Cervical flexor muscle training reduces pain, anxiety, and depression levels in patients with chronic neck pain by a clinically important amount: A prospective cohort study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Neck pain is the fourth leading cause of disability in the United States and exerts an important socio-economic burden around the world. The aims of this study were to determine the effectiveness of deep and superficial flexor muscle training in addition to home-based exercises in reducing chronic neck pain and anxiety/depression levels. METHODS: This was a prospective cohort study. Patients between 18 and 65 years old with chronic neck pain were eligible to participate if they had disability levels at least 5 out of 50 on the Neck Disability Index. Patients were divided into three groups: Group A received deep neck flexor and home-based exercises; Group B received superficial muscle and home-based exercises; and Group C received home-based exercises only. The Numeric Pain Rating Scale (NPRS), Neck Disability Index, and Hospital Anxiety and Depression Scale were administered at baseline and 7 weeks later. RESULTS: The highest improvements in pain intensity levels were observed in Group A with 4.75 (1.74) NPRS points, and the lowest were in Group C with 1.00 (1.10). The highest reductions in anxiety and depression levels were noted in Group A (2.80) and Group B (1.65), respectively. The highest improvements in pain intensity levels were observed among Groups A versus C with 2.80 (0.52) NPRS. The highest reductions in anxiety and depression levels were noted among Groups A versus C with 1.75 (1.10) points and Groups B versus C with 1.60 (0.90) points, respectively. CONCLUSIONS: Deep and superficial flexor muscle training along with home-based exercises is likely to reduce chronic neck pain and anxiety/depression levels by a clinically relevant amount. Future larger scaled randomized controlled trials are warranted to further support these findings.
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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 | 0.005 | 0.001 |
| 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".