Community–academic partnerships are collaborations involving academic and practice stakeholders. Increasingly, community–academic partnerships are being formed to enhance underrepresented communities’ engagement in research and to create opportunities for co-designed research that addresses the community’s priorities, focusing on outcomes the community considers most relevant [Reference Saleh, Saelens, Hayes and Coker1] and designed to be patient-centered and accessible. These partnerships are critical for implementation science when academic researchers may poorly understand methods for effectively adopting and implementing evidence-based practices in community settings [Reference Drahota, Meza and Brikho2–Reference Shelton, Adsul, Oh, Moise and Griffith4].
Federally Qualified Health Centers (FQHCs) are essential community partners for delivering real-world interventions to reduce asthma inequities in medically underserved communities. They provide safety-net primary care to populations in the USA [Reference Aschbrenner, Cruz and Kruse5]. FQHCs provide care for 1 in 11 of the US population, including one-third of those living in poverty, 25% of racial and ethnic minorities, 20% of uninsured persons, and ∼ 50% of Medicaid beneficiaries [6]. FQHCs also serve a disproportionate share of those who experience an unequal burden of chronic conditions, such as asthma (20% in FQHCs vs. 15% in the general population) [6]. When efforts are taken to build research and organizational capacity in these settings, FQHCs can engage primary care clinicians and staff and can enroll large numbers of individuals who have been historically underrepresented in biomedical research as evidenced most strikingly by the more than 10,000 participants recruited from FQHCs nationally for enrollment in the All of Us Research Program [Reference Inokuchi, Mehta and Burke7].
Primary care clinicians deliver up to 60% of asthma care in the US [Reference Akinbami, Santo, Williams, Rechtsteiner and Strashny8], and uncontrolled asthma is common in primary care settings [Reference Ortega, Bharmal and Khatri9] where there is less time and resources to achieve asthma control, relative to specialty care. These care challenges are even more pronounced in FQHCs where there are additional barriers such as inadequate reimbursement, high workforce attrition, high patient poverty and disease burden [Reference Aschbrenner, Cruz and Kruse5], less access to newer medications, including biologics, and other pressing social needs. Specific patient populations who receive care at FQHCs experience significant health inequities in asthma prevalence and disease burden. For example, those living below the poverty level have higher asthma prevalence compared to those living above the poverty level [10]. The asthma disease burden is particularly high among Black patients. Black adults have higher asthma prevalence (10.9%) relative to White (7.6%) and Hispanic adults (6.4%). Asthma mortality rates are also higher among Black adults (29.7/million) compared to White adults (11.8/million) and Hispanic adults (7.8/million) [10], reflecting their greater likelihood to experience a severe asthma exacerbation [Reference Lugogo, Judson and Haight11]. These data highlight that the patients served in FQHCs would most benefit from effective interventions to address unequal disease burden.
The purpose of the present manuscript is to use implementation science frameworks to inform the design of data collection and analysis to advance understanding of perceived and actual facilitators and barriers to implementation of a novel asthma intervention in FQHCs before initiating a practice-based clinical trial at these sites. Specifically, we used both the RE-AIM (Reach-Effectiveness-Adoption-Implementation-Maintenance) Model [Reference Glasgow, Harden and Gaglio12–Reference Mendel, Meredith, Schoenbaum, Sherbourne and Wells15] and the Consolidated Framework for Implementation Research (CFIR) [Reference Damschroder16,17], following conventions for operationalizing the constructs [Reference Kegler, Liang and Weiner18].
Methods
Overview
We used qualitative descriptive approaches grounded in naturalistic inquiry [Reference Bradshaw, Atkinson and Doody19] to guide our data collection and analytic approaches in exploring this study’s implementation metrics of interest. The qualitative data were collected as part of a pre-implementation assessment of local FQHCs who were approached to participate in an upcoming multi-site group-randomized clinical trial (RCT) of a shared decision-making (SDM) intervention to enhance asthma outcomes among Black adults with uncontrolled asthma. The RE-AIM [Reference Glasgow, Harden and Gaglio12–Reference Mendel, Meredith, Schoenbaum, Sherbourne and Wells15] and CFIR [Reference Damschroder16,17] frameworks allowed us to learn about the facilitators and barriers to trial implementation before roll-out and planned delivery of intervention components. We used the guidelines in the Standards for Reporting Qualitative Research checklist (Supplement Table 1) to foster comprehensive reporting of the qualitative data collected in the pre-trial phase [Reference O’Brien, Harris, Beckman, Reed and Cook20].
