Introduction
Clinical and translational research (CTR) is pivotal in advancing medical knowledge and improving health outcomes by bridging the gap between basic scientific discoveries and their application in clinical settings. It ensures that research findings are translated into medical practices and therapies that benefit patients [Reference Kazdin1]. CTR encompasses a range of activities, from basic science and clinical trials to implementation science, aimed at driving meaningful improvements in healthcare delivery. However, its success is shaped by more than scientific discovery alone; it depends heavily on the research environment, including infrastructure, funding, workforce capacity, and institutional support [Reference Seyhan2]. These structural components are essential in settings with persistent health disparities, where robust CTR systems help ensure that underrepresented populations benefit from research advancements.
Oklahoma presents a compelling case for examining CTR capacity. The state consistently ranks among the lowest nationally across multiple health indicators and experiences some of the most pronounced disparities in the country [Reference Chou, Hammon and Akins3,4]. According to the United Health Foundation, out of 50 states in the United States, Oklahoma ranked 45th in overall health outcomes in 2022, and near the bottom in obesity (48th), diabetes (46th), smoking (49th), and cardiovascular deaths (48th) [Reference Chou, Hammon and Akins3–6]. These challenges extend beyond individual behavior or access to care; they reflect systemic issues, including limited capacity to generate, translate, and apply health research locally.
In response, the National Institutes of Health (NIH) supported the creation of the Oklahoma Shared Clinical and Translational Resources (OSCTR) in 2013 to build CTR capacity statewide. Housed at the University of Oklahoma Health Sciences (OUHS), OSCTR is a collaboration of 15 institutional and community partners, including the Cherokee Nation, Southern Plains Tribal Health Board, and the Oklahoma City Veteran Affairs, working to expand research infrastructure, training, and mentorship with an explicit focus on underserved and rural populations [Reference Dao, Kota, James, Stoner and Akins7,Reference Campbell, Ogunsanya, Holmes, VanWagoner and James8]. Over the past decade, OSCTR has made considerable strides in providing pilot funding, professional development, and support services to researchers across the state.
Despite these efforts, persistent gaps remain. Many researchers, especially those in rural and tribal regions, still face limited access to data, underdeveloped mentorship structures, and fragmented infrastructure [Reference Chou, Hammon and Akins3,Reference Dao, Kota, James, Stoner and Akins7]. These shortcomings may explain why gains in health outcomes have not kept pace with infrastructure investments. Furthermore, past evaluations of CTR capacity in Oklahoma have primarily relied on quantitative indicators, such as grant counts and enrollment rates [Reference Chou, Hammon and Akins3,Reference Dao, Kota, James, Stoner and Akins7], which do not capture researchers’ lived experiences or institutional barriers.
To address this gap, we conducted a sequential, descriptive mixed-methods needs assessment, integrating survey data with qualitative input from CTR investigators and community partners. This design enables a more nuanced understanding of the barriers, facilitators, and unmet needs shaping research capacity across Oklahoma. By examining both the measurable and the experiential aspects of CTR, this study aims to inform a more equitable, effective, and sustainable research infrastructure across OSCTR and its partners [Reference Creswell and Clark9,Reference Burch and Heinrich10]. As OSCTR enters its second decade, these findings can guide strategic investments, strengthen interdisciplinary collaboration, and inform the redesign of support systems to better serve Oklahoma’s unique research ecosystem. Ultimately, this work aims to ensure that CTR investments translate into meaningful improvements in health outcomes, particularly for the state’s most underserved communities, and also offers a model for other states facing similar challenges.
Methods
Study design
Using a sequential, descriptive exploratory mixed-methods design, this study examined the barriers, needs, and facilitators to conducting CTR among active CTR researchers in Oklahoma. This design was chosen because it provides a comprehensive understanding of the phenomenon of interest [Reference Ivankova and Creswell11]. We began with a quantitative phase to gather data on research infrastructure, funding levels, and other objective metrics related to CTR across the state. This phase provided a broad overview of the research environment and helped identify initial trends and patterns. Subsequently, we conducted a qualitative phase, comprising focus groups with active CTR researchers, to explore their subjective experiences. By integrating these two phases, we aimed to enhance the validity and richness of our findings, capturing both the breadth and depth of CTR landscape in the state. This design also supported an iterative and reflexive research process, enabling the refinement and exploration of emerging themes throughout the study.
