JP7668930B2 - SLEEP INFORMATION PROCESSING METHOD, SLEEP INFORMATION PROCESSING PROGRAM, AND SLEEP INFORMATION PROCESSING SYSTEM - Google Patents

Description

The present invention relates to a sleep information processing method, a sleep information processing program, and a sleep information processing system that output sleep improvement information.

Living organisms that live on Earth, such as humans, have an internal rhythm that follows a cycle of approximately 24 hours, and are active during the day and in a resting mode at night. Human body temperature, blood pressure, pulse rate, and secretion of various hormones also follow a rhythm of approximately 24 hours, and immunity and metabolism are affected by internal rhythms. It has been reported that the internal rhythm of humans is slightly longer than 24 hours, for example, approximately 24 hours and 10 minutes (Science. 1999 Jun 25; 284(5423): 2177-81). For example, disruptions to one's lifestyle, such as staying up late, reversing one's day and night schedule, or oversleeping on the weekends, affect the internal rhythm, causing a drowsy state during the day, inability to recover from fatigue, and poor physical condition.

While on weekdays (Monday to Friday) people's bedtimes and wake-up times are roughly the same due to work (including school), on weekends (Saturday, Sunday, and national holidays) people may catch up on sleep or sleep in to rest. As a result, they may wake up feeling drowsy and unsatisfied on Monday morning, the first day of work. This difference between weekday sleep, which is subject to social constraints (work, school, housework, etc.), and unconstrained weekend sleep, which is in sync with the biological clock, is known academically as "social jet lag" (Chronobiol Int. 2006; 23(1-2): 497-509).

Several studies have confirmed that this social jet lag can cause the body clock to be delayed by 30 to 45 minutes if you simply sleep in for two days on a holiday (Chronobiol Int. 2010 Aug; 27(7): 1469-92, Sleep. 2001 May 1; 24(3): 272-81). Furthermore, once the rhythm has shifted, it is not easy to get it back to normal, and there are reports that this can lead to feelings of sleepiness and daytime fatigue continuing into the first half of the next week (Sleep and Biological Rhythms 2008; 6: 172-9).

JP 2019-162382 A Patent No. 5879833 Patent No. 6418671

Patent Document 1 relates to a device and program that supports the improvement of sleep quality. Patent Document 2 relates to an information processing device and program that evaluates sleep quality based on biological signals detected from a sleeping subject. Patent Document 3 relates to a personnel management support system that collects information on employees' lifestyle habits and sleep conditions through questionnaires and smoothly supports personnel management in an organization using statistical methods. However, none of Patent Documents 1 to 3 mentions the above-mentioned social jet lag.

The object of the present invention is to provide a sleep information processing method, a sleep information processing program, and a sleep information processing system that can provide sleep improvement information that takes social jet lag into account.

A first aspect of the present invention includes the steps of inputting into a computer first time information I1 relating to a bedtime SOw when the subject's sleep started and a wake-up time SEw when the subject's sleep ended on a workday, and second time information I2 relating to a bedtime SOf when the subject's sleep started and a wake-up time SEf when the subject's sleep ended on a non-workday;
a step of calculating a median sleep value MSw on working days based on the first time information I1, calculating a median sleep value MSf on non-working days based on the second time information I2, and determining a value SJL obtained by subtracting the median sleep value MSw from the median sleep value MSf or its absolute value |SJL| as a sleep duration variation parameter PL representing a sleep duration variation ;
inputting a sleep state parameter P representing a sleep state of the subject into said computer;
and outputting sleep improvement information by the computer using the sleep time variation parameter PL and the sleep state parameter PS.
This methodology allows us to provide information on improving sleep that takes social jet lag into account ,
Social jet lag can be adequately quantified.

In the present invention, the sleep state parameter PS is preferably a questionnaire result including at least one of sleep time, sleep quality, and daytime sleepiness.
This technique can accurately reflect the subject's sleep state.

A second aspect of the present invention provides a method for implementing a method of a computer comprising:
A function for inputting first time information I1 relating to a bedtime SOw when sleep started and a wake-up time SEw when said sleep ended on a working day of the subject, and second time information I2 relating to a bedtime SOf when sleep started and a wake-up time SEf when said sleep ended on a non-working day of the subject;
a function of calculating a median sleep value MSw on working days based on the first time information I1, calculating a median sleep value MSf on non-working days based on the second time information I2, and determining a value SJL obtained by subtracting the median sleep value MSw from the median sleep value MSf or its absolute value |SJL| as a sleep duration variation parameter PL representing a sleep duration variation ;
A function of inputting a sleep state parameter PS representing the sleep state of the subject;
The present invention provides a function of outputting sleep improvement information using the sleep time variation parameter PL and the sleep state parameter PS, and a sleep information processing program for realizing the function.
This methodology allows us to provide information on improving sleep that takes social jet lag into account ,
Social jet lag can be adequately quantified.

