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Identifying adolescents at risk for depression: Assessment of a global prediction model in the Great Smoky Mountains Study.

Publication ,  Journal Article
Caye, A; Marchionatti, LE; Pereira, R; Fisher, HL; Kohrt, BA; Mondelli, V; McGinnis, E; Copeland, WE; Kieling, C
Published in: J Psychiatr Res
November 2022

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.

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Published In

J Psychiatr Res

DOI

EISSN

1879-1379

Publication Date

November 2022

Volume

155

Start / End Page

146 / 152

Location

England

Related Subject Headings

  • Young Adult
  • Risk Factors
  • Psychiatry
  • Humans
  • Glucuronates
  • Disaccharides
  • Depressive Disorder, Major
  • Depression
  • Cohort Studies
  • Adult
 

Citation

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Caye, A., Marchionatti, L. E., Pereira, R., Fisher, H. L., Kohrt, B. A., Mondelli, V., … Kieling, C. (2022). Identifying adolescents at risk for depression: Assessment of a global prediction model in the Great Smoky Mountains Study. J Psychiatr Res, 155, 146–152. https://doi.org/10.1016/j.jpsychires.2022.08.017
Caye, Arthur, Lauro E. Marchionatti, Rivka Pereira, Helen L. Fisher, Brandon A. Kohrt, Valeria Mondelli, Ellen McGinnis, William E. Copeland, and Christian Kieling. “Identifying adolescents at risk for depression: Assessment of a global prediction model in the Great Smoky Mountains Study.J Psychiatr Res 155 (November 2022): 146–52. https://doi.org/10.1016/j.jpsychires.2022.08.017.
Caye A, Marchionatti LE, Pereira R, Fisher HL, Kohrt BA, Mondelli V, et al. Identifying adolescents at risk for depression: Assessment of a global prediction model in the Great Smoky Mountains Study. J Psychiatr Res. 2022 Nov;155:146–52.
Caye, Arthur, et al. “Identifying adolescents at risk for depression: Assessment of a global prediction model in the Great Smoky Mountains Study.J Psychiatr Res, vol. 155, Nov. 2022, pp. 146–52. Pubmed, doi:10.1016/j.jpsychires.2022.08.017.
Caye A, Marchionatti LE, Pereira R, Fisher HL, Kohrt BA, Mondelli V, McGinnis E, Copeland WE, Kieling C. Identifying adolescents at risk for depression: Assessment of a global prediction model in the Great Smoky Mountains Study. J Psychiatr Res. 2022 Nov;155:146–152.
Journal cover image

Published In

J Psychiatr Res

DOI

EISSN

1879-1379

Publication Date

November 2022

Volume

155

Start / End Page

146 / 152

Location

England

Related Subject Headings

  • Young Adult
  • Risk Factors
  • Psychiatry
  • Humans
  • Glucuronates
  • Disaccharides
  • Depressive Disorder, Major
  • Depression
  • Cohort Studies
  • Adult