Development of an oral health-related quality of life measure for the Malaysian adults population: cross-cultural adaptation of the Oral Health Impact Profile
Bibliographic record
Abstract
The main aim of this project was to develop an OHRQoL measure for the Malaysian adult population aged 18 and above by adapting the Oral Health Impact Profile (OHIP). It also aimed to compare two methods (frequency and regression) of developing a short form of the measure, to provide preliminary data on the impact of oral conditions on the quality of life of the adult population in Malaysia, and to compare these impacts between Malaysian and Canadian population aged 50 and above. The adaptation of this measure was based on the framework proposed by Herdman et al (1998). The OHIP was translated into the Malay language using a forward-backward translation technique. Thirty-six patients were interviewed to assess the conceptual equivalence and relevancy of each item. The adapted OHIP---L-OHIP(M)---contains 45 items. This questionnaire was pre-tested on 20 patients. A total of 171 respondents completed the short form [S-OHIP(M)] to assess the response format. The five-point frequency Likert scale could be used for Malaysian population. The preliminary results revealed that a substantial proportion of the sample included in this study experienced frequent psychological impacts associated with their oral conditions. The Malaysian population aged 50 and above had slightly higher impacts than Canadian population. However, the pattern of impacts was similar, where physical consequences were most affected and social aspects were the least affected. Both short forms (frequency and regression) performed equally well when tested for discriminative validity. However, the responsiveness of these measures was not tested in this present study. This could be one of the future research areas to determine which version will be superior in terms of detecting change. Field-testing was conducted in order to assess the suitability of two modes of administration (mail and interview) and to establish the psychometric properties of both the L-OHIP(M) and the S-OHIP(M). Both versions [L-OHIP(M) and S-OHIP(M)] were found to be valid and reliable. However, this study only provides initial evidence for the reliability and validity of these measures. Further study is recommended to collect more evidence to support the validity and reliability of these measures.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".