Huang Vincy, Head Anna, Hyseni Lirije, O'Flaherty Martin, Buchan Iain, Capewell Simon, Kypridemos Chris
Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, United Kingdom.
JMIR Res Protoc. 2021 Jul 26;10(7):e26854. doi: 10.2196/26854.
Tobacco 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.
The 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.
Two 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.
Data collection is in progress. Results are expected to be completed and submitted for publication by April 2021.
This 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.
PROSPERO 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.
烟草控制模型是预测特定人群中与烟草相关结果的数学模型。政策模拟模型被视为烟草控制模型的一个子类别，用于模拟烟草控制政策选项的潜在结果。然而，我们未能找到任何专门设计用于评估烟草控制模型质量的现有工具。
本系统方法学综述的目的是：（1）确定最佳建模实践，（2）突出常见陷阱，（3）制定评估烟草控制政策模拟模型质量的建议。至关重要的是，这些建议可使模型使用者能够评估当前和未来建模研究的质量，有可能为公众带来更好的烟草政策决策。本方案描述了计划中的系统综述阶段、论文纳入和排除标准、数据提取及分析。
两名评审员检索了五个数据库（Embase、EconLit、PsycINFO、PubMed和CINAHL Plus），以识别2013年7月至2019年8月期间发表的符合条件的研究。我们纳入了预测与烟草相关结果且侧重于任何人群和环境中烟草控制政策的论文。符合条件的论文由两名评审员独立筛选。设计并试用了数据提取表，以提取模型结构、数据来源、透明度、验证及其他质量指标。我们将采用叙述性综合方法，通过总结模型趋势、分析模型方法以及报告数据输入和结果质量来呈现结果。我们将利用本次综述及相关文献的结果，提出评估烟草控制政策模拟模型质量的建议。
数据收集正在进行中。预计结果将于2021年4月完成并提交发表。
本系统方法学综述将总结烟草控制政策模拟模型中存在的最佳实践和陷阱，并列出高质量烟草控制模拟模型的建议清单。一个更加标准化且质量有保证的烟草控制政策模拟模型将使建模者、政策制定者以及公众在模型构建和决策方面都受益。
国际系统综述前瞻性注册库PROSPERO CRD42020178146；https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020178146。
国际注册报告识别号（IRRID）：DERR1-10.2196/26854。
