Children’s Emotional Reactivity to Emotionally Evocative Stimuli: Associations With Internalizing Symptoms

Individual differences in emotional reactivity emerge early in development and predict important child outcomes. Unfortunately, methods used to assess these often fail to tap dynamic changes in emotion, obscuring nuanced relationships between maladaptive emotional reactivity and early internalizing psychopathology. We therefore explored the utility of an emerging, multimethod approach for examining children’s emotional reactivity. Thirty-nine children (22 girls; Mage = 7.19 years, SD = .76) viewed 11 video clips eliciting happiness, sadness, or fear. We used multilevel growth curve modeling to estimate change in children’s self-reported and observed emotion across clips of increasing potency. Higher anxious/depressive symptoms predicted steeper trajectories of child-rated happiness and lower happiness and fear toward low-intensity clips. Higher depressive symptoms predicted lower child-rated sadness toward a low-intensity clip. The limited associations between children’s symptoms and emotion ratings averaged across clips suggested that modeling child emotion across stimuli of varying intensity yields a valuable index of emotional reactivity

Development and validation of a battery of emotionally evocative film clips for use with young children

© 2019 American Psychological Association. Investigating normative and maladaptive emotional development requires the ability to elicit children\u27s reactivity to a range of affective stimuli. However, the field lacks a validated battery of stimuli tapping a broad range of childhood emotions. We therefore sought to validate a developmentally appropriate battery of emotionally evocative film stimuli, covering a range of affective responses, for use with children. During pilot work, clips were verified as age appropriate by parents of young children. Next, during a laboratory visit, 39 children (22 girls; Mage = 7.19 years, SD = .76) viewed 20 film clips thought likely to elicit either positive affect, dysphoria (i.e., sadness/anger), or fear, and provided self-reported emotional responses to clips. Children\u27s facial expressions during clips were also rated by trained coders blind to the intended purpose of the clips. We identified clips that successfully elicited the target emotion more so than nontarget emotions according to both coder ratings and child self-report. Implications for the use of these film clips in future research on child emotion are discussed

Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium

BackgroundDespite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC.MethodsLinkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals).ResultsPositive genetic correlation was observed between MD and AD (rg = + 0.47, P = 6.6 × 10 ). AC-quantity showed positive genetic correlation with both AD (rg = + 0.75, P = 1.8 × 10 ) and MD (rg = + 0.14, P = 2.9 × 10 ), while there was negative correlation of AC-frequency with MD (rg = -0.17, P = 1.5 × 10 ) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10 ). There was no evidence for reverse causation.ConclusionThis study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts