Validation of the OHIP-EDENT Instrument using the Factor Analysis Technique
Bibliographic record
Abstract
BackgroundOral Health Related Quality of Life (OHRQoL) plays a fundamental role in the overall well-being of an individual. The OHIP-EDENT questionnaire proposed by Allen and Locker evaluates OHRQoL in edentulous populations The original instrument comprises of 20 items across 7 domains which assess the functional, psychological, and social implications of being edentulous. While several authors have argued that the OHIP-EDENT scores accurately capture the latent construct of OHRQoL, conflicting findings in multiple studies challenge this idea. This results from the emergence of alternative-factor solutions with fewer domains documented in scientific literature, diverging from the originally postulated 7-factor solution of the OHIP-EDENT. ObjectiveTo estimate the extent to which the OHIP-EDENT accurately reflects OHRQoL using baseline data from two studies and evaluating the optimal factor structure which could potentially improve OHIP-EDENT's validity. Methodology The study draws on baseline data from participants in a US quasi-experimental study (N=165) and a Canadian randomized clinical trial (N=255), the Kaiser Meyer Olkin and Bartlett tests assessed sampling adequacy. The Exploratory Factor Analysis (EFA) on data from the US population identified the latent constructs of the OHIP-EDENT. After identifying the 3-factor structure from the EFA, a Confirmatory Factor Analysis (CFA) of the Canadian cohort data validated this hypothesized model. Factor analysis was performed on two separate datasets to ensure stability and generalizability of the 3-factor model. Subsequently, an additional step was carried out to evaluate the cross-cultural applicability of the OHIP-EDENT instrument. A 4-factor model (based on published literature) was tested on data of the Canadian population using CFA, and the 3-and 4-factor CFA models were compared. ResultsThe EFA on the US population revealed a three-factor configuration of the OHIP-EDENT (Cronbach’s alpha = 0.946). This hypothetical three-factor model was applied to the Canadian cohort and the CFA results revealed excellent fit (RMSEA=0.043; CFI=0.995). The four-factor solution from the Brazilian population also showed excellent results when tested in the Canadian cohort (RMSEA=0.037; CFI= 0.996). Conclusion The postulated 3-factor model identified constructs "Functional and Psychological Well-Being," "Social Impact," and "Physical Discomfort”, while the 4-factor model included an additional construct, “Masticatory-related complaints”, offering a more comprehensive framework to investigate the dimensions of OHRQoL in edentulous individuals
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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 | 0.064 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".