Mathematical modelling in tobacco control research: protocol for a systematic review. Issue 4 (15th April 2015)

• Record Type: Journal Article
• Authors: Feirman, Shari; Donaldson, Elisabeth; Pearson, Jennifer; Zawistowski, Grace; Niaura, Ray; Glasser, Allison; Villanti, Andrea C
• Is Part Of: BMJ open. Volume 5:Issue 4(2015)
• Publication Date: 2015-04-15
• Subjects: PUBLIC HEALTH -- STATISTICS & RESEARCH METHODS -- HEALTH ECONOMICS; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2014-007269
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Introduction: 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. Methods and analysis: 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. Ethics and dissemination: 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.