Wellness awareness determination program, device and terminal

Abstract

PURPOSE: To provide a wellness awareness determination program that can determine wellness awareness of customers from medical interview data.SOLUTION: A program is the system that undergoes computation processing of basic data serving as a lot of replies of subjects to a plurality of questions about wellness awareness pertaining to mind and body, and medical interview data serving as a reply of a customer to the question, and determines the wellness awareness of the customer. The system has: factor extraction procedure of extracting, by a factor analysis method from the basic data, an energy factor about an energy flow, a water factor about a water flow and a blood factor about a blood flow; and a wellness awareness determination procedure of calculating a score SA of the energy factor, a score of the water factor and a score of the blood factor as to the customer on the basis of the medical interview data, and, with an arithmetic average of the score of the water factor and the score of the blood factor as a score SL of a fluid flow, expressing wellness awareness pertaining to a flow sense of the customer by a position of a point (SL, SA) in a coordinate plane called a flow identification surface to determine the wellness awareness.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a program, an apparatus, and a terminal for determining a health awareness related to the physical and mental health of a customer or a subject based on interview data.

Background Art

[0002] As a technique for determining the constitution and health status of a customer or a subject based on interview data, for example, the techniques disclosed in Patent Documents 1 to 3 are known.

[0003] Patent Document 1 discloses an invention such as an information processing system in which a user can recognize his / her own state from the constitution and health level. In this invention, the constitution is expressed by six constitution scores for the six constitutions of "qi deficiency", "qi stagnation", "blood deficiency", "blood stasis", "dryness", and "water stagnation" in traditional Chinese medicine. Each constitution score is obtained by summing up the scores pre-assigned to each answer based on the user's answers to a plurality of questions prepared for each constitution. Further, using the six calculated constitution scores, a radar chart is created as a figure formed by using each constitution score as a vertex, and the health level of the user is calculated as the area of the generated radar chart.

[0004] Patent Document 2 discloses an invention such as an information processing system having an acquisition unit that acquires a user's answers to menopausal symptoms, and a determination unit that determines, based on the answers, which of eight balance types ( "excess heat and dampness", "excess heat and dryness", "excess cold and dampness", "excess cold and dryness", "deficiency heat and dampness", "deficiency heat and dryness", "deficiency cold and dampness", "deficiency cold and dryness") the user's balance state belongs to, which are represented by three axes of relative classifications of actual / virtual, cold / hot, and wet / dry. The questions consist of a total of 30 questions, including 5 questions regarding "excess", 5 questions regarding "deficiency", 5 questions regarding "cold", 5 questions regarding "heat", 5 questions regarding "wetness", and 5 questions regarding "dryness". For example, if the number of "excess" answers is more than the number of "deficiency" answers, it is determined that the user's balance state is one of "excess heat and dampness", "excess heat and dryness", "excess cold and dampness", or "excess cold and dryness".

[0005] Patent Document 3 discloses an invention such as a constitution determination method that determines a subject's temperament and constitution by machine learning based on interview information and biological information. In this invention, the constitution is determined by a classification that combines the temperament innate to the subject and the constitution that is formed on top of this temperament. There are multiple types of temperament, such as "qi deficiency", "qi stagnation", and "qi reversal", and multiple types of constitution, such as "blood deficiency", "blood stasis", and "fluid deficiency". A large amount of pre-prepared interview data (including biological information) is used to obtain a determination function for determining temperament and constitution by machine learning.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0007] In the technology described in Patent Document 1, a plurality of questions are prepared in advance for each constitution, and a user's constitution score is calculated based on the answers to those questions. How to classify the user's constitution is determined in advance based on Kampo theory. This document does not disclose finding an appropriate expression (or classification) of the user's health awareness based on the big data of the questionnaire. Such an idea cannot be found. Also in the technology described in Patent Document 2, the questions for determining eight balance types by three axes represented by the relative classifications of deficiency and excess, cold and heat, and dampness and dryness are selected in advance based on Kampo theory. This document also does not have the idea of finding an appropriate expression (or classification) of the user's health awareness based on the big data of the questionnaire. In the technology described in Patent Document 3, the determination function for determining the temperament and constitution of the subject is determined by a machine learning (supervised learning) method from the big data of the questionnaire (including biological information). The classification of temperament and constitution in the teacher data is determined in advance based on Kampo theory. This document also does not have the idea of finding an appropriate expression (or classification) of the subject's health awareness based on the big data of the questionnaire by "unsupervised learning". In addition, Japanese Patent Application Laid-Open No. 2021-047504, Japanese Patent Application Laid-Open No. 2015-504043, Japanese Patent Application Laid-Open No. 2012-523947, Japanese Patent Application Laid-Open No. 2002-140434, Japanese Patent Application Laid-Open No. 2011-087919, Japanese Patent Application Laid-Open No. 2002-119513, Japanese Utility Model Publication No. 59-155648, and Japanese Utility Model Publication No. 59-093403 also disclose inventions that classify the constitution of a user using the user's answers to questions for discriminating the type of constitution based on Kampo theory. However, these inventions do not have the idea of finding an appropriate expression (or classification) of the user's health awareness related to the body and mind based on the big data of the questionnaire without assuming Kampo theory. An object of one embodiment of the present invention is to find an appropriate expression (or classification) of health awareness related to physical and mental health by using a factor analysis method, which is a kind of unsupervised learning, for big data of questionnaires, and to provide a health awareness determination program capable of determining the health awareness of customers. Another object of another embodiment of the present invention is to provide a health awareness determination program capable of predicting whether or not a customer is concerned about matters related to physical and mental health by using the appropriate expression (or classification) of the above-mentioned health awareness. Still another object of another embodiment of the present invention is to provide a health awareness determination device configured to be able to execute the above health awareness determination program and / or a terminal for the device.

Means for Solving the Problems

[0008] The present invention has been made to solve such problems. A first aspect of the present invention is a program for calculating and processing basic data, which is the answers of a large number of subjects to three or more questions regarding health awareness related to physical and mental health, and questionnaire data, which is the answers of a customer to the above questions, to determine the health awareness of the customer. From the basic data, by factor analysis, at least a qi factor related to the circulation of qi, a water factor related to the circulation of water, and a blood factor related to the circulation of blood are extracted to calculate factor score coefficients, or a factor extraction procedure for reading out factor score coefficients that have been calculated in advance according to the above factor extraction procedure and stored in a storage means, and based on the questionnaire data and the factor score coefficients, the score S of the qi factor of the customer A and the score S of the water factor w and the score S of the blood factor B are calculated, and further, the arithmetic mean of the score S of the water factor w and the score S of the blood factor B is taken as the score S of the fluid factor related to the circulation of fluid L , and a health awareness determination procedure for expressing and determining the health awareness related to the customer's sense of circulation based on the position of the point (S L , S A ) in a coordinate plane called the circulation discrimination plane. The health awareness determination program has the above.

[0009] The second form of the present invention is, in the first form, wherein the question includes at least one of items related to anemia, lack of sleep, nervousness, and swelling of the feet, which are closely related to the circulation of qi, and at least one of items related to swelling of the feet, overeating, constipation (tendency), and lack of exercise, which are closely related to the circulation of water, and at least one of items related to low blood pressure, anemia, and coldness in the feet, which are closely related to the circulation of blood, and is a health awareness determination program.

[0010] The third form of the present invention is, in the first form, when a confirmation question regarding physical and mental health, in which the answer is a two-choice of "concerned" and "not concerned", is asked to the subject related to the basic data separately from the question related to the basic data, the ratio of the subjects who answered "concerned" is minimal in the region where the score S of the qi factor is small on the circulation discrimination surface, and maximal in the region where the score S A is large, and the confirmation question is a health awareness determination program which is a question regarding any one of health status, blood and lymph flow, various symptoms of pain, hormone balance, mental state, immunity, fatigue, sleep, scalp and hair, diet, and sensitive skin. A

[0011] The fourth form of the present invention is a program for calculating and processing basic data which is the answers of a large number of subjects to three or more questions regarding health awareness related to the body and mind, and interview data which is the answers of customers to the questions, and determining the health awareness of the customers. From the basic data, by factor analysis, at least a qi factor related to the circulation of qi, a water factor related to the circulation of water, and a blood factor related to the circulation of blood are extracted to calculate factor score coefficients, or a factor reading procedure for reading out factor score coefficients calculated in advance according to the factor extraction procedure and stored in a storage means, and based on the interview data and the factor score coefficients, the score S of the water factor, the score S of the blood factor, and the score S of the qi factor of the customer are calculated, and a point (S w , S B , S A of the customer in a coordinate space called a circulation discrimination space is calculated. w , S B , S​A and a health consciousness determination procedure for expressing and determining the customer's health consciousness related to circulation based on the position of the

[0012] A fifth aspect of the present invention is a program for judging the health consciousness of a customer by arithmetically processing basic data, which are answers of a large number of subjects to three or more questions regarding health consciousness related to mind and body, and interview data, which are answers of the customer to the said questions, the program comprising a factor extraction procedure for extracting at least a disorder factor relating to clarity of the site and cause of deterioration in condition and a repetitive chronic factor relating to the rhythm of deterioration and improvement in condition from the basic data by a factor analysis method, and calculating a factor score coefficient, or a factor reading procedure for reading out a factor score coefficient calculated in advance according to the factor extraction procedure and stored in a storage means, and a factor reading procedure for calculating a score S of the disorder factor of the customer based on the interview data and the factor score coefficient. FS and the score for recurrent chronic factors S RC and calculate the point (S FS ,S RC and a health consciousness determination procedure for expressing and determining the health consciousness related to the vague symptoms of the customer based on the position of the symptom.

