figure 8(c) shows an example of calculating the category-specific presentation ratio.

[0070] The candidate presentation unit 11 adjusts and presents the number of target behavior candidates to be presented for each of the categories CL1 to CL9 according to the category presentation ratios shown in Fig. 8(c). That is, the candidate presentation unit 11 normalizes the category presentation ratios shown in Fig. 8(c) so that the total becomes 100%, and then determines the number of target behavior candidates to be presented for each of the categories CL1 to CL9 by multiplying the normalized category presentation ratios by 12. Here, if the calculation result of the category presentation ratios by 12 is not an integer, the result is converted to an integer by rounding up, rounding down, or rounding up.

[0071] Note that the number of elemental characteristics relating to the number of people and the number of elemental characteristics relating to the location do not necessarily have to be the same. Furthermore, at least one of the elemental characteristics relating to the number of people and the elemental characteristics relating to the location may be four or more. In this case, the number of categories CL may be greater than the number of target behavior candidates (12) presented to the user. Even in this case, the embodiment of FIG. 4 and the modified example of FIG. 7 can be applied. For example, in the embodiment shown in FIG. 4 , a process can be set in which the number of presented target behavior candidates is set to 0. Furthermore, in the modified example shown in FIG. 7 , the number of presented target behavior candidates can be determined in descending order of the value calculated by multiplying the presentation rate by category by 12, and the process can be terminated when the total number reaches 12. Alternatively, a number of target behavior candidates greater than the number of categories may be presented (for example, if the number of categories is 16, the number of presented target behavior candidates can be set to 20).

[0072] Furthermore, in the above embodiment and the above modified example, the user may be prompted to respond to a question about the progress of the set target behavior during a predetermined period, and if a response indicating poor progress is entered, a process to lower the difficulty level of the target behavior may be executed. Responses indicating poor progress may be, for example, "not performed at all" or "attempted to perform once but failed, then stopped performing." The process to lower the difficulty level of the target behavior may, for example, be a process of identifying a category with a high degree of feasibility based on the implementation status information stored in the implementation status storage unit 22, re-presenting candidate target behaviors corresponding to that category, and allowing the user to select one. Alternatively, a process of withdrawing a target behavior with poor progress may be executed.

[0073] In addition, during the specified period, the user may be asked to respond about the progress of the set target behavior, and depending on the content of the response, advice on carrying out the target behavior for the remaining number of days in the specified period may be displayed.

[0074] In the above embodiment and modified example, an example has been described in which options for candidate target actions are presented, but in addition to selecting from the options, a target action may be set by inputting free text. When inputting free text to set a target action, the corresponding classification may also be input, so that the target action in free text and the classification can be managed in association with each other.

[0075] In the above embodiment and modified example, the answer information of "possible to implement" input through the target behavior selection screen and the achievement status information of "possible to implement" or "not possible to implement" input through the achievement status input screen are recorded as implementation status information in the implementation status storage unit 22. However, only the answer information or only the achievement status information may be recorded as implementation status information in the implementation status storage unit 22. In the former case, the behavior analysis unit 16 analyzes the degree of feasibility / impossibility for each category based on the answer information. In the latter case, the behavior analysis unit 16 analyzes the degree of feasibility / impossibility for each category based on the achievement status information recorded for each target behavior.

[0076] In the above embodiment and modified example, the behavior analysis unit 16 analyzes the degree of "possibility" of a behavior for each classification set according to the nature of the behavior. However, the behavior analysis unit 16 may analyze the degree of "impossibility." In this case, the candidate presentation unit 11 presents multiple target behavior candidates for the next predetermined period by adjusting the distribution so that the number of target behavior candidates corresponding to a classification with a high degree of impossibility is greater than the number of target behavior candidates corresponding to a classification with a low degree of impossibility.

[0077] Furthermore, in the above embodiment and the above modified example, an example has been described in which the behavior analysis unit 16 analyzes the degree of feasibility of each category of behavior. However, the present invention is not limited to this. For example, the degree of feasibility or impossibility of a user's behavior (the difficulty of the behavior) may be set in advance for each category. For example, the difficulty of the behaviors related to the first category CL1, which is set to "behavior performed alone indoors," the second category CL2, which is set to "behavior performed alone outdoors," the third category CL3, which is set to "behavior performed indoors with others," and the fourth category CL4, which is set to "behavior performed outdoors with others," may be set in advance so that CL1 < CL2 < CL3 < CL4.

[0078] As another example, the difficulty level of each target behavior candidate may be set in advance, and target behavior candidates with similar levels of difficulty may be assigned the same classification. The difficulty level for each target behavior candidate may be set from any perspective, not just from the perspective of the nature of the behavior (whether the behavior is performed alone or with others, or whether the behavior is performed indoors or outdoors). The number of difficulty ranks to be set may also be arbitrary, and in this case, a number of classifications corresponding to the number of ranks will be set. For example, one of four difficulty levels may be set for each of multiple target behavior candidates based on an arbitrary perspective, and multiple target behavior candidates may be sorted into four classifications CL11, CL12, CL13, and CL14 so that target behavior candidates with the same difficulty level are in the same classification.

