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Introduction: Implementation studies include both recipient populations, who will benefit from the study's evidence-based intervention, and study populations, who will participate in the intervention and contribute data to implementation outcomes. Decision making around inclusion criteria for the study population and whether to include the recipient population have significant implications for study design. We present 3 case studies of HIV prevention implementation studies that feature diverse study populations and describe the decision-making process around defining study populations to share generalizable lessons for the field.
Methods: We identified recipient and study populations for each study, described decision making regarding inclusion and exclusion criteria, and identified implications for measuring study aims.
Results: HIV prevention interventions focus on pre-exposure prophylaxis uptake and HIV testing in settings such as emergency departments, obstetrics/gynecology clinical practices, and free HIV testing sites. These studies were designed to inform scale-up of intervention strategies based on effectiveness, affordability, and feasibility. Decisions about whom to include in the study populations were based on context, strategies, and implementation outcomes.
Discussion: We identified important considerations across projects, including study context, strategies, and approaches. These factors can inform decisions around defining study populations to ensure successful measurement of study aims and sustainability of implementation outcomes.
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http://dx.doi.org/10.1097/QAI.0000000000003634 | DOI Listing |
Clin Epigenetics
September 2025
Department of Psychiatry and Psychotherapy, Philipps University Marburg, Marburg, Germany.
Background: Work-related stress is a well-established contributor to mental health decline, particularly in the context of burnout, a state of prolonged exhaustion. Epigenetic clocks, which estimate biological age based on DNA methylation (DNAm) patterns, have been proposed as potential biomarkers of chronic stress and its impact on biological aging and health. However, their role in mediating the relationship between work-related stress, physiological stress markers, and burnout remains unclear.
View Article and Find Full Text PDFNutr J
September 2025
Department of Gastroenterology and Hepatology, Hangzhou Red Cross Hospital, 208 Huancheng Dong Road, Hangzhou, 310003, Zhejiang Province, China.
Background: The potential association between dietary inflammatory index (DII) and colorectal cancer (CRC) risk, as well as colorectal adenomas (CRA) risk, has been extensively studied, but the findings remain inconclusive. We conducted this systematic review and dose-response meta-analysis to investigate the relationship between the DII and CRC and CRA.
Methods: We comprehensively searched the PubMed, Embase, Cochrane Library, and Web of Science databases for cohort and case-control studies reporting the relationship between DII and CRA, or between DII and CRC, as of 15 July 2025.
BMC Glob Public Health
September 2025
Kenya Medical Research Institute (KEMRI) - Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya.
Background: Between November 2023 and March 2024, coastal Kenya experienced another wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections detected through our continued genomic surveillance. Herein, we report the clinical and genomic epidemiology of SARS-CoV-2 infections from 179 individuals (a total of 185 positive samples) residing in the Kilifi Health and Demographic Surveillance System (KHDSS) area (~ 900 km).
Methods: We analyzed genetic, clinical, and epidemiological data from SARS-CoV-2 positive cases across pediatric inpatient, health facility outpatient, and homestead community surveillance platforms.
J Cannabis Res
September 2025
Department of EconomicsMA in Applied Economics, Lebanese American University, P.O. Box: 13-5053, Beirut, Lebanon.
Amidst the global shift toward cannabis legalization, this study examines medical cannabis (MC) sales as an indicator of economic activity and innovation. It explores associations between MC sales, and variables including tobacco use, alcohol consumption, amphetamine, cocaine and cannabis prevalence, and gross domestic product (GDP), using a fixed effects (FE) panel regression model. It also evaluates associations between cannabis legalization and MC sales over time using a dynamic Difference-in-Differences (DiD) approach with multiple time periods.
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