Usability and Adoption of Smartwatches by Older Adults in Bangladesh: User Study

Background: Wearables such as smartwatches can support point-of-care health management for older adults while reducing pressure on health care systems as aging populations grow. Although many studies emphasize technical accuracy, user-centered research on smartwatch adoption among older adults remains limited, particularly in low- and middle-income countries, such as Bangladesh. Objective: This study evaluated real-world usability, acceptance, and adoption of smartwatches among socioeconomically diverse older adults (aged ≥60 y) in a low- and middle-income country context. It examined how age, education, socioeconomic background, and cultural perceptions influence user experience, and identified barriers and facilitators related to comfort, usability, and long-term engagement. It also explored health-related features that older adults perceived as missing. Methods: Participants were recruited from older adult communities with diverse socioeconomic and educational backgrounds, and received a commercially available smartwatch. A mixed methods, 3-phase longitudinal design was conducted, including a short-term survey (n=27), 3 long-term survey data points (n=19, 18, and 18), and 2 focus group interviews (n=13 and 12). Quantitative analyses included paired t tests across longitudinal data points and chi-square tests for distributional associations, complemented by thematic qualitative analysis. Results: Comfort improved substantially over time, with participants rating the smartwatch as very comfortable, increasing from 26% (5/19) at baseline to 80% (16/20) at final follow-up. Heart rate monitoring remained the most frequently used feature, rising from 68.42% (13/19) to 75% (15/20). Paired t tests showed no significant longitudinal changes in daily usage (t5=0.00 to 0.22, P=.83 to ≥.99), comfort (t4=-0.07 to 0.30, P=.78 to .95), most liked features (t8=-0.63 to 0.51, P=.30 to .62), or clarity of instructions (t2=0.00 to 0.19, P=.87 to ≥.99). Significant increases were observed in feature usage (data point [DP] 2 vs DP3: t8=-4.16, P