All of Us participant perspectives on the return of value in research.

PURPOSE: To understand participant preferences for receiving specific types of research information, whether information preferences vary across sociodemographic groups, and the types of health providers participants could access to understand returned information. METHODS: All of Us Research Program participants completed a value of returning research information survey. Stratified sampling was implemented to enhance participant diversity and avoid noncoverage. We used weighted multivariable logistic regression to evaluate associations between the most valuable information types, access to providers, and sociodemographic variables. RESULTS: Participants (N = 20,405) were diverse in their race/ethnicity (eg, 52% were White, 18% were Hispanic/Latino or Spanish, 3% were Asian, and 20% were Black or African American). Most participants (78.6%) valued information about their risk of serious genetic diseases with available treatment. Primary care physicians, specialists, and genetic counselors were the top providers that participants could access for help understanding returned information. Information preferences and provider access varied across sociodemographic groups. For example, as income levels increased, the odds of placing value on genetic results indicating risk of serious disease with available treatment increased when compared with the lowest income levels (P value < .001). CONCLUSION: Although genetic information was most valuable to participants, preferences about specific information types varied across sociodemographic groups.

Patient Lung Cancer Screening Decisions and Environmental and Psychosocial Factors.

Importance: Screening for lung cancer using low-dose computed tomography is associated with reduced lung cancer-specific mortality, but uptake is low in the US; understanding how patients make decisions to engage with lung cancer screening is critical for increasing uptake. Prior research has focused on individual-level psychosocial factors, but environmental factors (eg, historical contexts that include experiencing racism) and modifying factors-those that can be changed to make it easier or harder to undergo screening-also likely affect screening decisions. Objective: To investigate environmental, psychosocial, and modifying factors influencing lung cancer screening decision-making and develop a conceptual framework depicting relationships between these factors. Design, Setting, and Participants: This multimethod qualitative study was conducted from December 2021 to June 2022 using virtual semistructured interviews and 4 focus groups (3-4 participants per group). All participants met US Preventive Services Task Force eligibility criteria for lung cancer screening (ie, age 50-80 years, at least a 20 pack-year smoking history, and either currently smoke or quit within the past 15 years). Screening-eligible US participants were recruited using an online panel. Main Outcomes and Measures: Key factors influencing screening decisions (eg, knowledge, beliefs, barriers, and facilitators) were the main outcome. A theory-informed, iterative inductive-deductive approach was applied to analyze data and develop a conceptual framework summarizing results. Results: Among 34 total participants (interviews, 20 [59%]; focus groups, 14 [41%]), mean (SD) age was 59.1 (4.8) years and 20 (59%) identified as female. Half had a household income below $20 000 (17 [50%]). Participants emphasized historical and present-day racism as critical factors contributing to mistrust of health care practitioners and avoidance of medical procedures like screening. Participants reported that other factors, such as public transportation availability, also influenced decisions. Additionally, participants described psychosocial processes involved in decisions, such as perceived screening benefits, lung cancer risk appraisal, and fear of a cancer diagnosis or harmful encounters with practitioners. In addition, participants identified modifying factors (eg, insurance coverage) that could make receiving screening easier or harder. Conclusions and Relevance: In this qualitative study of patient lung cancer screening decisions, environmental, psychosocial, and modifying factors influenced screening decisions. The findings suggest that systems-level interventions, such as those that help practitioners understand and discuss patients' prior negative health care experiences, are needed to promote effective screening decision-making.

Impact of financial compensation on enrollment and participation in a remote, mobile-app based research study.

