Latent Factor Structure and Construct Validity of the Cognitive Emotion Regulation Questionnaire-Short Form Among Two PTSD Samples

Artificial Neural Networks for Short-Form Development of Psychometric Tests: A Study on Synthetic Populations Using Autoencoders

Short-form development is an important topic in psychometric research, which requires researchers to face methodological choices at different steps. The statistical techniques traditionally used for shortening tests, which belong to the so-called exploratory model, make assumptions not always verified in psychological data. This article proposes a machine learning-based autonomous procedure for short-form development that combines explanatory and predictive techniques in an integrative approach. The study investigates the item-selection performance of two autoencoders: a particular type of artificial neural network that is comparable to principal component analysis. The procedure is tested on artificial data simulated from a factor-based population and is compared with existent computational approaches to develop short forms. Autoencoders require mild assumptions on data characteristics and provide a method to predict long-form items' responses from the short form. Indeed, results show that they can help the researcher to develop a short form by automatically selecting a subset of items that better reconstruct the original item's responses and that preserve the internal structure of the long-form.

Predictors of treatment completion in group psychotherapy for male veterans with posttraumatic stress disorder

Group therapy is a frequently used therapy format for posttraumatic stress disorder (PTSD). However, factors contributing to treatment completion remain understudied. The current study examined predictors of treatment completion, defined as having completed 10 out of 14 sessions within 16 weeks, in veterans with PTSD who engaged in a hybrid efficacy-effectiveness randomized controlled trial of group psychotherapy for PTSD. Veterans (N = 198) were randomly assigned to 14 sessions of either group cognitive behavioral treatment (GBCT; n = 98) or group present-centered treatment (GPCT; n = 100). Four primary domains of predictors were examined, encompassing sociodemographic factors, the severity of PTSD and comorbid conditions, modifiable predictors, and treatment condition. Multilevel binomial logistic regression models following the Fournier analysis approach were used to examine significant predictors within domains, which were then included in a final model. Overall, 70.7% of participants completed treatment (GCBT = 61.6%, GPCT = 79.8%). Participants in the GPCT condition were 2.389 times, 95% CI [1.394, 4.092], more likely to complete treatment than those in the GCBT condition. Older age, a higher income and level of educational attainment, more lifetime and current mental health diagnoses, and higher use of positive reappraisal ER skills predicted treatment completion. Higher levels of depressive symptoms, cumulative trauma burden, and use of positive refocusing ER skills predicted treatment noncompletion. These findings are discussed in the context of current clinical and research practices for examining treatment noncompletion, with attention to the inclusion of translational predictors.

Rumination in posttraumatic stress disorder: A systematic review

Initial models and empirical investigations of rumination in the clinical literature were predominantly in the domain of depression. However, rumination is now well-established as a transdiagnostic cognitive process, including in the context of posttraumatic stress. To clarify the current understanding of rumination in posttraumatic stress, we conducted a systematic review of the empirical literature on rumination in posttraumatic stress disorder (PTSD). Six sub-groups of studies on this topic were identified; these addressed: (i) the frequency and nature of rumination, (ii) cross-sectional relationships between rumination and PTSD symptoms, (iii) the capacity of rumination to predict PTSD longitudinally, (iv) other processes associated with rumination, (v) neurobiological correlates of rumination, and (vi) whether treating PTSD reduces rumination. This review synthesizes these domains of research and identifies key methodological limitations which limit causal inferences, and points to important areas of future research to advance knowledge on rumination in PTSD.