Multiple psychiatric diagnoses and return-to-work following posttraumatic stress injury rehabilitation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Posttraumatic stress injury (PTSI) is a term used to describe a range of psychiatric difficulties which arise following exposure to a psychologically traumatic event. The impact of being diagnosed with multiple psychiatric conditions on the return-to-work (RTW) outcomes of individuals with PTSI has not been adequately researched. OBJECTIVE: The current study examined whether the presence of two or more psychiatric conditions occurring simultaneously is predictive of RTW outcomes in workers with PTSI. METHOD: A population-based cohort design was conducted using archival data from injured workers admitted to a PTSI rehabilitation program. Differences in RTW outcomes and demographic, administrative, and clinical variables were compared between individuals with single and multiple psychiatric diagnoses. A range of variables were entered into a multivariable logistic regression model predicting RTW. RESULTS: The final logistic regression model indicated workers had higher odds of RTW if they had a single psychiatric diagnosis (Adjusted Odds Ratio (AOR) 2.20), non-elevated scores on a measure of traumatic stress (AOR 1.85), and reported higher self-perceived readiness to RTW (AOR 1.24). CONCLUSION: Being diagnosed with multiple psychiatric conditions appears to be associated with more negative RTW outcomes following PTSI rehabilitation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it