Background: There is no consensus on how to determine appropriate financial compensation for research recruitment. Selecting incentive amounts that are reasonable and respectful, without undue inducement, remains challenging. Previously, we demonstrated that incentive amount significantly impacts participants' willingness to complete various hypothetical research activities. Here we further explore this relationship in a mock decentralized study. Methods: Adult ResearchMatch volunteers were invited to join a prospective study where interested individuals were given an opportunity to view details for a study along with participation requirements, then offered a randomly generated compensation amount between $0 and $50 to enroll and participate. Individuals agreeing to participate were then asked to complete tasks using a remote mobile application (MyCap), for two weeks. Tasks included a weekly survey, a daily gratitude journal and daily phone tapping task. Results: Willingness to participate was 85% across all incentive levels but not significantly impacted by amount. Task completion appeared to increase as a function of compensation until a plateau at $25. While participants described the study as low burden and reported that compensation was moderately important to their decision to join, only 31% completed all study tasks. Conclusion: While offering compensation in this study did not have a strong effect on enrollment rate, this work provides insight into participant motivation when joining and participating in studies employing mobile applications.

Interoperability of phenome-wide multimorbidity patterns: a comparative study of two large-scale EHR systems.

Background: Electronic health records (EHR) are increasingly used for studying multimorbidities. However, concerns about accuracy, completeness, and EHRs being primarily designed for billing and administrative purposes raise questions about the consistency and reproducibility of EHR-based multimorbidity research. Methods: Utilizing phecodes to represent the disease phenome, we analyzed pairwise comorbidity strengths using a dual logistic regression approach and constructed multimorbidity as an undirected weighted graph. We assessed the consistency of the multimorbidity networks within and between two major EHR systems at local (nodes and edges), meso (neighboring patterns), and global (network statistics) scales. We present case studies to identify disease clusters and uncover clinically interpretable disease relationships. We provide an interactive web tool and a knowledge base combining data from multiple sources for online multimorbidity analysis. Findings: Analyzing data from 500,000 patients across Vanderbilt University Medical Center and Mass General Brigham health systems, we observed a strong correlation in disease frequencies (Kendall's τ = 0.643) and comorbidity strengths (Pearson ρ = 0.79). Consistent network statistics across EHRs suggest similar structures of multimorbidity networks at various scales. Comorbidity strengths and similarities of multimorbidity connection patterns align with the disease genetic correlations. Graph-theoretic analyses revealed a consistent core-periphery structure, implying efficient network clustering through threshold graph construction. Using hydronephrosis as a case study, we demonstrated the network's ability to uncover clinically relevant disease relationships and provide novel insights. Interpretation: Our findings demonstrate the robustness of large-scale EHR data for studying phenome-wide multimorbidities. The alignment of multimorbidity patterns with genetic data suggests the potential utility for uncovering shared biology of diseases. The consistent core-periphery structure offers analytical insights to discover complex disease interactions. This work also sets the stage for advanced disease modeling, with implications for precision medicine. Funding: VUMC Biostatistics Development Award, the National Institutes of Health, and the VA CSRD.

Relative predictive value of sociodemographic factors for chronic diseases among All of Us participants: a descriptive analysis.

BACKGROUND: Although sociodemographic characteristics are associated with health disparities, the relative predictive value of different social and demographic factors remains largely unknown. This study aimed to describe the sociodemographic characteristics of All of Us participants and evaluate the predictive value of each factor for chronic diseases associated with high morbidity and mortality. METHODS: We performed a cross-sectional analysis using de-identified survey data from the All of Us Research Program, which has collected social, demographic, and health information from adults living in the United States since May 2018. Sociodemographic data included self-reported age, sex, gender, sexual orientation, race/ethnicity, income, education, health insurance, primary care provider (PCP) status, and health literacy scores. We analyzed the self-reported prevalence of hypertension, coronary artery disease, any cancer, skin cancer, lung disease, diabetes, obesity, and chronic kidney disease. Finally, we assessed the relative importance of each sociodemographic factor for predicting each chronic disease using the adequacy index for each predictor from logistic regression. RESULTS: Among the 372,050 participants in this analysis, the median age was 53 years, 59.8% reported female sex, and the most common racial/ethnic categories were White (54.0%), Black (19.9%), and Hispanic/Latino (16.7%). Participants who identified as Asian, Middle Eastern/North African, and White were the most likely to report annual incomes greater than $200,000, advanced degrees, and employer or union insurance, while participants who identified as Black, Hispanic, and Native Hawaiian/Pacific Islander were the most likely to report annual incomes less than $10,000, less than a high school education, and Medicaid insurance. We found that age was most predictive of hypertension, coronary artery disease, any cancer, skin cancer, diabetes, obesity, and chronic kidney disease. Insurance type was most predictive of lung disease. Notably, no two health conditions had the same order of importance for sociodemographic factors. CONCLUSIONS: Age was the best predictor for the assessed chronic diseases, but the relative predictive value of income, education, health insurance, PCP status, race/ethnicity, and sexual orientation was highly variable across health conditions. Identifying the sociodemographic groups with the largest disparities in a specific disease can guide future interventions to promote health equity.

