Do current vocational evaluation practices in traumatic brain injury align with best practices? Strengths, challenges and recommendations
Bibliographic record
Abstract
Introduction To support implementation of the Inter-professional Guideline for Vocational Evaluation Following Traumatic Brain Injury we compared current practices to best practices as outlined in the guideline. Method We recruited health/vocational professionals who do vocational evaluation of traumatic brain injury survivors to participate in qualitative semi-structured interviews. We also conducted a document review of internal clinical and provincial workers’ compensation insurance documents. All data were analyzed using directed content analysis. Results Thirteen individuals participated and three types of documents were reviewed. Practices that were found to be frequently aligned with the Inter-professional Guideline for Vocational Evaluation Following Traumatic Brain Injury included: (a) identification of evaluation purpose; (b) obtaining informed consent; (c) gathering background information; (d) assessing persistent symptoms and abilities; (e) analyzing and synthesizing results; and (f) developing return to work recommendations. Practices partially aligned included: (a) incorporating the worker’s perspectives into the evaluation; (b) observing work behaviors in naturalistic settings (c) assessing available supports; and (d) assessing occupational/job demands in context. Practices that did not align with the guideline included: (a) evaluation of the workplace environment and workplace supports; (b) accommodation potential; and (c) assessment of workplace safety. Conclusion To support implementation of the guideline and enhance successful vocational outcomes, additional attention and resources should be dedicated to evaluating workplace-based factors and assessing workplace-based risks.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".