Perception of Recovery After Pediatric Mild Traumatic Brain Injury Is Influenced by the "Good Old Days" Bias: Tangible Implications for Clinical Practice and Outcomes Research
Bibliographic record
Abstract
Recovery from mild traumatic brain injury (mTBI) is primarily based on the resolution of post-concussive symptoms back to a premorbid level. However, the "good old days" bias means fewer premorbid symptoms are retrospectively recalled, thus skewing the determination of recovery relative to pre-injury. The objectives of this study were to investigate the "good old days" bias in pediatric mTBI and demonstrate the implications of this bias on perceived recovery. Children and adolescents 2-18 years old (mean = 10.9, SD = 4.4, N = 412) were recruited after sustaining an mTBI. Ratings of premorbid symptoms were provided: (a) in the Emergency Department (ED; by parents), (b) retrospectively at a 1-month follow-up (by parents and adolescents), and (c) retrospectively at a 3-month follow-up (by parents and adolescents). Parent ratings of premorbid symptoms decreased by 80% from the ED to 1-month post-injury (p < .001) but were stable from 1 to 3 months post-injury (p < .05). Adolescents premorbid ratings declined from 1 to 3 months post-injury. Slow recovery did not have a differential impact on premorbid reporting. Using premorbid ratings obtained in the ED, instead of retrospective symptom reporting at the time of follow-up, suggests that a significant minority of patients believed to be "not recovered" actually have the "same or lower" symptom ratings at 1 (29%) and 3 months (41%) post-injury compared with before the injury. The "good old days" bias is present in pediatric mTBI by 1-month post-injury, influences retrospective symptom reporting, and has measureable implications for determining recovery in research and clinical practice.
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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 | 0.013 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 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".