Controlled clinical trials (CCTs) have traditionally been limited to urban academic clinical centers. Implementation of CCTs in rural setting is challenged by lack of resources, the inexperience of patient care team members in CCT conductance and workflow interruption, and global inexperience with remote data monitoring.

We report our experience during the coronavirus disease 2019 (COVID-19) pandemic in activating through remote monitoring a multicenter clinical trial (the Study of Efficacy and Safety of Canakinumab Treatment for cytokine release syndrome (CRS) in Participants with COVID-19-induced Pneumonia [CAN-COVID] trial, ClinicalTrials.gov Identifier: NCT04362813) at a rural satellite hospital, the VCU Health Community Memorial Hospital (VCU-CMH) in South Hill, VA, that is part of the larger VCU Health network, with the lead institution being VCU Health Medical College of Virginia Hospital (VCU-MCV), Richmond, VA. We used the local resources at the facility and remote guidance and oversight from the VCU-MCV resources using a closed-loop communication network. Investigational pharmacy, pathology, and nursing were essential to operate the work in coordination with the lead institution.

Fifty-one patients with COVID-19 were enrolled from May to August 2020, 35 (69%) at VCU-MCV, and 16 (31%) at VCU-CMH. Among the patients enrolled at VCU-CMH, 37.5% were female, 62.5% Black, and had a median age of 60 (interquartile range 56–68) years.

Local decentralization of this trial in our experience gave rural patients access to a novel treatment and also accelerated enrollment and more diverse participants’ representative of the target population.

Lack of trust toward medical research is a major barrier to research participation, particularly among some population groups. Valid measures of trust are needed to develop appropriate interventions. The study purpose was to compare two previously validated scales that measure trust in biomedical research – one developed by Hall et al. (H-TBR; 2006) and the other by Mainous et al. (M-TBR; 2006) – in relation to socio-demographic variables and attitudes toward research. Differences between Black and White respondents were explored.

Two nearly identical surveys – one with H-TBR and the other with M-TBR – were systematically administered to a convenience sample. Internal consistency reliability of each scale was assessed. Associations were computed between scores on each scale with attitudes toward biomedical research and demographic variables (i.e., gender, age, race, and socioeconomic status). The difference between White and Black respondents on each TBR score while controlling for age, education, and race was also investigated.

A total of 2020 participants completed the H-TBR survey; 1957 completed the M-TBR survey. Mean item scores for M-TBR were higher (F = 56.05, p < 0.001) among Whites than Blacks. Whites also had higher mean item scores than Blacks on H-TBR (F = 7.09, p < 0.001). Both scales showed a strong association with participants’ perceived barriers to research (ps < 0.001) and significant, positive correlations with interest in research participation (ps < 0.001). Age and household income were positive predictors of TBR scores, but the effects of education differed.

Both scales are internally consistent and show associations with attitudes toward research. Whites score higher than Blacks on both TBR scales, even while controlling for age and socioeconomic status.

This paper is the fourth in a 5-part series that focuses on educating and training the clinical and translational science workforce. The goal of this paper is to delineate components of effective career development programs that go beyond didactic training. All academic health centers with a Clinical and Translational Science Award have a KL2 career development award for junior faculty, and many also have a TL1 training program for predoctoral and postdoctoral fellows. The training across these programs varies, however junior investigators across the United States experience similar challenges. Junior investigators can get overwhelmed with the demands of building their own research program, particularly in academia. 1Often, they are sidetracked by competing demands that can derail their progress. In these situations, junior investigators experience frustration and may search for alternative career paths. By providing them with additional professional skills in the 5 domains of: (1) self-awareness; (2) selecting the right topic and securing funding; (3) getting adequate support; (4) working with others; and (5) managing yourself, your career, and your demands. We will give junior investigators additional tools to manage these demands and facilitate their own career success.

