Effectiveness of a smartphone app in increasing physical activity amongst male adults: a randomised controlled trial.
Effectiveness of a smartphone app in increasing physical activity amongst male adults: a randomised controlled trial.
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DOI：
10.1186/s12889-016-3593-9
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发表时间：
2016-09-02
影响因子：
4.5
通讯作者：
van Woerden HC
中科院分区：
文献类型：
--
作者：
Harries T;Eslambolchilar P;Rettie R;Stride C;Walton S;van Woerden HC
对于缺乏内在锻炼动机的人来说，智能手机是促进身体活动的理想选择。这项研究测试了三个假设：H1——收到社会反馈比没有收到反馈产生更高的步数； H2 – 接收社会反馈比仅接收自己行走的反馈产生更高的步数； H3 – 收到自己步行的反馈会比没有反馈产生更高的步数 (H3)。一项平行组随机对照试验测量了反馈对步数的影响。年龄在 18-40 岁的健康男性参与者 (n = 165) 获得预装应用程序的手机，该应用程序可以连续记录步数，无需用户激活。参与者随身携带这些手机作为主要手机，进行两周的磨合和六周的试用。随机分为三组：无反馈（对照）；关于步数的个人反馈；小组反馈将步数与小组中其他人的步数进行比较。使用纵向多级回归分析评估主要结果指标，即每天的步数。控制变量包括对身体活动的态度和对身体活动的感知障碍。每组有 55 名参与者； 152人完成研究并纳入分析：n = 49，无反馈； n = 53，个人反馈； n = 50，个人和社会反馈。该研究为 H1 和 H3 提供了支持，但没有为 H2 提供支持。收到任何一种形式的反馈都可以解释 7.7% 的受试者间步数差异（F = 6.626，p < 0.0005）。与对照组相比，个人反馈组的预期步数高出 60%（对步数日志的影响 = 0.474，95% CI = 0.166–0.782），而社交反馈组的预期步数高 69%（对步数日志的影响 = 0.526，95% CI = 0.212–0.840）。两个反馈组（个人反馈与社会反馈）之间的差异不具有统计学意义。提供步数统计的始终在线智能手机应用程序可以增加年轻至中年男性的身体活动，但提供社交反馈并没有明显的增量影响。这种方法可能特别适合体力活动水平较低、不爱运动的人；现在应该对该人群进行测试。
Smartphones are ideal for promoting physical activity in those with little intrinsic motivation for exercise. This study tested three hypotheses: H1 – receipt of social feedback generates higher step-counts than receipt of no feedback; H2 – receipt of social feedback generates higher step-counts than only receiving feedback on one’s own walking; H3 – receipt of feedback on one’s own walking generates higher step-counts than no feedback (H3). A parallel group randomised controlled trial measured the impact of feedback on steps-counts. Healthy male participants (n = 165) aged 18–40 were given phones pre-installed with an app that recorded steps continuously, without the need for user activation. Participants carried these with them as their main phones for a two-week run-in and six-week trial. Randomisation was to three groups: no feedback (control); personal feedback on step-counts; group feedback comparing step-counts against those taken by others in their group. The primary outcome measure, steps per day, was assessed using longitudinal multilevel regression analysis. Control variables included attitude to physical activity and perceived barriers to physical activity. Fifty-five participants were allocated to each group; 152 completed the study and were included in the analysis: n = 49, no feedback; n = 53, individual feedback; n = 50, individual and social feedback. The study provided support for H1 and H3 but not H2. Receipt of either form of feedback explained 7.7 % of between-subject variability in step-count (F = 6.626, p < 0.0005). Compared to the control, the expected step-count for the individual feedback group was 60 % higher (effect on log step-count = 0.474, 95 % CI = 0.166–0.782) and that for the social feedback group, 69 % higher (effect on log step-count = 0.526, 95 % CI = 0.212–0.840). The difference between the two feedback groups (individual vs social feedback) was not statistically significant. Always-on smartphone apps that provide step-counts can increase physical activity in young to early-middle-aged men but the provision of social feedback has no apparent incremental impact. This approach may be particularly suitable for inactive people with low levels of physical activity; it should now be tested with this population.