A systematic review and analysis of data reduction techniques for the CReSS smoking topography device

Abstract

Introduction: Characterising smoking behaviour in an objective and ecologically valid manner is integral to understanding health complications associated with tobacco use. Smoking topography (ST) provides a representation of the physical attributes of smoking. However, there is no clear guidance on ST data exclusion and reduction techniques and the impact of different techniques.Methods: A search was conducted using MEDLINE, PubMed, and Scopus and limited to studies published between 2001‒2012. The search identified 23 studies using the CReSS device.Results: Few studies reported data reduction (n = 9) and exclusion (n = 4) criteria. Four data reduction techniques emerged and were applied to an existing dataset (n = 193, Mage = 38.98, FTND = 5.19, mean 17.23 cigarettes/day). Using repeated measures ANOVA, there were significant (p < 0.05) differences among all techniques for puff volume, peak flow, puff duration and interpuff interval, which were attenuated upon controlling for puff count.Conclusions: This review highlights the inconsistency in the literature regarding the disclosure of smoking topography data treatment and provides clear evidence that outcomes vary depending on the technique used. Greater transparency is needed and consideration should be given by researchers to the potential impact of methodological decisions on study findings.