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Tobacco Control Policy Simulation Models: Protocol for a Systematic Methodological Review
BACKGROUNDTobacco control models are mathematical models predicting tobacco-related outcomes in defined populations. The policy simulation model is considered as a subcategory of tobacco control models simulating the potential outcomes of tobacco control policy options. However, we could not identif...
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Published in: | JMIR research protocols 2021-07, Vol.10 (7), p.e26854-e26854 |
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description | BACKGROUNDTobacco control models are mathematical models predicting tobacco-related outcomes in defined populations. The policy simulation model is considered as a subcategory of tobacco control models simulating the potential outcomes of tobacco control policy options. However, we could not identify any existing tool specifically designed to assess the quality of tobacco control models. OBJECTIVEThe aims of this systematic methodology review are to: (1) identify best modeling practices, (2) highlight common pitfalls, and (3) develop recommendations to assess the quality of tobacco control policy simulation models. Crucially, these recommendations can empower model users to assess the quality of current and future modeling studies, potentially leading to better tobacco policy decision-making for the public. This protocol describes the planned systematic review stages, paper inclusion and exclusion criteria, data extraction, and analysis. METHODSTwo reviewers searched five databases (Embase, EconLit, PsycINFO, PubMed, and CINAHL Plus) to identify eligible studies published between July 2013 and August 2019. We included papers projecting tobacco-related outcomes with a focus on tobacco control policies in any population and setting. Eligible papers were independently screened by two reviewers. The data extraction form was designed and piloted to extract model structure, data sources, transparency, validation, and other qualities. We will use a narrative synthesis to present the results by summarizing model trends, analyzing model approaches, and reporting data input and result quality. We will propose recommendations to assess the quality of tobacco control policy simulation models using the findings from this review and related literature. RESULTSData collection is in progress. Results are expected to be completed and submitted for publication by April 2021. CONCLUSIONSThis systematic methodological review will summarize the best practices and pitfalls existing among tobacco control policy simulation models and present a recommendation list of a high-quality tobacco control simulation model. A more standardized and quality-assured tobacco control policy simulation model will benefit modelers, policymakers, and the public on both model building and decision making. TRIAL REGISTRATIONPROSPERO International Prospective Register of Systematic Reviews CRD42020178146; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020178146. INTERNATIONAL REGISTER |
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The policy simulation model is considered as a subcategory of tobacco control models simulating the potential outcomes of tobacco control policy options. However, we could not identify any existing tool specifically designed to assess the quality of tobacco control models. OBJECTIVEThe aims of this systematic methodology review are to: (1) identify best modeling practices, (2) highlight common pitfalls, and (3) develop recommendations to assess the quality of tobacco control policy simulation models. Crucially, these recommendations can empower model users to assess the quality of current and future modeling studies, potentially leading to better tobacco policy decision-making for the public. This protocol describes the planned systematic review stages, paper inclusion and exclusion criteria, data extraction, and analysis. METHODSTwo reviewers searched five databases (Embase, EconLit, PsycINFO, PubMed, and CINAHL Plus) to identify eligible studies published between July 2013 and August 2019. We included papers projecting tobacco-related outcomes with a focus on tobacco control policies in any population and setting. Eligible papers were independently screened by two reviewers. The data extraction form was designed and piloted to extract model structure, data sources, transparency, validation, and other qualities. We will use a narrative synthesis to present the results by summarizing model trends, analyzing model approaches, and reporting data input and result quality. We will propose recommendations to assess the quality of tobacco control policy simulation models using the findings from this review and related literature. RESULTSData collection is in progress. Results are expected to be completed and submitted for publication by April 2021. CONCLUSIONSThis systematic methodological review will summarize the best practices and pitfalls existing among tobacco control policy simulation models and present a recommendation list of a high-quality tobacco control simulation model. A more standardized and quality-assured tobacco control policy simulation model will benefit modelers, policymakers, and the public on both model building and decision making. TRIAL REGISTRATIONPROSPERO International Prospective Register of Systematic Reviews CRD42020178146; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020178146. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)DERR1-10.2196/26854.</description><identifier>ISSN: 1929-0748</identifier><identifier>EISSN: 1929-0748</identifier><identifier>DOI: 10.2196/26854</identifier><identifier>PMID: 34309577</identifier><language>eng</language><publisher>Toronto, Canada: JMIR Publications</publisher><subject>Protocol</subject><ispartof>JMIR research protocols, 2021-07, Vol.10 (7), p.e26854-e26854</ispartof><rights>Vincy Huang, Anna Head, Lirije Hyseni, Martin O'Flaherty, Iain Buchan, Simon Capewell, Chris Kypridemos. