This paper presents a descriptive analysis of common data collected across 11 independent studies in the National Research Mentoring Network (NRMN) from 2019 to 2024, focusing on participant demographics and participation in training programs prior to NRMN.

Analyses focused on data from 6,197 survey responses collected primarily at baseline. Descriptive analyses examined participants’ demographic characteristics (gender, combined race/ethnicity, disability, parent/guardian education, and career stage) and participation in training programs prior to NRMN.

The majority of respondents were female (70%). Most respondents identified as White (46%), Black (23%), Asian (18%), and Hispanic (17%). Most respondents (91%) did not report a disability. In terms of career stage, 55% were undergraduates. Sixty-three percent reported that their parent or guardian had completed a bachelor’s degree. Regarding participation in training programs prior to NRMN, 60% had participated in mentor training, and 62% reported involvement in research training activities such as workshops, field experiences, and conferences. Patterns of participation in prior mentorship or research program varied across demographic characteristics.

The NRMN common data reveal the backgrounds of over 6,000 participants engaged in mentorship intervention studies across the biomedical workforce. The dataset includes participants from diverse demographics and career stages with varying levels of participation in prior mentor training and exposure to research training programs. This extensive dataset provides a valuable opportunity to explore the long-term impact of mentorship on the biomedical workforce in future research.

Researchers and research organizations acknowledge the importance of paying research participants but often overlook the process of providing participant payments as a locus for improving equity and inclusion in clinical research. In this conceptual paper, we argue that participants’ lived experiences and social context should be recognized and respected when developing these processes.

We consider how participant payment processes that require specific payment types, delay the timing of payment, or require sharing sensitive information may impose barriers to equitable research. Building on findings from empirical research of participants’ perspectives on respect in research and a relational ethics framework of person-oriented research ethics, we explore how researchers and research organizations can better demonstrate respect through the research participation payment process.

We propose five considerations for demonstrating respect when providing payment: (1) practice cultural humility, (2) be mindful of socioeconomic factors, (3) be flexible, (4) be transparent, and (5) maintain open communication. These considerations are intended to address the lack of existing ethical guidance around the process for participant payments and promote more inclusive clinical research. We provide a set of sample questions for research teams to consider how they could modify their payment processes to better demonstrate respect.

By better demonstrating respect for participants when providing payment, researchers can work toward ensuring that their research procedures are more inclusive, respond to the needs of diverse communities, and result in more equitable relationships with participants.

Social media is increasingly being used in research, including recruitment.

For the Bayley Short Form Formative Study, which was conducted under the the National Children’s Study, traditional methods of recruitment proved to be ineffective. Therefore, digital media were identified as potential channels for recruitment.

Results included successful recruitment of over 1800 infant and toddler participants to the Study.

This paper outlines the methods, results, and future research opportunities.

Along with the greater research enterprise, Institutional Review Boards (IRBs) had to quickly adapt to the COVID-19 pandemic. IRBs had to review and oversee COVID-related research, while navigating strict public health measures and a workforce largely relegated to working from home. Our objectives were to measure adjustments to standard IRB review processes, IRB turnaround time and document and any novel ethical issues encountered.

Structured data requests were sent to members of the Consortium to Advance Effective Research Ethics Oversight directing Human Research Protection Programs (HRPP).

Fourteen of the 32 HRPP director members responded to a questionnaire about their approach to review and oversight during COVID-19. Eleven of the 14 provided summary data on COVID-19-specific protocols and six of the 11 provided protocol-related documents for our review. All respondents adopted at least one additional COVID-19-specific step to their usual review process. The average turnaround time for convened and expedited IRB reviews was 15 calendar days. In our review of the documents from 194 COVID-19-specific protocols (n = 302 documents), we identified only a single review that raised ethical concerns unique to COVID-19.

Our data provide a snapshot of how HRPPs approached the review of COVID-19-specific protocols at the start of the pandemic in the USA. While not generalizable to all HRPPs, these data indicate that HRPPs can adapt and respond quickly response to a pandemic and likely need little novel expertise in the review and oversight of COVID-19-specific protocols.

iLookOut, a web-based child abuse training for early childcare professionals (ECPs), has been shown to improve knowledge and attitudes related to correctly identifying and reporting suspected cases of child abuse. The overarching goal of the present study is to examine “what works for whom” for iLookOut in order to identify strategies for optimizing learner outcomes.

This prospective study enrolled 12,705 ECPs who completed iLookOut (November 2014–December 2018). We used structural equation models to test whether learner demographic and professional characteristics were differentially associated with implementation outcomes (i.e., acceptability and appropriateness) and whether these mediated subsequent indicators of training effectiveness (i.e., gains in knowledge).

Consistent with previous research, individuals with lower baseline knowledge scores showed greater knowledge gains (β = −.57; p < .001). Greater knowledge gains were seen for learners who reported higher acceptability (β = .08; p < .001) or appropriateness (β = .14; p < .001). Implementation outcomes strongly associated with knowledge gains included acceptability for female learners and appropriateness for learners who had not completed high school or had >15 years of experience in childcare settings. Where mediation was found, for the majority of groups, appropriateness emerged as the driving mediator.

Implementation outcomes emerged as important drivers of knowledge change for most groups. The iLookOut Core Training’s use of a multimedia learning environment, video-based storylines, and game-based techniques were endorsed by learners and correlated with increases in knowledge. Future work should explore why aspects of the iLookOut training are rated as less acceptable or appropriate by some groups and what changes would improve efficacy for low performing learners.

Point-of-care technologies (POCTs) have grown increasingly prevalent in clinical and at-home settings, offering various rapid diagnostic capabilities. This study presents findings from a nationwide survey conducted between November 2023 and January 2024, capturing clinician perceptions of POCTs.

