Get the Message: Targeting Beliefs to Develop Risk Reduction Intervention Messages for African American Adolescents

Risk reduction interventions that promote condom use, a vital component of most HIV prevention interventions, have been successful in increasing condom use among African American adolescents. Understanding theoretical components that lead to behavior change and selecting relevant risk reduction messages remain important considerations for targeting new interventions and tailoring existing interventions. The present study sought to (1) identify the most important theoretical determinants of condom use intention in African American adolescent males and females, separately, using the integrative model of behavior prediction, and (2) identify underlying beliefs within the determinants that were good candidates for message development in similar interventions. Using 446 African American adolescents, multi‐group SEM indicated that the gender‐specific IM exhibited a better fit than the overall model. Specifically, the IM had a stronger capacity for predicting condom use intention and condom use behavior for adolescent boys. Using a specific criteria for message selection, specific condom use beliefs were discussed as potential candidate messages for both African American males and females.     

Age Moderates the Mediational Role of Empathy in the Association Between Gender and Forgiveness

Researchers have suggested that empathy may serve to explain, at least in part, the relationship between gender and forgiveness. Some findings in the literature have supported this claim, while other studies have not. Accounting for the variable of age might help to explain these inconsistencies, as age has been found to influence the expression of empathy across gender. As such, in the present study we examined whether age might exert a conditional indirect effect on the relationship between gender and forgiveness as mediated by empathy. Participants were recruited from the community (N?=?62) and on a college campus (N?=?94). Within the community sample the average age was 74.8, while on the college campus the average age was 20.7. Participants were given a survey packet that included the Heartland Forgiveness Scale and the Empathy Quotient Scale, among other instruments. A moderated-mediational analysis showed that while gender was related to empathy and empathy was associated with forgiveness, empathy served as a significant mediator only for those younger than 62 years of age. This finding suggests that empathy serves as an important mediator in the relationship between gender and forgiveness for adults aged 61 and younger, because younger women are more likely to respond empathetically to a transgressor as compared to younger men. Older women also tend to be more forgiving than older men, but in the present study empathy was not as important of a factor in explaining this relationship for individuals 62 years and older. These findings help to address the inconsistencies in the literature with regard to the relationships among gender, age, empathy, and forgiveness.     

Training Pediatric Psychologists for Perinatal Behavioral Health Services in a Pediatric Hospital

Although pediatric hospitals specialize in providing care to children and adolescents, at The Children’s Hospital of Philadelphia (CHOP), our team has been providing behavioral health services for two unique parent populations—parents with a child in the Newborn Infant Intensive Care Unit and pregnant women carrying fetuses with specific birth defects and receiving prenatal care in the Center for Fetal Diagnosis and Treatment. A new training program was developed to expand the scope of pediatric psychologists’ practice to include perinatal behavioral health services, specifically for these two unique parent populations served at CHOP. The program includes direct service provision for adult mental health concerns, as well as education and support to help families cope with the existing medical conditions. This article describes the training program and its implementation as a model of training for other pediatric hospitals. The roles of psychologists embedded in these units and hospital privileges are discussed.     

A meaningful embrace: Contingent effects of embodied cues of affection

Can a mere gesture lead to intimate product bonding? In this research, we find that affectionate gestures (e.g. hugging, stroking) can serve as routes to object attachment. We suggest that the mere execution of an affectionate gesture can generate emotional attachment, which translates into enhanced product attitudes. However, this effect is contingent on the existence of facilitating conditions via the presence of humanlike characteristics in the target object of the affectionate gesture.     

Confirmatory Factor Analysis (CFA), Exploratory Structural Equation Modeling (ESEM), and Set-ESEM: Optimal Balance Between Goodness of Fit and Parsimony

Abstract

CFAs of multidimensional constructs often fail to meet standards of good measurement (e.g., goodness-of-fit, measurement invariance, and well-differentiated factors). Exploratory structural equation modeling (ESEM) represents a compromise between exploratory factor analysis’ (EFA) flexibility, and CFA/SEM’s rigor and parsimony, but lacks parsimony (particularly in large models) and might confound constructs that need to be kept separate. In Set-ESEM, two or more a priori sets of constructs are modeled within a single model such that cross-loadings are permissible within the same set of factors (as in Full-ESEM) but are constrained to be zero for factors in different sets (as in CFA). The different sets can reflect the same set of constructs on multiple occasions, and/or different constructs measured within the same wave. Hence, Set-ESEM that represents a middle-ground between the flexibility of traditional-ESEM (hereafter referred to as Full-ESEM) and the rigor and parsimony of CFA/SEM. Thus, the purposes of this article are to provide an overview tutorial on Set-ESEM, juxtapose it with Full-ESEM, and to illustrate its application with simulated data and diverse “real” data applications with accessible, heuristic explanations of best practice.