Abstract
We examine the use of scientific research in the development of policy documents within the context of clinical practice guidelines (CPGs) for diagnosing, treating, and managing diabetes. Using natural language processing, we identify “hidden citations” (i.e., textual credit without formal citations) and “token citations” (i.e., formal citations without textual credit) to scientific research within CPGs to understand how scientific evidence is selected and integrated. We find that both types of citations are pervasive, calling into question the use of formal citations alone in understanding the societal impact of scientific research. Using data on scholarly citations and expert ratings, we find that hidden citations are positively associated with the actual impact of the research on patients and caregivers while token citations associate positively with scientific impact. Qualitative insights gathered from interviews with senior guideline writers further illustrate the reasons for certain functions of scientific research, which involve balancing scientific rigor with practical demands in the guideline writing process, the need for local adaptations, political dynamics on the organizational level, and individual preferences towards certain types of studies or the use of experiential knowledge. Our work underscores the critical role of research utilization in translating scientific evidence into policy, showing that policymaker decisions shape societal impact as much as the engagement efforts of scientists, and extends institutional accounts of symbolic and substantive knowledge use.
| Original language | English |
|---|---|
| Article number | 105426 |
| Journal | Research Policy |
| Volume | 55 |
| Issue number | 3 |
| Number of pages | 30 |
| ISSN | 0048-7333 |
| DOIs | |
| Publication status | Published - Apr 2026 |
Bibliographical note
Published online: 2 February 2026.UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Research utilization in policy
- Institutional theory
- Hidden citations
- Token citations
- Societal impact
- Natural language processing
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