Cognitive Behavioral Therapy for Bariatric Surgery Patients: Preliminary Evidence for Feasibility,Acceptability, and Effectiveness

Bariatric surgery is the most effective treatment for extreme obesity; however, 20% to 50% of patients begin to regain their weight within the first 1.5 to 2 years following surgery. Despite some psychosocial factors predicting postoperative weight loss and weight regain, psychosocial interventions are not routinely offered in bariatric surgery programs. In this paper, we describe a 6-session cognitive behavioral therapy (CBT) intervention for preoperative and postoperative bariatric surgery patients with maladaptive eating behaviors or thought patterns, which can be delivered either in person or by telephone. In addition, we describe a small pilot study (n = 8) designed to examine the feasibility and acceptability of the CBT intervention, as well as its effectiveness in improving eating pathology and psychosocial functioning. Most pilot study participants reported improvements in binge eating severity, emotional eating, and depression from pre- to posttreatment, and all participants provided positive qualitative feedback regarding the intervention.     

Latina Immigrant Victims of Interpersonal Violence in New Jersey: A Needs Assessment Study

Recent studies have stressed the seriousness of male-female intimate partner violence (MFIPV) suffered by Latina women and the need for more comprehensive and culturally sensitive services for this population. This article provides an overall understanding of the type and severity of abuse suffered by examining Latina victims in New Jersey, a state that has a remarkably diverse and numerous Latino population. Socio-economic and residence statuses are considered, and self-help seeking behaviors and the challenges of women's social isolation are addressed. In addition, risk factors related to MFIPV, such as substance abuse and witnessed/experienced violence in childhood, are explored. The understanding of these characteristics and risk factors are critical to the design of prevention and intervention programs.     

Effects of Abusive Parenting,Caretaker Arrests,and Deviant Behavior on Dating Violence Among Homeless Young Adults

Although dating violence is widespread among young adult homeless populations, its risk factors are poorly understood by scholars. To address this gap, this study uses a social learning theory to examine the effects of abusive parenting and caretaker arrests on dating violence among 172 homeless young adults. Results from path analyses revealed that child physical abuse and caretaker arrests were positively associated with engaging in a greater number of school fights, which, in turn, was strongly and positively correlated with participating in more deviant subsistence strategies (e.g., stealing) since being on the street. Young people who participated in a greater number of delinquent acts were more likely to report higher levels of dating violence. Study results highlight the extent of social learning within the lives of homeless young adults, which is evident prior to their leaving home and while they are on the street.     

Removing the own-race bias in face recognition by attentional shift using fixation crosses to diagnostic features: An eye-tracking study

Hills and Lewis (2011) have demonstrated that the own-race bias in face recognition can be reduced or even removed by guiding participants' attention and potentially eye movements to the most diagnostic visual features. Using the same old/new recognition paradigm as Hills and Lewis, we recorded Black and White participants' eye movements whilst viewing Black and White faces following fixation crosses that preceded the bridge of the nose (between the eyes) or the tip of the nose. White faces were more accurately recognized when following high fixation crosses (that preceded the bridge of the nose) than when following low fixation crosses. The converse was true for Black faces. These effects were independent of participant race. The fixation crosses attracted the first fixation but had less effect on other eye-tracking measures. Furthermore, the location of the first fixation was predictive of recognition accuracy. These results are consistent with an attentional allocation model of the own-race bias in face recognition and highlight the importance of the first fixation for face perception (cf. Hsiao & Cottrell, 2008).     

Reaching beyond spatial perception: Effects of intended future actions on visually guided prehension

Three experiments examined whether manipulating actors' intentions, regarding forthcoming actions, influences the time course and kinematics of visually guided, reach‐to‐grasp movements. Subjects performed two‐step action sequences where the initial movement always involved reaching for and grasping cubes located at a constant distance. Demands of the second movement were systematically manipulated. Although the spatial parameters (cube size and distance) remained constant across all conditions, the durations of the initial movements differed substantially depending on the actions subjects intended to perform once the objects were in hand. Less time was required to engage a small (1 cm³) cube when the intention was to transport it to a new location on the workspace vs. a large (4 cm³) cube when the goal was to merely lift it above its current resting position (Experiment 1). This difference in duration of the initial movement reflects more time spent in the deceleration phase of the reach when the task does not require transporting the cube to a new location on the workspace. Further, this context effect is not related to accuracy demands (Experiment 2), or complexity (Experiment 3) of the intended second movement. These findings demonstrate that actions are determined both by the perceived spatial demands of the immediate movement as well as the intended goal of the entire action sequence.     

