Association between clinical biomechanical metrics of cervical spine function and pain or disability in people with neuromusculoskeletal neck pain: Protocol for a systematic review and planned meta-analysis
Bibliographic record
Abstract
INTRODUCTION/BACKGROUND: Neck pain is a burdensome condition associated with pain, disability, and economic cost. Neck pain has been associated with observable changes in neuromuscular function and biomechanics. Prior research shows impairments in kinematic control, including reduced mobility, velocity, and smoothness of cervical motion. However, the strength of association between these impairments and patient-reported pain and disability is unclear rendering development of novel and relevant rehabilitation strategies difficult. The aim of this systematic review is to synthesize existing evidence on the strength of association between clinical biomechanical metrics of neck function (ROM, strength, acceleration, accuracy, smoothness, etc.) and patient-reported neck pain and disability. METHODS/ANALYSIS: This protocol follows Cochrane guidelines and adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). MEDLINE, EMBASE, CINAHL, SPORTDiscus, Web of Science and Scopus will be searched, along with the gray literature, up to 20 November 2023, using terms and keywords derived from initial scoping searches. Observational studies, including cohorts and cross-sectional studies, that explore associations between clinical biomechanics of the neck and patient-reported outcomes of neck pain or disability will be included. Two reviewers will independently perform study selection, data extraction, and risk of bias assessment (National Institute of Health tool). Data will be synthesized using either a random effects meta-analytic approach or qualitatively using a modified Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach, dependent on the homogeneity of data available. DISCUSSION AND RELEVANCE: This review addresses a gap in the literature by systematically synthesizing findings on the relationship between neck function impairments and patient-reported outcomes. It will identify priorities for neck pain rehabilitation and gaps in current knowledge. DISSEMINATION: The results of this review will be disseminated through a peer-reviewed publication, conference presentation, and lay language summaries posted on an open-access website. TRIAL REGISTRATION: PROSPERO Registration number: CRD42023417317. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023417317.
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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 | 0.063 | 0.108 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.023 | 0.036 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.053 | 0.006 |
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".