Why the study?
The Short Mood and Feelings Questionnaire lacks a specific cut-point for the Brazilian population, and refined methods like item response theory and interval likelihood ratios involve complex calculations that hinder clinical implementation.
Does the Short Mood and Feelings Questionnaire (SMFQ) accurately detect depressive symptoms and internalizing-spectrum disorders in a Brazilian youth cohort?
Does the Short Mood and Feelings Questionnaire (SMFQ) accurately detect depressive symptoms and internalizing-spectrum disorders in a Brazilian youth cohort?
The application of interval likelihood ratios based on IRT T-scores improves the SMFQ's predictive ability for internalizing-spectrum conditions in youth.
SMFQ T-scores plus ILRs improve internalizing disorder prediction in Brazilian youth; leaves open prospective validation before routine use.
Background The Short Mood and Feelings Questionnaire (SMFQ) is a validated tool for assessing depressive symptoms in youth, though no specific cut-point exists for the Brazilian population. Item response theory (IRT) and interval likelihood ratios (ILRs) offer refined methods to monitor symptoms but involve complex calculations that hinder clinical implementation. Methods Cross-sectional data were drawn from an urban school-based sample (Brazilian High-Risk Cohort Study in 2018-2019, n=1,905, aged 14-23, 46.6% females). Diagnoses were based on Development and Well-Being Assessment (DAWBA) clinical ratings. SMFQ factor scores were estimated using IRT and transformed into T-scores. ROC curves evaluated diagnostic properties for internalizing- and externalizing-spectrum disorders. A calculator was developed to estimate post-test probabilities from T-scores using ILRs. Sensitivity analysis excluded MDD as a comorbid diagnosis. Results ROC curve analyses suggested a sum score cut-off of >6 and a T-score of >55 for detecting MDD. The SMFQ showed good accuracy for internalizing conditions (AUC > 0.8) but low for attention and externalizing disorders (AUC < 0.7). ILRs for internalizing conditions ranged from 0.12 (95% CI: 0.07–0.19) to 29.98 (95% CI: 11.99–75), with post-test probabilities exceeding pre-test probabilities for scores above the cut-off. Sensitivity analysis confirmed findings when excluding MDD. Including ILRs significantly improved predictive models over dichotomous cut-offs. Conclusion The application of ILRs based on IRT T-scores improved SMFQ’s predictive ability for internalizing-spectrum conditions, regardless of comorbidity. A calculator can integrate these methods into clinical practice, supporting real-time data-driven decisions.
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Jobim et al. (2025) studied this question.
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