Midcareer research faculty are a vital part of the advancement of science in U.S. medical schools, but there are troubling trends in recruitment, retention, and burnout rates.

The primary sampling frame for this online survey was recipients of a single R01 or equivalent and/or K-award from 2013 to 2019. Inclusion criteria were 3–14 years at a U.S. medical school and rank of associate professor or two or more years as assistant professor. Forty physician investigators and Ph.D. scientists volunteered for a faculty development program, and 106 were propensity-matched controls. Survey items covered self-efficacy in career, research, work-life; vitality/burnout; relationships, inclusion, trust; diversity; and intention to leave academic medicine.

The majority (52%) reported receiving poor mentoring; 40% experienced high burnout and 41% low vitality, which, in turn, predicted leaving intention (P < 0.0005). Women were more likely to report high burnout (P = 0.01) and low self-efficacy managing work and personal life (P = 0.01) and to be seriously considering leaving academic medicine than men (P = 0.003). Mentoring quality (P < 0.0005) and poor relationships, inclusion, and trust (P < 0.0005) predicted leaving intention. Non-underrepresented men were very likely to report low identity self-awareness (65%) and valuing differences (24%) versus underrepresented men (25% and 0%; P < 0.0005). Ph.D.s had lower career advancement self-efficacy than M.D.s (P < .0005).

Midcareer Ph.D. and physician investigators faced significant career challenges. Experiences diverged by underrepresentation, gender, and degree. Poor quality mentoring was an issue for most. Effective mentoring could address the concerns of this vital component of the biomedical workforce.

The Rockefeller Clinical Scholars (KL2) program began in 1976 and transitioned into a 3-year Master’s degree program in 2006 when Rockefeller joined the National Institute of Health Clinical and Translational Science Award program. The program consists of ∼15 trainees supported by the Clinical and Translational Science Award KL2 award and University funds. It is designed to provide an optimal environment for junior translational investigators to develop team science and leadership skills by designing and performing a human subjects protocol under the supervision of a distinguished senior investigator mentor and a team of content expert educators. This is complemented by a tutorial focused on important translational skills.

Since 2006, 40 Clinical Scholars have graduated from the programs and gone on to careers in academia (72%), government service (5%), industry (15%), and private medical practice (3%); 2 (5%) remain in training programs; 39/40 remain in translational research careers with 23 National Institute of Health awards totaling $23 million, foundation and philanthropic support of $20.3 million, and foreign government and foundation support of $6 million. They have made wide ranging scientific discoveries and have endeavored to translate those discoveries into improved human health.

The Rockefeller Clinical Scholars (KL2) program provides one model for translational science training.

This study identified underlying career orientation types of clinical research coordinators (CRCs) using cluster analysis. Select career (satisfaction, engagement, and planning) and competency-related (perceived competence) information was used to identify four distinct career orientation types.

A web-based survey was administered to CRCs employed in one of four research institutions affiliated with a National Institutes of Health-funded Clinical and Translational Research Award (CTSA) in the southeastern USA. Each respondent completed a survey containing questions about personal background, individual attributes, perceived professional competence, and career orientation.

The first CRC type (35.2%) possessed a positive, knowledge-seeking orientation, characterized by high career-related scores but a conservative assessment of perceived competence. The second CRC type (18.6%) represented an optimistic and confident career orientation reflected in moderate to high scores on each of the four identifying factors. The third CRC type (27.6%) reflected an inconsistent career orientation highlighted by lowered perceived competence. The final CRC type (18.6%) reflected a disengaged orientation characterized by negative responses to all career and competence factors.

Understanding the career orientation of CRCs can be helpful to institutional administrators and clinical investigators as they seek to support the professional development of CRCs through tailored training efforts or work-related supports. Knowledge of career orientation may also inform individual CRCs as they manage their personal career paths by assessing current levels of functioning, career-related strengths or weaknesses, and training needs.

Missing data are inevitable in medical research and appropriate handling of missing data is critical for statistical estimation and making inferences. Imputation is often employed in order to maximize the amount of data available for statistical analysis and is preferred over the typically biased output of complete case analysis. This article examines several types of regression imputation of missing covariates in the prediction of time-to-event outcomes subject to right censoring.

We evaluated the performance of five regression methods in the imputation of missing covariates for the proportional hazards model via summary statistics, including proportional bias and proportional mean squared error. The primary objective was to determine which among the parametric generalized linear models (GLMs) and least absolute shrinkage and selection operator (LASSO), and nonparametric multivariate adaptive regression splines (MARS), support vector machine (SVM), and random forest (RF), provides the “best” imputation model for baseline missing covariates in predicting a survival outcome.

