JP6426319B1 - Stress fatigue evaluation / health guidance support apparatus and method, and computer program - Google Patents

Abstract

[Issue] Support health guidance according to stress fatigue of workers.
A stress / fatigue evaluation / health guidance device (1) comprises: input means (11) capable of inputting a data set relating to stress fatigue acquired in a form in which each subject answers a question group; Based on the function output of the subject response data set for the function defined by performing multivariate analysis on the performance response data set answered by multiple workers who worked in the environment, based on the function output And analysis means (20) for estimating measures for the symptoms related to stress fatigue of each subject, and image output means (12, 13) for outputting an image of the estimated measures.
[Selected figure] Figure 1

Description

  The present invention is effective for stress fatigue, for example, according to the evaluation result of mental or physical health condition (herein, simply referred to as “stress fatigue” in the present application) of industrial physicians, for example, employees of a company. Stress / fatigue evaluation / health guidance support apparatus and method for supporting health or treatment or prevention guidance presenting a countermeasure (hereinafter referred to simply as "health guidance" in the present application) and computer program for causing a computer to function as such apparatus Belongs to the technical field of

  As devices related to this type of device, various devices have been proposed which detect or acquire vital signs and the like, and estimate or detect fatigue level, stress state, depression state, etc. based on them (Patent Document 1 6).

  On the other hand, industrial physicians conduct stress surveys, etc. for which employers are required to make efforts by the Ministry of Health, Labor and Welfare (for example, the Ministry of Health, Labor and Welfare version stress check program, job stress simple questionnaire, work place that can be done in 5 minutes Stress self-check (http://kokoro.mhlw.go.jp/check/ etc.), and provide health guidance based on their own experiences or according to the textbook according to the result. At this time, the computer is used for data collection, recording, output and the like.

JP, 2009-219683, A Unexamined-Japanese-Patent No. 2010-234000 JP 2012-75708 A JP, 2013-182493, A JP, 2014-121410, A Unexamined-Japanese-Patent No. 2017-153963

  However, according to the various devices described above, estimation and detection become possible only after detection of vital signs and the like. The estimation and detection of mental diseases and the like that hardly appear or are difficult to detect in vital signs and the like becomes fundamentally difficult.

  On the other hand, in a method in which an industrial physician investigates stress fatigue by interviewing, "an answer to a question" can not be obtained satisfactorily due to the low awareness of the respondent or the questioner. If it is attempted to execute computer analysis (ie, AI analysis or big data analysis) such as multivariate analysis on the answers collected in this way, the quantity and quality necessary to associate the answer of the question with the countermeasure etc. There has been no record of data being taken. In addition, under laws such as the Labor Standards Act and the Personal Information Protection Act, collecting data in long working hours and illegal working environments as a potentially important part of this type of data is now and in the future It is virtually impossible. For these reasons, the idea itself to collect the data and to use it is itself totally unexpected to the doctor or person skilled in the art.

  Under such a background, when using the above-mentioned various devices and inquiries, health guidance by the industrial physician includes the total number of employees, the time required for interviews and health guidance for each employee, the capacity of the industrial physician, etc. From that, it is impossible to practice as a real problem. For example, as of the end of June 2017, the implementation rate of interview guidance for “10% of highly stressed people”, which is legally obligatory, is only 0.6%.

  The present invention has been made in view of the above problems, and is capable of supporting health guidance according to stress fatigue of workers, employees, etc. with relative ease, stress fatigue evaluation / health guidance device and method The challenge is to provide Another object is to provide a computer program capable of causing a computer to function as such a device.

  The stress / fatigue evaluation / health guidance support device according to the present invention is a cause system related to stress / fatigue acquired in a format in which each subject answers a predetermined question group displayed on a screen or in a document in order to solve the above problems. The answer data of the response system, the response data of the corresponding system related to stress fatigue, and the response data of the symptom system related to stress fatigue If the analysis command is issued or added to this, it is the actual response data set that has been accumulated in the past and has been answered by multiple workers who worked in the previous working environment, and the actual response data It is sufficient to define a function that relates the response data of the causal system and the response data of the corresponding system with the response data of the symptom system in multivariate analysis on a set. Function input of the input subject answer data set with respect to the function defined by performing the multivariate analysis on the actual result data set with few or no omissions The system comprises: analysis means for estimating a countermeasure for a symptom related to stress fatigue of each subject based on the output; and image output means for outputting an image of the estimated countermeasure in a predetermined health instruction book format.

The stress fatigue evaluation / health guidance support method of the present invention is a causative system related to stress fatigue acquired in a format in which each subject answers a predetermined question group displayed on a screen or in a document in order to solve the above problems. When the subject response data set is input in the input step of inputting a subject response data set including the response data of the response system, the response data of the response system related to stress fatigue, and the response data of the symptom system related to stress fatigue; Or, in addition to this, when an analysis order is issued, this is a performance response data set that has been accumulated in the past and has been answered by a plurality of workers who worked in the previous working environment, It is sufficient to define a function that relates the response data of the causal system and the response data of the corresponding system with the response data of the symptom system in the variable analysis. Function input of the input subject answer data set with respect to the function defined by performing the multivariate analysis on the actual result data set with few or no omissions It comprises an analysis step of estimating measures for the stress fatigue related symptoms of each subject based on the output, and an image output step of outputting the estimated measures in the form of a predetermined health instruction book. The computer program of the present invention causes a computer to function as the above-described stress fatigue evaluation / health guidance device according to the present invention in order to solve the above-mentioned problems.

  These effects and other advantages of the present invention are clarified by the embodiments described hereinafter.

<Stress fatigue evaluation and health guidance device>
<1>
The stress / fatigue evaluation / health guidance support device according to the present embodiment is a response data of a causative system related to stress / fatigue acquired in a format in which each subject answers a predetermined question group displayed on an image or a document, stress / fatigue An input unit capable of inputting a subject response data set including response data of a response system according to claim 1 and response data of a symptom system related to stress fatigue, and when the subject response data set is input through the input unit In addition, when an analysis order is issued, this is a result response data set that has been accumulated in the past and has been answered by a plurality of workers who worked in the previous working environment, and is a multivariate analysis on the result response data set. The number of gaps is small enough to define a function that relates the response data of the cause system and the response data of the response system to the response data of the symptom system Based on the function output of the function, the function answer of the input subject answer data set is input to the function that is determined by performing the multivariate analysis to the non-actual result answer data set. The system comprises: analysis means for estimating a countermeasure for a symptom related to stress fatigue of each subject; and image output means for outputting an image of the estimated countermeasure in a predetermined health instruction book format.

  The stress / fatigue evaluation / health guidance support device according to the present embodiment is, for example, a predetermined group of questions displayed on a screen of a display or a document via an input unit (for example, 138 questions in the ESAIT system described later) The subject answer data set is input in the form that each subject answers to. The input may be performed by each subject using a keyboard, a tablet, a touch panel, a mouse, cursor operation, voice input, etc., which constitute an example of the input means. Alternatively, a sheet (for example, an OMR sheet etc.) marked with an answer by each subject may be read from a reader constituting an example of the input means, or a doctor or assistant who has obtained an answer via a questionnaire or verbally The operator may perform input operation via such input means on behalf of each subject.

  The “each subject” or the “subject” according to the present embodiment is, for example, a worker, an employee, an employee, an employee, or the like who belongs to a company that the industrial physician takes charge of.

  The “subject response data set” according to the present embodiment includes: (1) “must do a lot of work”, “can not handle work in time”, “do work at my own pace” (2) For example, response data related to stress fatigue such as “do sports”, “refresh with family”, “do massaging foot massage” and (3) For example, it includes response data of symptoms related to stress and fatigue such as "dizziness", "headache", and "it is difficult to stay in a person".

  Specifically, response data indicating options (for example, 2 options or 3 options to 5 options) in one question belonging to such a question group is collected for a plurality of questions for one subject, The corresponding answer group is the subject answer data set specific to this subject. Each answer data is, for example, data indicating which option the answer to a certain question is composed of the question identification number or code and the choice identification number or code. For example, if the serial number of the question is 16 and the number of the selected option is 3, the answer data will be "Data 16-3" in code notation.

  The response data of the cause system and the response data of the response system may be completely and intentionally separated and independently set from the beginning of the question preparation, and instead of such response data, both of the response system and the response system may be set. The response data which is also captured by the correspondence system or has both of these characteristics may occupy a part or all of the cause system data of the subject response data set and the correspondence system data.

