Treatment of Chronic Neck Pain in Patients with Forward Head Posture: A Systematic Narrative Review
Bibliographic record
Abstract
(1) Background: Forward head posture (FHP) is one of the most common cervical postural deviations and is characterized by head protrusion or forward head placement in relation to the shoulder in the sagittal plane. Patients with FHP often experience neck pain and disability. The aim of this study was to investigate whether treatment programs are effective in the management of neck pain in patients with FHP. (2) Methods: A MEDLINE (PubMed), Embase, Cochrane Library, and Scopus database search was conducted for English language articles on patients with chronic neck pain and FHP published until 12 April 2023. To identify potentially relevant articles, the following key search phrases were combined: 'forward head posture' and 'pain'. After searching, 2516 potentially relevant articles were identified. After reading the titles and abstracts and assessing their eligibility based on full-text articles, 16 articles were included in this review. (3) Results: Among the 16 studies that investigated the efficacy of treatment programs for managing chronic pain in patients with FHP, 11 investigated the effect of exercise programs, and 5 investigated the effect of manual therapy. Patients reported significant improvement in pain and disability after receiving treatment programs such as corrective postural exercises and special manual therapy techniques. (4) Conclusions: Various treatment programs, including postural corrective exercises and manual therapy, are beneficial for improving pain and disability in patients with FHP.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".