我们从体力活动研究中排除了谁? 检查步计数据处理中排除偏差的可能性
Melody Smith1, Alana Cavadino2, Anantha Narayanan1,3
1School of Nursing, The University of Auckland, Auckland, New Zealand.
Journal of physical activity & health
|February 6, 2025
概括
对于计步器身体活动 (PA) 研究而言,更严格的数据清理显著减少了参与者数量,并引入了偏差. 研究人员必须明确报告PA数据清理方法,以确保研究有效性.
科学领域:
- 测量身体活动的测量.
- 生物统计学 生物统计学
- 公共卫生研究 公共卫生研究
背景情况:
- 步行计衍生体力活动 (PA) 数据被广泛使用,但由于数据清理标准的不同,可能包含系统偏差.
- 不同的纳入标准对样本大小和社会人口统计学代表性在步数计研究中的影响仍然不清楚.
研究的目的:
- 为了探索现有的计步器数据清理标准.
- 根据社会人口统计学因素,研究不同的纳入标准如何影响样本大小的保留和参与者排除.
主要方法:
- 分析了来自新西兰的社区调查的数据.
- 参与者穿着Yamax CW300计步器7天,通过调查收集的社会人口统计数据.
- 分析包括异常值的删除,每天最低步骤的确定,第一天数据删除评估和偏差风险评估.
主要成果:
- 从895名参与者获得了计步器数据,每天设置100步作为有效的一天门.
- 增加纳入标准的严格性导致参与者保留率降低,偏见增加.
- 排斥偏差较低的模型证明了收性和并发性有效性.
结论:
- 更严格的计步器数据纳入标准可能会导致实质性的,偏见的样本大小减少.
- 对数据清理方法及其潜在偏差的透明报告对于基于步数计的身体活动研究至关重要.
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