[Italian translation and validation of the Nordic IRSST standardized questionnaire for the analysis of musculoskeletal symptoms].
Bibliographic record
Abstract
BACKGROUND: Data on self-reported symptoms and/or functional impairments are important in research on work-related musculoskeletal disorders (WRMSDs). In such cases the availability of international standardized questionnaires is extremely important since they permit comparison of studies performed in different Countries. OBJECTIVES: Translation into Italian and validation of the Nordic Musculoskeletal Questionnaire (NMQ), a tool which is widely used in studies on WRMSDs in the international scientific literature. METHODS: The extended Canadian version of the NMQ was translated into Italian. As per the current guidelines, the cross-cultural adaptation was performed by translation of the items from French, back-translation by independent mother-tongue translators and committee review. The resulting version of the questionnaire underwent pre-testing in 3 independent groups of subjects. The comprehensibility, reliability (internal consistency and reproducibility) and sensitivity were evaluated. RESULTS: After translation/back-translation and review of the items the comprehensibility of the Italian version of the questionnaire was judged good in a group of 40 workers. The internal consistency was evaluated using the Cronbach's Alpha test in the same group and in another 98 engineering workers: the results were on the whole acceptable. The reproducibility, which was tested with Cohen's Kappa test in the 40 workers, was good/excellent. In a preliminary evaluation, performed in 30 outpatients of a of Rehabilitation Service, sensitivity was very good. CONCLUSIONS: The results show that the Italian version of the Nordic Musculoskeletal Questionnaire is valid for self-administration and can be applied in 'field" studies on self-reported musculoskeletal symptoms and functional impairments in group of workers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".