The Effect of 8 Weeks of Corrective Exercises on Pain, Range of Motion, and Craniovertebral Angle in Migraine Patients with Forward Head: A Semi-Experimental Study
Bibliographic record
Abstract
Background and Objectives: Migraine is one of neurological disorders and is often associated with head and neck posture.Therefore, the aim of this study was to determine the effect of 8 weeks of corrective exercises on pain, range of motion, and the craniovertebral angle in migraine patients with forward head posture. Material and Methods:This quasi-experimental study with a pre-test/post-test design and a control group was conducted on 26 migraine patients with forward head posture in Yazd, Iran, in 2024.Participants were randomly divided into two groups included 12 in the exercise group and 14 in the control group.The exercise group performed 8 weeks of corrective exercises including strength and stretching exercises, while the control group continued their normal daily activities.Pain was measured using the McGill Pain Questionnaire, and range of motion was assessed using a goniometer.Data were analyzed using multivariate analysis of covariance (MANCOVA). Results:The results indicated that 8 weeks of corrective exercises significantly affected pain components in migraine patients with musculoskeletal neck abnormalities (p<0.001), with the greatest impact on pain perception, showing a 28.65% reduction.Additionally, these exercises significantly improved the rotational range of motion of the neck (p<0.001).The craniovertebral angle of the participants also showed a significant increase following the exercises (p<0.001).Conclusion: Correcting forward head posture and subsequently improving body posture can reduce pain and enhance the range of motion in the neck muscles of migraine patients.Therefore, it is recommended that corrective exercises for forward head posture be included in therapeutic interventions for migraine patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".