Trajectories of fear avoidance behavior and recovery after mild traumatic brain injury: Findings from the Toronto Concussion Study.
Bibliographic record
Abstract
OBJECTIVE: Fear avoidance behavior is associated with more severe postconcussion symptoms after mild traumatic brain injury (mTBI). However, it remains unclear when after injury fear avoidance behavior becomes a barrier to recovery. This study investigated changes in early fear avoidance behavior after mTBI and its associations with postconcussion symptoms. METHOD: = 216). RESULTS: Based on normative reference values, the two most common postconcussion trajectories of fear avoidance behavior were those with persistently low and those with initially elevated but decreasing fear avoidance behavior. Using linear regression, we found an interaction effect between fear avoidance behavior at Weeks 2 and 8, indicating that participants with persistently elevated fear avoidance behavior (at Weeks 2 and 8) had more severe postconcussion symptoms at Week 8, whereas participants with initially elevated but decreasing fear avoidance behavior tended to recover well. CONCLUSION: Early fear avoidance behavior often decreases, but when it does not, it is associated with worse recovery from mTBI. These findings may inform the timing and design of interventions targeting fear avoidance behavior in patients with mTBI. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".