There has been growing interest in preventive intervention “crossover” effects on suicidal thoughts and behaviors (STBs), in which targeting early risk factors may mitigate distal risk for STBs without STBs having been the targeted outcomes of the primary study. The present study extends an 11-study integrative data analysis of the Coping Power (CP) intervention (N = 3182) to assess indirect effects of different forms of CP on teacher- and parent-reported STBs as transmitted through different subdimensions of internalizing and externalizing problems. Compared to school-as-usual, all forms of CP (Standard/Group CP, Individual CP, CP with Mindfulness, Internet-Enhanced CP) led to reductions in parent- and/or teacher-reported youth STBs. Subgroup analyses suggested that boys benefitted from Individual CP and CP with Mindfulness mediated by reductions in aggressive behavior, whereas boys in Standard CP saw reductions in STBs mediated by reductions in conduct problems. Girls saw reductions in STBs in CP with Mindfulness mediated by reductions in anxiety. Some inferences made for individual α and β paths and mediation effects differed when using standard parametric approaches for inference versus bias-corrected percentile bootstrapping. These differences highlight cautions regarding statistical inference for prevention researchers who study highly skewed zero-inflated latent variables such as STBs. Findings are discussed in light of (a) earlier etiological research on biological sex-specificity in the pathways to early risk for suicide and (b) how variation in program components of CP and its adaptations may reduce STB risk across different populations, age groups, and modes of program delivery.
Youth and young adults experience high attrition across the HIV care continuum, including elevated risk of antiretroviral therapy (ART) nonadherence and virologic failure. This study examined how financial well-being relates to ART adherence among youth with HIV (YWH), including those using oral or LAI-based regimens. We analyzed baseline data from YWH aged 18–29 years in the United States enrolled between 2023 and 2025 in a randomized controlled trial addressing HIV care barriers, mental health, and substance use. Oral ART adherence was measured using a validated scale, with high adherence defined as a score ≥ 80
Digital health technologies (DHTs) are revolutionizing medical research, offering unprecedented insights into health monitoring and disease detection through continuous, real-world data collection. Here we characterize the data in one of the largest and most demographically rich DHT datasets as part of the All of Us Research Program. Through a historic device distribution effort, the program reached a broad range of participants nationwide, yielding a DHT dataset with an expanded a large demographic scope. This dataset contains Fitbit data from more than 59,000 participants spanning 14 years with more than 39 million step observations and 31 million sleep observations. Nearly half (46%) of participants with Fitbit data also contributed electronic health records, physical measurements, genomics and survey data. This resource enables researchers to study relationships between digital health metrics and clinical outcomes, advancing DHT methodologies through its large size, broad representation and multi-modal data linkage.
This study evaluated death ascertainment from publicly available internet sources for patients in two large tertiary care US healthcare systems, Mass General Brigham (MGB) and Vanderbilt University Medical Center (VUMC), benchmarked against state and federal vital statistics data. Names, dates of birth, and dates of death were extracted from 8.1 million internet media records using previously developed natural language processing models. Internet records were matched to 78 848 deceased patients from MGB and VUMC on first name, last name, and date of birth. Dates of death were validated against state vital statistics databases or the National Death Index as reference standards. We calculated sensitivity and positive predicted values (PPV) of internet sources in identifying dates of death within 7 days of the reference standard. Exact matching of records between internet media and reference standards on first name, last name, and date of birth, resulted in 30 067 (38.8%) matches, which showed PPV for death identification (98.2%-MGB; 98.9%-VUMC) in internet media and increased sensitivity of death capture over EHR alone by 24% at MGB and 18% at VUMC. In conclusion, using internet sources to augment mortality data increased capture of death meaningfully over reliance on EHR records alone.
BACKGROUND:The field of environmental health sciences increasingly demands comprehensive and diverse data sets, particularly in response to emerging research areas such as climate change, mixtures, and exposomics. The data needed to address the complexity of environmental health research questions often extend beyond the boundaries of a single study or data resource. Traditional data management approaches struggle to harmonize the ever-expanding and heterogeneous data sources needed for research in the environmental health sciences. Harmonization may help address this issue as it involves aligning and standardizing various elements of data to allow comprehensive analysis, data pooling, and interpretation across studies. OBJECTIVES:The primary objective is to inform researchers about the transformative potential of embracing harmonization methodologies and to motivate contributions to ongoing efforts, thereby fostering advancements. METHODS:Using the Environmental Health Language Collaborative's Data Harmonization Use Case, we provide a practical illustration of existing data harmonization approaches, identify gaps, and emphasize future research and application directions. We selected two publicly available environmental epidemiology studies on the topic of childhood asthma and three studies on the topic of biomarkers of metals exposure during pregnancy and birth outcomes and applied several existing harmonization approaches to assess interoperability. DISCUSSION:Our process revealed the potential limitations of many existing harmonization approaches, with notable failures to identify common variables across independent data sets and lack of agreement between human and computer-based approaches. This use case identified various challenges with existing approaches, including reliance on often incomplete data documentation and large amounts of manual effort. To address these challenges, we recommend the continued advancement and dissemination of community data standards, the development of software and tools to facilitate harmonization through automation, and strategic efforts to promote engagement in data harmonization within the environmental health sciences community. Collaborative science is needed to advance our understanding of environmental contributors to health, and realizing the harmonization potential of our scientific data is a step toward improved collaboration.
