Skip to content

Digital Care for Holistic Health in Older Adults With Diabetes and Multimorbidity

Digital Care Community Common Good Program Enhances Holistic Health Management for Middle Aged and Older Adults With Diabetes Mellitus and Multiple Chronic Conditions

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07310849
Enrollment
169
Registered
2025-12-30
Start date
2026-05-12
Completion date
2027-07-01
Last updated
2026-08-21

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cardio Vascular Disease, CKD, Dyslipidemia, Gout Arthritis, Hypertension, Type2Diabetes

Keywords

community care, diabetes mellitus, multimorbidity, quality of life, self-management

Brief summary

The purpose of this study was to explore the effectiveness of the "Digital Care Community Common Good" program in improving disease control indicators, self-management abilities, depression, and quality of life among patients with comorbidities and type 2 diabetes. The study was designed as a two-year experimental study, with a specific area in New Taipei City selected as the research site. In the first year, the main tasks include establishing an integrated intervention team composed of primary healthcare providers and community resources, expanding the functionalities of the mHealth platform, developing digital educational materials for diabetes comorbidities care, and recruiting and training 6 to 8 community care volunteers. Additionally, 169 eligible participants with type 2 diabetes and comorbidities will be recruited from four communities, completing baseline assessments and randomization into groups. In the second year, a 6-month intervention and effectiveness evaluation of the " Digital Care Community Common Good " program will be implemented. The intervention includes online and in-person educational sessions, telephone care, use of the mHealth platform (featuring educational, data monitoring, contextual learning, interactive, and reminders), as well as home visits, case discussions, and individualized care plans for high-risk cases. Disease control indicators, selfmanagement abilities, depression, and quality of life will be tracked immediately post-intervention, at 3 month, and at 6 month to assess outcomes and changes over time. This study expects to enhance health management for diabetes patients with comorbidities through digital care and interdisciplinary collaboration, offering evidence-based insights and recommendations for policy implementation in the integration of community and primary healthcare models.

Interventions

BEHAVIORALDigital Care Community Common Good Program

a 6-month Digital Care Community Common Good program (online and in-person educational sessions, telephone care, use of the mHealth platform (featuring educational, data monitoring, contextual learning, interactive, and reminders), as well as home visits, case discussions, and individualized care plans for high-risk cases.)

BEHAVIORALUsual Care

receives usual care and the local integrated medical network information, including clinics and healthcare institutes that provide comorbidity care and counseling.

Sponsors

Chang Gung University of Science and Technology
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
DOUBLE (Subject, Outcomes Assessor)

Eligibility

Sex/Gender
ALL
Age
50 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Age and Consent: Individuals aged 50 years or older who are willing to provide written informed consent. * Language and Literacy: Participants must be literate and able to communicate in Mandarin or Taiwanese. * Medical Diagnosis: Participants must have a physician-confirmed diagnosis of type 2 diabetes mellitus (T2DM) and at least one comorbid chronic disease (e.g., hypertension, hyperlipidemia, chronic kidney disease, or heart disease). * Technology Use: Participants must own a smartphone and be willing to use the LINE messaging app and web-based health education links. * Residence: Participants must reside within one of the four participating communities and have no plans to move away during the study intervention period.

Exclusion criteria

* Those with severe diabetes-related complications, such as renal failure, cerebrovascular disease, diabetic foot, or retinopathy. * Individuals with psychiatric disorders, undergoing active cancer treatment, or those unable to perform independent self-care (e.g., due to visual impairment or mobility limitations). * Individuals without diabetes but with other chronic diseases. * Individuals residing in long-term care institutions. * Individuals who are simultaneously participating in other intervention programs.

Design outcomes

Primary

MeasureTime frameDescription
The Disease Self-Management ScaleT0 Pre-Test: Conducted before the intervention. T1: Conducted immediately after completing the intervention. T2: Conducted three months after completing the intervention. T3: Conducted six months after completing the intervention.This study employs the Disease Self-Management Scale by Professor Ching-Min Chen (2012), based on the Chronic Disease Care Management Model. The scale includes 39 items across four subscales: Partnership, Self-care performance, Problem-solving, and Emotional management. Each item is rated on a 4-point Likert scale (0-3), reflecting participants' self-management behaviors over the past three months. Higher scores indicate better self-management ability. The scale has been validated in community-based studies involving older adults with multiple metabolic chronic diseases, demonstrating strong reliability and validity. Cronbach's alpha (total scale): .83. Subscales: Partnership (.88), Self-care activities (.78), Problem-solving (.90), Emotional management (.60). Internal consistency is considered satisfactory.

Countries

Taiwan

Contacts

CONTACTFei-Ling Wu
flwu@mail.cgust.edu.tw+886-918279618

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Aug 22, 2026