  The analysis means receives the subject answer data set input through the input means, or when the analysis command is given in addition to this, the subject answer data set input as described above is input to the function. Then, based on the output of the function, measures against symptoms related to stress fatigue of each subject (for example, based on the correlation between the answer data of the symptom system and the answer data of the cause system, the subject specific to the subject) Specific to the subject based on the level of correlation between the response data of the symptom system and the response data of the response system, such as preventive actions such as reduction, elimination, and improvement of the cause considered to be the cause of the stress fatigue symptoms. Measures to prevent or ameliorate or reduce stress fatigue, such as measures that are effective for ameliorating the symptoms of stress fatigue in the "Or referred to as a" corresponding measures for symptoms "), such as an effective countermeasure against symptoms of stress fatigue) to estimate.

  Here, the “result reply data set” according to the present embodiment is a result reply data set which is accumulated in the past and is answered by a plurality of workers who worked in the previous working environment, and the result reply data set The result response data set with few or no omissions enough to define the function that relates the response data of the cause system and the response data of the response system and the response data of the symptom system in multivariate analysis for For example, the “full data set for stress fatigue survey” described below, which includes a working environment that is overly illegal or virtually impossible to obtain. The performance response data set is composed of a plurality of data (for example, a collection of test subject response data sets of a large number such as hundreds in the past) of the same or similar data as the test subject response data set of each subject. In particular, the actual response data set can be used in harsh working environments, such as now over 200 hours a month or 300 hours overtime, which are not currently legally or virtually accepted or data can be taken seriously. Includes data answered by workers who have worked.

  The function used by the analysis means is that multivariate analysis is performed on such a performance response data set (that is, strict multivariate analysis based on a data set with completeness and toughness is performed). , Is predetermined. In particular, stress-fatigue response has many symptoms common to both adaptation disorder and depressiveness, and it is possible to classify severity (for example, refer to ICD-10 in international classification), regardless of the cause, There is a basic basis that fatigue causes universal symptoms according to graded intensity. Under this principle, multivariate analysis is performed using the response data of the causative system and the response data of the corresponding system as independent variables and the response data of the symptom system as dependent variables, the causative system response data and the symptom system The correlation data with the response data of can be obtained significantly, and the response data of the corresponding system can be correlated significantly with the response data of the symptom system.

  The analysis means takes measures against stress fatigue related symptoms of each subject based on the function output in which the input subject response data set is a function input in the function thus determined (for example, “sports” It is better to incorporate measures such as “to go to massage”, “preventing holidays” and “disappearing late at night” etc.

  For example, using the “full data set for stress fatigue survey” described below, multivariate analysis shows that extremely strong correlation can be obtained among a large number of response data, and the function generates a function output according to the purpose. It is defined as a function to Therefore, the estimation of the countermeasure based on the function output of the function (or the estimation of the symptom based on the function output of the function and the estimation of the effective countermeasure for the estimated symptom) is accordingly likely or significant It becomes one.

  At this time, in addition to estimating the countermeasure as described above, the analysis means is a symptom related to stress fatigue of each subject based on the function output of the function (for example, main components of high stress and stress fatigue, In particular, stress fatigue signs that easily appear on oneself may be estimated.

  The image output means outputs the image of the countermeasure thus estimated in a predetermined health instruction book format (for example, in the form of an interview instruction reference material) (ie, typically an image output by a display or printing by a printer) Output.

  Note that the image output unit is an image of the estimated symptom in a predetermined evaluation document format (for example, in the form of comprehensive evaluation) in parallel with or simultaneously with or in parallel with the image output of such countermeasure. You may output it.

  As described above in detail, according to the present embodiment, if the subject answer data set acquired for each subject is function input to the analysis means, measures (or symptoms and measures) are estimated and further estimated. The countermeasure is individually output in the format of the health instruction manual (or the estimated symptoms and the estimated countermeasure are output in the format of the evaluation document and the format of the health instruction manual, respectively).

Therefore, it becomes possible for industrial physicians and the like to give health instructions to the respective subjects while referring to the health instruction book on which the countermeasure has been presented or specified. Depending on the situation, it may be possible for an assistant or the like to give health guidance without an industrial physician, or for each subject to view a health instruction book (or an evaluation book and a health instruction book) without an industrial physician. That is, according to the present embodiment, it is possible to easily support health guidance according to the stress fatigue of each worker or each employee who belongs to the company or the like who is each subject.
<2>
In one aspect of the present embodiment, the analysis means estimates a symptom related to stress fatigue of each subject based on the function output, estimates a countermeasure for the estimated symptom as the countermeasure, and The image output means outputs the image of the estimated symptom in the form of a predetermined evaluation sheet in parallel with or in parallel with the image output of the estimated countermeasure.

According to this aspect, by inputting the subject answer data set to a predetermined function, the symptom of each subject (for example, main components of high stress and stress fatigue, specifically, based on the function output) Are stress fatigue signs that easily appear to you such as “anxiety”, “body complaints”, stress fatigue that is occurring today or now such as “fatigue” or “irritability”, or personal scores related to symptoms, in other words For example, an evaluation related to a symptom of stress fatigue is estimated, and an effective countermeasure (for example, a countermeasure that it is better to adopt it) is estimated for the estimated symptom. Furthermore, these are output as images in the format of the evaluation book and the health instruction book. Therefore, it becomes possible for an industrial physician etc. to give interview guidance, television interview guidance, etc. to each subject, considering both an evaluation book and a health instruction book as reference information in the same page or in multiple pages. It becomes very convenient in practical use.
<3>
In another aspect of this embodiment, the function is a relationship between the response data of the cause system and the response data of the symptom system by principal component analysis and multiple regression analysis as the multivariate analysis, and the response data of the correspondence system. It is a function defined by deriving the relationship with the response data of the symptom system.

According to this aspect, it is possible to sequentially generate a smaller number of composite variables as principal components while weighting the response data of the large number of variables such as the causative system and the corresponding system and the symptom system by the principal component analysis. Integrate variables. The weighting here is performed such that the principal component contains as much information content of the original variable as possible. A regression equation for estimating a dependent variable (for example, response data of a symptom system) from the independent variables (for example, response data of a causative system and response data of a corresponding system) is obtained by multiple regression analysis. That is, it is determined whether or not an independent variable (for example, response data of the causative system and response data of the corresponding system) significantly affects the dependent variable (for example, response data of the symptom system). By performing these analyzes in advance, the function used by the analysis means is determined from the result response data set. Thus, by using the existing analysis method, it becomes possible to determine the function relatively easily and reliably, and the analysis processing by the analysis means becomes easy and can be executed later.
<4>
In another aspect of the present embodiment, the analysis means may be a difference group of response data of the cause system for each subject and a difference group of response data of the corresponding system for each subject (e.g., specifically, By executing the simulation with the function input for the function, the choice of the cause and the choice of the cause that intentionally makes a difference between strength, high, low, early and late etc. with respect to the cause and the response in each subject's answer. The symptom reduction prediction is performed so that the symptom of each subject is statistically reduced or improved (ideally, optimized), and the countermeasure is estimated based on the result of the symptom reduction prediction.

According to this aspect, the analysis means uses the difference group of the response data as the function input. Here, “difference group” intentionally makes a difference in the degree of load, magnitude, strength, high / low, early / late, etc. with respect to the cause or response in each subject's answer (ie, selected in the subject's answer) It means a plurality of cause options or a plurality of corresponding options, such as selecting an option different from an option. Then, the symptom is improved or reduced on the simulation result of the difference group compared with the symptom estimated for the subject (ideally, it is most improved or reduced, in other words, optimized) The response data of the cause system or the response system at the time of Mutual comparison or relative evaluation or absolute evaluation of the degree of symptom reduction in the difference group is estimated to have the most or relatively effective effect on symptom reduction, such as the cause to be eliminated or the action to be taken. Become.
<5>
In another aspect of the present embodiment, the analysis unit first estimates, as the correspondence, the one of a plurality of predetermined measures, which has the largest effect, and then, among the plurality of measures. We estimate what is the second most effective, and then estimate what is better than adopting one of the multiple measures.

According to this aspect, the countermeasure with the largest effect, the countermeasure with the second effect, and a countermeasure better than not incorporating it are respectively estimated, and finally the image output means outputs the image. Ru. For this reason, it is possible to refer to the plurality of measures on the health instruction book, and the industrial physician etc. can be presented to the subject almost as it is, which is very convenient for the industrial physician etc. Furthermore, since a plurality of measures are presented to the subject, it is easy to practice the measures with a high degree of freedom.
<6>
Alternatively, in another aspect of the present embodiment, as the countermeasure, the analysis means may perform lifestyle or environmental adjustment to reduce or improve the symptom that is considered to be most affected under a predetermined standard. presume.

