Psychometric Validation of the CLEFT-Q Patient Reported Outcome Measure: A Prospective Study to Examine Cross-Sectional Construct Validity
Bibliographic record
Abstract
ObjectiveCLEFT-Q is a condition-specific patient-reported outcome measure (PROM) for patients with cleft lip and/or palate (CL/P). The aim of this study was to examine the cross-sectional construct validity of the CLEFT-Q scales.DesignConstruct validity was assessed through a prospective study that tested hypotheses regarding correlations of scores with other PROMs that measure related constructs.SettingSeven cleft centres in Canada, the USA, and UK were involved.Patients/ParticipantsPatients were aged eight to 29 years with CL/P.InterventionsBefore undergoing rhinoplasty, orthognathic, cleft lip scar revision, and alveolar bone graft, participants were asked to complete the following PROMs: CLEFT-Q (9 scales), Child Oral Health Impact Profile (socio-emotional subscale) and Cleft Hearing Appearance and Speech Questionnaire (features 1 subscale).Main Outcome Measure(s)The correlation coefficients examining the relationship between the scales were the main outcome measures. Correlations (Spearman) were calculated and interpreted as follows: <0.3 weak, 0.30 to 0.50 moderate, ≥0.50 strong.ResultsParticipants (n = 177) were mostly male (61%) and aged between eight and 11 years (42%). Overall, 38 of 52 (73%) hypotheses tested were supported. More specifically, 20 of 26 (77%) hypotheses about correlations between the appearance scales were supported, two of three (67%) hypotheses about correlations between the health-related quality of life scales were supported, and 16 of 23 (70%) hypotheses about correlations between the appearance and health-related quality of life scales were supported.ConclusionsCross-sectional construct validity of the CLEFT-Q scales adds further evidence of the psychometric properties of this instrument.
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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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".