# Construction of community home-based older adult care service model based on modular design concept

## TL;DR

This study creates a modular care model for elderly at home in China, focusing on matching services with diverse needs.

## Contribution

The novel modular service framework with dynamic customization addresses fragmented resources and heterogeneous demands in elderly care.

## Key findings

- Elderly demand for care includes five dimensions, with spiritual/cultural engagement and age-friendly modifications being most urgent.
- Advanced age, disability, living alone, education, and chronic disease correlate with higher care demand intensity.
- A modular framework with a dynamic service combination function was developed to enable precise customization.

## Abstract

To address the supply–demand mismatch in community home-based older adult care services amid China’s deepening aging population crisis.

This study employs a modular design concept, selecting Liaoning Province—the region with the nation’s highest aging rate—as the research area. A questionnaire survey was conducted among 331 community-dwelling older adults, and multiple linear regression analysis was applied to identify factors influencing care service demands.

Key findings include: (1) Older adult’ demands manifest a five-dimensional structure (life assistance, medical care, spiritual/cultural engagement, rights protection, and age-friendly modifications), with spiritual/cultural engagement (score rate: 68.40%) and age-friendly modifications (67.67%) being the most urgent needs. (2) Subgroups including advanced age (≥71 years), disabled, living alone, highly educated, and chronic disease individuals exhibited significantly higher demand intensity (p < 0.05). For instance, the regression coefficient (B) for medical care demand among the disabled reached 0.545. (3) Based on these results, a modular service framework was constructed, featuring five functionally independent core modules. A dynamic service package combination function was innovatively proposed, utilizing a module activation coefficient (αk,i) and an module weighting factor (βk,i) to achieve precise customization.

Centered on community residents’ committees (CRCs) as coordination hubs, this model enables dynamic monitoring and optimization through the Demand-Service Matching Index (DSMI), offering an actionable solution to reconcile fragmented resources and heterogeneous demands, thereby supporting both older adults and their caregivers in regional older adult care systems.