A third aspect of the present invention is a method for inputting a first time information I1 relating to a bedtime SOw when the subject's sleep started and a wake-up time SEw when the sleep ended on a workday of the subject, and a second time information I2 relating to a bedtime SOf when the subject's sleep started and a wake-up time SEf when the sleep ended on a non-workday of the subject;
a calculation means for calculating a median sleep value MSw on working days based on the first time information I1, calculating a median sleep value MSf on non-working days based on the second time information I2, and determining a value SJL obtained by subtracting the median sleep value MSw from the median sleep value MSf or its absolute value |SJL| as a sleep duration variation parameter PL representing a sleep duration variation ;
A second input means for inputting a sleep state parameter PS representing the sleep state of the subject;
The present invention provides a sleep information processing system including: an output means for outputting sleep improvement information using the sleep time variation parameter PL and the sleep state parameter PS.
This methodology allows us to provide information on improving sleep that takes social jet lag into account ,
Social jet lag can be adequately quantified.

This invention can provide information for improving sleep that takes social jet lag into account.

1 is a block diagram showing an example of a sleep information processing system according to an embodiment of the present invention. This is an explanatory diagram of social jet lag. 3 is a flowchart showing an example of a sleep information processing method according to the present invention. An example of sleep improvement information is a graph showing absolute presenteeism (productivity) (Z-axis) as a function of the Athens Insomnia Scale (X-axis) and social jet lag (Y-axis). 5 is a graph in which the numerical values on the three axes in FIG. 4 are simply expressed as two values, "good" and "bad." Another example of sleep improvement information is a graph showing the odds ratio of contracting a cold (Z-axis) as a function of the Athens Insomnia Scale total score (X-axis) and social jet lag (Y-axis).

The following describes an embodiment of the present invention with reference to the drawings.

Figure 1 is a block diagram showing an example of a sleep information processing system according to an embodiment of the present invention. The sleep information processing system 1 includes a host computer 10 capable of operating as a server, a storage device 11 for storing various databases, and multiple terminals 21, 22, and 23 capable of operating as clients.

The host computer 10 includes a processor, memory, an interface, etc., and executes calculation processing according to various pre-set programs (for example, programs using the statistical processing programming language "R"). These various programs include the sleep information processing program of the present invention. The host computer 10 can generally be connected to data input devices such as a keyboard and a pointing device, and data output devices such as a display, printer, and projector. The host computer 10 may be a single computer for centralized processing, or may be distributed across multiple computers for distributed processing.

The storage device 11 is composed of a hard disk drive, an optical disk drive, a solid state drive, a magnetic tape drive, etc., and is connected to the host computer 10 so as to be able to communicate with it via wired or wireless communication. The storage device 11 may be a single unit for centralized processing, or may be distributed across multiple storage devices for distributed processing.

The terminals 21, 22, and 23 are composed of a personal computer PC, a tablet terminal, a smartphone, a mobile phone, etc., and are equipped with means for inputting data, such as a keyboard, a pointing device, a touch panel, various switches, a microphone, a camera, etc., and further equipped with means for outputting data, such as a liquid crystal panel, an organic LED panel, an LED lamp, a speaker, etc. These terminals 21, 22, and 23 can be connected to each other so as to be able to communicate with each other via a network line such as the Internet or an intranet, and can also be connected to the host computer 10 so as to be able to communicate with each other.

In the present invention, a questionnaire form is presented to the users of terminals 21 to 23, who then respond to the questionnaire. The host computer 10 then compiles and statistically processes the individual questionnaire results to create and update a sleep information database, and outputs individual sleep improvement information corresponding to each individual user to terminals 21 to 23, respectively.

Figure 2 is an explanatory diagram of social jet lag. The horizontal axis shows the time from 10 pm to 10 am, and the vertical axis shows the repetition of one week including Monday to Friday (weekdays) and Saturday and Sunday (holidays). The left end of the bar graph shows the bedtime, the right end of the bar graph shows the wake-up time, and the length of the bar graph shows the sleep time. The top five bar graphs of the week show the sleep time from Monday to Friday, and the bottom two bar graphs show the sleep time on Saturday and Sunday. Here, as an example, we focus on the median sleep time, which is in the middle of the sleep time, and there is a difference of about three hours between the median sleep time on weekdays and on holidays, and this difference is called the "social jet lag time." Here, we have exemplified the case where the subject is a regular worker with two days off per week (for example, working from 9 am to 5 pm), but the same can be applied to cases where the subject is off work on one of the weekdays and works on one of the holidays.

Figure 3 is a flow chart showing an example of a sleep information processing method according to the present invention. The method includes steps S1 to S5. Note that the order in which steps S1, S2, S3, and S4 are performed is arbitrary and can be changed as necessary. Such a sleep information processing method can be implemented in the host computer 10 and terminals 21, 22, and 23 using various programming languages, such as HTML, CSS, JavaScript, PHP, Java, Python, C++, C#, Swift, Ruby, and R.