Study setting
The OSCTR initiative, launched with a $20.3 million grant from the NIH in September 2013, represents a significant collaborative effort led by OUHS [Reference Dao, Kota, James, Stoner and Akins7]. The initiative includes partnerships with a wide range of institutions across Oklahoma, such as the Oklahoma Medical Research Foundation, the University of Oklahoma’s Norman (OU Norman) and Tulsa campuses (OUHS Tulsa), the Veterans Administration, Oklahoma State University and its Health Sciences Center, among others. These partnerships are instrumental in advancing CTR programs in Oklahoma, offering essential research support services, and facilitating faculty development in translational research methodologies. In line with its overarching goals, OSCTR has initiated a comprehensive needs assessment to ensure the alignment of its services with the current requirements of CTR researchers and partner institutions.
Target population
The target population comprised active CTR researchers identified from the IRB protocol management system at OUHS. Individuals listed as Principal Investigators or Co-Investigators with ongoing IRB-approved protocols were included in the sampling frame. The initial sampling frame consisted of 1,460 unique investigators with active IRB protocols. After the initial survey invitation email, 251 investigators were identified as “ineligible” because they had retired or left the university. An additional 60 investigators were inaccessible during the survey period based on out-of-office email responses. This resulted in a final sample of 1,149 eligible participants. After three invitations to participate in the survey, 164 responses were received, yielding a response rate of 14.3% (see Fig. 1 for sampling flowchart).
Figure 1. Sampling flowchart.
Data collection
Data collection occurred in two phases: phases one and two. In phase one, the exploratory stage, barriers, needs, and facilitators were initially identified through a web-based survey (n = 164) (see Appendix A). The survey was modeled after several instruments, including the 2012 OSCTR survey [Reference Dao, Kota, James, Stoner and Akins7], the Advance-CTR (Rhode Island) [Reference Willey, Fede and Stevenson12], and the STRiDE needs assessment (Delaware) [Reference Fan, Mattera and Ackerman13]. The initial draft was reviewed by OSCTR leadership, and revisions were made based on their feedback. The survey was then pilot-tested with a small group of investigators to improve relevance, ensure clarity of questions, and reduce the overall questionnaire length. The final survey included the following sections: description of research activities, barriers, needs, and facilitators to CTR, awareness of OSCTR services and resources, and demographics (age, gender, current position/academic rank, degrees held, primary affiliation, types of research, manuscript authorship activity). A final question asked if participants would be interested in participating in a follow-up interview. The survey was administered online using REDCaP [Reference Harris, Taylor, Thielke, Payne, Gonzalez and Conde14]. An initial email invitation containing the survey link was distributed in February 2019, with four follow-up reminders sent over the next four weeks before the survey closed in March 2019. Descriptive statistics were analyzed using SPSS v25.
In phase two, the explanatory phase, findings from the survey were further explored through four qualitative focus groups involving 23 participants randomly selected from phase one. These focus groups were conducted between 2020 and 2022. The extended gap between the survey and the focus groups was due to the onset of the COVID-19 pandemic, which delayed both in-person and virtual data collection efforts during that time.
Measures
Quantitative measures
Description of research activities. This was assessed by asking participants to indicate the types of research they conduct: clinical, basic, public health, education, community-based participatory, health services, dissemination and implementation, methodological, engineering, translational, and therapeutic development research.
Demographics. Participants provided demographic information, including gender, current position/academic rank, degrees held, primary affiliation, and types of research conducted. Information on manuscript submissions was gathered, such as whether participants had submitted manuscripts as lead, senior, or corresponding authors in the past year.
