Preliminary psychologic survey of orofacial outpatients. Part 1: Predictors of anxiety or depression.
Bibliographic record
Abstract
AIMS: To identify predictors for anxiety and depression in orofacial outpatients and to investigate the patients' compliance rate in taking a series of psychologic tests. METHODS: Three thousand six hundred sixty-six patients completed a battery of questionnaires. These consisted of items inquiring about sex, age, past history of disease, presence of pain, the Hospital Anxiety and Depression Scale (HADS), the Eysenck Personality Questionnaire Short Form (S-EPQ), a Japanese dental version of the McGill Pain Questionnaire (JDMPQ), a visual analog scale (VAS) of pain, pain duration, and diagnosis. After univariate analyses had determined those variables with significant differences between an over-probable group (OPG, HADS scores > or = 8) and an absent group (AG, HADS scores < 8), we estimated the odds ratios of these variables for OPG as independent variables, and every variable was adjusted between the independent variables by multiple logistic regression models. RESULTS: For anxiety, 3 variables were independently related to the OPG and considered to be meaningful: age 30 or older, neuroticism score on the S-EPQ, and selection of the JDMPQ pain expression term "sickening." For depression, 4 variables were independently related to the OPG and considered to be meaningful: age 30 or older, neuroticism and extroversion scores on the S-EPQ, and selection of the JDMPQ pain expression term "sickening." The compliance rate for the tests was under half of the patients (3,666 of 7,542 patients). CONCLUSION: Although the predictability for anxiety or depression by some baseline parameters is considered to be low, age, personality traits, and choice of certain pain expression terms are useful predictors of anxiety or depression. The improvement of the compliance rate for psychologic screening will be a future challenge for Japanese clinics managing orofacial patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".