Site selection
We identified four FQHCs in New York City and New Jersey serving a predominantly Black adult population with asthma to learn clinicians’ and administrators’ perspectives of pre-trial implementation indicators, including anticipated barriers and facilitators to the planned multi-site RCT. Participating sites either expressed an interest in trial participation or were eligible for participation. Potential sites were members of the Clinical Directors Network’s (CDN) extensive practice-based research network (PBRN), our community–academic liaison for this project. CDN is a not-for-profit clinician membership organization, PBRN, and clinician training organization, founded to provide peer-initiated activities for clinicians practicing in low-income, minority, and other underserved communities. CDN’s overall goal is to translate clinical research into clinical practice for the enhancement of health equity and improvement of public health.
Asthma intervention
The Brief Evaluation of Asthma Therapy (BrEAThe) intervention trains clinicians to deliver a four-step 9-minute SDM intervention using motivational interviewing techniques focused on asthma self-management integrated into an office visit for uncontrolled asthma. Training required 2 hours of instruction. Office visits are audio recorded and scored for fidelity by an adjudicator masked to assignment. Feedback is then provided within 48 hours of the office visit via an email to the clinician. The BrEAThe intervention has undergone feasibility testing and has been shown to be efficacious in improving asthma control for three months post-intervention in a population of Black adults with uncontrolled asthma [Reference George, Bruzzese and Lynn21,Reference George, Pantalon and Sommers22]. In this group-randomized efficacy-implementation trial, we plan to compare asthma control among Black adults receiving the active or dose-matched attention control condition in a 12-month longitudinal study. Clinicians will be randomized to deliver either a brief SDM (i.e., 9 minutes) intervention using motivational interviewing (active) or a 9-minute healthy exercise/eating discussion (control condition) at a single office visit [Reference George, Bruzzese and Lynn21,Reference George, Pantalon and Sommers22]. A web-based application (’app’) will be used in the trial to prompt the clinician through the scripted steps of the active and control interventions and visits will be audio recorded to allow assessment of fidelity. Study staff from the Clinical Directors Network (CDN) will support the project by screening patients from primary care clinician panels for uncontrolled asthma, enrolling those interested, and collecting all data.
Interview guide development
We followed best practices for the development of an interview guide [Reference Kallio, Pietilä, Johnson and Kangasniemi23], consulting with an implementation science expert (RS) to draft an initial guide informed by constructs from the RE-AIM and CFIR frameworks [Reference King, Shoup and Raebel24]. RE-AIM provides guidance in tracking dissemination and implementation outcomes, and CFIR helps identify and explain multi-level contextual factors that influence successful implementation. Internal piloting of the guide allowed for item refinement and order. The guide was iteratively refined in that what was learned from earlier interviews informed later interviews. The interview guide integrates constructs from the RE-AIM framework (Reach [patient engagement], Effectiveness [impact on outcomes], Adoption [provider acceptance], Implementation [organizational and workflow integration], and Maintenance [sustainability over time]) to assess the likelihood of successful adoption and implementation. Additionally, facilitators and barriers to implementation are mapped to the CFIR dimensions ensuring a structured evaluation of implementation factors (Intervention Characteristics [usefulness, feasibility], Inner Setting [organizational climate, leadership support], Outer Setting [broader healthcare challenges], Characteristics of Individuals [provider perceptions], and Implementation Process [facilitators, barriers, and long-term success factors]) (see Table 1).
Interview guide informed by the RE-AIM and CFIR frameworks
RE-AIM = Reach-Effectiveness-Adoption-Implementation-Maintenance; CFIR = Consolidated Framework for Implementation Research; BrEAThe = Brief Evaluation of Asthma Therapy.
Population studied and recruitment
We used purposive sampling to identify clinicians responsible for a caseload of adults with asthma or administrators responsible for chronic disease management initiatives at their respective FQHC. All who were approached agreed to be interviewed. Participants received the consent form in advance, and study staff reviewed it with participants, answering any questions pertaining to the purpose of study procedures, prior to obtaining verbal informed consent. Basic sociodemographic data, that is, sex, age, race, ethnicity, role, and discipline, were collected after consent and prior to the start of the interview. All data were stored on a HIPAA-compliant server behind a password protected firewall accessible only to the study team. The study was approved by the Western Institutional Review Board, Inc. (tracking ID # 20211166). Interviews were conducted between November 2021 and March 2022.
