Generalization of free-operant avoidance behavior in pigeons

Three groups of four pigeons, trained to press a treadle on a free-operant avoidance schedule, were given auditory discrimination training. Alternating 2-min components of avoidance and no shock were paired with either a tone or white noise. The pigeons were subsequently given two types of generalization tests, with and without avoidable shocks scheduled. Two of the groups, trained interdimensionally, produced excitatory and inhibitory generalization gradients along the tone frequency dimension. A predicted post-discrimination gradient was computed from the algebraic summation of these gradients of excitation and inhibition. The predicted gradient was compared with the actual post-discrimination gradient obtained from the third group of pigeons that had been given intradimensional discrimination training on the tone frequency dimension. The predicted postdiscrimination gradient agreed in shape with the empirical postdiscrimination gradient. The results in general support Spence's (1937) gradient interaction theory.     

An analysis-of-variance model for the intrasubject replication design

One- and two-way analysis-of-variance procedures are shown logically to be appropriate for testing hypotheses in successive treatment reversal designs for one-subject and N-subject experiments, respectively. The applicability of these designs is demonstrated through analyses of typical data.     

Electroencephalographic asymmetries in adolescents with major depression: influence of comorbidity with anxiety disorders

This study examined whether adolescents with major depressive disorder (MDD) display the abnormal electroencephalographic (EEG) alpha asymmetries found in depressed adults. Resting EEG was recorded in 25 right-handed female outpatients (19 with MDD, 11 of whom also had a current anxiety disorder; 6 with anxiety disorders only) and 10 non-ill controls. In contrast to the non-ill controls, adolescents having MDD but no anxiety disorder showed alpha asymmetry indicative of less activation over right than over left posterior sites. Within the MDD patient group, comorbid anxiety disorders reduced the posterior alpha asymmetry, supporting the potential importance of evaluating anxiety in studies of regional brain activation in adolescent MDD. These preliminary findings are similar to those from adult studies that suggest that MDD is associated with right parietotemporal hypoactivation.     

Islamic Trauma Healing: Integrating Faith and Empirically Supported Principles in a Community-Based Program

Access to adequate, much less state-of-the-art, mental health care is a global problem. Natural disasters, civil war, and terrorist conflict have forcibly displaced millions of Muslims and have resulted in a remarkable level of individual and communitywide trauma exposure. As a result, many are at risk for posttraumatic stress and other trauma-related disorders. Many religiously oriented Muslims traditionally rely on Islamic principles and teachings, as well as their community, to cope with and address trauma-related distress. Islamic Trauma Healing is a six-session, lay-led group intervention developed within a Somali Muslim community that integrates evidence-based trauma-focused cognitive-behavioral therapy principles with cultural and religious practices aimed to enhance uptake and create an easily up-scalable intervention for a wide range of trauma. In sessions, narratives of prophets who have undergone trauma (e.g., Prophet Ayyub, faith during hard times) present Islamic principles and facilitate cognitive shifts. Group members spend individual time turning to Allah in dua (i.e., informal prayer), focused on exposure to trauma memories. Program themes arc across suffering to healing to growth following trauma. This paper describes the core theoretical principles and methods in the Islamic Trauma Healing program. We also describe leader perspectives and the program’s train-the-trainer model, in which lay leaders are trained to further disseminate the program and allow Islamic Trauma Healing to be owned and sustained by the Muslim community.     

Effects of perceived weight discrimination on willingness to adopt unhealthy behaviours: influence of genomic information

Objective: Weight-based discrimination negatively influences health, potentially via increased willingness to engage in unhealthful behaviours. This study examines whether the provision of genomic obesity information in a clinical context can lead to less willingness to engage in unhealthy eating and alcohol consumption through a mediated process including reduced perceptions of blame and discrimination.

Design: A total of 201 overweight or obese women aged 20–50 interacted with a virtual physician in a simulated clinical primary care environment, which included physician-delivered information that emphasised either genomic or behavioural underpinnings of weight and weight loss.

Main Outcome Measures: Perceived blame and weight discrimination from the doctor, and willingness to eat unhealthy foods and consume alcohol.

Results: Controlling for BMI and race, participants who received genomic information perceived less blame from the doctor than participants who received behavioural information. In a serial multiple mediation model, reduced perceived blame was associated with less perceived discrimination, and in turn, lower willingness to eat unhealthy foods and drink alcohol.

Conclusion: Providing patients with genomic information about weight and weight loss may positively influence interpersonal dynamics between patients and providers by reducing perceived blame and perceived discrimination. These improved dynamics, in turn, positively influence health cognitions.     

Maximum likelihood estimation of latent interaction effects with the LMS method

In the context of structural equation modeling, a general interaction model with multiple latent interaction effects is introduced. A stochastic analysis represents the nonnormal distribution of the joint indicator vector as a finite mixture of normal distributions. The Latent Moderated Structural Equations (LMS) approach is a new method developed for the analysis of the general interaction model that utilizes the mixture distribution and provides a ML estimation of model parameters by adapting the EM algorithm. The finite sample properties and the robustness of LMS are discussed. Finally, the applicability of the new method is illustrated by an empirical example. This research has been supported by a grant from the Deutsche Forschungsgemeinschaft, Germany, No. Mo 474/1 and Mo 474/2. The data for the empirical example have been provided by Andreas Thiele of the University of Frankfurt, Germany. The authors are indebted to an associate editor and to three anonymous reviewers ofPsychometrika whose comments and suggestions have been very helpful.