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How Can We Increase Translation of Research into Practice? Types of Evidence Needed
Abstract
This review summarizes key factors that have interfered with translation of research to practice and what public health researchers can do to hasten such transfer, focusing on characteristics of interventions, target settings, and research designs. The need to address context and to utilize research, review, and reporting practices that address external validity issues—such as designs that focus on replication, and practical clinical and behavioral trials—are emphasized. Although there has been increased emphasis on social-ecological interventions that go beyond the individual level, interventions often address each component as if it were an independent intervention. Greater attention is needed to connectedness across program levels and components. Finally, examples are provided of evaluation models and current programs that can help accelerate translation of research to practice and policy.
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“This may be explained by the fact that the former analysis included efficacy-type studies, which are implemented in optimal conditions and may result in larger effect sizes (37).”
From Global diabetes prevention interventions: A systematic review and network meta-analysis of the real-world impact on incidence, weight, and glucose (2018) · cites this paper as [37]
In the citing paper
“Despite its importance, such translation research is relatively rare (6–8), perhaps because using current approaches translation can be arduous and slow, sometimes taking 15 to 20 years (9, 10).”
From The Multiphase Optimization Strategy for Engineering Effective Tobacco Use Interventions (2011) · cites this paper as [9]
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Feldstein, A. C., & Glasgow, R. E. (2008) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/s1553-7250(08)34030-6 · Cited by 987
Self-citationDiffusion Theory and Knowledge Dissemination, Utilization, and Integration in Public Health
Green, L. W., Ottoson, J. M., García, C., & Hiatt, R. A. (2009) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.031308.100049 · Cited by 953
Metadata
- Authors
- Glasgow, R. E., & Emmons, K. M.
- Affiliations
- Kaiser Permanente (US)
- Harvard University (US)
- Venue
- Annual Review of Public Health
- Publisher
- Annual Reviews
- Published
- 2007-04-01
- Volume
- 28
- Issue
- 1
- Pages
- 413-433
- ISSN
- 0163-7525 (ISSN-L)
- 1545-2093
- OpenAlex
- W2112604521
- Cited by
- 1,050
- References
- 107
- Citations by year
- 2026: 16 · 2025: 27 · 2024: 39 · 2023: 120 · 2022: 38 · 2021: 43 · 2020: 52 · 2019: 55 · 2018: 48 · 2017: 56 · 2016: 50 · 2015: 87 · 2014: 72 · 2013: 59 · 2012: 66
- FWCI
- 6.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Public Health (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK035524, R01 DK 35524-05)
- National Center for Chronic Disease Prevention and Health Promotion (3U48 DP 00064-01S1)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Health Sciences › Health Professions › General Health Professions › Health Sciences Research and Education
- Social Sciences › Public Administration › Evaluation and Performance Assessment
- Keywords
- research-to-practice translation, evidence-based practice, public health interventions, generalizability, context, replication study, evaluation model, evidence-based policy, research design
- MeSH terms
- Decision Making, Organizational, Health Policy, Health Promotion, Humans, Policy Making, Research Design, Reproducibility of Results, Public Health Practice, Evidence-Based Medicine
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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