Understanding, categorizing, and using implementation science theories, models, and frameworks is a complex undertaking. The issues involved are even more challenging given the large number of frameworks and that some of them evolve significantly over time. As a consequence, researchers and practitioners may be unintentionally mischaracterizing frameworks or basing actions and conclusions on outdated versions of a framework.

This paper addresses how the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework has been described, summarizes how the model has evolved over time, and identifies and corrects several misconceptions.

We address 13 specific areas where misconceptions have been noted concerning the use of RE-AIM and summarize current guidance on these issues. We also discuss key changes to RE-AIM over the past 20 years, including the evolution to Pragmatic Robust Implementation and Sustainability Model, and provide resources for potential users to guide application of the framework.

RE-AIM and many other theories and frameworks have evolved, been misunderstood, and sometimes been misapplied. To some degree, this is inevitable, but we conclude by suggesting some actions that reviewers, framework developers, and those selecting or applying frameworks can do to prevent or alleviate these problems.

Systematic review and analysis of definitions of translational research.

The final corpus was comprised of 33 papers, each read by at least 2 reviewers. Definitions were mapped to a common set of research processes for presentation and analysis. Influence of papers and definitions was further evaluated using citation analysis and agglomerative clustering.

All definitions were mapped to common research processes, revealing most common labels for each process. Agglomerative clustering revealed 3 broad families of definitions. Citation analysis showed that the originating paper of each family has been cited ~10 times more than any other member.

Although there is little agreement between definitions, we were able to identify an emerging consensus 5-phase (T0–T4) definition for translational research. T1 involves processes that bring ideas from basic research through early testing in humans. T2 involves the establishment of effectiveness in humans and clinical guidelines. T3 primarily focuses on implementation and dissemination research while T4 focuses on outcomes and effectiveness in populations. T0 involves research such as genome-wide association studies which wrap back around to basic research.

We used systematic review and analysis to identify emerging consensus between definitions of translational research phases.

The validated long Research Participant Perception Survey (RPPS-Long) elicits valuable data at modest response rates.

To address this limitation, we developed shorter RPPS-Ultrashort and RPPS-Short versions, fielded them with the RPPS-Long to a random sample of a national research volunteer registry, and assessed response and completion rates, test/retest reliability, and demographics.

In total, 2228 eligible registry members received survey links. Response rates were 64% (RPPS-Ultrashort), 63% (RPPS-Short), and 51% (RPPS-Long), respectively (p<0.001). Completion rates were 63%, 54%, and 37%, respectively (p<0.001). All surveys were reliable with Cronbach α=0.81, 0.84, and 0.87, respectively. Retest reliability was highest for RPPS-short (κ=0.85). Provision of compensation increased RPPS-short completion rate from 54% to 71% (p<0.001). Compensated respondents were younger (p<0.001), with greater minority representation (p=0.03).

Shorter surveys were reliable and produced higher response and completion rates then long surveys. Compensation further increased completion rates and shifted sample age and race profiles.

The updated common rule, for human subjects research, requires that consents “begin with a ‘concise and focused’ presentation of the key information that will most likely help someone make a decision about whether to participate in a study” (Menikoff, Kaneshiro, Pritchard. The New England Journal of Medicine. 2017; 376(7): 613–615.). We utilized a community-engaged technology development approach to inform feature options within the REDCap software platform centered around collection and storage of electronic consent (eConsent) to address issues of transparency, clinical trial efficiency, and regulatory compliance for informed consent (Harris, et al. Journal of Biomedical Informatics 2009; 42(2): 377–381.). eConsent may also improve recruitment and retention in clinical research studies by addressing: (1) barriers for accessing rural populations by facilitating remote consent and (2) cultural and literacy barriers by including optional explanatory material (e.g., defining terms by hovering over them with the cursor) or the choice of displaying different videos/images based on participant’s race, ethnicity, or educational level (Phillippi, et al. Journal of Obstetric, Gynecologic, & Neonatal Nursing. 2018; 47(4): 529–534.).

We developed and pilot tested our eConsent framework to provide a personalized consent experience whereby users are guided through a consent document that utilizes avatars, contextual glossary information supplements, and videos, to facilitate communication of information.

The eConsent framework includes a portfolio of eight features, reviewed by community stakeholders, and tested at two academic medical centers.

Early adoption and utilization of this eConsent framework have demonstrated acceptability. Next steps will emphasize testing efficacy of features to improve participant engagement with the consent process.

Innovative evidence-based interventions are needed to equip research mentors with skills to address cultural diversity within research mentoring relationships. A pilot study assessed initial outcomes of a culturally tailored effort to create and disseminate a novel intervention titled Culturally Aware Mentoring (CAM) for research mentors.

Intervention development resulted in 4 products: a 6 hour CAM training curriculum, a facilitator guide, an online pretraining module, and metrics to evaluate the effectiveness of CAM training.

Participants were 64 research mentors from 3 US research-intensive universities. Quantitative pretraining and posttraining evaluation survey data were collected.

Participants found high value and satisfaction with the CAM training, reported gains in personal cultural awareness and cultural skills, and increased intentions and confidence to address cultural diversity in their mentoring.

Study findings indicate that the CAM training holds promise to build research mentors’ capacity and confidence to engage directly with racial/ethnic topics in research mentoring relationships.

The US National Institutes of Health (NIH) established the Clinical and Translational Science Award (CTSA) program in response to the challenges of translating biomedical and behavioral interventions from discovery to real-world use. To address the challenge of translating evidence-based interventions (EBIs) into practice, the field of implementation science has emerged as a distinct discipline. With the distinction between EBI effectiveness research and implementation research comes differences in study design and methodology, shifting focus from clinical outcomes to the systems that support adoption and delivery of EBIs with fidelity.

