Impact of Completing CLEFT-Q Scales That Ask About Appearance on Children and Young Adults: An International Study
Bibliographic record
Abstract
OBJECTIVE: To describe the impact of completing the CLEFT-Q appearance scales on patients with cleft lip and/or palate and to identify demographic and clinical characteristics and CLEFT-Q scores associated with reporting a negative impact. DESIGN: International cross-sectional survey. SETTING: Recruitment took place between October 2014 and November 2016 at 30 craniofacial clinics located in 12 countries. PATIENTS: Aged 8 to 29 years with cleft lip and/or palate. MAIN OUTCOME MEASURE(S): Participants were asked 4 questions to evaluate the impact of completing the field test version of a patient-reported outcome measure (the CLEFT-Q) that included 154 items, of which 79 (51%) asked about appearance (of the face, nose, nostrils, teeth, lips, jaws, and cleft lip scar). RESULTS: The sample included 2056 participants. Most participants liked answering the CLEFT-Q (88%) and the appearance questions (82%). After completing the appearance scales, most participants (77%) did not feel upset or unhappy about how they look, and they felt the same (67%) or better (23%) about their appearance after completing the questionnaire. Demographic and clinical variables associated with feeling unhappy/upset or worse about how they look included country of residence, female gender, more severe cleft, anticipating future cleft-specific surgeries, and reporting lower (ie, worse) scores on CLEFT-Q appearance and health-related quality-of-life scales. CONCLUSION: Most participants liked completing the CLEFT-Q, but a small minority reported a negative impact. When used in clinical practice, CLEFT-Q scale scores should be examined as soon as possible after completion in order that the clinical team might identify patients who might require additional support.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 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".