First, when the host computer 10 receives a request to send a questionnaire from a user via the terminals 21, 22, and 23, it sends a predetermined questionnaire form to the terminals 21, 22, and 23. The details of the questionnaire form will be described later. The terminals 21, 22, and 23 display the received questionnaire form on their screens.

In step S1, the user inputs into terminals 21, 22, and 23, in accordance with the questionnaire form, first time information I1 relating to the bedtime SOw when sleep began and the wake-up time SEw when sleep ended on the subject's workday, and second time information I2 relating to the bedtime SOf when sleep began and the wake-up time SEf when sleep ended on the subject's non-workday. Terminals 21, 22, and 23 transmit the input data to host computer 10. The user may be the same as the subject, or may be a different person.

Next, in step S2, the host computer 10 calculates a sleep time fluctuation parameter PL that indicates sleep time fluctuation based on the first time information I1 and the second time information I2 received from the terminals 21, 22, and 23. One example of this calculation method is a method of calculating the central sleep time (https://mctq.jp/use/index_para.html).

In detail, the median sleep time MSw on a workday can be calculated as MSw = SOw + (SDw) / 2. However, if the calculated value of MSw exceeds 24, the median sleep time is calculated by subtracting 24 from the value. Next, the length of sleep (sleep segment) SDw on a workday can be calculated as follows: (1) if it does not cross midnight, SDw = SEw - SOw, and (2) if it does cross midnight, SDw = SEw - (SOw - 24). Here, SEw is the wake-up time on the workday (input value in 24-hour notation), and SOw is the bedtime on the workday (input value in 24-hour notation). If there are multiple workdays, the average of the values for each workday may be used.

Next, the median sleep time MSf on a non-working day can be calculated as MSf = SOf + (SDf) / 2. However, if the calculated value of MSf exceeds 24, the median sleep time is calculated by subtracting 24 from the value. Next, the length of sleep (sleep segment) SDf on a non-working day can be calculated as follows: (1) if the sleep segment does not cross midnight, SDf = SEf - SOf, and (2) if the sleep segment does cross midnight, SDf = SEf - (SOf - 24). Here, SEf is the wake-up time on the non-working day (input value in 24-hour format), and SOf is the bedtime on the non-working day (input value in 24-hour format). If there are multiple non-working days, the average of the values for each non-working day may be used.

Next, the social jet lag time is calculated as the sleep time variation parameter PL. The social jet lag time includes the following two types.
・Relative social jet lag time SJL (= MSf-MSw)
・Absolute social jet lag time |SJL| (|| is the absolute value)
However, if the value of |SJL| exceeds 12, the value subtracted from 24 (SJL' in the formula below) is used as the social jet lag time.
SJL'=24- |SJL|
In the present invention, either the relative social jet lag time SJL or the absolute social jet lag time |SJL| can be used.

In the above explanation, the difference in median sleep time between work days and non-work days was calculated, but it is also possible to calculate 1) the difference in bedtime between work days and non-work days, 2) the difference in wake-up time between work days and non-work days, and 3) the difference between the time that is x% (0<x<100) of the sleep period after bedtime between work days and non-work days.

Next, in step S3, the user inputs a physical condition parameter PB representing the subject's physical condition to the terminal 21, 22, or 23. The terminal 21, 22, or 23 transmits the input data to the host computer 10. Details of the physical condition parameter PB will be described later.

Next, in step S4, the user inputs a sleep state parameter PS representing the subject's sleep state to terminals 21, 22, and 23. Terminals 21, 22, and 23 transmit the input data to host computer 10. Details of the sleep state parameter PS will be described later.

The various data input by the user in this way is compiled by the host computer 10, subjected to statistical processing, and stored in the storage device 11.

Next, in step S5, the host computer 10 uses the sleep time variation parameter PL calculated in step S2 and the physical condition parameter PB and sleep state parameter PS received from the terminals 21, 22, and 23 to refer to the database stored in the storage device 11, generate sleep improvement information corresponding to these parameters, and transmit it to the terminals 21, 22, and 23. The terminals 21, 22, and 23 display the received sleep improvement information on a screen or output it as sound from a speaker. Details of the sleep improvement information will be described later.

Next, we will explain the questionnaire presented to each user. An example of the questionnaire content is shown below. Questions 1 to 8 are quoted from the Athens Insomnia Scale (AIS) (Soldatos et al.: "Athens Insomnia Scale: validation of an instrument based on ICD-10 criteria", Journal of Psychosomatic Research 48:555-560, 2000). Questions 13 to 18 are quoted from the abbreviated version of the World Health Organization (WHO) Health and Work Performance Questionnaire (https://www.hcp.med.harvard.edu/hpq/ftpdir/WMHJ-HPQ-SF_2018.pdf) of the WHO World Mental Health Japan Survey.

