Test-Retest Reliability of a Self-Administered Musculoskeletal Symptoms and Job Factors Questionnaire Used in Ergonomics Research
Bibliographic record
Abstract
The purpose of this study was to investigate the test-retest reliability of questionnaire items related to musculoskeletal symptoms and the reliability of specific job factors. The type of questionnaire items described in the present study have been used by several investigators to assess symptoms of musculoskeletal disorders and problematic job factors among workers from a variety of occupations. Employees at a plastics molding facility were asked to complete an initial symptom and jobs factors questionnaire and then complete an identical questionnaire either two or four weeks later. Of the 216 employees participating in the initial round, 99 (45.8%) agreed to participate in the retest portion of the study. The kappa coefficient was used to determine repeatability for categorical outcomes. The majority of the kappa coefficients for the 58 questionnaire items were above 0.50 but ranged between 0.13 and 1.00. The section of the questionnaire having the highest kappa coefficients was the section related to hand symptoms. Interval lengths of two and four weeks between the initial test and retest were found to be equally sufficient in terms of reliability. The results indicated that the symptom and job factors questionnaire is reliable for use in epidemiologic studies. Like all measurement instruments, the reliability of musculoskeletal questionnaires must be established before drawing conclusions from studies that employ the instrument.
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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 | 0.020 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".