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OBJECTIVE: Road accidents cause millions of deaths and disabilities globally, especially among pedestrians who are more vulnerable. Effective measures are needed to protect them, and this study focuses on identifying interventions to improve pedestrian visibility in traffic injuries. METHODS: This systematic review followed PRISMA guidelines and used search terms related to injury, pedestrian, visibility, and study design. Searches were conducted in databases like PubMed, ScienceDirect, Web of Science, Scopus, SAGE journals, and Cochrane Library until March 2024. Studies included were in English, peer-reviewed, and focused on pedestrians of all ages. Various experimental and quasi-experimental studies were considered. Interventions aimed at improving pedestrian visibility to prevent traffic injuries were classified into five categories. The quality of selected articles was assessed for potential biases using JBI checklists. RESULTS: Initially, 5,144 abstracts were identified. After applying exclusion criteria, 5,028 were removed, leaving 116 abstracts for review. Out of these, 21 were selected for full-text review. Finally, nine studies were chosen for further evaluation. These studies included one randomized controlled trial, six quasi-experimental studies, and two pretest/post-test interventions. Follow-up periods varied from immediate to one year, and outcomes were primarily measured by observation in eight studies. The interventions employed included educational/behavioral, technological, and multifaceted approaches, all of which significantly improved outcomes over the duration of the studies. All studies were conducted in high-income countries. The quality of the studies varied, with two studies rated as strong quality, six as medium quality, and one as weak quality. CONCLUSIONS: The study emphasizes the importance of visibility-enhancing measures for reducing pedestrian injuries but identifies shortcomings in study design, theoretical frameworks, and generalizability. It suggests future research should adopt robust methods, incorporate validated models, and evaluate legal and community-specific factors to create more effective safety measures.
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Sarvi et al. (2025) studied this question.
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