Getting Luck Properly Under Control

This article proposes a new account of luck and how luck impacts attributions of credit for agents' actions. It proposes an analogy with the expected value of a series of wagers and argues that luck is the difference between actual outcomes and expected value. The upshot of the argument is that when considering the interplay of intention, chance, outcomes, skill, and actions, we ought to be more parsimonious in our attributions of credit when exercising a skill and obtaining successful outcomes, and more generous in our attributions of credit when exercising a skill but obtaining unsuccessful outcomes. Furthermore, the article argues that when agents skillfully perform an action, they deserve the same amount of credit whether their action is successful or unsuccessful in achieving the goal.     

Quantifying and Testing Indirect Effects in Simple Mediation Models When the Constituent Paths Are Nonlinear

Most treatments of indirect effects and mediation in the statistical methods literature and the corresponding methods used by behavioral scientists have assumed linear relationships between variables in the causal system. Here we describe and extend a method first introduced by Stolzenberg (1980) Stolzenberg, R. M. 1980. The measurement and decomposition of causal effects in nonlinear and nonadditive models.. Sociological Methodology, 11: 459–488. [Crossref] , [Google Scholar] for estimating indirect effects in models of mediators and outcomes that are nonlinear functions but linear in their parameters. We introduce the concept of the instantaneous indirect effect of X on Y through M and illustrate its computation and describe a bootstrapping procedure for inference. Mplus code as well as SPSS and SAS macros are provided to facilitate the adoption of this approach and ease the computational burden on the researcher.     

Addressing Moderated Mediation Hypotheses: Theory,Methods, and Prescriptions

This article provides researchers with a guide to properly construe and conduct analyses of conditional indirect effects, commonly known as moderated mediation effects. We disentangle conflicting definitions of moderated mediation and describe approaches for estimating and testing a variety of hypotheses involving conditional indirect effects. We introduce standard errors for hypothesis testing and construction of confidence intervals in large samples but advocate that researchers use bootstrapping whenever possible. We also describe methods for probing significant conditional indirect effects by employing direct extensions of the simple slopes method and Johnson-Neyman technique for probing significant interactions. Finally, we provide an SPSS macro to facilitate the implementation of the recommended asymptotic and bootstrapping methods. We illustrate the application of these methods with an example drawn from the Michigan Study of Adolescent Life Transitions, showing that the indirect effect of intrinsic student interest on mathematics performance through teacher perceptions of talent is moderated by student math self-concept.     

A Comparison of Multilevel Imputation Schemes for Random Coefficient Models: Fully Conditional Specification and Joint Model Imputation with Random Covariance Matrices

Abstract

Literature addressing missing data handling for random coefficient models is particularly scant, and the few studies to date have focused on the fully conditional specification framework and “reverse random coefficient” imputation. Although it has not received much attention in the literature, a joint modeling strategy that uses random within-cluster covariance matrices to preserve cluster-specific associations is a promising alternative for random coefficient analyses. This study is apparently the first to directly compare these procedures. Analytic results suggest that both imputation procedures can introduce bias-inducing incompatibilities with a random coefficient analysis model. Problems with fully conditional specification result from an incorrect distributional assumption, whereas joint imputation uses an underparameterized model that assumes uncorrelated intercepts and slopes. Monte Carlo simulations suggest that biases from these issues are tolerable if the missing data rate is 10% or lower and the sample is composed of at least 30 clusters with 15 observations per group. Furthermore, fully conditional specification tends to be superior with intraclass correlations that are typical of crosssectional data (e.g., ICC?=?.10), whereas the joint model is preferable with high values typical of longitudinal designs (e.g., ICC?=?.50).