Data collection
An experienced qualitative expert (MG) and trained interviewer (SK) together conducted individual semi-structured interviews. All interviews were conducted on a HIPAA-compliant virtual platform; only audio recordings were retained. Once a verbatim transcript had been created, audio recordings were deleted. All participants were provided with a $50 gift card for their time.
Qualitative analysis
Transcripts were transcribed and inductively coded by an interdisciplinary team (MG [nurse scientist], SS [research associate], KD [public health master’s student], JMB [psychologist]) using conventional content analysis to build an iterative codebook that directed subsequent analysis. In this process, the coding team first read transcripts independently to identify codes, that is, concise representations of core concepts discussed by participants [Reference Sandelowski25]. Coding conflicts were resolved through group consensus. Codes representing similar aspects of a concept were grouped to form categories or subthemes. Lastly, overarching themes that cut across the interviews were identified. A saturation table was constructed to track code identification chronologically. When no new codes were identified in later interviews, data collection ended as the sample was determined to be large enough to provide comprehensive data. NVIVO 12 (Lumivero, Denver, CO) was used to manage data. Multiple approaches were used to reduce the risk of bias in collecting and analyzing the qualitative data. These included, but were not limited to, peer debriefing to enhance the credibility of analysis, a codebook to foster code application consistency, and interprofessional coding teams to increase the likelihood of unbiased interpretations [Reference Guba26].
Results
Sixteen key stakeholders participated: eight administrators, six clinicians, and two individuals in clinician and administrator roles. The 10 clinician/clinician-administrators included 4 physicians, 3 nurse practitioners, 2 nurses, and 1 physician assistant. Table 2 provides the demographic characteristics of the participants. Interviews averaged 36 minutes in length (range 24–49 minutes). All but one category demonstrated saturation by interview 13 (see Supplemental Table 2).
Demographics and roles of the interviewed stakeholders
Themes
Three overarching themes related to implementation of the proposed RCT in the FQHC were identified. Each of these themes corresponded to key dimensions of RE-AIM and CFIR: multi-level factors influencing implementation (aligned with RE-AIM Adoption and Implementation; CFIR Inner Setting, Outer Setting, and Characteristics of Individuals), pandemic-specific concerns (aligned with RE-AIM Implementation and Maintenance; CFIR Outer Setting), and unintended consequences of implementation (aligned with RE-AIM Effectiveness; CFIR Process and Characteristics of Individuals). Supporting exemplars are noted in the text below and/or in Table 3.
Additional exemplar quotes
Multi-level factors that can impact implementation
In this theme, participants identified barriers and facilitators that would make it more or less likely that the RCT and/or intervention components would be successfully implemented in the FQHCs.
Patient-level factors (RE-AIM reach; CFIR patient needs and resources)
Participants identified patient-related barriers and facilitators that could impact RCT success. Existing trust between clinicians and patients was seen as a facilitator to recruitment and engagement. One administrator (Site 2) said, “Most of them [clinicians] are women of color, which is the majority of our patients, so that’s easier to build trust.”
However, behavioral and socioeconomic challenges were seen as key barriers: “The biggest barrier is having them [patients] be interested in how to take care of themselves,” said another administrator (Site 4). Other anticipated obstacles to patient participation included high rates of multiple chronic conditions, substance use disorders, poverty, unstable housing, and low educational attainment.
Clinician-level factors (RE-AIM adoption; CFIR characteristics of individuals and inner setting)
While lack of clinician time to participate in research during clinical hours was seen as the primary obstacle to RCT implementation, this was balanced by the desire to learn new interventions, particularly if it was seen as benefiting patients. One administrator said, “The providers are always willing and wanting to participate in anything that’s going to better the health of their patients” (Site 4, Administrator).
Administrative considerations (RE-AIM implementation; CFIR inner setting)
Buy-in across all levels of FQHC staff, from clerical to leadership, was critical to the successful roll-out of research at FQHCs. Some centers had dedicated research champions who were seen as ensuring successful trial implementation. For other administrators, research endeavors were seen as necessary to attract new patients. “It’s going to be additional patients for the clinic, so our numbers are gonna’ go up,” said one administrator (Site 4). Equally appealing was the possibility that the intervention could effectively enhance disease control, thus decreasing the number of unplanned urgent visits.
