Unique ID issued by UMIN | UMIN000036231 |
---|---|
Receipt number | R000041275 |
Scientific Title | Development of a model for supporting a health and productivity management of small and medium-sized companies using IoT and AI contributing to the mental and physical health improvement of employees: A Mixed Method |
Date of disclosure of the study information | 2019/03/18 |
Last modified on | 2022/12/21 15:16:05 |
Development of a model for supporting a health and productivity management of small and medium-sized companies using IoT and AI contributing to the mental and physical health improvement of employees
Development of a model for supporting a health and productivity management of small and medium-sized companies using IoT
Development of a model for supporting a health and productivity management of small and medium-sized companies using IoT and AI contributing to the mental and physical health improvement of employees: A Mixed Method
Development of a model for supporting a health and productivity management of small and medium-sized companies using IoT: A Mixed Method
Japan |
Not applicable
Nursing | Adult |
Others
NO
Evaluate the effects of the health and productivity management of companies that have implemented the health and productivity management program including the IoT-based behavior change program for improving the health of employees. Finally, we will evaluate the model to support the health and productivity management of small and medium-sized companies.
Others
Qualitative and quantitative evaluation of the model
Exploratory
Pragmatic
As it is an exploratory study of evaluating the model, multiple evaluation items are set.
1. Psychological Indicators: Work engagement (UWES: Utrecht Work Engagement Scale) score, Job and family satisfaction (work stress questionnaire)
2. Labor Productivity: Presentism / absentism (WHO-HPQ, short version) score
3. Sleep improvement: Pittsburgh Sleep Quality Index (PSQI)
4. Health literacy: HLS-EU-Q47 Japanese version, Degree of interest one's own body: Likert scale (0 to 10)
5. Behavior change indicators: Frequency rate of using IoT and changes in values
6. Physiological Indicators (collected by IoT): blood pressure, body weight
7. Qualitative evaluation of this model: Interviews and observation: progress of the health and productivity management, evaluation of this model, attainment rate of health-checkup, improvement of health checkup results/number of medical treatment needy/who made a hospital visits/without hospital visits employees
Observational
20 | years-old | <= |
Not applicable |
Male and Female
All employees (included Regular and part-time employment, all types of work-style) from small and medium-sized companies (ACT CHUSHOKU, Co. LTD., Miyoshi Kamotsu Express (ended in July 2020), FRESTA, Co., LTD., TSUBAME Travel Co., LTD), and who did not opt-out in this study.
1 Those who requested opt-out in this study
2 Part-time job students
3 Those who are absent for more than 3 months in the study site for any reason
440
1st name | Michiko |
Middle name | |
Last name | Moriyama |
Hiroshima University
Graduate School of Biomedical and Health Sciences
734-8553
Kasumi 1-2-3, Minamiku, Hiroshima
082-257-5365
morimich@hiroshima-u.ac.jp
1st name | Michiko |
Middle name | |
Last name | Moriyama |
Hiroshima University
Graduate School of Biomedical and Health Sciences
734-8553
Kasumi 1-2-3, Minamiku, Hiroshima
082-257-5365
morimich@hiroshima-u.ac.jp
Hiroshima University
Hiroshima University
Other
Hiroshima University
Kasumi 1-2-3, Minami-ku, Hiroshima
082-257-1576
iryo-seisaku@office.hiroshima-u.ac.jp
NO
2019 | Year | 03 | Month | 18 | Day |
Unpublished
401
Due to COVID-19, it was difficult to work with the company, and they were forced to significantly reduce sales and suspend business. As a result, no significant improvement was observed, but as a result of each company's efforts, and efforts to maintain the physical and mental health of employees, the baseline condition was maintained.
2022 | Year | 06 | Month | 23 | Day |
Delay expected |
Currently under review process of a journal (baseline data), and now producing a manuscript on this cohort study.
A total of 760 employees enrolled, among them 439 retuned. Validated answers were 377, which were analyzed for this study.
The characteristics of the employees were shown in Table 1. More males (60.5%), and the highest percentage of age group was in the 40s(27.6%) following 50s(26.5%). The majority (70.3%) were married, and regarding work years, 10 to 15 years were the most (21.8%). Physical activity levels were low (Level 1) 17.0%, normal (Level 2) 45.1%, and high (Level 3) 33.4%. Regarding the quality of sleep and HL, 39.0% have sleep disorders with a score of 6 or higher on PIQS, and 72.4% showed low HL with a score of 33 or lower on HLS-EL-Q47.
Enveloped questionnaires were distributed to the employees on an opt-out basis through the personnel manager of each company who was assigned a health and productivity manager position in this study. After participants filled the questionnaires, they returned the questionnaire in a sealed envelope through in-house mail.
None
Work engagement, presenteeism, concern on own body, job satisfaction, family life satisfaction
Completed
2018 | Year | 11 | Month | 16 | Day |
2019 | Year | 01 | Month | 23 | Day |
2019 | Year | 04 | Month | 01 | Day |
2021 | Year | 03 | Month | 31 | Day |
2021 | Year | 12 | Month | 31 | Day |
2021 | Year | 12 | Month | 31 | Day |
2022 | Year | 03 | Month | 31 | Day |
Companies who participated in this project implement a health and productivity management program including health behavior change programs with supporters outside of the companies (for 1.5 years) (Observational research).
2019 | Year | 03 | Month | 17 | Day |
2022 | Year | 12 | Month | 21 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000041275