Kim, SunwookOjelade, AanuoluwapoMoore, AlbertGutierrez, NancyHarris-Adamson, CarisaBarr, AlanSrinivasan, DivyaRempel, David M.Nussbaum, Maury A.2024-01-222024-01-222023-12-120014-0139https://hdl.handle.net/10919/117499Work-related musculoskeletal disorders (WMSDs) are a major health concern in the construction industry. Occupational exoskeletons (EXOs) are a promising ergonomic intervention to help reduce WMSD risk. Their adoption, however, has been low in construction. To understand the contributing factors to EXO use-intention and assist in future decision-making, we built decision trees to predict responses to each of three EXO use-intention questions (Try, Voluntary Use, and Behavioral Intention), using online survey responses. Variable selection and hyperparameter tuning were used respectively to reduce the number of potential predictors and improve prediction performance. The importance of variables in each final tree was calculated to understand which variables had a greater influence. The final trees had moderate prediction performance. The root node of each tree included EXOs becoming standard equipment, fatigue reduction, or performance increase. Important variables were found to be quite specific to different decision trees. Practical implications of the findings are discussed.Pages 1-22application/pdfenIn CopyrightExoskeleton acceptancedecision makingergonomic interventionimplementationworkplace injuriesArticle - Refereedhttps://doi.org/10.1080/00140139.2023.2289859Nussbaum, Maury [0000-0002-1887-8431]Ojelade, Aanuoluwapo [0000-0001-9715-3254]Kim, Sun Wook [0000-0003-3624-1781]380856901366-5847