Barriers. To assess barriers to conducting CTR, participants rated the extent to which they perceived limited access to various research supports as impediments. These supports included grant administration, regulatory issues, conducting research, pilot project funding, and proposal development, and others. A total of 16 barriers were included, with responses captured on a scale from “Not at all” to “A great deal,” along with an option for “N/A.”
Needs. This was assessed by evaluating respondents’ anticipated utilization of various research support resources and services over the next 6 months. This assessment included inquiries about the likelihood of utilizing different tools and assistance, such as web-based research networking, online tutorials, individual assistance with research services, support with regulatory processes, participant recruitment, clinical testing equipment, data analysis expertise, and study design.
Facilitators. Facilitators were assessed by asking participants which services or resources provided by OSCTR’s Professional Development Core contributed most to advancing their CTR efforts. Options included scientific writing, bench-to-bedside collaboration, mentoring practices, data security, and access to specialized tools such as bioinformatics and mHealth technologies.
Overall Satisfaction. A one-item 5-point Likert scale (ranging from “Not at all” to “Extremely”) assessed participants’ satisfaction with the institution’s overall efforts at supporting CTR.
Qualitative measures
Focus group interviews were conducted in person by MEO, assisted by NH, and facilitated using a semi-structured interview guide developed by the study team to capture rich qualitative data aligned with the study goals. The guide included open-ended questions and specific probes to allow for in-depth exploration of barriers, needs, and facilitators not fully captured by the survey (see Appendix B). Key questions focused on barriers to CTR, such as challenges with resource identification, regulatory processes, protected time, professional collaboration, and institutional support. Additional questions explored training, funding, and professional development needs. Facilitators were examined to understand effective strategies for overcoming obstacles and meeting research needs. Focus groups also addressed potential solutions and implementation strategies to generate actionable strategies. All sessions were audio recorded and supplemented with interviewer notes. Interviews ranged 57–76 minutes and were professionally transcribed verbatim. After checking for accuracy, MEO coded each interview line-by-line and developed a coding framework using Atlas.ti v9. Audio transcripts were content-analyzed to create inductive categories, and generated codes were combined to form themes, which were labeled based on their order and frequency. To ensure reliability, additional team members independently tested the coding framework by comparing transcripts to identified themes. The themes were extracted through coding, developed from combined recordings and notes, and reviewed by the investigators. An audit trail was maintained throughout, and peer debriefing was conducted to enhance credibility. Final findings were presented to participants for feedback to enrich interpretation. The study was approved by the University of Oklahoma Institutional Review Board (IRB #9840), and informed consent was obtained from all participants.
Mixed methods integration
Integrating qualitative and quantitative data allowed for a comprehensive understanding of the barriers, needs, and facilitators in conducting CTR in Oklahoma. By combining these approaches, the study leveraged numerical data to identify patterns and trends. In contrast, qualitative data provided the underlying experiences and explanations, enhancing the overall depth and impact of the findings. To facilitate alignment across methods, themes and topics from the survey informed the development of the interview guide, allowing for consistency in data collection. Findings from both phases were then merged to explore convergence, divergence, triangulation, complementarity, and expansion across data types [Reference Fetters, Curry and Creswell15]. This integration enabled a robust and nuanced interpretation of the findings, combining statistical patterns with lived experiences to inform future CTR infrastructure improvements (see Fig. 2).
Figure 2. Sequential mixed methods design of the barriers, needs, and facilitators of clinical and translational research in Oklahoma. CTR = clinical and translational research; OSCTR = Oklahoma Shared Clinical and Translational Resources.
Results
Participant Characteristics. A total of 164 researchers participated in the web-based survey, and 23 were included in the qualitative study. Most survey respondents were female (n = 84, 51.2%), with a slightly higher proportion of females in the qualitative group (n = 14, 60.9%). Most survey participants identified Medicine as their primary affiliation (n = 102, 64.2%). In contrast, the qualitative sample showed more diversity in affiliation, with Medicine (n = 9, 39.1%) being the most common, followed by Public Health (n = 4, 17.4%) and other disciplines. Regarding academic ranking, Assistant Professors were the most represented in the survey (n = 51, 31.1%) and the qualitative interviews (n = 11, 47.8%). A majority of participants held a PhD degree (survey: n = 82, 35.0%; qualitative: n = 12, 52.2%), and more than 70% of participants in both groups reported engagement in clinical or patient-oriented research (survey: n = 120, 73.2%; qualitative: n = 17, 73.9%). Table 1 presents the descriptive characteristics of all study participants.
