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青年运动员身体特质纵向研究中的统计分析考虑因素:定性系统方法学综述。

Statistical analysis considerations within longitudinal studies of physical qualities in youth athletes: A qualitative systematic methodological review.

机构信息

Carnegie Applied Rugby Research (CARR) Centre, Leeds Beckett University, Carnegie School of Sport, Leeds, United Kingdom.

England Performance Unit, The Rugby Football League, Leeds, United Kingdom.

出版信息

PLoS One. 2022 Jul 7;17(7):e0270336. doi: 10.1371/journal.pone.0270336. eCollection 2022.

Abstract

BACKGROUND

The evaluation of physical qualities in talent identification and development systems is vital and commonplace in supporting youth athletes towards elite sport. However, the complex and dynamic development of physical qualities in addition to temporal challenges associated with the research design, such as unstructured data collection and missing data, requires appropriate statistical methods to be applied in research to optimise the understanding and knowledge of long-term physical development.

AIM

To collate and evaluate the application of methodological and statistical methods used in studies investigating the development of physical qualities within youth athletes.

METHODS

Electronic databases were systematically searched form the earliest record to June 2021 and reference lists were hand searched in accordance with the PRISMA guidelines. Studies were included if they tested physical qualities over a minimum of 3 timepoints, were observational in nature and used youth sporting populations.

RESULTS

Forty articles met the inclusion criteria. The statistical analysis methods applied were qualitatively assessed against the theoretical underpinnings (i.e. multidimensional development, non-linear change and between and within athlete change) and temporal challenges (i.e. time variant and invariant variables, missing data, treatment of time and repeated measures) encountered with longitudinal physical testing research. Multilevel models were implemented most frequently (50%) and the most appropriately used statistical analysis method when qualitatively compared against the longitudinal challenges. Independent groups ANOVA, MANOVA and X2 were also used, yet failed to address any of the challenges posed within longitudinal physical testing research.

CONCLUSIONS

This methodological review identified the statistical methods currently employed within longitudinal physical testing research and addressed the theoretical and temporal challenges faced in longitudinal physical testing research with varying success. The findings can be used to support the selection of statistical methods when evaluating the development of youth athletes through the consideration of the challenges presented.

摘要

背景

在人才选拔和发展体系中评估身体素质至关重要且很常见,这有助于支持青年运动员进入精英运动领域。然而,身体素质的复杂和动态发展,加上研究设计所带来的时间挑战,例如非结构化数据收集和缺失数据,要求应用适当的统计方法来优化对长期身体素质发展的理解和认识。

目的

整理和评估应用于研究青年运动员身体素质发展的方法学和统计方法的应用。

方法

根据 PRISMA 指南,系统地从最早的记录到 2021 年 6 月在电子数据库中进行搜索,并手动搜索参考文献列表。如果研究测试了至少 3 个时间点的身体素质,是观察性的,并且使用了青年运动人群,则纳入研究。

结果

有 40 篇文章符合纳入标准。应用的统计分析方法根据理论基础(即多维发展、非线性变化以及运动员之间和内部的变化)和遇到的时间挑战(即时变和不变变量、缺失数据、时间处理和重复测量)进行了定性评估。多层次模型应用最频繁(50%),并且在与纵向物理测试研究的挑战进行定性比较时,是最适当使用的统计分析方法。独立组 ANOVA、MANOVA 和 X2 也被使用,但未能解决纵向物理测试研究中提出的任何挑战。

结论

本方法学综述确定了当前在纵向物理测试研究中使用的统计方法,并在不同程度上解决了纵向物理测试研究中面临的理论和时间挑战。研究结果可以用于支持在评估青年运动员的发展时选择统计方法,考虑到所提出的挑战。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4835/9262234/d015e639206a/pone.0270336.g001.jpg

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