[0079] In the above embodiment and modified example, the cognitive behavioral therapy support device 1 is configured to include all of the functional blocks 11 to 16 and the storage units 21 to 22 shown in Fig. 1, but the present invention is not limited to this. For example, a cognitive behavioral therapy support system may be configured by a terminal on which a cognitive behavioral therapy support app is installed and a server device connected to the terminal via a communication network such as the Internet and / or a mobile phone network, and the functional blocks 11 to 16 and the storage units 21 to 22 may be distributed between the terminal and the server device.

[0080] Furthermore, the above-described embodiments are merely examples of specific embodiments for carrying out the present invention, and the technical scope of the present invention should not be construed as being limited thereby. In other words, the present invention can be carried out in various forms without departing from the gist or main characteristics thereof.

[0081] REFERENCE SIGNS LIST 1 Cognitive behavioral therapy support device 11 Candidate presentation unit 12 Target behavior setting unit 13 Implementation status recording unit 14 Answer input unit 15 Achievement status input unit 16 Behavior analysis unit 16a Element-specific implementation feasibility ratio calculation unit 16b Element-specific presentation ratio calculation unit 16c Classification-specific presentation ratio calculation unit 21 Behavior storage unit 22 Implementation status storage unit

Claims

1. A cognitive behavioral therapy support device comprising: a candidate presentation unit that presents a plurality of target behavior candidates and prompts a user to select one; and a target behavior setting unit that sets one or more target behavior candidates selected by the user as target behaviors for a specified period of time, wherein the candidate presentation unit presents the plurality of target behavior candidates by adjusting the distribution based on the degree to which the user can or cannot perform the behavior for each classification set for the behavior so that the number of target behavior candidates that fall into a classification with a low degree of feasibility or a classification with a high degree of infeasibility is greater than the number of target behavior candidates that fall into a classification with a high degree of feasibility or a classification with a low degree of infeasibility.

2. The cognitive behavioral therapy support device of claim 1, further comprising: an implementation status recording unit that acquires and records implementation status information indicating whether or not the user can perform some or all of the actions indicated by the multiple target behavior candidates presented by the candidate presentation unit; and a behavior analysis unit that analyzes the degree of feasibility or impossibility of the actions for each of the categories set according to the nature of the actions based on the implementation status information, wherein the candidate presentation unit adjusts the distribution based on the degree of feasibility or impossibility for each category analyzed by the behavior analysis unit at the end of a specified period so that the number of target behavior candidates that fall into a category with a low degree of feasibility or a category with a high degree of impossibility is greater than the number of target behavior candidates that fall into a category with a high degree of feasibility or a category with a low degree of impossibility, and presents the multiple target behavior candidates for the next specified period.

3. The cognitive behavioral therapy support device described in claim 2, characterized in that the implementation status recording unit acquires and records achievement status information indicating the achievement status of the target behavior selected by the user as the implementation status information regarding some of the multiple target behavior candidates presented by the candidate presentation unit, and the behavior analysis unit analyzes the degree of feasibility of implementation for each of the categories based on the achievement status information recorded for each target behavior.

4. The cognitive behavioral therapy support device described in claim 2, characterized in that the candidate presentation unit presents the multiple target behavior candidates and prompts the user to answer which target behavior candidates the user can perform and to select the target behavior from among the target behavior candidates the user cannot perform; the implementation status recording unit acquires and records answer information by the user as the implementation status information regarding some or all of the multiple target behavior candidates presented by the candidate presentation unit, and acquires and records achievement status information indicating the achievement status of the target behavior selected by the user; and the behavior analysis unit analyzes the degree of feasibility of implementation for each of the categories based on the answer information and the achievement status information.

5. The cognitive behavioral therapy support device described in claim 2, characterized in that the candidate presentation unit presents the multiple target behavior candidates and prompts the user to answer which target behavior candidates the user can perform and to select the target behavior from among the target behavior candidates the user cannot perform; the implementation status recording unit acquires and records the user's response information as the implementation status information regarding some or all of the multiple target behavior candidates presented by the candidate presentation unit; and the behavior analysis unit analyzes the degree of feasibility of each category based on the response information.

6. A cognitive behavioral therapy support device as described in any one of claims 2 to 5, characterized in that, when processing is repeatedly executed over n (n≧2) predetermined periods, during the first m (1≦m<n) predetermined periods, the behavior analysis unit does not perform processing, but performs processing by the candidate presentation unit, the target behavior setting unit, and the implementation status recording unit, and the candidate presentation unit presents the multiple target behavior candidates that fall into the multiple categories in an equal distribution; and during the m+1th and subsequent predetermined periods out of the n times, the candidate presentation unit, the target behavior setting unit, the implementation status recording unit, and the behavior analysis unit perform processing, and the candidate presentation unit presents the multiple target behavior candidates that fall into the multiple categories in a distribution adjusted based on the degree of feasibility of each category.

