Assessment of musculoskeletal symptoms and their impacts in the adolescent population: adaptation and validation of a questionnaire
Bibliographic record
Abstract
BACKGROUND: Valid and reliable instruments measuring musculoskeletal symptoms prevalence and their impacts in the adolescent population are scarce. The Extended Nordic Musculoskeletal Questionnaire (NMQ-E) is a reliable instrument that measures the prevalence, severity and impact of musculoskeletal symptoms. The purpose of this study was: (1) to develop a musculoskeletal symptom screening tool for younger populations derived from the NMQ-E and NMQ French versions and (2) to assess the validity and reliability of the adapted version of the instrument. METHODS: Based on the results of a translated (French) and adapted NMQ-E administered to 61 adolescents, a final 27-item dichotomous questionnaire was developed. The questionnaire measured the 6-month prevalence of musculoskeletal symptoms and the impact of these symptoms on school attendance as well as on sports and leisure activity participation. Among the adolescents who agreed to participate, thirty-nine (mean age: 13.7 ± 1.8) formed the reliability cohort and thirty-four (mean age: 14.2 ± 2.3) formed the criterion validity cohort. Reliability was measured by test-retest with a mean time interval of 28 hours. Criterion validity was assessed by comparing the answers to the questionnaires to the participants' clinical records. Statistical tests used were proportions of observed agreement (Po) and the Cohen kappa statistic (k). RESULTS: The mean Po for the test-retest was 0.92 for the 6-month symptom prevalence items, 0.99 for the impact of symptoms on school items and 0.96 for the impact on sports and leisure activities items. Kappa values for the reliability assessment ranged between 0.57 and 1.00 for the 27 dichotomous variables. The criterion validity kappa obtained for the agreement between participants' clinical records and questionnaires was k = 0.76. CONCLUSIONS: Kappa values for the reliability and the criterion validity are of moderate to perfect agreement beyond chance, indicating that there are only minor variations between tests, and good agreement between questionnaire items and clinical records. These results indicate that the adapted version of the NMQ-E is an appropriate self-administered musculoskeletal symptom screening tool for the adolescent population. Items related to the impacts of symptoms would benefit from additional validation using school and sport attendance records.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".