The value of Source Data Verification (SDV) has been a common theme in the applied Clinical Translational Science literature. Yet, few published assessments of SDV quality exist even though they are needed to design risk-based and reduced monitoring schemes. This review was conducted to identify reports of SDV quality, with a specific focus on accuracy.

A scoping review was conducted of the SDV and clinical trial monitoring literature to identify articles addressing SDV quality. Articles were systematically screened and summarized in terms of research design, SDV context, and reported measures.

The review found significant heterogeneity in underlying SDV methods, domains of SDV quality measured, the outcomes assessed, and the levels at which they were reported. This variability precluded comparison or pooling of results across the articles. No absolute measures of SDV accuracy were identified.

A definitive and comprehensive characterization of SDV process accuracy was not found. Reducing the SDV without understanding the risk of critical findings going undetected, i.e., SDV sensitivity, is counter to recommendations in Good Clinical Practice and the principles of Quality by Design. Reference estimates (or methods to obtain estimates) of SDV accuracy are needed to confidently design risk-based, reduced SDV processes for clinical studies.

Type 2 diabetes (T2DM) poses a significant public health challenge, with pronounced disparities in control and outcomes. Social determinants of health (SDoH) significantly contribute to these disparities, affecting healthcare access, neighborhood environments, and social context. We discuss the design, development, and use of an innovative web-based application integrating real-world data (electronic health record and geospatial files), to enhance comprehension of the impact of SDoH on T2 DM health disparities.

We identified a patient cohort with diabetes from the institutional Diabetes Registry (N = 67,699) within the Duke University Health System. Patient-level information (demographics, comorbidities, service utilization, laboratory results, and medications) was extracted to Tableau. Neighborhood-level socioeconomic status was assessed via the Area Deprivation Index (ADI), and geospatial files incorporated additional data related to points of interest (i.e., parks/green space). Interactive Tableau dashboards were developed to understand risk and contextual factors affecting diabetes management at the individual, group, neighborhood, and population levels.

The Tableau-powered digital health tool offers dynamic visualizations, identifying T2DM-related disparities. The dashboard allows for the exploration of contextual factors affecting diabetes management (e.g., food insecurity, built environment) and possesses capabilities to generate targeted patient lists for personalized diabetes care planning.

As part of a broader health equity initiative, this application meets the needs of a diverse range of users. The interactive dashboard, incorporating clinical, sociodemographic, and environmental factors, enhances understanding at various levels and facilitates targeted interventions to address disparities in diabetes care and outcomes. Ultimately, this transformative approach aims to manage SDoH and improve patient care.

Social determinants of health (SDOH) can contribute to disparities that negatively impact health outcomes and healthcare utilization. Comprehensive screening is frequently overlooked during inpatient clinical care. This pilot aimed to evaluate the capturability of a multi-domain SDOH screening tool during hospitalization, as well as correlation of SDOH needs to readmissions.

The Protocol for Responding to and Assessing Patients’ Assets, Risks and Experiences (PRAPARE) screening tool was implemented on admission with adult inpatients at an academic tertiary medical center in central Pennsylvania. A total of 80 patients were screened over an 8-week period using the PRAPARE tool.

43.7% of participants were identified as having at least one SDOH need and 21.2% were identified as having two or more needs. Of the participants identified as having at least one SDOH need through PRAPARE screening, 42.5% experienced a readmission within 30 days, compared to 15% readmissions among participants with no identified SDOH needs. For each additional SDOH need a patient had, the odds they experienced a readmission increased by 2.2 times.

The study findings suggest that utilization of the PRAPARE screening tool has the ability to capture significant SDOH needs among hospitalized patients. This study also suggests that higher SDOH needs correlate to increased odds of experiencing a hospital readmission.

There are two main schools of thought about statistical inference: frequentist and Bayesian. The frequentist approach relies solely on available data for predictions, while the Bayesian approach incorporates both data and prior knowledge about the event of interest. Bayesian methods were developed hundreds of years ago; however, they were rarely used due to computational challenges and conflicts between the two schools of thought. Recent advances in computational capabilities and a shift toward leveraging prior knowledge for inferences have led to increased use of Bayesian methods.