According to this aspect, a lifestyle or environmental adjustment for reducing or ameliorating a symptom (for example, a main component of stress fatigue specific to the subject) that is considered to have the greatest effect under a predetermined standard is estimated, and the final Specifically, the image is output by the image output means. For this reason, such a lifestyle or environmental adjustment can be referred to on the health instruction book, and it becomes possible for the industrial physician etc. to be presented to the subject almost as it is, which is very convenient for the industrial physician etc. Furthermore, for the subject, lifestyle or environmental adjustment is presented directly, which makes it easy to practice countermeasures.
<7>
In an aspect in which the analysis means described above estimates a symptom, the analysis means compares the symptom with an absolute evaluation axis that does not fall within the group (typically, a company) to which each of the subjects belongs and the relative within the group It may be configured to estimate about two axes with the evaluation axis.

If configured in this way, the estimated symptoms can be evaluated in two ways: absolute evaluation that does not fall within the framework of a group such as a company, and relative evaluation within the group, and the symptoms of stress fatigue are evaluated. The usefulness of the device related to the function is significantly improved.
<8>
In the aspect in which the analysis means described above estimates the symptoms, the input means is operated to indicate that the disclosure of the estimated symptoms is agreed or not immediately before or after the respective subjects answer If the operation prompting the user to prompt the input and the consent is input, the estimated symptom is disclosed to each subject, and the operation input indicating the disagreement is input, the estimated symptom May not be disclosed to each subject.

By this configuration, the disclosure can be blocked if the subject does not want to disclose his / her symptoms, and the disclosure can benefit from the disclosure if the subject wants or is allowed to disclose his / her symptoms. . Therefore, since it becomes possible to operate evaluation and health guidance by the device while respecting the will of the subject without any problem from the viewpoint of personal information protection, it is very convenient in practical use.
<9>
In another aspect of the present embodiment, the input means further includes another question group (e.g., for example, preset for each of the subjects for plotting on a predetermined radar chart (e.g., stress fatigue profile or symptom profile) and population analysis). The other answer group by each subject can be input in response to the 57-item question related to the stress check of the Ministry of Health, Labor and Welfare, and the analysis means further includes the other answer input through the input means Evaluate the stress fatigue of each of the test subjects and the stress fatigue in the group to which each test subject belongs (that is, the stress fatigue in the group analysis) based on the group and making items to be adopted when drawing the radar chart. The image output means comprises the stress fatigue of each of the evaluated subjects and the stress fatigue of the evaluated population. S, the output in the format of the radar chart.

According to this aspect, the radar chart of the stress fatigue profile or symptom profile adopted by the Ministry of Health, Labor and Welfare, for example, for the individual subject and the group (for example, Can map for a specific company or business establishment). Therefore, it is possible to refer to the radar chart in succession or simultaneously or in parallel with the countermeasure on the same image output means for the industrial doctor who uses the device, for the subject, and for the company to which the subject belongs. So it will be very useful.
<10>
In another aspect of the present embodiment, the input unit further inputs another answer group by each subject to another question group in which each subject is preset for predetermined radar chart drawing and group analysis. When the analysis means estimates the countermeasure based on the function output, the analysis means is configured to: (1) a condition related to stress fatigue of each subject based on the function output; Estimated on an absolute evaluation axis that does not fit into the frame of the group to which the subject belongs, and (2) based on the function output, the symptoms related to stress fatigue by group, the absolute evaluation of each subject belonging to the group (3) at least one of the at least one adopted in drawing the radar chart on the basis of another answer group input through the input means. A predetermined index related to stress fatigue of each subject defined by an item is determined, and the index is determined based on the estimated symptom of each subject and the estimated symptom by group and the predetermined index defined. It may be configured to estimate a countermeasure.

  According to this aspect, in addition to the subject answer data set being input in a format in which each subject answers the predetermined question group (for example, the 138 questions in the ESAIT system described later) via the input means, Other subjects by each subject for a given radar chart (for example, stress / fatigue profile or symptom profile) and other question groups (for example, 57 questions related to the stress check of the Ministry of Health, Labor and Welfare) preset for drawing and population analysis The answer group of is input.

  Then, when the analysis means estimates the countermeasure based on the function output, first, based on the function output, an absolute evaluation of the symptoms related to stress fatigue of each subject does not fall within the frame of the group to which each subject belongs. Estimate on the axis. In parallel with or in parallel with this, based on the function output, symptoms related to stress fatigue by group are estimated by the average value of symptoms estimated on the absolute evaluation axis of each subject belonging to the group . Furthermore, based on the other answer group input through the input means, a predetermined index related to stress fatigue of each subject defined by at least one item adopted when drawing the radar chart is determined. Further, the countermeasure is estimated based on the estimated condition of each subject and the condition of each group and the predetermined index thus determined.

Thus, typically, the symptoms of each subject estimated on the absolute evaluation axis in the ESAIT system, the group-by-group symptoms estimated on the absolute evaluation axis in the ESAIT system, and typically the welfare It is possible to estimate measures based on at least a total of three variables of a predetermined index defined based on a group of answers to the 57-item question group related to the stress check of the Ministry of Labor.
<11>
In the aspect in which the countermeasure is estimated based on the symptoms of each subject and the symptoms according to the group and the predetermined index, the analysis unit determines the degree of stress due to the work / performance environment for each subject as the predetermined index. It may be configured to define the degree of support and satisfaction from the surroundings, as well as the degree of self-fulfillment.

When configured in this manner, typically, the symptoms of each subject estimated on the absolute evaluation axis in the ESAIT system, the group-by-group symptoms estimated on the absolute evaluation axis in the ESAIT system, and the typical The degree of stress due to work and performance environment, the degree of support and satisfaction from the surroundings, and the degree of self-fulfillment are defined based on the group of answers to the 57 questions concerning the stress check of the Ministry of Health, Labor and Welfare. It is possible to estimate countermeasures based on at least five variables in total.
<12>
When configured in this way, the analysis unit further relates to each subject based on the estimated condition of each subject, the estimated condition for each group, and the predetermined index determined. Evaluate at least one of stress / fatigue intensity, pattern of reaction to each subject to personal environment, psychological regulation, and points to be noted in environmental conditions, and estimate the countermeasure against the evaluated at least one. It may be configured to

If configured in this way, from at least a total of five variables, it should be noted automatically in the intensity of stress and fatigue, the reaction pattern to each subject to the personal environment, the psychological regulation, and the environmental conditions for each subject. You can evaluate points.
<Stress fatigue evaluation / health guidance support method>
<13>
In the stress fatigue evaluation / health guidance support method according to the present embodiment, response data of a causative system related to stress fatigue obtained in a format in which each subject answers a predetermined question group displayed on a screen or in a document, stress An input step of inputting a subject response data set including response data of a response system related to fatigue and a response data of a symptom system related to stress fatigue; or when the subject response data set is input at the input step When an analysis order is issued, it is an actual response data set that has been accumulated in the past and has been answered by a plurality of workers who worked in the previous working environment, and the cause is the multivariate analysis on the actual response data set. There are few omissions enough to define the response data of the response system and the response data of the response system and the response data of the symptom system Based on the function output of the function, the function answer of the input subject answer data set is input to the function that has been determined by performing the multivariate analysis in the corresponding result answer data set. The method further comprises: an analysis step of estimating a countermeasure for a symptom related to stress fatigue of each subject; and an image output step of outputting an image of the estimated countermeasure in a predetermined health instruction book format.

According to the stress fatigue evaluation and health guidance support method according to the present embodiment, as in the case of the stress fatigue evaluation and health guidance support device according to the present embodiment described above, the industrial physician etc. presents or clearly indicates the countermeasure. It is possible to provide health guidance to each subject in question while referring to the health guidance book, and it is possible to easily support health guidance according to the stress fatigue of each worker or each employee belonging to a company as each subject. It becomes.
<Computer program>
<14>
A computer program according to the present embodiment causes a computer to function as a stress fatigue evaluation / health guidance device (including its various aspects) according to the present embodiment in order to solve the above-mentioned problems.

