A modified short version of the oral health impact profile for assessing health-related quality of life in edentulous adults.
Bibliographic record
Abstract
PURPOSE: The aim of this study was to develop a shortened version of the Oral Health Impact Profile (OHIP) appropriate for use in edentulous patients and to evaluate its measurement properties. MATERIALS AND METHODS: Data were collected from the Ontario Study of Older Adults and a longitudinal clinical trial of implant-retained prostheses undertaken in Newcastle Dental Hospital, UK. All subjects completed an OHIP at baseline, and UK subjects also completed an OHIP posttreatment. Using an item impact reduction method, a shortened version of the OHIP (called OHIP-EDENT) was derived from both datasets. Discriminant validity and responsiveness properties of this modified version were compared with OHIP-14 and OHIP-49. RESULTS: Using an item impact method of reducing the 49 OHIP items produced very similar subsets in both Canadian and British populations; the modified version had little overlap with the current short version (OHIP-14). Discriminant validity properties of OHIP-EDENT were similar to OHIP-14 and OHIP-49. Using effect sizes to assess sensitivity to change, OHIP-EDENT exhibited less susceptibility to floor effects than OHIP-14 and appeared to measure change as effectively as OHIP-49. CONCLUSION: The modified shortened version of the OHIP derived in this study has measurement properties comparable with the full 49-item version. This modified shortened version may be more appropriate for use in edentulous patients than the current short version.
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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 | 0.002 | 0.008 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".