Many biostatisticians with expertise in frequentist approaches lack the skills to apply Bayesian techniques. To address this gap, four faculty experts in Bayesian modeling at the University of Michigan developed a practical, customized workshop series. The training, tailored to accommodate the schedules of full-time staff, focused on immersive, project-based learning rather than traditional lecture-based methods. Surveys were conducted to assess the impact of the program.

All 20 participants completed the program and when surveyed reported an increased understanding of Bayesian theory and greater confidence in using these techniques. Capstone projects demonstrated participants’ ability to apply Bayesian methodology. The workshop not only enhanced the participants’ skills but also positioned them to readily apply Bayesian techniques in their work.

Accommodating the schedules of full-time biostatistical staff enabled full participation. The immersive project-based learning approach resulted in building skills and increasing confidence among staff statisticians who were unfamiliar with Bayesian methods and their practical applications.

Persistence in physician-scientist careers has been suboptimal, particularly among women. There is a gender gap in self-confidence in medicine. We measured the impact of our physician-scientist training programs on trainee’s confidence in professional, personal, and scientific competencies, using a survey measuring self-rated confidence in 36 competencies across two timepoints.

Results were analyzed for the full survey and for thematic subscales identified through exploratory factor analysis (EFA). A mixed effects linear model and a difference in differences (DID) design were used to assess the differential impact of the programing by gender and career level.

Analysis included 100 MD-PhD or MD-only medical student or resident/fellow trainees enrolled between 2020 and 2023. Five subscales were identified through EFA; career sustainability, science productivity, grant management, goal setting, and goal alignment (Cronbach’s alpha 0.85–0.94). Overall, mean scores increased significantly for all five subscales. Women significantly increased their confidence levels in all five areas, whereas men increased only in science productivity and grant management. Mixed effects models showed significant increases over time for women compared to men in career sustainability and goal alignment. Residents and fellows had greater increases than medical students across all subscales.

Physician-scientist trainees fellows increased their confidence in personal, professional, and scientific skills during training. Training had a greater impact on women than men in building confidence in sustaining careers and aligning their goals with professional and institutional priorities. The magnitude of increased confidence among residents and fellows exceeded that in medical students.

Leveraging the National COVID-19 Cohort Collaborative (N3C), a nationally sampled electronic health records repository, we explored associations between individual-level social determinants of health (SDoH) and COVID-19-related hospitalizations among racialized minority people with human immunodeficiency virus (HIV) (PWH), who have been historically adversely affected by SDoH.

We retrospectively studied PWH and people without HIV (PWoH) using N3C data from January 2020 to November 2023. We evaluated SDoH variables across three domains in the Healthy People 2030 framework: (1) healthcare access, (2) economic stability, and (3) social cohesion with our primary outcome, COVID-19-related hospitalization. We conducted hierarchically nested additive and adjusted mixed-effects logistic regression models, stratifying by HIV status and race/ethnicity groups, accounting for age, sex, comorbidities, and data partners.

Our analytic sample included 280,441 individuals from 24 data partner sites, where 3,291 (1.17%) were PWH, with racialized minority PWH having higher proportions of adverse SDoH exposures than racialized minority PWoH. COVID-19-related hospitalizations occurred in 11.23% of all individuals (9.17% among PWH, 11.26% among PWoH). In our initial additive modeling, we observed that all three SDoH domains were significantly associated with hospitalizations, even with progressive adjustments (adjusted odds ratios [aOR] range 1.36–1.97). Subsequently, our HIV-stratified analyses indicated economic instability was associated with hospitalization in both PWH and PWoH (aOR range 1.35–1.48). Lastly, our fully adjusted, race/ethnicity-stratified analysis, indicated access to healthcare issues was associated with hospitalization across various racialized groups (aOR range 1.36–2.00).

Our study underscores the importance of assessing individual-level SDoH variables to unravel the complex interplay of these factors for racialized minority groups.

To better understand and prevent research errors, we conducted a first-of-its-kind scoping review of clinical and translational research articles that were retracted because of problems in data capture, management, and/or analysis.

The scoping review followed a preregistered protocol and used retraction notices from the Retraction Watch Database in relevant subject areas, excluding gross misconduct. Abstracts of original articles published between January 1, 2011 and January 31, 2020 were reviewed to determine if articles were related to clinical and translational research. We reviewed retraction notices and associated full texts to obtain information on who retracted the article, types of errors, authors, data types, study design, software, and data availability.

