Outcomes and Device Usage for Fully Automated Internet Interventions Designed for a Smartphone or Personal Computer: The MobileQuit Smoking Cessation Randomized Controlled Trial

Brian G Danaher, Milagra S Tyler, Ryann C Crowley, Håvar Brendryen, John R Seeley, Brian G Danaher, Milagra S Tyler, Ryann C Crowley, Håvar Brendryen, John R Seeley

Abstract

Background: Many best practice smoking cessation programs use fully automated internet interventions designed for nonmobile personal computers (desktop computers, laptops, and tablets). A relatively small number of smoking cessation interventions have been designed specifically for mobile devices such as smartphones.

Objective: This study examined the efficacy and usage patterns of two internet-based best practices smoking cessation interventions.

Methods: Overall, 1271 smokers who wanted to quit were randomly assigned to (1) MobileQuit (designed for-and constrained its use to-mobile devices, included text messaging, and embodied tunnel information architecture) or (2) QuitOnline (designed for nonmobile desktop or tablet computers, did not include text messages, and used a flexible hybrid matrix-hierarchical information architecture). Primary outcomes included self-reported 7-day point-prevalence smoking abstinence at 3- and 6-month follow-up assessments. Program visits were unobtrusively assessed (frequency, duration, and device used for access).

Results: Significantly more MobileQuit participants than QuitOnline participants reported quitting smoking. Abstinence rates using intention-to-treat analysis were 20.7% (131/633) vs 11.4% (73/638) at 3 months, 24.6% (156/633) vs 19.3% (123/638) at 6 months, and 15.8% (100/633) vs 8.8% (56/638) for both 3 and 6 months. Using Complete Cases, MobileQuit's advantage was significant at 3 months (45.6% [131/287] vs 28.4% [73/257]) and the combined 3 and 6 months (40.5% [100/247] vs 25.9% [56/216]) but not at 6 months (43.5% [156/359] vs 34.4% [123/329]). Participants in both conditions reported their program was usable and helpful. MobileQuit participants visited their program 5 times more frequently than did QuitOnline participants. Consistent with the MobileQuit's built-in constraint, 89.46% (8820/9859) of its visits were made on an intended mobile device, whereas 47.72% (691/1448) of visits to QuitOnline used an intended nonmobile device. Among MobileQuit participants, 76.0% (459/604) used only an intended mobile device, 23.0% (139/604) used both mobile and nonmobile devices, and 0.1% (6/604) used only a nonmobile device. Among QuitOnline participants, 31.3% (137/438) used only the intended nonmobile devices, 16.7% (73/438) used both mobile and nonmobile devices, and 52.1% (228/438) used only mobile devices (primarily smartphones).

Conclusions: This study provides evidence for optimizing intervention design for smartphones over a usual care internet approach in which interventions are designed primarily for use on nonmobile devices such as desktop computers, laptops. or tablets. We propose that future internet interventions should be designed for use on all of the devices (multiple screens) that users prefer. We forecast that the approach of designing internet interventions for mobile vs nonmobile devices will be replaced by internet interventions that use a single Web app designed to be responsive (adapt to different screen sizes and operating systems), share user data across devices, embody a pervasive information architecture, and complemented by text message notifications.

Trial registration: ClinicalTrials.gov NCT01952236; https://ichgcp.net/clinical-trials-registry/NCT01952236 (Archived by WebCite at http://www.webcitation.org/6zdSxqbf8).

Keywords: device; eHealth; internet; mHealth; smartphone; smoking; tobacco.

Conflict of interest statement

Conflicts of Interest: None declared.

©Brian G Danaher, Milagra S Tyler, Ryann C Crowley, Håvar Brendryen, John R Seeley. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 06.06.2019.

