Frequency, Timing, and Course of Depressive Symptomatology After Whiplash
Bibliographic record
Abstract
In Brief Study Design. Population-based incidence cohort. Objective. To report the incidence, timing, and course of depressive symptoms after whiplash. Summary of Background Data. Evidence is conflicting about the frequency, time of onset, and course of depressive symptoms after whiplash. Methods. Adults making an insurance claim or seeking health care for traffic-related whiplash were followed by telephone interview at 6 weeks, and 3, 6, 9, and 12 months post-injury. Depressive symptoms were assessed at baseline and at each follow-up. Results. Of the 5,211 subjects reporting no pre-injury mental health problems, 42.3% (95% confidence interval, 40.9–43.6) developed depressive symptoms within 6 weeks of the injury, with subsequent onset in 17.8% (95% confidence interval, 16.5–19.2). Depressive symptoms were recurrent or persistent in 37.6% of those with early post-injury onset. Pre-injury mental health problems increased the risk of later onset depressive symptoms and of a recurrent or persistent course of early onset depressive symptoms. Conclusions. Depressive symptomatology after whiplash is common, occurs early after the injury, and is often persistent or recurrent. This suggests that, like neck pain and headache, depressed symptomatology is part of the cluster of acute whiplash symptoms. Clinicians should be aware of both physical and psychologic injuries after traffic collisions. Depressive symptoms are common after whiplash, with the majority of cases occurring within the first 6 weeks after the injury. Of those with early onset depressive symptoms, almost 38% experience persistent or recurrent symptoms. Pre-injury mental health problems increase the risk that early onset depressive symptoms will fail to resolve.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".