Adapting Cognitive Processing Therapy to Treat Co-Occurring Posttraumatic Stress Disorder and Mild Traumatic Brain Injury: A Case Study

This case study aims to provide evidence for the effectiveness of adapting a particular manualized cognitive behavioral therapy intervention to treat co-occurring posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI). This study presents the treatment of a woman who experienced co-occurring mTBI and PTSD following a motor vehicle accident, a dual diagnosis that was established through a flexible assessment approach involving interviews as well as standardized psychological, neuropsychological, and neurobehavioral testing. Treatment planning led to a-priori adaptation of Cognitive Processing Therapy (CPT) to treat both her PTSD symptoms and the sequelae associated with her mTBI. The therapist maintained fidelity to the manualized structure and content of CPT protocol, adapting portions of the treatment to add specific emphasis on issues of identity confusion and role loss in service of addressing these common functional impairments that can accompany mTBI. Discussion focuses on application of CPT for future treatment of comorbid PTSD and TBI amidst complicating factors, including role losses and medical and safety issues. This case study is especially relevant due to the prevalence of co-occurring PTSD and TBI across a variety of populations.     

Working with Research Integrity—Guidance for Research Performing Organisations: The Bonn PRINTEGER Statement

This document presents the Bonn PRINTEGER Consensus Statement: Working with Research Integrity—Guidance for research performing organisations. The aim of the statement is to complement existing instruments by focusing specifically on institutional responsibilities for strengthening integrity. It takes into account the daily challenges and organisational contexts of most researchers. The statement intends to make research integrity challenges recognisable from the work-floor perspective, providing concrete advice on organisational measures to strengthen integrity. The statement, which was concluded February 7th 2018, provides guidance on the following key issues:

1. § 1.
   Providing information about research integrity
    
2. § 2.
   Providing education, training and mentoring
    
3. § 3.
   Strengthening a research integrity culture
    
4. § 4.
   Facilitating open dialogue
    
5. § 5.
   Wise incentive management
    
6. § 6.
   Implementing quality assurance procedures
    
7. § 7.
   Improving the work environment and work satisfaction
    
8. § 8.
   Increasing transparency of misconduct cases
    
9. § 9.
   Opening up research
    
10. § 10.
    Implementing safe and effective whistle-blowing channels
     
11. § 11.
    Protecting the alleged perpetrators
     
12. § 12.
    Establishing a research integrity committee and appointing an ombudsperson
     
13. § 13.
    Making explicit the applicable standards for research integrity
     

     

Ego depletion improves insight

Initial acts of self-control can reduce effort and performance on subsequent tasks – a phenomenon known as ego depletion. Ego depletion is thought to undermine the capacity or willingness to engage executive control, an important determinant of success for many tasks. We examined whether ego depletion improves performance on a task that favours less executive control: insight problem solving. In two experiments, participants completed an ego-depletion manipulation or a non-depleting control condition followed by an insight problem-solving task (i.e., matchstick arithmetic). Participants in the depleting condition demonstrated greater insight problem-solving accuracy than those in the non-depleting control condition. Priming theories of willpower did not impact these results. Although ego depletion is widely regarded as a “state of impairment”, attendant decreases in executive control may foster insightful thinking.     

The Impact of Home Ownership on Life Satisfaction in Urban China: A Propensity Score Matching Analysis

China has implemented a series of socioeconomic reforms since 1978. One of the reforms allows urban residents to purchase their own houses rather than renting houses from state institutions which has resulted in a rapid increase in home ownership. This paper estimates the impact of home ownership on life satisfaction in urban China on the basis of the 2010 wave of the China General Social Survey. Special attention is paid to the methodological problem of confoundedness between the determinants of home ownership and life satisfaction. Propensity score matching (PSM) is applied to control it. The results show that PSM reduces upward estimation bias caused by confoundedness and that it is more appropriate to control confoundedness than ordered probit regression. The estimates furthermore indicate that home ownership has a significant positive impact on life satisfaction of medium- and high income urban residents. For low income urban residents, the impact is also positive, though insignificant. The outcomes connect to the objectives of national development policy and thus have several important policy implications. First, the central and local governments, especially in provinces where it is still low, may want to continue stimulating home ownership as it enhances life satisfaction. Secondly, specific programs may be designed to make home ownership financially affordable for low income groups. Thirdly, local governments may want to initiate or intensify urban (renewal) programs to improve poor public facilities including public transportation, green space and sports accommodations in the immediate vicinity of depressing low income neighborhoods.     

Health-related quality of life in transgender adolescents: Associations with body image and emotional and behavioral problems

Background: Transgender adolescents who apply for treatment often experience a marked increase in body-related distress when entering puberty, accompanied by internalizing problems and poor peer relations. Although adolescence is a time of considerable psychosocial and physical change, generally associated with a decline in health-related quality of life (HRQoL), research on HRQoL in transgender youth and possible predictors is sparse. This study thus aims to explore the predictive value of body image factors and emotional and behavioral problems for HRQoL.

Methods: This cross-sectional one-group observational study was carried out at the Child and Adolescent psychiatric department (Gender Identity Service) in Hamburg, Germany. A sample of n = 126 (103 trans male and 23 trans female) adolescents, who were referred for counseling and/or treatment completed different standardized instruments before undergoing any sort of treatment. Firstly, five dimensions of HRQoL were explored in transgender adolescents and secondly, a linear regression model was applied to assess the impact of body image and emotional and behavioral problems on overall HRQoL.

Results: HRQoL was generally impaired in transgender adolescents compared to norm scores, especially with regard to aspects of psychological and physical well-being. Linear regression analysis revealed that greater internalizing problems and less body satisfaction significantly predicted lower HRQoL outcomes.

Conclusions: Impaired HRQoL may be explained by high degrees of internalizing problems and low body satisfaction. Thus, one important aim of mental health professionals working with youth should be to provide appropriate treatment and counseling options that may contribute to overall well-being in the long-term.     

Retrieving relevant factors with exploratory SEM and principal-covariate regression: A comparison

Behavioral researchers often linearly regress a criterion on multiple predictors, aiming to gain insight into the relations between the criterion and predictors. Obtaining this insight from the ordinary least squares (OLS) regression solution may be troublesome, because OLS regression weights show only the effect of a predictor on top of the effects of other predictors. Moreover, when the number of predictors grows larger, it becomes likely that the predictors will be highly collinear, which makes the regression weights’ estimates unstable (i.e., the “bouncing beta” problem). Among other procedures, dimension-reduction-based methods have been proposed for dealing with these problems. These methods yield insight into the data by reducing the predictors to a smaller number of summarizing variables and regressing the criterion on these summarizing variables. Two promising methods are principal-covariate regression (PCovR) and exploratory structural equation modeling (ESEM). Both simultaneously optimize reduction and prediction, but they are based on different frameworks. The resulting solutions have not yet been compared; it is thus unclear what the strengths and weaknesses are of both methods. In this article, we focus on the extents to which PCovR and ESEM are able to extract the factors that truly underlie the predictor scores and can predict a single criterion. The results of two simulation studies showed that for a typical behavioral dataset, ESEM (using the BIC for model selection) in this regard is successful more often than PCovR. Yet, in 93% of the datasets PCovR performed equally well, and in the case of 48 predictors, 100 observations, and large differences in the strengths of the factors, PCovR even outperformed ESEM.