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.

To conduct high-quality, rigorous research, and advance scientific knowledge, Translational Teams (TTs) engage in information behaviors, including seeking, using, creating, sharing, storing, and retrieving information, in ways specific to the translational context. Currently, little is known about TTs’ approach to information management. This qualitative pilot study explored how TTs at the University of Wisconsin-Madison interact with information, as well as the scientific and organizational impact of their interactions.

We conducted interviews with ten members of UW TTs. Interviews were transcribed and thematic analysis was conducted.

Four themes emerged: (1) TT members did not recognize the centrality of information or information behaviors to their scientific work; (2) TT members engaged in similar information behaviors and used similar tools across disciplines and topics; (3) TT members did not receive support or guidance from their institution in managing information; and (4) Individualized choices of TT members conflicted at the team level, causing confusion and increasing the potential for data and information loss. Acting as freelance information management agents, TT members made individualized decisions about what tools to use and how to use them, often in a piecemeal manner and without communicating these decisions to other team members.

Research institutions should both encourage teams to discuss their information management approaches at the beginning of a project and provide leaders with training on how to have these conversations and what topics should be included. Additionally, institutions can provide researchers with guidelines for using software platforms to help mitigate information management challenges.

The study objective was to evaluate whether the formation and funding of team science-guided Integrated Clinical Research Ensembles (ICREs) enhance individual faculty productivity, measured by publication and impact factor adjusted citation rates. The setting was a multi-institutional NIH Clinical and Translational Science Award-supported hub.

Monthly faculty publication and impact factor adjusted citation rates were analyzed using data extracted from the hub-managed Faculty Collaboration Database (FCD). The FCD imports indexed publications for all faculty members across four academic institutions, drawing from PubMed and faculty curriculum vitae. Monthly publication counts were modeled using Poisson regression, fitted using generalized estimating equations to account for clustering of observed monthly publication rates of individual faculty. Publication rates were compared before and after ICRE formation and funding, and between faculty in and outside ICREs.

Before joining ensemble teams, ICRE faculty had an 87% higher monthly publication rate than non-ICRE faculty. As ICREs were funded, the monthly publication rate increased an average 72% compared to baseline levels and future citation rates determined by journal impact factors increased by 150%.

Faculty publication and citation rates significantly increased following ICRE funding, demonstrating the potential of structured team science models to boost academic productivity and influence. Faculty inclined to participate in team science through formalized ICREs were already among the more productive faculty.

In Michigan, the COVID-19 pandemic severely impacted Black and Latinx communities. These communities experienced higher rates of exposure, hospitalizations, and deaths compared to Whites. We examine the impact of the pandemic and reasons for the higher burden on communities of color from the perspectives of Black and Latinx community members across four Michigan counties and discuss recommendations to better prepare for future public health emergencies.

Using a community-based participatory research approach, we conducted semi-structured interviews (n = 40) with Black and Latinx individuals across the four counties. Interviews focused on knowledge related to the pandemic, the impact of the pandemic on their lives, sources of information, attitudes toward vaccination and participation in vaccine trials, and perspectives on the pandemic’s higher impact on communities of color.

Participants reported overwhelming effects of the pandemic in terms of worsened physical and mental health, financial difficulties, and lifestyle changes. They also reported some unexpected positive effects. They expressed awareness of the disproportionate burden among Black and Latinx populations and attributed this to a wide range of disparities in Social Determinants of Health. These included racism and systemic inequities, lack of access to information and language support, cultural practices, medical mistrust, and varied individual responses to the pandemic.

Examining perspectives and experiences of those most impacted by the pandemic is essential for preparing for and effectively responding to public health emergencies in the future. Public health messaging and crisis response strategies must acknowledge the concerns and cultural needs of underrepresented populations.