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<p>Long-term adherence to exercise delivered through digital health interventions is critical but remains a major challenge, particularly among older people. We pooled intervention-arm data from two randomised controlled trials in 511 community-living older people who participated in a home-based digital balance exercise programme for 52 weeks. Weekly adherence was automatically recorded and expressed as percentage of prescribed dose. Group-based trajectory modelling identified distinct trajectories of adherence and multinomial adaptive lasso regression examined cognitive, physical, demographic and psychological predictors of trajectory group membership. Eight adherence trajectories emerged: overachievers (3.9%), consistent adherers (8.2%), fluctuating adherers (23.1%), intermittent adherers (15.9%), late attrition (11.4%), steady decliners (18.4%), early attrition (14.9%), and non-adherers (4.3%). On average, participants achieved 56% of their prescribed dose. Executive function and standing balance predicted adherence trajectory group membership. Poor executive function was associated with high initial adherence followed by a steep decline, while poorer balance was associated with more sustained adherence. Demographic or general health variables did not significantly predict adherence trajectories. Adherence to digital exercise is a dynamic behaviour, shaped by behavioural capability rather than by age or comorbidities. These findings inform the design of adaptive digital interventions to promote long-term adherence to digital programmes among older people.</p>

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Adherence trajectories and predictors of digital balance exercise for fall prevention in community-living older people

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月1日

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  • Kimberley S. van Schooten,
  • Meghan Ambrens,
  • Mei Ling Lim,
  • Rachael Sung,
  • Michele L. Callisaya,
  • Jacqueline C. T. Close,
  • Kaarin J. Anstey,
  • Stephen R. Lord,
  • Kim Delbaere

摘要

Long-term adherence to exercise delivered through digital health interventions is critical but remains a major challenge, particularly among older people. We pooled intervention-arm data from two randomised controlled trials in 511 community-living older people who participated in a home-based digital balance exercise programme for 52 weeks. Weekly adherence was automatically recorded and expressed as percentage of prescribed dose. Group-based trajectory modelling identified distinct trajectories of adherence and multinomial adaptive lasso regression examined cognitive, physical, demographic and psychological predictors of trajectory group membership. Eight adherence trajectories emerged: overachievers (3.9%), consistent adherers (8.2%), fluctuating adherers (23.1%), intermittent adherers (15.9%), late attrition (11.4%), steady decliners (18.4%), early attrition (14.9%), and non-adherers (4.3%). On average, participants achieved 56% of their prescribed dose. Executive function and standing balance predicted adherence trajectory group membership. Poor executive function was associated with high initial adherence followed by a steep decline, while poorer balance was associated with more sustained adherence. Demographic or general health variables did not significantly predict adherence trajectories. Adherence to digital exercise is a dynamic behaviour, shaped by behavioural capability rather than by age or comorbidities. These findings inform the design of adaptive digital interventions to promote long-term adherence to digital programmes among older people.