It is essential to enhance the effectiveness of elderly care systems by accurately identifying community age-friendly service needs. Existing need assessment approaches often rely on self-reported demands or single-dimensional capability assessments, which may fail to capture the complex interaction between older adults’ functional status and their caregiving environments. This study proposes a methodological framework for identifying community age-friendly service needs based on dual digital capability portraits. The framework integrates two analytical dimensions: individual functional capability and family caregiving capability. Firstly, a dual capability assessment framework was developed to capture the multidimensional characteristics of older adults and their household caregiving environments. Secondly, the assessment results were transformed into structured digital capability portraits to enable the standardized representation of capability information. Thirdly, capability–service need mapping matrices were constructed to establish explicit rule-based relationships between capability states and corresponding service needs. Based on these components, a hybrid decision-support approach combining rule-based reasoning and collaborative filtering was designed to generate prioritized service recommendations. A mobile application was developed to demonstrate the operational feasibility of the proposed method using a pilot sample of community-dwelling older adults. The framework facilitates the systematic translation of capability assessment outcomes into structured identification of service needs. The pilot application demonstrates how digital capability portraits can be operationalized to produce personalized service recommendations within community care settings. This study presents a methodological framework for identifying community age-friendly service needs through dual digital capability portraits and structured capability–service mapping.
Xue et al. (Wed,) studied this question.