How to increase the potential policy impact of environmental science research. / Bilotta, Gary; Milner, Alice; Boyd, Ian.

In: Environmental Sciences Europe, Vol. 27, No. 9, 29.03.2015, p. 1-6.

Research output: Contribution to journalArticlepeer-review

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How to increase the potential policy impact of environmental science research. / Bilotta, Gary; Milner, Alice; Boyd, Ian.

In: Environmental Sciences Europe, Vol. 27, No. 9, 29.03.2015, p. 1-6.

Research output: Contribution to journalArticlepeer-review

Harvard

Bilotta, G, Milner, A & Boyd, I 2015, 'How to increase the potential policy impact of environmental science research', Environmental Sciences Europe, vol. 27, no. 9, pp. 1-6. https://doi.org/10.1186/s12302-015-0041-x

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Bilotta, Gary ; Milner, Alice ; Boyd, Ian. / How to increase the potential policy impact of environmental science research. In: Environmental Sciences Europe. 2015 ; Vol. 27, No. 9. pp. 1-6.

BibTeX

@article{a9317311538b46bcb69b0fcc9e6a0c01,
title = "How to increase the potential policy impact of environmental science research",
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{\textquoteright} 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.",
keywords = "policy, environmental science, study design, bias, statistical power, randomization, statistical validity",
author = "Gary Bilotta and Alice Milner and Ian Boyd",
year = "2015",
month = mar,
day = "29",
doi = "10.1186/s12302-015-0041-x",
language = "English",
volume = "27",
pages = "1--6",
journal = "Environmental Sciences Europe",
number = "9",

}

RIS

TY - JOUR

T1 - How to increase the potential policy impact of environmental science research

AU - Bilotta, Gary

AU - Milner, Alice

AU - Boyd, Ian

PY - 2015/3/29

Y1 - 2015/3/29

N2 - 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.

AB - 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.

KW - policy

KW - environmental science

KW - study design

KW - bias

KW - statistical power

KW - randomization

KW - statistical validity

U2 - 10.1186/s12302-015-0041-x

DO - 10.1186/s12302-015-0041-x

M3 - Article

VL - 27

SP - 1

EP - 6

JO - Environmental Sciences Europe

JF - Environmental Sciences Europe

IS - 9

ER -