Conceptualizing and Measuring Trust, Mistrust, and Distrust: Implications for Advancing Health Equity and Building Trustworthiness.

Trust is vital to public confidence in health and science, yet there is no consensus on the most useful way to conceptualize, define, measure, or intervene on trust and its related constructs (e.g., mistrust, distrust, and trustworthiness). In this review, we synthesize literature from this wide-ranging field that has conceptual roots in racism, marginalization, and other forms of oppression. We summarize key definitions and conceptual frameworks and offer guidance to scholars aiming to measure these constructs. We also review how trust-related constructs are associated with health outcomes, describe interventions in this field, and provide recommendations for building trust and institutional trustworthiness and advancing health equity. We ultimately call for future efforts to focus on improving the trustworthiness of public health professionals, scientists, health care providers, and systems instead of aiming to increase trust in these entities as they currently exist and behave.

Integrating participants as partners in research governance and operations: an approach from the All of Us Research Program Engagement Core.

OBJECTIVES: During the last two decades, researchers and funders increasingly recognised the value of engaging patients and communities in research. Despite progress, community engagement remains challenging. There are few examples of successful participant engagement in governance of large-scale research programmes. Here we describe efforts to engage participants as partners in new governance roles in the All of Us Research Program, a precision medicine research initiative which intends to enrol at least one million participants. Using intentional, participant-centric engagement strategies, the All of Us Engagement Core recruited and integrated a diverse group of participants into governance roles including Steering and Executive Committees. Evaluation measures included a survey to assess Consortium Members' readiness for participant engagement. RESULTS: Over a 3-year period, all items on the survey increased (higher readiness). Of the 291 respondents to the 2021 survey, respondents most frequently agreed that participant perspectives are essential (100%), participants understand enough to contribute meaningfully (94%) and participants should be involved in setting goals (96%). Respondents least frequently agreed that participants should have an equal voice in Working Groups (75%), Steering Committee (69%) and Executive Committee (63%). CONCLUSION: In conclusion, participants can be effectively integrated into large-scale research governance, which is associated with increased researcher readiness for engagement.

Leveraging the Expertise of the CTSA Program to Increase the Impact and Efficiency of Clinical Trials.

Importance: Multicenter clinical trials play a critical role in the translational processes that enable new treatments to reach all people and improve public health. However, conducting multicenter randomized clinical trials (mRCT) presents challenges. The Trial Innovation Network (TIN), established in 2016 to partner with the Clinical and Translational Science Award (CTSA) Consortium of academic medical institutions in the implementation of mRCTs, consists of 3 Trial Innovation Centers (TICs) and 1 Recruitment Innovation Center (RIC). This unique partnership has aimed to address critical roadblocks that impede the design and conduct of mRCTs, in expectation of accelerating the translation of novel interventions to clinical practice. The TIN's challenges and achievements are described in this article, along with examples of innovative resources and processes that may serve as useful models for other clinical trial networks providing operational and recruitment support. Observations: The TIN has successfully integrated more than 60 CTSA institution program hubs into a functional network for mRCT implementation and optimization. A unique support system for investigators has been created that includes the development and deployment of novel tools, operational and recruitment services, consultation models, and rapid communication pathways designed to reduce delays in trial start-up, enhance recruitment, improve engagement of diverse research participants and communities, and streamline processes that improve the quality, efficiency, and conduct of mRCTs. These resources and processes span the clinical trial spectrum and enable the TICs and RIC to serve as coordinating centers, data centers, and recruitment specialists to assist trials across the National Institutes of Health and other agencies. The TIN's impact has been demonstrated through its response to both historical operational challenges and emerging public health emergencies, including the national opioid public health crisis and the COVID-19 pandemic. Conclusions and Relevance: The TIN has worked to reduce barriers to implementing mRCTs and to improve mRCT processes and operations by providing needed clinical trial infrastructure and resources to CTSA investigators. These resources have been instrumental in more quickly and efficiently translating research discoveries into beneficial patient treatments.

