An AI-Assisted Cognitive Engagement Mobile App for Older Adults: Development and Mixed Methods Usability Study.

Authors

Hojin Shin, Minjun Shin

Published in

JMIR formative research. Volume 10. Pages e103986. Sep 10, 2026. Epub Sep 10, 2026.

Abstract

Alzheimer disease and age-related cognitive decline reduce memory engagement and limit caregiver insight, creating a need for accessible tools that support everyday cognitive activity in older adults. Although AI holds promise for personalized cognitive support, few AI-based apps have been developed and evaluated for memory engagement in this population, and fewer incorporate on-device emotional analysis with privacy-preserving design.
This study developed and evaluated RecallLive, an AI-assisted mobile app supporting structured memory interactions for older adults, and examined its usability, engagement, perceived usefulness, and behavioral intention, guided by the Technology Acceptance Model.
RecallLive integrates metadata-based photo clustering to generate memory videos, an on-device convolutional neural network that classifies frame-level emotional responses, and a large language model (LLM)-based module that converts these outputs into caregiver summaries. A sequential 2-phase mixed methods design was used. In phase 1, 202 US adults aged 65 years or older viewed a structured demonstration and completed a survey measuring ease of use, engagement, design clarity, perceived usefulness, and intention to use. In phase 2, 10 participants completed a hands-on session followed by semistructured interviews analyzed thematically. Quantitative analyses were conducted using Python (v.3.11; Python Software Foundation) and included internal consistency estimates; 2-tailed, 1-sample t tests against the scale midpoint; and simple linear regression.
All subscales showed strong reliability (Cronbach α=0.86-0.92). Ease of use (mean 3.77, SD 0.78) and engagement (mean 4.09, SD 0.67) significantly exceeded the scale midpoint (t₂₀₁=14.00 and t₂₀₁=23.19; both P<.001), and perceived usefulness was also rated highly (mean 4.06, SD 0.82). Perceived usefulness was strongly associated with the stated intention to use or recommend the app (β=.796; R²=0.634; F_1,200=346.18; P<.001). Phase 2 complemented these results, showing clear navigation and interpretable feedback.
RecallLive was perceived as usable, engaging, and useful, with perceived usefulness strongly associated with adoption intention. In addition to efficiency, emotional relevance shaped engagement, particularly among participants with caregiving experience or personal connections to dementia. Future studies should use larger samples, longer direct-use periods, and longitudinal and clinical-integration designs to evaluate sustained use and cognitive outcomes.

PMID:
42721354
Bibliographic data and abstract were imported from PubMed on 11 Sep 2026.

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