首页> 外文期刊>International Journal of Behavioral Nutrition and Physical Activity >Development of methods to objectively identify time spent using active and motorised modes of travel to work: how do self-reported measures compare?
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Development of methods to objectively identify time spent using active and motorised modes of travel to work: how do self-reported measures compare?

机译:开发方法来客观地确定使用主动和机动出行方式花费的时间:自我报告的措施如何比较?

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Background Active commuting may make an important contribution to population health. Accurate measures of these behaviours are required, but it is unknown how self-reported estimates compare to those derived from objective measures. We sought to develop methods for objectively deriving time spent in specific travel behaviours from a combination of locational and activity data, and to assess the convergent validity of two self-reported estimates. Methods In 2010 and 2011, a sub-sample of participants from the Commuting and Health in Cambridge study concurrently completed objective monitoring using combined heart rate and movement sensors and global positioning system devices and reported their past-week commuting in a questionnaire (modes used, and usual time spent walking and cycling per trip) and in a day-by-day diary (all modes and durations). Automated and manual approaches were used to objectively identify total time spent using active and motorised modes. Agreement between self-reported and objectively-derived times was assessed using Lin?s concordance coefficients, Bland-Altman plots and signed-rank tests. Results Compared to objective assessments, day-by-day diary estimates of time spent using active modes on the commute were overestimated by a mean of 1.1 minutes/trip (95% limits of agreement (LOA): ?7.7 to 9.9, p?
机译:背景主动通勤可能对人口健康做出重要贡献。需要对这些行为进行准确的测量,但是未知的是,自我报告的估算值与客观测量结果相比。我们试图开发一种方法,以从位置和活动数据的组合中客观得出在特定旅行行为中花费的时间,并评估两个自我报告的估算值的收敛性。方法在2010年和2011年,来自剑桥通勤与健康研究的参与者子样本同时完成了使用组合式心率和运动传感器以及全球定位系统设备的客观监测,并在问卷中报告了他们过去一周的通勤情况(使用的方式,和每次旅行花在步行和骑自行车上的通常时间)以及每天的日记(所有方式和时长)。使用自动和手动方法来客观地确定使用主动和电动模式花费的总时间。使用Lin的一致性系数,Bland-Altman图和有序秩检验来评估自我报告时间与客观得出时间之间的一致性。结果与客观评估相比,在通勤中使用活动模式的日常日记估计时间被平均高估了1.1分钟/行程(协议限制(LOA)的95%:? 7.7至9.9,p?< 0.001)。当单独使用步行或骑自行车时,高估的幅度稍大,但不显着(p = 0.247)(平均:2.4分钟/行程,95%LOA:6.8至11.5)。通勤所花费的总时间被平均高估了1.9分钟/行程(95%LOA:?15.3至19.0,p?<?0.001)。自我报告的平常时间与客观估计之间的平均差异是:骑行每分钟1.1分钟(95%LOA:8.7至6.4),步行每分钟+2.4分钟(95%LOA:10.9至15.7)。对于步行和骑自行车,通常的和每天的时间估计之间的平均差<1分钟/行程。结论我们开发了一种新颖的方法,可以结合目标数据来确定使用主动模式和机动模式所花费的时间以及通勤所花费的总时间。与客观得出的时间相比,主动报告通勤所花费的自我报告时间与较高的LOA略有高估,因此建议谨慎使用这些时间来推断个人上下班的每周活动总量。

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