According to the computer program of the present embodiment, a solid-state storage device removable from the computer system, such as a storage medium such as a ROM, a CD-ROM, a DVD-ROM, a hard disk or a USB (Universal Serial Bus) memory storing the computer program. From this, if the computer program is read and executed on a computer system, or if the computer program is executed after being downloaded to a computer system via, for example, a communication means, the above-described embodiment can be performed. The stress fatigue evaluation / health guidance device (including its various aspects) can be realized relatively easily.
<Recording medium>
In the recording medium of the present embodiment, the computer program of the above-described present embodiment is recorded.

  According to the recording medium of the present embodiment, the computer program of the present embodiment recorded by being attached to or connected to the computer system, or inserted into an appropriate reading device provided in or connected to the computer system, The computer system can be read and executed, and the stress / fatigue evaluation / health guidance apparatus according to the above-described embodiment can be realized relatively easily.

  Such effects and other advantages of the present embodiment will be clarified by the embodiments described hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS It is a block diagram of the ESAIT system which is an example of the stress fatigue evaluation and health guidance apparatus which concerns on an Example. It is a conceptual block diagram which shows a mode that the terminal device etc. which comprise the ESAIT system which is an example of a stress fatigue evaluation and health guidance apparatus based on an Example were accommodated in the communication network. It is a flowchart which shows the flow of an example from an answer input to an image output based on an Example. It is a top view which shows an example of the question group which urges selection of the answer data for analysis based on an example. It is a top view which shows an example of the question group which urges selection of the response data for radar chart drawing and group analysis based on an Example. It is a top view showing an example of a radar chart concerning an example. It is a top view which shows an example of the evaluation note of the stress fatigue which concerns on high stress / main component obtained as a result of analysis based on an Example. It is a top view which shows an example of the health instruction book which shows the countermeasure against stress fatigue obtained as a result of analysis based on an Example. It is a top view which shows another example of the health instruction manual which shows the countermeasure against stress fatigue based on an Example. It is a characteristic view showing that it is necessary to cover the whole range of severity in multivariate analysis for estimating measures or symptoms. When an answer is not enough, even if it performs multivariate analysis, it is a characteristic view showing that analysis is impossible. FIG. 10 is a conceptual diagram illustrating a complete data set that enables multivariate analysis. It is a graphic conceptual diagram (the 1) which shows the outline | summary of the effect of the ESAIT system which concerns on an Example. It is a schematic conceptual diagram (the 2) which shows the outline | summary of the effect of the ESAIT system which concerns on an Example.

  First, with reference to FIGS. 1 and 2, the basic configuration of an ESAIT (Exhaustion, Stress, Analysis, Instruction, Treatment) system 1 as an example of a stress / fatigue evaluation / health guidance apparatus according to an embodiment will be described.

  In FIG. 1, the ESAIT system 1 comprises an input device 11 constituting an example of the "input unit" according to the present invention, a display unit 12 and a printing apparatus 13 constituting an example of the "image output unit" according to the present invention The apparatus 14 is provided with the processing apparatus 20 which constitutes an example of the "analysis means" according to the present invention. The display device 12 may constitute an example of the “input unit” according to the present invention together with the input device 11. The data storage device 14 may be, for example, a USB memory.

  The processing apparatus 20 includes a stress / fatigue determination unit 21, a high stress / principal component determination unit 22, a multiple regression analysis unit 23, and a measure presentation unit 24 corresponding to the difference. The processing device 20 includes, for example, a CPU, a processor, a memory, and the like, or a personal computer, a computer, and a tablet terminal, and performs predetermined operations (see FIG. 3 etc.) according to a computer program as described in detail below. It is configured to do.

  The ESAIT system 1 shown in FIG. 1 is very convenient because it functions as described in detail later with reference to FIG. 3 and the like even in a stand-alone format such as a single personal computer. The ESAIT system 1 is used, for example, by an industrial doctor who is in charge of a company, and an input operation and a browsing operation are performed by the industrial doctor and each subject (that is, workers, employees, etc.). The ESAIT system 1 is disposed at a business office or the like where each subject can face. Or, bring it by an industrial physician.

  In FIG. 2, the ESAIT system 1 is distributed on the Internet 200, and the Internet 200 includes a plurality of terminal devices 100 each having an input device 11, a display device 12 and a printing unit 13, a processing device 20, and data. A storage device 14 is housed.

  The processing device 20 may be included in each of the terminals 100, and the data storage device 14 may be included in each of the terminals 100. However, with the configuration shown in FIG. It is sufficient to have only the browser function.

  The ESAIT system 1 shown in FIG. 2 is, for example, a large-scale storage device arranged in a data processing center or the like while constituting the processing device 20 by a high function computer arranged in a data processing center or the like. The plurality of terminal devices 100 are very convenient because they function as will be described in detail later with reference to FIG. In addition, sharing the data storage device 14 with a plurality of terminals 100 is convenient because it becomes easy to execute sharing and management of data. Each of the terminal devices 100 is used, for example, by an industrial doctor who takes charge of a company, and an input operation and a browsing operation are performed by the industrial doctor and each subject (that is, a worker, an employee, etc.). Each of the terminal devices 100 is disposed at a business office or the like where each subject can face. Alternatively, it may be brought by an industrial physician.

  Incidentally, in FIG. 1, if the data storage device 14 is constructed with a USB memory, there is obtained an advantage that the whole ESAIT system 1 can be made compact, for example, a system can be constructed from a notebook personal computer and a USB memory.

  Next, the detailed configuration of the ESAIT system 1 according to the present embodiment will be described with reference to FIGS. 4 and 9, which respectively show the flow chart of FIG. 3 and the input / output data of the ESAIT system 1 together with FIGS. The operation will be described.

  Here, FIG. 3 shows a series of operations from the input of the answer data to the evaluation (in other words, the output of the evaluation data) and the health instruction (in other words, the output of the countermeasure data) by the ESAIT system 1. Show. FIG. 4 shows a part of the 138 items of high power questions (or the input screen of the answer data) as input data of the ESAIT system 1, and FIG. 5 shows another of the ESAIT system 1 The input data is a group of 57 items of the Ministry of Health, Labor and Welfare stress check (or an input screen of the response data). FIG. 6 shows an example of a radar chart among the evaluation data output from the ESAIT system 1, and FIG. 7 shows an example of high stress / principal component data among the evaluation data output from the ESAIT system 1. FIG. 8 shows an example of countermeasure data presented as having three effects uniquely to the individual subject by the ESAIT system 1, and FIG. 9 shows the individual subject by the ESAIT system 1. Inherently, an example of countermeasure data presented as a lifestyle for improving / preventing stress fatigue is shown.

  In FIG. 3, first, an answer is input via the input device 11 (step S10). Specifically, the 138 items of high-detection questions, that is, the ESAIT questions (see FIG. 4) and 57 items of the Ministry of Health, Labor and Welfare, which are displayed on the screen of the display device 12 or on a document via the input device 11 A subject response data set is input in a format in which each subject responds to the stress check question group (see FIG. 5).

  In the excerpted part of the 138 items of the high detection question group shown in FIG. 4, the answer data in four stages for each item (that is, the answer data of ESAIT) is input. In FIG. 4, for example, if the answer to the question A-2 “There is less going out on holidays” is “3 (slightly applicable)”, the answer data for this question is “DATAa-2-3”. Become. Further, for example, if the answer to "Satisfied with work" of the question D-1 is "4 (dissatisfied)", the answer data to this question is "DATAb-1-4". Since these response data are input to the evaluation / teaching function obtained by multivariate analysis, the data itself may have any format as long as it can be uniquely identified. That is, the format of the response data is arbitrary as long as it conforms to the format of the response data used in the evaluation / guidance function so as to meet the purpose of specifying the correlation on the evaluation / guidance function.

  You may add "score" (for example, 0 to 5 points according to an extent) to such response data as an index which shows the seriousness or the effectiveness degree of correspondence. Specifically, for example, in the case of symptom type response data of ESAIT, "I feel miserable", "I feel like I am being scolded by something" and "I am 4 points are assigned to each answer data such as “I think it is not worth giving up”, and data to that effect is added to the symptom-based answer data of ESAIT. Alternatively, for example, in the case of ESAIT cause system or response system response data, "I relate to many people", "think in positive terms", and "put BGM" as indicating the strength of the cause and the effectiveness of the response. For the answer data, etc., 2 points, 1 point and 3 points are assigned in this order, and data to that effect is added to the cause system or response system answer data of ESAIT.

