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.

Nurses are critical to the research enterprise. However all nurses are not prepared to participate as members of the research team since education and training in clinical research nursing and nurse-specific Good Clinical Practice are not consistently included in nursing curricula. The lack of nurse education and training in clinical research and Good Clinical Practice leaves research participants vulnerable with a nursing workforce that is not prepared to balance fidelity to protocol and patient quality care and safety.

A collaborative network of nurses within Clinical and Translational Science Awards and beyond was established to address this education and training need. Over a 2-year period, using expert opinion, Delphi methods, and measures of validity and reliability the team constructed curriculum and knowledge test items.

A pilot modular electronic curriculum, including knowledge pretest and post-tests, in clinical research nursing and nurse-specific Good Clinical Practice competencies was developed.

As the scope and setting of clinical research changes, it is likely that all practicing nurses, regardless of their practice setting or specialty, will care for patients on research protocol, making all nurses, in essence, clinical research nurses. The curriculum developed by this protocol will address that workforce education and training need.

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.

Little is known about practices used to disseminate findings to non-research, practitioner audiences. This study describes the perspectives, experience and activities of dissemination & implementation (D&I) scientists around disseminating their research findings.

The study explored D&I scientists’ experiences and recommendations for assessment of dissemination activities to non-research audiences. Existing list serves were used to recruit scientists. Respondents were asked three open-ended questions on an Internet survey about dissemination activities, recommendations for changing evaluation systems and suggestions to improve their own dissemination of their work.

Surveys were completed by 159 scientists reporting some training, funding and/or publication history in D&I. Three themes emerged across each of the three open-ended questions. Question 1 on evaluation generated the themes of: 1a) promotional review; 1b) funding requirements and 1c) lack of acknowledgement of dissemination activities. Question 2 on recommended changes generated the themes of: 2a) dissemination as a requirement of the academic promotion process; 2b) requirement of dissemination plan and 2c) dissemination metrics. Question 3 on personal changes to improve dissemination generated the themes of: 3a) allocation of resources for dissemination activities; 3b) emerging dissemination channels and 3c) identify and address issues of priority for stakeholders.

Our findings revealed different types of issues D&I scientists encounter when disseminating findings to clinical, public health or policy audiences and their suggestions to improve the process. Future research should consider key requirements which determine academic promotion and grant funding as an opportunity to expand dissemination efforts.

The electronic health record (EHR) and patient portal are used increasingly for clinical research, including patient portal recruitment messaging (PPRM). Use of PPRM has grown rapidly; however, best practices are still developing. In this study, we examined the use of PPRM at our institution and conducted qualitative interviews among study teams and patients to understand experiences and preferences for PPRM.

We identified study teams that sent PPRMs and patients that received PPRMs in a 60-day period. We characterized these studies and patients, in addition to the patients’ interactions with the PPRMs (e.g., viewed, responded). From these groups, we recruited study team members and patients for semi-structured interviews. A pragmatic qualitative inquiry framework was used by interviewers. Interviews were audio-recorded and analyzed using a rapid qualitative analysis exploratory approach.

Across ten studies, 35,037 PPRMs were sent, 33% were viewed, and 17% were responded to. Interaction rates varied across demographic groups. Six study team members completed interviews and described PPRM as an efficient and helpful recruitment method. Twenty-eight patients completed interviews. They were supportive of receiving PPRMs, particularly when the PPRM was relevant to their health. Patients indicated that providing more information in the PPRM would be helpful, in addition to options to set personalized preferences.

PPRM is an efficient recruitment method for study teams and is acceptable to patients. Engagement with PPRMs varies across demographic groups, which should be considered during recruitment planning. Additional research is needed to evaluate and implement recommended changes by study teams and patients.

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.

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.

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.

Air pollution is linked to mortality and morbidity. Since humans spend nearly all their time indoors, improving indoor air quality (IAQ) is a compelling approach to mitigate air pollutant exposure. To assess interventions, relying on clinical outcomes may require prolonged follow-up, which hinders feasibility. Thus, identifying biomarkers that respond to changes in IAQ may be useful to assess the effectiveness of interventions.

We conducted a narrative review by searching several databases to identify studies published over the last decade that measured the response of blood, urine, and/or salivary biomarkers to variations (natural and intervention-induced) of changes in indoor air pollutant exposure.

Numerous studies reported on associations between IAQ exposures and biomarkers with heterogeneity across study designs and methods. This review summarizes the responses of 113 biomarkers described in 30 articles. The biomarkers which most frequently responded to variations in indoor air pollutant exposures were high sensitivity C-reactive protein (hsCRP), von Willebrand Factor (vWF), 8-hydroxy-2′-deoxyguanosine (8-OHdG), and 1-hydroxypyrene (1-OHP).

This review will guide the selection of biomarkers for translational studies evaluating the impact of indoor air pollutants on human health.

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.