Consensus on the effects of exergames on fundamental movement skills in childhood: a systematic review and meta-analysis
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background Physical inactivity is a public health crisis that is influenced by practical barriers in childhood. We define a category of interventions that can reduce barriers, with exergames being one example. There is mixed evidence on fundamental movement skills effects, due to variability in experimental outcomes, that may be limiting usage. This meta-analysis of the source of variability determines the effect of exergames upon fundamental movement skills. Methods We surveyed 9 research databases (PubMed, APA PsycINFO, SPORTDiscus, IEEE Xplore, ACM Digital Library, Scopus, Proquest, Web of Science, ScienceDirect, and Google Scholar) to identify studies of the postintervention effects of exergames upon children’s fundamental movement skills, published between Jan 2010 and May 2024. Records were identified through boolean search terms and then manual reviews of abstracts and full text. Results In total, 17 statistically significant comparisons from 12 studies were identified. Comparisons between groups involved variance in coaching levels, activity structure levels, and whether the activity was an exergame or not. We used systematic hypothesis testing to explore all explanations for fundamental movement skills variability. All reported results were consistent with the hypothesis that variance in fundamental movement skills effects were due to variance in coaching or activity structure levels, rather than exergame status. There was no evidence of a differential effect for skill components. Conclusions Low-barrier exergames, as defined in our taxonomy of exergame types, are just as effective as traditional activity for fundamental movement skills adaptation. They should be freely chosen by teachers and parents, to overcome the practical challenges that are spiralling into physically inactive lifestyles. Future research should utilise our taxonomy and model of statistically significant effects to manage the methodological variability that makes building upon previous findings challenging.