[0013] The sixth aspect of the present invention is the fifth aspect of the present invention, wherein, when subjects related to the basic data are asked a confirmation question about physical and mental health, which has two options of "I'm worried" and "I'm not worried", in addition to the questions related to the basic data, the ratio of subjects who answered "I'm worried" is greater than the score S of the disorder factor on the vague complaint discrimination surface. FS is smallest in the small region, and the score S FS The health awareness assessment program includes questions about health condition, blood and lymph flow, various pain symptoms, hormone balance, mental state, immunity, fatigue, sleep, scalp and hair, diet, and sensitive skin.

[0014] The seventh aspect of the present invention is a health awareness determination program in any one of the first to sixth aspects, basic data that is the responses of a large number of examinees to three or more questions regarding the body and mind, or factor score coefficients calculated by factor analysis from the basic data, and interview data that is the customer's responses to the questions, and includes a computer configured to be capable of executing the health awareness determination program, and is a health awareness determination device for determining the health awareness of the customer, having a storage means for storing the same.

[0015] The eighth aspect of the present invention is, in the seventh aspect, a computer configured to be capable of executing a health awareness determination program as a server, and a terminal capable of two-way communication with the server via a network, having an input means for inputting interview data that is the customer's responses to the questions, a transmission means for transmitting the input interview data to the server, a reception means for receiving the determination result of the customer's health awareness from the server, and an output means for displaying the received determination result, and is a terminal for a health awareness determination device.

Advantages of the Invention

[0016] According to one aspect of the present invention, by using the factor analysis method, which is a kind of unsupervised learning, for the big data of the questionnaire, it is possible to find an appropriate expression (or classification) of health awareness and provide a health awareness determination program capable of determining the health awareness of a customer. According to another aspect of the present invention, it is possible to provide a health awareness determination program capable of predicting whether the customer is concerned about matters related to the body and mind by using the above-mentioned appropriate expression (or classification) of health awareness. According to still another aspect of the present invention, it is possible to provide a health awareness determination device configured to be capable of executing the above health awareness determination program and / or a terminal for the device.

Brief Description of the Drawings

[0017]

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Embodiments for Carrying Out the Invention

[0018] Next, embodiments of a health awareness determination program, a health awareness determination device, and a terminal for the device according to the present invention will be described in detail with reference to the drawings.

[0019] According to a first aspect of the present invention, there is provided a program for arithmetically processing basic data, which are answers from a large number of subjects to three or more questions regarding health consciousness related to mind and body, and interview data, which are answers from a customer to the questions, to determine the health consciousness of the customer, the program comprising a factor extraction procedure for extracting at least a Qi factor relating to the circulation of Qi, a Water factor relating to the circulation of water, and a Blood factor relating to the circulation of blood from the basic data by a factor analysis method, and calculating factor score coefficients, or a factor reading procedure for reading out factor score coefficients calculated in advance according to the factor extraction procedure and stored in a storage means, and a factor reading procedure for calculating a Qi factor score S of the customer based on the interview data and the factor score coefficients. A and the water factor score S w And the blood factor score S B Calculate the water factor score S w and blood factor score S B The arithmetic mean of the above is the score S of the fluid factor related to fluid circulation. L Let the point (S L ,S A and a health consciousness determination procedure for expressing and determining the customer's health consciousness related to circulation based on the position of the

[0020] (Advantages of using factor analysis to assess health consciousness related to circulation through interviews) In this embodiment of the present invention, in determining health consciousness related to circulation by interview, the following is determined only from the customer's answers to direct questions about circulation of qi, water, and blood: Instead of calculating the score for each factor, the number of questions directly asked is reduced, and factor analysis is used to integrate all the answers to about 10 to 100 questions, preferably about 15 to 40 questions, about general health consciousness related to the body and mind, to calculate the score for each factor of the customer, and the health consciousness related to the circulation sense of the customer is judged comprehensively and indirectly based on the scores of these factors, so that the accuracy of the judgment can be improved. In addition, the score (S L ,S ABased on the position of , the health awareness related to the customer's sense of circulation can be accurately determined and visually represented, so that both the customer and the seller can grasp and share the judgment result of the health awareness related to the customer's sense of circulation in a short time.

[0021] (The number of subjects in the basic data) Here, the "large number of subjects" in the basic data is not limited, but generally refers to 1,000 or more subjects, preferably 3,000 or more subjects, and more preferably 5,000 or more subjects. The larger the scale of the basic data composed of the responses of the subjects belonging to the sample population randomly sampled from the population of the target customer group, the smaller the deviation between the relative position of each customer in the sample population grasped by the score of each factor and the true relative position of the customer in the population, and the higher the judgment accuracy of the health awareness.

[0022] (Circulation discrimination surface) The circulation discrimination surface is a coordinate plane. In principle, taking the score of the liquid factor of the customer or the subject as S L and the score of the qi factor as S A , it is a coordinate plane that represents and determines the health awareness related to the sense of circulation of the customer or the subject according to the position of the point (S L , S A ). Here, although the score S L of the liquid factor takes real values, S L is transformed by a non-decreasing function so that it takes values belonging to a specific interval [a, b] or (a, b), such as a closed interval [0, 1] or an open interval (0, 1), where a and b are real numbers. After the transformation, S L (denoted as S L ’) can be used instead of S L , or, for example, S L that is discretized into multiple levels in an arbitrary manner by applying a non-decreasing function transformation, such as in 5 levels of 0.5, 1.5, 2.5, 3.5, 4.5 (also denoted as S L ’), can be used instead of S L . Similarly, for the score S A of the liquid factor, S A ’ after the same transformation can be used instead of S Amay be used instead. S L ’ and S A ’ both take substantially continuous values belonging to a specific interval, the meguri discrimination surface that expresses and determines the health awareness related to the customer's or subject's sense of circulation based on the position of the point (S L ’, S A ) becomes rectangular. S L ’ and S A ’ both take values discretized into multiple stages, the meguri discrimination surface that expresses and determines the health awareness related to the customer's or subject's sense of circulation based on the position of the point (S L ’, S A ) is a set of lattice points (or a set of grid cells) formed by the intersection of a plurality of vertical lines and a plurality of horizontal lines. The above-described points are the same for the indefinite complaint discrimination surface described later.

[0023] According to the second aspect of the present invention, in the first aspect, the questionnaire includes at least one of items related to anemia, lack of sleep, nervousness, and swelling of the feet, which are closely related to the circulation of qi, and at least one of items related to swelling of the feet, overeating, constipation (tendency), and lack of exercise, which are closely related to the circulation of water, and at least one of items related to low blood pressure, anemia, and coldness in the feet, which are closely related to the circulation of blood. A health awareness determination program can be provided. By the questionnaire satisfying the above conditions, it can be expected that the factors extracted as a result of factor analysis include factors related to each of the circulation of qi, the circulation of water, and the circulation of blood.

[0024] (Score S of the fluid factor L (Definition and its graphical meaning) The score S of the fluid factor L is defined by the following formula 1. (Formula 1) S L = (S B + S W ) / 2 That is, the score S of the fluid factor L is defined as the arithmetic mean of the score S of the blood factor B and the score S of the water factor W . The score S of the liquid factor defined by Equation 1 L will be described in terms of its graphical meaning. As shown in Fig. (1-1), on the coordinate plane where the score S of the blood factor is taken on the horizontal axis B and the score S of the water factor is taken on the vertical axis W , a straight line passing through the origin and making an angle of 45° with the horizontal axis in the first quadrant is taken, and this straight line is called the diagonal axis. Let the foot of the perpendicular dropped from the point P(S B , S W ) to the diagonal axis be the point Q. The value obtained by dividing the distance between the point Q and the origin (more precisely, the signed distance) by the square root of 2 is the score S L of the liquid factor. The score S L of the liquid factor is considered to represent the "degree of physical and mental discomfort".

[0025] (Definition of the degree of physical and mental discomfort S C and its graphical meaning) The degree of physical and mental discomfort S C is defined by the following Equation 2. (Equation 2) S C = (S L + S A ) / 2 That is, the degree of physical and mental discomfort S C is defined as the arithmetic mean of the score S L of the liquid factor and the score S A of the qi factor. The graphical meaning of the degree of physical and mental discomfort S C defined by Equation 2 will be described. As shown in Fig. (1-2), on the coordinate plane (the circulation discrimination plane) where the score S of the liquid factor is taken on the horizontal axis L and the score S of the qi factor is taken on the vertical axis A , a straight line passing through the origin and making an angle of 45° with the horizontal axis in the first quadrant is taken, and this straight line is called the diagonal axis. Let the foot of the perpendicular dropped from the point R(S L , S A ) to the diagonal axis be the point S. The value obtained by dividing the distance between the point S and the origin (more precisely, the signed distance) by the square root of 2 is the degree of physical and mental discomfort S C . The greater the degree of physical and mental discomfort, the more conscious one is of the poor condition of the body and mind.

