From evidence to impact: The use of scientific research in policy documents

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. • We examine the utilization patterns of scientific research in policy documents. • We focus on how scientific evidence is selected and integrated in the context of clinical practice guidelines (CPGs) for the diagnosis, treatment, and management of diabetes. • 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. • Both types of citations are pervasive, calling into question the use of formal citations alone in understanding the societal impact of scientific research. • Qualitative insights further illustrate the reasons for certain use patterns of scientific research.

Authors

Institutions

Publication Details

Journal
Research Policy
Published
2026-02-02
DOI
https://doi.org/10.1016/j.respol.2026.105426
Primary Topic
Clinical practice guidelines implementation
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From evidence to impact: The use of scientific research in policy documents

Andreas Distel, Marion Poetz, Christoph Grimpe
Research Policy
Clinical practice guidelines implementation
article

From evidence to impact: The use of scientific research in policy documents

Andreas Distel, Marion Poetz, Christoph Grimpe
article en

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. • We examine the utilization patterns of scientific research in policy documents. • We focus on how scientific evidence is selected and integrated in the context of clinical practice guidelines (CPGs) for the diagnosis, treatment, and management of diabetes. • 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. • Both types of citations are pervasive, calling into question the use of formal citations alone in understanding the societal impact of scientific research. • Qualitative insights further illustrate the reasons for certain use patterns of scientific research.

Research PolicyVol. 55(3)
Centre for European Economic Research (DE), Copenhagen Business School (DK), Erasmus University Rotterdam (NL)
Österreichische Nationalstiftung für Forschung, Technologie und Entwicklung, Novo Nordisk
Quality Education
Openalex Percentile: Top 71%
Clinical practice guidelines implementation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.