Reliability of translation of the RAND 36-item health survey in a post-rehabilitation population
Bibliographic record
Abstract
The aim of this study is to evaluate the reliability of the RAND 36-item Health survey as a measure of health-related quality of life in a general Dutch post-rehabilitation population. A total of 752 ex-rehabilitation patients were invited to complete the Dutch RAND 36-item health survey. After 2 weeks, the people who responded to the first questionnaire were asked to complete the same questionnaire again. Internal consistency of the questionnaire was expressed as Cronbach's α. Test-retest reliability was expressed as intraclass correlation coefficient (ICC) and presented in Bland-Altman plots. Internal consistency was found acceptable for all subscales (n=276; Cronbach's α ranged from 0.81 to 0.95). Test-retest reliability was found acceptable for research and group comparisons for all subscales (n=184; ICC ranged from 0.71 to 0.88). Overall, test-retest reliability of the physical functioning (ICC=0.86), pain (ICC=0.87), and general health (ICC=0.88) subscale was relatively high, and that of health change (ICC=0.71) was relatively low. Reliability of the questionnaire did not notably differ between participants who indicated stable health and participants who indicated health change during the past weeks. In conclusion, the Dutch translation of the RAND 36-item health survey is reliable for research and group comparisons in a general post-rehabilitation population. However, the RAND 36-item health survey is not sufficiently reliable for individual comparisons within this population.
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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 | 0.062 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".