@article{ref1,
title="Identifying adolescents at risk for depression: assessment of a global prediction model in the Great Smoky Mountains Study",
journal="Journal of psychiatric research",
year="2022",
author="Caye, Arthur and Marchionatti, Lauro E. and Pereira, Rivka and Fisher, Helen L. and Kohrt, Brandon A. and Mondelli, Valeria and McGinnis, Ellen and Copeland, William E. and Kieling, Christian",
volume="155",
number="",
pages="146-152",
abstract="The Identifying Depression Early in Adolescence Risk Score (IDEA-RS) has been externally assessed in samples from four continents, but North America is lacking. Our aim here was to evaluate the performance of the IDEA-RS in predicting future onset of Major Depressive Disorder (MDD) in an adolescent population-based sample in the United States of America - the Great Smoky Mountains Study (GSMS). We applied the intercept and weights of the original IDEA-RS model developed in Brazil to generate individual probabilities for each participant of the GSMS at age 15 (N = 1029). We then evaluated the performance of such predictions against the diagnosis of MDD at age 19 using simple, case-mix corrected and refitted models. Furthermore, we compared how prioritizing the information provided by parents or by adolescents affected performance. The IDEA-RS exhibited a C-statistic of 0.63 (95% CI 0.53-0.74) to predict MDD in the GSMS when applying uncorrected weights. Case-mix corrected and refitted models enhanced performance to 0.69 and 0.67, respectively. No significant difference was found in performance by prioritizing the reports of adolescents or their parents. The IDEA-RS was able to parse out adolescents at risk for a later onset of depression in the GSMS cohort with above chance discrimination. The IDEA-RS has now showed above-chance performance in five continents.<p /> <p>Language: en</p>",
language="en",
issn="0022-3956",
doi="10.1016/j.jpsychires.2022.08.017",
url="http://dx.doi.org/10.1016/j.jpsychires.2022.08.017"
}