Decentralized clinical trials in the trial innovation network: Value, strategies, and lessons learned.

New technologies and disruptions related to Coronavirus disease-2019 have led to expansion of decentralized approaches to clinical trials. Remote tools and methods hold promise for increasing trial efficiency and reducing burdens and barriers by facilitating participation outside of traditional clinical settings and taking studies directly to participants. The Trial Innovation Network, established in 2016 by the National Center for Advancing Clinical and Translational Science to address critical roadblocks in clinical research and accelerate the translational research process, has consulted on over 400 research study proposals to date. Its recommendations for decentralized approaches have included eConsent, participant-informed study design, remote intervention, study task reminders, social media recruitment, and return of results for participants. Some clinical trial elements have worked well when decentralized, while others, including remote recruitment and patient monitoring, need further refinement and assessment to determine their value. Partially decentralized, or "hybrid" trials, offer a first step to optimizing remote methods. Decentralized processes demonstrate potential to improve urban-rural diversity, but their impact on inclusion of racially and ethnically marginalized populations requires further study. To optimize inclusive participation in decentralized clinical trials, efforts must be made to build trust among marginalized communities, and to ensure access to remote technology.

The RIC Recruitment & Retention Materials Toolkit - a resource for developing community-informed study materials.

Clinical trials face many challenges with meeting projected enrollment and retention goals. A study's recruitment materials and messaging convey necessary key information and therefore serve as a critical first impression with potential participants. Yet study teams often lack the resources and skills needed to develop engaging, culturally tailored, and professional-looking recruitment materials. To address this gap, the Recruitment Innovation Center recently developed a Recruitment & Retention Materials Content and Design Toolkit, which offers research teams guidance, actionable tips, resources, and customizable templates for creating trial-specific study materials. This paper seeks to describe the creation and contents of this new toolkit.

Communication Interactions, Needs, and Preferences During Clinical Encounters of African American Parent-Child Dyads.

Human papillomavirus (HPV) vaccination rates remain suboptimal among African American adolescents. Although provider recommendations during clinical encounters are believed to be highly effective in increasing uptake and series completion, little has been reported about parent-child perspectives on the counseling received during these encounters. Among African American parent-child dyads, we sought to explore and compare interactions, needs, and preferences during clinical encounters by child's HPV vaccination status. We applied a qualitative, phenomenological study design to conduct semi-structured interviews with African American parent-child dyads representing children who were unvaccinated (n = 10), had initiated but not completed (n = 11), or had completed the HPV vaccine series (n = 9). Using iterative, inductive-deductive thematic analysis, five themes were generated: (1) parents' attitudes varied about the HPV vaccine but were mostly positive for vaccines in general; (2) patient-parent-provider clinical encounters from the parent perspective; (3) patient-parent-provider clinical encounters from the child perspective; (4) methods of distribution of supplemental HPV information; and (5) communication desired on HPV vaccination by parents and children. Parents stating they received a provider's recommendation increased by vaccination status (unvaccinated: 6 out of 10; initiated: 7 out of 11; completed: 9 out of 9). Most parents and children were not satisfied with provider communication on the HPV vaccine and used supplemental materials to inform decision-making. Ongoing communication on the HPV vaccine was requested even post-vaccination of the child. During clinical encounters, children and parental messaging needs are similar yet dissimilar. We offer communication strategies and messaging that can be used for African American parent-child dyads by child HPV vaccination status during a clinical encounter.

The All of Us Data and Research Center: Creating a Secure, Scalable, and Sustainable Ecosystem for Biomedical Research.

