Clinical research is critical for healthcare advancement, but participant recruitment remains challenging. Clinical research professionals (CRPs; e.g., clinical research coordinator, research assistant) perform eligibility prescreening, ensuring adherence to study criteria while upholding scientific and ethical standards. This study investigates the key information CRP prioritizes during eligibility prescreening, providing insights to optimize data standardization, and recruitment approaches.

We conducted a freelisting survey targeting 150 CRPs from diverse domains (i.e., neurological disorders, rare diseases, and other diseases) where they listed essential information they look for from medical records, participant/caregiver inquiries, and discussions with principal investigators to determine a potential participant’s research eligibility. We calculated the salience scores of listed items using Anthropac, followed by a two-level analytic procedure to classify and thematically categorize the data.

The majority of participants were female (81%), identified as White (44%) and as non-Hispanic (64.5%). The first-level analysis universally emphasized age, medication list, and medical history across all domains. The second-level analysis illuminated domain-specific approaches in information retrieval: for instance, history of present illness was notably significant in neurological disorders during participant and principal investigator inquiries, while research participation was distinctly salient in potential participant inquiries within the rare disease domain.

This study unveils the intricacies of eligibility prescreening, with both universal and domain-specific methods observed. Variations in data use across domains suggest the need for tailored prescreening in clinical research. Incorporating these insights into CRP training and refining prescreening tools, combined with an ethical, participant-focused approach, can advance eligibility prescreening practices.

Community inclusion in research may increase the quality and relevance of research, but doing so in an equitable way is complex. Novel approaches used to build engagement with historically marginalized communities in other sectors may have relevance in the clinical research sector.

To address long-standing gaps and challenges, a stakeholder group was convened to develop a theory of change (ToC), a structured method for obtaining input from stakeholders to enhance the design, conduct, and dissemination of research. The stakeholder group, comprised of Black residents within a metropolitan area, followed a structured monthly meeting schedule for 12 months to produce an outcome map, a model that formally defines aspects of research and engagement for this community.

Stakeholders reported significant improvements in trust in and engagement with research over the 12-month period, but not changes in health empowerment (individual, organizational, or community level). Through this convening process, a ToC and outcome map were developed with the focus of building bidirectional relationships between groups identifying as Black, Indigenous, and People of Color (BIPOC) and researchers in Boston, MA. Additionally, the group developed a community ownership model and guidelines for researchers to adhere to when utilizing the ToC and outcome map with BIPOC communities.

Co-ownership of models to develop bidirectional relationships between researchers and community members, such as the ToC and outcome map, may advance and further the value and reach of community-based participatory research while increasing levels of trust and engagement in research.

The value of Source Data Verification (SDV) has been a common theme in the applied Clinical Translational Science literature. Yet, few published assessments of SDV quality exist even though they are needed to design risk-based and reduced monitoring schemes. This review was conducted to identify reports of SDV quality, with a specific focus on accuracy.

A scoping review was conducted of the SDV and clinical trial monitoring literature to identify articles addressing SDV quality. Articles were systematically screened and summarized in terms of research design, SDV context, and reported measures.

The review found significant heterogeneity in underlying SDV methods, domains of SDV quality measured, the outcomes assessed, and the levels at which they were reported. This variability precluded comparison or pooling of results across the articles. No absolute measures of SDV accuracy were identified.

A definitive and comprehensive characterization of SDV process accuracy was not found. Reducing the SDV without understanding the risk of critical findings going undetected, i.e., SDV sensitivity, is counter to recommendations in Good Clinical Practice and the principles of Quality by Design. Reference estimates (or methods to obtain estimates) of SDV accuracy are needed to confidently design risk-based, reduced SDV processes for clinical studies.

Research study complexity refers to variables that contribute to the difficulty of a clinical trial or study. This includes variables such as intervention type, design, sample, and data management. High complexity often requires more resources, advanced planning, and specialized expertise to execute studies effectively. However, there are limited instruments that scale study complexity across research designs. The purpose of this study was to develop and establish initial psychometric properties of an instrument that scales research study complexity.

Technical and grammatical principles were followed to produce clear, concise items using language familiar to researchers. Items underwent face, content, and cognitive validity testing through quantitative surveys and qualitative interviews. Content validity indices were calculated, and iterative scale revision was performed. The instrument underwent pilot testing using 2 exemplar protocols, asking participants (n = 31) to score 25 items (e.g., study arms, data collection procedures).

