Low Back Pain After Traffic Collisions
Bibliographic record
Abstract
STUDY DESIGN: A population-based, incidence cohort study was conducted. OBJECTIVE: To measure the incidence and prognosis for collision-related low back pain before and after a change in the insurance compensation system. SUMMARY OF BACKGROUND DATA: Low back pain is a common and costly occupational injury. It also occurs after traffic collisions, but less is known about its frequency and recovery in this setting. METHODS: An incidence cohort of 4473 low back pain injury claims was formed between July 1, 1994 and December 31, 1995 in Saskatchewan. On January 1, 1995 the public insurance system changed from a tort system to a no-fault system, eliminating compensation for pain and suffering. The incidence of claims and the time to claim closure were calculated before and after this change. Prognostic models were built using baseline and follow-up data. RESULTS: The 6-month incidence of claims decreased from 256 to 176 per 100,000 after the insurance change. The median time to claim closure dropped from 505 days for tort claims to 210 days and 216 days for claims made during the first and second 6 months of the no-fault period. Improvements in bodily pain and physical functioning and the absence of depressive symptoms were associated with faster claim closure. High pain intensity, female gender, full-time employment, concentration problems, and lawyer involvement early in the claim process delayed claim closure. CONCLUSIONS: Low back pain is a common traffic injury with a prolonged recovery. Its incidence and prognosis are affected by multiple factors, including the type of compensation system. Our study suggests that biopsychosocial factors are important in determining prognosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".