Community-based organizations (CBOs) are important equity-promoting delivery channels for evidence-based interventions (EBIs). However, CBO practitioners often cannot access needed support to build EBI skills. Additionally, the capacity-building literature is hindered by inconsistent definitions, limited use of validated measures, and an emphasis on the perspectives of EBI developers versus implementers. To address these gaps, we explored commonalities and differences between CBO practitioners and academics in conceptualizing and prioritizing core EBI skills.

We utilized Group Concept Mapping, a mixed-methods approach connecting qualitative data (e.g., regarding the range of critical EBI skills) and quantitative data (e.g., sorting and ranking data regarding unique skills) to create conceptual maps integrating perspectives from diverse participants. A total of 34 practitioners and 30 academics working with cancer inequities participated in the study.

Participants nominated 581 core skills for EBI use, and our team (including practitioners and academics) identified 98 unique skills from this list. Participants sorted them into conceptual groups, yielding five clusters: (1) using data and evaluation, (2) selecting and adapting EBIs, (3) connecting with community members, (4) building diverse and equitable partnerships, and (5) managing EBI implementation. The ordering of importance and presence of skill clusters were similar across groups. Overall, importance was rated higher than presence, suggesting capacity gaps.

There are helpful commonalities between practitioners’ and academics’ views of core EBI skills in CBOs and apparent capacity gaps. However, underlying patterns suggest that differences between the groups’ perceptions warrant further exploration.

Assess the extent to which the clinical trial registration and reporting policies of 25 of the world’s largest public and philanthropic medical research funders meet best practice benchmarks as stipulated by the 2017 WHO Joint Statement, and document changes in the policies and monitoring systems of 19 European funders over the past year.

Cross-sectional study, based on assessments of each funder’s publicly available documentation plus validation of results by funders. Our cohort includes 25 of the largest medical research funders in Europe, Oceania, South Asia, and Canada.

Scoring all 25 funders using an 11-item assessment tool based on WHO best practice benchmarks, grouped into three primary categories: trial registries, academic publication, and monitoring, plus validation of results by funders.

How many of the 11 WHO best practice items each of the 25 funders has put into place, and changes in the performance of 19 previously assessed funders over the preceding year.

The 25 funders we assessed had put into place an average of 5/11 (49%) WHO best practices. Only 6/25 funders (24%) took the PI’s past reporting record into account during grant application reviews. Funders’ performance varied widely from 0/11 to 11/11 WHO best practices adopted. Of the 19 funders for which 2021(2) baseline data was available, 10/19 (53%) had strengthened their policies over the preceding year.

Most medical research funders need to do more to curb research waste and publication bias by strengthening their clinical trial policies.

The rapid implementation of telemedicine during the COVID-19 pandemic may have exacerbated the existing health disparities. This study investigated the association between the area deprivation index (ADI), which serves as a measure of socioeconomic deprivation within a geographic area, and the utilization of telemedicine in primary care.

The study data source was electronic health records. The study population consisted of patients with at least one primary care visit between March 2020 and December 2021. The primary outcome of interest was the visit modality (office, phone, and video). The exposure of interest was the ADI score grouped into quartiles (one to four, with one being the least deprived). The confounders included patient sociodemographic characteristics (e.g., age, gender, race, ethnicity, insurance coverage, marital status). We utilized generalized estimating equations to compare the utilization of telemedicine visits with office visits, as well as phone visits with video visits.

The study population included 41,583 patients with 127,165 office visits, 39,484 phone visits, and 20,268 video visits. Compared to patients in less disadvantaged neighborhoods (ADI quartile = one), patients in more disadvantaged neighborhoods (ADI = two, three, or four) had higher odds of using phone visits vs office visits, lower odds of using video visits vs office visits, and higher odds of using phone visits vs video visits.

Patients who resided in socioeconomically disadvantaged neighborhoods mainly relied on phone consultations for telemedicine visits with their primary care provider. Patient-level interventions are essential for achieving equitable access to digital healthcare, particularly for low-income individuals.

The Michigan Integrative Well-Being and Inequality (MIWI) Training Program aims to provide state-of-the-art, interdisciplinary training to enhance the methodological skills of early-career scientists interested in integrative approaches to understanding health disparities. The goals of this paper are to describe the scientific rationale and core design elements of MIWI, and to conduct a process evaluation of the first cohort of trainees (called “scholars”) to complete this program.

Mixed methods process evaluation of program components and assessment of trainee skills and network development of the first cohort (n = 15 scholars).

The program drew 57 applicants from a wide range of disciplines. Of the 15 scholars in the first cohort, 53% (n = 8) identified as an underrepresented minority, 60% (n = 9) were within 2 years of completing their terminal degree, and most (n = 11, 73%) were from a social/behavioral science discipline (e.g., social work, public health). In the post-program evaluation, scholars rated their improvement in a variety of skills on a one (not at all) to five (greatly improved) scale. Areas of greatest growth included being an interdisciplinary researcher (mean = 4.47), developing new research collaborations (mean = 4.53), and designing a research study related to integrative health (mean = 4.27). The qualitative process evaluation indicated that scholars reported a strong sense of community and that the program broadened their research networks.

These findings have implications for National Institutes of Health (NIH) efforts to train early-career scientists, particularly from underrepresented groups, working at the intersection of multiple disciplines and efforts to support the formation of research networks.