Table 1. Quantitative characteristics for the overall sample and for the qualitative data participants
Barriers, Needs, Facilitators, and Overall Satisfaction in CTR. Notably, “Protected time for research” and “Pilot project funding” were identified as significant barriers, with over 15% of respondents indicating these as “a great deal” of a barrier. Challenges like IRB inter-institutional collaboration, data analysis, and proposal development also emerged as notable concerns. Regarding needs, there was strong interest in “Online tutorials, flowcharts & templates” and “Individual assistance with policies/procedures,” with nearly 50% of participants indicating they were likely to use these resources within the next 6 months. In contrast, services like “PROFILES web-based research networking,” received lower levels of awareness or interest, as suggested by the high proportion of respondents who were unsure about their potential use. Among the facilitators, “Scientific writing” (46.2%), “Designing clinical studies” (43.6%), and “Data analysis for clinical studies” (43.6%) were identified as the top activities that supported researchers’ work. Other areas of interest included “Accessing local data sources & research facilities” (39.7%) and “Bench-to-bedside collaboration” (35.3%). Finally, over 50% of respondents (67% total) were moderately-extremely satisfied with the institution’s support for CTR. However, about one-third expressed lower levels of satisfaction (“Slightly” or “Not at all”), pointing to potential areas for improvement in the institution’s support mechanisms. See Figs. 3–6 for a summary of the findings.
Figure 3. Barriers to clinical and translational research. Participants were asked: “In the past year, to what extent have you experienced the following barriers or challenges?” (See figure above). EHR = Electronic Health Record; IRB = Institutional Review Board.
Figure 4. Clinical and translational research (CTR) needs. The Oklahoma Shared Clinical and Translational Resources aims to provide a wide range of services to support CTR. Participants were asked: “Please rate the level of interest in using these services.” (See figure above.)
Figure 5. Facilitators. The Oklahoma Shared Clinical and Translational Resources (OSCTR) Professional Development Core offers educational opportunities to enhance the clinical and translational research (CTR) capabilities of investigators. Participants were asked to identify which of the following OSCTR-provided CTR-related activities has most helped them advance their research.
Figure 6. Overall satisfaction. How satisfied are you with your institution’s overall efforts at supporting clinical and translational research?
Mixed Methods Integration. Quantitative and qualitative data were integrated to better understand the barriers, needs, and facilitators in conducting CTR. This approach leveraged the strengths of both methods; quantitative data identified key trends and patterns, while qualitative data provided the context, depth, and explanations necessary to interpret those findings meaningfully. By triangulating results across diverse data sources, our study aimed to provide a comprehensive assessment of the factors shaping the CTR landscape and offer actionable recommendations to strengthen research capacity and collaboration across the state [Reference Burch and Heinrich10]. Table 2 contains a summary of these findings.
Table 2. Mixed-methods meta-inference of barriers, needs, and facilitators in clinical and translational research
OSCTR = Oklahoma Shared Clinical and Translational Resources.
Discussion
This study provides a descriptive analysis of the barriers, needs, and facilitators affecting CTR in Oklahoma. By integrating quantitative (survey) and qualitative (focus group) data, our mixed-methods approach allowed an in-depth exploration of the key factors shaping the research environment. This approach not only identified broad trends through the survey but also provided depth and a detailed understanding of these factors through qualitative interviews. Additionally, our study highlights the successes and ongoing challenges in the research landscape. While OSCTR’s significant investment in infrastructure and resources has positively contributed to CTR in Oklahoma, the barriers, needs, and facilitators identified in this study offer essential perspectives on areas where further alignment between institutional structures and the evolving needs of clinical research could further enhance research productivity and support.
