Course and Prognostic Factors for Neck Pain in the General Population
Bibliographic record
Abstract
STUDY DESIGN: Best evidence synthesis. OBJECTIVE: To undertake a best evidence synthesis on course and prognosis of neck pain and its associated disorders in the general population. SUMMARY OF BACKGROUND DATA: Knowing the course of neck pain guides expectations for recovery. Identifying prognostic factors assists in planning public policies, formulating interventions, and promoting lifestyle changes to decrease the burden of neck pain. METHODS: The Bone and Joint Decade 2000-2010 Task Force on Neck Pain and its Associated Disorders (Neck Pain Task Force) conducted a critical review of literature published between 1980 and 2006 to assemble the best evidence on neck pain. Findings from studies meeting criteria for scientific validity were abstracted into evidence tables and included in a best evidence synthesis. RESULTS: We found 226 articles on the course and prognostic factors in neck pain and its associated disorders. After critical review, 70 (31%) of these were accepted on scientific merit. Six studies related to course and 7 to prognostic factors in the general population. Between half and three quarters of persons in these populations with current neck pain will report neck pain again 1 to 5 years later. Younger age predicted better outcome. General exercise was unassociated with outcome, although regular bicycling predicted poor outcome in 1 study. Psychosocial factors, including psychologic health, coping patterns, and need to socialize, were the strongest prognostic factors. Several potential prognostic factors have not been well studied, including degenerative changes, genetic factors, and compensation policies. CONCLUSION: The Neck Pain Task Force undertook a best evidence synthesis to establish a baseline of the current best evidence on the course and prognosis for this symptom. General exercise was not prognostic of better outcome; however, several psychosocial factors were prognostic of outcome.
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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 | 0.030 | 0.138 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".