Psychometric characteristics of the “General Oral Health Assessment Index (GOHAI) » in a French representative sample of patients with schizophrenia
Bibliographic record
Abstract
BACKGROUND: The "General Oral Health Assessment Index" (GOHAI) was widely used in clinical or epidemiological studies worldwide, as it was available for use in different languages. Therefore, the aim of this study was to evaluate the psychometric characteristics of the GOHAI in a representative sample of patients with schizophrenia. METHODS: A total of 90 schizophrenic patients (in-patients and out-patients) were recruited from the participants of the "buccodor study" (NCT02167724) between March and September 2015. They were selected using a random stratified sampling method according to their age, sex, or residential area (urban/rural area). GOHAI validity (construct, predictive, concurrent and known group validity) and internal consistency (reliability) were tested. Test-retest reliability was evaluated in 32 subjects. RESULTS: The mean age was 47.34 (SD = 12.17). Internal consistency indicated excellent agreement, with a Cronbach's α value of 0.82 and average inter-item correlation of 0.65. Intraclass correlation coefficients for test-retest reliability with 95% confidence intervals were not significantly different (p > 0.05). Construct validity was supported by three factor that accounted for 60.94% of the variance observed. Predictive validity was corroborated as statistically significant differences were observed between a high GOHAI score, which was associated with self-perceived satisfaction with oral health, lower age and high frequency of toothbrushing. Concurrent validity was corroborated as statistically significant relationships were observed between the GOHAI scores and most objective measures of dental status. For known group validity, they was no significant difference of the mean GOHAI score between out or in-patients (p > 0.05). CONCLUSION: Acceptable psychometric characteristics of the GOHAI could help caregivers to develop ways to improve the Oral Health related Quality Of Life of schizophrenic patients. TRIAL REGISTRATION: Clinical Trials Gov NCT02167724 . Date registered 17 June, 2014.
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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 | 0.005 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".