Engaging patients, caregivers, and other stakeholders to help guide the research process is a cornerstone of patient-centered research. Lived expertise may help ensure the relevance of research questions, promote practices that are satisfactory to research participants, improve transparency, and assist with disseminating findings.

Traditionally engagement has been conducted face-to-face in the local communities in which research operates. Decentralized platform trials pose new challenges for the practice of engagement. We used a remote model for stakeholder engagement, relying on Zoom meetings and blog communications.

Here we describe the approach used for research partnership with patients, caregivers, and clinicians in the planning and oversight of the ACTIV-6 trial and the impact of this work. We also present suggestions for future remote engagement.

The ACTIV-6 experience may inform proposed strategies for future engagement in decentralized trials.

Computational analysis of genome or exome sequences may improve inherited disease diagnosis, but is costly and time-consuming.

We describe the use of iobio, a web-based tool suite for intuitive, real-time genome diagnostic analyses.

We used iobio to identify the disease-causing variant in a patient with early infantile epileptic encephalopathy with prior nondiagnostic genetic testing.

Iobio tools can be used by clinicians to rapidly identify disease-causing variants from genomic patient sequencing data.

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.

Community stakeholders often participate in community research training curricula development. There is limited information describing how their input informs curricula. This paper describes input solicitation methods, input received, and examples of its integration.

From June 2014 to June 2016, community members (CMs) and community-based organizations (CBOs) guided curricula development tailored for CMs and CBOs, respectively. Engagement methods included a strategic planning retreat, surveys, a listening session, workgroup meetings, and community engagement studios. Descriptive statistics were used to summarize survey input. For other methods, input was extracted and compiled from facilitator notes.

CMs (n=37) and CBOs (n=83) providing input included patients and caregivers and advocacy, community service, and faith-based organizations, respectively. The major feedback categories were training topic priorities, format (e.g., face-to-face vs. online), logistics (e.g., training frequency), and compensation (e.g., appropriateness). Input directly guided design of CBO and CM curricula (e.g., additional time devoted to specific topics based on feedback) or helped to finalize logistics.

Multiple quantitative and qualitative methods can be used to elicit input from community stakeholders to inform the development of community research training curricula. This input is essential for the development of training curricula that are culturally relevant and acceptable.

The National Academies of Sciences (NAS) emphasize the need for interdisciplinary team science (TS) training, but few training resources are available. COALESCE, an open-access tool developed with National Institutes of Health support and located at teamscience.net, is considered a gold standard resource but has not previously been evaluated. COALESCE launched four learning modules in 2011. The Science of TS (SciTS) module, an interactive encyclopedia, introduces foundational concepts. Three scenario-based modules simulate TS challenges in behavioral, clinical, and basic biomedical sciences. This study examined user characteristics, usage patterns, and effects of completing the four modules on TS knowledge, attitudes, and skills.

Repeated measures ANOVA tested for pre-post changes in performance and compared learning by users with biomedical versus other disciplinary backgrounds.

From 2011 through 2017, the site attracted 16,280 new users who engaged in 6461 sessions that lasted more than 1 min. The modal registrant identified as working in a biomedical field (47%), in an academic institution (72%), and expressed greater interest in the practice than the SciTS (67%). Those completing pre- and post-tests (n = 989) showed significant improvement in knowledge, attitudes, and skills after taking all scenario-based modules (p < 0.005); knowledge and attitudes were unchanged after the SciTS encyclopedia. Biomedical and other health professionals improved comparably.

Evaluation of the TS training tool at teamscience.net indicates broad dissemination and positive TS-related outcomes. Site upgrades implemented between 2018 and 2020, including adding five new modules, are expected to increase the robustness and accessibility of the COALESCE training resource.

The Institute of Translational Health Sciences (ITHS) promotes and supports translational research collaboration between clinicians, communities, and investigators across the five-state Washington, Wyoming, Alaska, Montana, and Idaho (WWAMI) region. The ITHS has developed a collaborative regional clinical research network, the Northwest Participant & Clinical Interactions Network (NW PCI), involving 12 diverse clinical health systems and academic institutions.