Barriers
One key barrier identified through convergent meta-inference was the lack of protected time for research, an issue consistently highlighted in both the survey and focus group data. Over 70% of participants identified as clinical researchers, and both data types underscored the challenge of balancing patient care with research responsibilities. The dual demands of conducting patient-oriented research while managing teaching, administrative, and clinical duties emerged as a key hindrance to research productivity. This convergence reinforces existing literature identifying protected time as a critical factor in enabling research productivity and career advancement [Reference Finn, Syvyk and Bakillah16,Reference Elias, Sawatsky and Ratelle17]. Researchers involved in clinical studies often face unique challenges balancing their research projects with other obligations, which can dilute their focus and impede progress [Reference Kimberly, Kogut, Stevenson, Fede, Hayward and Tenca18–Reference Smith and Johnson20]. Without sufficient protected time, researchers may experience increased stress and reduced output, ultimately impacting both individual success and the broader research capacity of their institutions [Reference Finn, Syvyk and Bakillah16–21]. For instance, Elias et al. reported that the absence of protected time significantly contributes to reduced productivity and job satisfaction among faculty in academic settings [Reference Elias, Sawatsky and Ratelle17]. This aligns with our findings, where clinical researchers expressed that competing professional demands compromised their ability to engage meaningfully in research. Protected time is not just a facilitator of productivity but a fundamental requirement for high-quality research, particularly in translational research fields where sustained focus and dedicated effort are essential [Reference Elias, Sawatsky and Ratelle17,Reference Griesbach, Theobald and Kolman22]. Studies have also shown that strategies such as flexible scheduling, course buyouts, and administrative support for grant management can help mitigate the pressure on clinician-researchers, allowing them to allocate adequate time to research [Reference Elias, Sawatsky and Ratelle17,Reference Griesbach, Theobald and Kolman22]. These interventions not only foster a conducive environment for research but also contribute to better career progression and higher retention rates among clinician-researchers [Reference Jagsi, Griffith, Jones, Stewart and Ubel23].
Funding emerged as a complementary theme. While survey data rated pilot and bridge funding as moderate barriers, qualitative narratives revealed their critical role in sustaining momentum between funding cycles and supporting collaborative research. Participants emphasized the challenge of building and retaining research teams without predictable internal support. These findings highlight the need for institutional investments that provide flexible funding across the research continuum, particularly during early-stage development and transitional periods [Reference Willey, Fede and Stevenson12,Reference Kimberly, Kogut, Stevenson, Fede, Hayward and Tenca18,Reference Hall, Vogel and Huang24]. To address this, institutions might consider expanding internal programs offering interim funding during critical gaps and establishing centralized think tanks or advisory bodies to support strategic grant planning and continuity [Reference Finn, Syvyk and Bakillah16,Reference Kimberly, Kogut, Stevenson, Fede, Hayward and Tenca18,Reference Hall, Vogel and Huang24–Reference Yates and Warren27]. Additionally, targeted initiatives tailored to collaborative or interdisciplinary research could better meet the evolving needs of the CTR workforce [Reference Melkers, Woolley, Kreth, Bozeman, Ponomariov and Boardman25].
Administrative and regulatory challenges, such as IRB processes and inter-institutional coordination, were highlighted through explanatory meta-inference. Though less prominent in survey responses, focus group accounts painted a picture of institutional inefficiencies, delays, and communication breakdowns that impeded research progress. These findings clarify the quantitative ratings and suggest that even moderate administrative burdens may have an outsized impact on workflow and morale, supporting recommendations for streamlined IRB processes and enhanced inter-institutional agreements [Reference Kimberly, Kogut, Stevenson, Fede, Hayward and Tenca18,Reference Fudge, Sadler, Fisher, Maher, Wolfe and McKevitt28]. Issues related to data access showed strong triangulation between survey and focus group responses. Researchers reported difficulties locating and gaining access to large datasets and noted the lack of a centralized data management system. Both data strands underscore the importance of standardizing data processes and creating shared repositories to improve research efficiency and reproducibility [Reference Sehrawat, Noseworthy, Siontis, Haddad, Halamka and Liu29,Reference Jean-Louis and Seixas30]. The consistency of these findings across methods strengthens the argument for data infrastructure reform. Finally, the challenge of accessing physical infrastructure, such as lab and meeting spaces, emerged through explanatory inference. Although considered a lower barrier in the survey, qualitative data showed that these logistical delays often occurred even after funding was secured, disrupting research timelines. This aligns with existing research showing how misalignment between funding and facility readiness can create logistical delays and reduce institutional research output [Reference Renger, Basson and Hart31]. Addressing these gaps through proactive planning and resource allocation could improve efficiency and create a more supportive research environment.
