Trajectories and predictors of adherence to the StandingTall digital exercise program

Background: Long-term adherence to exercise and digital health interventions is critical but remains a major challenge, particularly among older people. While balance exercise is effective in preventing falls, little is known about how older people engage with such programs over time, and what drives sustained adherence.

Methods: We analysed adherence data from 511 community-living older people who participated in a home-based digital balance exercise program for 52 weeks. Participants were prescribed two hours of exercise per week, with progressive weekly targets and adherence automatically recorded by the app. Using group-based trajectory modelling, we identified distinct patterns of adherence and examined predictors of these patterns based on cognitive, physical, demographic and psychological characteristics.

Results: Eight behavioural trajectories emerged (i.e., overachievers, consistent adherers, fluctuating adherers, intermittent adherers, late attrition, steady decliners, early attrition, non-adherers), ranging from consistent high adherence to early attrition. Average adherence across the cohort was moderate (56%) of the prescribed dose over 52 weeks. Two objective measures of behavioural capability (i.e., executive function and standing balance) predicted adherence trajectories. Poorer executive function was associated with “boom-and-bust” patterns, while poorer balance was linked to more sustained adherence, suggesting a greater perceived need for training. No demographic or general health factors predicted adherence.

Conclusions: Adherence to digital exercise is a dynamic process shaped primarily by cognitive capacity and balance ability rather than age or health status. Framed within the COM-B model, our findings demonstrate that behavioural capability predicts long-term adherence and reveal a critical early window for targeted support. Despite regular follow-up calls, adherence declined most steeply in the first 10-15 weeks, highlighting a gap in behaviourally focused strategies. This study establishes a new behavioural framework for precision engagement in digital health, with implications for the design of adaptive, personalised interventions that support older people to age well at home.