ArticleJMIR aging2026
Developing Customized Personas to Capture Intrinsic Capacity Profiles and Digital Monitoring Intentions in Older Adults: Mixed Methods Study.
Article in JMIR aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Latent profile analysis and analytical model construction based on heterogeneity of intrinsic capacity in Chinese older adults.Frontiers in aging neuroscience · 2026Article
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8 authors.
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Abstract
backgroundIntegrated Care for Older People (ICOPE), focused on monitoring and optimizing the intrinsic capacity (IC) of older adults, is a new model of geriatric care that is currently being accelerated globally. Digital health technologies are recommended for longitudinal IC monitoring to provide precise and timely interventions. However, little is known about the psychological intentions of engaging in digital monitoring of IC according to the profile heterogeneity of IC among older adults.
objectiveThis study aims to map a set of customized personas to capture the profiles of IC and match psychological intentions that support personalized digital IC monitoring.
methodsAn explanatory sequential mixed methods study was conducted at 16 sites in Beijing, China. Older adults aged ≥60 years (n=481) were selected to complete the quantitative survey. Latent profile analysis, descriptive statistics, and logistic regression analyses were performed to cluster subgroups using Mplus (Muthén & Muthén) and SPSS (IBM Corp). A subsample of participants from each profile (n=25) was purposively sampled for semistructured interviews. An inductive-deductive content analysis was used to identify similar attributes and to affirm the personas gradually. A joint statistical and thematic visualization method was used to integrate the customized personas.
resultsThree profiles of IC patterns emerged: "multisubdomain decline-IC imbalance group," "multisubdomain moderate-sensory deficit group," and "multisubdomain robust-whole balance group." The distribution of latent profiles was influenced by age, education, monthly per capita household income, self-rated health, and number of chronic diseases, while positively impacting older adults' functional ability. The following customized personas were captured regarding established themes: "affects my mood-anxious evader," characterized by avoidance and anxiety, low digital interest, and perceived social isolation; "capitalize on what comes-accommodative adopter," pragmatically oriented toward disease detection, with moderate digital openness but limited self-efficacy; and "more autonomy-active improver," who exhibited proactive engagement, high digital literacy, and motivation rooted in self-management and social participation.
conclusionsThis study is the first to integrate latent profile analysis with customized qualitative personas to link the heterogeneity of IC with the psychological intentions underlying digital monitoring. The resulting personas model provides an actionable framework for tailoring digital IC monitoring strategies in community-based integrated care. The findings emphasize the need to align monitoring approaches with older adults' IC characteristics, psychological readiness, digital literacy, and social support to enhance engagement in digital IC monitoring.
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