title: Assessing the effect of an interactive decision-aid smartphone smoking cessation application (app) on quit rates: a double-blind automated randomised control trial protocol.
abstract: BACKGROUND
  In a previous study exploring the feasibility of a smoking cessation application (app), we found that about 77% of the respondents from three countries were ready to quit in the next 30 days without significant differences between countries in terms of age, operating system and number of quitting attempts. However, the efficacy of smartphone apps for smoking cessation has not yet been established. This study tests the efficacy of a smartphone smoking cessation decision-aid app compared with an app that contains only smoking cessation information.
  
  
  METHODS
  This is an automated double-blind, randomised controlled trial of a smoking cessation app that contains the eligibility requirements and baseline questionnaire and will randomise the participants into one of the two subapps (the intervention and the control). Participants will be recruited directly from the Apple app stores in Australia, Singapore, the UK and the USA. Daily smokers aged 18 and above will be randomised into one of the subapps after completing the baseline questionnaire. Abstinence rates will be measured at 10 days, 1 month, 3 months and 6 months, with the 1-month follow-up abstinence rate as the primary outcome. Logistic regression mixed models will be used to analyse the primary outcome.
  
  
  BACKGROUND
  This study was approved by the University of Sydney's Human Ethics Committee. The results of the trial will be published in peer-reviewed journals according to the CONSORT statement.
  
  
  BACKGROUND
  Australian New Zealand ClinicalTrial RegistryACTRN12613000833763.
authors.affiliation: School of Public Health, University of Sydney, Sydney, New South Wales, Australia Public Health and Health Informatics School, College of Health Sciences, Saudi Electronic University, Riyadh, Saudi Arabia.
authors.forename: Nasser F
authors.initials: NF
authors.lastname: BinDhim
authors.affiliation: School of Public Health, University of Sydney, Sydney, New South Wales, Australia.
authors.forename: Kevin
authors.initials: K
authors.lastname: McGeechan
authors.affiliation: School of Public Health, University of Sydney, Sydney, New South Wales, Australia.
authors.forename: Lyndal
authors.initials: L
authors.lastname: Trevena
mesh_terms: D003661:Decision Support Techniques; D004311:Double-Blind Method; D006801:Humans; D063731:Mobile Applications; D012107:Research Design; D000066908:Simulation Training; D000068997:Smartphone; D016540:Smoking Cessation / Q000379:methods*
keywords: PREVENTIVE MEDICINE; PUBLIC HEALTH