No. 1 Question item: Athens Insomnia Scale Question format: Select one Question: About the problem of falling asleep (how long it took to fall asleep after getting in bed and turning off the lights)
○Please select something that you have experienced at least three times a week in the past month [Required]
(1) There were no problems
(2) It took a while
(3) It took a long time
(4) It took a very long time or I couldn't sleep at all.

No. 2 Question item: Athens Insomnia Scale Question format: Select one Question: Problems waking up during the night ○ Please select the problem you have experienced at least three times a week in the past month [Required]
(1) It wasn't enough to be a problem.
(2) I had some trouble
(3) I am in a lot of trouble
(4) Serious illness or complete inability to sleep

No. 3 Question item: Athens Insomnia Scale Question format: Select one Question: Problems with waking up earlier than desired and not being able to fall back asleep ○ Please select the problem you have experienced at least three times a week in the past month [Required]
(1) No such thing happened.
(2) It was a little early
(3) It was pretty fast
(4) I woke up very early or couldn't sleep at all.

No. 4 Question item: Athens Insomnia Scale Question format: Select one Question: About total sleep time ○ Please select the item you have experienced at least three times a week in the past month [Required]
(1) It was enough
(2) It was a little lacking
(3) It was quite lacking
(4) I got very little sleep or I couldn't sleep at all.

No. 5 Question item: Athens Insomnia Scale Question format: Select one Question: About overall quality of sleep ○ Please select the item you have experienced at least three times a week in the past month [Required]
(1) Satisfied
(2) A little dissatisfied
(3) Very dissatisfied
(4) Very dissatisfied or could not sleep at all

No. 6 Question item: Athens Insomnia Scale Question format: Select one Question: About daytime satisfaction ○ Please select the one you have experienced at least three times a week in the past month [Required]
(1) As usual
(2) Slight decrease
(3) Significantly decreased
(4) Very low

No. 7 Question item: Athens Insomnia Scale Question format: Select one Question: About daytime activities (physical and mental)
○Please select something that you have experienced at least three times a week in the past month [Required]
(1) As usual
(2) Slight decrease
(3) Significantly decreased
(4) Very low

No. 8 Question item: Athens Insomnia Scale Question format: Select one Question: Daytime sleepiness ○ Please select the one you have experienced at least three times a week in the past month [Required]
(1) Not at all
(2) A little
(3) Quite a bit
(4) Intense

No. 9 Question item: Time information Question format: Free description Question: [Wake-up time on weekdays] We would like to ask you about your recent living situation. Please tell us the time you usually wake up on work (school) days in four digits (24-hour format) [Required]
Example: 6:30am → 0630
4-digit free answer

No. 10 Question item: Time information Question format: Free description Question: [Bedtime on weekdays] We would like to ask you about your recent living situation. Please tell us the time you usually go to bed on work (school) days in four digits (24-hour format) [Required]
Example: 11:30 pm → 2330
Example: 12:30 a.m. → 0030
Example: 1:30am → 0130
4-digit free answer

No. 11 Question item: Time information Question format: Free description Question: [Bedtime on weekdays] We would like to ask about your recent living situation. Please tell us the time you wake up on days when you do not have work (school) in four digits (24-hour format) [Required]
Example: 6:30am → 0630
4-digit free answer

No. 12 Question item: Time information Question format: Free description Question: [Bedtime on holidays] We would like to ask about your recent lifestyle. Please tell us the time you usually go to bed on days when you do not have work (school) in four digits (24-hour format).
Example: 11:30 pm → 2330
Example: 12:30 a.m. → 0030
Example: 1:30am → 0130
4-digit free answer

No. 13 Question item: Absenteeism (B3) Question format: Free description Question: Approximately how many hours did you work during the past 7 days? Please answer with two numbers [Required]
(Please answer within the range of 00 to 97. If it is more than 97 hours, please enter 97.)
Two-digit free answer

No. 14 Question: Absenteeism (B4) Question format: Free text Question: In a typical week, how many hours does your employer expect you to work? Please answer with two numbers [required]
(If it fluctuates, estimate the average.)
(Please answer within the range of 00 to 97. If it is more than 97 hours, please enter 97.)
Two-digit free answer

No. 15 Question item: Absenteeism (B6) Question format: Free description Question: Approximately how many hours did you work during the last 4 weeks (28 days)? [Required]
(Please refer to the example below and answer the number of hours for the past 4 weeks (28 days))
Examples of calculating the number of hours worked in the past 4 weeks: ・40 hours per week for 4 weeks = 160 hours ・35 hours per week for 4 weeks = 140 hours ・40 hours per week for 4 weeks, with 2 8-hour days off = 144 hours ・40 hours per week for 4 weeks, with 3 4-hour days off = 148 hours ・35 hours per week for 4 weeks, with 2 8-hour days off, and 3 4-hour days off = 112 hours Free response in 3 digits