  In the 57-item stress check question group of 57 items shown in FIG. 5, 4-step answer data (that is, answer data of MHLW) for each item is input. In FIG. 5, for example, if the answer to "must work hard" of question A-3 is "Yes" and "Well right (second step)", the answer data for the question of this A-3 is " It becomes DATAa-3-2. Also, for example, if the answer to "Satisfied with work" of question D-1 is "No" and "very unsatisfactory (first stage)", the answer data to the question of D-1 is "DATAd-1-". It will be 1 ”. These questions and response data are the same as those by the existing Ministry of Health, Labor and Welfare.

  The input in step 10 may be input by each subject by a keyboard, a tablet, a touch panel, a mouse, a cursor operation, a voice input, and the like constituting an example of the input device 11. When the display device 12 partially carries out these functions, the display device 12 partially constitutes one example of both the “input unit” and the “image output unit” according to the present invention. Alternatively, a reader (for example, an OMR sheet or the like) whose answer is marked by each subject may be read from a reader that constitutes an example of the input device 11.

  The answer data is, for example, the answer data of the cause system such as “must do a lot of work”, “the work can not be processed in time”, “sport”, “refresh with family” It is set from the beginning so that it can be separated from the response data of the response system such as “. Furthermore, for example, response data of symptom systems such as “dizziness” and “headache” are set from the beginning so as to be divided from the response data of these causal systems and the response data of the corresponding systems. The answer data input in step S10 is constructed as an answer data set by combining a large number of these three types of answer data. In multivariate analysis, if analysis is performed without distinction between the causative system and the corresponding system, specifically, if these are treated as independent variables without separation, the response data contains the causative system and the corresponding system in terms of data handling. As the two types of response data of and the response data of symptom system, corresponding effects similar to the case of multivariate analysis using three types of response data described below can be obtained.

  Next, when the input of the test subject response data set (step S10) is completed as described above, an analysis command by the industrial doctor or the like is issued to the ESAIT system 1, and the processing in the processing apparatus 20 is started (step S11 to S15).

  Specifically, on the other hand, analysis processing is performed on the subject answer data set for the 57-item stress check question group of 57 items, and data generation for radar chart drawing as shown in FIG. 6 is performed (step S11 ). At this time, for example, when answers from a plurality of subjects belonging to the same group such as the same business place are input, the group analysis is also for drawing a radar chart (for group analysis) in the same format (see FIG. 6). Data generation is performed. About these stress analysis processing (step S11), it is the same as that by the existing Ministry of Health, Labor and Welfare. The analysis processing here is mainly executed by the stress fatigue determination unit 21 (see FIG. 1).

  On the other hand, in response to the evaluation / teaching function prepared in the processing device 20 in parallel with the process of step S11 and stored as electronic data in the data storage device 14, the subject answer data input in step S10 A set (however, a part for the high detection question group unique to the ESAIT system 1) is function input. In the present embodiment, in particular, the evaluation / teaching function is determined in advance by multivariate analysis of the result response data set.

  The “performance response data set” according to the present embodiment includes a working environment that is now legally illegal or virtually impossible to obtain, in other words, covers the entire range of severity, eg, The “full data set on stress fatigue surveys”. This complete data set has few gaps enough to define the evaluation / guidance function that relates the response data of the cause system and the response data of the response system to the response data of the symptom system in multivariate analysis on the response data set . The complete data set and the evaluation / teaching function obtained as a result of multivariate analysis thereof will be further described later (see FIGS. 10 to 12).

  Based on the function output of the evaluation / teaching function determined in this way, the processing device 20 is a main component of high stress and stress fatigue as a symptom related to stress fatigue of each subject, specifically, stress that tends to appear in oneself. A fatigue sign or the like is estimated or determined (step S12). The analysis process here is mainly performed by the high stress / principal component determination unit 22 (see FIG. 1).

  For example, individual item data constituting the stress fatigue data 51 shown in FIG. 7 is estimated or determined as a function output corresponding to the answer data specific to the subject (see FIG. 4). That is, with respect to stress fatigue of the subject, a main component which is high stress is determined. Specifically, based on the function output, stress fatigue signs that easily appear in oneself such as “anxiety”, “body complaints”, “stress fatigue” such as “fatigue”, “frustration”, or stress fatigue that is occurring in oneself, Alternatively, it determines an individual score related to the condition, in other words, an evaluation related to the condition of stress fatigue. This result is finally presented as a determination result indicating that, for example, “principal component 1 (deterioration of self-evaluation and instability) is determined to be high”, as described later.

  Furthermore, multiple regression analysis and principal component analysis are performed on the input response data set based on the evaluation and instruction function thus determined (step S13). That is, "individual multivariate analysis" is performed on the basis of the existing evaluation / teaching function predetermined by the complete data set. Then, the high stress estimated in step S12 is sequentially input to the evaluation / teaching function by sequentially inputting a difference group consisting of a group of a plurality of response data different from this, that is, having differences based on the subject's response data set. Whether or not the symptom and the effect of reducing the symptom of the main component are all or nothing is checked for each difference by the simulation having the difference group as a function input (step S14). The analysis processing here is mainly executed by the multiple regression analysis unit 23 (see FIG. 1).

  More specifically, cause system or corresponding system response data (for example, 2 points are allocated) which minimize the sum of principal component scores determined to be high stress (principal component) in step S12 (for example, With the relationship “etc.” as the independent variable and the principal component score (in other words, the response data of the symptom system) as the dependent variable, the result of the multiple regression analysis is used to determine the cause to be excluded or the recommended correspondence. Here, in the simulation results related to the multiple regression analysis, for example, as the response data of the cause system or the response system that gives a high score, “I relate to many people”, “think on positive side”, and “BGM The answer data, such as “put over”, is a countermeasure for high scores to which 4 points are assigned respectively. In this way, simulation is performed by multiple regression analysis with the response data of the cause system or the response system of ESAIT input in step S10 as the independent variable and the response data of the symptom system (the main component score thereof) as the dependent variable. Estimate the answer of the causal system or the corresponding system that minimizes the sum of the principal component scores.

  In this way, the processing device 20 presents, among the response data of the cause system or the response system, the one having a large effect. That is, a countermeasure that is optimal or has a large or corresponding effect is estimated and presented as a countermeasure (step S15). The analysis processing here is mainly executed by the measure presentation unit 24 (see FIG. 1) according to the difference.

  In this way, based on the correlation between the response data of the symptom system and the response data of the causal system in the evaluation / teaching function set in advance, it causes the symptom of stress fatigue specific to the subject. We estimate effective measures for stress fatigue symptoms specific to the subject, such as preventive actions such as reduction, elimination, and improvement of the cause. For example, it is estimated that it is better to remove “overtime work (do not work)”, “customer turn (do not work)”, etc., and indicate that or output electronic data or code data assigned to that effect. . That is, these are presented as one effective countermeasure (step S15).

  In addition, based on the correlation between the response data of the symptom system and the response data of the response system in the evaluation / teaching function set in advance, measures effective for improving the symptoms of stress fatigue specific to the subject are estimated. Do. For example, it is estimated that the user should take measures such as "eat with three meals" and "do sports" and output electronic data or code data indicating or assigned to that effect. That is, these are presented as other effective countermeasures (step S15).

  The analysis process of step S11 described above and the analysis process of steps S12 to S15 described above may not be performed in parallel, but may be performed in tandem.

  As described above, the stress fatigue data generated in step S11 by the processing apparatus 20 and the high stress / principal data and countermeasure data generated in steps S12 to S15 are the response data input in step S10. The set is recorded or stored in the data storage device 14 (step S18).

  In parallel with or in parallel to this recording operation, the display device 12 or the printing device 13 adds the countermeasure data estimated in the steps S12-15, for example, to the interviews shown in FIGS. An image is output in the form of instructional reference material (step S19). In addition, the stress fatigue data estimated in step S11 is output as an image in the form of a radar chart shown in FIG. 6 (step S19).

Here, in FIG. 6, factors that are considered to cause stress are presented in the upper radar chart, and mind-body responses caused by stress are presented in the middle radar chart, and factors that affect stress response are in the lower stage. Is presented on the radar chart. Such a radar chart (in other words, a stress chart or a stress profile) is known by the Ministry of Health, Labor and Welfare. That is, in this embodiment, the affinity with the existing system led by the Ministry of Health, Labor and Welfare is also sufficiently taken.
In FIG. 7, as the main component of high stress / stress fatigue, high stress / principal component data 51 (specifically, “deterioration and instability of self-evaluation,” “sleep,” following the fixed text to that effect)・ A group of data composed of multiple high stress / principal data such as “disorder of life rhythm”, “disorder and hypersensitivity of autonomic nervous system”, ... “feeling of energy loss” is presented in the middle . This is generally in the form of a comment together with a fixed phrase.