After reviewing 1,266 abstracts, we reviewed 884 associated retraction notices and 786 full-text articles. Authors initiated the retraction over half the time (58%). Nearly half of retraction notices (42%) described problems generating or acquiring data, and 28% described problems with preparing or analyzing data. Among the full texts that we reviewed: 77% were human research; 29% were animal research; and 6% were systematic reviews or meta-analyses. Most articles collected data de novo (77%), but only 5% described the methods used for data capture and management, and only 11% described data availability. Over one-third of articles (38%) did not specify the statistical software used.

Authors may improve scientific research by reporting methods for data capture and statistical software. Journals, editors, and reviewers should advocate for this documentation. Journals may help the scientific record self-correct by requiring detailed, transparent retraction notices.

Translational science (TS) teams develop and conduct translational research. Academic TS teams can be categorized under three constituency groups: trainees and faculty, clinical research professionals (CRP), and community partners. Our study objectives were to define individual and team competencies of these three constituency groups during their career life course and determine relative importance and the level of mastery of each of the competencies needed at different stages of their life course.

Each group was composed of experts for their constituency group. We applied individual and team competencies in TS teams by Lotrecchiano et al. (2020) as a starting point for structured expert discussions following a modified Delphi approach that we adapted based on the emergent needs and insights per constituency group.

The degree of relevance and level of mastery for individual and team competencies varies for trainees and faculty members across the career life course based on opportunities provided and relative importance at that career stage. However, CRPs enter TS teams at various career stages with fundamental, skilled, or advanced levels of smart skills that may or may not be contextual to their role. Community partners equally possess and develop competencies in a non-linear and contextual fashion that are required to facilitate constructive, bi-directional collaboration with other members of TS teams.

Team science competencies across the career life course do not develop linearly among different constituency groups and require an adaptive framework to enhance TS team effectiveness.

The knowledge, skills, and abilities needed for clinical research professionals (CRPs) are described in the Joint Task Force (JTF) for Clinical Trial Competencies Framework as a basis for leveled educational programs, training curricula, and certification. There is a paucity of literature addressing team science competencies tailored to CRPs. Gaps in training, research, and education can restrict their capability to effectively contribute to team science.

The CRP Team Science team consisted of 18 members from 7 clinical and translational science awarded institutions. We employed a multi-stage, modified Delphi approach to define “Smart Skills” and leveled team science skills examples using individual and team science competencies identified by Lotrecchiano et al.

Overall, 59 team science Smart Skills were identified resulting in 177 skills examples across three levels: fundamental, skilled, and advanced. Two examples of the leveled skillsets for individual and team competencies are illustrated. Two vignettes were created to illustrate application for training.

This work provides a first-ever application of team science for CRPs by defining specific individual and team science competencies for each level of the CRP career life course. This work will enhance the JTF Domains 7 (Leadership and Professionalism) and 8 (Communication and Teamwork) which are often lacking in CRP training programs. The supplement provides a full set of skills and examples from this work.

Developing team science skills for CRPs may contribute to more effective collaborations across interdisciplinary clinical research teams. These skills may also improve research outcomes and stabilize the CRP workforce.

This study explores the transformative effects of the Community Plunge, an educational program at the Wake Forest University School of Medicine (WFUSOM), on healthcare delivery, community engagement, and trainee perspectives. It addresses the broader context of health outcomes, where clinical care only accounts for 20%, emphasizing the critical role of social determinants of health (SDOH) and individual behaviors in the remaining 80%.

WFUSOM’s Community Plunge, established in 2002, involves a guided tour of the community, discussions with residents, and debriefing sessions. Qualitative interviews with 20 clinicians were conducted to extract key themes and insights.

The study identified several key outcomes. First, participants gained crucial insights into the community’s history, structural challenges, and prevalent SDOH, enhancing their understanding of the diverse patient populations they serve. Second, the program positively influenced clinician attitudes, fostering empathy, reducing paternalism, and promoting holistic patient care. Third, participants expressed a desire for increased community involvement and reported career trajectory changes toward advocacy and volunteerism. However, challenges such as time constraints were acknowledged.

