Identification of factors contributing to risk for PTSD is essential to inform prevention and intervention efforts. Intervention efforts should be targeted to students experiencing PTSD symptoms as they enter college.

Predictive models for recovering from alcohol use disorder (AUD) and identifying related predisposition biomarkers can have a tremendous impact on addiction treatment outcomes and cost reduction. Our sample (N = 1376) included individuals of European (EA) and African (AA) ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA) who were initially assessed as having AUD (DSM-5) and reassessed years later as either having AUD or in remission. To predict this difference in AUD recovery status, we analyzed the initial data using multimodal, multi-features machine learning applications including EEG source-level functional brain connectivity, Polygenic Risk Scores (PRS), medications, and demographic information. Sex and ancestry age-matched stratified analyses were performed with supervised linear Support Vector Machine application and were calculated twice, once when the ancestry was defined by self-report and once defined by genetic data. Multifeatured prediction models achieved higher accuracy scores than models based on a single domain and higher scores in male models when the ancestry was based on genetic data. The AA male group model with PRS, EEG functional connectivity, marital and employment status features achieved the highest accuracy of 86.04%. Several discriminative features were identified, including collections of PRS related to neuroticism, depression, aggression, years of education, and alcohol consumption phenotypes. Other discriminated features included being married, employed, medication, lower default mode network and fusiform connectivity, and higher insula connectivity. Results highlight the importance of increasing genetic homogeneity of analyzed groups, identifying sex, and ancestry-specific features to increase prediction scores revealing biomarkers related to AUD remission.

This study examined the prevalence rates of sexual violence revictimization during each year of college. In addition, the impact of key mental health concerns on these rates was investigated. Incoming first-year students at a large, urban university completed a survey about their exposure to incidences of sexual assault before college and about their mental health symptoms. During each subsequent spring semester, experiences of sexual assault and mental health symptoms were reassessed. The sample was limited to individuals who reported sexual assault for at least one time period ( N = 3,294). More than 60% of individuals who endorsed an initial incident of sexual assault reported no subsequent incidences, leading to an overall revictimization rate of 39.5%. Rates of revictimization were higher for those identifying as women, as compared to men, and those identifying as White, as compared to those identifying as Asian or “other.” Trauma-related distress and increased symptoms of alcohol use disorder (AUD) and depression were all related to a greater risk of experiencing revictimization. Given that experiencing an initial sexual assault greatly increases the risk of experiencing revictimization, and considering the notable prevalence rates of sexual assault on college campuses, it is imperative to examine trends in revictimization throughout the course of college. Examining factors that increase risk for experiencing revictimization is crucial to developing university-wide effective prevention and intervention efforts. In addition to the efforts to increase the reporting of incidences of sexual assault, universal programming efforts should also focus on factors that promote resilience in the face of sexual assault, such as reducing risky drinking behavior, increasing social support, and reducing stigma around the reporting of mental health symptoms.

The Campbell Collaboration was founded on the principle that systematic reviews on the effects of interventions will inform and help improve policy and services. Campbell offers editorial and methodological support to review authors throughout the process of producing a systematic review. A number of Campbell's editors, librarians, methodologists and external peer reviewers contribute. Plain language summaryInterventions to reduce homelessness and improve housing stability are effectiveThere are large numbers of homeless people around the world. Interventions to address homelessness seem to be effective, though better quality evidence is required. What is this review about?There are large numbers of homeless people around the world. Recent estimates are over 500,000 people in the USA, 100,000 in Australia and 30,000 in Sweden. Efforts to combat homelessness have been made on national levels as well as at local government levels.This review assesses the effectiveness of interventions combining housing and case management as a means to reduce homelessness and increase residential stability for individuals who are homeless, or at risk of becoming homeless. What is the aim of this review?This Campbell systematic review examines the effectiveness of interventions to reduce homelessness and increase residential stability for individuals who are homeless, or at risk of becoming homeless. Forty-three studies were included in the review, 37 of which are from the USA. What studies are included?Included studies were randomized controlled trials of interventions for individuals who were already, or at-risk of becoming, homeless, and which measured impact on homelessness or housing stability with follow-up of at least one year.A total of 43 studies were included. The majority of the studies (37) were conducted in the United States, with three from the United Kingdom and one each from Australia, Canada, and Denmark. 6The Campbell Collaboration | www.campbellcollaboration.org What are the main findings of this review?Included interventions perform better than the usual services at reducing homelessness or improving housing stability in all comparisons. These interventions are: These interventions seem to have similar beneficial effects, so it is unclear which of these is best with respect to reducing homelessness and increasing housing stability. What do the findings of this review mean?A range of housing programs and case management interventions appear to reduce homelessness and improve housing stability, compared to usual services.However, there is uncertainty in this finding as most the studies have risk of bias due to poor reporting, lack of blinding, or poor randomization or allocation concealment of participants. In addition to the general need for better conducted and reported studies, there are specific gaps in the research with respect to: 1) disadvantaged youth; 2) abstinence-contingent housing with case management or day treatment; 3) non-abstinence contingent housing comparing group vs independent living; 4) Hous...

Relatively little is known about the possible effects of personalized genetic risk information on smoking, the leading preventable cause of morbidity and mortality. We examined the acceptability and potential behavior change associated with a personalized genetically informed risk tool (RiskProfile) among current smokers. Current smokers (n = 108) were enrolled in a pre-post study with three visits. At visit 1, participants completed a baseline assessment and genetic testing via 23andMe. Participants’ raw genetic data (CHRNA5 variants) and smoking heaviness were used to create a tailored RiskProfile tool that communicated personalized risks of smoking-related diseases and evidence-based recommendations to promote cessation. Participants received their personalized RiskProfile intervention at visit 2, approximately 6 weeks later. Visit 3 involved a telephone-based follow-up assessment 30 days after intervention. Of enrolled participants, 83% were retained across the three visits. Immediately following intervention, acceptability of RiskProfile was high (M = 4.4; SD = 0.6 on scale of 1 to 5); at 30-day follow-up, 89% of participants demonstrated accurate recall of key intervention messages. In the full analysis set of this single-arm trial, cigarettes smoked per day decreased from intervention to 30-day follow-up [11.3 vs. 9.8; difference = 1.5; 95% confidence interval (0.6–2.4); P = 0.001]. A personalized genetically informed risk tool was found to be highly acceptable and associated with a reduction in smoking, although the absence of a control group must be addressed in future research. This study demonstrates proof of concept for translating key basic science findings into a genetically informed risk tool that was used to promote progress toward smoking cessation. Prevention Relevance: This study demonstrates that personal genetic information can be incorporated into a risk feedback tool that was highly acceptable to current smokers and associated with reductions in smoking. These findings may pave the way for effectiveness and implementation research on genetically-informed behavior change interventions to enhance cancer prevention efforts.