Policy Evaluation Network (PEN): Protocol for systematic literature review examining the evidence for impact of policies across seven different policy domains Article Swipe
Kevin Volf
,
Liam Kelly
,
Enrique Garcíá Bengoechea
,
Bláthín Casey
,
Anna Gobis
,
Jeroen Lakerveld
,
Joanna Żukowska
,
Peter Gelius
,
Sven Messing
,
Sarah Forberger
,
Catherine Woods
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.12688/hrbopenres.13089.2
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.12688/hrbopenres.13089.2
Introduction: Over 40 million deaths annually are due to noncommunicable diseases, 15 million of these are premature deaths and physical inactivity contributes an estimated 9% to this figure. Global responses have included the Sustainable Development Goals (SDGs) and the Global Action Plan on Physical Activity (GAPPA). Both point to policy action on physical activity (PA) to address change, yet the impact of policy on PA outcomes is unknown. The protocol described outlines the methodology for systematic literature reviews that will be undertaken by the Policy Evaluation Network (PEN) to address this knowledge gap. Methods: The seven best investments for promotion of population PA identified in the Toronto Charter highlighted seven policy domains (schools, transport, urban design, primary health care systems, public education, community-wide programmes and sport) which will form the basis of these PEN reviews. Seven individual scientific literature searches across six electronic databases will be conducted. Each will use the key concepts of policy, PA, evaluation and a distinct concept for each of the seven policy domains. This will be supplemented with a search of the reference list of included articles. Methodological quality will be assessed and overall effectiveness for each included study will be described according to pre-determined criteria. Conclusions: Each review will provide policy makers with a list of policy statements and corresponding actions which the evidence has determined impact on PA directly or indirectly. By collating the evidence, and demonstrating the depth of the science base which informs these policy recommendations, each review will provide guidance to policymakers to use evidence-based or evidence-informed policies to achieve the 15% relative reduction in physical inactivity as defined by GAPPA. Registration: PROSPERO CRD42020156630 (10/07/2020).
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.12688/hrbopenres.13089.2
- https://hrbopenresearch.org/articles/3-62/v2/pdf
- OA Status
- gold
- Cited By
- 1
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3145190916
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3145190916Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.12688/hrbopenres.13089.2Digital Object Identifier
- Title
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Policy Evaluation Network (PEN): Protocol for systematic literature review examining the evidence for impact of policies across seven different policy domainsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-12-01Full publication date if available
- Authors
-
Kevin Volf, Liam Kelly, Enrique Garcíá Bengoechea, Bláthín Casey, Anna Gobis, Jeroen Lakerveld, Joanna Żukowska, Peter Gelius, Sven Messing, Sarah Forberger, Catherine WoodsList of authors in order
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https://doi.org/10.12688/hrbopenres.13089.2Publisher landing page
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https://hrbopenresearch.org/articles/3-62/v2/pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://hrbopenresearch.org/articles/3-62/v2/pdfDirect OA link when available
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Action plan, Political science, Systematic review, Population, Health policy, Economic growth, Health care, Medicine, Environmental health, MEDLINE, Economics, Management, LawTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2021: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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