A mobile app to predict and manage behavioral and psychological symptoms of dementia: Development, usability, and users' acceptability.

Abstract

Objective: Non-pharmacological interventions are considered the first-line treatment for behavioral and psychological symptoms of dementia (BPSD); however, traditional approaches have shown only small effect sizes. Mobile technology offers an opportunity to improve BPSD assessment and management in people living with dementia (PLWD). We aimed (1) to develop a mobile application (app) featuring a real-time BPSD diary, machine-learning-based BPSD prediction, and individualized non-pharmacological care programs, including therapeutic use of music and reminiscent content, and (2) to test its usability, acceptability, and preliminary efficacy among PLWD and caregivers. Methods: An Android-based app was developed through the following three phases: (1) needs assessment, (2) software development and initial testing with experts, and (3) beta-testing with end users who were dyads of PLWD and caregivers. The preliminary efficacy, usability, and acceptability of the app were assessed using validated BPSD questionnaires and face-to-face interviews with the dyads. Logs of the dyads' program participation (i.e., types, time, and duration), BPSD diaries, and engagement levels of PLWD were also collected through the app. Results: Five dyads created BPSD diaries (range: 22-48) over 3 weeks. Overall, the BPSD symptoms decreased after the beta-testing period. Each dyad participated in the care programs for 106-204 min, during which music alone was most frequently used. Engagement levels ranged from 3.38 to 4.94 (out of 5). Conclusions: The app was deemed usable, acceptable, and feasible for PLWD and caregivers. The upgraded app will be further tested and can be easily implemented at home or in the community.