The effectiveness of aerobic exercise on pain and disability in individuals with neck pain: A systematic review and meta‐analysis
Bibliographic record
Abstract
The present review aimed to investigate the effectiveness of aerobic exercise (AE) compared to other interventions in decreasing pain intensity and reducing disability in individuals with neck pain. A systematic review (SR) of randomized controlled trials was conducted. This SR was registered in PROSPERO (CRD42021231231). Searches were conducted in five electronic databases (MEDLINE, Embase, CINAHL, Cochrane and SCOPUS). Studies were selected if they included adults over 18 years old with neck pain. The primary outcomes were pain intensity and physical function. A meta-analysis was conducted when applicable. Cochrane RoB Tool-2 was used to determine the risk of bias of included studies, and the certainty of the evidence was determined using the GRADE approach. Out of 4669 initial records screened, six studies published in 12 articles were included. AE was not statistically different compared to no-treatment or other interventions (e.g., localized exercise or acupuncture) on pain intensity measured with a visual analogue scale (VAS) (mean difference (MD) [95%CI]: 5.16 mm [-6.38, 16.70]). Contrarily, strengthening exercise was better than AE for pain intensity (MD [95%CI]: -11.34 mm [-21.6, -1.09]) after treatment. However, when AE was combined with other therapy (strengthening exercises or acupuncture), the combined therapy was better than isolated treatments (MD [95%CI]: 7.71 mm [1.07, 14.35]). A high heterogeneity was observed between protocols, comparisons, and results (magnitudes and directions). In conclusion, AE had positive results only when combined with other therapies to reduce pain intensity and disability in patients with neck pain. However, the evidence is limited, low-quality, and heterogeneous.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.033 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".