Are Factors of Posture and Balance Integrated in Research Studies on Upper Extremity Musculoskeletal Pain in Instrumental Musicians?: A Scoping Review
Bibliographic record
Abstract
It is widely believed that posture and balance stressors are factors in playing-related pain for musicians using hand-held musical instruments. This purpose of this scoping review was to assess the available literature relative to the effects of posture and balance in musicians with neuromusculoskeletal injuries. A search of Medline, Web of Science, and SportDiscus seeking articles combining posture and balance considerations with pain in performing artists was performed. From 1,403 articles initially identified by the search parameters, the further abstract/title review for relevance and inclusiveness of pain and posture/balance variables in performing artists resulted in the retention of 29 articles for this full-text scoping review. The full-text analysis assessed publication type, study design, participant population, methodology, statistical methods, main results, and whether the study evaluated the relationship between posture/balance and pain in musicians. Overall, most of the studies including musicians were observational or descriptive. Although, in recent years, there has been an increase in the number of interventional studies regarding posture, balance and pain in musicians, there is still minimal evidence about the contribution of posture and balance characteristics to pain in musician performers. To reliably establish a predictable relationship with injury symptomatology experienced by musicians, it is essential to integrate standardized, validated measurements of posture and balance in the evaluation of all musicians who report to a health professional with neuromusculoskeletal pain. This will not only allow researchers to determine the effect of postural righting dysfunction on neuromusculoskeletal injuries in musicians, but also may provide a foundation for clinicians to develop effective interventions.
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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 | 0.027 | 0.122 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.029 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".