Clinical and Translational Science Award (CTSA) Program hubs are well-positioned to advance dissemination and implementation (D&I) research and training capacity nationally, though little is known about what D&I research support and services CTSAs provide. To address this gap, the CTSA Dissemination, Implementation, and Knowledge Transfer Working Group conducted an environmental scan of CTSAs (2017–2018).

Of 67 CTSA institutions, we contacted 43 that previously reported delivering D&I research services. D&I experts from these institutions were emailed a survey assessing D&I resources, services, training, and scientific projects. Responses were categorized and double-coded by study authors using a content analysis approach.

Thirty-five of the 43 D&I experts (81.4%) responded. Challenges to CTSAs in developing and supporting D&I science activities were related to inadequate D&I science workforce (45.7%) and lack of understanding of D&I science (25.7%). Services provided included consultation/mentoring programs (68%), pilot funding/grants (50%), and workshops/seminars/conferences (46%). Training and workforce development in D&I were frequently identified as future priorities. Recommendations included increase training to meet demand (68.6%), accessible D&I tools/resources (34.3%), greater visibility/awareness of D&I methods (34.3%), consultation services (22.9%), and expand D&I science workforce (22.9%).

CTSAs have tremendous potential to support the advancement and impact of D&I science across the translational continuum. Despite the growing presence of D&I science in CTSAs, continued commitment and prioritization are needed from CTSA and institutional leadership to raise awareness of D&I science and its value, meet training demands, and develop necessary infrastructure for conducting D&I science.

Chemical structure is a vital consideration early in the drug development process. Its role in analysis of safety and efficacy is relatively diminished after drugs are approved for clinical use. This interdisciplinary study explores a strategy by which readily available clinical data may be used along with structural features of drugs to identify associations with potential utility for both clinical decision-making and drug development.

Chemical functional groups and structural groups (SGs) of 261 drugs were manually classified in tiers, and their incidence of gastrointestinal (GI) and central nervous system (CNS) adverse drug reactions (ADRs) were obtained from a clinical database. Drugs with an GI or CNS ADR incidence of at least 10% were analyzed for correlations with their functional and SGs.

Eight statistically significant associations were detected by preliminary analysis: piperazine and methylene groups were associated with higher rate of CNS ADRs; while amides, secondary alcohols, and di-substituted phenyl groups were associated with lower rates of GI or CNS ADRs or both.

Although further study is necessary to understand these associations and build upon this strategy, this exploratory analysis establishes a methodology by which chemical properties of drugs may be used to aid in clinical decision-making when choosing between otherwise equivalent drug therapy options, as the presence of specific groups on drugs may be associated with increased or decreased risks of specific ADRs.

Minority and older adult patients remain underrepresented in cancer clinical trials (CCTs). The current study sought to examine sociodemographic inequities in CCT interest, eligibility, enrollment, decline motivation, and attrition across two psychosocial CCTs for gynecologic, gastrointestinal, and thoracic cancers.

Patients were approached for recruitment to one of two interventions: (1) a randomized control trial (RCT) examining effects of a cognitive-behavioral intervention targeting sleep, pain, mood, cytokines, and cortisol following surgery, or (2) a yoga intervention to determine its feasibility, acceptability, and effects on mitigating distress. Prospective RCT participants were queried about interest and screened for eligibility. All eligible patients across trials were offered enrollment. Patients who declined yoga intervention enrollment provided reasons for decline. Sociodemographic predictors of enrollment decisions and attrition were explored.

No sociodemographic differences in RCT interest were observed, and older patients were more likely to be ineligible. Eligible Hispanic patients across trials were significantly more likely to enroll than non-Hispanic patients. Sociodemographic factors predicted differences in decline motivation. In one trial, individuals originating from more urban areas were more likely to prematurely discontinue participation.

These results corroborate evidence of no significant differences in CCT interest across minority groups, with older adults less likely to fulfill eligibility criteria. While absolute Hispanic enrollment was modest, Hispanic patients were more likely to enroll relative to non-Hispanic patients. Additional sociodemographic trends were noted in decline motivation and geographical prediction of attrition. Further investigation is necessary to better understand inequities, barriers, and best recruitment practices for representative CCTs.