Midcareer is a critical transition point for biomedical research faculty and a common dropout point from an NIH-funded career. We report a study to assess the efficacy of a group peer mentoring program for diverse biomedical researchers in academic medicine, seeking to improve vitality, career advancement, and cross-cultural competence.

We conducted a stratified randomized controlled trial with a waitlist control group involving 40 purposefully diverse early midcareer research faculty from 16 states who had a first-time NIH R01 (or equivalent) award, a K training grant, or a similar major grant. The yearlong intervention (2 to 3 days quarterly) consisted of facilitated, structured, group peer mentoring. Main study aims were to enhance faculty vitality, self-efficacy in achieving research success, career advancement, mentoring others, and cultural awareness and appreciation of diversity in the workplace.

Compared to the control group, the intervention group’s increased vitality did not reach statistical significance (P = 0.20), but perceived change in vitality was 1.47 standard deviations higher (D = 1.47, P = 0.03). Self-efficacy for career advancement was higher in the intervention group (D = 0.41, P = 0.05) as was self-efficacy for research (D = 0.57, P = 0.02). The intervention group also valued diversity higher (D = 0.46, P = 0.02), had higher cognitive empathy (D = 0.85, P = 0.03), higher anti-sexism/racism skills (D = 0.71, P = 0.01), and higher self-efficacy in mentoring others (D = 1.14, P = 0.007).

The mentoring intervention resulted in meaningful change in important dimensions and skills among a national sample of diverse early midcareer biomedical faculty. This mentoring program holds promise for addressing the urgencies of sustaining faculty vitality and cross-cultural competence.

With persistent incidence, incomplete vaccination rates, confounding respiratory illnesses, and few therapeutic interventions available, COVID-19 continues to be a burden on the pediatric population. During a surge, it is difficult for hospitals to direct limited healthcare resources effectively. While the overwhelming majority of pediatric infections are mild, there have been life-threatening exceptions that illuminated the need to proactively identify pediatric patients at risk of severe COVID-19 and other respiratory infectious diseases. However, a nationwide capability for developing validated computational tools to identify pediatric patients at risk using real-world data does not exist.

HHS ASPR BARDA sought, through the power of competition in a challenge, to create computational models to address two clinically important questions using the National COVID Cohort Collaborative: (1) Of pediatric patients who test positive for COVID-19 in an outpatient setting, who are at risk for hospitalization? (2) Of pediatric patients who test positive for COVID-19 and are hospitalized, who are at risk for needing mechanical ventilation or cardiovascular interventions?

This challenge was the first, multi-agency, coordinated computational challenge carried out by the federal government as a response to a public health emergency. Fifty-five computational models were evaluated across both tasks and two winners and three honorable mentions were selected.

This challenge serves as a framework for how the government, research communities, and large data repositories can be brought together to source solutions when resources are strapped during a pandemic.

Clinical trials provide the “gold standard” evidence for advancing the practice of medicine, even as they evolve to integrate real-world data sources. Modern clinical trials are increasingly incorporating real-world data sources – data not intended for research and often collected in free-living contexts. We refer to trials that incorporate real-world data sources as real-world trials. Such trials may have the potential to enhance the generalizability of findings, facilitate pragmatic study designs, and evaluate real-world effectiveness. However, key differences in the design, conduct, and implementation of real-world vs traditional trials have ramifications in data management that can threaten their desired rigor.

Three examples of real-world trials that leverage different types of data sources – wearables, medical devices, and electronic health records are described. Key insights applicable to all three trials in their relationship to Data and Safety Monitoring Boards (DSMBs) are derived.

Insight and recommendations are given on four topic areas: A. Charge of the DSMB; B. Composition of the DSMB; C. Pre-launch Activities; and D. Post-launch Activities. We recommend stronger and additional focus on data integrity.

Clinical trials can benefit from incorporating real-world data sources, potentially increasing the generalizability of findings and overall trial scale and efficiency. The data, however, present a level of informatic complexity that relies heavily on a robust data science infrastructure. The nature of monitoring the data and safety must evolve to adapt to new trial scenarios to protect the rigor of clinical trials.

Recruitment of study participants is challenging and can incur significant costs. Social media advertising is a promising method for recruiting clinical studies and may improve cost efficiency by targeting populations likely to match a study’s qualifications. Prior systematic reviews of social media as a recruitment tool have been favourable, however, there are no meta-analyses of its cost-effectiveness.

Studies evaluating recruitment costs through social media and non-social media methods were identified on MEDLINE and EMBASE. Articles were screened through a two-step process in accordance with PRISMA guidelines. Cost data were extracted from selected articles and meta-analyzed using the Mantel-Haenszel method. The primary outcome was the relative cost-effectiveness of social media compared to non-social media recruitment, defined as the odds ratio of recruiting a participant per US dollar spent. The secondary outcome was the cost-effectiveness of social media recruitment compared to other online recruitment methods only.

In total, 23 studies were included in the meta-analysis. The odds ratio of recruiting a participant through social media advertising compared to non-social media methods per dollar spent was 1.97 [95% CI 1.24–3.00, P = 0.004]. The odds ratio of recruiting a participant through social media compared to other online methods only was 1.66 [95% CI 1.02–2.72, P = 0.04].

Social media advertising may be more cost-effective than other methods of recruitment, however, the magnitude of cost-effectiveness is highly variable between studies. There are limited data on newer social media platforms and on difficult-to-reach populations such as non-English speakers or older individuals.