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Kirshenbaum JS, Chahal R, Ho TC, et al. Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics. J Child Psychol Psychiatry. 2021;doi: 10.1111/jcpp.13512.
Kirshenbaum, J. S., Chahal, R., Ho, T. C., King, L. S., Gifuni, A. J., Mastrovito, D., Coury, S. M., Weisenburger, R. L., & Gotlib, I. H. (2021). Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics. Journal of child psychology and psychiatry, and allied disciplines, . https://doi.org/10.1111/jcpp.13512
Kirshenbaum, Jaclyn S, et al. "Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics." Journal of child psychology and psychiatry, and allied disciplines vol. (2021). doi: https://doi.org/10.1111/jcpp.13512
Kirshenbaum JS, Chahal R, Ho TC, King LS, Gifuni AJ, Mastrovito D, Coury SM, Weisenburger RL, Gotlib IH. Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics. J Child Psychol Psychiatry. 2021 Aug 27; doi: 10.1111/jcpp.13512. Epub 2021 Aug 27. PMID: 34448494.
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J Child Psychol Psychiatry. 2021 Aug 27; doi: 10.1111/jcpp.13512. Epub 2021 Aug 27.

Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics.

Journal of child psychology and psychiatry, and allied disciplines

Jaclyn S Kirshenbaum, Rajpreet Chahal, Tiffany C Ho, Lucy S King, Anthony J Gifuni, Dana Mastrovito, Saché M Coury, Rachel L Weisenburger, Ian H Gotlib

Affiliations

  1. Department of Psychology, Stanford University, Stanford, CA, USA.
  2. Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
  3. Psychiatry Department, Douglas Mental Health University Institute, McGill University, Montréal, QC, Canada.

PMID: 34448494 DOI: 10.1111/jcpp.13512

Abstract

BACKGROUND: Suicidal ideation (SI) typically emerges during adolescence but is challenging to predict. Given the potentially lethal consequences of SI, it is important to identify neurobiological and psychosocial variables explaining the severity of SI in adolescents.

METHODS: In 106 participants (59 female) recruited from the community, we assessed psychosocial characteristics and obtained resting-state fMRI data in early adolescence (baseline: aged 9-13 years). Across 250 brain regions, we assessed local graph theory-based properties of interconnectedness: local efficiency, eigenvector centrality, nodal degree, within-module z-score, and participation coefficient. Four years later (follow-up: ages 13-19 years), participants self-reported their SI severity. We used least absolute shrinkage and selection operator (LASSO) regressions to identify a linear combination of psychosocial and brain-based variables that best explain the severity of SI symptoms at follow-up. Nested-cross-validation yielded model performance statistics for all LASSO models.

RESULTS: A combination of psychosocial and brain-based variables explained subsequent severity of SI (R

CONCLUSIONS: A linear combination of baseline and follow-up psychosocial variables best explained the severity of SI. Follow-up analyses indicated that graph theory resting-state metrics did not increase the prediction of the severity of SI in adolescents. Attending to internalizing and externalizing symptoms is important in early adolescence; resting-state connectivity properties other than local graph theory metrics might yield a stronger prediction of the severity of SI.

© 2021 Association for Child and Adolescent Mental Health.

Keywords: Suicidal ideation; adolescence; graph theory; internalizing and externalizing symptoms; resting-state fMRI

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