Organizational-level factors (RE-AIM implementation and maintenance; CFIR inner setting and outer setting)
Characteristics of the FQHC practice model that were perceived as enabling RCT implementation included a focus on serving the community and on quality improvement. One clinician said, “We’re very quality assurance [oriented]. We really do a lot of best practice models, and we are always giving statistics” (Site 1). However, heavy clinician workloads may impede RCT implementation, leading to clinician burnout and attrition. “It’s very hard sometimes. You have to see a certain number of patients; double-booked. It’s a lot. A big turnover, sometimes. Right now, we’re settled [i.e., not experiencing staff turnover]. I don’t know how long it’s gonna’ last,” reported one clinician (Site 1).
Shared decision-making (SDM) intervention considerations (RE-AIM effectiveness; CFIR intervention characteristics)
Upon learning about the intervention components and required training for interventionists to deliver the active or control interventions, participants reflected on components of the intervention that would impede or foster implementation. Two impediments were (1) length of the training (2 hours for the active SDM intervention) and (2) the potential perceived risk that a clinician randomized to serve as an interventionist might see integrating the 9-minute research intervention into an office visit as an added burden. This was countered by strong support for the intervention components, that is, SDM and motivational interviewing, which were characterized as brief, evidence-based, and tailored. In addition, motivational interviewing training was perceived as beneficial to the clinicians’ continuing educational needs and was viewed as a valuable skill that would apply to patient populations beyond those with uncontrolled asthma. Further, current asthma guidelines were described as “terrible” (Site 2, Clinician/Administrator), and the SDM (active) intervention was seen as a way of overcoming limitations of current asthma guidelines. The plan to offer patient remuneration at each data collection point was considered respectful of patient’s time and perceived as potentially helpful in overcoming some of the individual-level barriers identified.
Implementation considerations during the COVID-19 pandemic with implications for current healthcare delivery challenges
In this second theme, clinicians and administrators highlighted factors specific to the pandemic that would serve as facilitators or barriers to conducting the trial in the context of COVID-19, mapping to RE-AIM Implementation and Maintenance and CFIR Outer setting. Importantly, these factors are relevant to ongoing changes in health care delivery, for example, telehealth options after the pandemic.
Barriers to implementation
Interviews were conducted during the pandemic and reflected concerns common in the clinical care setting: frequent COVID-19 cases among staff and mandated isolation periods left FQHCs chronically understaffed. Staff burnout and the loss of staff to more lucrative offers from nearby hospital systems amplified understaffing challenges then and now.
Facilitators to implementation
Participants perceived several pandemic-specific factors as making it more likely that the intervention could be successfully implemented after the pandemic. For example, increased remuneration for telehealth increased providers’ interest in and use of telehealth. Despite the connectivity issues that were commonly experienced by low-income communities in New York during the pandemic [Reference Kang27], one administrator noted, “to my amazement, a lot of the patients do like telehealth, you know, ‘cause they don’t have to come in” (Site 4). Additional enabling factors included the availability of large clinical spaces that could be used for research since telehealth has replaced many in-person office visits. Additionally, the increased attention on the potential adverse effects of COVID-19 infections among those with asthma in the media was seen as making it more likely that patients would be interested in enrolling in studies to improve asthma control.
Unintended consequences of implementation
Participants identified potential unintended consequences of the intervention in this final theme (related to RE-AIM Effectiveness; CFIR Process and Characteristics of Individuals). Two potentially adverse outcomes were identified: the risk of increasing patients’ anxiety about asthma control during a time of already heightened anxiety about asthma and COVID-19, as well as the risk that longer office visits would be necessary as many patients have multiple chronic conditions, not only uncontrolled asthma. However, all participants were optimistic about the likelihood of successful implementation if challenges were recognized and managed.
Discussion
Although each clinical setting will have its own unique barriers and facilitators that need to be understood, this paper contributes to understanding the factors that may influence implementation in the context of FQHCs, for example, high clinician attrition, demanding appointment schedules, an essential but understudied implementation setting for addressing inequities [Reference Baumann, Shelton, Kumanyika and Haire-Joshu28]. This step is essential in ensuring a safe and effective implementation of the asthma control RCT, as done in previous practice-based FQHC studies [Reference Matthews, Watson, Duangchan, Steffen and Winn29–Reference Wolff, McHugh, Qadir, Lassar, Tao and Stulberg31]. In this qualitative assessment of pre-trial implementation factors, clinicians and administrators identified three broad themes related to implementation of the proposed asthma control RCT in their FQHC that would increase or reduce the likelihood for success of the BrEAThe trial: (1) multi-level factors (including patient-level factors, clinician-level factors, administrative considerations, organizational-level factors, and intervention components); (2) pandemic-specific concerns with implications for implementation feasibility in the current healthcare delivery environment; and (3) the potential for unintended consequences of implementing the intervention. These findings align with implementation science frameworks, specifically the RE-AIM framework, which assesses Reach, Effectiveness, Adoption, Implementation, and Maintenance, and the CFIR framework, which examines inner and outer setting factors, individual characteristics, intervention characteristics, and process elements.