No. 16 Question item: Presenteeism (B9) Question format: Select one Q: On a scale of 0 to 10, where 0 is the performance that anyone can achieve in your job and 10 is the performance of the best worker, how would you rate the usual performance of most workers in jobs similar to yours? [Required]
0 Worst performance 1
2
3
4
5
6
7
8
9
10. Best Performance

No. 17 Question item: Presenteeism (B10) Question format: Select one Q: On the same 0 to 10 scale, how would you rate your usual performance over the past 1-2 years? [Required]
0 Worst performance 1
2
3
4
5
6
7
8
9
10. Best Performance

No. 18 Question item: Presenteeism (B11) Question format: Select one Question: On the same 0 to 10 scale, how would you rate your overall performance on each of your workdays during the past 4 weeks (28 days)? [Required]
0 Worst performance 1
2
3
4
5
6
7
8
9
10. Best Performance

No. 24 Question item: Cold Question format: Select one Question: Have you had a cold between September 2017 and February 2018? Please select the number of times you have had a cold [Required]
(1) I didn’t catch a cold.
(2) I caught a cold once.
(3) I caught a cold twice.
(4) Have had a cold three or more times

No. 25 Question item: Cold Question format: Select one Question: Did you have influenza between September 2017 and February 2018?
Please select the number of times you have had the flu [Required]
(1) I didn’t get the flu.
(2) I had the flu once.
(3) Having had influenza more than twice

No. 26 Question item: Other Question format: Free text Question: Please tell us if there is anything you are concerned about or would like to know about sleep. [Free response]

Next, we will explain the sleep state parameter PS. An example of the sleep state parameter PS is shown below.

1) Evaluation content: Severity of insomnia, sleep quality, daytime sleepiness, sleep duration, etc. Evaluation index/evaluation method: Athens Insomnia Scale Value used for evaluation: Total score of 8 questions

2) Evaluation content: quality of sleep Evaluation index/method: Pittsburgh Sleep Quality Index Values used for axis: Total score calculated from answers to 18 questions

3) Evaluation content: quality of sleep Evaluation index/method: St. Mary's Hospital Sleep Questionnaire Values used for evaluation: score of any question out of 14 questions that make up the questionnaire

4) Evaluation content: Sleep quality Evaluation index/evaluation method: Sleep quality VAS (Visual Analog Scale)
Values used for evaluation: VAS score

5) Evaluation content: Daytime sleepiness Evaluation index/evaluation method: Epworth Sleepiness Scale Value used for evaluation: Total score of 8 questions

6) Evaluation content: Daytime sleepiness Evaluation index/method: Karolinska Sleepiness Scale (a scale for evaluating sleepiness on a 9-point scale)
Numerical value used for evaluation: Score

7) Evaluation content: Daytime sleepiness Evaluation index/assessment method: degree of sleepiness VAS (Visual Analog Scale)
Values used for evaluation: VAS score

8) Evaluation content: Sleep time (length)
Evaluation index/evaluation method: Sleep time Values used for evaluation: Actual time or some kind of score Overview: Actual length (e.g. 6 hours 30 minutes) or scoring of time (e.g. 6-8 hours is 3 points). Scoring of subjective evaluation such as whether it was enough/not enough, etc.

Next, we will explain the Athens Insomnia Scale (AIS). An example of the Athens Insomnia Scale is shown below, and the total score for each number is used.

No. 1 Problems falling asleep 0. No problem 1. Took me a little time 2. Took me quite a long time 3. Took me a very long time or I couldn't fall asleep at all

No. 2: Problems with waking up during the night 0. Not enough to be a problem 1. A little troublesome 2. Quite troublesome 3. Serious or couldn't sleep at all

No. 3: Regarding the problem of waking up earlier than the desired wake-up time and not being able to fall asleep any further: 0. Never 1. A little early 2. Quite early 3. Very early or not able to fall asleep at all

No. 4 Total sleep time: 0. Enough 1. A little bit not enough 2. Quite not enough 3. Not enough or I couldn't sleep at all

No. 5 Overall quality of sleep 0. Satisfied 1. Slightly dissatisfied 2. Quite dissatisfied 3. Very dissatisfied or could not sleep at all

No. 6: Regarding daytime satisfaction: 0. As usual 1. A little less 2. Quite less 3. Extremely less

No. 7 Daytime activities (physical and mental)
0. As usual 1. A little bit worse 2. Quite a bit worse 3. Extremely worse

