Role of Bio-Psychosocial factors in return to work following a compensable knee injury
Bibliographic record
Abstract
Objectives The purpose of this study was to examine the relationship between work status and biomedical factors, psychosocial factors, occupational factors, physical disability, and barriers to full recovery.Methods This study was a cross sectional evaluation of workers with an active compensation claim following a work-related injury to the knee joint.Results Data of 60 consecutive injured workers, mean age, 47 ± 14, 40 (67%) males were used for analysis. Thirty-one (52%) patients were unable to work and 29 (48%) patients were working at the time of assessment. Patient’s age, gender, range of motion, and strength did not have a direct relationship with work status (p > 0.05). Obesity had a negative impact on work status (p = 0.035). Depression (p = 0.001), anxiety (p = 0.002), and the fear avoidance of the Optimal Screening for Prediction of Referral and Outcome (OSPRO-YF) scale (p = 0.019) showed higher levels of psychosocial issues in the non-working sample. Patients with 3 or more barriers (p = 0.020) and higher disability score (p = 0.004) showed an inferior work status.Discussion Presence of obesity, depression, anxiety, fear-related beliefs, higher reported disability, and accumulative number of barriers are indicative of poorer recovery and a less successful RTW after an occupational knee injury.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".