Group differences in outcomes of a personalised digital physical activity program designed for chronic conditions

Background:
There is international consensus that the benefits of increasing physical activity (PA) outweigh the risks for individuals living with the most common and serious long term health conditions, including diabetes, cardiovascular disease, cancer, obesity, and depression. Exercise Intelligence (EXI) is a medically validated, evidence-based digital platform that provides automated, individualized, progressive PA programs, based on users’ unique combination of health conditions, PA history and current fitness levels. EXI incorporates behavioural science to support insufficiently active users to overcome barriers to achieving recommended PA levels.
Purpose:
Assess differences in the effectiveness of EXI for increasing PA in real world settings according to: baseline activity levels, use of a wearable activity tracker vs. no wearable, and independent vs. care pathway user.
Methods:
Retrospective analysis of routinely collected PA data from EXI users. Repeated measures analysis of variance was employed to assess and compare change over time in user sub-groups.
Results:
When users were split by week 1 activity level, after 16 weeks, weekly activity minutes increased by 1922% (190 mins) in the first quartile (lowest activity), by 369% (143 mins) in the second quartile, and by 97% (96 mins) in the third quartile (N=334). A similar pattern was seen in weekly steps increases. Adherence to the PA prescription (N=1,172) and weekly steps (N=2,439) were significantly higher in users with wearable devices compared to users without, at 16 weeks. Users who joined EXI via a healthcare professional or program had consistently higher adherence compared to those who joined independently.
Conclusions:
EXI appears to be highly effective for individuals with very low PA levels, enabling the achievement of recommended PA levels in 16 weeks.
Practical implications:
Digital personalised PA programs should be integrated into care pathways, combined with wearable activity trackers and targeted towards populations with the lowest PA levels.
Funding:
None