Return to work following total knee arthroplasty: A multiple case study of stakeholder perspectives
Bibliographic record
Abstract
Objective: The study’s aim was to gain insights into factors influencing sustainable return to work following total knee arthroplasty (TKA). Design: A descriptive multiple-case design was used. A case was defined as a worker’s following TKA work disability situation. Settings: The cases came from public hospitals in urban and semi-urban areas in Quebec (Canada) and involved mostly non-work-related TKAs. Subjects: Workers had to be between 6 and 12 months post-TKA, have physical/manual jobs and currently employed. Their rehabilitation professionals and workplace representatives (employer and/or union) were also recruited, based on the work disability paradigm. Main measures: Semi-structured interviews, questionnaires on pain, physical work demands (workers only), and observation of the work activities of those workers back at work were used. Cases were compared and categorized for worker-perceived levels of difficulty in returning to or staying at work: little or no difficulty ( n = 8); some difficulty ( n = 5); not back at work due to excessive difficulty with their knee ( n = 4). Results: A total of 17 cases were constituted. In only one case, the worker benefitted from an interdisciplinary work rehabilitation approach. Results highlight the interplay among these factors: (1) the workers’ perceptions of their residual symptoms and ability to manage them, (2) the interaction between work adjustments and tools offered by the employers and the workers’ own strategies, and (3) perceptions of the workers’ physical capacities. Conclusion: Workers’ who face high levels of work demands/difficulties and who have limited access to work adjustments and tools should be referred for work rehabilitation.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".