LASSO on an average observed the smallest bias, mean square error, mean square prediction error, and median absolute deviation (MAD) of the final analysis model’s parameters among all five methods considered. SVM performed the second best while GLM and MARS exhibited the lowest relative performances.

LASSO and SVM outperform GLM, MARS, and RF in the context of regression imputation for prediction of a time-to-event outcome.

The Clinical and Translational Science Awards (CTSA) program of the National Center for Advancing Translational Sciences (NCATS) seeks to improve population health by accelerating the translation of scientific discoveries in the laboratory and clinic into practices for the community. CTSAs achieve this goal, in part, through their pilot project programs that fund promising early career investigators and innovative early-stage research projects across the translational research spectrum. However, there have been few reports on individual pilot projects and their impacts on the investigators who receive them and no studies on the long-term impact and outcomes of pilot projects.

The Georgia CTSA funded 183 pilot projects from 2007 to 2015. We used a structured evaluation framework, the payback framework, to document the outcomes of 16 purposefully-selected pilot projects supported by the Georgia CTSA. We used a case study approach including bibliometric analyses of publications associated with the selected projects, document review, and investigator interviews.

These pilot projects had positive impact based on outcomes in five “payback categories”: (1) knowledge; (2) research targeting, capacity building, and absorption; (3) policy and product development; (4) health benefits; and (5) broader economic benefits.

Results could inform our understanding of the diversity and breadth of outcomes resulting from Georgia CTSA-supported research and provide a framework for evaluating long-term pilot project outcomes across CTSAs.

To examine research participants’ levels of satisfaction and perceptions and aid researchers to better engage research volunteers from all racial and ethnic populations in clinical trials. A participant satisfaction survey was developed that focused on three domains to reflect satisfaction with delivery of care, environment, and center operations. In addition, the survey contained open-ended questions to reflect overall experiences and perceptions. Two hundred and seventy-eight participants (55% African American and 29% non-Hispanic Whites) with an average age of 52 years completed the survey.

The results indicated that the majority of the participants rated their satisfaction very highly across all domains. Ninety percent stated they were very satisfied/satisfied or very strongly agreed/agreed in the three domains. Obtaining high-quality care/access to health care professionals (60%), learning more about their illness/disease (60%), and helping others (57%) were noted as important factors in choosing to participate in a trial. Regarding overall experience, majority of respondents stated that friendliness, expertise of staff, learning more about their disease, and contributing to science were important. Further, financial compensation was not a primary motivation for participation. A majority of participants stated that they would participate in future studies and would recommend a friend or a family member to participate in clinical trials.

The findings indicate that the degree of satisfaction with the research staff and with the specific trial itself are important determinants for enrolling, completing a study, and for participating in future trials.

Pregnant women living in rural locations in the USA have higher rates of maternal and infant mortality compared to their urban counterparts. One factor contributing to this disparity may be lack of representation of rural women in traditional clinical research studies of pregnancy. Barriers to participation often include transportation to research facilities, which are typically located in urban centers, childcare, and inability to participate during nonwork hours.

POWERMOM is a digital research app which allows participants to share both survey and sensor data during their pregnancy. Through non-targeted, national outreach a study population of 3612 participants (591 from rural zip codes and 3021 from urban zip codes) have been enrolled so far in the study, beginning on March 16, 2017, through September 20, 2019.

On average rural participants in our study were younger, had higher pre-pregnancy weights, were less racially diverse, and were more likely to plan a home birth compared to the urban participants. Both groups showed similar engagement in terms of week of pregnancy when they joined, percentage of surveys completed, and completion of the outcome survey after they delivered their baby. However, rural participants shared less HealthKit or sensor data compared to urban participants.

Our study demonstrated the feasibility and effectiveness of enrolling pregnant women living in rural zip codes using a digital research study embedded within a popular pregnancy app. Future efforts to conduct remote digital research studies could help fill representation and knowledge gaps related to pregnant women.

Obtaining informed consent from prospective participants for research studies that include next-generation nucleotide sequencing (NGS) presents significant challenges because of the need to explain all the potential implications of participating, including the possible return of “incidental” findings, in easy-to-understand language.

After reviewing the consent processes at other institutions, we decided to supplement the protocol-specific informed consent form with the following: (1) a short pamphlet for the prospective participant that includes a series of questions that she or he is encouraged to ask the investigator, and (2) a more detailed companion guide for investigators to help them develop simple-language answers to the questions. Both documents are available to use or modify.

We propose an approach to obtaining informed consent for NGS studies that encourages discussion of key issues without creating a complex, comprehensive document for participants; it also maximizes investigator flexibility. We also suggest mechanisms to return restricted information to participants.

