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Not recruiting yet

Development of a Frailty Risk Prediction Model and Preliminary Evaluation of a Risk-stratified Social Robot-assisted Intervention in Middle-aged and Older Spousal Caregivers

NCT07740031 · The Hong Kong Polytechnic University · Updated 31 July 2026

What is being tested
Virtual social robot-assisted intervention; Wait-list control group
For
Frailty
Kind of study
Tests a treatment or device on volunteers. No drug phase (a device or procedure study).
Who can join
Ages 50 years and older. About 60 people. The full rules are on the registry page.
Where
Not stated
When
Starts or started 1 Aug 2026, ends 30 June 2028. Registered 31 July 2026.
Results
None posted yet.

In the researchers' words

Background With population ageing accelerating worldwide, long-term care needs are rising, and family caregivers have become an essential yet often under-recognised component of care systems. Older family caregivers are particularly susceptible to frailty because they shoulder substantial caregiving responsibilities while simultaneously experiencing their own age-related decline in health and physiological reserve. Frailty is a clinically important state of heightened vulnerability to stressors and is associated with serious adverse outcomes, including disability, hospitalisation, and mortality. In family caregivers, frailty may compromise not only health and quality of life, but also their capacity to sustain caregiving, with wider implications for the sustainability of family-based long-term care. Research gaps A scoping review conducted by this team indicated that middle-aged and older family caregivers, particularly spousal caregivers, are vulnerable to frailty, with caregiving-related, sociodemographic, physical, psychological, and social factors contributing to this condition. However, existing evidence remains fragmented. Caregiver-specific prognostic tools for estimating future frailty risk are lacking, and risk-stratified interventions among family caregivers are sparse. Aim This study aims to develop and validate an incident frailty risk prediction model for…
ClinicalTrials.gov, NCT07740031