Compassion Satisfaction,Compassion Fatigue,and Burnout: A Replication Study with Victim Advocates

Abstract

Past research has investigated the rates of compassion satisfaction (CS), compassion fatigue (CF), and burnout within health-care providers. Findings indicate higher levels of CS and lower levels of CF predict lower rates of burnout. The current study extended prior research by replicating past research findings, but with victim advocates. This study enrolled a national sample of 142 victim advocates. A hierarchal linear regression was run to test the research questions. In level 1, years of experience was not significant and only accounted for 1.1% of the variance in burnout. When adding CS, the model became significant (p?<?.001) and CS accounted for an additional 51.8% of the variance. When CF was added to the final model, it was significant (p?<?.001), and accounted for an additional 19.3% of the variance. When comparing the findings to past studies, our findings were similar; however, our study did find that CS and CF accounted for significantly more variance than past studies with health-care providers. Therefore, CS and CF might be greater predictors of burnout in victim advocates than in health-care providers. Future studies should aim to create interventions to increase CS and decrease CF, to reduce burnout.     

A Bayesian approach for generalized linear models with explanatory biomarker measurement variables subject to detection limit: an application to acute lung injury

Biomarkers have the potential to improve our understanding of disease diagnosis and prognosis. Biomarker levels that fall below the assay detection limits (DLs), however, compromise the application of biomarkers in research and practice. Most existing methods to handle non-detects focus on a scenario in which the response variable is subject to the DL; only a few methods consider explanatory variables when dealing with DLs. We propose a Bayesian approach for generalized linear models with explanatory variables subject to lower, upper, or interval DLs. In simulation studies, we compared the proposed Bayesian approach to four commonly used methods in a logistic regression model with explanatory variable measurements subject to the DL. We also applied the Bayesian approach and other four methods in a real study, in which a panel of cytokine biomarkers was studied for their association with acute lung injury (ALI). We found that IL8 was associated with a moderate increase in risk for ALI in the model based on the proposed Bayesian approach.     

Childhood Sexual Abuse Severity Reconsidered: A Factor Structure of CSA Characteristics

To address the lack of empirically grounded measures of childhood sexual abuse severity, a survey of self-report items was developed following a thorough review of the childhood sexual abuse literature. An exploratory factor analysis was conducted using data collected from a convenience sample of college students that included 275 females and males with a history of childhood sexual abuse. The solution produced seven factors interpreted as the following: (a) less intrusive forms of childhood sexual abuse (e.g., sexual invitations, kissing), (b) more intrusive forms of childhood sexual abuse (e.g., oral sex, intercourse), (c) humiliation/fear, (d) childhood sexual abuse involving photography, (e) familiarity with the perpetrator, (f) physical force/rape, and (g) active digital penetration. Correlations among these factors further suggested the existence of two relatively independent second-order factors, one based on the levels of physical intrusiveness and the other composed of the psychological/emotional factors. While arguably the most common measurement of severity, physical intrusiveness had little association with critical factors such as humiliation, fear, and association with the perpetrator. Consequently, physical intrusiveness appears to be an inadequate stand-alone measure of childhood sexual abuse severity. These results are proposed to lay the groundwork for an improved, more comprehensive measure of childhood sexual abuse severity.     

Trauma-informed care training in a child welfare system: Moving it to the front line

The use of trauma-informed practices in the child welfare system is critically important to prevent system-induced trauma and encourage timely assessment, triage and referral for care when indicated. Ultimately, such measures have the potential over time to decrease the risk for mental health problems in children exposed to a trauma. This study evaluates an initiative in Arkansas to train child welfare front-line staff members in trauma-informed care practices. We evaluated the impact of the training on knowledge and use of trauma-informed care practices among three types of child welfare staff (Caseworkers, Program Assistants and Other front-line staff). Results suggest that this training process was highly successful in improving knowledge of trauma-informed care practices, especially among staff with the least formal education and training. We also found a significant increase in staff use of trauma-informed care practices at the three-month follow-up with little difference observed across staff groups. Barriers that may prevent staff from full implementation of training concepts are described and strategies to address barriers are proposed.