Cross-sectional and Prospective Correlates of Recovery Expectancies in the Rehabilitation of Whiplash Injury
Bibliographic record
Abstract
OBJECTIVES: Investigations have shown that expectancies are significant prognostic indicators of recovery outcomes following whiplash injury. However, little is currently known about the determinants of recovery expectancies following whiplash injury. The purpose of the present study was to examine the cross-sectional and prospective correlates of recovery expectancies in individuals admitted to a rehabilitation program for whiplash injury. MATERIALS AND METHODS: Participants (N=96) completed measures of recovery expectancies, psychosocial variables, symptom severity, symptom duration, and disability at time 0 (admission) and time 1 (discharge). RESULTS: Consistent with previous research, more positive recovery expectancies at time 0 were related to reductions in pain at time 1 (r=-0.33, P<0.01). Scores on measures of pain catastrophizing, fear of movement and reinjury, and depression were significantly correlated with recovery expectancies. Pain severity, duration of work disability, and neck range of motion were not significantly correlated with recovery expectancies. Over the course of treatment, 40% of the sample showed moderate to large changes (an increase of ≥20%) in recovery expectancies, there were small changes (<20%) in 30% of the sample, and negative changes in 20% of the sample. A hierarchical regression showed that decreases in fear of movement and reinjury (β=-0.25, P<0.05) and pain catastrophizing (β=-0.23, P<0.05) were associated with increases in recovery expectancies through the course of treatment. CONCLUSIONS: The discussion addresses the processes linking pain-related psychosocial factors to recovery expectancies and makes recommendations for interventions that might be effective in increasing recovery expectancies.
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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 | 0.010 |
| 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 | 0.001 |
| 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".