Evaluating Effectiveness of Telerehabilitation Services Among Injured Workers Treated in a Canadian Workers’ Compensation System: A Population-Based Study
Bibliographic record
Abstract
Abstract Purpose To evaluate the effectiveness of telerehabilitation for promoting return-to-work (RTW) among injured workers. Methods We conducted a pragmatic, quasi-experimental study comparing telerehabilitation, in-person, or hybrid services. Descriptive statistics analyzed demographics, occupational factors, and patient-reported outcome measures (PROMs). ANOVAs and Kruskal-Wallis tests investigated differences between mode of delivery and changes in PROM scores. Logistic and Cox proportional hazard regression examined associations between mode of delivery and RTW status or days receiving wage replacement benefits in the first year post-discharge, respectively, while controlling for potential confounders. Results A slight majority of 3,708 worker sample were male (52.8%). Mean (standard deviation (SD)) age across all delivery formats was 45.5 (12.5) years. Edmonton zone had the highest amount of telerehabilitation delivery (53.5%). The majority of workers had their program delivered in a hybrid format (54.1%) and returned to work (74.4%) at discharge. All PROMs showed improvement although differences across delivery formats were not clinically meaningful. Delivery via telerehabilitation had significantly lower odds of RTW at discharge (Odds Ratio: 0.82, 95% Confidence Interval: 0.70–0.97) and a significantly lower risk of experiencing suspension of wage replacement benefits in the first year following discharge (Hazard Ratio: 0.92, 95% Confidence Interval: 0.84–0.99). Associations were no longer significant when confounders were controlled for. Conclusion RTW outcomes were not statistically different across delivery formats, suggesting that telerehabilitation is a novel strategy that may improve equitable access and earlier engagement in occupational rehabilitation. Factors such as gender and geographic location should be considered when deciding on service delivery format.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".