Needs
Research networking emerged as a top priority across both data strands, showing clear convergence. Quantitatively, over one-third of participants indicated a likelihood of using such resources in the next six months, and qualitatively, researchers described the challenge of identifying collaborators, sometimes seeking partnerships outside their institutions due to the absence of centralized directories. This alignment highlights the institutional value of searchable databases or online platforms to promote collaboration and interdisciplinary science, consistent with recommendations in the literature [Reference Kelly, Chladek and Rolland32,Reference Hruby, McKiernan, Bakken and Weng33].
The need for scientific writing support reflected a pattern of expansion. While survey data indicated broad interest in writing assistance, qualitative data emphasized the added need for mentorship and expert feedback on proposal and manuscript development. Participants shared how peer support, access to experienced grant writers, and mentorship could enhance research quality and competitiveness. These findings highlight the importance of structured writing programs, review groups, and senior-to-junior mentoring models that support technical writing and provide strategic guidance for securing funding and publishing high-impact work [Reference Weber-Main, McGee and Eide Boman34–Reference Jones, McGee and Weber-Main36].
Access to local data sources and facilities was another commonly reported need, demonstrating explanatory meta-inference. While nearly 40% of survey respondents expressed interest in these resources, focus group narratives clarified systemic barriers that hinder effective use, such as the lack of awareness about data custodians or outdated protocols. These findings suggest that addressing this need requires more than access, it calls for centralized, well-maintained portals and consistent institutional communication to facilitate data utilization [Reference Hruby, McKiernan, Bakken and Weng33,Reference Jones, McGee and Weber-Main36–Reference Kent, Berry, Budds, Skipper and Williams38].
Notably, two needs emerged exclusively from qualitative data, showing expansion not captured in survey responses: the need for bridge/pilot funding and access to trained mentors. Participants emphasized that gaps in support during unfunded periods or post-submission phases can halt momentum and lead to burnout or attrition, particularly for early-career investigators. Similarly, they identified the absence of formal mentorship structures as a critical gap, noting that while some found informal guidance, many lacked reliable access to mentors who could support career development, grant navigation, and long-term planning [Reference Williams, Craig and Robson19,Reference Ransdell, Lane, Schwartz, Wayment and Baldwin35,Reference Johnson, Fuchs and Sterling39–Reference Wiskur, Mickel and Williams41]. These findings reinforce the need for sustained investment in bridge funding mechanisms and structured, goal-oriented mentoring programs to promote equity in research success and retention [Reference Willey, Fede and Stevenson12,Reference Kimberly, Kogut, Stevenson, Fede, Hayward and Tenca18,Reference Cunningham42–Reference Kulage and Larson45].
