Objectives: To examine nurse-supported interventions on sustained mobile health (mHealth) engagement and identify predictors of long-term use in community-dwelling older adults.
Design: Explanatory sequential mixed methods.
Setting and participants: Twelve clinical sites in Liaoning, China (March 2023 to February 2024). Included 1532 participants (quantitative); 32 for qualitative interviews.
Methods: Quantitative: XGBoost machine learning on longitudinal behavioral data. Qualitative: Thematic analysis of in-depth interviews. Integration via joint display.
Results: Morning (8-10 am) notification responsiveness was the strongest retention predictor (mean SHapley Additive exPlanations = 0.34). "Digital companionship" emerged qualitatively (58% anthropomorphized features; χ2 = 9.32, P = .002). Nurse mediation increased data-sharing willingness by 16% vs commercial platforms (P < .001); 89% of high-adherence users valued clinical integration (P < .001).
Conclusions and implications: Nurse support enhances engagement via optimized timing, trust, and integration. Implement nurse-led coaching, electronic health record integration, and supportive reimbursement. Future studies should assess long-term outcomes and cross-cultural applicability.
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