Comparative predictive validity of a psychological risk screening tool in adults after mild traumatic brain injury
Bibliographic record
Abstract
Objective To determine the comparative predictive validity of the Subgroups for Targeted Treatment modified for concussion (STarT-C) with full-length psychological measures (legacy questionnaires) in adults, six months after mild traumatic brain injury (mTBI).Materials and Methods Participants (n = 107) were recruited from outpatient concussion services in New Zealand and assessed on average 6 weeks (Time 1) and 6 months after mTBI (Time 2). The primary outcome was post-concussion symptoms at Time 2 measured with the Rivermead Post-concussion Symptoms Questionnaire (RPQ). Comparative predictive validity was determined by comparing the STarT-C at Time 1 with full-length legacy questionnaires that measured STarT-C constructs (distress, depression, fear avoidance, recovery expectations, catastrophizing) at Time 1.Results The STarT-C total score and psychosocial sub-score showed significant correlations with all psychological legacy questionnaires at Time 1 (r = ~0.3 to ~ 0.7). The STarT-C showed similar additional predictive value on symptoms at Time 2, as all legacy psychological questionnaires together (delta R2 = 8% vs. delta R2 = 8%).Conclusions The STarT-C showed comparable prognostic value for post-concussion symptom outcomes with a battery of psychological questionnaires. Further research should consider if stratified risk using STarT-C high, medium, and low sub-categories improves targeted treatment referral decision making by clinicians and mTBI outcomes.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".