[0026] According to the third aspect of the present invention, in the first aspect, when a confirmation question regarding physical and mental health, which is a binary choice of "concerned" or "not concerned", is asked to the subject related to the basic data separately from the question related to the basic data, the ratio of the subjects who answered "concerned" is the score S of the qi factor on the meguri discrimination surface A is the minimum in the region where is small, and the score S A is the maximum in the region where is large, and the confirmation question can provide a health awareness determination program that is a question regarding any one of health status, blood and lymph flow, various symptoms of pain, hormone balance, mental state, immunity, fatigue, sleep, scalp and hair, diet, and sensitive skin. Here, the questions related to the basic data are about 10 to about 100 questions that use their answers for factor analysis. The confirmation questions, which are different from the questions related to the basic data, are several to several dozen questions provided to confirm the accuracy of health awareness determination based on the position on the meguri discrimination surface. According to this aspect of the present invention, when the scores of each factor of a customer are displayed on the meguri discrimination surface as described above, the probability that the customer's answer to the confirmation question will be "concerned" can be predicted with high accuracy based on the position on the meguri discrimination surface.

[0027] According to the fourth aspect of the present invention, it is a program for calculating the basic data, which is the answers of a large number of subjects to three or more questions regarding health awareness related to the body and mind, and the interview data, which is the customer's answers to the questions, to determine the customer's health awareness. From the basic data, by factor analysis, at least a qi factor related to the circulation of qi, a water factor related to the circulation of water, and a blood factor related to the circulation of blood are extracted to calculate a factor score coefficient, or a factor reading procedure for reading out the factor score coefficient that has been calculated in advance according to the factor extraction procedure and stored in the storage means, and based on the interview data and the factor score coefficient, the customer's score S of the water factor w and the score S of the blood factor B and the score S of the qi factor A are calculated, and a point (S w , S B , SA ) position can provide a health awareness determination program having a health awareness determination procedure for expressing and determining the health awareness related to the customer's sense of circulation.

[0028] (Circulation identification space) The circulation identification space is a coordinate space. In principle, the score of the water factor of the customer or the subject is S w , the score of the blood factor is S B , and the score of the qi factor is S A . As such, the health awareness related to the customer's or the subject's sense of circulation is expressed and determined by the position of the point (S w , S B , S A ). Here, the score S of the water factor W takes a real value, but after performing a non-decreasing function transformation on S W so that it takes a value belonging to a specific interval, the S (denoted as S W ’) can be used instead of S W , or S W can be discretized into multiple levels in an arbitrary manner after performing a non-decreasing function transformation on S W (also denoted as S W ’) and used instead of S W . Similarly, for the score S of the blood factor B and the score S of the qi factor A , the transformed S B ’ and S A ’ can be used instead of S B and S A respectively. When all of S w ’, S B ’, and S A ’ can take approximately continuous values belonging to a specific interval, the circulation identification space for expressing and determining the health awareness related to the customer's or the subject's sense of circulation by the position of the point (S w ’, S B ’, S A ’) is a rectangular parallelepiped. When all of S w ’, S B ’, and S A ’ can take discretized values in multiple levels, the point (S w ’, S B ’, SA The circulation discrimination space for expressing and determining the health awareness related to the customer's or subject's sense of circulation according to the position of ') is a set of lattice points (or a set of cubic dice arranged in a lattice) formed by the intersection of a plurality of vertical lines, a plurality of horizontal lines, and a plurality of perpendicular lines.

[0029] In this main form of the present invention, when determining the health awareness related to the sense of circulation through a questionnaire, instead of calculating each score only from the customer's answers to direct questions regarding the circulation of qi, the circulation of water, and the circulation of blood, the number of direct questions is reduced, and factor analysis is used to comprehensively calculate the scores of each factor of the customer by combining all the answers to about 10 to 100 questions, preferably about 15 to 40 questions, regarding the health awareness related to the physical and mental state in general. The health awareness related to the customer's sense of circulation is determined comprehensively and indirectly based on the scores of these factors, so the accuracy of the determination can be improved. In addition, the point (S w , S B , S A ) in the circulation discrimination space accurately determines the health awareness related to the customer's sense of circulation and expresses it three-dimensionally and visually. Therefore, both the customer and the seller can grasp and share the determination result of the health awareness related to the customer's sense of circulation in a short time.

[0030] According to the fifth form of the present invention, it is a program for performing arithmetic processing on basic data, which is the answers of a large number of subjects to three or more questions regarding the health awareness related to the physical and mental state, and questionnaire data, which is the answers of the customer to the above questions, to determine the health awareness of the customer. From the basic data, at least a factor extraction procedure for extracting a disorder factor related to the clarity of the site and cause of the deterioration of the condition and a repetitive chronic factor related to the rhythm of the deterioration and improvement of the condition by factor analysis and calculating the factor score coefficient, or a factor reading procedure for reading out the factor score coefficient calculated in advance according to the above factor extraction procedure and stored in the storage means, and based on the questionnaire data and the factor score coefficient, the score S of the disorder factor of the customer FS and the score S of the repetitive chronic factor RC are calculated, and the point (S FS,S RC It is possible to provide a health awareness determination program having a health awareness determination procedure for expressing and determining the health awareness related to the customer's indefinite complaints based on the position of

[0031] (Malaise factor and repetitive chronic factor) The malaise factor is a factor related to the site and clarity of the cause of the deterioration of the condition. When the score of the malaise factor is large, the site and cause of the deterioration of the condition are unclear (=malaise = the condition is out of order), and when the score is small, the site and cause of the deterioration of the condition are clear (=dyscomfort = the condition is bad). The questionnaire items that contribute positively to the score of the malaise factor are items such as blushing on the face, tired eyes, swelling in the feet, and headache, and the questionnaire items that contribute negatively are items such as decreased vision, lack of exercise, irregular menstruation, and stiff shoulders. The malaise factor is not a unipolar factor representing the strength of the degree of discomfort, but a bipolar factor. That is, a large score of the malaise factor indicates a strong degree of "(indistinct cause) malaise", and a small score of the same indicates a strong degree of "(distinct cause) discomfort". The repetitive chronic factor is a factor related to the rhythm of the deterioration and improvement of the condition. A large score of the repetitive chronic factor indicates that the discomfort continues and has become chronic (=chronic), and when the score is small, it indicates that the discomfort is repeated with a period of remission (=repetitive). The questionnaire items that contribute positively to the score of the repetitive chronic factor are items such as bad breath, decreased vision, low back pain of unknown cause, and blushing on the face, and the questionnaire items that contribute negatively are items such as coldness in the feet, swelling in the feet, menstrual pain, and being irritable. The repetitive chronic factor is also not a unipolar factor representing the strength of the degree of discomfort, but a bipolar factor. That is, a large score of the repetitive chronic factor indicates a strong degree of "chronicity", and a small score of the same factor indicates a strong degree of "repetition".

[0032] (Indefinite distress identification plane) The indefinite distress identification plane is a coordinate plane which, in principle, takes the score of the discomfort disorder factor of a customer or a subject as S FS , and the score of the repetitive chronic factor as S RC , and expresses and determines the health awareness related to the indefinite distress of the customer or the subject according to the position of the point (S FS , S RC ). Here, instead of the score S FS of the discomfort disorder factor, S FS is subjected to a transformation by a continuous or discontinuous non-decreasing function, and the transformed S FS (denoted as S FS ’) may be used instead of S FS . The same applies to the score S RC of the repetitive chronic factor. As shown in Fig. (5-12), the indefinite distress identification plane can be divided, for example, into two left and right regions: a “disorder” region with a large score of the discomfort disorder factor and a “discomfort” region with a small score of the factor. Also, the indefinite distress identification plane can be divided, for example, into two upper and lower regions: a “chronic” region with a large score of the repetitive chronic factor and a “repetitive” region with a small score of the factor. By combining these two types of divisions, the indefinite distress identification plane can be divided into four regions: an upper right “chronic disorder” region, an upper left “chronic discomfort” region, a lower left “discomfort repetition” region, and a lower right “disorder repetition” region.

[0033] (Definition of chronic disorder degree) The chronic disorder degree is defined by the following formula 3. (Formula 3) Chronic disorder degree = (S FS + S RC ) / 2 That is, the chronic disorder degree is the average of the score S FS of the discomfort disorder factor and the score S RCIt is defined as the arithmetic mean. Since both the malcoordination factor and the repetitive chronicity factor are bipolar factors, the degree of chronic malcoordination is also a bipolar quantity. In terms of the indefinite complaint discrimination aspect, the degree of chronic malcoordination is large in the "chronic malcoordination" area in the upper right and small in the "malcoordination repetition" area in the lower left. In Fig. (5-12), the bidirectional arrow A indicates the direction in which the degree of chronic malcoordination increases and decreases. When the degree of chronic malcoordination is large, troubles such as "uneasiness" like menopausal symptoms are predicted. When the degree of chronic malcoordination is small, uneasiness symptoms associated with PMS and menstrual difficulties in the younger generation are predicted.