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 26.07.2021. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-a8c28d979c8b90cfd326e24ad3318ea8860022ce1527a80909af38513ca71a613</citedby><cites>FETCH-LOGICAL-c375t-a8c28d979c8b90cfd326e24ad3318ea8860022ce1527a80909af38513ca71a613</cites><orcidid>0000-0003-3960-8999 ; 0000-0002-2569-0701 ; 0000-0001-8944-4131 ; 0000-0002-4577-9869 ; 0000-0002-0746-9229 ; 0000-0003-3392-1650 ; 0000-0002-6620-9953</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8367099/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml></links><search><creatorcontrib>Huang, Vincy</creatorcontrib><creatorcontrib>Head, Anna</creatorcontrib><creatorcontrib>Hyseni, Lirije</creatorcontrib><creatorcontrib>O'Flaherty, Martin</creatorcontrib><creatorcontrib>Buchan, Iain</creatorcontrib><creatorcontrib>Capewell, Simon</creatorcontrib><creatorcontrib>Kypridemos, Chris</creatorcontrib><title>Tobacco Control Policy Simulation Models: Protocol for a Systematic Methodological Review</title><title>JMIR research protocols</title><description>BACKGROUNDTobacco control models are mathematical models predicting tobacco-related outcomes in defined populations. The policy simulation model is considered as a subcategory of tobacco control models simulating the potential outcomes of tobacco control policy options. However, we could not identify any existing tool specifically designed to assess the quality of tobacco control models. OBJECTIVEThe aims of this systematic methodology review are to: (1) identify best modeling practices, (2) highlight common pitfalls, and (3) develop recommendations to assess the quality of tobacco control policy simulation models. Crucially, these recommendations can empower model users to assess the quality of current and future modeling studies, potentially leading to better tobacco policy decision-making for the public. This protocol describes the planned systematic review stages, paper inclusion and exclusion criteria, data extraction, and analysis. METHODSTwo reviewers searched five databases (Embase, EconLit, PsycINFO, PubMed, and CINAHL Plus) to identify eligible studies published between July 2013 and August 2019. We included papers projecting tobacco-related outcomes with a focus on tobacco control policies in any population and setting. Eligible papers were independently screened by two reviewers. The data extraction form was designed and piloted to extract model structure, data sources, transparency, validation, and other qualities. We will use a narrative synthesis to present the results by summarizing model trends, analyzing model approaches, and reporting data input and result quality. We will propose recommendations to assess the quality of tobacco control policy simulation models using the findings from this review and related literature. RESULTSData collection is in progress. Results are expected to be completed and submitted for publication by April 2021. CONCLUSIONSThis systematic methodological review will summarize the best practices and pitfalls existing among tobacco control policy simulation models and present a recommendation list of a high-quality tobacco control simulation model. A more standardized and quality-assured tobacco control policy simulation model will benefit modelers, policymakers, and the public on both model building and decision making. TRIAL REGISTRATIONPROSPERO International Prospective Register of Systematic Reviews CRD42020178146; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020178146. 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The policy simulation model is considered as a subcategory of tobacco control models simulating the potential outcomes of tobacco control policy options. However, we could not identify any existing tool specifically designed to assess the quality of tobacco control models. OBJECTIVEThe aims of this systematic methodology review are to: (1) identify best modeling practices, (2) highlight common pitfalls, and (3) develop recommendations to assess the quality of tobacco control policy simulation models. Crucially, these recommendations can empower model users to assess the quality of current and future modeling studies, potentially leading to better tobacco policy decision-making for the public. This protocol describes the planned systematic review stages, paper inclusion and exclusion criteria, data extraction, and analysis. METHODSTwo reviewers searched five databases (Embase, EconLit, PsycINFO, PubMed, and CINAHL Plus) to identify eligible studies published between July 2013 and August 2019. We included papers projecting tobacco-related outcomes with a focus on tobacco control policies in any population and setting. Eligible papers were independently screened by two reviewers. The data extraction form was designed and piloted to extract model structure, data sources, transparency, validation, and other qualities. We will use a narrative synthesis to present the results by summarizing model trends, analyzing model approaches, and reporting data input and result quality. We will propose recommendations to assess the quality of tobacco control policy simulation models using the findings from this review and related literature. RESULTSData collection is in progress. Results are expected to be completed and submitted for publication by April 2021. CONCLUSIONSThis systematic methodological review will summarize the best practices and pitfalls existing among tobacco control policy simulation models and present a recommendation list of a high-quality tobacco control simulation model. A more standardized and quality-assured tobacco control policy simulation model will benefit modelers, policymakers, and the public on both model building and decision making. TRIAL REGISTRATIONPROSPERO International Prospective Register of Systematic Reviews CRD42020178146; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020178146. 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title | Tobacco Control Policy Simulation Models: Protocol for a Systematic Methodological Review |
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