No. 8 Daytime sleepiness: 0. Not at all 1. A little 2. Quite a bit 3. Extremely

For information on the Pittsburgh Sleep Quality Index, please refer to the following URL (Yuriko Doi, Masumi Minowa, Masako Okawa, Makoto Uchiyama: Creation of a Japanese version of the Pittsburgh Sleep Quality Index. Psychiatry and Therapy 1998; 13 (6); 755-769.) http://www.kanen.ncgm.go.jp/study_download/20111202_02_02.pdf
For information on the St. Mary's Hospital Sleep Questionnaire, please refer to the following literature (Uchiyama Makoto, Ota Katsuya, Okawa Masako: Assessment scales for sleep and sleep disorders. Clinical Psychiatry Course 13: Sleep Disorders (edited by Ota Tatsuro and Okawa Masako), Nakayama Shoten, p498, 1999).
VAS (Visual Analog Scale) is a method for inputting numerical values from 0 to 100 on a visual analog scale.
For information on the Epworth Sleepiness Scale, see the following URL (Takegami M, Suzukamo Y, Wakita T, et al: Development of a Japanese version of the Epworth Sleepiness Scale (JESS) based on Item Response Theory. Sleep Med, 10 (5): 556-565, 2009).
https://www.jrs.or.jp/quicklink/journal/nopass_pdf/044110896j.pdf
For more information on the Karolinska sleepiness scale, please see the following literature (Kaida K, Takahashi M, Aakerstedt T, et al: Validation of the Karolinska sleepiness scale against performance and EGG variables. Clin Neurophysiol 2006; 117: 1574-81).

Next, we will explain the physical condition parameter PB. An example of the physical condition parameter PB is shown below.

1) Content of evaluation: Presenteeism Evaluation index/method: (1) WHO-HPQ absolute presenteeism (questionnaire No. 18 presenteeism (B11) multiplied by 10), (2) WHO-HPW relative presenteeism (questionnaire No. 18 presenteeism (B11) divided by question No. 16 presenteeism (B9). If the value is 0.25 or less, it is converted to 0.25. If the value is 2.0 or more, it is converted to 2.0. If B9=0 and B11=1-10, it is converted to 2.0. If B9=B11=0, it is converted to 1.0.), (3) University of Tokyo single-item version, (4) WLQ (Work Limitations Questionnaire), (5) SPS (Stanford Presentism Scale), (6) Wfun (Work Functioning Impairment Scale), (7) QQmethod
Values used for evaluation:
Summary: See p.27-31 of https://www.meti.go.jp/policy/mono_info_service/healthcare/kenkokeiei-guidebook2804.pdf. See https://www.hcp.med.harvard.edu/hpq/ftpdir/WMHJ-HPQ-SF_2018.pdf.

2) Evaluation content: cold Evaluation index/evaluation method: had a cold/did not have a cold Value used for evaluation: odds ratio

3) Content of evaluation: Physical condition Evaluation index/method: Subjective sense of health Values used for evaluation: Scoring of answers on a scale using verbal options

4) Evaluation content: Fatigue Evaluation index/method: (1) Chalder Fatigue Scale, (2) VAS (Visual Analog Scale)
Numerical values used for evaluation: (1) Total score calculated from answers to 15 questions, (2) VAS score

5) Evaluation content: Mental health Evaluation index/evaluation method: K6
Evaluation score: Total score of 6 questions

6) Evaluation content: Eye strain Evaluation index/evaluation method: (1) Yes/No, (2) VAS (Visual Analog Scale)
Values used for evaluation: (1) odds ratio, (2) VAS score

7) Evaluation content: Degree of motivation Evaluation index/method: (1) VAS (Visual Analog Scale), (2) Utrecht Work Engagement Scale (UWES)
Numerical values used for evaluation: (1) VAS score, (2) score for any of the 17, 9, or 3 questions that make up the questionnaire. Overview: For more information on work engagement, see the following literature (Shimazu, A., Schaufeli, WB, Kosugi, S. et al. (2008). Work engagement in Japan: Validation of the Japanese version of Utrecht Work Engagement Scale. Applied Psychology: An International Review, 57, 510-523).

8) Evaluation content: degree of stiff shoulders Evaluation index/evaluation method: (1) yes/no, (2) VAS (Visual Analog Scale)
Values used for evaluation: (1) odds ratio, (2) VAS score

9) Evaluation content: Degree of low back pain Evaluation index/evaluation method: (1) Yes/No, (2) VAS (Visual Analog Scale)
Values used on the axes: (1) odds ratio, (2) VAS score

10) Evaluation content: Degree of constipation Evaluation index/evaluation method: (1) Yes/No, (2) VAS (Visual Analog Scale)
Values used for evaluation: (1) odds ratio, (2) VAS score

11) Evaluation content: Degree of runny nose Evaluation index/evaluation method: (1) Yes/No, (2) VAS (Visual Analog Scale)
Values used for evaluation: (1) odds ratio, (2) VAS score

12) Evaluation content: Degree of nasal congestion Evaluation index/evaluation method: (1) Yes/No, (2) VAS (Visual Analog Scale)
Values used for evaluation: (1) odds ratio, (2) VAS score

13) Evaluation content: Severity of headache Evaluation index/evaluation method: (1) Yes/No, (2) VAS (Visual Analog Scale)
Values used for evaluation: (1) odds ratio, (2) VAS score

14) Evaluation content: Absenteeism Evaluation index/evaluation method: Number of days absent or absent due to illness Values used for evaluation: Number of days absent or absent due to illness

Next, sleep improvement information will be described. As an example of sleep improvement information, FIG. 4 is a graph showing absolute presenteeism (productivity) (Z-axis) as a function of the Athens Insomnia Scale (X-axis) and social jet lag (Y-axis). From this graph, it can be seen that absolute presenteeism decreases as the Athens Insomnia Scale and social jet lag increase.