Facilitators
The findings from this study highlight several key facilitators of CTR, with strong support from both data strands and primarily demonstrating convergence, complementarity, and triangulation. The role of professional development, including training in clinical study design, data analysis, and scientific writing, exhibited apparent convergence between survey data and focus group responses. Participants described how OSCTR’s workshops enhanced their research skills and increased their confidence in pursuing new studies. This dual support affirms that institutional training programs are appreciated and impactful and that expanding these offerings, especially for early-career or researchers from underrepresented backgrounds, can strengthen institutional research capacity [Reference Kimberly, Kogut, Stevenson, Fede, Hayward and Tenca18,Reference Stanley, Hom, Chu and Joiner46]. Bench-to-bedside collaboration also showed a meaningful explanatory relationship. Participants described how collaborative meetings with clinical teams accelerated translation from lab to practice. This finding highlights the importance of institutional structures supporting translational dialog, as researchers can achieve greater real-world impact. This is a critical aim of the CTR initiative, bridging the gap between basic science and clinical application [Reference Dao, Kota, James, Stoner and Akins7,Reference Lieschke, Giles, Ball, Ohr and Parker47]. Finally, data management resources were identified through triangulation. Quantitative data showed an uptake of OSCTR’s data management support, while qualitative accounts emphasized how centralized databases enhanced recruitment efficiency and study planning. This alignment suggests that investment in accessible data infrastructure and training can address a recognized need and significantly streamline research workflows [Reference Whitmire, Boock and Sutton48].
Implications for practice
While some of the challenges identified in this study, such as limited protected time, mentorship needs, and grant support, are common across research environments, several findings appear uniquely specific to Oklahoma. Participants repeatedly emphasized the lack of centralized infrastructure for research collaboration and data access, reporting challenges in identifying collaborators and navigating fragmented or inconsistent data-sharing protocols. These challenges are compounded by Oklahoma’s geographic dispersion and institutional silos, spanning urban medical centers, rural health systems, and sovereign tribal nations, each with differing access to research infrastructure and support. Additionally, participants described a heavy reliance on OSCTR as the primary CTR support mechanism, with few alternative institutional resources available. This overcentralization highlights the need for decentralized, regionally responsive support systems, including local mentorship hubs, institution-specific pilot funding, and interoperable data platforms. Participants also pointed to limited cross-institutional coordination, which hindered interdisciplinary collaboration and created duplicative efforts across campuses. Tailoring solutions to these state-specific realities will be critical to strengthening the research environment and improving health outcomes in Oklahoma.
Our study findings offer actionable suggestions for enhancing the CTR environment in Oklahoma, which can inform the continued development of the OSCTR, recently renewed for another 10 years, as well as other similar mechanisms nationwide. Interventions such as implementing structured mentoring programs, streamlining administrative processes, and creating centralized data management systems could address the barriers and needs identified in this study [Reference Yates and Warren27,Reference Ransdell, Lane, Schwartz, Wayment and Baldwin35,Reference Wiskur, Mickel and Williams41,Reference Cunningham42]. Additionally, innovative communication strategies, such as podcasts and newsletters, can help connect researchers to available resources and foster collaboration [Reference Malecki, Quinn and Zilbert49]. A prime example is the GROklahoma Podcast, launched in 2023 by OSCTR in response to reported gaps in awareness and researcher isolation [50]. The podcast highlights available research resources, funding opportunities, and interviews with CTR scientists and support staff, fostering greater awareness and collaboration among researchers across the state. This locally developed platform exemplifies how Oklahoma’s CTR leaders are using novel, low-barrier tools to bridge geographic and institutional divides. Such an approach may serve as a model for other resource-constrained states.
OSCTR’s renewed funding also presents a timely opportunity to expand pilot and bridge funding mechanisms, strengthen mentorship infrastructure, and enhance professional development workshops, particularly those tailored to rural, tribal, and early-career investigators. As Oklahoma’s CTR landscape continues to evolve, these findings should guide strategic investments across the state and inform national conversations on sustaining equitable research environments in low-capacity settings. Based on our mixed-methods findings, we identified several priority areas for improving CTR infrastructure and support across Oklahoma. These recommendations may serve as a roadmap for targeted investment in state-specific research infrastructure and collaborative strategies. A summary of these priorities is presented in Table 3.
Table 3. Recommendations to strengthen clinical and translational research infrastructure in Oklahoma
Note: Recommendations are based on integrated findings from surveys and focus groups using convergence, complementarity, and explanatory integration across data strands with clinical and translational research stakeholders in Oklahoma. CTR = clinical and translational research.