Area-level social determinants of health (SDoH) and individual-level social risks are different, yet area-level measures are frequently used as proxies for individual-level social risks. This study assessed whether demographic factors were associated with patients being screened for individual-level social risks, the percentage who screened positive for social risks, and the association between SDoH and patient-reported social risks in a nationwide network of community-based health centers.

Electronic health record data from 1,330,201 patients with health center visits in 2021 were analyzed using multilevel logistic regression. Associations between patient characteristics, screening receipt, and screening positive for social risks (e.g., food insecurity, housing instability, transportation insecurity) were assessed. The predictive ability of three commonly used SDoH measures (Area Deprivation Index, Social Deprivation Index, Material Community Deprivation Index) in identifying individual-level social risks was also evaluated.

Of 244,155 (18%) patients screened for social risks, 61,414 (25.2%) screened positive. Sex, race/ethnicity, language preference, and payer were associated with both social risk screening and positivity. Significant health system-level variation in both screening and positivity was observed, with an intraclass correlation coefficient of 0.55 for social risk screening and 0.38 for positivity. The three area-level SDoH measures had low accuracy, sensitivity, and area under the curve when used to predict individual social needs.

Area-level SDoH measures may provide valuable information about the communities where patients live. However, policymakers, healthcare administrators, and researchers should exercise caution when using area-level adverse SDoH measures to identify individual-level social risks.

Clinical/translational science (CTS) is team-based, requiring effective collaboration and communication across many disciplines involving a variety of stakeholders. We implemented a pre-doctoral team-based training model with didactic and experiential curricular interventions to support the development of CTS research skills in a cross-disciplinary team environment. We assessed the potential impact of this new training model as a team science intervention that can catalyze new cross-disciplinary collaborations across the institution.

Between 2016 and 2020, 32 pre-doctoral students and 26 co-mentors participated in the assessment of the CTS Team program over a two-year period of TL1 training grant support. Data collection and analyses followed a program logic model and used a variety of metrics for clinical and translational scientist career success.

CTS training in the context of CTS Teams supported improved self-efficacy for clinical research skills and resulted in a significant increase in the frequency of participation in cross-disciplinary collaborative activities by both trainees and mentors. Most CTS Team co-mentor pairs had not previously collaborated. Two-thirds of the co-mentors plan to continue collaborating, and most (85%) currently use or plan to use collaboration tools, for example, written collaboration plans, authorship agreements.

The CTS Team training model provides a unique clinical and translational science team training experience that embeds authentic cross-disciplinary research collaboration into PhD research projects. It establishes trainee cohorts that are diverse in terms of scientific disciplines and translational research phases, and creates a new cross-disciplinary community of practice across faculty members and research groups in multiple colleges.

Science Cafés facilitated by the Clinical and Translational Science Institute of Southeast Wisconsin seek to increase health and scientific literacy through informal conversation between researchers and community members. The goal was to understand what factors have the greatest influence on attendees’ perceived changes in health and science literacy levels (PCHSL) to increase impact.

Previous research established the evaluation used in the Science Cafés to measure PCHSL. In this study, comparisons were made between (1) 2 different approaches to Science Cafés (Genomics Science Cafés or Health Science Cafés) and (2) regression models to show which factors best predicted PCHSL.

The approach of the Genomics Science Cafés series to Science Cafés showed a larger impact on PCHSL. Regression models suggest SES and education significantly contributes to PCHSL.

Insights for program development to have greater impact on PCHSL were identified. Continuing to optimize dissemination of research findings to the public is essential for improving community health and well-being.

Clinical and Translational Science Awards (CTSAs) and Practice-Based Research Networks (PBRNs) have complementary missions. We replicated a 2008 survey of CTSA-PBRN leaders to understand how organizational relationships have evolved.

We surveyed 60 CTSA community engagement (CE) Directors and 135 PBRN Directors and analyzed data using between and within-group comparisons.

In total, 43% of CTSA CE Directors (26/60) and 42% of PBRN Directors (57/135) responded. Quantitative responses revealed growing alignment between CTSA/PBRN perceptions, with a few areas of discordance. CE Directors noted declining financial support for PBRNs. PBRN Directors identified greater CTSA effectiveness in PBRN engagement, consultation, and collaborative grant submissions. Qualitative data revealed divergent experiences across CTSA/PBRN programs.

Relationships between CTSAs and PBRNs are maturing; for some that means strengthening and for others a growing vulnerability. Findings suggest a mutual opportunity for PBRNs and CTSAs around applied research. Studies to characterize exemplar CTSA-PBRN collaborations are needed.