How to increase the potential policy impact of environmental science research

Gary Bilotta, Alice Milner, Ian Boyd

Research output: Contribution to journalArticle

Abstract

This article highlights eight common issues that limit the policy impact of environmental science research. The article also discusses what environmental scientists can do to resolve these issues, including (1) optimising the directness of their study so that it examines similar processes/populations/environments/ecosystems to that of policy interest; (2) using the most powerful study design possible, to increase confidence in the identified causal mechanisms; (3) selecting a sufficient sample size, to reduce the chance of false positives/negatives and increase policy-makers’ confidence in extrapolation of the findings; (4) minimizing the risk of bias through randomization of study units to treatment and control groups (reducing the risk of selection bias), blinding of study units and investigators (reducing the risk of performance and detection bias), following-up study units from enrolment to study completion (reducing the risk of attrition bias) and prospectively registering the study on a publically-available platform (reducing the risk of reporting and publication bias); (5) proving that statistical analyses meet test assumptions by reporting the results of statistical assumption checks, ideally publishing full datasets online in an open-access format; (6) publishing the research whether statistically significant or not, policy-makers are just as interested in the negative or insignificant results as they are in the positive results; (7) making the study easy to find and use, the title and abstract of an article are of high importance in determining whether articles are examined in detail or not and used to inform policy; (8) contributing towards systematic reviews on environmental topics, to provide policy-makers with comprehensive, reproducible and updateable syntheses of all the evidence on a given topic.
Original languageEnglish
JournalEnvironmental Sciences Europe
Volume27
DOIs
Publication statusPublished - 29 Mar 2015

Bibliographical note

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

Keywords

  • Policy
  • Environmental science
  • Study design
  • Bias
  • Statistical power
  • Randomization
  • Statistical validity
  • Systematic review

Fingerprint Dive into the research topics of 'How to increase the potential policy impact of environmental science research'. Together they form a unique fingerprint.

Cite this