Interview Versus Questionnaire Symptom Reporting in People With the Postconcussion Syndrome
Bibliographic record
Abstract
OBJECTIVE: To compare spontaneous, interview-based, postconcussion symptom reporting to endorsement of symptoms on a standardized questionnaire. PARTICIPANTS: Sixty-one patients referred to a concussion clinic following mild traumatic brain injury. PROCEDURE: Patients recalled their current symptoms and problems via open-ended interview and then completed a structured postconcussion checklist. MAIN OUTCOME MEASURES: Open-ended interview and the British Columbia Postconcussion Symptom Inventory (BC-PSI). RESULTS: On average, patients endorsed 3.3 symptoms (SD = 1.9) during open-ended interview and 9.1 symptoms (SD = 3.2) on the BC-PSI (P < .001). Approximately 44% endorsed 4 or more symptoms during interview compared with 92% on the BC-PSI. The percentage of patients endorsing items on the BC-PSI compared with interview was significantly greater on all 13 items. It was common for patients to endorse symptoms as moderate-severe on the BC-PSI, despite not spontaneously reporting those symptoms during the interview. CONCLUSIONS: Clinicians need to be cautious when interpreting questionnaires and be aware of the possibility of nonspecific symptom endorsement, symptom overendorsement, symptom expectations influencing symptom endorsement, and the nocebo effect.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".