This descriptive article details NW PCI’s development, infrastructure and governance, tools, characteristics, and initial outcomes.

Regional NW PCI sites are conducting largely industry-sponsored studies; they are interested in including more grant-funded research. Regional NW PCI sites had over 1,240 open studies involving over 6700 patients in 2016. NW PCI trials are largely industry-sponsored; NW PCI sites are interested in including more grant-funded research. In its first three years, the NW PCI Coordinating Center facilitated regional sites’ participation in 34 new grant and contract applications across diverse topics.

The NW PCI model supports the goals of the developing CTSA Trial Innovation Network by increasing access to cutting-edge research across the Northwestern U.S., by supporting investigators seeking diverse populations, including those with rare diseases, for their research studies, and by providing settings to test implementation and dissemination of effective interventions.

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 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.

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 field of dissemination and implementation science has the potential to narrow the translational research-to-practice gap and improve the use of evidence-based practices (EBPs) within community-based settings. Yet, foundational research related to dissemination efforts, such as understanding researcher attitudes, practices, and the determinants to sharing research findings, is lacking within extant literature.

A sequential explanatory (QUAN $$ \to $$ qual) mixed methods design was used to examine 85 academic researchers’ perspectives and self-reported dissemination methods used to share research outcomes with community stakeholders to better understand researcher’s usual dissemination practices (referred to as dissemination-as-usual). Quantitative surveys collected researcher demographic data, attitudes toward dissemination efforts, and dissemination strategy use.

Multiple linear regression examined predictors of the quantity of dissemination strategies utilized by researchers, finding that years since earning their degree, time spent disseminating, and the number of reasons for engaging in dissemination efforts predicted greater numbers of dissemination strategies utilized by researchers. Individual, semi-structured interviews with a subset of researchers (n = 18) expanded upon quantitative findings, identifying barriers and facilitators to their dissemination efforts. Data strands were integrated using a joint display, and the Dissemination of Research model guided data interpretation. More established researchers experienced fewer barriers and more facilitators to support their use of a variety of dissemination strategies to share findings with community stakeholders. However, researchers reported needing specific training, institutional support, and/or dedicated time to plan and enact dissemination strategies.

The necessary first step in research translation is the dissemination of research evidence, and understanding dissemination-as-usual can identify areas of need to advance translational science.

How the productivity and careers of KL2 scholars compare with scholars receiving individual K-awards is unknown.

The productivity of KL2 scholars (n=21) at our institution was compared with that of K08 (n=34) and K23 (n=26) scholars.

KL2 and K23 scholars had greater productivity than K08 scholars (p=0.01). Professional advancement was similar among groups.

At our institution, scholarly productivity and professional advancement did not differ by type of K-award.

To enhance enrollment into randomized clinical trials (RCTs), we proposed electronic health record-based clinical decision support for patient–clinician shared decision-making about care and RCT enrollment, based on “mathematical equipoise.”

As an example, we created the Knee Osteoarthritis Mathematical Equipoise Tool (KOMET) to determine the presence of patient-specific equipoise between treatments for the choice between total knee replacement (TKR) and nonsurgical treatment of advanced knee osteoarthritis.

With input from patients and clinicians about important pain and physical function treatment outcomes, we created a database from non-RCT sources of knee osteoarthritis outcomes. We then developed multivariable linear regression models that predict 1-year individual-patient knee pain and physical function outcomes for TKR and for nonsurgical treatment. These predictions allowed detecting mathematical equipoise between these two options for patients eligible for TKR. Decision support software was developed to graphically illustrate, for a given patient, the degree of overlap of pain and functional outcomes between the treatments and was pilot tested for usability, responsiveness, and as support for shared decision-making.

The KOMET predictive regression model for knee pain had four patient-specific variables, and an r2 value of 0.32, and the model for physical functioning included six patient-specific variables, and an r2 of 0.34. These models were incorporated into prototype KOMET decision support software and pilot tested in clinics, and were generally well received.

Use of predictive models and mathematical equipoise may help discern patient-specific equipoise to support shared decision-making for selecting between alternative treatments and considering enrollment into an RCT.