  In Figure 8, as a presentation of lifestyle and environmental adjustment to improve / prevent stress fatigue from a comprehensive point of view, countermeasure data showing that the effect seems to be the largest following the fixed text to that effect. 61 (specifically, a data group configured as a set of two countermeasure data of “try to work hard” and “play sports”) is presented in the upper row. Countermeasure data 71 showing that it is considered to be effective next (specifically, "three meals properly", "we go to sleep on holidays", "the aim aims at 80%", ..., "the deadline The data group configured as a set of a plurality of countermeasure data "to clarify" is presented in the middle. Countermeasure data 81 showing that it seems to be better to take in (specifically, "I cherish the mind play," "I do not overreact to things," and "I speak out the trouble" The data group (a group of data constructed as a set of two countermeasure data) is presented at the bottom. These are all in the form of comments together with the fixed text.

  As shown in Figure 9, lifestyle / environmental adjustment to improve / prevent stress fatigue that has the most influence (in other words, the most adverse effect on the subject at present), following the fixed text to that effect Response measures data 91 (specifically, "take a well-balanced diet", "think positive", "talk to many people", ..., "understand the contents of work well Data group configured as a set of a plurality of countermeasure data, "to be able to do" is presented. This, too, is in the form of comments together with the fixed text.

  As is clear from FIGS. 7 to 9, the presented countermeasure data is output as an image as a comment sentence that makes sense as the content of the health guidance. Therefore, industrial physicians and the like can practice interview guidance or health guidance extremely easily with reference to the interview guidance reference material, even without knowledge as a psychiatric specialist.

  Next, focusing on the necessity of the “complete data set” according to the present embodiment, in particular, in order to specify an evaluation / instruction function related to multivariate analysis, FIG. Description will be added with reference to FIG.

  As shown in Fig. 10, when taking a graph that takes the level of stress fatigue condition to the left and right, and takes the frequency on the vertical axis, the Ministry of Health, Labor and Welfare imposes the duty of interview guidance effort, and stress fatigue is in the top 10%. However, it has been found that there are places that do not require health guidance (ie, a company or a business place) such as "A team" located on the left side of the graph. That is, the “A team” is generally relaxed. On the other hand, in the graph, all members have reached the peak of stress fatigue like “C team” located to the right in the graph, and not only the top 10% but all members are originally targeted for health guidance (ie company or It has been found that business establishments also exist. In the graph, places in an average labor mode (ie, a company or business establishment) are shown as "B team" in the center of the graph. Because there is a wide range of stress-fatigue distribution of the basic data collection target group in this way, it is necessary to cover the entire range of severity as a performance response data set for determining evaluation and guidance functions by multivariate analysis. is there.

  According to the research conducted by the applicants of the present invention, not only the range covered by the actual response data set but also the requirements for the items forming the data and the requirements such as the high response rate are included as the actual response data set. Summarizing the necessary requirements, 1) basic data to create a scale that can measure the severity of extreme symptoms above the level of overwork death, and 2) that the survey items are universal and reflect the situation in the field Collection target group shows wide stress fatigue distribution, 3) Employees with clear response motives are those who answered the actual situation without possibility of personal information leakage, 4) High accuracy It is a complete data set that enables multivariate analysis of

  As shown in FIG. 11, according to the research of the applicants of the present invention, when a survey of 100 questions (Q1 to Q100) and 100 persons (A1 to A100) is conducted, missing answer data which is sparse in the figure There were only 200 unanswered responses / 10,000 total responses randomly to the extent indicated by the ▪ mark indicating (ie unanswered parts) (ie, an average of 2 answers were missed per person) However, the number of samples available for multivariate analysis using all variables is drastically reduced to 18 only. That is, with only a 2% loss, over 80% of the samples become unusable for multivariate analysis. In this case, it will be impossible to decide the evaluation / instruction function that can be used and used in multivariate analysis.

  On the other hand, as shown in FIG. 12, when the applicants of the present invention asked and answered questions to create a complete data set, the application restarts with an arrow from the bottom to the top in the left half of the figure (re-question) As shown in, when there is an unanswered question, I will return to it and prompt for an answer. This operation is repeated until the remaining 2% unanswered is completely answered in the example of FIG. As a result, as shown in the right half of FIG. 12, finally, a large number of answer data sets, which are about 1000 people, are obtained as the actual answer data sets which are "complete data sets". In addition, since the error of the statistic calculated from n samples is generally considered to be 1 / n of the route, if there are about 1000 samples, the error is already small to about 3%. There is almost no need to collect thousands or tens of thousands of statistics. As described above, in the “full data set” according to the present embodiment, legally acquiring data relating to situations such as illegal long working hours, overtime work, working on holidays, etc. under the current labor standard law etc. It is a dataset that has been made practically impossible by the recent social situation, and it is answered by workers highly motivated to the improvement survey of working conditions (and the surveyor is also highly motivated It is an extremely valuable data set that can be obtained for the first time).

  This embodiment spends a long time in the past when social conditions covered data covering the entire range of such severity, and it was possible to investigate it, and workers and their employers among them It builds on the existence of a valuable performance response data set as a crystal of constant effort among investigators and stakeholders.

A brief description of the survey actually conducted will be added here.
<Person to be surveyed>
An information related company with about 750 employees. Target company. Due to the strong relationship with other companies, it is difficult to adjust the work load independently, and it is required to continue the work to be carried out on delivery date, and a succession of sick absences, leavers and retirees become major problems for workers, labor unions and businesses It was According to interviews conducted before the survey, a maximum of 270 hours per month for overtime hours worked over the last two months, and a maximum of 210 hours for two months on average. As an industrial physician as a method to improve this situation, we proposed the importance of acquiring health management methods that enable rational improvement by collecting information on cause systems, result systems, and response systems.
<Information collection>
In addition to the health and safety committee and work patrols once a month in 4 business sites and in 2 business sites in 2 business sites, regular health check-ups and those who have an interview, for convenience of business, those who can interview can have managerial positions randomly Interviews were conducted with the nominated employees and the applicants. The interviews were for everyone, and they kept the confidentiality obligation unless there was hope or consent. If there is a request or consent, the only information provision destination is the personnel and general affairs manager who publicizes the relationship between business and internal personnel in order to avoid obstacles to the target person's own business and surrounding business execution and personal relationships. In just under 20 years, we conducted interviews with over 400 structured questionnaires.
<Result>
(1) Survey contents:
Individuals were surveyed about the causes of stress and fatigue, symptoms, lifestyle changes, measures, and preventive actions. The question was taken as the original survey item of the comprehensive health survey for 1000 workers in S prefecture. Since then, the contents of the questionnaires examined by each Health and Safety Committee for about five years were repeatedly revised while collecting the opinions of employees at the workplaces to which each member belongs.
(2) Motivating correct answers:
In the same five years as in the previous paragraph, both employers and unions are informed that “the survey is aimed at the health of the employees themselves and the health management of the whole company”, and the surveys are anonymous and unanswered questions to obtain accurate answers. If there is a problem, we will return to this question and conduct a complete answer, and we will carry out using a system that will end at the time, and obtain a complete data set of 201 questions and 740 people.
In addition, by deleting the question that the contribution rate to the symptom was small, the total number is 138 (high power question group), and the Ministry of Health, Labor and Welfare, vocational stress simple survey questionnaire 57 questions in total are combined. It was a questionnaire.

  Next, with reference to FIG. 13 and FIG. 14, the function and effect of the present embodiment will be further described.

  As shown in FIG. 13, in the present embodiment, when the test subject response data set is input to the ESAIT system 1 (see step S10 in FIG. 3), the analysis processing by the processing device 20 is quickly executed in the ESAIT system 1 (FIG. Step 3 (refer to steps S11 to S15), image output of individual scores, which are symptoms related to stress fatigue specific to the subject, and measures output of stress fatigue specific to the subject in the form of interview instruction materials, include the subject The result of population analysis for the entire population of companies etc. is output as an image (see step S19 in FIG. 3). That is, by the automatic processing of the ESAIT system 1, three types of image output are obtained: (1) personal scores for all, (2) personal instruction materials for all, and (3) group analysis results.

