A method for rapid assessment of visual ergonomics and lighting conditions (RAVEL): An in-depth development and psychometrics study.

Abstract

In workplaces heavily reliant on visual tasks, various factors can significantly influence an individual's performance, necessitating the use of reliable tools to identify and mitigate these factors. This study aimed to develop a swift assessment method for visual ergonomics and lighting conditions, evaluating its validity in real-world scenarios. The questionnaire's content validity was determined by a panel of experts using the content validity ratio (CVR) and content validity index (CVI). Construct validity was assessed through exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and latent class analysis (LCA). Internal consistency was measured using Cronbach's alpha coefficient. The RAVEL index, derived from the calculated effect coefficients of items, classified total scores through receiver operator curves (ROCs). The rapid assessment method, comprising two parts with 30 items, demonstrated acceptable reliability with CVR, CVI, and Cronbach's alpha coefficient (α) at 0.75, 0.87, and 0.896, respectively. The EFA on the first part's 22 items identified three factors, confirmed by CFA. The LCA on the second part's eight items revealed that a two-class model best fit the data, with Bayesian information criterion (BIC) = 24249, 17, Akaik information criterion (AIC) = 2179.89, and an entropy R-squared of 0.83, indicating appropriate subject classification based on the model. The RAVEL score was categorized into three levels, with optimal cut points of 55 and 63. In conclusion, the study demonstrated that this method based on visual ergonomics serves as a rapid and reliable tool for assessing visual ergonomic risks of display users in the workplace.