Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/3988
Title: Prediction model for return to work of injured workers in Hong Kong
Authors: Xu, Yanwen
Keywords: Hong Kong Polytechnic University -- Dissertations
Work capacity evaluation -- China -- Hong Kong
Workers' compensation -- China -- Hong Kong
Work -- Psychological aspects
Issue Date: 2005
Publisher: The Hong Kong Polytechnic University
Abstract: This study aims to formulate a prediction model of return to work for a group of workers who have been suffering from chronic pain and physical injury while also being out of work in Hong Kong. The results of the study will enable us to better understand the factors which might influence injured workers' resumption of a productive work role. The findings will also shed light on the development of relevant interventions and system for the return to work process of such workers. The participants were 67 (Mean age= 42.67) injured workers participated in a six-week return to work program which included training and placement. Assessments of the participants were conducted before they commenced the program (at the beginning of the 1st week), at the end of the program (end of the 3rd week), and at the end of the follow-up period (the 12th week post-program). The return-to-work outcomes were gathered in the last assessment. A total of 8 tests were administered covering physical, psychological, psychosocial, and vocational outcomes. Data on the demographic characteristics and work history of the participants were also obtained.
The return to work rate of the participants was 0% at the admission and 65.7% three months after the program. Significant differences were identified between those participants who were successful in the return to work process and those who were not. There were significantly more participants in the non return to work group (81.3%) who pursued civil claim against their employers, than in the return to work group (51.4%) (X²= 6.59, df= 1, p= 0.010). The participants in the return to work group were also found to have higher scores on the confidence in return to work (F(l,52)= 9.87, p= 0.003) and LASER Action subscale score (F(l,63)= 5.00, p= 0.025). When the variable "attorney involvement" was excluded from the analysis, participants' return to work outcomes were found to be significantly predicted by the readiness of return to work (action) (OR= 1.25) at the baseline. As the participants progressed in the program, their return to work was significantly predicted by their confidence in returning to work (OR= 1.41) and readiness of return to work (action) (OR=1.39). By the 3rd assessment, return-to-work outcomes were predicted by readiness of return to work (pre-contemplation) (OR= 0.75). The accuracy of the predictions ranged from 65.2% (at the baseline) to 78.0% (at 3rd week of the training program). The prediction model, however, was dominated by the variable "attorney involvement", when it was included as one of the predictor (OR= 0.23 to 0.27). Besides the conventional logistic regression method, case-based reasoning was used as the alternative method to develop the prediction model. The case-based reasoning algorithm was based on 14 variables. The usefulness of the algorithm was tested on 32 new participants, and the accuracy of predicting return to work outcomes was 62.5%. The combination of readiness of return to work, confidence, and attorney involvement appears to best predict medium-term return-to-work outcomes; that is, longer than 3 months. The findings further indicate that variables that are important for predicting return to work are likely to be confounded by the stages at which injured workers are assessed. The interventions in which the workers participate may also influence the results. As a result, these prediction models should be interpreted with caution. The results shed light on the development of return-to-work intervention programs and clinical pathways for injured workers. Further studies should focus on testing in detail the interaction effects between workers, interventions, and the environment.
Description: x, 126 leaves : ill. ; 30 cm.
PolyU Library Call No.: [THS] LG51 .H577M RS 2005 Xu
URI: http://hdl.handle.net/10397/3988
Rights: All rights reserved.
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