For ease of understanding, Fig. 5 is a graph in which the numerical values on the XYZ axes in Fig. 4 are simply expressed as two values, "good" and "bad." In this case, eight combinations are assumed, and examples of sleep improvement messages corresponding to each combination are shown below. The two values, "good" and "bad," are shown in the following order: (presenteeism, Athens Insomnia Scale, social jet lag).

1 Bad Good Bad Your work performance is poor. It is becoming clear that both sleep state and rhythm affect performance. Your sleep quality is good, but your sleep rhythm between weekdays and weekends is disrupted, so try to maintain the same sleep rhythm as much as possible.

2 Good Good Bad It is becoming clear that both sleep state and rhythm affect performance. Your work performance is currently good, but your sleep rhythm between weekdays and weekends seems to be disrupted. If you continue to live a life with a disrupted sleep rhythm, your performance may decline. Be conscious of living with the same sleep rhythm as much as possible.

3 Bad Good Good Your work performance is poor. It is known that both sleep state and rhythm affect performance, but your sleep state and your sleep rhythm between weekdays and weekends seem to be in good condition. There may be some other problem other than sleep. Try to maintain your current sleep habits.

4 Good Good Good Your work performance is in good condition. It is becoming clear that both sleep state and rhythm affect performance, but it seems that both your sleep state and sleep rhythm are in good condition. Please continue to maintain your current lifestyle rhythm.

5 Bad Bad Bad Your work performance is poor. It is known that both sleep state and rhythm affect performance, but you have a bad sleep state and your sleep rhythm is also disturbed between weekdays and weekends. First of all, try to be conscious of living with the same sleep rhythm as much as possible.

6 Good Bad Bad Your sleep is bad, and your sleep rhythm between weekdays and weekends is also disrupted. It is becoming clear that sleep state and rhythm affect work performance. Your work performance is currently good, but from now on, try to be conscious of keeping your sleep rhythm as consistent as possible so that your work performance does not decline.

7 Bad Bad Good Your work performance is poor. It is becoming clear that sleep conditions and rhythms affect work performance. You have a good sleep rhythm on weekdays and weekends, but your sleep condition is not good. If you are stressed, you cannot get good quality sleep. Try to relax.

8 Good Bad Good It is becoming clear that sleep conditions and rhythms affect work performance. You have a good sleep rhythm on weekdays and weekends, but your sleep condition is not good. Your work performance is good now, but you should aim to improve your sleep condition so that your work performance does not decline. Stress makes it difficult to get good quality sleep. Try to relax.

As another example of sleep improvement information, Figure 6 is a graph showing the odds ratio of catching a cold (Z-axis) as a function of the Athens Insomnia Scale total score (X-axis) and social jet lag (Y-axis). For convenience, the odds ratio of each variable category is visualized using a bar graph, assuming an Athens Insomnia Scale total score of 3p or less and social jet lag of less than one hour as the criteria. From this graph, it can be seen that the odds ratio of catching a cold increases as the Athens Insomnia Scale total score increases and as social jet lag increases.

Next, we will explain how to calculate the odds ratio of contracting a cold. For the analysis target population, the logistic regression model of the following formula (1) is used, in which the dependent variable is the presence or absence of contracting a cold, and the Athens Insomnia Scale total score (4 categories) and the social jet lag (3 categories) are the explanatory variables, to estimate the odds associated with changes in the classification levels of the Athens Insomnia Scale total score (4 categories) and the social jet lag (3 categories).

where i indicates the i-th subject, p indicates the probability of catching a cold as determined by the questionnaire, ATN indicates the four Athens Insomnia Scale classifications (up to 3p, 4-5p, 6-9p, 10p+), and SJL indicates the three social jet lag classifications (up to 1h, 1-2h, 2h+). The odds ratios associated with changes in ATN and SJL are estimated as exp(β ₂ ) and exp(β ₃ ), respectively. Note that in actual calculations, dummy variables are used for ATN and SJL, with ATN=up to 3pt and SJL=up to 1h as the reference categories, respectively.

The statistical processing programming language R3.6.0 was used for the estimation. Below is the R language code used for the estimation using hypothetical data.

