No abstract

Many issues of interest to counseling psychologists involve questions regarding how individuals change over time. Although counseling psychologists often examine average levels of change, statistical methods can also identify patterns of change over time by empirically grouping together individuals with similar patterns of change (e.g., group-based trajectory modeling and latent growth mixture modeling). The purpose of this article is to provide an overview of these methods for counseling psychologists. We discuss the conceptual frameworks and assumptions of average-level and person-centered techniques such as group-based trajectory modeling and latent growth mixture modeling. We provide a nontechnical guide for conducting these analyses using data from a study of psychotherapy outcomes in a sample of mental health center clients ( N = 1,050). We discuss caveats associated with these methods, including the potential for overinterpreting nongeneralizable results. Last, we suggest best practices for reporting and interpreting results.

We assessed PTSD prevalence and symptoms as a function of whether participants’ worst lifetime event met Criterion A1 for PTSD (DSM-IV-TR; APA, 2000) and whether the event was directly or indirectly experienced in a community sample of adult women (N = 884). Exposure to both non-Criterion A1 and Criterion A1 events was systematically assessed. PTSD was assessed with regard to participants’ self-nominated worst event using the PTSD module of the SCID-I/NP (First, Spitzer, Gibbon, & Williams, 1997). There were no differences in PTSD prevalence rates between Criterion A1 and non-A1 events; however, directly-experienced worst events were significantly more likely to meet PTSD criteria than were indirectly-experienced worst events. Non-Criterion A1 and directly-experienced worst events were associated with significantly more PTSD symptoms than were Criterion A1 or indirectly-experienced events, respectively. Criterion A2 (experiencing fear, helplessness, or horror) had little effect on PTSD rates.

Potentially morally injurious events (PMIEs) entail acts of commission (e.g., cruelty, proscribed or prescribed violence) or omission (e.g., high stakes failure to protect others) and bearing witness (e.g., to grave inhumanity, to the gruesome aftermath of violence), or being the victim of others' acts of commission (e.g., high stakes trust violations) or omission (e.g., being the victim of grave individual or systemic failures to protect) that transgress deeply held beliefs and expectations about right and wrong. Although there is a proliferation of interest in moral injury (the outcome associated with exposure to PMIEs), there has been no operational definition of the putative syndrome and no standard assessment scheme or measure, which has hampered research and care in this area. We describe an international effort to define the syndrome of moral injury and develop and validate the Moral Injury Outcome Scale (MIOS) in three stages. To ensure content validity, in Stage I, we conducted interviews with service members, Veterans, and clinicians/Chaplains in each country, inquiring about the lasting impact of PMIEs. Qualitative analysis yielded six operational definitions of domains of impact of PMIEs and components within domains that establish the parameters of the moral injury syndrome. From the domain definitions, we derived an initial pool of scale items. Stage II entailed scale refinement using factor analytic methods, cross-national invariance testing, and internal consistency reliability analyses of an initial 34-item MIOS. A 14-item MIOS was invariant and reliable across countries and had two factors: Shame-Related (SR) and Trust-Violation-Related (TVR) Outcomes. In Stage III, MIOS total and subscale scores had strong convergent validity, and PMIE-endorsers had substantially higher MIOS scores vs. non-endorsers. We discuss and contextualize the results and describe research that is needed to substantiate these inaugural findings to further explore the validity of the MIOS and moral injury, in particular to examine discriminant and incremental validity.