Display options
Cite
Naughton F, Hopewell S, Lathia N, et al. A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study. JMIR Mhealth Uhealth. 2016;4(3):e106doi: 10.2196/mhealth.5787.
Naughton, F., Hopewell, S., Lathia, N., Schalbroeck, R., Brown, C., Mascolo, C., McEwen, A., & Sutton, S. (2016). A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study. JMIR mHealth and uHealth, 4(3), e106. https://doi.org/10.2196/mhealth.5787
Naughton, Felix, et al. "A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study." JMIR mHealth and uHealth vol. 4,3 (2016): e106. doi: https://doi.org/10.2196/mhealth.5787
Naughton F, Hopewell S, Lathia N, Schalbroeck R, Brown C, Mascolo C, McEwen A, Sutton S. A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study. JMIR Mhealth Uhealth. 2016 Sep 16;4(3):e106. doi: 10.2196/mhealth.5787. PMID: 27637405; PMCID: PMC5045522.
Copy Download .nbib Format: NLM
Share it on

JMIR Mhealth Uhealth. 2016 Sep 16;4(3):e106. doi: 10.2196/mhealth.5787.

A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study.

JMIR mHealth and uHealth

Felix Naughton, Sarah Hopewell, Neal Lathia, Rik Schalbroeck, Chloë Brown, Cecilia Mascolo, Andy McEwen, Stephen Sutton

Affiliations

  1. Behavioural Science Group, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. [email protected].

PMID: 27637405 PMCID: PMC5045522 DOI: 10.2196/mhealth.5787

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.

Keywords: JITAI; context sensing; craving; ecological momentary intervention; geofence; just-in-time adaptive intervention; mobile phone app; smoking cessation; tailoring

Conflict of interest statement

AM receives a personal income from Cancer Research UK via University College London. He has received travel funding, honorariums, and consultancy payments from manufacturers of smoking cessation produ

References

  1. JMIR Mhealth Uhealth. 2015 Nov 04;3(4):e101 - PubMed
  2. Nicotine Tob Res. 2014 May;16 Suppl 2:S88-92 - PubMed
  3. Nicotine Tob Res. 2016 May;18(5):1025-31 - PubMed
  4. J Consult Clin Psychol. 1970 Oct;35(2):135-42 - PubMed
  5. Nicotine Tob Res. 2013 Dec;15(12):2081-7 - PubMed
  6. J Health Psychol. 2015 Nov;20(11):1427-33 - PubMed
  7. Nicotine Tob Res. 2008 Jul;10(7):1185-90 - PubMed
  8. J Health Psychol. 2011 Mar;16(2):332-41 - PubMed
  9. Telemed J E Health. 2014 Mar;20(3):206-14 - PubMed
  10. JMIR Mhealth Uhealth. 2015 May 14;3(2):e42 - PubMed
  11. Nicotine Tob Res. 2013 Oct;15(10):1651-4 - PubMed
  12. Nicotine Tob Res. 2013 Nov;15(11):1883-91 - PubMed
  13. Lancet. 2012 Dec 15;380(9859):2224-60 - PubMed
  14. Addiction. 2012 Jan;107(1):197-205 - PubMed
  15. Exp Clin Psychopharmacol. 2008 Jun;16(3):207-14 - PubMed
  16. Res Nurs Health. 2006 Dec;29(6):533-42 - PubMed
  17. J Subst Abuse Treat. 2009 Apr;36(3):235-43 - PubMed
  18. Health Psychol. 2015 Dec;34(12):1191-4 - PubMed
  19. Health Psychol. 2007 Jan;26(1):77-84 - PubMed
  20. Lancet. 2011 Jul 2;378(9785):49-55 - PubMed
  21. Nicotine Tob Res. 2012 May;14 (5):569-77 - PubMed
  22. Psychopharmacology (Berl). 2014 Jul;231(13):2595-602 - PubMed
  23. J Med Internet Res. 2011 Aug 12;13(3):e55 - PubMed
  24. Addiction. 2014 Jul;109(7):1184-93 - PubMed
  25. J Consult Clin Psychol. 1996 Apr;64(2):366-79 - PubMed
  26. J Med Internet Res. 2015 Jan 16;17(1):e17 - PubMed
  27. BMJ. 2008 Sep 29;337:a1655 - PubMed
  28. J Addict Med. 2013 Jul-Aug;7(4):249-54 - PubMed
  29. Addiction. 2015 Oct;110(10 ):1549-60 - PubMed
  30. JAMA. 1994 Feb 23;271(8):589-94 - PubMed
  31. Addiction. 2008 Mar;103(3):478-84; discussion 485-6 - PubMed
  32. Addict Behav. 2011 Apr;36(4):315-9 - PubMed
  33. Psychopharmacology (Berl). 2004 Dec;177(1-2):195-9 - PubMed
  34. Br J Health Psychol. 2010 Feb;15(Pt 1):1-39 - PubMed
  35. Cochrane Database Syst Rev. 2016 Apr 10;4:CD006611 - PubMed
  36. J Med Internet Res. 2013 Apr 18;15(4):e86 - PubMed
  37. Health Educ Res. 2013 Oct;28(5):911-22 - PubMed
  38. Eur Addict Res. 2015;21(1):1-5 - PubMed
  39. Health Psychol. 2011 Sep;30(5):588-96 - PubMed
  40. BMJ. 2010 Sep 17;341:c4587 - PubMed

Publication Types

Grant support