The All of Us Research Program's Data and Research Center (DRC) was established to help acquire, curate, and provide access to one of the world's largest and most diverse datasets for precision medicine research. Already, over 500,000 participants are enrolled in All of Us, 80% of whom are underrepresented in biomedical research, and data are being analyzed by a community of over 2,300 researchers. The DRC created this thriving data ecosystem by collaborating with engaged participants, innovative program partners, and empowered researchers. In this review, we first describe how the DRC is organized to meet the needs of this broad group of stakeholders. We then outline guiding principles, common challenges, and innovative approaches used to build the All of Us data ecosystem. Finally, we share lessons learned to help others navigate important decisions and trade-offs in building a modern biomedical data platform.

PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis.

Motivation: Multimorbidity, characterized by the simultaneous occurrence of multiple diseases in an individual, is an increasing global health concern, posing substantial challenges to healthcare systems. Comprehensive understanding of disease-disease interactions and intrinsic mechanisms behind multimorbidity can offer opportunities for innovative prevention strategies, targeted interventions, and personalized treatments. Yet, there exist limited tools and datasets that characterize multimorbidity patterns across different populations. To bridge this gap, we used large-scale electronic health record (EHR) systems to develop the Phenome-wide Multi-Institutional Multimorbidity Explorer (PheMIME), which facilitates research in exploring and comparing multimorbidity patterns among multiple institutions, potentially leading to the discovery of novel and robust disease associations and patterns that are interoperable across different systems and organizations. Results: PheMIME integrates summary statistics from phenome-wide analyses of disease multimorbidities. These are currently derived from three major institutions: Vanderbilt University Medical Center, Mass General Brigham, and the UK Biobank. PheMIME offers interactive exploration of multimorbidity through multi-faceted visualization. Incorporating an enhanced version of associationSubgraphs, PheMIME enables dynamic analysis and inference of disease clusters, promoting the discovery of multimorbidity patterns. Once a disease of interest is selected, the tool generates interactive visualizations and tables that users can delve into multimorbidities or multimorbidity networks within a single system or compare across multiple systems. The utility of PheMIME is demonstrated through a case study on schizophrenia. Availability and implementation: The PheMIME knowledge base and web application are accessible at https://prod.tbilab.org/PheMIME/. A comprehensive tutorial, including a use-case example, is available at https://prod.tbilab.org/PheMIME_supplementary_materials/. Furthermore, the source code for PheMIME can be freely downloaded from https://github.com/tbilab/PheMIME. Data availability statement: The data underlying this article are available in the article and in its online web application or supplementary material.

Approaches for enhancing the informativeness and quality of clinical trials: Innovations and principles for implementing multicenter trials from the Trial Innovation Network.

One challenge for multisite clinical trials is ensuring that the conditions of an informative trial are incorporated into all aspects of trial planning and execution. The multicenter model can provide the potential for a more informative environment, but it can also place a trial at risk of becoming uninformative due to lack of rigor, quality control, or effective recruitment, resulting in premature discontinuation and/or non-publication. Key factors that support informativeness are having the right team and resources during study planning and implementation and adequate funding to support performance activities. This communication draws on the experience of the National Center for Advancing Translational Science (NCATS) Trial Innovation Network (TIN) to develop approaches for enhancing the informativeness of clinical trials. We distilled this information into three principles: (1) assemble a diverse team, (2) leverage existing processes and systems, and (3) carefully consider budgets and contracts. The TIN, comprised of NCATS, three Trial Innovation Centers, a Recruitment Innovation Center, and 60+ CTSA Program hubs, provides resources to investigators who are proposing multicenter collaborations. In addition to sharing principles that support the informativeness of clinical trials, we highlight TIN-developed resources relevant for multicenter trial initiation and conduct.

Correction: Development of a Tailored Mobile Phone-Based Intervention to Facilitate Parent-Child Communication and Build Human Papillomavirus Vaccine Confidence: Formative Qualitative Study.

[This corrects the article DOI: 10.2196/43041.].