Evidence map›Paper›PMID 34448494›Full record

ArticleJournal of child psychology and psychiatry, and allied disciplines2022

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

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

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of child psychology and psychiatry, and allied disciplines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Jaclyn S KirshenbaumDepartment of Psychology, Stanford University, Stanford, CA, USA.ORCID 0000-0001-8685-5840
Rajpreet ChahalDepartment of Psychology, Stanford University, Stanford, CA, USA.ORCID 0000-0003-0985-5622
Tiffany C HoDepartment of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.ORCID 0000-0002-4500-6364
Lucy S KingDepartment of Psychology, Stanford University, Stanford, CA, USA.ORCID 0000-0002-2552-0614
Anthony J GifuniDepartment of Psychology, Stanford University, Stanford, CA, USA.
Dana MastrovitoDepartment of Psychology, Stanford University, Stanford, CA, USA.
Saché M CouryDepartment of Psychology, Stanford University, Stanford, CA, USA.
Rachel L WeisenburgerDepartment of Psychology, Stanford University, Stanford, CA, USA.
Ian H GotlibDepartment of Psychology, Stanford University, Stanford, CA, USA.
Stanford University · USDouglas Mental Health University Institute · CAUniversity of California, San Francisco · US

Funding

Psychobiological Mechanisms Underlying the Association Between Early Life Stress and Depression Across AdolescenceR37MH101495 · NIMH · STANFORD UNIVERSITY · PI IAN H GOTLIB · 2018 to 2026
$6.6M
The Roles of Inflammatory and Glutamatergic Processes in the Neurodevelopmental Mechanisms Underlying Adolescent DepressionK01MH117442 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HO, TIFFANY CHEING · 2018 to 2022
$881k
The Effects of Early Life Stress on the Development of Brain Networks: Predicting Risk for Depression and Suicidal Ideation in AdolescenceF32MH120975 · NIMH · STANFORD UNIVERSITY · PI CHAHAL, RAJPREET · 2020 to 2022
$126k
NIH HHS F32MH120975NIMH NIH HHS F32 MH120975NIMH NIH HHS K01 MH117442NIMH NIH HHS R37 MH101495Stanford University Precision Health and Integrated Diagnostics Center
6 · The paper itself

Abstract

backgroundSuicidal 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.

methodsIn 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.

resultsA combination of psychosocial and brain-based variables explained subsequent severity of SI (R

conclusionsA 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.

Indexed as

ConnectomeSuicidal IdeationAdolescentBrainFemaleHumansMagnetic Resonance ImagingSelf Reportadolescencegraph theoryinternalizing and externalizing symptomsresting-state fMRISuicidal ideation

Identifiers

PMID34448494
PMCPMC8882198
OpenAlexW3194747393

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.