title: A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study.
abstract: BACKGROUND
  A major cause of lapse and relapse to smoking during a quit attempt is craving triggered by cues from a smoker's immediate environment. To help smokers address these cue-induced cravings when attempting to quit, we have developed a context-aware smoking cessation app, Q Sense, which uses a smoking episode-reporting system combined with location sensing and geofencing to tailor support content and trigger support delivery in real time.
  
  
  OBJECTIVE
  We sought to (1) assess smokers' compliance with reporting their smoking in real time and identify reasons for noncompliance, (2) assess the app's accuracy in identifying user-specific high-risk locations for smoking, (3) explore the feasibility and user perspective of geofence-triggered support, and (4) identify any technological issues or privacy concerns.
  
  
  METHODS
  An explanatory sequential mixed-methods design was used, where data collected by the app informed semistructured interviews. Participants were smokers who owned an Android mobile phone and were willing to set a quit date within one month (N=15). App data included smoking reports with context information and geolocation, end-of-day (EoD) surveys of smoking beliefs and behavior, support message ratings, and app interaction data. Interviews were undertaken and analyzed thematically (N=13). Quantitative and qualitative data were analyzed separately and findings presented sequentially.
  
  
  RESULTS
  Out of 15 participants, 3 (20%) discontinued use of the app prematurely. Pre-quit date, the mean number of smoking reports received was 37.8 (SD 21.2) per participant, or 2.0 (SD 2.2) per day per participant. EoD surveys indicated that participants underreported smoking on at least 56.2% of days. Geolocation was collected in 97.0% of smoking reports with a mean accuracy of 31.6 (SD 16.8) meters. A total of 5 out of 9 (56%) eligible participants received geofence-triggered support. Interaction data indicated that 50.0% (137/274) of geofence-triggered message notifications were tapped within 30 minutes of being generated, resulting in delivery of a support message, and 78.2% (158/202) of delivered messages were rated by participants. Qualitative findings identified multiple reasons for noncompliance in reporting smoking, most notably due to environmental constraints and forgetting. Participants verified the app's identification of their smoking locations, were largely positive about the value of geofence-triggered support, and had no privacy concerns about the data collected by the app.
  
  
  CONCLUSIONS
  User-initiated self-report is feasible for training a cessation app about an individual's smoking behavior, although underreporting is likely. Geofencing was a reliable and accurate method of identifying smoking locations, and geofence-triggered support was regarded positively by participants.
authors.affiliation: Behavioural Science Group, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. fmen2@medschl.cam.ac.uk.
authors.forename: Felix
authors.identifier: http://orcid.org/0000-0001-9790-2796
authors.initials: F
authors.lastname: Naughton
authors.forename: Sarah
authors.identifier: http://orcid.org/0000-0003-1825-073X
authors.initials: S
authors.lastname: Hopewell
authors.forename: Neal
authors.identifier: http://orcid.org/0000-0003-1696-5838
authors.initials: N
authors.lastname: Lathia
authors.forename: Rik
authors.identifier: http://orcid.org/0000-0002-9855-5797
authors.initials: R
authors.lastname: Schalbroeck
authors.forename: Chloë
authors.identifier: http://orcid.org/0000-0002-9229-3351
authors.initials: C
authors.lastname: Brown
authors.forename: Cecilia
authors.identifier: http://orcid.org/0000-0001-9614-4380
authors.initials: C
authors.lastname: Mascolo
authors.forename: Andy
authors.identifier: http://orcid.org/0000-0001-8753-0394
authors.initials: A
authors.lastname: McEwen
authors.forename: Stephen
authors.identifier: http://orcid.org/0000-0003-1610-0404
authors.initials: S
authors.lastname: Sutton
keywords: JITAI; context sensing; craving; ecological momentary intervention; geofence; just-in-time adaptive intervention; mobile phone app; smoking cessation; tailoring