Vandelanotte Corneel, Short Camille E, Plotnikoff Ronald C, Schoeppe Stephanie, Alley Stephanie J, To Quyen, Rebar Amanda L, Duncan Mitch J
Physical Activity Research Group, Appleton Institute, Central Queensland University, Rockhampton, QLD, Australia.
Melbourne Centre for Behaviour Change, Melbourne School of Psychological Science and Melbourne School of Health Science, University of Melbourne, Melbourne, VIC, Australia.
Front Digit Health. 2024 May 21;6:1356067. doi: 10.3389/fdgth.2024.1356067. eCollection 2024.
The relationship between intervention engagement and behaviour change may vary depending on the specific engagement metric being examined. To counter this composite engagement measures may provide a deeper understanding of the relationship between engagement and behaviour change, though few studies have applied such multidimensional engagement metrics. The aim of this secondary analysis of RCT data was to examine how a composite engagement score mediates the effect of a web-based computer-tailored physical activity intervention.
501 inactive Australian adults were randomised to a no-treatment control or intervention group. Intervention participants received 8 sessions of web-based personalised physical activity advice over a 12-week intervention period and the ability to complete action plans. Change in physical activity was assessed using Actigraph accelerometers at baseline, 3-months and 9-months. Engagement with the intervention (i.e., a composite score including frequency, intensity, duration and type) was continuously assessed during the intervention period using website tracking software and database metrics. Generalised structural equation models were used to examine how a composite engagement score mediated intervention effects at 3 months and 9 months.
At 3 months, mediation analysis revealed that the intervention group had significantly higher engagement scores than the control group [a-path exp(b) = 6.462, 95% CI = 5.121-7.804, < 0.001]. Further, increased engagement with the intervention platform was associated with an increased time spent in moderate-to-vigorous physical activity [ab-coefficient exp(b) = 1.008, 95% CI = 1.004-1.014, < 0.001]; however, the magnitude of this effect was small. There were no significant mediation effects at the 9-month time point.
The findings suggest that a composite intervention engagement score has a small positive influence on physical activity changes and that other factors (e.g., behaviour change techniques) are likely to be more important drivers of behaviour change.
干预参与度与行为改变之间的关系可能因所考察的具体参与度指标而异。为应对这一情况，综合参与度测量可能会更深入地理解参与度与行为改变之间的关系，不过很少有研究应用这种多维参与度指标。这项对随机对照试验（RCT）数据进行二次分析的目的是研究综合参与度得分如何介导基于网络的计算机定制体育活动干预的效果。
501名不活跃的澳大利亚成年人被随机分为无治疗对照组或干预组。干预组参与者在为期12周的干预期内接受8次基于网络的个性化体育活动建议，并能够完成行动计划。在基线、3个月和9个月时使用Actigraph加速度计评估体育活动的变化。在干预期内，使用网站跟踪软件和数据库指标持续评估对干预的参与度（即包括频率、强度、持续时间和类型的综合得分）。使用广义结构方程模型来研究综合参与度得分如何在3个月和9个月时介导干预效果。
在3个月时，中介分析显示干预组的参与度得分显著高于对照组[a路径指数(b)=6.462，95%置信区间=5.121-7.804，P<0.001]。此外，对干预平台的参与度增加与中等至剧烈体育活动的时间增加相关[ab系数指数(b)=1.008，95%置信区间=1.004-1.014，P<0.001]；然而，这种影响的程度较小。在9个月时间点没有显著的中介效应。
研究结果表明，综合干预参与度得分对体育活动变化有较小的积极影响，其他因素（如行为改变技术）可能是行为改变的更重要驱动因素。