[0034] According to the sixth aspect of the present invention, in the fifth aspect, when a confirmation question regarding physical and mental health, where the answer is a binary choice of "concerned" or "not concerned", is asked to the subject related to the basic data separately from the questions related to the basic data, the ratio of the subjects who answered "concerned" is such that, on the indefinite complaint discrimination surface, the score S of the malcoordination factor FS is the minimum in the area where it is small, and the score S FS is the maximum in the area where it is large, and the confirmation question can provide a health awareness determination program that is a question regarding any one of health status, blood and lymph flow, various symptoms of pain, hormone balance, mental state, immunity, fatigue, sleep, scalp and hair, diet, and sensitive skin. According to this aspect, by displaying the scores of each factor of the customer on the indefinite complaint discrimination surface as described above, the probability that the customer's answer to the confirmation question will be "concerned" can be predicted with high accuracy based on the position on the indefinite complaint discrimination surface, or based on the combination of the position on the indefinite complaint discrimination surface and the position on the meguri discrimination surface.

[0035] According to the seventh aspect of the present invention, there is provided a health awareness determination device for determining the health awareness of the customer, including a computer configured to be capable of executing the health awareness determination program of any one of the first to sixth aspects, and storage means for storing the basic data, which is the answers of a large number of subjects to three or more questions regarding the body and mind, or the factor score coefficients calculated by factor analysis from the basic data, and the interview data, which is the answers of the customer to the questions. ​

[0036] According to the eighth aspect of the present invention, in the seventh aspect, a computer configured to be able to execute a health awareness determination program is used as a server, and is a terminal capable of two-way communication with the server via a network. The terminal includes an input means for inputting inquiry data that is an answer to the customer's said inquiry, a transmission means for transmitting the input said inquiry data to the server, a reception means for receiving a determination result of the customer's health awareness from the server, and an output means for displaying the received said determination result. Thus, a terminal for a health awareness determination device can be provided.

[0037] Next, examples will be described.

[0038] <1. Factor analysis and determination of factor score coefficients> (Extraction of basic data and factors) The inventor of the present invention conducted an inquiry on 6,500 female subjects aged 29 to 69 years using a set of 75 questions useful for analyzing health awareness shown in the tables of FIGS. 2A and 2B, and obtained valid responses including the confirmation questions shown in FIG. 2C from 5,161 people. The respondents are in almost a constant proportion of people in each age group at 5-year intervals. The analysis result obtained by analyzing this valid response by factor analysis using it as basic data, and a health awareness determination program and the like according to one aspect of the present invention will be described. Figure 3 is a table showing the factor score coefficients of 15 factors extracted by analyzing the basic data consisting of the binary response values (0 or 1) of each subject for each question in the above-mentioned 75-item questionnaire set using factor analysis with an orthogonal model. The factor score coefficients are shown only for the 30 questions of h01 to h30, and are omitted for other questions. Also, the description of factor loadings is omitted. The number of factors to be extracted was set to 15 because the number of eigenvalues of the covariance matrix of the above response values standardized to an average of 0 and a standard deviation of 1 that are 1 or more is 15 (Kaiser-Guttman criterion). The maximum likelihood method was used for estimating the factor loadings, and six rotations were performed until convergence using the varimax method without Kaiser normalization. The regression method is used for calculating the factor scores. For any factor, the score of that factor for the subject can be calculated (excluding the deviation of the constant) by multiplying the factor score coefficient by the response value of the subject for each question and taking the sum for all questions.

[0039] (Selection of 30-item questionnaire) Next, considering the ease of the questionnaire, 30 questions (h01 to h30) were selected from the 75 questions based on the criterion of whether or not they significantly contribute to the variance of the scores related to each factor. Hereinafter, when calculating the score related to an arbitrary factor for each subject, instead of taking the sum for all 75 questions of the product of the factor score coefficient and the response value of the subject, the sum is taken only for the above 30 questions, and for simplicity, the partial sum calculated in this way is called by the same term "score related to the factor" or "factor score". Strictly speaking, taking the partial sum loses the orthogonality between the factor scores related to two different factors. However, as described above, since 30 questions that significantly contribute to the variance of the factor scores related to each factor are selected, the two are in a state of approximate orthogonality.

[0040] (Naming of factors) Five out of the 15 factors were named as follows. Note that the terms of Kampo theory were referred to in naming the factors. However, it should be noted that the above-mentioned questionnaire items and the factor analysis procedure are independent of Kampo theory, and each factor was naturally obtained from big data in the process of factor extraction including varimax rotation. Factor 3 is a factor related to "circulation of water". The higher the score related to this factor, the worse the "circulation of water" is. In this specification, this factor is referred to as the "water factor". As can be read from Figure 3, the questionnaire items that contribute positively to the score related to this factor are items such as swelling in the feet, overeating, constipation (susceptibility), lack of exercise, and cold feet, and the items that contribute negatively are items such as eye fatigue. Factor 9 is a factor related to "circulation of qi". The higher the score related to this factor, the worse the "circulation of qi" is. In this specification, this factor is referred to as the "qi factor". As can be read from Figure 3, the questionnaire items that contribute positively to the score related to this factor are items such as anemia, lack of sleep, nervousness, and swelling in the feet, and the items that contribute negatively are items such as eye fatigue and irregular menstruation. Factor 15 is a factor related to "circulation of blood". The higher the score related to this factor, the worse the "circulation of blood" is. In this specification, this factor is referred to as the "blood factor". As can be read from Figure 3, the questionnaire items that contribute positively to the score related to this factor are items such as low blood pressure, anemia, and swelling in the feet, and the item that contributes negatively is overeating. Factor 7 is a factor related to "disharmony-dysregulation", which is a bipolar factor. A high score related to this factor means "dysregulation", and a low score means "disharmony". In this specification, this factor is referred to as the "disharmony-dysregulation factor". As can be read from Figure 3, the questionnaire items that contribute positively to the score related to this factor are items such as blushing on the face, eye fatigue, swelling in the feet, and headache, and the items that contribute negatively are items such as decreased vision, lack of exercise, and irregular menstruation. Factor 6 is a factor related to "recurrent chronicity". A high score related to this factor means "chronicity of discomfort", and a low score means "recurrence with a remission period of discomfort". In this specification, this factor is referred to as the "recurrent chronicity factor". As can be read from FIG. 3, the questionnaire items that contribute positively to the score related to this factor are bad breath, decreased vision, low back pain of unknown cause, facial flushing, etc., and the questionnaire items that contribute negatively are cold feet, swelling of the feet, menstrual pain, etc. In this example, the binary response values (0 or 1) of each subject for each questionnaire were used, but the questionnaire (response value) may be a three-choice (e.g., 0, 1, or 2), four-choice, five-choice, or more. Also, in this example, the factor scores were calculated by the regression method, but the method for calculating the factor scores in the present invention is not limited to the regression method. Any calculation method that can express the factor score as a linear combination of observed quantities, such as the Bartlett method, the Anderson-Rubin method, etc., can be used in the present invention.

[0041] (Normalization of factor score coefficients) Here, the method for calculating the score of each factor of the customer and the normalization of the factor score coefficients shown in FIG. 3 are supplemented. The score fi of the i-th factor can generally be calculated by the following formula 4. (Formula 4) fi = Σ aij × (xj - mj) / σj Here, aij is the (original) factor score coefficient estimated by factor analysis based on the basic data, xj is the value of the customer's response to the j-th questionnaire, and mj and σj are the average value and standard deviation of the response values of the subjects to the j-th questionnaire in the basic data. Σ means the sum over j. In formula 4, the sum over j generally extends over all the questionnaires (e.g., 75 items) described in the questionnaire related to the basic data. However, when some questionnaires are selected from the questionnaires described in the questionnaire related to the basic data when interviewing the customer, the sum over j in formula 4 extends over the questionnaires selected in the interview (e.g., 30 items). Now, when the questions have only binary answers (0 or 1), it is convenient to consider the value aij / σj (let's call it cij) obtained by dividing the (original) factor score coefficient aij by the standard deviation σj. This is because when calculating the factor scores of the subjects or customers, the factor scores can be calculated (except for an additive constant) by simply adding up cij for the questions with an answer value of 1. In this specification, unless otherwise specified, cij will be referred to as the factor score coefficient, and a ij will be referred to as the (original) factor score coefficient.

