Adult Disease Risk Prediction Using Wearables, Hearing, and Health Data

April 13, 2026 updated by: National Health Research Institutes, Taiwan

A Study to Build a Disease Risk Prediction Model for Adults by Integrating Data From Wearable Devices, Hearing Tests, and Multiple Health Databases

This prospective cohort study aims to develop and validate a personalized disease risk prediction model for adults by integrating multiple sources of health data. The study will recruit community-dwelling adults aged 18 years and older in Taiwan. After providing informed consent, participants will complete a structured questionnaire, undergo pure tone hearing testing, and wear a smartwatch for 2 weeks to collect continuous physiological data, including heart rate and physical activity. With participant authorization, the study will also collect data from personal health records and national health insurance databases to allow longer-term follow-up of health outcomes.

The main goals of the study are to examine the relationships among hearing, lifestyle factors, and wearable device data; to identify combinations of risk factors associated with progression from health to subclinical or chronic disease states; and to develop analytical methods for integrating heterogeneous health data from questionnaires, physiological monitoring, hearing tests, and medical databases. Machine learning methods will be used to identify important predictors and build risk prediction models.

The study hypothesis is that combining hearing measures, lifestyle information, wearable physiological data, and longitudinal medical record data will improve the ability to identify individuals at higher risk of future disease compared with using a single source of information alone. The long-term objective is to support early risk identification, personalized health management, and prevention strategies in community adults.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Detailed Description

This study is a prospective cohort study designed to integrate multimodal health data for the development and validation of personalized disease risk prediction models in community-dwelling adults in Taiwan. The study focuses on combining actively collected research data, continuous wearable device data, hearing assessment results, and longitudinal health records to better understand the transition from health to subclinical states and chronic disease.

Participants aged 18 years and older will be recruited from community settings. After informed consent is obtained, study procedures will include a structured questionnaire, pure tone audiometry, and 2 weeks of smartwatch monitoring. The questionnaire will collect demographic characteristics, personal and family disease history, and lifestyle factors such as exercise, sleep, smoking, and alcohol use. Hearing function will be assessed using pure tone audiometry. Continuous physiological data collected from the wearable device will include heart rate and physical activity, such as step counts. Research staff will assist participants with device setup, application installation, and instructions for use to improve data completeness and consistency.

With participant authorization, the study will also obtain personal health record data and link study data with national health insurance databases to support longitudinal follow-up and ascertainment of disease outcomes. These linked data sources may include outpatient, inpatient, pharmacy, insurance enrollment, catastrophic illness, death registry, cancer registry, and adult preventive health examination records. The integration of these heterogeneous data sources is intended to provide a more complete picture of individual health trajectories and disease progression than can be achieved with any single data source alone.

The scientific objectives of the study are to:

  1. evaluate the associations among hearing status, lifestyle factors, and continuous wearable-derived physiological measures;
  2. identify combinations of key predictors associated with progression from health to subclinical or chronic disease states;
  3. establish an analytical framework for integrating heterogeneous data from questionnaires, hearing tests, wearable monitoring, and medical databases; and
  4. develop and validate high-accuracy personalized disease risk prediction models using statistical and machine learning methods.

Data processing will include data cleaning, handling of missing values, outlier checking, standardization, and cross-source data integration. Statistical analyses will include correlation and regression approaches to examine relationships among hearing, lifestyle, and wearable variables. Machine learning methods, including feature selection and supervised learning algorithms such as random forests and gradient boosting methods, will be used to identify important predictors and construct risk prediction models. Model performance will be evaluated using measures such as area under the receiver operating characteristic curve and accuracy. Internal and, where available, external validation strategies will be used to assess robustness and generalizability.

The central hypothesis of the study is that integrating hearing measures, lifestyle information, wearable physiological data, and longitudinal medical record data will improve disease risk prediction compared with models based on a single type of data alone. The long-term goal is to support early identification of high-risk individuals, facilitate personalized health management, and provide evidence for preventive health strategies in adult populations.

A strong emphasis will be placed on data privacy and confidentiality. All study data will be coded using unique study identifiers. The linkage file connecting study identifiers to personal identifiers will be stored separately with restricted access and encryption. After data collection, cleaning, and linkage procedures are completed and verified, the linkage file will be permanently destroyed so that subsequent analyses are conducted on de-identified data only. Any reports or publications resulting from the study will present aggregated findings without personally identifiable information.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Estimated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
1500

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.

Study Locations

  • Taiwan
    • Miaoli
      • Zhunan, Miaoli, Taiwan, 350
        • Recruiting
        • National Health Research Institutes
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

Community-dwelling adults aged 18 years and older in Taiwan will be recruited from community settings, including community care stations, public health centers, activity centers, lifelong learning centers for older adults, and collaborating local organizations. Public recruitment may also be conducted through online platforms and social media. Recruitment will be carried out across multiple geographic regions in Taiwan to include participants from both urban and rural communities.

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
Community-Dwelling Adults
Adults aged 18 years and older recruited from community settings in Taiwan. Participants will complete a structured questionnaire, undergo hearing assessment, wear a smartwatch for 2 weeks, and authorize collection of personal health records and linked national health insurance data for health outcome follow-up.

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
Performance of Personalized Disease Risk Prediction Models
Time Frame: At the completion of data collection and model validation, including baseline assessment and 2-week wearable monitoring
Model performance will be evaluated for personalized disease risk prediction models developed using integrated questionnaire, hearing, wearable device, personal health record, and national health insurance data. Performance metrics will include area under the receiver operating characteristic curve (AUC-ROC), accuracy, and related validation measures in training and test datasets.
At the completion of data collection and model validation, including baseline assessment and 2-week wearable monitoring

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
National Health Research Institutes, Taiwan

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
January 9, 2026

Primary Completion (Estimated)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
January 1, 2029

Study Completion (Estimated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
January 1, 2029

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
April 13, 2026

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
April 13, 2026

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
April 21, 2026

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
April 21, 2026

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
April 13, 2026

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
April 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • EC1140910

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Individual participant data will not be shared. The study involves sensitive personal health information, including questionnaire data, hearing assessment data, wearable device data, personal health records, and linked national health insurance database records. Although study data will be de-identified for analysis, the protocol includes strict privacy protection and data security procedures, and no plan for external sharing of individual participant data has been established.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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