Feirman Shari, Donaldson Elisabeth, Pearson Jennifer, Zawistowski Grace, Niaura Ray, Glasser Allison, Villanti Andrea C
The Schroeder Institute for Tobacco Research and Policy Studies, Legacy, Washington DC, USA Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
The Schroeder Institute for Tobacco Research and Policy Studies, Legacy, Washington DC, USA The George Washington University Milken Institute School of Public Health.
BMJ Open. 2015 Apr 15;5(4):e007269. doi: 10.1136/bmjopen-2014-007269.
Tobacco control researchers have recently become more interested in systems science methods and mathematical modelling techniques as a means to understand how complex inter-relationships among various factors translate into population-level summaries of tobacco use prevalence and its associated medical and social costs. However, there is currently no resource that provides an overview of how mathematical modelling has been used in tobacco control research. This review will provide a summary of studies that employ modelling techniques to predict tobacco-related outcomes. It will also propose a conceptual framework for grouping existing modelling studies by their objectives.
We will conduct a systematic review that is informed by Cochrane procedures, as well as guidelines developed for reviews that are specifically intended to inform policy and programme decision-making. We will search 5 electronic databases to identify studies that use a mathematical model to project a tobacco-related outcome. An online data extraction form will be developed based on the ISPOR-SMDM Modeling Good Research Practices. We will perform a qualitative synthesis of included studies.
Ethical approval is not required for this study. An initial paper, published in a peer-reviewed journal, will provide an overview of our findings. Subsequent papers will provide greater detail on results within each study objective category and an assessment of the risk of bias of these grouped studies.
烟草控制研究人员最近对系统科学方法和数学建模技术越来越感兴趣,以此作为一种手段来理解各种因素之间复杂的相互关系如何转化为烟草使用流行率及其相关医疗和社会成本的人群层面总结。然而,目前尚无资源概述数学建模在烟草控制研究中的应用情况。本综述将总结采用建模技术预测烟草相关结果的研究。它还将提出一个概念框架,以便根据现有建模研究的目标对其进行分组。
我们将按照Cochrane程序以及为专门为政策和项目决策提供信息的综述制定的指南进行系统综述。我们将搜索5个电子数据库,以识别使用数学模型预测烟草相关结果的研究。将根据国际药物经济学与结果研究协会-社会与决策科学建模良好研究实践制定在线数据提取表。我们将对纳入的研究进行定性综合分析。
本研究无需伦理批准。一篇发表在同行评审期刊上的初始论文将概述我们的研究结果。后续论文将更详细地阐述每个研究目标类别中的结果,并对这些分组研究的偏倚风险进行评估。