[Virtual data creation code]
Y <- c(rep(0, 430), rep(1, 570))
ATN <- c(rep("~3p", 140), rep("4~5p", 50), rep("6~9p", 60), rep("10p~", 20),
rep("~3p", 60), rep("4~5p", 30), rep("6~9p", 20), rep("10p~", 10),
rep("~3p", 10), rep("4~5p", 10), rep("6~9p", 10), rep("10p~", 10),
rep("~3p", 130), rep("4~5p", 90), rep("6~9p", 70), rep("10p~", 40),
rep("~3p", 70), rep("4~5p", 40), rep("6~9p", 60), rep("10p~", 20),
rep("~3p", 10), rep("4~5p", 10), rep("6~9p", 10), rep("10p~", 20))
SJL <- c(rep("~1h", 340), rep("1~2h", 80), rep("2h~", 10),
rep("~1h", 390), rep("1~2h", 150), rep("2h~", 30))
d <- data.frame(Y, ATN, SJL)

[Odds ratio estimation code]
RESULT <- glm(Y ~ ATN + SJL, data = d, family = binomial)
exp(RESULT$coefficients)

As an example, the estimated odds ratios for the above hypothetical data are shown below (Table 1). From the estimated results, as shown in Figure 6, it can be seen that for ATN = ~3p, the odds ratio when ATN = 10p ~ is 1.60. Similarly, it can be seen that for SJL = ~1h, the odds ratio when SJL = 2h ~ is 2.01. Furthermore, for ATN = ~3p and SJL = ~1h, the odds ratio when ATN = 10p ~ and SJL = 2h ~ is 1.60 x 2.01 = 3.21.

When outputting the sleep improvement information (S5), the graph shown in FIG. 6 may be displayed on the screen of the terminals 21, 22, 23 together with the sleep improvement message described above. Furthermore, together with the graph shown in FIG. 6 and the sleep improvement message described above, the answer results regarding colds (questions No. 24 and No. 25), for example, a message saying "You have had a cold in the past six months," may be displayed together. Furthermore, together with the graph shown in FIG. 6 and the sleep improvement message described above, advice such as "Your sleeping habits make you 1.8 times more likely to catch a cold than the group with good sleeping conditions" may be displayed together.

In addition, when displaying the graphs shown in Figures 4 and 6, a graph calculated based on a database that reflects the data entered by the current user may be displayed, or a graph calculated based on a database before the data entered by the current user is reflected may be displayed.

The present invention is industrially useful in that it can provide information for improving sleep that takes social jet lag into account.

1 Sleep information processing system 10 Host computer 11 Storage device 21, 22, 23 Terminal

Claims (4)

inputting into a computer first time information I1 relating to a bedtime SOw when the subject's sleep started and a wake-up time SEw when the sleep ended on a workday of the subject, and second time information I2 relating to a bedtime SOf when the subject's sleep started and a wake-up time SEf when the sleep ended on a non-workday of the subject;
a step of calculating a median sleep value MSw on working days based on the first time information I1, calculating a median sleep value MSf on non-working days based on the second time information I2, and determining a value SJL obtained by subtracting the median sleep value MSw from the median sleep value MSf or its absolute value |SJL| as a sleep duration variation parameter PL representing a sleep duration variation ;
inputting a sleep state parameter P representing a sleep state of the subject into said computer;
and outputting sleep improvement information by the computer using the sleep time variation parameter PL and the sleep state parameter PS. The sleep information processing method according to claim 1 , wherein the sleep state parameter PS is a questionnaire result including at least one of sleep time, sleep quality, and daytime sleepiness . On the computer,
A function for inputting first time information I1 relating to a bedtime SOw when sleep started and a wake-up time SEw when said sleep ended on a working day of the subject, and second time information I2 relating to a bedtime SOf when sleep started and a wake-up time SEf when said sleep ended on a non-working day of the subject;
a function of calculating a median sleep value MSw on working days based on the first time information I1, calculating a median sleep value MSf on non-working days based on the second time information I2, and determining a value SJL obtained by subtracting the median sleep value MSw from the median sleep value MSf or its absolute value |SJL| as a sleep duration variation parameter PL representing a sleep duration variation ;
A function of inputting a sleep state parameter PS representing the sleep state of the subject;
A sleep information processing program for realizing a function of outputting sleep improvement information using the sleep time variation parameter PL and the sleep state parameter PS. a first input means for inputting first time information I1 relating to a bedtime SOw when the subject's sleep started and a wake-up time SEw when the sleep ended on a workday, and second time information I2 relating to a bedtime SOf when the subject's sleep started and a wake-up time SEf when the sleep ended on a non-workday;
a calculation means for calculating a median sleep value MSw on working days based on the first time information I1, calculating a median sleep value MSf on non-working days based on the second time information I2, and determining a value SJL obtained by subtracting the median sleep value MSw from the median sleep value MSf or its absolute value |SJL| as a sleep duration variation parameter PL representing a sleep duration variation ;
A second input means for inputting a sleep state parameter PS representing the sleep state of the subject;
and an output unit for outputting sleep improvement information using the sleep time variation parameter PL and the sleep state parameter PS.

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