The instrument (Research Complexity Index) demonstrated face, content, and cognitive validity. Item mean and standard deviation ranged from 1.0 to 2.75 (Protocol 1) and 1.31 to 2.86 (Protocol 2). Corrected item-total correlations ranged from .030 to .618. Eight elements appear to be under correlated to other elements. Cronbach’s alpha was 0.586 (Protocol 1) and 0.764 (Protocol 2). Inter-rater reliability was fair (kappa = 0.338).

Initial pilot testing demonstrates face, content, and cognitive validity, moderate internal consistency reliability and fair inter-rater reliability. Further refinement of the instrument may increase reliability thus providing a comprehensive method to assess study complexity and related resource quantification (e.g., staffing requirements).

A gap in the literature exists pertaining to a global research nurse/research midwife resources and communication skill set necessary to engage with participants of diverse populations and geographic regions in the community or home-based conduct of decentralized clinical trials.

An embedded mixed methods study was conducted to examine research nurse/research midwife knowledge base, experiences, and communication skill sets pertaining to decentralized trials across global regions engaged in remote research: the USA, Republic of Ireland, United Kingdom, and Australia.

An online survey was deployed across international research nurse/research midwife stakeholder groups, collecting demographics, decentralized trial experience, barriers and facilitators to optimal trial conduct, and the self-perceived communication competence (SPCC) and interpersonal communication competence (IPCC) instruments.

86 research nurses and research midwives completed the survey across all countries: The SPCC and IPCC results indicated increased clinical research experience significantly correlated with increased SPCC score (p < 0.05). Qualitative content analysis revealed five themes: (1) Implications for Role, (2) Safety and Wellbeing, (3) Training and Education, (4) Implications for Participants, and (5) Barriers and Facilitators.

Common trends and observations across the global sample can inform decentralized trial resource allocation and policy pertaining to the research nurse/research midwife workforce. This study demonstrates shared cultural norms of research nursing and midwifery across varied regional clinical trial ecosystems.

To compare how clinical researchers generate data-driven hypotheses with a visual interactive analytic tool (VIADS, a visual interactive analysis tool for filtering and summarizing large datasets coded with hierarchical terminologies) or other tools.

We recruited clinical researchers and separated them into “experienced” and “inexperienced” groups. Participants were randomly assigned to a VIADS or control group within the groups. Each participant conducted a remote 2-hour study session for hypothesis generation with the same study facilitator on the same datasets by following a think-aloud protocol. Screen activities and audio were recorded, transcribed, coded, and analyzed. Hypotheses were evaluated by seven experts on their validity, significance, and feasibility. We conducted multilevel random effect modeling for statistical tests.

Eighteen participants generated 227 hypotheses, of which 147 (65%) were valid. The VIADS and control groups generated a similar number of hypotheses. The VIADS group took a significantly shorter time to generate one hypothesis (e.g., among inexperienced clinical researchers, 258 s versus 379 s, p = 0.046, power = 0.437, ICC = 0.15). The VIADS group received significantly lower ratings than the control group on feasibility and the combination rating of validity, significance, and feasibility.

The role of VIADS in hypothesis generation seems inconclusive. The VIADS group took a significantly shorter time to generate each hypothesis. However, the combined validity, significance, and feasibility ratings of their hypotheses were significantly lower. Further characterization of hypotheses, including specifics on how they might be improved, could guide future tool development.

Diabetes mellitus in underrepresented racial and ethnic groups (URG) is rapidly increasing in incidence and has worse outcomes than diabetes in non-Hispanic White individuals. Rare and Atypical Diabetes Network (RADIANT) established recruitment targets based on the racial and ethnic distribution of the USA to enroll a diverse study population. We examined participation of URG across RADIANT study stages and described strategies to enhance recruitment and retention of URG.

RADIANT is a multicenter NIH-funded study of people with uncharacterized forms of atypical diabetes. RADIANT participants consent online and progress through three sequential study stages, as eligible.

