Physical activity programs for cardiovascular outcomes in community wheelchair users: A systematic review

Abstract

Purpose: Physical inactivity is one of the important factors leading to chronic diseases including cardiovascular disease (CVD) in individuals with disabilities. However, not many Physical Activity (PA) interventions are available for improving the efficacy of PA and cardiovascular outcomes among community wheelchair users. Therefore, this systematic review will appraise the existing PA interventions for the community dwelling wheelchair users; we especially examined features of the PA programs that showed the improvements in PA and the CVD outcomes compared to the interventions that did not show any improvements in these outcomes among these population. The study also aimed to provide some recommendations for future research.

Materials and methods: A comprehensive and systematic search of literature published between 2015 and 2020 using the databases Scopus, Pubmed, Embase, and Cochrane CENTRAL was conducted. This review has followed the Preferred Reporting Items for Systematic Review (PRISMA) guidelines. The quality of the evidence was assessed by Using Joanna Briggs Institute's critical appraisal tool. Studies that tested the efficacy of PA interventions for community-dwelling adult wheelchair users and published in English were involved. Two reviewers reviewed the literature and any disagreements among these reviewers were resolved by a third reviewer.

Results: Fourteen articles were selected for this review. Most of the studies reported improvements in PA. A few studies followed up the participants and majority of the studies have looked at the CVD outcomes.

Conclusion: Large-scale studies with follow-ups, and community participatory research that evaluates the effect of PA interventions on PA and CVD outcomes among wheelchair users are needed.

Keywords: cardiovascular disease; community; physical activity; technology use; wheelchair users.

Figure 1

Show the data identification and stepwise data extraction including screening of the articles, removal of duplicates, and selection of the articles based on the inclusion and exclusion criteria.