Strengths and limitations
This study comprehensively examined the barriers, needs, and facilitators to conducting CTR in Oklahoma using a sequential, descriptive mixed-methods approach. A key strength of this study lies in its integration of quantitative and qualitative data, which provided both a broad understanding of trends and a deep exploration of individual experiences. This design also enabled a nuanced perspective of the CTR landscape across the state. Focusing on Oklahoma offered important regional insights, especially regarding the structural and geographic challenges that researchers face in rural, tribal, and underserved settings. Additionally, by targeting experienced Principal Investigators (PIs) and Co-Investigators (co-Is), the study highlights the challenges at the leadership level of research teams, providing actionable recommendations for enhancing institutional support and research productivity.
Nonetheless, several limitations warrant consideration. First, while informative, the sample size may not fully capture the diversity of perspectives across all research roles, particularly for the qualitative component. Focusing on PIs and Co-Is may have excluded early-career researchers, trainees, or staff facing CTR-related challenges. Second, the time gap between the survey (2019) and focus group data collection (2020–2022), compounded by the COVID-19 pandemic, may have introduced variability due to shifts in institutional priorities and research demands. Additionally, the ongoing impact of the pandemic likely contributed to evolving research priorities and institutional adaptations, which may have influenced participants’ experiences during this period. Despite these limitations, this study provides a robust foundation for institutional and statewide efforts to strengthen CTR in Oklahoma and similarly situated research environments.
Conclusion
This mixed-methods study offers a comprehensive assessment of the CTR landscape in Oklahoma, identifying key barriers, needs, and facilitators that shape research participation and productivity. The convergence of findings across data strands, particularly regarding protected research time, pilot funding, mentorship, and collaboration, highlights their centrality to advancing CTR efforts. Qualitative data expanded on these findings by contextualizing the institutional and interpersonal dynamics that influence research engagement and success. Tailored interventions such as structured mentoring programs, centralized data access, enhanced research networking platforms, and streamlined administrative processes are essential for fostering a more supportive research ecosystem.
Advancing CTR in Oklahoma is essential for addressing persistent healthcare challenges, promoting health equity, and improving patient outcomes across diverse populations. By investing in research infrastructure, encouraging interdisciplinary collaboration, and cultivating strong institutional and community partnerships, Oklahoma can strengthen its research capacity and build a more resilient and responsive research environment. A summary of context-specific recommendations to guide these efforts is presented in Table 3, offering a practical roadmap to inform institutional strategy, resource allocation, and statewide coordination.
Importantly, Oklahoma’s experience offers a transferable model for other states confronting similar geographic, structural, and capacity-related challenges. Strengthening CTR is vital for scientific advancement and a necessary step toward realizing equitable healthcare solutions and improving the well-being of all Oklahomans.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/cts.2025.10066
Acknowledgment
We sincerely thank the researchers and institutional stakeholders across Oklahoma who participated in the survey and focus groups. Their time and commitment to advancing CTR were instrumental to this work. We also appreciate the contributions of our research team and administrative staff who assisted with data collection, transcription, and analysis. Finally, we acknowledge the continued support and collaboration across departments and disciplines at OUHS, which reflect the spirit of this project and contribute to the advancement of CTR throughout the state.
Author contributions
Motolani Ogunsanya: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing-original draft, Writing-review & editing; Laura Beebe: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Validation, Visualization, Writing-review & editing; Janis Campbell: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Validation, Visualization, Writing-review & editing; Nicole Holmes: Conceptualization, Data curation, Methodology, Project administration, Validation, Visualization, Writing-review & editing; Timothy VanWagoner: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing-review & editing; Judith James: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing-review & editing.
Funding statement
This research was primarily supported by funding from the National Institute of General Medical Sciences (U54GM104938 NIH U54) to the University of Oklahoma Health Sciences (PI: James) via the Institutional Development Award (IDeA) program. The content is solely the authors’ responsibility and does not necessarily represent the official views of the National Institutes of Health.
Competing interests
The authors have no conflicts of interest to declare.
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