The survey was distributed via email to healthcare professionals through academic and industry listservs and through LinkedIn posts. A total of 159 responses were analyzed.

Core priorities, including accuracy, ease of use, and availability, remain consistently valued over the years. However, several perceived benefits, including continuous patient monitoring, diagnostic certainty, and patient management exhibited significant declines in agreement compared to previous years. Despite this, clinician perceptions of POCTs’ abilities to enhance patient–provider communication remained stable. Evolving concerns may reflect heightened expectations and greater scrutiny as these technologies become commonplace. Agreement that POCTs may undermine clinical expertise increases, while concerns related to reimbursement and usability decline. Pilot questions related to artificial intelligence (AI) and machine learning (ML) indicated moderate openness to adopting AI-enhanced POCTs, particularly with tools offering novel clinical insights.

While POCTs continue to be an asset in clinical settings, the findings of this study suggest a shift in provider attitudes toward a more neutral standpoint. Limitations include a low response rate, self-selection, and missing demographic data from a subset of participants. Future surveys will further integrate AI/ML-related questions while prioritizing broader demographic and geographic reach.

A majority of transplanted organs come from donors after brain death (BD). Renal grafts from these donors have higher delayed graft function and lower long-term survival rates compared to living donors. We designed a novel porcine BD model to better delineate the incompletely understood inflammatory response to BD, hypothesizing that adhesion molecule pathways would be upregulated in BD.

Animals were anesthetized and instrumented with monitors and a balloon catheter, then randomized to control and BD groups. BD was induced by inflating the balloon catheter and animals were maintained for 6 hours. RNA was extracted from kidneys, and gene expression pattern was determined.

In total, 902 gene pairs were differently expressed between groups. Eleven selected pathways were upregulated after BD, including cell adhesion molecules.

These results should be confirmed in human organ donors. Treatment strategies should target involved pathways and lessen the negative effects of BD on transplantable organs.

Integrating community expertise into scientific teams and research endeavors can holistically address complex health challenges and grand societal problems. An in-depth understanding of the integration of team science and community engagement principles is needed. The purpose of this scoping review was to identify how and where team science and community engagement approaches are being used simultaneously in research.

We followed Levac’s enhancement of Arksey and O’Malley’s Scoping Review Framework and systematically searched PubMed, CINAHL, Scopus, ERIC, and Embase for team science and community engagement terms through January 2024.

Sixty-seven articles were reviewed. Publications describing integrated team science and community-engaged research have increased exponentially since 2004. Over half were conducted outside of the U.S., utilized qualitative methods, included community-researcher co-development of research question and study design, and described team partnership goals, roles, and management. Fewer studies evaluated partnership, built community capacity, described financial compensation to communities, or described team dynamics facilitation.

As researchers continue to integrate community engagement and team science, common criteria and strategies for integrating the approaches are needed. We provide 19 recommendations for research teams, research institutions, journals, and funding bodies in service of advancing the science and practice of this integration.

Artificial intelligence (AI) technology is rapidly entering biomedical research, and there is a need to assess and develop curricula that address trainees’ learning objectives and interests. Studies of biomedical workforce development show that the prospective engagement of students in formulating educational objectives and activities improves motivation and learning outcomes. This study aimed to explore the educational applications of a novel AI-powered technology in undergraduate education.

A mixed-methods approach using elicitation interviews and cultural domain analysis was applied to identify the salience of ideas around the educational uses of Functional Unit State Identification & Navigation with Whole Slide Images (FUSION), an AI-powered cell-visualization technology. Interviews from 21 students were reduced to learning application statements and assessed for cultural salience and clustering for potential educational applications.

Saturation was reached after 11 interviews, and analysis resulted in eight clusters of 25 unique consensus-based statements. Students thought of the technology as a tool for cell analysis and measuring, but they also viewed applications for medical and K-12 education, public engagement, and note-keeping for technology research. Methodologically, our study demonstrates the potential of cultural consensus for learner-centered curriculum development.

Our findings suggest that trainees perceive many educational uses of FUSION, including those that fit traditional biomedical research curricula and translational applications. Trainees should be engaged in co-design to support and guide technology translation for educational use.

Real-world data, such as administrative claims and electronic health records, are increasingly used for safety monitoring and to help guide regulatory decision-making. In these settings, it is important to document analytic decisions transparently and objectively to assess and ensure that analyses meet their intended goals.

The Causal Roadmap is an established framework that can guide and document analytic decisions through each step of the analytic pipeline, which will help investigators generate high-quality real-world evidence.

In this paper, we illustrate the utility of the Causal Roadmap using two case studies previously led by workgroups sponsored by the Sentinel Initiative – a program for actively monitoring the safety of regulated medical products. Each case example focuses on different aspects of the analytic pipeline for drug safety monitoring. The first case study shows how the Causal Roadmap encourages transparency, reproducibility, and objective decision-making for causal analyses. The second case study highlights how this framework can guide analytic decisions beyond inference on causal parameters, improving outcome ascertainment in clinical phenotyping.

These examples provide a structured framework for implementing the Causal Roadmap in safety surveillance and guide transparent, reproducible, and objective analysis.

Although the involvement of citizen scientists in research can contribute to scientific benefits, much remains unknown about participants’ lived experiences in research. Thus, the purpose of this study was to explore how citizen scientists describe their role in, motivation for, and communication with researchers.

In-depth interviews (N = 9) were conducted with citizen scientists at a translational health research center.

Key results include that citizen scientists were invested in learning researchers’ discipline-specific language and viewed small group sizes as conducive to their active participation.

Programs can apply these findings in an effort to improve citizen scientists’ long-term engagement in research.