[0042] <2. Divide the encounter discrimination surface into a 5×5 grid for health awareness determination> (Distribution on the encounter discrimination surface of people who are "concerned about their health status") The basic data includes, in addition to the above 75 questions, the answer values (0 or 1) to the 11 binary confirmation questions (c1 to c11) regarding health awareness related to the physical and mental aspects shown in Figure 2C. For example, the number of valid answers to the confirmation question c1 regarding "health status" is 5161, and the number of valid answers to the other confirmation questions c2 to c11 is also approximately the same. Each subject included in the above basic data can be placed at a point (coordinates are (S L on the horizontal axis and the value S A of the qi factor score discretized into 5 levels from 1 to 5 on the vertical axis, which is a point (coordinate) on the encounter discrimination surface consisting of 5×5 (= 25) grids, that is, a grid). L ,S A )) on the 5×5 grid. Here, the discretization of the score of the ye factor is to divide the interval between the maximum value and the minimum value into 5 equal intervals (category 1 to category 5). Categories 1 to 4 are all intervals that include the left end but not the right end, and category 5 is an interval that includes both ends. When the score belongs to each category i for i = 1, 2, ···, 5, the discrete value of the factor score is set to i. It is considered that the probability that a customer who has received the confirmation question c1 answers YES varies depending on the position in the cyclic identification space. That probability can be estimated from the basic data. Generally, as shown in the table diagram on the left side of Fig. (4-1), the higher the score of the liquid factor, the higher the score of the qi factor, and the higher the degree of physical and mental cyclic discomfort, the higher the proportion of subjects who answered that they were "concerned about their health status". Regarding the "degree of physical and mental cyclic discomfort", refer to Equation 2. The proportion of subjects is shown as a percentage (%), and when the number of subjects belonging to each cell is 5 or less, the proportion is not displayed.

[0043] An explanation will be given for the diagram on the right side of Fig. (4-1). Three thick arrows are drawn. The "2.2 times" written above the rightward arrow means that the proportion of subjects who answered that they were "concerned about their health status" among the subjects whose liquid factor score belongs to either category 4 or 5 is 2.2 times the proportion of subjects who answered that they were "concerned about their health status" among the subjects whose liquid factor score belongs to either category 1, 2, or 3. Also, the "2.4 times" written above the upward arrow means that the proportion of subjects who answered that they were "concerned about their health status" among the subjects whose qi factor score belongs to either category 4 or 5 is 2.4 times the proportion of subjects who answered that they were "concerned about their health status" among the subjects whose qi factor score belongs to either category 1, 2, or 3. Also, the "2.4 times" written above the upper-right diagonal arrow means that the proportion of subjects who answered that they were "concerned about their health status" among the subjects whose degree of physical and mental cyclic discomfort belongs to either category 4 or 5 is 2.4 times the proportion of subjects who answered that they were "concerned about their health status" among the subjects whose degree of physical and mental cyclic discomfort belongs to either category 1, 2, or 3. Furthermore, being written as 1.4 times the blood factor means that the ratio of the subjects who answered that they were concerned about their "health status" among the subjects whose blood factor scores belong to either category 4 or 5 is 1.4 times that of the subjects who answered that they were concerned about their "health status" among the subjects whose blood factor scores belong to any of categories 1, 2, or 3. Also, being written as 2.1 times the water factor means that the ratio of the subjects who answered that they were concerned about their "health status" among the subjects whose water factor scores belong to either category 4 or 5 is 2.1 times that of the subjects who answered that they were concerned about their "health status" among the subjects whose water factor scores belong to any of categories 1, 2, or 3.

[0044] (Distribution on the identification surface of people who are concerned about other confirmation questionnaire items) Regarding each of the 10 items c2 to c11 of the confirmation questionnaire related to the body and mind other than "health status", that is, "blood and lymph flow", "various symptoms of pain", "hormone balance", "mental state", "immunity", "fatigue", "sleep", "scalp and hair", "diet", and "sensitive skin", the figures showing the distribution on the identification surface of the subjects are Figures (4-2) to (4-11). Regarding the items of the confirmation questionnaire other than "sensitive skin", generally, the higher the score of the liquid factor, the higher the score of the qi factor, and the greater the degree of physical and mental discomfort, the higher the ratio of the subjects who answered that they were concerned about the item. Regarding "sensitive skin", generally, the ratio of the subjects who answered that they were concerned about "sensitive skin" inside the identification surface is small, and there is a tendency to be large at the peripheral part of the identification surface.

[0045] Among the subjects whose degree of physical and mental discomfort belongs to either category 4 or 5, the ratio of the subjects who answered that they were concerned about the items of the confirmation questionnaire is how many times that of the subjects whose degree of physical and mental discomfort belongs to any of categories 1, 2, or 3 and who answered that they were concerned about the item. When the item of the confirmation questionnaire is any of the 10 items other than "sensitive skin", it is 2.2 times or more. It can be seen that the degree of physical and mental discomfort is useful in predicting whether the subjects are concerned about the items of the confirmation questionnaire, which are matters of concern related to the subjects' body and mind.

[0046] In this embodiment, the cyclical discrimination surface is considered to be divided into a 5×5 grid. In general, however, the cyclical discrimination surface may be divided into an m×n grid and the same analysis may be performed. Here, m and n are each integers of 1 or more.

[0047] <3. Health awareness determination by dividing the indefinite distress discrimination surface into 5×5 grids> (Distribution on the indefinite distress discrimination surface of people who are concerned about "health status") For each subject included in the above basic data, in the same manner as in the case of the above cyclical discrimination surface, as shown in the left table of FIG. (5-1), the score of the disorder factor is discretized into a value S on a 5-point scale of 1 to 5. FS is taken as the horizontal axis, and the score of the repetitive chronic factor is discretized into a value S on a 5-point scale of 1 to 5. RC is taken as the vertical axis, and it can be placed at a point (coordinates are (S FS , S RC )) on the indefinite distress discrimination surface consisting of 5×5 (=25) grids, that is, at a grid. Generally, as shown in the left table of FIG. (5-1), the higher the score of the disorder factor, the higher the score of the repetitive chronic factor, and the higher the degree of chronic disorder, the higher the proportion of subjects who answered that they were concerned about "health status". For the "degree of chronic disorder", refer to Equation 3 and FIG. (5-12).

[0048] An explanation will be given for the right figure in FIG. (5-1). A thick arrow pointing diagonally upward to the right is drawn. The fact that "2.1 times" is written above this arrow means that the proportion of subjects who answered that they were concerned about "health status" among the subjects whose degree of chronic disorder belongs to either category 4 or 5 is 2.1 times the proportion of subjects who answered that they were concerned about "health status" among the subjects whose degree of chronic disorder belongs to either category 1, 2, or 3.

[0049] (Distribution on the indefinite distress discrimination surface of people who are concerned about other confirmation questionnaire items) Regarding the 10 items c2 to c11 of the confirmation questions related to the physical and mental aspects other than "health status", namely, "blood and lymph flow", "various symptoms of pain", "hormone balance", "mental state", "immunity", "fatigue", "sleep", "scalp and hair", "diet", and "sensitive skin", the figures showing the distribution on the indeterminate complaint discrimination surface of the subjects are Figures (5-2) to (5-11). Generally, for these items of the confirmation questions, the higher the score of the disorder factor, the higher the score of the repeated chronic factor, and the higher the degree of chronic disorder, the higher the proportion of subjects who answered that they were concerned about the item.

[0050] Among the subjects whose degree of chronic disorder belongs to either category 4 or 5, the ratio of the subjects who answered that they were concerned about the item of the confirmation question is 1.34 times that of the subjects whose degree of chronic disorder belongs to either category 1, 2, or 3 and who answered that they were concerned about the item. When the item of the confirmation question is "sensitive skin", it is 1.34 times, and when the item is any of the 10 items other than "sensitive skin", it is 1.9 times or more. It can be seen that the degree of chronic disorder is useful in predicting whether the item of the confirmation question, which is a concern related to the physical and mental aspects of the subject, is a matter of concern.

[0051] Figure (5-13) shows the percentage of people who are concerned about "menopausal problems" on the indefinite complaint discrimination surface. In this figure, the indefinite complaint discrimination surface is first divided into a 5×5 grid, and further, the scores of the disharmony factor and the repeated chronicity factor are each re-divided into three levels: L (categories 1 and 2; small), M (category 3; normal), and H (categories 4 and 5; large). Eventually, the indefinite complaint discrimination surface is divided into a total of 9 regions (regions HH, HM, HL, MH, MM, ML, LH, LM, LL) of 3×3. The numbers shown in each region represent the number of subjects whose scores of the disharmony factor and the repeated chronicity factor correspond to that region. The percentages shown in each region represent the percentage of people who are concerned about "menopausal problems" among the subjects whose scores of the disharmony factor and the repeated chronicity factor correspond to that region. The percentage of people who are concerned about "menopausal problems" reaches a maximum value of 23% in region HH. This is 2.6 times the average value of 8.9%. In other words, a large "chronic disharmony degree" predicts menopausal problems. More generally, a large "chronic disharmony degree" predicts "subtle" problems such as menopausal symptoms. As shown in Figure 2B, the question (h50) related to "menopausal problems" is included in the 75 questions related to the basic data, but not in the 30 questions (h01~h30) used for calculating the factor scores.

[0052] FIG. (5-14) shows the percentage of people who are concerned about "dysmenorrhea" on the indefinite complaint discrimination surface divided into nine regions in the same way as FIG. (5-13). The numbers shown in each region represent the scores of the disorder factor and the recurrent chronic factor and the number of subjects whose scores correspond to that region. The percentages shown in each region represent the percentage of subjects whose scores of the disorder factor and the recurrent chronic factor correspond to that region and who are concerned about "dysmenorrhea". The percentage of people who are concerned about "dysmenorrhea" takes the maximum value of 51% in region LL. This is 2.5 times the average value of 20.5%. In other words, a small "chronic disorder degree" predicts "dysmenorrhea". More generally, a small "chronic disorder degree" predicts disorders such as PMS and menstrual difficulties in the younger generation. As shown in FIG. 2A, the question (h04) related to "dysmenorrhea" is included in both the 75 questions in the basic data and the 30 questions (h01~h30) used for calculating the factor scores.

