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Name:
UMIN ID:

Recruitment status Preinitiation
Unique ID issued by UMIN UMIN000036231
Receipt No. 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 2019/08/11

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Basic information
Public 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
Acronym Development of a model for supporting a health and productivity management of small and medium-sized companies using IoT
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
Scientific Title:Acronym Development of a model for supporting a health and productivity management of small and medium-sized companies using IoT: A Mixed Method
Region
Japan

Condition
Condition Not applicable
Classification by specialty
Nursing Adult
Classification by malignancy Others
Genomic information NO

Objectives
Narrative objectives1 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.
Basic objectives2 Others
Basic objectives -Others Qualitative and quantitative evaluation of the model
Trial characteristics_1 Exploratory
Trial characteristics_2 Pragmatic
Developmental phase

Assessment
Primary outcomes 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, Stress (work stress questionnaire (stress check) score
2. Labor Productivity: Presentism / absentism (WHO-HPQ, short version) score
3. Sleep improvement: Pittsburgh Sleep Quality Index (PSQI)
4. Health literacy: Health literacy scale-Degree of interest in 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): Advanced Glycation End Products (AGEs), blood pressure, body weight/BMI, urinary sodium (direct measured by participants)
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
Key secondary outcomes

Base
Study type Observational

Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment

Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10

Eligibility
Age-lower limit
20 years-old <=
Age-upper limit

Not applicable
Gender Male and Female
Key inclusion criteria 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, FRESTA, Co., LTD., TSUBAME Travel Co., LTD), and who did not opt out in this study.
Key exclusion criteria 1 Those who requested opt-out in this study
2 Those who are absent for more than 3 months in the study site for any reason
Target sample size 6000

Research contact person
Name of lead principal investigator
1st name Michiko
Middle name
Last name Moriyama
Organization Hiroshima University
Division name Graduate School of Biomedical and Health Sciences
Zip code 734-8553
Address Kasumi 1-2-3, Minamiku, Hiroshima
TEL 082-257-5365
Email morimich@hiroshima-u.ac.jp

Public contact
Name of contact person
1st name Kana
Middle name
Last name Kazawa
Organization Hiroshima University
Division name Graduate School of Biomedical and Health Sciences
Zip code 734-8553
Address Kasumi 1-2-3, Minamiku, Hiroshima
TEL 082-257-5382
Homepage URL
Email kkazawa@hiroshima-u.ac.jp

Sponsor
Institute Hiroshima University
Institute
Department

Funding Source
Organization Hiroshima University
Organization
Division
Category of Funding Organization Other
Nationality of Funding Organization

Other related organizations
Co-sponsor
Name of secondary funder(s)

IRB Contact (For public release)
Organization Hiroshima University
Address Kasumi 1-2-3, Minami-ku, Hiroshima
Tel 082-257-1576
Email iryo-seisaku@office.hiroshima-u.ac.jp

Secondary IDs
Secondary IDs NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW

Institutions
Institutions

Other administrative information
Date of disclosure of the study information
2019 Year 03 Month 18 Day

Related information
URL releasing protocol
Publication of results Unpublished

Result
URL related to results and publications
Number of participants that the trial has enrolled
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description

Progress
Recruitment status Preinitiation
Date of protocol fixation
2018 Year 11 Month 16 Day
Date of IRB
2019 Year 01 Month 23 Day
Anticipated trial start date
2019 Year 04 Month 01 Day
Last follow-up date
2021 Year 03 Month 31 Day
Date of closure to data entry
Date trial data considered complete
Date analysis concluded

Other
Other related information Companies who participated in this project implement a health and productivity management program including 3 programs listed below with supporters outside of the companies (for 1 year) (Observational research).
(1) Disease management program for diabetes, CKD, CVD, (2)Improvement of sleep and stress program, and (3) Antiaging program
Health and productivity management program evaluation devices including IoT : AGEs sensor (SHARP), BP machine (TERUMO)

Management information
Registered date
2019 Year 03 Month 17 Day
Last modified on
2019 Year 08 Month 11 Day


Link to view the page
URL(English) https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000041275

Research Plan
Registered date File name

Research case data specifications
Registered date File name

Research case data
Registered date File name


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