This study highlights facilitators and barriers affecting RCT implementation at different levels, aligning with RE-AIM (Adoption, Implementation, Maintenance) and CFIR (Inner Setting, Characteristics of Individuals, and Intervention Characteristics). Many of the variables our participants identified as likely to increase or reduce successful trial implementation have been reported previously as they relate to communities that are underrepresented in biomedical research generally [Reference Inokuchi, Mehta and Burke7,Reference Thakur, Lovinsky-Desir and Appell32], and FQHCs specifically [Reference LeBlanc, Testa and Waterman33,Reference Peacock, Saltzman and Denson34]. For example, trusting relationships between patients and providers and a commitment to the community are at the core of the care that FQHCs deliver; these features of patient-centered care are known to foster research participation by groups who are underrepresented in biomedical research [Reference Thakur, Lovinsky-Desir and Appell32]. However, these enabling factors would likely be offset by the constraints of working in resource-scarce environments [Reference Choi, Weech-Maldonado and Powers35] and the demands that impacted work engagement and burnout during the pandemic [Reference Peacock, Saltzman and Denson34] which have consequences for impeding research engagement.
Interestingly, the FQHC clinician and administrator participants interviewed during COVID-19 did not see the pandemic as a barrier to research but rather as an unparalleled opportunity for conducting clinical research then and now. While this was not true for many academic research enterprises [Reference Nomali, Mehrdad and Heidari36,Reference Karimi-Maleh, Dragoi and Lichtfouse37], clinical research conducted in the community was impacted to a lesser extent because technology allowed for the online delivery of interventions and remote data collection, aspects of telehealth that address the ongoing need for alternative health care delivery post-pandemic. In addition, subjects’ fear of contracting the virus during travel or long waits at research settings were mitigated when home visits or local community facilities could be used as places to conduct research or collect data [Reference Nomali, Mehrdad and Heidari36].
Our participants also perceived that their patients with asthma were experiencing more anxiety during the pandemic. During this time, there was a great deal of concern that COVID-19 infection might lead to more serious adverse outcomes for those with chronic respiratory conditions. This was cited as the reason for increased levels of anxiety observed among those with asthma, relative to those without asthma [Reference Ekström, Mogensen and Georgelis38,Reference de Boer, Houweling, Hendriks, Vercoulen, Tramper-Stranders and Braunstahl39]. Our participants believed that they could channel this anxiety into greater participant enrollment even after the pandemic. While anxiety has been shown to increase information-seeking behaviors [Reference Charpentier, Cogliati Dezza, Vellani, Globig, Gädeke and Sharot40] this may not translate to clinical trial participation, particularly in FQHCs [Reference Inokuchi, Mehta and Burke7]. For example, to successfully recruit for the All of Us Research Program, Inokuchi and colleagues had to establish performance management and operations improvement metrics, build data analytics and decision support systems, and facilitate research capacity through education and skill development. Despite our participants’ optimism about recruiting for an asthma trial during the pandemic, social isolation mandates and fear of virus transmission likely led to higher anxiety, which has been linked to reduced rates of enrollment in and higher withdrawal rates from clinical trials during COVID-19 [Reference LeBlanc, Testa and Waterman33,Reference Nomali, Mehrdad and Heidari36,Reference Abdulhussein, Yap, Manzar, Miodragovic and Cordeiro41]. Notably, one of our participants identified the risk of unduly increasing patient anxiety about asthma control in the backdrop of the pandemic as an unintentional consequence of the trial.
