
INTRODUCTION: CTSA hubs provide vital infrastructure for high-impact research. The Translational Science Case Studies Work Group was formed to examine research facilitators and barriers, aiming to understand and improve how the CTSA program supports investigators and enhances their translational programs. METHODS: We employed a comparative case study design (meta-synthesis) to examine successful translational science (TS) efforts. Working group members were recruited from the National CTSA Evaluators Group. In addition to cases derived from evaluator interviews, we selected cases from TSBM/NIH archives, member institutions, and CTSA conferences, prioritizing those with proven clinical or public health dissemination. Our methodology combined existing cases with semi-structured investigator interviews to capture stakeholder perspectives. Through cross-case analysis, we coded for critical facilitators, barriers, and solutions to inform theoretical models and best practices for accelerating TS. RESULTS: We have established a library of standardized case studies, now being prepared for a repository available to all CTSA hubs. We secured 63 cases, exceeding our target of one per participating hub (30 total). After discarding five incomplete entries, we maintain 49 active case studies. These include adaptations from NIH OEPR, NIEHS, and the Journal of Clinical and Translational Science (JCTS), as well as TSBM cases. The Coding Committee has finalized the strategy and detailed codebook. Coding analysis has commenced, with 10 cases coded completely by a dyad and double-checked by a separate coder. Final coding is projected to conclude in February 2026. DISCUSSION: Our comparative analysis will yield insights to streamline the translational process. These best practices empower CTSA hubs to proactively bypass common roadblocks, accelerating the delivery of life-saving research discoveries to public health practice.
Impact, Case Study, Translational Impact Summit 2026, Translational Science, Mixed Methods
Impact, Case Study, Translational Impact Summit 2026, Translational Science, Mixed Methods
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
