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没有一个基于加速度计的体力活动数据收集方案能够适用于所有的研究问题。

No one accelerometer-based physical activity data collection protocol can fit all research questions.

机构信息

Department of medicine and optometry, eHealth Institute, Linnaeus University, 39182, Kalmar, Sweden.

Karolinska Institutet, Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Alfred Nobels Allé 23, 141 83, Huddinge, Sweden.

出版信息

BMC Med Res Methodol. 2020 Jun 3;20(1):141. doi: 10.1186/s12874-020-01026-7.

Abstract

BACKGROUND

Measuring physical activity and sedentary behavior accurately remains a challenge. When describing the uncertainty of mean values or when making group comparisons, minimising Standard Error of the Mean (SEM) is important. The sample size and the number of repeated observations within each subject influence the size of the SEM. In this study we have investigated how different combinations of sample sizes and repeated observations influence the magnitude of the SEM.

METHODS

A convenience sample were asked to wear an accelerometer for 28 consecutive days. Based on the within and between subject variances the SEM for the different combinations of sample sizes and number of monitored days was calculated.

RESULTS

Fifty subjects (67% women, mean ± SD age 41 ± 19 years) were included. The analyses showed, independent of which intensity level of physical activity or how measurement protocol was designed, that the largest reductions in SEM was seen as the sample size were increased. The same magnitude in reductions to SEM was not seen for increasing the number of repeated measurement days within each subject.

CONCLUSION

The most effective way of reducing the SEM is to have a large sample size rather than a long observation period within each individual. Even though the importance of reducing the SEM to increase the power of detecting differences between groups is well-known it is seldom considered when developing appropriate protocols for accelerometer based research. Therefore the results presented herein serves to highlight this fact and have the potential to stimulate debate and challenge current best practice recommendations of accelerometer based physical activity research.

摘要

背景

准确测量身体活动和久坐行为仍然是一个挑战。在描述平均值的不确定性或进行组间比较时,最小化均数标准差(SEM)非常重要。样本量和每个受试者内重复观察的次数会影响 SEM 的大小。在这项研究中,我们研究了不同样本量和重复观察次数组合如何影响 SEM 的大小。

方法

我们邀请了一个方便的样本佩戴加速度计连续 28 天。基于个体内和个体间的方差,计算了不同样本量和监测天数组合的 SEM。

结果

共纳入 50 名受试者(67%为女性,平均年龄为 41±19 岁)。分析表明,无论身体活动的强度水平如何,或者如何设计测量方案,增加样本量都会显著降低 SEM。而增加每个受试者内重复测量天数对 SEM 的降低程度并不相同。

结论

降低 SEM 的最有效方法是增加样本量,而不是增加每个个体的观察期。尽管减少 SEM 以提高组间差异检测能力的重要性已经得到广泛认可,但在制定基于加速度计的研究的适当方案时,很少考虑到这一点。因此,本文的结果强调了这一事实,并有可能引发讨论和挑战当前基于加速度计的身体活动研究的最佳实践建议。

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