A population‐based survey of beliefs about neck pain from whiplash injury, work‐related neck pain, and work‐related upper extremity pain
Bibliographic record
Abstract
BACKGROUND: Beliefs about pain conditions appear to influence recovery in a variety of musculoskeletal conditions. Little is known about population beliefs about neck and arm pain. AIMS: To evaluate population beliefs of three common musculoskeletal conditions: work-related neck and arm pain and whiplash injury (WAD). METHODS: Mail-out surveys were delivered to 2000 adult residents of two Canadian provinces cross-sectionally. To evaluate beliefs about the three conditions, the back beliefs questionnaire was modified yielding three comparable 10-item measures. In addition, we inquired about the belief about how quickly the condition settles. Respondents indicated their level of agreement on a 5-point Likert scale with lower scores interpreted as negative or pessimistic. Overall and item specific descriptive statistics are reported. A one-way repeated measures ANOVA was performed to compare beliefs across conditions. RESULTS: Three hundred (15%) surveys were returned. Overall belief scores were different across conditions (p<0.001). Post-hoc tests revealed beliefs about whiplash injury were more negative compared to the other conditions (p<0.017). There were moderate levels of uncertainty in the responses, especially in regard to whiplash injury. For items related to active coping, over 55% of respondents agreed that remaining active and exercising was important. The sample was pessimistic in regard to recovery and resuming usual activities for all conditions, but more so in the case of WAD. CONCLUSIONS: Population beliefs related to neck pain, arm pain, and WAD in the two Canadian provinces sampled were consistent with the literature in regard to remaining active, but appeared misinformed relating to the prognosis of these conditions. Strategies for reeducating the public are indicated.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".