Perceived injustice contributes to poor rehabilitation outcomes in individuals who have sustained workplace injuries
Bibliographic record
Abstract
The experience of unnecessary suffering as a result of another's actions or the experience of irreparable losses are likely to give rise to perceptions of injustice. Until recently, little systematic research had been conducted on the effects of perceptions of injustice on recovery outcomes following injury. It is now becoming clear that justice-related appraisals can have a dramatic impact on the physical and emotional consequences of injury. High levels of perceived injustice have been associated with more severe pain, more severe emotional distress, and more pronounced disability. Research has also pointed to multiple sources of a client's perceptions of injustice including, the person responsible for the accident, the insurance representative, as well as the health care provider. This presentation will summarize what is currently known about the relation between perceived injustice and recovery outcomes. The presentation will also address the processes by which perceptions of injustice might contribute to adverse health and mental health outcomes consequent to injury. Implications for prevention and intervention will be discussed.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".