Getting the most out of intensive longitudinal data: a methodological review of workload-injury studies
| Autor: | Clare L Ardern, Tim J. Gabbett, Bruno D. Zumbo, Ben C Sporer, Chad Cook, Karim M. Khan, Johann Windt |
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| Rok vydání: | 2018 |
| Předmět: |
Applied psychology
Poison control Workload Logistic regression 03 medical and health sciences 0302 clinical medicine Risk Factors Injury prevention Medicine Humans 030212 general & internal medicine Longitudinal Studies Prospective Studies Sports and Exercise Medicine workloads Prospective cohort study Uncategorized business.industry Proportional hazards model Research Human factors and ergonomics methodology 030229 sport sciences General Medicine training load Models Theoretical Systematic review Athletes Research Design statistics athletic injury Athletic Injuries business Physical Conditioning Human |
| Zdroj: | BMJ Open |
| ISSN: | 2044-6055 |
| Popis: | ObjectivesTo systematically identify and qualitatively review the statistical approaches used in prospective cohort studies of team sports that reported intensive longitudinal data (ILD) (>20 observations per athlete) and examined the relationship between athletic workloads and injuries. Since longitudinal research can be improved by aligning the (1) theoretical model, (2) temporal design and (3) statistical approach, we reviewed the statistical approaches used in these studies to evaluate how closely they aligned these three components.DesignMethodological review.MethodsAfter finding 6 systematic reviews and 1 consensus statement in our systematic search, we extracted 34 original prospective cohort studies of team sports that reported ILD (>20 observations per athlete) and examined the relationship between athletic workloads and injuries. Using Professor Linda Collins’ three-part framework of aligning the theoretical model, temporal design and statistical approach, we qualitatively assessed how well the statistical approaches aligned with the intensive longitudinal nature of the data, and with the underlying theoretical model. Finally, we discussed the implications of each statistical approach and provide recommendations for future research.ResultsStatistical methods such as correlations, t-tests and simple linear/logistic regression were commonly used. However, these methods did not adequately address the (1) themes of theoretical models underlying workloads and injury, nor the (2) temporal design challenges (ILD). Although time-to-event analyses (eg, Cox proportional hazards and frailty models) and multilevel modelling are better-suited for ILD, these were used in fewer than a 10% of the studies (n=3).ConclusionsRapidly accelerating availability of ILD is the norm in many fields of healthcare delivery and thus health research. These data present an opportunity to better address research questions, especially when appropriate statistical analyses are chosen. |
| Databáze: | OpenAIRE |
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