Using smartwatches, hearing tests, and health records to predict disease risk in adults
Official title: A Study to Build a Disease Risk Prediction Model for Adults by Integrating Data From Wearable Devices, Hearing Tests, and Multiple Health Databases
Run by National Health Research Institutes, Taiwan · NCT07541547 · Data updated 2026-11-12
This project will try to see if combining smartwatch data, hearing tests, questionnaires, and health records can predict future disease risk for adults living in Taiwan.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 1500 (estimated) |
| Sponsor | National Health Research Institutes, Taiwan Academic / other |
| Locations | 1 site (Zhunan, Miaoli) |
| Status | Recruiting |
| Started | January 9, 2026 |
| Main results expected | January 2029 |
| Study ends | January 2029 |
| Registry record updated | April 21, 2026 |
| Trial ID | NCT07541547 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are community-dwelling adults in Taiwan aged 18 or older who can consent, use a smartphone app, complete a questionnaire and hearing test, and wear a smartwatch for two weeks.
✕Probably not a fit
People who are severely frail, have dementia, lack a smartphone or the ability to use the required app, or have bilateral deafness without hearing aids may not be able to participate or benefit from the approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This is a prospective cohort study enrolling community-dwelling adults aged 18 and older in Taiwan who complete a questionnaire, undergo pure tone audiometry, and wear a smartwatch for two weeks to collect continuous physiological data like heart rate and activity. With participant permission, investigators will link these data to personal health records and national health insurance databases for longer-term outcome follow-up. Researchers will use machine learning and statistical models to identify combinations of hearing measures, lifestyle factors, and wearable signals associated with progression from health to subclinical or chronic disease. The project aims to develop and validate personalized risk prediction models that integrate heterogeneous health data sources.
Why it matters
Potential benefit: If successful, the approach could help identify people at higher risk earlier and support more timely, personalized prevention or monitoring.
How similar studies have gone: Previous research using wearables and electronic health data has shown promise for predicting some conditions, but combining hearing tests with wearable data and national insurance records is relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adults aged 18 years and older * Living in the community in Taiwan * Able to understand the study procedures and provide written informed consent * Able and willing to complete the study questionnaire, hearing assessment, and wearable device monitoring procedures * Has access to a smartphone and is able to install and use the study-related application, with assistance from study staff if needed Exclusion Criteria: * Diagnosis of dementia * Too frail or has other health conditions that make participation in the study procedures not feasible * Bilateral deafness without use of any hearing assistive device * Does not have a smartphone or is unable to use a smartphone application required for the study procedures
Where it's running
-
National Health Research Institutes
Zhunan, Miaoli, Taiwan Recruiting
Study contacts
- Study coordinator: Ren-Hua Chung, PhD
- Email: rchung@nhri.edu.tw
- Phone: 886-37206166
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.