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.

OBJECTIVE: Integrating pediatric obesity care into primary care remains challenging, especially in underserved areas. To address this, the REACH-KIDS (Reverse Consult Care Model for the Comprehensive Treatment of Pediatric Obesity in Primary Care) program, which aims to empower primary care clinician through education and resources was developed. This study describes the design and early evaluation of a quality improvement initiative aimed at building PCP capacity in pediatric obesity care using a collaborative care model. METHODS: The REACH-KIDS model was implemented across two sites, involving didactic mini-series sessions designed to educate primary care clinicians on obesity care. The program's feasibility was evaluated by tracking attendance, engagement, satisfaction, and knowledge gained. Between November 2023 and May 2024, two mini-series were conducted across the sites, and feedback was gathered to assess shifts in clinical practice, particularly in anti-obesity medication use. RESULTS: At Site one, 68, 67, and 67 attendees participated in September, October, and November 2023 sessions, respectively. At Site two, 42, 45, and 52 attendees participated in March, April, and May 2024. Most attendees (75%) reported a shift in clinical practice regarding obesity pharmacotherapy after attending the mini-series. Satisfaction with the sessions was high, and knowledge assessments significantly improved participants' understanding of obesity treatment options. Notably, participants reported increased confidence in prescribing anti-obesity medications, indicating a positive clinical impact of the educational intervention. CONCLUSIONS: The REACH-KIDS model demonstrated feasibility and effectiveness in improving primary care clinicians' knowledge of comprehensive obesity care. This quality improvement initiative highlights the potential of education and collaboration to enhance obesity care in primary care settings. Future studies should focus on expanding this model and assessing its impact on clinical outcomes in underserved populations. Limitations include the restricted geographic scope and reliance on self-reported changes in clinical practice; future work will require objective measures of patient outcomes and broader implementation.

Men's health, particularly in the domain of urology, faces significant challenges in access to care, patient outcomes, and cost efficiency. Despite advances in medical treatment, conditions such as prostate cancer remain a leading cause of cancer-related death among men, with African American men disproportionately affected at twice the mortality rate of other groups. Compounding these challenges is a critical shortage of urologists, with 62% of US counties lacking a practicing urologist and only 1 new urologist entering the field for every 10 retiring. This shortage results in delayed diagnoses, increased rates of advanced-stage conditions, and significant health disparities. To address these pressing issues, telehealth and technology-based integrated care models present a promising solution. Telehealth expands access to specialized urological care by overcoming geographical barriers and offering virtual consultations, at-home diagnostics, and continuous patient engagement. Artificial intelligence-driven tools further enhance the efficiency and accuracy of care delivery, improving provider experience by automating administrative tasks and facilitating early intervention through predictive analytics. Furthermore, remote patient monitoring devices provide accurate, cost-effective, and highly accessible alternatives. These innovations reduce provider burnout, lower health care costs, and, critically, improve patient outcomes. This paper explores the potential of telehealth and integrated care in men's health urology as a practical pathway to bridging access gaps, enhancing care quality, and achieving cost savings. By leveraging digital health solutions, health care systems and employers can promote health equity, increase engagement, and ensure that all men receive timely and effective urological care.

OBJECTIVE: Shared Decision Making (SDM) is heralded as a standard for patient-centered care, but implementation of SDM in routine mental health practice has proven difficult to achieve. Human-centered design (HCD) may hold promise for improving SDM implementation in busy clinical settings. This study describes applying HCD to develop an SDM documentation support tool intended to encourage successful use of SDM by mental health clinicians. METHODS: This descriptive, proof-of-concept study utilized the Discover-Design-Build-Test HCD framework to simplify a comprehensive SDM protocol for mental health decision making. Implementation was piloted within multiple primary care clinics. The study consisted of three phases: information gathering (interviewing clinicians), solution generation and prototyping, and testing a final prototype in routine care settings. RESULTS: Our project proceeded through eight cycles of user design and feedback. Clinicians pilot tested the final product, a documentation note template incorporating SDM prompts and explanations. It is currently available for clinical use. CONCLUSIONS: Clinicians were able to use the HCD-redesigned SDM documentation note template intuitively, i.e., without explicit instruction. Leveraging buy-in from users throughout the entirety of the process (from problem investigation to solution discussions) created opportunities to tailor implementation strategies and may support ownership of the end-product by primary stakeholders. PRACTICE IMPLICATIONS: HCD may be a promising methodology for streamlining the adoption of complex clinical tasks like SDM.

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.