Therefore,
(A) If it is a subject,
・ Fatigue, stress sign (individual result) which is easy to appear to oneself
・ Measures effective for oneself to reduce and prevent it (personal score)
・ Currently, the degree of fatigue and stress that has occurred to you (individual score)
Is presented as a display on the screen of the display device 12 or as a printed matter from the printing device 13, which is very convenient.
(B) If you are an industrial physician,
・ The degree of fatigue and stress sign of the whole business place in charge and necessity and urgency of the measures (group analysis result)
-Interview guidance subject list (individual grade) (group analysis result)
・ Points to keep in mind about each subject when interviewing (interviewing instruction materials)
Is presented as a display on the screen of the display device 12 or as a printed matter from the printing device 13, which is very convenient.
(C) If you are a business,
・ Basic data for administrative report (individual record)
・ Basic data for population analysis (population analysis results)
Is presented as a display on the screen of the display device 12 or as a printed matter from the printing device 13, which is very convenient.

  As shown in FIG. 14, the processing performed by the ESAIT system 1 of this embodiment can be summarized as follows: a response data set for stress factors in the living environment, and a response data set for daily lifestyle / preventive action Simulation is performed by inputting, as a function, the response data set for the other fatigue / stress factors into the evaluation / instruction function set in advance and possessed by the processing apparatus 20. As a result, an effective countermeasure is automatically presented for changes in mental and physical symptoms, lifestyle habits, and the like, and improvement of plus α is achieved.

  In the embodiment described above, the processing device 20 is configured to estimate stress symptoms on two axes of an absolute evaluation axis that does not fall within the frame of the company to which each test subject belongs and a relative evaluation axis in the company. May be This point will be discussed below.

The stress and fatigue symptoms of individuals and companies are the content and severity of symptoms, ie, “absolute evaluation axis (evaluation within a general distribution including stress-fatigue symptoms related to work modes over equivalent to overwork death equivalent time)” It is necessary or at least desirable to consider by both of the "relative evaluation axes" in the belonging company.
[1] The distribution of overtime work for companies targeted by this system includes the current Japanese labor status of up to 270 hours of overtime overtime for a month and up to 210 hours on average for two months in industry interview data It showed distribution and made it possible to evaluate stress and fatigue status of individuals and companies by "absolute evaluation".
[2] In the legally mandated "stress check", it is a big problem that the implementer (mainly industrial physician) has to give specific instructions optimized for each individual, but most industries Such guidance is practically difficult because the doctor is a doctor other than a psychiatrist and psychosomatic doctor. As a result, under the present circumstances, the implementation rate of the interview guidance which should be carried out to "10% of high stress people" in the organization is only 0.6% at the end of June 2017. At the same time, the content of instruction must be based on textbook knowledge. This system presented effective methods to give high-quality instruction with clear and clear statistical basis even if it is not a specialist.
[3] It is not an argument that it is the most important issue to take measures against personal health problems in relation to work-related injuries, but recent courtesies have come to recognize the responsibility of companies, superiors and industrial physicians. The system which extracts information maximally on the basis of personal declaration and automatically gives specific guidance optimized for the individual in a prompt and automatic manner supports "health management" of the enterprise. Like ISO, rational and high quality health care will bring a healthy workforce to a company, and it will also be one big measure against a declining labor force.
As a result of these, the absolute and relative evaluation of individual and company average stress and fatigue within the comprehensive distribution of stress and fatigue, and automatic output and presentation of teaching materials with statistical significance to stress and fatigue Individual-optimized prompt guidance has become possible without relying on the expertise of industrial physicians.

  As discussed above, the ESAIT system 1 is extremely useful, which enables two types of evaluation, an absolute evaluation that does not fall within the framework of a company, and a relative evaluation within the company.

  In the embodiment described above, the display apparatus 12 or the printing apparatus 13 may output the image of the high stress person in the order of the stress fatigue scores. That is, according to the symptoms of stress fatigue estimated in step S11 of FIG. 3 in response to the input of answer data of 57 items of the Ministry of Health, Labor and Welfare, or in place of or in addition to this, answers of 138 items of ESAIT system The top 10% high stressed person list may be automatically created according to the high stress / principal component symptom estimated in step S12 of FIG. 3 according to the data input. With this configuration, when selecting a subject to be interviewed, the order of interviewing can be automatically obtained. Therefore, in the case of an industrial physician or the like, the selection work and the ordering work are not performed. It is very convenient in practice to get rid of it.

  However, regardless of the order of points, when "depressive symptoms" at high risk are estimated, they may be automatically extracted and added to the top 10% list. Alternatively, a special flag may be set to provide a warning or an urgent indication that "depression symptoms" have appeared.

As described above in detail, according to the present embodiment, high stress / principal component data and countermeasure data are image-outputted respectively in the format of an interview instruction book if an answer data set acquired for each subject is input. . Therefore, the industrial physician etc. can relatively easily evaluate the stress fatigue of each worker or each employee belonging to the company etc. while referring to this, and can support the health guidance according to the evaluation result. It is very useful in practice.
<Other Embodiments>
In the present embodiment, in addition to the subject answer data set in the ESAIT system being input through the input device 11 (see FIG. 1, FIG. 2, etc.), the 57 item questions pertaining to the stress check of the Ministry of Health, Labor and Welfare Other answer groups by each subject are input.

  Then, when the processing device 20 estimates the countermeasure based on the function output, first, the symptom EL (p) related to the stress fatigue of each subject based on the function output to which the subject answer data set is input, Estimate on an absolute evaluation axis that does not fit into the frame of the group to which each subject belongs. In parallel with or in parallel with this, based on the function output with the subject answer data set as an input, the symptom EL (w) relating to stress fatigue by group is on the absolute evaluation axis of each subject belonging to the group Estimated by the average value of symptoms estimated in. The average value here may be a simple average, or may be a weighted average with a predetermined weighting according to the evaluation item or the evaluation result or the evaluation result or the classification. In any case, this absolute evaluation axis can be used in the case of the ESAIT system.

  As a specific example of "the symptom EL (p) of each subject" estimated here, "It is judged as moderate in individual stress / fatigue evaluation", "relatively high in personal stress / fatigue evaluation It is judged as (High), "In personal stress / fatigue evaluation, it is judged as Extremy High." Similarly, as a specific example of the “group-specific symptom EL (w)” estimated here, “The overall stress / fatigue evaluation of the business site is judged to be Moderate”, “for the business site. Overall stress / fatigue evaluation is judged to be relatively high (High), etc. "All stress / fatigue evaluation in the business place is judged to be severe (Extremy High)".

  For example, with regard to the symptom EL (p) of each subject, 1.933461 or more corresponds to severe (Extremry High) on the absolute evaluation axis unique to the ESAIT system, and 0.48278 or more and less than 1.933461 (high) (High), -0.71111 or more and less than 0.48 278 corresponds to moderate, -1.25985 or more and less than -0.71111 corresponds to low (low), and less than -1.2985 It is estimated to correspond to Extremy Low).

  For example, with regard to symptoms EL (w) related to stress fatigue by group, as in the case of symptoms EL (p) of each subject described above, 1.933461 or more on the absolute evaluation axis unique to the ESAIT system Corresponds to the severity (Extremry High), 0.48278 or more and less than 1.933461 corresponds to the high (High), -0.71111 or more and less than 0.48278 corresponds to the Moderate (Moderate), -1.25985 or more It is estimated that less than -0.71111 corresponds to Low and less than -1.25985 corresponds to Extremy Low.

  On the other hand, based on the answer group to the 57-item question related to the stress check of the Ministry of Health, Labor and Welfare input through the input device 11, the processing device 20 performs (1) business · as a predetermined index related to stress fatigue of each subject. The degree of stress (js: job stress) by the performance environment is quantified or divided into levels L (js), (d) The degree of support and satisfaction (ss: support and satisfaction) is quantified or divided into levels What is L (ss), (3) sr: the degree of self-realization (digitization or level division) L (sr) is determined.

  As specific examples of "stress due to work and performance environment (js)" defined here, "work and performance environment stress is an evaluation with Moderate", "work and performance environment stress is mild (Low) It is evaluated that). As a specific example of "support from the surroundings and satisfaction (ss)", "the satisfaction of the support from the surroundings is moderate", and "the satisfaction of the support from the surroundings is high (high)" 'S answer. Specific examples of "self-realization (sr)" include "The feeling of self-realization seems to be Moderate" and "The feeling of self-realization seems to be high (High)".