Only one other participant identified a potential unintentional consequence of trial implementation: the risk of neglecting other medical or social needs if a primary care visit focused on asthma control. While the financial health of FQHCs has improved with Medicaid expansion [Reference Jung, Huang and Mayeda42], small operating margins and increasing enrollment of uninsured patients place intense financial demands on clinicians to see as many patients as possible in a day; 15-minute bookings and frequent double bookings were commonly reported in our participating FQHCs. Further complicating financial performance demands are multiple unmet clinical and social determinants of health needs. FQHCs serve demographics facing high rates of chronic conditions, disease outcome disparities, and social inequities [6,43]. This makes chronic disease management particularly challenging in settings like FQHCs with limited human and financial resources [Reference Inokuchi, Mehta and Burke7]. It is not surprising, then, that one participant identified that a potential unintentional consequence of the planned intervention was either a longer visit or a visit that focused on uncontrolled asthma at the expense of other pressing medical needs. This is a challenge facing implementation trials, where unintended consequences could include reduced access to care for vulnerable populations [Reference Fiscella, Sanders and Holder44]. Shortening the allotted time for an office visit has clinical implications and affects patient and provider satisfaction [Reference Linzer, Bitton and Tu45–Reference Bokhour and Cutrona47]. Alternatively, other participants identified improved asthma control as lessening their workload because unscheduled urgent visits would be reduced.
Limitations
Because interviews took place over five months at the time of heightened anxiety about a surge in COVID-19 infections from the omicron and delta variants, relaxed eligibility requirements for vaccines and boosters, and shortened isolation periods, and because earlier COVID-19 infections had particularly impacted the New York–New Jersey areas, the views expressed may have been unusually pronounced, transient and not representative of FQHC staff or administrators outside the region. In addition, the study faced challenges commonly associated with small qualitative research. For instance, findings are derived from a relatively small sample limited to four northeastern urban FQHCs, which may not fully capture the diversity of experiences across broader populations and geographic areas. Also, participants willing to engage in interviews may differ systematically from those who decline, potentially skewing the results toward individuals with stronger opinions or specific experiences. There is also a risk that staff perception of patient barriers could misrepresent the end-user perspective since patients were not interviewed. Despite efforts to maintain neutrality, the presence of an interviewer and the phrasing of questions may inadvertently shape participant responses. The findings are also influenced by the specific social, cultural, and institutional settings in which the study was conducted, making them less transferable to different healthcare systems or geographic locations. Lastly, there was also the risk that interest in participating in the upcoming trial may have led some staff to self-censure their answer to interview questions, leading to socially desirable responses.
Conclusions
In summary, findings from this study highlight the potential benefits of conducting assessments of perceived and actual barriers and facilitators prior to implementing a practice-based clinical trial. While COVID-19 provided a unique context for clinical trial roll-out, post-pandemic implications related to staffing levels and burnout were applicable to current health care delivery challenges. These data may provide crucial pre-trial implementation metrics that, when combined with other planned assessments, may provide a more comprehensive assessment of clinical trial implementation in FQHCs. By focusing on the needs and outcomes that matter most to the community, this type of community- and implementation science-informed research may encourage more community–academic partnerships that can increase research engagement by underrepresented populations of clinicians, staff, and patients.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/cts.2025.10204.
Author contributions
Maureen George: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing; Samrawit Solomon: Data curation, Formal analysis, Writing – original draft, Writing – review & editing; Rhea Khurana: Formal analysis, Supervision, Writing – original draft, Writing – review & editing; Safa Elkefi: Methodology, Validation, Writing – review & editing; Kayla A. Diggs: Formal analysis, Validation, Writing – original draft, Writing – review & editing; Marija Zeremski: Data curation, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing; Jean-Marie Bruzzese : Conceptualization, Formal analysis, Supervision, Writing – original draft, Writing – review & editing; Andrea Cassells: Conceptualization, Data curation, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing; Jonathan Tobin: Data curation, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing; Emily DiMango : Conceptualization, Investigation, Methodology, Supervision, Validation, Writing –original draft, Writing – review & editing; Supakorn Kueakomoldej: Formal analysis, Validation, Writing – original draft, Writing – review & editing; Phoenix A. Matthews: Formal analysis, Methodology, Supervision, Validation, Writing – review & editing; Rachel Shelton: Conceptualization, Formal analysis, Supervision, Writing – original draft, Writing – review & editing.
Funding statement
This study was funded by a grant from the National Institute of Nursing Research through grant R01NR (1R01NR019275; PI George).
Competing interests
George has received speaker honoraria from AstraZeneca and Regeneron and provides consulting services to AstraZeneca, Genentech, Roche, Verona, and VisionHealth. Solomon, Khurana, Elkefi, Diggs, Zeremski, Bruzzese, Cassells, Tobin, DiMango, Kueakomoldej, Matthews and Shelton declare that they have no conflicts of interest.
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