Factors Influencing Neck Pain Intensity in Whiplash-associated Disorders in Sweden
Bibliographic record
Abstract
OBJECTIVES: To investigate if sociodemographic and economic factors, preinjury health status, and collision factors are associated with initial neck pain intensity in whiplash-associated disorders (WAD) in Sweden. The factors of interest were demographic and socioeconomic factors, prior health, and collision factors. METHODS: A cohort study of car occupants, insured by either of 2 Swedish traffic insurers, age 18 to 74 years, who filed an injury claim and reported WAD after a motor vehicle collision (n=1187) were approached with mailed questionnaires. These contained questions about prior health, details about the collision, and symptoms after the collision. Neck pain intensity was measured on a visual analog scale and categorized into mild pain (0 to 30 mm), moderate pain (31 to 54 mm), and severe pain (55 to 100 mm). RESULTS: Low educational level [odds ratio (OR) 2.8; 95% confidence interval (CI) 1.8-4.5], being sole adult in the family (OR 1.6; 95%CI 1.1-2.2), prior neck pain (OR 2.9; 95%CI 1.4-6.2), prior headache (OR 2.2; 95%CI 0.7-6.9), prior poor general health (OR 2.6; 95%CI 1.4-4.8), and exposure to rollover collision (OR 1.9; 95%CI 1.0-3.8) were all associated with severe initial neck pain intensity. Most of these factors were also associated with moderate pain intensity. DISCUSSION: This study confirms results from a previous study that sociodemographic and economic status, preinjury health status, and collision-related factors are associated with participants' rating of initial neck pain intensity in WAD. The findings are of importance for interpreting and understanding the underlying factors of pain rating.
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 | 0.034 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".