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

被引:3
作者
Owen, Cameron [1 ,2 ,3 ]
Till, Kevin [1 ,4 ]
Darrall-Jones, Josh [1 ]
Jones, Ben [1 ,2 ,4 ,5 ,6 ,7 ]
机构
[1] Leeds Beckett Univ, Carnegie Appl Rugby Res CARR Ctr, Carnegie Sch Sport, Leeds, England
[2] Rugby Football League, England Performance Unit, Leeds, England
[3] British Swimming, Loughborough, England
[4] Leeds Rhinos Rugby League Club, Leeds, England
[5] Univ New England, Sch Sci & Technol, Armidale, NSW, Australia
[6] Univ Cape Town, Fac Hlth Sci, Dept Human Biol, Div Exercise Sci & Sports Med, Cape Town, South Africa
[7] Sports Sci Inst South Afr, Cape Town, South Africa
来源
PLOS ONE | 2022年 / 17卷 / 07期
关键词
MODELING DEVELOPMENTAL-CHANGES; MULTIDIMENSIONAL PERFORMANCE-CHARACTERISTICS; REPEATED-SPRINT ABILITY; TALENT IDENTIFICATION; CAREER PROGRESSION; BETWEEN-PERSON; ELITE; PLAYERS; FITNESS; GROWTH;
D O I
10.1371/journal.pone.0270336
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
BackgroundThe 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. AimTo collate and evaluate the application of methodological and statistical methods used in studies investigating the development of physical qualities within youth athletes. MethodsElectronic 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. ResultsForty 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 X-2 were also used, yet failed to address any of the challenges posed within longitudinal physical testing research. ConclusionsThis 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.
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页数:28
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