Validation of the Dutch Version of the BODY-Q Measuring Appearance, Health-Related Quality of Life, and Experience of Healthcare in Patients Undergoing Bariatric and Body Contouring Surgery
Bibliographic record
Abstract
BACKGROUND: The BODY-Q is a patient-reported outcome measure developed for use in bariatric and body contouring surgery. OBJECTIVES: The objective of this study was to examine the validity and reliability of the Dutch version of the BODY-Q. METHODS: The BODY-Q consists of 163 items in 21 independently functioning scales that measure appearance, health-related quality of life, and experience of care. The data used to validate the Dutch BODY-Q were provided by 2 prospective multicenter cohort studies across 3 hospitals in the Netherlands. The BODY-Q was administered before and after surgery at 3 or 4 months and 12 months. Rasch measurement theory (RMT) analysis was used to evaluate the BODY-Q for targeting, category threshold order, Rasch model fit, Person Separation Index, and differential item functioning by language (original English data vs Dutch data). RESULTS: Data were collected between January 2016 and May 2019. The study included 876 participants, who provided 1614 assessments. Validity was supported by 3 RMT findings: most scales showed good targeting, 160 out of 163 items (98.2%) evidenced ordered thresholds, and 142 out of 163 items (87.1%) fitted the RMT model. Reliability was high with Person Separation Index values >0.70 for 19 out of 21 scales. There was negligible influence of differential item functioning by language on person item locations and the scale scoring. CONCLUSIONS: This study provides evidence for the reliability and validity of the Dutch BODY-Q for use in bariatric and body contouring patients in the Netherlands. The Dutch BODY-Q can be used in (inter)national research and clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".