Relationships Between Cervical Range of Motion, Self-Rated Disability and Fear of Movement Beliefs in Chronic Neck Pain Patients
Bibliographic record
Abstract
ObjectivesTo investigate the relationship between impairment [cervical ranges of motion [CROMs]], self-reported disability, and fear of movement beliefs in chronic neck pain patients.MethodsData was obtained from a convenience sample of chronic neck pain patients in private clinics. CROMs were obtained using a CROM device, self-rated disability was measured using the neck disability index [NDI], and fear of movement beliefs was measured using the Tampa Scale for Kinesiophobia [TSK]. Age, gender, and duration of neck pain were also obtained. Bivariate and multivariate statistics were employed.ResultsThirty-five participants with a mean age of 42.3 years and neck pain duration of 4.75 [4.61] years completed the study. The average scores for the outcome measures were: NDI = 26 percent, TSK = 51 percent, and total CROM = 288 degrees. The NDI correlated with the TSK at 0.50 [P = 0.006]. The correlation between the NDI and total ROM was −0.58 [P = 0.0003] while the correlation between total ROM and the TSK just failed to reach significance [−0.32; P = 0.06]. In the multivariate analysis, only the NDI loaded significantly onto the total ROM and explained 29 percent of the variance of ROM on its own.ConclusionIn this study, self-rated disability in chronic neck pain patients was found to correlate with fear-avoidance beliefs and with a measure of impairment – ranges of motion in the cervical spine. When evaluating reductions in ranges of cervical motion in chronic neck pain patients, the effect of their self-ratings of disability should be considered.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".