The concept of validity in sociodental indicators and oral health‐related quality‐of‐life measures
Bibliographic record
Abstract
BACKGROUND: Most of the psychometric instruments used to measure quality of life associated with oral impairment and disability from the perspectives of older adults focus on negative experiences, and pay little attention to the possibility of positive reactions to disablement. This oversight challenges the validity of the instruments in current use, and raises questions about the process used to validate them. OBJECTIVES: In this study, we consider the general attributes of psychometric validity, and how they have been applied to oral health-related instruments. CONCLUSIONS AND RECOMMENDATIONS: The psychometric characteristics and predictive validity of existing dental instruments are still weak, probably because the instruments fail to address the broad range of personal variables that influence oral health, disability and quality of life. We recommend, therefore, that a continuous process of validation be adopted to include: (1) assessments of the theoretical framework supporting the instruments; (2) evaluations of the focus and structure of the questions used; and (3) enhancements of the prediction value of instruments applicable to oral health-related beliefs and behaviours.
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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 | 0.205 | 0.449 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".