Early in-session predictors of response to trauma-focused cognitive therapy

Volume 1 of this thesis examines the predictors of response to trauma-focused treatment for posttraumatic stress disorder (PTSD). It is presented in three parts. Part 1 is a literature review of research evaluating the impact of trauma-focused therapy for PTSD on comorbid symptoms of depression. The Downs and Black (1998) checklist was used to assess study quality. Results indicated that both trauma-focused CBT and EMDR treatments were effective in reducing comorbid depression symptoms. However, as interventions varied widely and some studies were affected by significant methodological problems, the generalisability of these results may be limited, and thus areas for further research are also suggested. Part 2 is an empirical study exploring early in-session client and therapist factors that predict later response to treatment. Audio and video recordings of the first or second therapy session of 54 known treatment responders or non-responders were blind-rated for client perseverative thinking, therapist adherence and therapeutic alliance. Results revealed that more perseverative thinking was observed for non-responders than responders to treatment. No group differences were found in regards to therapist adherence or therapeutic alliance. Exploratory analyses revealed that across the sample as a whole, perseverative thinking was associated with reduced therapist adherence to the treatment manual and poorer therapeutic alliance. As this study is one of the first of its kind in this area, recommendations were made for future research opportunities to explore these findings further. Part 3 is a critical appraisal of the empirical study. This elaborates on the main findings of this project and discusses the methodological challenges involved in undertaking this type of research, particularly developing and applying a novel coding frame

The Food and Shelter Initiative: Final Report

Summarizes the foundation's two-year initiative to prevent homelessness and hunger in the Greater Boston area. Highlights grantees' direct assistance to the homeless and lessons learned, and assesses short-term and long-term solutions

Religious Support in a Defense Support of Civil Authorities (DSCA) Environment

To layout a strategic overview of Religious Support in a Defense Support of Civil Authorities (DSCA) environment for the Illinois National Guard focusing on geographic separation, organizational abandonment and continuity of care during a projected 7.7 magnitude earthquake

Identifying Fake News using Emotion Analysis

This paper presents research applying Emotional Analysis to “Fake News” and “Real News” articles to investigate whether or not there is a difference in the emotion used in these two types of news articles. The paper reports on a dataset for Fake and Real News that we created, and the natural language processing techniques employed to process the collected text. We use a lexicon that includes predefined words for eight emotions (anger, anticipation, disgust, fear, surprise, sadness, joy, trust) to measure the emotional impact in each of these eight dimensions. The results of the emotion analysis are used as features for machine learning algorithms contained in the Weka package to train a classifier. This classifier is then used to analyze a new document to predict/classify it to be “Fake” or “Real” News