Literature Collection

INTRODUCTION: Quantitative global or regional brain imaging measurements, known as imaging-specific or -derived phenotypes (IDPs), are commonly used in genotype-phenotype association studies to explore the genomic architecture of the brain and how it may be affected by neurological diseases (e.g., Alzheimer's disease), mental health (e.g., depression), and neurodevelopmental disorders (e.g., attention-deficit hyperactivity disorder [ADHD]). For this purpose, medical images have been used as IDPs using a voxel-wise or global approach via principal component analysis. However, these methods have limitations related to multiple testing or the inability to isolate high variation regions, respectively. METHODS: To address these limitations, this study investigates a localized, principal component analysis-like approach for dimensionality reduction of cross-sectional T1-weighted MRI datasets utilizing diffeomorphic morphometry. This approach can reduce the dimensionality of images while preserving spatial information and enables the inclusion of spatial locality in the analysis. In doing so, this method can be used to explore morphometric brain changes across specific components and spatial scales of interest and to identify associations with genome regions in a multivariate genome-wide association study. For a first clinical feasibility study, this method was applied to data from the Adolescent Brain Cognitive Development (ABCD) study, including adolescents with ADHD (n = 1,359), obsessive-compulsive disorder (n = 1,752), and depression (n = 1,766). RESULTS: Meaningful associations of specific morphometric features with genome regions were identified with the data and corresponded to previous found brain regions in the respective mental health and neurodevelopmental disorder cohorts. DISCUSSION: In summary, the localized, principal component analysis-like approach can reduce the dimensionality of medical images while still being able to identify meaningful local brain region alterations that are associated with genomic markers across multiple scales. The proposed method can be applied to various image types and can be easily integrated in many genotype-phenotype association study setups.

Ohio is one of the hardest-hit states in the United States when it comes to opioid overdose deaths. Confronted with over 4,000 opioid overdose deaths in 2017, the Ohio Department of Mental Health and Addiction Services launched the Community Collective Impact Model for Change (CCIM4C) initiative to encourage 12 Ohio counties to think more deeply about primary prevention. By moving upstream and taking a look at the causes of the opioid crisis, the counties involved in the CCIM4C initiative were able to expand the range of potential partners and potential solutions, moving from emergency response alone to broader efforts to support social connection, economic security, and other social determinants of health. Each county brought together a wide array of partners, including local employers, community colleges, health care organizations, faith leaders, youth-serving organizations, first responders, librarians, school board members, public health officials, parks and recreation staff, and people with lived experience. This article focuses on the efforts of three counties-Ashtabula, Lorain, and Lawrence-to take on the community conditions that increase the risk of unhealthy substance use and addiction. It describes what they learned as they went beyond a sole focus on preventing opioid overdoses and deaths-as critically important as that is-to transforming their communities to support health and well-being in the first place.

There is a high prevalence of stimulant use among HIV-infected individuals, which is associated with suboptimal antiretroviral therapy (ART) adherence, HIV treatment interruptions, detectable HIV viral load, and transmission of HIV via increased sexual risk behavior. Contingency management (CM) is an initially effective treatment for stimulant use. However, the effects of CM are not sustained after the active intervention has ended. One potential contributor to the intractability of existing treatments may be a lack of attention to replacement activities or the role of depressed mood. Behavioral activation (BA) is an evidence-based approach for depression that involves identifying and participating in pleasurable, goal-directed activities. As a potential approach to address the CM rebound effect - informed by our formative qualitative research with the participant population - we conducted an open pilot trial of an intervention combining CM-BA for HIV-infected individuals with stimulant use disorder. Participants completed weekly BA therapy sessions (10-16 sessions) and thrice-weekly toxicology screenings (12 weeks); contingencies were rewarded for negative toxicology tests to support reengagement into positive life activities. Major assessments were conducted at baseline, 3-, and 6-months. Toxicology screening was repeated prior to the 6-month assessment. Eleven participants with stimulant use disorder enrolled; 7 initiated treatment and completed the full intervention. The mean age was 46 (SD = 5.03) and 14% identified as a racial/ethnic minority. Of the completers, the mean change score in self-reported stimulant use within the past 30 days (within-person change; reduction in self-reported stimulant use) was 4.14 days at 3 months and 5.0 days at 6 months [Cohen's d = 0.89]. The mean change score in weekly toxicology screens (reduction in positive toxicology screens) was .71 at 3 months and 1 at 6 months [Cohen's d = 1.05]. Exit interviews indicated that the integrated intervention was well received and acceptable. This study provides preliminary evidence that a combined CM-BA intervention for this population was feasible (100% retention at 6-months), acceptable (100% of intervention sessions attended; participants rated the intervention 'acceptable' or 'very acceptable'), and may be an option to augment the potency and sustained impact of CM for this population. Future pilot testing using a randomized controlled design is warranted.

PURPOSE AND APPROACH: Women in recovery describe stigma, negative treatment, and limited support as barriers to achieving their health and parenting goals. Mobile health technologies carefully tailored to support the unique needs of recovery communities can provide less burdensome alternatives to in-person services for women transitioning out of substance use treatment. An iterative design process integrated women's interests into the structure, content, and interaction flow of a mobile health (mHealth) app. SETTING AND PARTICIPANTS: Participants included women in recovery from opioid, alcohol, and polysubstance use disorders in a comprehensive housing program in urban Arizona. METHODS: Five focus groups with 3-7 participants each (n = 27 total) informed creation of the mHealth app. Informed by theoretical models of usability and person-centered design, development involved an iterative series of focus groups in which we asked women to comment on interest in using each feature. This provided a qualitative priority framework for feature development. We then modified the app and repeated the process to gauge consensus and continually refine our prototype. RESULTS: Women were interested in access to resources, such as housing, counseling, and parenting advice in settings known to treat women in recovery with respect. They also asked for positive messages, chatting with peers, and access to expert answers. They were less interested in points-based learning modules and "scored" activities, leading us to develop a "daily challenges" concept that builds good habits, but does not feel like "classwork". Women's recommendations shaped an mHealth app tailored to maximize utility, access, and safety for this at-risk population. CONCLUSION: Integration of user-centered design with applied ethnographic techniques guided the development of a custom-tailored mHealth app responsive to lived experiences and needs of women in recovery. Future research should evaluate the potential for user-centered apps to increase self-efficacy, perceived social support, and to reduce risk of relapse.