7. The cognitive behavioral therapy support device described in claim 6, characterized in that the candidate presentation unit changes the distribution ratio of the number of presented target behavior candidates for each category during the processing of a specified period from the m+1th to the nth times.

8. A cognitive behavioral therapy support device as described in any one of claims 2 to 5, characterized in that the implementation status recording unit assigns points to actions that can be performed or cannot be performed and records implementation status information, the behavior analysis unit calculates the total value of the points for each of the categories to analyze the degree to which the actions can be performed or cannot be performed for each of the categories, and the candidate presentation unit determines the number of target behavior candidates to be presented for each of the categories based on the total value of points calculated for each of the categories by the behavior analysis unit.

9. A cognitive behavioral therapy support device as described in any one of claims 2 to 5, characterized in that the behavior analysis unit analyzes the degree to which the behavior can be performed or cannot be performed for each of the categories by counting the number of behaviors recorded as performable or not performable by the implementation status recording unit for each of the categories, and the candidate presentation unit determines the number of target behavior candidates to be presented for each of the categories based on the value counted for each of the categories by the behavior analysis unit.

10. A cognitive behavioral therapy support device as described in any one of claims 2 to 5, characterized in that the behavior analysis unit calculates the proportion of behaviors that are executable or not executable for each of the decomposition element properties that define the nature of the behavior recorded by the implementation status recording unit, and determines the number of target behavior candidates to be presented for each of the classifications related to the nature of the behavior identified by a combination of multiple of the decomposition element properties based on the calculated proportions.

11. A cognitive behavioral therapy support device as described in claim 1, characterized in that the classification is set according to the nature of the behavior, and the degree to which the user can or cannot perform the behavior is set in advance for each classification.

12. A cognitive behavioral therapy support device as described in claim 1, characterized in that the degree to which the user can or cannot perform the behavior is set in advance for each of the target behavior candidates, and the same classification is set for target behavior candidates of the same degree.

13. A cognitive behavioral therapy support system comprising: a candidate presentation unit that presents a plurality of target behavior candidates and prompts a user to select one; and a target behavior setting unit that sets one or more target behavior candidates selected by the user as target behaviors for a predetermined period, wherein the candidate presentation unit presents the plurality of target behavior candidates by adjusting the distribution based on the degree to which the user can or cannot perform the behavior for each classification set for the behavior so that the number of target behavior candidates that fall into a classification with a low degree of feasibility or a classification with a high degree of infeasibility is greater than the number of target behavior candidates that fall into a classification with a high degree of feasibility or a classification with a low degree of infeasibility.

14. A cognitive behavioral therapy support system as described in claim 13, further comprising: an implementation status recording unit that acquires and records implementation status information indicating whether or not the user can perform some or all of the actions indicated by the multiple target behavior candidates presented by the candidate presentation unit; and a behavior analysis unit that analyzes the degree of feasibility or impossibility of the actions for each of the categories set according to the nature of the actions based on the implementation status information, wherein the candidate presentation unit adjusts the distribution based on the degree of feasibility or impossibility for each category analyzed by the behavior analysis unit at the end of a specified period so that the number of target behavior candidates that fall into a category with a low degree of feasibility or a category with a high degree of impossibility is greater than the number of target behavior candidates that fall into a category with a high degree of feasibility or a category with a low degree of impossibility, and presents the multiple target behavior candidates for the next specified period.

15. A cognitive behavioral therapy support program that causes a computer to execute a candidate presentation process that presents multiple target behavior candidates and prompts the user to make a selection, and a target behavior setting process that sets one or more target behavior candidates selected by the user as target behaviors for a specified period, wherein in the candidate presentation process, the multiple target behavior candidates are presented by adjusting the distribution based on the degree to which the user can or cannot perform the behavior for each classification set for the behavior so that the number of target behavior candidates that fall into a classification with a low degree of feasibility or a classification with a high degree of infeasibility is greater than the number of target behavior candidates that fall into a classification with a high degree of feasibility or a classification with a low degree of infeasibility.

16. The cognitive behavioral therapy support program of claim 15, further comprising causing the computer to execute an implementation status recording process that acquires and records implementation status information indicating whether or not the user can perform some or all of the actions indicated by the multiple target behavior candidates presented by the candidate presentation process, and a behavior analysis process that analyzes the degree of feasibility or impossibility of the actions for each of the categories set according to the nature of the actions based on the implementation status information, wherein in the candidate presentation process, based on the degree of feasibility or impossibility for each category analyzed by the behavior analysis process at the end of a specified period, the multiple target behavior candidates for the next specified period are presented by adjusting the distribution so that the number of target behavior candidates that fall into a category with a low degree of feasibility or a category with a high degree of impossibility is greater than the number of target behavior candidates that fall into a category with a high degree of feasibility or a category with a low degree of impossibility.

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