Validation of a Dutch translation of the fibromyalgia impact questionnaire
Bibliographic record
Abstract
OBJECTIVES: To validate a Dutch translation of the fibromyalgia impact questionnaire (FIQ). MATERIALS AND METHODS: Data were taken from two randomized clinical trials on Spa treatment and venlafaxine in fibromyalgia (FM). Participants completed the Dutch FIQ and a set of validated questionnaires for general health (RAND-36), depression (Beck depression inventory, BDI), pain (McGill pain questionnaire, MPQ) and fatigue (checklist individual strength, CIS). Internal consistency within the FIQ item 'physical functioning' was studied using Cronbach's alpha. Test-retest reliability was studied with intra-class-correlation (ICC) in a subsample of 76 control subjects over a 3 month period without specific intervention. Construct validity was evaluated by correlating the FIQ to other questionnaires. Sensitivity to change was studied using standardized response means (SRM). RESULTS: The study sample consisted of 213 women and 11 men (mean age 47 yrs, mean disease duration 11 yrs). Cronbach's alpha for the item 'physical functioning' was 0.91, indicating high internal consistency. Test-retest reliability was acceptable, with ICC ranging from 0.45 for 'morning tiredness' to 0.71 for 'physical function'. FIQ correlated significantly with the RAND-36, with Spearman's rho ranging from -0.60 to -0.70 for items measuring the same concept. Similar patterns of correlation were seen with MPQ, BDI and CIS. Sensitivity to change was sufficient, with SRM after Spa treatment ranging from 0.3 for 'work days missed' to 0.9 for 'days felt good'. Similar SRM were found in the venlafaxine trial for patients reporting general improvement. CONCLUSION: The Dutch FIQ is a valid instrument for measuring health status in FM, showing sufficient reliability, construct validity and responsiveness.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".