We enrolled 601 participants with mean age 44 ± 16.8 years, 64.4% female. At Stage 1, 80.6% were White, 7.2% African American (AA), 12.2% other/more than one race, and 8.4% Hispanic. Enrollment of URG was significantly below preset targets across most stages. Referral sources differed by race (p < 0.001) but not ethnicity (p = 0.15). Most AA participants were referred by RADIANT investigators (58.5% vs. 24.5% in Whites), whereas flyers, news, social media, and family or friends were more frequent referral sources for White individuals (26.4% vs. 12.2% in AA). Ongoing initiatives to increase enrollment of URG in RADIANT include engaging with clinics/hospitals serving URG, screening electronic medical records, and providing culturally competent study coordination and targeted advertisement.

There is low participation of URG in RADIANT, potentially limiting the generalizability of its discoveries. Investigations into barriers and facilitators for recruitment and retention of URG in RADIANT, with implications for other studies, are ongoing.

The purpose of this scoping review is two-fold: to assess the literature that quantitatively measures outcomes of mentorship programs designed to support research-focused junior faculty and to identify mentoring strategies that promote diversity within academic medicine mentoring programs.

Studies were identified by searching Medline using MESH terms for mentoring and academic medicine. Eligibility criteria included studies focused on junior faculty in research-focused positions, receiving mentorship, in an academic medical center in the USA, with outcomes collected to measure career success (career trajectory, career satisfaction, quality of life, research productivity, leadership positions). Data were abstracted using a standardized data collection form, and best practices were summarized.

Search terms resulted in 1,842 articles for title and abstract review, with 27 manuscripts meeting inclusion criteria. Two studies focused specifically on women, and four studies focused on junior faculty from racial/ethnic backgrounds underrepresented in medicine. From the initial search, few studies were designed to specifically increase diversity or capture outcomes relevant to promotion within academic medicine. Of those which did, most studies captured the impact on research productivity and career satisfaction. Traditional one-on-one mentorship, structured peer mentorship facilitated by a senior mentor, and peer mentorship in combination with one-on-one mentorship were found to be effective strategies to facilitate research productivity.

Efforts are needed at the mentee, mentor, and institutional level to provide mentorship to diverse junior faculty on research competencies and career trajectory, create a sense of belonging, and connect junior faculty with institutional resources to support career success.

Clinical research staff play a critical role in recruiting families for pediatric research, but their views are not well described. We aimed to describe how pediatric research staff build trusting research relationships with patients and their families.

We interviewed research staff at one pediatric research institution and its affiliated academic medical center between November 2020 and February 2021. Staff were eligible if they conducted participant recruitment, consent, and/or enrollment for clinical research. We developed our semi-structured interview guide based on a framework for trusting researcher-community partnerships.

We interviewed 28 research staff, with a median age of 28 years (range 22–50) and a median of 5 years of experience (range 1–29). Interviewees identified factors relevant to relationship building across three levels: the individual staff member, the relational interaction with the family, and the institutional or other structural backdrop. Individual factors included how staff developed recruitment skills, their perceived roles, and their personal motivations. Relational factors spanned four stages of recruitment: before the approach, forming an initial connection with a family, building the connection, and following up. Structural factors were related to access and diversity, clinical interactions, and the COVID-19 pandemic.

Research staff discussed tensions and supports with various actors, challenges with the integration of research and clinical care, the importance of voluntariness for building trust, and multiple contributors to inequities in research. These findings reveal the importance of ensuring research staff have a voice in institutional policies and are supported to advocate for patients and families.

Managing healthcare data is a major challenge for today’s medicine. The use of artificial intelligence and big data tools has allowed solving questions related to this topic. However, the wide heterogeneity in the psychiatric consultation record makes the retrospective analysis of these data limited due to a lack of information or differences between specialists.

We aim to develop a platform that allows the structured record of medical care data (based on dementia) while maintaining flexibility and format for its usefulness during clinical practice in psychiatry.

We developed a web-based platform for the structured and semi-structured record of psychiatric evaluation. The instrument is diagnosed-oriented (for our version we used dementia). We used Core outcome sets and expert opinion to identify the relevant outcomes for the attention.

A web-based platform is presented for the care of people with suspected dementia at different levels of care designed with the potential to record information of interest in research but also of clinical utility for closer follow-up.

This strategy allows developing the proposal towards other pathologies of interest. Also, with the integration of recommendation algorithms, a monitoring and recommendation system could be achieved to promote knowledge of psychiatric illness from routine practice. This proposal intends to have an impact by increasing the quality of care, reducing care times, and providing better approaches from primary care systems.

No significant relationships.