The Mentoring Competency Assessment (MCA) is an example of a validated instrument for measuring mentor skills for postsecondary Science, Technology, Engineering, Mathematics, and Medicine research. The purpose of this study was to revalidate the MCA scale using a larger, more diverse population since the original MCA was validated on a small sample of predominantly senior white male faculty.

The MCA was completed by 1626 mentors from a survey data set of 1759 respondents who participated in eight or more hours of face-to-face Entering Mentoring-based training between 2010 and 2019. We conducted principal component analysis (PCA) with varimax rotation to investigate the internal structure of the MCA and Hatcher’s criteria were applied. After a team of mentoring experts independently interpreted the PCA results and reached a consensus on the interpretations of the components, factor analysis and internal consistency reliability analysis were applied to assess the construct validity and the reliability.

While the 26-item MCA instrument was originally validated with six subscales, through the factor and reliability analyses, all the parameter estimates for each item of seven components of 24-item MCA were significant and had relatively high internal consistency; the alpha coefficient for the components ranged from 0.77 to 0.86.

Five items from the MCA have been dropped, leaving a condensed 21 item scale (MCA-21) which loads onto six competencies, and should now be used to effectively measure mentoring skills. We provide recommendations for furthering the scale development and validation of common measures.

An important part of biomedical research is the translation of discoveries into clinical or community applications that impact patient health. For a vast majority of clinical applications and sustainable community interventions, a time-tested way to get innovations to patients is through licensing of the technology and commercial development, often through startups. While biomedical scientists and trainees are schooled in discovery research, the processes of commercialization are foreign or intimidating. Further, many trainees will not aspire to a faculty position, and other avenues of advancement are desirable.

At Case Western Reserve University, we developed and launched a Translational Fellows Program to provide such training for the community, focusing specifically on graduate students and postdoctoral fellows. The goals of this program include familiarizing our trainees with the principles of entrepreneurship, product development, and startups. This is accomplished through study of their laboratory’s technology to identify points of translational focus and to increase awareness to potentially move ideas and products toward societal impact. This program leverages much of our existing infrastructure and provides a mechanism for the prioritization of the translation of the technology as well as “release-time” to promote effort.

Launched in summer 2020, our first cohort had 3 of the 12 fellows launching startups based on their technology and submitting an National Institutes of Health Small Business Innovation Research (SBIR) proposal. At least 80% reported increased knowledge and confidence in five of six key translational competencies.

We are now continuing and improving the program and searching for sustainable support to stabilize the program for a long-term productive future.

Racial disparities in colorectal cancer (CRC) can be addressed through increased adherence to screening guidelines. In real-life encounters, patients may be more willing to follow screening recommendations delivered by a race concordant clinician. The growth of telehealth to deliver care provides an opportunity to explore whether these effects translate to a virtual setting. The primary purpose of this pilot study is to explore the relationships between virtual clinician (VC) characteristics and CRC screening intentions after engagement with a telehealth intervention leveraging technology to deliver tailored CRC prevention messaging.

Using a posttest-only design with three factors (VC race-matching, VC gender, intervention type), participants (N = 2267) were randomised to one of eight intervention treatments. Participants self-reported perceptions and behavioral intentions.

The benefits of matching participants with a racially similar VC trended positive but did not reach statistical significance. Specifically, race-matching positively influenced screening intentions for Black participants but not for Whites (b = 0.29, p = 0.10). Importantly, perceptions of credibility, attractiveness, and message relevance significantly influenced screening intentions and the relationship with race-matching.

To reduce racial CRC screening disparities, investments are needed to identify patient-focused interventions to address structural barriers to screening. This study suggests that telehealth interventions that match Black patients with a Black VC can enhance perceptions of credibility and message relevance, which may then improve screening intentions. Future research is needed to examine how to increase VC credibility and attractiveness, as well as message relevance without race-matching.