[0053] The concentration of female hormones in a woman's blood changes with age in life, increases in her 20s, is then kept almost constant, and decreases in her 40s to 50s. When the concentration of female hormones increases rapidly, disorders such as PMS and menstrual difficulties in the younger generation appear, and the signs can be predicted by a small "chronic disorder degree". When the amount of female hormones decreases rapidly, "fussy" troubles such as menopausal symptoms appear, and the signs can be predicted by a large "chronic disorder degree". The "chronic disorder degree" is related to the time change rate (annual change rate) of the concentration of female hormones.

[0054] In the above embodiment, first, the indefinite complaint discrimination surface was considered by dividing it into 5×5 grids. Generally, the indefinite complaint discrimination surface may first be divided into m×n grids, and if necessary, it may be re-divided roughly by combining adjacent grids, and the same analysis may be performed. Here, m and n are integers of 1 or more respectively.

[0055] <4. Health Awareness Judgment Using the Position of Points on the Meguri Discrimination Surface> (Distribution on the Meguri Discrimination Surface of People Who Are Concerned about "Health Status") For each subject included in the above basic data, as shown in Fig. (6-1), after linearly transforming the score of the liquid factor so that the maximum value is 1 and the minimum value is 0, the interval [0,1] is divided into 20 equally spaced intervals (category 1 to category 20), and according to which interval the score of the liquid factor after linear transformation belongs to, the discretized value S at 20 levels is obtained. L Taking the value S discretized at 20 levels for the score of the gas factor in the same way on the horizontal axis, A and taking the value S discretized at 20 levels for the score of the gas factor in the same way on the vertical axis, one point on the circulation discrimination plane consisting of 20×20 (=400) grids (the coordinates are (S L , S A ), that is, the point at the center of the grid) can be placed. For example, when the score of the liquid factor after linear transformation of the subject belongs to category 1 and the score of the gas factor also belongs to category 2, the subject is placed at the point with coordinates (0.025, 0.075) on the rectangular circulation discrimination plane. In Fig. (6-1), 400 subjects randomly selected from the basic data are shown as white circles (〇) when the answer to the confirmation question is YES and as crosses (×) when the answer is NO. It is considered that the probability that a customer who has received the confirmation question c1 of whether they are "concerned about their health status" answers YES varies depending on the position on the circulation discrimination plane. That probability can be estimated from the basic data. The contour lines drawn in Fig. (6-1) show the probability estimated by the method described later. On the lower side of the circulation discrimination plane where the score of the gas factor after linear transformation is 0, the probability takes the minimum value of 0.100, and on the upper side where the score of the gas factor after linear transformation is 1, the probability takes the maximum value of 0.990.

[0056] (Distribution on the circulation discrimination plane of people who are concerned about other items of the confirmation question) For each of the 10 items c2 to c11 of the confirmation questions related to the physical and mental aspects other than "health status", that is, "blood and lymph flow", "various symptoms of pain", "hormone balance", "mental state", "immunity", "fatigue", "sleep", "scalp and hair", "diet", and "sensitive skin", the probability that the subject who received the confirmation question answers YES was estimated by the method described below, and the figures shown by the contour lines on the meguri discrimination surface are Figures (6-2) to (6-11). The maximum value, minimum value of the probability and their locations on the meguri discrimination surface are also plotted with black circles.

[0057] For any of the 11 items of the confirmation questions, the probability that the subject answers YES takes the minimum value on or near the lower side where the score of the qi factor after linear transformation takes a value of 0.1 or less, and takes the maximum value on or near the upper side where the score of the qi factor after linear transformation takes a value of 0.9 or more on the rectangular meguri discrimination surface. The maximum value, minimum value, average probability (= the ratio of the subjects who answered YES among all subjects), and the f1 score of the determination described below are as follows in order. Items of confirmation questions Maximum value Minimum value Average probability f1 score c1 Health status 0.990 0.100 0.270 0.449 c2 Blood and lymph flow 0.776 0.094 0.243 0.510 c3 Various symptoms of pain 0.839 0.059 0.172 0.338 c4 Hormone balance 0.757 0.084 0.234 0.462 c5 Mental state 0.926 0.097 0.252 0.538 c6 Immunity 0.790 0.090 0.244 0.387 c7 Fatigue 0.852 0.098 0.286 0.454 c8 Sleep 0.931 0.074 0.288 0.534 c9 Scalp and hair 0.663 0.098 0.231 0.435 c10 Diet 0.948 0.043 0.217 0.429 c11 Sensitive skin 0.183 0.044 0.105 0.183 For any of the 11 items of the confirmation questions, the maximum value of the above probability is about 5 to about 20 times the minimum value, and the f1 score of the determination is about 2 times the average probability. It can be seen that the determination of the health awareness related to the physical and mental state according to the position on the meguri discrimination surface is effective.

[0058] (Method for estimating probability on the meguri discrimination surface) Here, the method for estimating the above probability on the meguri discrimination surface will be described. First, the basic data including about 5161 subjects was randomly divided into three: training data, CV data (cross-validation data), and test data, at ratios of approximately 70%, 15%, and 15% respectively. Assume that the probability is expressed as a non-linear and two-variable function f(x1, x2; θ) of the score x1 of the liquid factor discretized into 20 steps within the interval [0, 1] as described above, and the score x2 of the qi factor also discretized into 20 steps within the interval [0, 1]. θ is a parameter, as shown in Figure 8 and is the weight of the neural network. Here, d = 2, the input layer L1 has two neurons, and two values x1 and x2 are input to each neuron. The output layer L3 has one neuron, which outputs the corresponding probability p when x1 and x2 are input. p takes a value greater than 0 and less than 1. For example, when estimating the function f(x1, x2; θ) for item c1 of the confirmation questions, the value (0 or 1) of the subject's answer to c1 becomes the teacher data. The hidden layer L2 has two layers, and each layer consists of 16 neurons. All neurons are sigmoid neurons with a bias term, and the neural network is fully connected. The cost function is the binary cross-entropy function with a regularization term added. The regularization term is necessary to balance and suppress the unnecessary complexity of the function, that is, overfitting, and the unnecessary simplicity of the function, that is, high bias. The regularization term uses the square of the Frobenius norm of the weights of each neuron excluding the bias term. The regularization parameter λ that multiplies the regularization term was fixed to any one of the candidate values 30, 10, 3, 1, 0.3, 0.1, 0.03, 0.01, ···, 0.0001, and on the training data, the weights θ that minimize the cost function were obtained by the gradient descent method. The thus obtained weights θ = θ(λ) depend on the regularization parameter λ. Next, among the candidate values of λ, the one λ = λ min for which the cost function excluding the regularization term (binary cross-entropy function) is minimized on the CV data was obtained. The weights θ(λ min ) at this λ = λ min ) give the function f(x1, x2; θ(λ min )) of the two variables to be obtained. The curve shown in Fig. (6-1) is the contour plot of this function f. Finally, on the test data, it was predicted whether the function f(x1, x2; θ(λ min )) is greater than or equal to the threshold h, and the f1 score representing the accuracy of the prediction was calculated. The threshold h was selected in advance from among the candidate values of the threshold 0.01, 0.02, 0.03, ···, 0.99 so that the f1 score of the same prediction on the CV data is maximized.

[0059] (f1 score) Assume that for each data in a certain dataset, an actual value taking a value of 1 or 0 is given. On the other hand, assume that for each data in that dataset, a predicted value taking a value of 1 or 0 is also given. The number of data satisfying the following respective conditions among the data included in the dataset is represented by TP, FP, TN, and FN in order. TP ··· The number of data for which the predicted value is 1 and the actual value is also 1. FP ··· The number of data for which the predicted value is 1 but the actual value is 0. TN ··· The number of data for which the predicted value is 0 and the actual value is also 0. FN ··· The number of data for which the predicted value is 0 but the actual value is 1. When the "precision" and "recall" are defined as precision = TP / (TP + FP) and recall = TP / (TP + FN), the f1 score is defined by the following equation 5. The f1 score is the harmonic mean of the "precision" and the "recall". (Equation 5) 1 / f1 score = (1 / precision + 1 / recall) / 2 Note that the "precision" indicates the ratio of data with an actual value of 1 among the data with a predicted value of 1. Also, the "recall" indicates the ratio of data with a predicted value of 1 among the data with an actual value of 1.

