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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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Developing Customized Personas to Capture Intrinsic Capacity Profiles and Digital Monitoring Intentions in Older

Zehui Xuan1, Yirou Niu1, Ruifu Kang1

  • 1School of Nursing, Capital Medical University, Beijing, China.

JMIR Aging
|May 27, 2026
PubMed
Summary

This study identifies distinct profiles of older adults’ intrinsic capacity (IC) and corresponding psychological intentions for digital monitoring. Tailoring digital health strategies to these personas can improve engagement in integrated care for older people.

Keywords:
digital monitoringintegrated care for older peopleintrinsic capacitylatent profile analysismixed methods studyolder adultspersonas

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Area of Science:

  • Geriatric Medicine
  • Digital Health
  • Health Psychology

Background:

  • Integrated Care for Older People (ICOPE) globally accelerates, emphasizing intrinsic capacity (IC) monitoring for older adults.
  • Digital health technologies are crucial for longitudinal IC monitoring and timely interventions.
  • Understanding psychological intentions for digital IC monitoring, considering IC heterogeneity, remains underexplored.

Purpose of the Study:

  • To develop customized personas reflecting intrinsic capacity (IC) profiles in older adults.
  • To match psychological intentions with these personas to support personalized digital IC monitoring.

Main Methods:

  • An explanatory sequential mixed methods study involving 481 older adults (≥60 years) in Beijing, China.
  • Quantitative phase: Latent profile analysis, descriptive statistics, and logistic regression to cluster IC profiles.
  • Qualitative phase: Semistructured interviews with 25 participants from each profile, analyzed using inductive-deductive content analysis.

Main Results:

  • Three intrinsic capacity (IC) profiles emerged: 'multisubdomain decline-IC imbalance,' 'multisubdomain moderate-sensory deficit,' and 'multisubdomain robust-whole balance.'
  • Profile distribution was influenced by age, education, income, self-rated health, and chronic diseases, impacting functional ability.
  • Customized personas identified: 'anxious evader' (low digital interest, anxiety), 'accommodative adopter' (pragmatic, moderate digital openness), and 'active improver' (proactive, high digital literacy).

Conclusions:

  • This study uniquely integrates latent profile analysis with qualitative personas to link IC heterogeneity with digital monitoring intentions.
  • The developed personas model offers a framework for tailoring digital IC monitoring within community-based integrated care.
  • Effective digital IC monitoring requires aligning strategies with older adults' IC characteristics, psychological readiness, digital literacy, and social support.