Dataset Information

Measurement of gender and sexuality in the Adolescent Brain Cognitive Development (ABCD) study.

ABSTRACT: The Adolescent Brain Cognitive Development^SM (ABCD) study is a longitudinal study of adolescent brain development and health that includes over 11,800 youth in the United States. The ABCD study includes broad developmental domains, and gender and sexuality are two of these with noted changes across late childhood and early adolescence. The Gender Identity and Sexual Health (GISH) workgroup recommends measures of gender and sexuality for the ABCD study, prioritizing those that are developmentally sensitive, capture individual differences in the experience of gender and sexuality, and minimize participant burden. This manuscript describes the gender and sexuality measures used in ABCD and provides guidance for researchers using these data. Data showing the utility of these measures and longitudinal trends are presented. Including assessment of gender and sexuality in ABCD allows for characterization of developmental trajectories of gender and sexuality, and the broad scope of ABCD data collection allows examination of identity development in an intersectional manner.

SUBMITTER: Potter AS

PROVIDER: S-EPMC8759998 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundWhile identifying risk factors for adolescent depression is critical for early prevention and intervention, most studies have sought to understand the role of isolated factors rather than across a broad set of factors. Here, we sought to examine multi-level factors that maximize the prediction of depression symptoms in US children participating in the Adolescent Brain and Cognitive Development (ABCD) study.MethodsA total of 7,995 participants from ABCD (version 3.0 release) provided complete data at baseline and 1-year follow-up data. Depression symptoms were measured with the Child Behavior Checklist. Predictive features included child demographic, environmental, and structural and resting-state fMRI variables, parental depression history and demographic characteristics. We used linear (elastic net regression, EN) and non-linear (gradient-boosted trees, GBT) predictive models to identify which set of features maximized prediction of depression symptoms at baseline and, separately, at 1-year follow-up.ResultsBoth linear and non-linear models achieved comparable results for predicting baseline (EN: MAE = 3.757; R2 = 0.156; GBT: MAE = 3.761; R2 = 0.147) and 1-year follow-up (EN: MAE = 4.255; R2 = 0.103; GBT: MAE = 4.262; R2 = 0.089) depression. Parental history of depression, greater family conflict, and shorter child sleep duration were among the top predictors of concurrent and future child depression symptoms across both models. Although resting-state fMRI features were relatively weaker predictors, functional connectivity of the caudate was consistently the strongest neural feature associated with depression symptoms at both timepoints.ConclusionsConsistent with prior research, parental mental health, family environment, and child sleep quality are important risk factors for youth depression. Functional connectivity of the caudate is a relatively weaker predictor of depression symptoms but may represent a biomarker for depression risk.

Dataset Information

Measurement of gender and sexuality in the Adolescent Brain Cognitive Development (ABCD) study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets