Effectiveness of Manual Therapy on Function in Neck Pain Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Neck pain is a musculoskeletal disorder that occurs in the neck due to various factors such as incorrect ergonomic position when carrying out an activity. One intervention that can be carried out to improve the function of neck pain sufferers is by providing manual therapy. This study aims to determine the effectiveness of manual therapy for functional use in patients with neck pain. Subjects and Method: This was a meta-analysis study using PICO as follows, P=Patients with neck pain, I=manual therapy, C=non-manual therapy, O=functional improvement. The articles used in this research were obtained from several databases such as Google Scholar, NCBI, PubMed, Springer Link, Science Direct. The keywords used are "Randomized control trial" AND "neck pain" OR "cervical pain" OR "Cervicalgia" Upper cervical pain" AND "manual therapy" OR "Manipulation treatment" OR "thoracic manipulation in neck pain" OR "Cervical spine manipulation” OR “Passive therapy” OR “Ostheopathic” OR “neck pain rehabilitation” AND “Disability” OR “Functional” OR “Neck pain disability index”. The articles included in this research are full text articles with the study design used being a Randomized Controlled Trial. The full text review application uses PRISMA flow diagrams. Results: A total of 8 articles that have been analyzed come from Spain, the Netherlands, Minensota, Canada, Australia and Turkey. This study shows that there is an effect on neck pain sufferers who are given manual therapy intervention - 0.08 units of influence compared to non-manual therapy, this effect is not statistically significant on function and this effect has a statistically significant effect (SMD = - 0.08; CI 95% CI= -0.35 to 0.20; p= 0.590). Conclusion: The manual therapy has an impact on mobile range of motion of the joint in neck pain patients compared to those without manual therapy.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".