Optimizing the Psychosocial Function Measures in the International Consortium for Health Outcomes Measurement Standard Set for Cleft
Bibliographic record
Abstract
BACKGROUND: To ensure the feasibility of implementing PROMs in clinical practice, they must be continually appraised for undue burden placed on patients and clinicians and their usefulness for decision-making. This study assesses correlations between the CLEFT-Q psychosocial scales in the International Consortium for Health Outcomes Measurement Standard Set for cleft and explores their associations with patient characteristics and psychosocial care referral. METHODS: Spearman correlation coefficients were calculated for CLEFT-Q psychological function, social function, school function, face, speech function, and speech-related distress scales. Logistic regressions were used to assess the association of cleft phenotype, syndrome, sex, and adoption status on scale scores and clinical referral to psychosocial care for further evaluation and management. RESULTS: Data were obtained from 3067 patients with cleft lip and/or palate at three centers. Strong correlations were observed between social function and psychological function (r > 0.69) and school function (r > 0.78) scales. Correlation between school function and psychological function scales was lower (r = 0.59 to 0.68). Genetic syndrome (OR, 2.37; 95% CI, 1.04 to 5.41), psychological function (OR, 0.92; 95% CI, 0.88 to 0.97), school function (OR, 0.94; 95% CI, 0.90 to 0.98), and face (OR, 0.96; 95% CI, 0.94 to 0.98) were significant predictors for referral to psychosocial care. CONCLUSIONS: Because social function as measured by the CLEFT-Q showed strong correlations with both school and psychological function, its additional value for measuring psychosocial function within the Standard Set is limited, and it is reasonable to consider removing this scale from the International Consortium for Health Outcomes Measurement Standard Set for cleft.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".