Implementation research designs share many of the foundational elements and assumptions of efficacy/effectiveness research. Designs and methods that are currently applied in implementation research include experimental, quasi-experimental, observational, hybrid effectiveness–implementation, simulation modeling, and configurational comparative methods.

Examples of specific research designs and methods illustrate their use in implementation science. We propose that the CTSA program takes advantage of the momentum of the field's capacity building in three ways: 1) integrate state-of-the-science implementation methods and designs into its existing body of research; 2) position itself at the forefront of advancing the science of implementation science by collaborating with other NIH institutes that share the goal of advancing implementation science; and 3) provide adequate training in implementation science.

As implementation methodologies mature, both implementation science and the CTSA program would greatly benefit from cross-fertilizing expertise and shared infrastructures that aim to advance healthcare in the USA and around the world.

Digital health is rapidly expanding due to surging healthcare costs, deteriorating health outcomes, and the growing prevalence and accessibility of mobile health (mHealth) and wearable technology. Data from Biometric Monitoring Technologies (BioMeTs), including mHealth and wearables, can be transformed into digital biomarkers that act as indicators of health outcomes and can be used to diagnose and monitor a number of chronic diseases and conditions. There are many challenges faced by digital biomarker development, including a lack of regulatory oversight, limited funding opportunities, general mistrust of sharing personal data, and a shortage of open-source data and code. Further, the process of transforming data into digital biomarkers is computationally expensive, and standards and validation methods in digital biomarker research are lacking.

In order to provide a collaborative, standardized space for digital biomarker research and validation, we present the first comprehensive, open-source software platform for end-to-end digital biomarker development: The Digital Biomarker Discovery Pipeline (DBDP).

Here, we detail the general DBDP framework as well as three robust modules within the DBDP that have been developed for specific digital biomarker discovery use cases.

The clear need for such a platform will accelerate the DBDP’s adoption as the industry standard for digital biomarker development and will support its role as the epicenter of digital biomarker collaboration and exploration.

Training for the clinical research workforce does not sufficiently prepare workers for today’s scientific complexity; deficiencies may be ameliorated with training. The Enhancing Clinical Research Professionals’ Training and Qualifications developed competency standards for principal investigators and clinical research coordinators.

Clinical and Translational Science Awards representatives refined competency statements. Working groups developed assessments, identified training, and highlighted gaps.

Forty-eight competency statements in 8 domains were developed.

Training is primarily investigator focused with few programs for clinical research coordinators. Lack of training is felt in new technologies and data management. There are no standardized assessments of competence.

Asian Americans constitute 5% of the U.S. population. Their willingness to participate in research is important to examine because it influences participation rates and the representativeness of study results.

A total of 17,339 community members participated from six diverse Clinical and Translational Award (CTSA) sites. Community members were asked about their willingness to volunteer for eight different types of health research, their expectation of monetary compensation for research participation, their trust in research and researchers, their preferred language to receive health information, and their socio-demographic background. We examined Asian Americans’ willingness to participate in various types of health research studies and compared their perceptions with other racial/ethnic groups (i.e., Asian n = 485; African-American n = 9516; Hispanic/Latino n = 1889; Caucasian n = 4760; and other minority n = 689).

Compared to all other racial/ethnic groups, Asian Americans were less willing to participate in all eight types of health research. However, Asian Americans reported a lower amount of fair compensation for research participation than African-Americans and Hispanics/Latinos but were as likely to trust researchers as all other racial/ethnic groups.

Asian Americans are less willing to participate in health research than other racial/ethnic groups, and this difference is not due to dissatisfaction with research compensation or lower trust in researchers. Lack of trust in research and language barriers should be addressed to improve representativeness and generalizability of all populations in research.

The COVID-19 pandemic has created a high demand on personal protective equipment, including disposable N95 masks. Given the need for mask reuse, we tested the feasibility of vaporized hydrogen peroxide (VHP), ultraviolet light (UV), and ethanol decontamination strategies on N95 mask integrity and the ability to remove the infectious potential of SARS-CoV-2.

Disposable N95 masks, including medical grade (1860, 1870+) and industrial grade (8511) masks, were treated by VHP, UV, and ethanol decontamination. Mask degradation was tested using a quantitative respirator fit testing. Pooled clinical samples of SARS-CoV-2 were applied to mask samples, treated, and then either sent immediately for real-time reverse transcriptase–polymerase chain reaction (RT-PCR) or incubated with Vero E6 cells to assess for virucidal effect.

Both ethanol and UV decontamination showed functional degradation to different degrees while VHP treatment showed no significant change after two treatments. We also report a single SARS-CoV-2 virucidal experiment using Vero E6 cell infection in which only ethanol treatment eliminated detectable SARS-CoV-2 RNA.

We hope our data will guide further research for evidenced-based decisions for disposable N95 mask reuse and help protect caregivers from SARS-CoV-2 and other pathogens.

The Latino population in the United States is rapidly growing and faces profound health disparities; however, engagement of Latinos in biomedical research remains low. Our community-based participatory research partnership has recruited 2083 Spanish-speaking Latinos into 21 studies over 15 years. We sought to identify and describe the strategies we have used to successfully recruit and retain Spanish-speaking Latinos in research.

We abstracted and analyzed data from archived study notes, progress reports, team meeting minutes, and in-depth interviews conducted annually from community-based participatory research partnership members. We used a nominal group process to refine and prioritize strategies.

Overall, 13 recruitment strategies and 12 retention strategies emerged. These strategies relied on the creativity and perseverance of the study team and partners.

It is essential that we develop and disseminate effective recruitment and retention strategies that engage Latinos in biomedical research to reduce health disparities and promote health equity.