Electronic data capture is essential to advancing family-centered coordinated care in early intervention (EI). The purpose of this paper is to report on EI service coordinator response to piloting an electronic parent-reported outcome (e-PRO) assessment as part of their routine workflow, including lessons learned that may inform future phases of e-PRO implementation.

This second pilot study involved families enrolled in a large EI program (n=1040 families) in concert with their implementation of a statewide quality improvement initiative for care plan development and outcomes reporting. A total of 22 EI service coordinators and supervisors were engaged in 3 phases: initial e-PRO intervention, peer-mentor enhancement, and standard recruitment protocol.

Implementation of the e-PRO intervention and peer-mentoring enhancement yielded low enrollment rates over the first 6 months (n=17). A standard recruitment protocol has resulted in enrollment growth (n=83) towards the targeted enrollment rate (n=832).

This study reports on early insights for building and sustaining a productive academic-community partnership for e-PRO implementation to support family-centered coordinated care. Lessons learned from this academic-community partnership with respect to strategies for enhancing community significance, collaboration, return, and control are discussed as they inform further development of this intervention before scale-up.

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.

The main objective of this study was to report stress and anxiety levels during the COVID-19 pandemic on early- to mid-career women researchers in healthcare sciences research and determine the associated factors.

A 50-item self-administered internet questionnaire was developed using a mix of Likert-type scales and open-ended response questions. The survey was distributed June 10–August 3, 2020. Anxiety and stress as well as personal/family demands were assessed through validated measures (Patient Reported Outcomes Measurement Information System [PROMIS]-Anxiety Short Form and Perceived Stress Scale [PSS]) and open-ended responses.

One hundred and fifty-one early-career women in healthcare sciences research completed the survey; mean respondent age was 37.3 ± 5.2 years; and all had a college degree or higher, 50.3% holding a PhD and 35.8% MD. Race and ethnicity were reported in 128; the majority were White (74.0%). One-third (31.2%) reported being “very much” concerned about reaching their research productivity goals and 30.1% were “very much” concerned about academic promotion and tenure. Fifty percent reported a “moderate” PROMIS anxiety score and 72.1% reported a “moderate” PSS score. For the open-ended responses, 65.6% reported a worry about their professional goals because of the COVID-19 pandemic. Major concerns revolved around finances, childcare, and job security.

Throughout the pandemic, early- and mid-career women in healthcare sciences research have reported moderate to high overall stress, anxiety, and worries. These concerns appear related to household settings, additional responsibilities, financial concerns, and reduced research productivity. Institutions and funding agencies should take these concerns into consideration and offer support.

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.

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.

In order to conduct translational science, scientists must combine domain-specific expertise with knowledge on how to identify and cross translational hurdles, and insights on positioning discoveries for the next translational stage. Expert educators from the Clinical and Translational Science Awards (CTSA) Consortium identified 97 knowledge, skills, and abilities (KSAs) important to include in training programs for translational scientists. To assist educators and trainees to use these KSAs, a conceptual model called “Personalized Pathways” was developed that prioritizes KSAs based on trainee background, research area, or phenotype, and expertise on the research team.

To understand how CTSA educators prioritize specific KSAs when developing personalized training plans for different translational phenotypes and to identify areas of similarity and difference across phenotypes.

A web-based, cross-sectional survey of CTSA educators was done. For a selected phenotype, respondents recommended one of four levels of mastery for each of the 97 KSAs. Results were tabulated by frequency, weighted by importance, and divided into tertiles representing high, middle, and lower priority KSAs. Agreement across phenotypes was compared using Krippendorff’s alpha.

Ten KSAs were high training priority for Preclinical, Clinical, and Community-Engaged phenotypes. These address research methods, responsible conduct of research, team building, and communicating research results. Nine KSAs were in the next tertile for priority reflecting KSAs in biostatistics, bioinformatics, regulatory precepts, and translating implications of research findings.

A smaller set of KSAs can be prioritized for training Preclinical-, Clinical-, and Community-Engaged researchers. Future work should explore this approach for other phenotypes.

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.