[0060] <5. Health awareness determination using the position of points on the indefinite complaint discrimination surface> (Distribution on the indefinite complaint discrimination surface of people who are concerned about their "health status") Each subject included in the above basic data, similar to the case of the above-mentioned meguri discrimination surface, as shown in Fig. (7-1), has a score S of the discomfort factor discretized into 20 steps within the interval [0, 1]. FS Taking this as the horizontal axis, and also taking the score S of the repetitive chronic factor discretized into 20 steps within the interval [0, 1]. RC as the vertical axis, it can be placed at a point (coordinates are (S FS , S RC )) on the indefinite complaint discrimination surface consisting of 20×20 (=400) grids, that is, at the center of the grid. In Fig. (7-1), 400 subjects randomly selected from the basic data are shown as white circles (〇) when their answer to the confirmation question is YES, and as crosses (×) when the answer is NO. It is considered that the probability that a customer who has received the confirmation question c1 of whether they are concerned about their "health status" answers YES varies depending on the position on the indefinite complaint discrimination surface. That probability can be estimated from the basic data. The isoclines drawn in Fig. (7-1) show the probability estimated in the same way as in the above-mentioned meguri discrimination surface. On the indefinite complaint discrimination surface, the probability takes a minimum value of 0.194 in the left region where the score of the discomfort factor after linear transformation is 1 / 3 or less, and takes a maximum value of 0.735 on the right side where the score of the discomfort factor after linear transformation is 1.

[0061] (Distribution on the indefinite complaint discrimination surface of people who are concerned about other confirmation question items) For each of the 10 items c2 to c11 of the confirmation questions related to the physical and mental aspects other than "health status", that is, "blood and lymph flow", "various symptoms of pain", "hormone balance", "mental state", "immunity", "fatigue", "sleep", "scalp and hair", "diet", and "sensitive skin", the probability that the subject who received the confirmation question answers YES was estimated in the same way as on the above-mentioned meguri discrimination surface, and the figures shown by the contour lines on the indefinite complaint discrimination surface are Figures (7-2) to (7-11). The maximum value, minimum value of the probability and their locations on the indefinite complaint discrimination surface are also plotted with black circles.

[0062] For any of the 11 items of the confirmation questions, the probability that the subject answers YES takes the minimum value in the left region or on the left side where the score of the disorder factor after linear transformation is 1 / 3 or less on the rectangular indefinite complaint discrimination surface, and takes the maximum value on the right side or in the vicinity where the score of the disorder factor after linear transformation is 0.9 or more. The maximum value, minimum value, average probability (= the ratio of the subjects who answered YES among all the subjects), and the f1 score of the determination are as follows in order. Items of confirmation questions Maximum value Minimum value Average probability f1 score c1 Health status 0.735 0.194 0.270 0.589 c2 Blood and lymph flow 0.643 0.117 0.243 0.410 c3 Various symptoms of pain 0.523 0.070 0.172 0.338 c4 Hormone balance 0.761 0.121 0.234 0.343 c5 Mental state 0.714 0.143 0.252 0.389 c6 Immunity 0.606 0.172 0.244 0.372 c7 Fatigue 0.693 0.160 0.286 0.450 c8 Sleep 0.756 0.216 0.288 0.446 c9 Scalp and hair 0.666 0.038 0.231 0.382 c10 Diet 0.590 0.138 0.217 0.360 c11 Sensitive skin 0.292 0.011 0.105 0.249 For any of the 11 items of the confirmation questions, the maximum value of the above probabilities is about 4 to about 20 times the minimum value, and the f1 score of the determination is about 1.5 to about 2 times the average probability. It can be seen that the determination of the health awareness related to the physical and mental state according to the position on the indefinite complaint discrimination surface is effective.

[0063] <6. Health awareness determination using the positions of points in various discrimination spaces> The Meguri discrimination surface can be considered as a two-dimensional discrimination space that takes the score of the liquid factor on the first axis and the score of the qi factor on the second axis. Similarly, the indefinite complaint discrimination surface can be considered as a two-dimensional discrimination space that takes the score of the disorder factor on the first axis and the score of the repeated chronic factor on the second axis. In addition, the following discrimination spaces can also be considered. · A three-dimensional Meguri discrimination space that takes the score of the water factor on the first axis, the score of the blood factor on the second axis, and the score of the qi factor on the third axis. · A four-dimensional Meguri 2 indefinite complaint discrimination space that takes the score of the liquid factor on the first axis, the score of the qi factor on the second axis, the score of the disorder factor on the third axis, and the score of the repeated chronic factor on the fourth axis. · The score of the water factor is taken on the first axis, the score of the blood factor is taken on the second axis, the score of the qi factor is taken on the third axis, the score of the disorder factor is taken on the fourth axis, and the score of the repeated chronic factor is taken on the fifth axis, a five-dimensional Meguri 3 indefinite complaint discrimination space. On each of these discrimination spaces, in the same way as above, probabilities are estimated using the neural network shown in FIG. 8, the answers of the subjects for each item of the confirmation questions are predicted using a threshold value, and the f1 score of the prediction can be obtained. However, the number d of neurons in the input layer needs to be adjusted according to the dimension of the discrimination space. The hidden layer consists of two layers, and 16 neurons are arranged in each layer. The f1 scores obtained on each discrimination space in this way are shown in Table 1 below.

[0064]

Table 1

[0065] For each of the above identification spaces, for any of the 11 items of the confirmation questions, the F1 score of the determination is about 1.5 to about 2.5 times the average probability, and it can be seen that the determination of the health awareness related to the physical and mental health according to the position on each identification space is effective.

[0066] <7. Configuration of Health Awareness Determination Device> (Independent Health Awareness Determination Device) FIG. 9 is a configuration diagram showing the configuration of a health awareness determination device according to an embodiment of the present invention configured using an independent computer. The health awareness determination device 1 of the present embodiment includes an independent computer 10 such as a personal computer, a smartphone, a tablet, a wearable device, smart glasses, AR goggles, an input means 20 composed of a keyboard, a mouse, a touch panel display, etc., an output means 40 composed of a display, a printer, etc., a register of the CPU, a memory such as a RAM and a ROM, a hard disk drive (HDD), a solid state drive (SSD), a removable storage device such as a USB memory and an SD card, and / or a CD-R drive, a DVD drive, etc., a storage means 30 capable of writing and reading information by a computer. The storage means 30 stores a health awareness determination program according to the present invention, basic data which is the answers of a large number of subjects to three or more questions regarding physical and mental health, and / or factor score coefficients calculated by factor analysis from the basic data, and interview data which is the answers of the customer to the questions input using the input means 20. The health awareness determination device 1 may be operated by a customer or may be operated by a store staff such as a chiropractor. The input means 20 is used to input the interview data of each customer. Here, the interview data of each customer may include answers to questions related to health awareness and confirmation questions, presence or absence of use of food and drugs, answers to questions related to beauty and diet, age, gender and other information. It may also be operated by a store staff such as a chiropractor. The input means 20 is used to input the interview data of each customer. Here, the interview data of each customer may include answers to questions related to health awareness and confirmation questions, presence or absence of use of food and drugs, answers to questions related to beauty and diet, age, gender and other information.

[0067] In one embodiment of the present invention, the computer 10 executes a health awareness determination program stored in the storage means 30, and based on the basic data consisting of answers to questions regarding the health awareness of a large number of subjects stored in the storage means 30 and the customer's medical interview data input by the input means 20 and stored in the storage means 30, determines the health awareness of the customer by factor analysis and outputs the determination result by the output means 40. Alternatively, in another embodiment of the present invention, the factor score coefficients obtained by factor analysis of the basic data are stored in the storage means 30 in advance. The computer 10 executes a health awareness determination program, reads the factor score coefficients stored in the storage means 30, and based on the read factor score coefficients and the customer's medical interview data input by the input means 20 and stored in the storage means 30, determines the health awareness of the customer and outputs the determination result by the output means 40. When factor analysis is performed in advance and the factor score coefficients are stored in the storage means 30, the factor analysis may be performed using the computer 10 or another computer. In the latter case, the factor score coefficients obtained by the analysis using another computer can be read by the computer 10 via a removable storage means 30 or via a network.

[0068] In addition to the determination result of health awareness, the above determination result can include recommended foods and advice regarding health and the like. The determination result of the customer's health awareness is the position of a point arranged on at least one of the cycle discrimination aspect, the indefinite complaint discrimination aspect, the cycle discrimination space, the cycle 2 indefinite complaint discrimination space, and the cycle 3 indefinite complaint discrimination space, and the position of the point can be expressed by the above various methods or a known method using projection onto a lower-dimensional space or plane.

[0069] (Terminal for Health Awareness Determination Device) FIG. 10 is a configuration diagram showing the configuration of a terminal 11 for a health awareness determination device according to an embodiment of the present invention. In the present embodiment, health awareness determination is performed by a server 12 (which is also a computer 10), and input and output are performed by a terminal 11 close to a customer or a store staff. The server 12 and the terminal 11 can communicate bidirectionally via a wired or wireless network 70 such as an intranet or the Internet. The terminal 11 is a computer such as a personal computer, a smartphone, a tablet, a wearable device, smart glasses, or AR goggles. The terminal 11 includes an input means 21 composed of a keyboard, a mouse, a touch panel display, etc., an output means 41 composed of a display, a printer, etc., a memory such as a register of a CPU, RAM, or ROM, a hard disk drive (HDD), a solid state drive (SSD), a removable storage device such as a USB memory or an SD card, and / or a storage means 31 capable of writing and reading information by a computer such as a CD-R drive or a DVD drive. The server 12 is a computer such as a server machine, a personal computer, a smartphone, a tablet, a wearable device, smart glasses, or AR goggles, and includes a memory such as a register of a CPU, RAM, or ROM, a hard disk drive (HDD), a solid state drive (SSD), a removable storage device such as a USB memory or an SD card, and / or a storage means 32 capable of writing and reading information by a computer such as a CD-R drive or a DVD drive.

