OBJECTIVE: Screening protocols that rely on a single informant are inadequate in predicting pediatric depression. Multi-informant and risk factor screening approaches are potentially more sensitive methods for identifying depression risk, but the incremental validity of these protocols has not been adequately tested. Using a translational analytic approach and multimethod, longitudinal study design, we simultaneously tested several multi-indicator approaches to depression screening to identify an optimal algorithm for predicting depression onset in youth. METHOD: Participants were 222 never-depressed children and adolescents (Mage = 10.75 years old, SDage = 1.85; female = 50.45%; 82.88% White), who completed baseline questionnaires for depressive symptoms and cognitive vulnerabilities, in addition to a morphed face task to assess pupil dilation. Mothers, meanwhile, completed baseline questionnaires and a semistructured interview to assess maternal and pediatric depression. Follow-up depression diagnostic assessments with both the mother and youth occurred every 6 months for 2 years. Receiver operating characteristics and reclassification analyses were used to test our aims. RESULTS: Overall, we found moderate support for a multi-informant approach, and convincing evidence that individual differences in pupil dilation uniquely predicted depression onset. Youth with subthreshold depressive symptoms and elevated pupil dilation were over twice as likely to develop a first lifetime episode of depression compared to one's risk rate based on sex and age. CONCLUSIONS: Our study provides one of the first screening batteries for detecting first lifetime episodes of depression in youth. The unique and incremental validity provided by pupil dilation suggests feasible biological indicators of depression risk can improve primary prevention efforts that target depression, such as universal pediatric depression screening. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
OBJECTIVE: Screening protocols that rely on a single informant are inadequate in predicting pediatric depression. Multi-informant and risk factor screening approaches are potentially more sensitive methods for identifying depression risk, but the incremental validity of these protocols has not been adequately tested. Using a translational analytic approach and multimethod, longitudinal study design, we simultaneously tested several multi-indicator approaches to depression screening to identify an optimal algorithm for predicting depression onset in youth. METHOD:Participants were 222 never-depressedchildren and adolescents (Mage = 10.75 years old, SDage = 1.85; female = 50.45%; 82.88% White), who completed baseline questionnaires for depressive symptoms and cognitive vulnerabilities, in addition to a morphed face task to assess pupil dilation. Mothers, meanwhile, completed baseline questionnaires and a semistructured interview to assess maternal and pediatric depression. Follow-up depression diagnostic assessments with both the mother and youth occurred every 6 months for 2 years. Receiver operating characteristics and reclassification analyses were used to test our aims. RESULTS: Overall, we found moderate support for a multi-informant approach, and convincing evidence that individual differences in pupil dilation uniquely predicted depression onset. Youth with subthreshold depressive symptoms and elevated pupil dilation were over twice as likely to develop a first lifetime episode of depression compared to one's risk rate based on sex and age. CONCLUSIONS: Our study provides one of the first screening batteries for detecting first lifetime episodes of depression in youth. The unique and incremental validity provided by pupil dilation suggests feasible biological indicators of depression risk can improve primary prevention efforts that target depression, such as universal pediatric depression screening. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Authors: Thomas Insel; Bruce Cuthbert; Marjorie Garvey; Robert Heinssen; Daniel S Pine; Kevin Quinn; Charles Sanislow; Philip Wang Journal: Am J Psychiatry Date: 2010-07 Impact factor: 18.112
Authors: J Kaufman; B Birmaher; D Brent; U Rao; C Flynn; P Moreci; D Williamson; N Ryan Journal: J Am Acad Child Adolesc Psychiatry Date: 1997-07 Impact factor: 8.829
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