Validation of the Rivermead Post-Concussion Symptoms Questionnaire (RPQ) on Patients Injured in High Impact Car Accidents
Bibliographic record
Abstract
Background:The Rivermead Post-Concussion Symptoms Questionnaire (RPQ) is used widely in clinical assessments.Its 16 items describe subjective neuropsychological symptoms.This study evaluates the criterion validity, convergent validity, and internal consistency of the RPQ in a sample of survivors of high impact motor vehicle accidents (MVAs).Method: De-identified data on 65 post-MVA patients (mean age 38.1 years, SD=13.1;24 men, 41 women) were available.Their data include scores on the Rivermead Post-Concussion Symptoms Questionnaire (RPQ), Subjective Neuropsychological Symptoms Scale (SNPSS), Insomnia Severity Index (ISI), Whetstone's and Steiner's measures of post-MVA driving anxiety, and the PCL-5 measure of PTSD.The data also included ratings of the worst pain, least pain, and of average pain (Items 3, 4, and 5 of the Brief Pain Inventory) and ratings of depression, anger, and of anxiety (Items 10 to 12 of the Whiplash Disability Questionnaire). Results:The patients' average RPQ score was 45.5 (SD=9.8)and that of the normal controls 8.3 (13.2): the effect size corresponds to point biserial coefficient of .84,thus indicating a very satisfactory criterion validity.The convergent validity is also satisfactory (r=.79 to the SNPSS).Cronbach alpha coefficient for the full 16 item RPQ was excellent (.97) and would not be improved by evaluating separately the first 3 RPQ items and the next 13 items. Discussion and Conclusions:We recommend that the RPQ be employed jointly with SNPSS in clinical assessments and research.The SNPSS includes important post-concussive symptoms missing in the RPQ as well as other subjective neuropsychological symptoms.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".