As clinical trials were rapidly initiated in response to the COVID-19 pandemic, Data and Safety Monitoring Boards (DSMBs) faced unique challenges overseeing trials of therapies never tested in a disease not yet characterized. Traditionally, individual DSMBs do not interact or have the benefit of seeing data from other accruing trials for an aggregated analysis to meaningfully interpret safety signals of similar therapeutics. In response, we developed a compliant DSMB Coordination (DSMBc) framework to allow the DSMB from one study investigating the use of SARS-CoV-2 convalescent plasma to treat COVID-19 to review data from similar ongoing studies for the purpose of safety monitoring.

The DSMBc process included engagement of DSMB chairs and board members, execution of contractual agreements, secure data acquisition, generation of harmonized reports utilizing statistical graphics, and secure report sharing with DSMB members. Detailed process maps, a secure portal for managing DSMB reports, and templates for data sharing and confidentiality agreements were developed.

Four trials participated. Data from one trial were successfully harmonized with that of an ongoing trial. Harmonized reports allowing for visualization and drill down into the data were presented to the ongoing trial’s DSMB. While DSMB deliberations are confidential, the Chair confirmed successful review of the harmonized report.

It is feasible to coordinate DSMB reviews of multiple independent studies of a similar therapeutic in similar patient cohorts. The materials presented mitigate challenges to DSMBc and will help expand these initiatives so DSMBs may make more informed decisions with all available information.

Studies examining the role of geographic factors in coronavirus disease-2019 (COVID-19) epidemiology among rural populations are lacking.

Our study is a population-based longitudinal study based on rural residents in four southeast Minnesota counties from March through October 2020. We used a kernel density estimation approach to identify hotspots for COVID-19 cases. Temporal trends of cases and testing were examined by generating a series of hotspot maps during the study period. Household/individual-level socioeconomic status (SES) was measured using the HOUSES index and examined for association between identified hotspots and SES.

During the study period, 24,243 of 90,975 residents (26.6%) were tested for COVID-19 at least once; 1498 (6.2%) of these tested positive. Compared to other rural residents, hotspot residents were overall younger (median age: 40.5 vs 43.2), more likely to be minorities (10.7% vs 9.7%), and of higher SES (lowest HOUSES [SES] quadrant: 14.6% vs 18.7%). Hotspots accounted for 30.1% of cases (14.5% of population) for rural cities and 60.8% of cases (27.1% of population) for townships. Lower SES and minority households were primarily affected early in the pandemic and higher SES and non-minority households affected later.

In rural areas of these four counties in Minnesota, geographic factors (hotspots) play a significant role in the overall burden of COVID-19 with associated racial/ethnic and SES disparities, of which pattern differed by the timing of the pandemic (earlier in pandemic vs later). The study results could more precisely guide community outreach efforts (e.g., public health education, testing/tracing, and vaccine roll out) to those residing in hotspots.

The Clinical and Translational Science Award Program (CTSA) Trial Innovation Network (TIN) was launched in 2016 to increase the efficiency and effectiveness of multisite trials by supporting the development of national infrastructure. With the advent of the COVID-19 pandemic, it was therefore well-positioned to support clinical trial collaboration. The TIN was leveraged to support two initiatives: (1) to create and evaluate a mechanism for coordinating Data and Safety Monitoring Board (DSMB) activities among multiple ongoing trials of the same therapeutic agents, and (2) to share data across clinical trials so that smaller, likely underpowered studies, could be combined to produce meaningful and actionable data through pooled analyses. The success of these initiatives was understood to be dependent upon the willingness of investigators, study teams, and US National Institutes of Health research networks to collaborate and share information.

To inform these two initiatives, we conducted semistructured interviews with members of CTSA hubs and clinical research stakeholders that probed barriers and facilitators to collaboration. Thematic analysis identified topics relevant across institutions, individuals, and DSMBs.

The DSMB coordination initiative was viewed as less controversial, while the data pooling initiative was seen as complex because of its potential impact on publication, authorship, and the rewards of discovery. Barriers related to resources, centralization, and technical work were significant, but interviewees suggested these could be handled by the provision of central funding and supportive frameworks. The more intractable findings were related to issues around credit and ownership of data.

Based on our interviews, we conclude with nine recommended actions that can be implemented to support collaboration.

