Neck Muscle Endurance, Self-Report, and Range of Motion Data From Subjects With Treated and Untreated Neck Pain
Bibliographic record
Abstract
BACKGROUND: Despite the high prevalence and cost of neck-pain problems, there is currently little data available on the physical characteristics associated with different levels of neck pain. OBJECTIVE: To investigate associations between categories of response to neck pain/discomfort and (1) the endurance time of neck muscles, neck range of motion (ROM), and neck and head morphology, (2) sensitization or stretch effects arising from repeating end-of-range measurements, and (3) self-report data from neck pain and disability questionnaires. DESIGN: A cross-sectional study design. METHODS: Fifty-five Australian volunteers with and without neck pain, who were not taking time off work, were measured for neck muscle endurance, active neck ROM, craniocervical and thoracic posture, neck length, and head circumference and completed questionnaires about any neck pain/discomfort and disability. RESULTS: Twenty-two subjects reported a level of neck pain/discomfort that had required treatment (treated neck pain), a group of 17 subjects reported experiencing low-level neck pain/discomfort on a recurrent basis for which they had not sought treatment (untreated neck pain), whereas 16 subjects had no experience of neck pain or discomfort (no pain). Neck muscle endurance time was significantly lower for both pain groups. The affective dimension of the Short-Form McGill Pain Questionnaire and neck disability questionnaires were scored significantly higher by subjects who had sought treatment than by those in either of the untreated groups. Both pain groups showed a range decrease for most directions of neck motion at second measurement. CONCLUSIONS: Neck muscle endurance times, repeated end-ROM testing, the Short-Form McGill Pain Questionnaire, and disability questionnaires may distinguish between groups with untreated, treated, and no neck pain.
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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) | 0.000 | 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; 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".