Let's face it: video conferencing psychotherapy requires the extensive use of ostensive cues

The COVID-19 crisis has required many therapists to switch to video conferencing psychotherapy (VCP). Knowledge about the importance of epistemic trust and its determinants has been accumulating over the last few years, with important implications for psychotherapy and specific significance for the transition to VCP. The present paper provides a brief background on the concept of epistemic trust, research on the determinants of its development and the integrative framework it provides for some traditional concepts in psychotherapy, such as the therapeutic alliance. In particular, research on ostensive cuing, which requires significant modification in a remote delivery context, has important implications in the transition to VCP. We will advance some suggestions while illustrating the ideas with clinical case studies. This knowledge may be of value to psychotherapists, who are required to make substantial changes in the nature of the encounter with their patients, and may help them identify benefits and hindrances that might arise from this transition, as well as pointing out techniques that may encourage effective adaptation to the change

Psychological Impact of Coronavirus Disease 2019 Among Italians During the First Week of Lockdown

Pandemics and government-mandated quarantining measures have a substantial impact on mental health. This study investigated the psychological impact of the coronavirus disease 2019 (COVID-19) crisis on Italian residents during the first week of government-imposed lockdown and the role of defense mechanisms as protective factors against distress. In this cross-sectional study, 5,683 Italians responded to an online survey assessing socio-demographics, overall psychological distress, post-traumatic symptoms, and defense mechanisms using validated measures as the Symptom Checklist-90 (SCL-90), the Impact of Event Scale-Revised (IES-R), and the Defense Mechanisms Rating Scale-Self-Report-30 (DMRS-SR-30). Data were collected from March 13 to March 18, within the first week of lockdown in Italy. Results showed that younger age and female gender were associated with increased psychological distress. Having positive cases nearby, more days on lockdown, and having to relocate were also associated with greater distress. Higher overall defensive functioning (ODF) was associated with lower levels of depression (r = −.44, 95% CI −0.48, −0.40), anxiety (r = −.38, 95% CI −0.42, −0.35), and post-traumatic stress symptoms (PTSS) (r = −.34, 95% CI −0.38, −0.30). Conversely, less adaptive defensive functioning was related to greater affective distress across all domains. Each increased unit of ODF decreased the chances of developing post-traumatic stress symptoms (PTSS) by 71% (odds ratio = 0.29, p < 0.001, 95% CI.026,.032). The psychological impact of COVID-19 among Italians during the early weeks of government lockdown has been significant. The pandemic continues to have extraordinary mental health impact as it moves across the globe. Given the salience of defensive functioning in psychological distress, consideration of interventions that foster the use of more adaptive defenses may be an important component of building resilience amidst a pandemic

Educational psychology in latin america: with linear hierarchical models

Research in clinical psychology, since its inception, has been aimed at analyzing, predicting and explaining the effect of treatments, by studying the change of patients in the course of them. To study the effects of therapy, research based on quantitative analysis models has historically used classical methods of parametric statistics, such as Pearson correlations, least squares regressions Student’s T-Tests and Variance Analysis (ANOVA). Hierarchical linear models (HLMs) represent a fundamental statistical strategy for research in psychotherapy, as they allow to overcome dependence on the observations usually presented in your data. The objective of this work is to present a guide to understanding, applying and reporting HLMs to study the effects of psychotherapy

Intrusive Traumatic Re-Experiencing Domain (ITRED) – Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium

Background Intrusive Traumatic Re-Experiencing Domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods Data was collected from nine sites taking part in the ENIGMA-PTSD Consortium (n=584) and included itemized PTSD symptoms scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and Trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. Random forest classification model was built on a training set using cross-validation (CV), and the averaged CV model performance for classification was evaluated using area-under-the-curve (AUC). The model was tested using a fully independent portion of the data (test dataset), and the test AUC was evaluated. Results RsFC signatures differentiated TE-only participants from PTSD and from ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and from ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontal-parietal network, differentiated TE-only participants from one group (PTSD or ITRED-only), but to a lesser extent from the other. Conclusion Neural network connectivity supports ITRED as a novel neurobiologically-based approach to classifying post-trauma psychopathology

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder:a mega-analysis by the ENIGMA-PGC PTSD workgroup

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p -FDR &lt; 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.</p

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder:a mega-analysis by the ENIGMA-PGC PTSD workgroup

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p -FDR &lt; 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.</p

Implementing precision methods in personalizing psychological therapies: barriers and possible ways forward

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: No data was used for the research described in the article.Highlights: • Personalizing psychological treatments means to customize treatment for individuals to enhance outcomes. • The application of precision methods to clinical psychology has led to data-driven psychological therapies. • Applying data-informed psychological therapies involves clinical, technical, statistical, and contextual aspects