Normative Data for the Fear Avoidance Behavior After Traumatic Brain Injury Questionnaire in a Clinical Sample of Adults With Mild TBI
Bibliographic record
Abstract
OBJECTIVE: Fear avoidance behavior after a concussion or mild traumatic brain injury (mTBI) is associated with a number of adverse outcomes, such as higher symptom burden, emotional distress, and disability. The Fear Avoidance Behavior after Traumatic Brain Injury Questionnaire (FAB-TBI) is a recently developed and validated self-report measure of fear avoidance after mTBI. The objective of this study was to derive clinical normative data for the FAB-TBI. To determine whether demographic stratification was necessary and to further support clinical interpretation, we also explored associations between fear avoidance behavior and demographic and injury variables. SETTING: Five concussion clinics in Canada. PARTICIPANTS: Adults who sustained an mTBI (N = 563). DESIGN: Cross-sectional. MAIN MEASURES: Participants completed the Fear Avoidance Behavior after Traumatic Brain Injury Questionnaire (FAB-TBI) and measures of postconcussion symptom burden (Rivermead Postconcussion Symptoms Questionnaire, Sport Concussion Assessment Tool-5) at clinic intake. RESULTS: Generalized linear modeling revealed that females reported more fear avoidance than males (95% CI = 0.66 to 2.75), indicating that FAB-TBI normative data should be stratified by sex. Differences between recruitment sites on FAB-TBI scores were reduced but not eliminated by controlling for potential confounds. Loss of consciousness (95% CI =0.61 to 2.76) and higher postconcussion symptom burden (95% CI = 0.79 to 1.03) were also associated with higher FAB-TBI scores, but time since injury was not (95% = CI -0.4 to 0.03). Tables to convert FAB-TBI raw scores to Rasch scores to percentiles are presented. CONCLUSION: These findings support clinical interpretation of the FAB-TBI and further study of fear avoidance after mTBI.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".