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A threshold regression model to predict return to work after traumatic limb injury.
Wen-Hsuan Hou1, Hung-Yi Chuang2, Mei-Ling Ting Lee3
1Master Program in Long-Term Care, College of Nursing, Taipei Medical University, Taipei, Taiwan; School of Gerontology Health Management, College of Nursing, Taipei Medical University, Taipei, Taiwan; Department of Physical Medicine and Rehabilitation, Taipei Medical University Hospital, Taipei, Taiwan.
Predictors of return-to-work (RTW) after traumatic limb injury were identified. Older age, lower limb injuries, and part-time work predicted slower recovery, while higher education accelerated RTW.
Area of Science:
- Occupational Health
- Rehabilitation Medicine
- Traumatology
Background:
- Traumatic limb injuries significantly impact a worker's ability to return to employment.
- Understanding predictors of return-to-work (RTW) is crucial for effective rehabilitation strategies.
Purpose of the Study:
- To examine the severity of initial impairment and recovery rate predictors for RTW in workers with traumatic limb injuries.
- To identify factors influencing the speed and likelihood of returning to work post-injury.
Main Methods:
- A 2-year prospective cohort study involving 1124 workers with traumatic limb injuries.
- Data collected via questionnaires and chart reviews at baseline and follow-up points (1-24 months).
- Threshold regression analysis used to estimate the impact of predictors on impairment and RTW recovery rates.
Main Results:
- 75.27% of participants returned to work.
- Elderly workers and those with lower limb injuries experienced greater initial impairment.
- Higher education, part-time employment, and higher self-efficacy were associated with less initial impairment.
- Older age, part-time jobs, lower limb, or combined injuries slowed recovery; higher education accelerated it.
Conclusions:
- Baseline impairment and recovery rates towards RTW are influenced by various demographic and injury-related factors.
- The findings offer evidence for clinicians and researchers to optimize RTW interventions for injured workers.
- Identifying specific predictors allows for tailored support to improve occupational rehabilitation outcomes.
