Maternal Executive Functioning and Scaffolding in Families of Children with and without Parent-Reported ADHD.

Parental scaffolding robustly predicts child developmental outcomes, including improved self-regulation and peer relationships and fewer externalizing behaviors. However, few studies have examined parental characteristics associated with a parent's ability to scaffold. Executive functioning (EF) may be an important individual difference factor associated with maternal scaffolding that has yet to be examined empirically. Scaffolding may be particularly important for children with attention-deficit/hyperactivity disorder (ADHD) and disruptive behavior disorder (DBD) symptoms due to their core difficulties with inattention, disorganization, EF, and self-regulation, their need for greater parental structure, and higher-than-average rates of parental EF deficits. Yet, little research has examined child ADHD in relation to parental scaffolding. This cross-sectional study examined: (1) the association between maternal EF (as measured by the Hotel Test, Barkley's Deficits in Executive Functioning Scale, and Digit Span) and observed scaffolding, (2) the association between parent-reported child ADHD/DBD symptoms and scaffolding, and (3) the interaction between child ADHD/DBD symptoms and maternal EF in predicting scaffolding. In a sample of 84 mothers and their 5-10 year-old biological children (62% male) with and without parent-reported ADHD, we found that maternal EF, as measured by Digit Span and the Hotel Test, predicted observed maternal scaffolding. However, child ADHD/DBD symptoms did not significantly predict maternal scaffolding controlling for child age, maternal education, and maternal EF, nor did the interaction of maternal EF and parent-reported child ADHD/DBD symptoms. Working memory and task shifting may be key components of parental EF that could be targeted in interventions to improve parental scaffolding.

Crowdsourcing prior information to improve study design and data analysis.

Though Bayesian methods are being used more frequently, many still struggle with the best method for setting priors with novel measures or task environments. We propose a method for setting priors by eliciting continuous probability distributions from naive participants. This allows us to include any relevant information participants have for a given effect. Even when prior means are near-zero, this method provides a principle way to estimate dispersion and produce shrinkage, reducing the occurrence of overestimated effect sizes. We demonstrate this method with a number of published studies and compare the effect of different prior estimation and aggregation methods.

Order-constrained linear optimization.

Despite the fact that data and theories in the social, behavioural, and health sciences are often represented on an ordinal scale, there has been relatively little emphasis on modelling ordinal properties. The most common analytic framework used in psychological science is the general linear model, whose variants include ANOVA, MANOVA, and ordinary linear regression. While these methods are designed to provide the best fit to the metric properties of the data, they are not designed to maximally model ordinal properties. In this paper, we develop an order-constrained linear least-squares (OCLO) optimization algorithm that maximizes the linear least-squares fit to the data conditional on maximizing the ordinal fit based on Kendall's τ. The algorithm builds on the maximum rank correlation estimator (Han, 1987, Journal of Econometrics, 35, 303) and the general monotone model (Dougherty & Thomas, 2012, Psychological Review, 119, 321). Analyses of simulated data indicate that when modelling data that adhere to the assumptions of ordinary least squares, OCLO shows minimal bias, little increase in variance, and almost no loss in out-of-sample predictive accuracy. In contrast, under conditions in which data include a small number of extreme scores (fat-tailed distributions), OCLO shows less bias and variance, and substantially better out-of-sample predictive accuracy, even when the outliers are removed. We show that the advantages of OCLO over ordinary least squares in predicting new observations hold across a variety of scenarios in which researchers must decide to retain or eliminate extreme scores when fitting data.

Comparing Multi-Informant Assessment Measures of Parental Monitoring and Their Links with Adolescent Delinquent Behavior.

OBJECTIVE: Parents' poor monitoring of adolescents' whereabouts and activities is commonly linked to adolescents' increased engagement in delinquent behaviors. Yet, different domains of parental monitoring (parental monitoring behaviors vs. parental knowledge) and reports from multiple informants (parent vs. adolescent) may vary in their links to delinquent behavior. DESIGN: Seventy-four parental caregivers and 74 adolescents completed survey measures of parental monitoring and knowledge, and adolescents completed self-report surveys of delinquent behavior. RESULTS: We observed low-to-moderate magnitudes of correspondence between parent- and adolescent-reports of parental monitoring behaviors and parental knowledge. Adolescent self-reported delinquent behavior related to parent and adolescent reports of parental monitoring behaviors and parental knowledge, with adolescents who self-reported engagement in delinquent behaviors evidencing lower levels of parental knowledge and higher levels of poor monitoring compared to adolescents who did not self-report engagement in delinquent behaviors. Adolescent self-reported engagement in delinquent behaviors evidenced stronger links to parental monitoring when based on adolescent reports of monitoring (relative to parent reports), whereas stronger links held between adolescent self-reported delinquent behavior and parental knowledge when based on parent reports of knowledge (relative to adolescent reports). CONCLUSIONS: Links between monitoring and adolescents' delinquent behavior vary by the kind of monitoring measure completed as well as the informant completing the measure. These findings inform measurement selection in research and clinical assessments of parental monitoring and adolescent delinquent behavior.

Psychological resilience: the impact of affectivity and coping on state anxiety and positive emotions during and after the Washington, DC sniper killings.

This research examined the impact of affectivity and coping on state anxiety and positive emotions among young adults living in the Washington, DC metro area both during and after the Washington, DC sniper killings. Participants completed questionnaires during three waves of data collection: (1) during the sniper attacks (n=92); (2) within two weeks after the snipers were captured (n=45); and (3) six months later (n=43). Affectivity (measured by neuroticism) was significantly associated with state anxiety and positive emotions during all three time periods. Coping (measured by constructive thinking) predicted state anxiety and positive emotions during the shootings, but was unrelated to either outcome immediately after the attacks, and marginally related to them six months later. Consistent with the Dynamic Model of Affect, state anxiety and positive emotions were more strongly (and negatively) correlated with each other during the killings than they were after the snipers were apprehended. Taken together, these results support transactional models of stress that emphasize the interaction between dispositional and situational influences, and they suggest that affectivity reflects a fundamental set of reactions to one's environment, while coping dispositions result in more stress-specific responses. Additional theoretical and practical implications of these findings are also discussed.

The cognitive processing of somatic anxiety: using functional measurement to understand and address the fear of pain

Although anxiety has both dispositional and situational determinants, little is known about how individuals’ anxiety-related sensitivities and their expectations about stressful events combine to determine anxiety. This research used Information Integration Theory and Functional Measurement to assess how participants’ anxiety sensitivity and event expectancy are cognitively integrated to determine their anxiety about physical pain. Two studies were conducted—one with university students and one with anxiety clinic patients—in which participants were presented with multiple scenarios of a physically painful event, each representing a different degree of event probability, from which subjective expectancies were derived. Independent variables included anxiety sensitivity (low, moderate, high) and event expectancy (low, medium, high, no probability information). Participants were asked to indicate their anxiety (dependent measure) in each expectancy condition in this 3 X 4 mixed, quasi-experimental design. The results of both studies strongly suggest that anxiety sensitivity and event expectancy are integrated additively to produce somatic anxiety. Additional results and their implications for the treatment of anxiety-related disorders are also discussed(AU)