Dataset Information

Measuring retention within the adolescent brain cognitive development (ABCD)^SM study.

ABSTRACT: The Adolescent Brain Cognitive Development (ABCD)^SM study aims to retain a demographically diverse sample of youth and one parent across 21 sites throughout its 10-year protocol while minimizing selective (systematic) attrition. To evaluate the effectiveness of these efforts, the ABCD Retention Workgroup (RW) has employed a data-driven approach to examine, track, and intervene via three key metrics: (1) which youth completed visits late; (2) which youth missed visits; and (3) which youth withdrew from the study. The RW actively examines demographic (race, education level, family income) and site factors (visit satisfaction, distance from site, and enrollment in ancillary studies) to strategize efforts that will minimize disengagement and loss of participating youth and parents. Data showed that the most robust primary correlates of late visits were distance from study site, race, and parental education level. Race, lower parental education level, parental employment status, and lower family income were associated with higher odds of missed visits, while being enrolled in one of the ancillary studies was associated with lower odds of missed visits. Additionally, parents who were primary Spanish speakers withdrew at slightly higher rates. These findings provide insight into future targets for proactive retention efforts by the ABCD RW.

SUBMITTER: Feldstein Ewing SW

PROVIDER: S-EPMC8844713 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Measuring retention within the adolescent brain cognitive development (ABCD)<sup>SM</sup> study.

Feldstein Ewing Sarah W SW Dash Genevieve F GF Thompson Wesley K WK Reuter Chase C Diaz Vanessa G VG Anokhin Andrey A Chang Linda L Cottler Linda B LB Dowling Gayathri J GJ LeBlanc Kimberly K Zucker Robert A RA Tapert Susan F SF Brown Sandra A SA Garavan Hugh H

Developmental cognitive neuroscience 20220204

The Adolescent Brain Cognitive Development (ABCD)<sup>SM</sup> study aims to retain a demographically diverse sample of youth and one parent across 21 sites throughout its 10-year protocol while minimizing selective (systematic) attrition. To evaluate the effectiveness of these efforts, the ABCD Retention Workgroup (RW) has employed a data-driven approach to examine, track, and intervene via three key metrics: (1) which youth completed visits late; (2) which youth missed visits; and (3) which yo ...[more]

PMID: 35152002

Similar Datasets

Project description:BackgroundConcerns abound regarding childhood smartphone use, but studies to date have largely relied on self-reported screen use. Self-reporting of screen use is known to be misreported by pediatric samples and their parents, limiting the accurate determination of the impact of screen use on social, emotional, and cognitive development. Thus, a more passive, objective measurement of smartphone screen use among children is needed.ObjectiveThis study aims to passively sense smartphone screen use by time and types of apps used in a pilot sample of children and to assess the feasibility of passive sensing in a larger longitudinal sample.MethodsThe Adolescent Brain Cognitive Development (ABCD) study used passive, objective phone app methods for assessing smartphone screen use over 4 weeks in 2019-2020 in a subsample of 67 participants (aged 11-12 years; 31/67, 46% female; 23/67, 34% White). Children and their parents both reported average smartphone screen use before and after the study period, and they completed a questionnaire regarding the acceptability of the study protocol. Descriptive statistics for smartphone screen use, app use, and protocol feasibility and acceptability were reviewed. Analyses of variance were run to assess differences in categorical app use by demographics. Self-report and parent report were correlated with passive sensing data.ResultsSelf-report of smartphone screen use was partly consistent with objective measurement (r=0.49), although objective data indicated that children used their phones more than they reported. Passive sensing revealed the most common types of apps used were for streaming (mean 1 hour 57 minutes per day, SD 1 hour 32 minutes), communication (mean 48 minutes per day, SD 1 hour 17 minutes), gaming (mean 41 minutes per day, SD 41 minutes), and social media (mean 36 minutes per day, SD 1 hour 7 minutes). Passive sensing of smartphone screen use was generally acceptable to children (43/62, 69%) and parents (53/62, 85%).ConclusionsThe results of passive, objective sensing suggest that children use their phones more than they self-report. Therefore, use of more robust methods for objective data collection is necessary and feasible in pediatric samples. These data may then more accurately reflect the impact of smartphone screen use on behavioral and emotional functioning. Accordingly, the ABCD study is implementing a passive sensing protocol in the full ABCD cohort. Taken together, passive assessment with a phone app provided objective, low-burden, novel, informative data about preteen smartphone screen use.

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

Measuring retention within the adolescent brain cognitive development (ABCD)^SM study.

Publications

Measuring retention within the adolescent brain cognitive development (ABCD)<sup>SM</sup> study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Measuring retention within the adolescent brain cognitive development (ABCD)SM study.

Publications

Measuring retention within the adolescent brain cognitive development (ABCD)<sup>SM</sup> study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Measuring retention within the adolescent brain cognitive development (ABCD)^SM study.