Gastric symptoms and low perceived maternal warmth are associated with eating disorder symptoms in young adolescent girls.

OBJECTIVE: This study sought to determine whether gastric symptoms are associated with later eating disorder (ED) symptoms during early adolescence, and whether this relationship is moderated by parental warmth/acceptance and/or the child's sex. METHOD: Longitudinal data from the Adolescent Brain Cognitive DevelopmentSM Study were utilized. Participants ages 9-10 years old (N = 4,950; 2,370 female) completed measures at baseline and 1 year later (Y1). At baseline, gastric symptoms were measured by parent-reported items from the Child Behavior Checklist (CBCL), and perceived parental acceptance was measured by youth report on the Children's Report of Parent Behavior Inventory (CRPBI) Acceptance subscale separately for mothers and fathers. ED symptoms at Y1 were assessed by parent report on a computerized version of the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS). Linear mixed-effects models were conducted separately for maternal and paternal acceptance to test relationships among variables. RESULTS: A three-way interaction between baseline gastric symptoms, sex, and maternal acceptance predicted Y1 ED symptoms (𝛽 = 0.08; p < .01). Post-hoc analyses revealed that the interaction between gastric symptoms and maternal acceptance was significant for girls only (𝛽 = -0.06, p < .01), such that low maternal acceptance was associated with a stronger relationship between baseline gastric symptoms and Y1 ED symptoms. No statistically significant main effects or interactions were found in the model for paternal acceptance. DISCUSSION: Gastric symptoms and low perceived maternal acceptance may interact to result in heightened risk for EDs in young adolescent girls.

Extracurricular Activities, Screen Media Activity, and Sleep May Be Modifiable Factors Related to Children's Cognitive Functioning: Evidence From the ABCD Study®.

This study used a machine learning framework in conjunction with a large battery of measures from 9,718 school-age children (ages 9-11) from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study to identify factors associated with fluid cognitive functioning (FCF), or the capacity to learn, solve problems, and adapt to novel situations. The identified algorithm explained 14.74% of the variance in FCF, replicating previously reported socioeconomic and mental health contributors to FCF, and adding novel and potentially modifiable contributors, including extracurricular involvement, screen media activity, and sleep duration. Pragmatic interventions targeting these contributors may enhance cognitive performance and protect against their negative impact on FCF in children.

The propensity to sign-track is associated with externalizing behavior and distinct patterns of reward-related brain activation in youth.

Externalizing behaviors in childhood often predict impulse control disorders in adulthood; however, the underlying bio-behavioral risk factors are incompletely understood. In animals, the propensity to sign-track, or the degree to which incentive motivational value is attributed to reward cues, is associated with externalizing-type behaviors and deficits in executive control. Using a Pavlovian conditioned approach paradigm, we quantified sign-tracking in 40 healthy 9-12-year-olds. We also measured parent-reported externalizing behaviors and anticipatory neural activations to outcome-predicting cues using the monetary incentive delay fMRI task. Sign-tracking was associated with attentional and inhibitory control deficits and the degree of amygdala, but not cortical, activation during reward anticipation. These findings support the hypothesis that youth with a propensity to sign-track are prone to externalizing tendencies, with an over-reliance on subcortical cue-reactive brain systems. This research highlights sign-tracking as a promising experimental approach delineating the behavioral and neural circuitry of individuals at risk for externalizing disorders.

Latent Variables Quantifying Neighborhood Characteristics and Their Associations with Poor Mental Health.

Neighborhood characteristics can have profound impacts on resident mental health, but the wide variability in methodologies used across studies makes it difficult to reach a consensus as to the implications of these impacts. The aim of this study was to simplify the assessment of neighborhood influence on mental health. We used a factor analysis approach to reduce the multi-dimensional assessment of a neighborhood using census tracts and demographic data available from the American Community Survey (ACS). Multivariate quantitative characterization of the neighborhood was derived by performing a factor analysis on the 2011-2015 ACS data. The utility of the latent variables was examined by determining the association of these factors with poor mental health measures from the 500 Cities Project 2014-2015 data (2017 release). A five-factor model provided the best fit for the data. Each factor represents a complex multi-dimensional construct. However, based on heuristics and for simplicity we refer to them as (1) Affluence, (2) Singletons in Tract, (3) African Americans in Tract, (4) Seniors in Tract, and (5) Hispanics or Latinos in Tract. African Americans in Tract (with loadings showing larger numbers of people who are black, single moms, and unemployed along with fewer people who are white) and Affluence (with loadings showing higher income, education, and home value) were strongly associated with poor mental health (R2=0.67, R2=0.83). These findings demonstrate the utility of this factor model for future research focused on the relationship between neighborhood characteristics and resident mental health.

Pilot Trial of Acceptance-Based Behavioral Weight Loss and Neurocognition Among American Indians.

Acceptance-based behavioral therapies (ABTs) for obesity may be superior to standard behavioral therapies but have not been adequately tested with American Indians (AIs). Neurocognitive function is also unexamined in relation to behavioral weight loss among AIs despite findings that neurocognition predicts outcomes in general samples, may help explain some of the benefits of ABTs, and may be relevant to marginalized groups. The primary objective of this pilot was to examine the feasibility/acceptability of ABT in an AI sample. Exploratory analyses examined the relationship between neurocognition and weight loss. Forty-eight AI adults with overweight/obesity (ages 43.3 ± 10.3 years, 85% female; baseline body mass index = 36.8 ± 4.4 kg/m2) enrolled in a 6-month open ABT weight loss trial. Feasibility indices, including screening/enrollment, session attendance, retention rates for posttreatment assessments, and program acceptability were examined. Percent weight loss (%WL) was assessed as well as fluid and crystalized neurocognition (National Institutes of Health Toolbox Cognition Battery [NIHTB-CB]). We enrolled 79% of the eligible sample and retained 75% (N = 36) at posttreatment assessments. Program completers lost an average of 5.2 ± 4.9% of initial body weight (dz = 1.14), whereas intent-to-treat analyses show a mean loss of 4.1 ± 4.7%. Participants reported high satisfaction, effectiveness, and cultural appropriateness. Exploratory analyses of neurocognitive domains suggested that crystalized cognition was higher among completers, and higher baseline cognitive flexibility predicted greater %WL (ß = .34, p = .05). ABT resulted in clinically significant weight loss in an AI sample. A controlled trial of ABT in a larger, more diverse sample is warranted to determine whether (a) the findings are robust, generalizable, and/or superior to other treatments and (b) neurocognitive factors moderate outcomes.

Mapping sign-tracking and goal-tracking onto human behaviors.

As evidenced through classic Pavlovian learning mechanisms, environmental cues can become incentivized and influence behavior. These stimulus-outcome associations are relevant in everyday life but may be particularly important for the development of impulse control disorders including addiction. Rodent studies have elucidated specific learning profiles termed 'sign-tracking' and 'goal-tracking' which map onto individual differences in impulsivity and other behaviors associated with impulse control disorders' etiology, course, and relapse. Whereas goal-trackers are biased toward the outcome, sign-trackers fixate on features that are associated with but not necessary for achieving an outcome; a pattern of behavior that often leads to escalation of reward-seeking that can be maladaptive. The vast majority of the sign- and goal-tracking research has been conducted using rodent models and very few have bridged this concept into the domain of human behavior. In this review, we discuss the attributes of sign- and goal-tracking profiles, how these are manifested neurobiologically, and how these distinct learning styles could be an important tool for clinical interventions in human addiction.