We aimed to ascertain the relationship between several factors and successful return to work using a structural equation model.

We used original data from the Panel Study of Worker’s Compensation Insurance, and defined four latent variables as occupational, individual, supportive, and successful return to work. Each latent variable was defined by its observed variables, including age, workplace size, and quality of the medical services. A theoretical model in which all latent variables had a relationship was suggested. After examining the model, we modified some pathways that were not significant or did not fit, and selected a final structural equation model that had the highest goodness of fit.

All three latent variables (occupational, individual, and supportive) showed statistically significant relationships with successful return to work. The occupational and supportive factors had relationships with each other, but there was no relationship between individual and the other factors. Nearly all observed variables had significance with their latent variables. The correlation coefficients from the latent variables to successful return to work were statistically significant and the indices for goodness of fit were satisfactory. In particular, four observed variables—handicap level, duration of convalescence, working duration, and support from the company—showed construct validities with high correlation coefficients.

All factors that we examined are related to successful return to work. We should focus on the supportive factor the most because its variables are modifiable to promote a return to work by those injured in their workplace.