Preventing Smoking Relapse Using Text Messages: Analysis of Data From the txt2stop Trial.


Devries, KM; Kenward, MG; Free, CJ; (2012) Preventing Smoking Relapse Using Text Messages: Analysis of Data From the txt2stop Trial. Nicotine & tobacco research , 15 (1). pp. 77-82. ISSN 1462-2203 DOI: 10.1093/ntr/nts086

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Abstract

INTRODUCTION: Interactive text message-based technologies which operate in real time have the potential to be especially effective for delivery of relapse prevention interventions. We examined predictors of use of a text message system for providing support for lapses and cravings, describe the natural history of requests for support, and predictors of time to requests for support.<br/> METHODS: Data were collected prospectively from participants in the intervention arm of txt2stop, a large randomized controlled trial of an automated, text message-based smoking cessation intervention. Txt2stop included 2,915 men and women aged 16-78, recruited from London, United Kingdom from 2009 to 2010. Participants could text "crave" or "lapse" when they experienced either; an automated system registered the time of the text message to the nearest second.<br/> RESULTS: One thousand one hundred and twenty one (38.5%) participants sent a lapse or crave message to request support. Women were more likely to lapse at some point during the trial. Of those who lapsed, being female, younger age, and setting a Saturday quit date were predictors of sending a lapse text requesting support. Half of all crave texts arrived within 106 hr of quitting. Half of all lapse texts arrived between 4 and 17 days after the quit date. Sending a crave text, being female, younger, and setting a quit date on a Saturday were associated with shorter time to sending a first lapse text.<br/> CONCLUSIONS: Text-based lapse support should be developed and evaluated, especially for women. Smokers may benefit from additional support to prevent lapses on days 4-17 postquit attempt.<br/>

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Medical Statistics
Faculty of Epidemiology and Population Health > Dept of Population Health (2012- ) > Dept of Nutrition and Public Health Interventions Research (2003-2012)
Faculty of Epidemiology and Population Health > Dept of Population Health (2012- )
Faculty of Public Health and Policy > Dept of Global Health and Development
Research Centre: Social and Mathematical Epidemiology (SaME)
PubMed ID: 22523120
Web of Science ID: 312880900010
URI: http://researchonline.lshtm.ac.uk/id/eprint/39172

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