Physician-scientists have long been in high demand owing to their role as key drivers of biomedical innovation, but their dwindling prevalence in research and medical communities threatens ongoing progress. As the principal avenue for physician-scientist development, combined MD–PhD training programs and NIH-funded Medical Scientist Training Programs (MSTPs) must address all aspects of career development, including grant writing skills.

The NIH F-series grants – the F30 grant in particular – model the NIH format of federal funding, and are thus ideal opportunities to acquire biomedical research grant preparation experience. Therefore, in this report, we describe a curricular model through which predoctoral MSTP students obtain exposure to – and training for – F-series grant conceptualization, writing, and evaluation.

Since the development of these longitudinal courses, we observed trending improvements in student funding success rates, particularly among original submissions, and perceived benefits among participating students.

To improve maternal health outcomes, increased diversity is needed among pregnant people in research studies and community surveillance. To expand the pool, we sought to develop a network encompassing academic and community obstetrics clinics. Typical challenges in developing a network include site identification, contracting, onboarding sites, staff engagement, participant recruitment, funding, and institutional review board approvals. While not insurmountable, these challenges became magnified as we built a research network during a global pandemic. Our objective is to describe the framework utilized to resolve pandemic-related issues.

We developed a framework for site-specific adaptation of the generalized study protocol. Twice monthly video meetings were held between the lead academic sites to identify local challenges and to generate ideas for solutions. We identified site and participant recruitment challenges and then implemented solutions tailored to the local workflow. These solutions included the use of an electronic consent and videoconferences with local clinic leadership and staff. The processes for network development and maintenance changed to address issues related to the COVID-19 pandemic. However, aspects of the sample processing/storage and data collection elements were held constant between sites.

Adapting our consenting approach enabled maintaining study enrollment during the pandemic. The pandemic amplified issues related to contracting, onboarding, and IRB approval. Maintaining continuity in sample management and clinical data collection allowed for pooling of information between sites.

Adaptability is key to maintaining network sites. Rapidly changing guidelines for beginning and continuing research during the pandemic required frequent intra- and inter-institutional communication to navigate.

COVID-19 has caused tremendous death and suffering since it first emerged in 2019. Soon after its emergence, models were developed to help predict the course of various disease metrics, and these models have been relied upon to help guide public health policy.

Here we present a method called COVIDNearTerm to “forecast” hospitalizations in the short term, two to four weeks from the time of prediction. COVIDNearTerm is based on an autoregressive model and utilizes a parametric bootstrap approach to make predictions. It is easy to use as it requires only previous hospitalization data, and there is an open-source R package that implements the algorithm. We evaluated COVIDNearTerm on San Francisco Bay Area hospitalizations and compared it to models from the California COVID Assessment Tool (CalCAT).

We found that COVIDNearTerm predictions were more accurate than the CalCAT ensemble predictions for all comparisons and any CalCAT component for a majority of comparisons. For instance, at the county level our 14-day hospitalization median absolute percentage errors ranged from 16 to 36%. For those same comparisons, the CalCAT ensemble errors were between 30 and 59%.

COVIDNearTerm is a simple and useful tool for predicting near-term COVID-19 hospitalizations.

The COVID vaccine trials illustrated the critical need for the development of mechanisms to serve as a bridge between least advantaged communities and researchers. Such mechanisms would increase the number of studies that are designed with community needs and interests in mind, in ways that will close gaps rather than widen them. This paper reports on the creation of the Community Coalition for Equity in Research, a community-driven resource designed to build community capacity to provide researchers with credible and actionable input on study design and implementation and increase researchers’ understanding of factors that influence community support of research.

We provide a description of the Coalition’s structure and process and an evaluation of its first year of operation. Researchers rated their experience very positively and reported that the Coalition’s review will improve their research. Coalition members reported high levels of satisfaction with their participation and the processes set up for them to engage with researchers. Members also largely agreed that their participation has value for their community, and that it has increased their interest in research and the likelihood that they would recommend research participation to others.

The Coalition represents a model for increasing two-way engagement between researchers and the larger community. We are optimistic that the Coalition will continue to develop and grow into a vibrant entity that will bring value to both investigators and our local communities and will increase the consideration of equity as a foundational principle in all translational research.