  For example, for L (js) related to stress due to work and performance environment, 4 or more and less than 8 in the "right half (5 items) of Ministry of Health, Labor and Welfare radar chart 1" corresponds to mild (Low), 8 or more and less than 15 Is equivalent to Moderate, and 16 or more and less than 20 are defined as equivalent to High. For example, with regard to L (ss) pertaining to the support and satisfaction from the surroundings, in the “Ministry of Health, Labor and Welfare radar chart 3”, 4 or more and 7 or less correspond to Low, and 8 or more and 12 or less are Moderate. And 13 or more and 16 or less are defined as corresponding to High. For example, for L (sr) relating to the degree of self-fulfillment, in “left half (4 items) of Ministry of Health, Labor and Welfare radar chart 1”, 4 or more and 7 or less correspond to Low, and 8 or more and 12 or less are moderate. It corresponds to the degree (Moderate), and 13 or more and 16 or less is defined as what corresponds to the altitude (High).

  Thereafter, the processing device 20 calculates the values of the symptom EL (p) and the group-specific symptoms EL (w) of each subject on the absolute evaluation axis estimated as described above, and the values of the three predetermined indexes determined as described above. The countermeasure is estimated based on L (js), L (ss), L (sr). More specifically, from the combination of the five variables EL (p), EL (w), L (js), L (ss) and L (sr) determined in this manner, stress and Evaluate the strength of fatigue, the response pattern to each subject to the personal environment, psychological regulation, points to be kept in mind in environmental conditions, and estimate measures for the evaluated ones.

  For example, as an example of a combination of five variables, the value of EL (p) is Extremy Low, the value of EL (w) is Extremy Low, and the value of L (js) is Low and L (ss). If the value of is Low and the value of L (sr) is Low, then it may be necessary to ask about the personal motivations for doing work and current tasks as an interview point. Countermeasures will be estimated.

  The countermeasures thus estimated are finally outputted as images in the form of a health instruction manual through the display 12 or the printing device 13 (see FIG. 1, FIG. 2, etc.). That is, it is added to the comment suggested to the industrial physician etc. as a point of interview and guidance. In this way, for each subject himself / herself to be added to the comment as "forward-looking proposal based on data" etc. automatically about what kind of direction and what should be taken care of in the future. Is possible.

  The present invention is not limited to the above-described embodiment or example, and can be appropriately modified without departing from the scope or spirit of the invention which can be read from the claims and the specification as a whole. An apparatus and method for fatigue assessment and health guidance and a computer program are also included in the technical scope of the present invention.

DESCRIPTION OF SYMBOLS 1 ... ESAIT system, 11 ... Input device, 12 ... Display, 13 ... Printing device, 14 ... Data storage device, 20 ... Processing device, 21 ... Stress fatigue determination part, 22 ... High stress / principal component determination part, 23 ... Heavy Regression analysis unit 24 Measures presentation unit according to difference 100 Terminal device 200 Internet

Claims (14)

Response data of the causative system related to stress fatigue, response data on the corresponding system related to stress fatigue, and symptom system related to stress fatigue, which are acquired in a format in which each subject answers a predetermined question group displayed on an image or a document An input means capable of inputting a subject answer data set including answer data;
When the subject response data set is input through the input means, or when an analysis command is issued in addition to this, answers are made by a plurality of workers accumulated in the past and working in the previous working environment The response data set, and the multivariate analysis for the response data set is sufficient to define the response data of the cause system and the response data of the response system and the response data of the symptom system. Function output of the function by inputting the input subject answer data set as a function of the function defined by performing the multivariate analysis to the actual answer data set with few or no omissions Analysis means for estimating measures for symptoms related to stress fatigue of each subject based on
And an image output unit configured to output an image of the countermeasure that has been estimated in the format of a predetermined health instruction book. The analysis means estimates a symptom related to stress fatigue of each subject based on the function output, and estimates a countermeasure for the estimated symptom as the countermeasure.
The image output means outputs an image of the estimated symptom in the form of a predetermined evaluation note in parallel with or in parallel with the image output of the estimated countermeasure. The stress fatigue evaluation and health guidance device according to Item 1.   The function is a relationship between the response data of the cause system and the response data of the symptom system by the principal component analysis and the multiple regression analysis as the multivariate analysis, and a relationship between the response data of the correspondence system and the response data of the symptom system The stress / fatigue evaluation / health guidance device according to claim 1 or 2, which is a function determined by leading the stress.   The analysis means is a statistic by executing a simulation in which a difference group of the response data of the causal system for each subject and a difference group of the response data of the corresponding system for each subject are used as a function input to the function. 4. The method according to any one of claims 1 to 3, wherein symptom reduction prediction is performed so that the symptoms of each subject are reduced or improved, and the countermeasure is estimated based on the result of the symptom reduction prediction. Stress fatigue evaluation and health guidance device described in Section.   The analysis means first estimates, as the countermeasure, the one with the largest effect among the predetermined plural types of countermeasures, and then the one with the second effect among the plural types of countermeasures. 5. The stress fatigue evaluation according to any one of claims 1 to 4, characterized by estimating and then estimating a better one than taking one of the plurality of measures, rather than taking it. Health guidance device.   The analysis means is characterized in that, as the countermeasure, a lifestyle or an environmental adjustment for reducing or improving one of the symptoms that is considered to be most affected under a predetermined standard is estimated. The stress fatigue evaluation and health guidance device according to any one of 4.   3. The apparatus according to claim 2, wherein the analysis means estimates the symptom on two axes of an absolute evaluation axis not in the frame of a group to which each subject belongs and a relative evaluation axis in the group. Stress fatigue evaluation and health guidance equipment. The input means urges an operation input indicating that the disclosure of the estimated symptom is agreed or not in parallel with or in parallel with the response of each subject.
When the operation input to the effect of consent is performed, the estimated symptom is disclosed to each of the test subjects, and when the operation input to the effect that the consent is not input, the estimated symptom is the test object The stress / fatigue evaluation / health guidance device according to claim 2 or 7, which is not disclosed in the above. The input means is further configured to be able to input another answer group by each subject with respect to another question group previously set for predetermined radar chart drawing and group analysis.
The analysis means further includes stress fatigue of each of the test subjects and the test subjects, each of which makes an item to be adopted when drawing the radar chart based on another answer group input through the input means. Assess stress fatigue in the population,
9. The image output means outputs the stress fatigue of each subject evaluated and the stress fatigue of the evaluated population in the format of the radar chart, respectively. Stress fatigue evaluation and health guidance device according to one item. The input means is further configured to be able to input another answer group by each subject with respect to another question group previously set for predetermined radar chart drawing and group analysis.
When the analysis means estimates the countermeasure based on the function output,
(1) Based on the function output, estimate symptoms related to stress fatigue of each subject on an absolute evaluation axis that does not touch the frame of the group to which each subject belongs, and (2) based on the function output The condition relating to stress fatigue in the group is estimated by the average value of the condition estimated on the absolute evaluation axis of each subject belonging to the group, and (3) the other input through the input means And a predetermined index related to stress fatigue of each subject defined by at least one item adopted when drawing the radar chart based on the group of answers
The stress / fatigue evaluation according to claim 1, wherein the countermeasure is estimated based on the estimated condition of each subject, the estimated condition for each group, and the predetermined index. Health guidance device.   The analysis means is characterized in that, as the predetermined index, the degree of stress due to work and performance environment, the degree of support and satisfaction from the surroundings, and the degree of self-actualization pertaining to each subject. Stress fatigue evaluation and health guidance device described.   The analysis means is based on the estimated condition of each subject, the estimated condition according to the group, and the predetermined index, and the stress / fatigue intensity of the individual subject to the individual environment Evaluate at least one of response patterns to each subject in question, psychological regulation, and points to be noted in environmental conditions, and estimate the countermeasure for the evaluated at least one. Stress fatigue evaluation and health guidance device described. Response data on the cause system related to stress fatigue, response data on the response system related to stress fatigue, and symptom system related to stress fatigue, which are acquired in a format in which each subject answers a predetermined question group displayed on the screen or in a document An input step of inputting a subject answer data set including answer data of
When the subject response data set is input in the input step or if an analysis instruction is issued in addition to this, the results accumulated by the past and answered by a plurality of workers who worked in the previous working environment A response data set, which is missing by a multivariate analysis on the actual response data set to a function that associates the response data of the cause system and the response data of the corresponding system with the response data of the symptom system Based on the function output of the function, the function answer of the input subject answer data set is input to the function determined by performing the multivariate analysis in the corresponding or less result answer data set Analysis step for estimating measures for symptoms related to stress and fatigue of each subject;
An image output step of outputting an image of the estimated countermeasure in the format of a prescribed health instruction book.   A computer program that causes a computer to function as the stress fatigue evaluation / health guidance device according to any one of claims 1 to 12.