The study advocates for collaborative efforts to enhance the program’s impact, including proactive measures to ensure respectful engagement during community tours. It positions the Community Plunge as an innovative, scalable, and transformative strategy for experiential SDOH exposure, crucial for the evolving social consciousness of healthcare learners.

Community health workers and promotoras (CHW/Ps) increasingly support research conducted in communities but receive variable or no training. We developed a culturally and linguistically tailored research best practices course for CHW/Ps that can be taken independently or in facilitated groups. The purpose of this study was to evaluate the facilitated training.

CHW/Ps were recruited from communities and partners affiliated with study sites in Michigan, Florida, and California. They participated in virtual or in-person training facilitated by a peer in English or Spanish and then completed a survey about their abilities (i.e., knowledge and skills for participating in research-related work) and perceptions of the training. Linear regression analyses were used to examine differences in training experience across several factors.

A total of 394 CHW/Ps, mean age 41.6 ± 13.8 years, completed the training and survey (n = 275 English; 119 Spanish). Most CHW/Ps were female (80%), and 50% identified as Hispanic, Latino, or Spanish. Over 95% of CHW/Ps rated their abilities as improved after training; 98% agreed the course was relevant to their work and felt the training was useful. Small differences were observed between training sites.

Most CHW/Ps rated the training positively and noted improved knowledge and skills for engaging in research-related work. Despite slight site differences, the training was well received, and CHW/Ps appreciated having a facilitator with experience working in community-based settings. This course offers a standard and scalable approach to training the CHW/P workforce. Future studies can examine its uptake and effect on research quality.

Cervical cancer screening rates in the USA fall behind national targets, requiring innovation to circumvent screening barriers. Cervical cancer screening where human papillomavirus (HPV) testing is performed on vaginal samples collected by the patients themselves (self-sampling) are effective and acceptable, and patient-operated rapid HPV tests (self-testing) are currently under development. It is unclear why there is ambivalence toward HPV self-sampling and self-testing among clinicians, an important stakeholder group. We conducted a mixed convergent quantitative and qualitative study to identify the factors influencing clinicians’ attitudes toward self-sampling and self-testing.

A survey of Midwest clinicians distributed by professional group media and a market research firm between May and November 2021 was analyzed (n = 248) alongside in-depth interviews with Midwest clinicians from professional groups (n = 23). Logistic regression models examined willingness to support self-sampling and self-testing across respondent characteristics.

We report that family practice physicians and those in rural areas were more willing to adopt HPV self-sampling (adjusted OR (aOR) = 3.16 [1.43–6.99]; aOR = 2.17 [1.01–4.68]). Clinician willingness to support self-testing was positively associated with current use of self-testing for other conditions and negatively associated with performing 10 or more monthly cervical cancer screenings (aOR = 2.02 [1.03–3.95], aOR = 0.42 [0.23–0.78]). Qualitative data contextualize how clinical specialty and experience with self-sampling and self-testing for other conditions inform clinician perspectives.

These data suggest clinician populations most accepting of initiatives to implement self-sampling and self-testing for cervical cancer screening and highlight that experience with other forms of self-testing could facilitate more widespread adoption for cervical cancer.

The purpose of this study was to evaluate data from different implementations of the Mentoring Up curriculum, designed by the Center for the Improvement of Mentored Experiences in Research. The study investigated the relationship between participants’ self-reported change in mentoring competence and the behaviors they intended to implement post-training.

The data set included 401 respondents who consented to participate after 59 Mentoring Up training events hosted by 34 institutions between 2015 and 2022. Responses to the Mentoring Competency Assessment (MCA) were analyzed to determine which factors were related to self-reported changes in participants’ mentoring competencies post-training.

Quantitative analysis showed that intent to change, perceived value of training, training modality, and prior mentor training were all significantly associated with the magnitude of change in MCA scores between pre- and post-tests. Further, participants who engaged in face-to-face training found significantly more value in the training than those who participated online. Analysis of open-ended questions demonstrated that participants with larger changes in MCA scores were more likely to address core principles of Mentoring Up curriculum when discussing their behavior change plans post-training.

Participants improved their mentoring competence by participating in the Mentoring Up curriculum, and this change was significantly and practically associated with an intent to modify their behavior in their mentoring relationships.