[0070] The terminal 11 has an input means 21 for inputting interview data, which is an answer to a question regarding the customer's health awareness. The input interview data is temporarily stored in the storage means 31 of the terminal 11. The terminal 11 has an interview data transmission means 51 for transmitting the input interview data of the customer to the server 12 via the network 70. The terminal 11 has an interview data transmission means 51 for transmitting the input interview data of the customer to the server 12 via the network 70.

[0071] The server 12 has an interview data receiving means 52 for receiving the interview data of the customer transmitted from the terminal 11. The received interview data of the customer is temporarily stored in the storage means 32 of the server 12. In one embodiment of the present invention, the server 12 executes a health awareness determination program stored in the storage means 32, and based on the basic data consisting of answers to questions regarding the health awareness of a large number of subjects stored in the storage means 32 and the interview data of the customer received by the interview data receiving means 52 and stored in the storage means 32, determines the health awareness of the customer by factor analysis, and has a determination result transmitting means 62 for transmitting the determination result to the terminal 11 via the network 70. Alternatively, in another embodiment of the present invention, the server 12 stores in the storage means 32 the factor score coefficients obtained in advance by factor analysis of the basic data. The server 12 executes a health awareness determination program stored in the storage means 32, reads the factor score coefficients stored in the storage means 32, and based on the read factor score coefficients and the interview data of the customer received by the interview data receiving means 52 and stored in the storage means 32, determines the health awareness of the customer, and has a determination result transmitting means 62 for transmitting the determination result to the terminal 11 via the network 70.

[0072] The terminal 11 has a determination result receiving means 61 for receiving the determination result of the health awareness of the customer transmitted from the server 12. The terminal 11 temporarily stores the determination result of the health awareness of the customer received from the server 12 in the storage means 31. The terminal 11 has an output means 41 for outputting the received determination result of the health awareness of the customer. The mode of output of the determination result of the health awareness by the output means 41 is the same as the case where the above computer 10 outputs the determination result of the health awareness by the output means 40.

[0073] The present invention is not limited to the above embodiments and examples, and it goes without saying that various modifications, design changes, etc. within the scope not departing from the technical idea of the present invention are included in its technical scope.

Industrial Applicability

[0074] According to the present invention, by using a factor analysis method using big data, the position on the meguri discrimination surface for expressing the health awareness related to the meguri feeling and / or the position on the indefinite complaint discrimination surface for expressing the health awareness related to indefinite complaints are clarified, and the relationship with the self-awareness of discomfort such as "concerned about health status" and "concerned about blood and lymph flow", it is possible to provide a health awareness determination program, a health awareness determination device, and a terminal for the health awareness determination device that can objectively and accurately determine the health awareness of customers based on the interview data. According to the present invention, it is possible to more accurately recommend products such as health foods, beauty products, drugs, and crude drugs, and provide advice related to physical and mental health in online stores or real stores such as chiropractic clinics, drugstores, beauty salons, clinics, aesthetic salons, and cosmetics sales stores than before. The present invention has wide industrial applicability.

Explanation of Signs

[0075] 1 Health awareness determination device 10 Computer 20 Input means 30 Storage means 40 Output means 11 Terminal 21 (Terminal's) input means 31 (Terminal's) storage means 41 (Terminal's) output means 51 (Terminal's) interview data transmission means 61 (Terminal's) determination result reception means 12 Server 52 (Server's) interview data reception means 62 (Server's) determination result transmission means 70 Network A Arrow L1 Input layer L2 Hidden layer L3 Output layer

Claims

1. Basic data which is the responses of a large number of examinees to three or more questions regarding health awareness related to the body and mind, The interview data which is the customer's response to the said questions, A program for performing arithmetic processing on these to determine the customer's health awareness, From the basic data, by factor analysis, at least a qi factor related to the circulation of qi, a water factor related to the circulation of water, and a blood factor related to the circulation of blood are extracted to calculate factor score coefficients, or a factor extraction procedure, or a factor reading procedure for reading out factor score coefficients that have been calculated in advance according to the factor extraction procedure and stored in a storage means, Based on the interview data and the factor score coefficients, the score S of the qi factor of the customer A and the score S of the water factor w and the score S of the blood factor B are calculated. Furthermore, the sum average of the score S of the water factor w and the score S of the blood factor B is taken as the score S of the liquid factor related to the circulation of the liquid L and a health awareness determination procedure for expressing and determining the health awareness related to the customer's circulation feeling based on the position of the point (S L , S A ) in the coordinate plane called the circulation discrimination plane A health awareness determination program having the above.

2. The health awareness determination program according to claim 1, wherein the questions include at least one of the items related to anemia, lack of sleep, nervousness, and swelling of the feet, which are closely related to the circulation of qi, and at least one of the items related to swelling of the feet, overeating, constipation (tendency), and lack of exercise, which are closely related to the circulation of water, and at least one of the items related to low blood pressure, anemia, and cold feet, which are closely related to the circulation of blood.

3. When a subject related to the basic data is asked a confirmation question about physical and mental health with a binary choice of "concerned" or "not concerned" separately from the questions related to the basic data, the proportion of subjects who answered "concerned" is the smallest in the area where the score S of the qi factor is small on the meguri discrimination surface, and the largest in the area where the score S A is large, and A when the score S The health awareness determination program according to claim 1, wherein the confirmation questions are questions related to any one of health status, blood and lymph flow, various symptoms of pain, hormone balance, mental state, immunity, fatigue, sleep, scalp and hair, diet, and sensitive skin.

4. Basic data which is the responses of a large number of examinees to three or more questions regarding health awareness related to the body and mind, The interview data which is the customer's response to the said questions, A program for performing arithmetic processing on these to determine the customer's health awareness, From the basic data, by factor analysis, at least a qi factor related to the circulation of qi, a water factor related to the circulation of water, and a blood factor related to the circulation of blood are extracted to calculate factor score coefficients, or a factor extraction procedure, or a factor reading procedure for reading out factor score coefficients that have been calculated in advance according to the factor extraction procedure and stored in a storage means, Based on the interview data and the factor score coefficients, the score S of the water factor of the customer w and the score S of the blood factor B and the score S of the qi factor A are calculated, and the health awareness related to the customer's sense of circulation is expressed and determined by the position of the point (S w , S B , S A ) in the coordinate space called the circulation discrimination space. A health awareness determination program having the above.

5. Basic data which is the responses of a large number of examinees to three or more questions regarding health awareness related to the body and mind, The interview data which is the customer's response to the said questions, A program for performing arithmetic processing on these to determine the customer's health awareness, From the basic data, by factor analysis, at least the clarification of the site and cause of the deterioration of the condition A factor extraction procedure for extracting a malcoordination factor related to the body and a repetitive chronic factor related to the rhythm of deterioration and improvement of the condition, and calculating a factor score coefficient, or a factor reading procedure for reading out a factor score coefficient that has been calculated in advance according to the factor extraction procedure and stored in a storage means, Based on the interview data and the factor score coefficients, the score S of the customer for the disharmony factor FS and the score S of the repetitive chronic factor RC are calculated, and the health awareness related to the customer's indefinite complaint is expressed and determined by the position of the point (S FS , S RC ) in the coordinate plane called the indefinite complaint identification plane, and a health awareness determination procedure A health awareness determination program having the above.

6. When a confirmation question regarding physical and mental health with a binary choice of "concerned" or "not concerned" is asked to the subject related to the basic data, separately from the questions related to the basic data, the proportion of subjects who answered "concerned" is the smallest in the area where the score S of the disorder factor is small on the indefinite complaint discrimination surface, and is the largest in the area where the score S FS is large, and FS when the score S The confirmation question is the health awareness determination program according to claim 5, which is a question regarding any one of health status, blood and lymph flow, various symptoms of pain, hormone balance, mental state, immunity, fatigue, sleep, scalp and hair, eating habits, and sensitive skin.

7. The health awareness determination program according to any one of claims 1 to 6, Basic data that is the answers of a large number of subjects to three or more questions regarding the body and mind, or factor score coefficients calculated by factor analysis from the basic data, Questionnaire data that is the customer's answers to the above questions, Having a storage means for storing the above, Including a computer configured to be able to execute the health awareness determination program, A health awareness determination device for determining the health awareness of the customer.

8. Regarding the computer configured to be able to execute the health awareness determination program according to claim 7 as a server, a terminal capable of two-way communication with the server via a network, An input means for inputting questionnaire data that is the customer's answers to the above questions, A transmission means for transmitting the input questionnaire data to the server, A receiving means for receiving the determination result of the customer's health awareness from the server, An output means for displaying the received determination result, A terminal for a health awareness determination device having the above.

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