Differential item functioning related to ethnicity in an oral health‐related quality of life measure
Bibliographic record
Abstract
OBJECTIVE: To assess whether an oral health-related quality of life (OHRQoL)measure showed differential item functioning (DIF) by ethnicity. METHODS: A simple random sample of 12- and 13-year-old schoolchildren enrolled in the Taranaki District Health Board's school dental service, New Zealand. Each child (n = 430) completed the Child Perception Questionnaire (CPQ(11-14)) in the dental clinic waiting room, prior to a dental examination. The dataset included age, gender, ethnicity, and deprivation status. The general principle of the analytic plan was that equal scores from each CPQ(11-14) item were expected from both non-Mäori and Mäori groups regardless of their ethnic group. Ordinal logistic regression was performed. The dependent variables were the CPQ(11-14) items. The ethnicity group and each CPQ(11-14) domain score were the independent variables. Non-uniform DIF was assessed through adding an interaction term for each CPQ(11-14) sub-scale. RESULTS: Non-uniform DIF was found in two items, one in the Functional Limitations sub-scale and another in the Social Well-being sub-scale. Uniform DIF was found in one item of the Emotional Well-being sub-scale. CONCLUSION: Both non-uniform and uniform DIF by ethnicity was found in three of 37 items of the CPQ(11-14) questionnaire, showing it is important to perform DIF analysis when applying OHRQoL measures.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".