Figures

Figure 1
Figure 1
Screenshot 1 of MobileQuit and QuitOnline.
Figure 2
Figure 2
Screenshot 2 of MobileQuit and QuitOnline.
Figure 3
Figure 3
Screenshot 3 of MobileQuit and QuitOnline.
Figure 4
Figure 4
Screenshot 4 of MobileQuit and QuitOnline.
Figure 5
Figure 5
MobileQuit's detective activity.
Figure 6
Figure 6
Standard regimen of 290 text messages planned to be sent to MobileQuit participants by message type.
Figure 7
Figure 7
Consolidated Standards of Reporting Trials diagram depicting flow of participants through the study.

References

    1. Brendryen H, Drozd F, Kraft P. A digital smoking cessation program delivered through internet and cell phone without nicotine replacement (happy ending): randomized controlled trial. J Med Internet Res. 2008;10(5):e51. doi: 10.2196/jmir.1005.
    1. Brendryen H, Kraft P. Happy Ending: a randomized controlled trial of a digital multi-media smoking cessation intervention. Addiction. 2008 Mar;103(3):478–84; discussion 485. doi: 10.1111/j.1360-0443.2007.02119.x.
    1. Etter J. Comparing the efficacy of two internet-based, computer-tailored smoking cessation programs: a randomized trial. J Med Internet Res. 2005;7(1):e2. doi: 10.2196/jmir.7.1.e2.
    1. Japuntich SJ, Zehner ME, Smith SS, Jorenby DE, Valdez JA, Fiore MC, Baker TB, Gustafson DH. Smoking cessation via the internet: a randomized clinical trial of an internet intervention as adjuvant treatment in a smoking cessation intervention. Nicotine Tob Res. 2006 Dec;8(Suppl 1):S59–67.
    1. McKay HG, Danaher BG, Seeley JR, Lichtenstein E, Gau JM. Comparing two web-based smoking cessation programs: randomized controlled trial. J Med Internet Res. 2008;10(5):e40. doi: 10.2196/jmir.993.
    1. Strecher VJ, Shiffman S, West R. Randomized controlled trial of a web-based computer-tailored smoking cessation program as a supplement to nicotine patch therapy. Addiction. 2005 May;100(5):682–8. doi: 10.1111/j.1360-0443.2005.01093.x.
    1. Swartz LH, Noell JW, Schroeder SW, Ary DV. A randomised control study of a fully automated internet based smoking cessation programme. Tob Control. 2006 Feb;15(1):7–12. doi: 10.1136/tc.2003.006189.
    1. Wantland DJ, Portillo CJ, Holzemer WL, Slaughter R, McGhee EM. The effectiveness of Web-based vs non-Web-based interventions: a meta-analysis of behavioral change outcomes. J Med Internet Res. 2004 Nov 10;6(4):e40. doi: 10.2196/jmir.6.4.e40.
    1. Myung S, McDonnell DD, Kazinets G, Seo HG, Moskowitz JM. Effects of Web- and computer-based smoking cessation programs: meta-analysis of randomized controlled trials. Arch Intern Med. 2009 May 25;169(10):929–37. doi: 10.1001/archinternmed.2009.109.
    1. Taylor GMJ, Dalili MN, Semwal M, Civljak M, Sheikh A, Car J. Internet-based interventions for smoking cessation. Cochrane Database Syst Rev. 2017 Sep 4;9:CD007078. doi: 10.1002/14651858.CD007078.pub5.
    1. Graham AL, Carpenter KM, Cha S, Cole S, Jacobs MA, Raskob M, Cole-Lewis H. Systematic review and meta-analysis of internet interventions for smoking cessation among adults. Subst Abuse Rehabil. 2016;7:55–69. doi: 10.2147/SAR.S101660. doi: 10.2147/SAR.S101660.
    1. Intille SS, Kukla C, Farzanfar R, Bakr W. Just-in-time technology to encourage incremental, dietary behavior change. AMIA Annu Symp Proc. 2003:874.
    1. Riley WT, Rivera DE, Atienza AA, Nilsen W, Allison SM, Mermelstein R. Health behavior models in the age of mobile interventions: are our theories up to the task? Transl Behav Med. 2011 Mar;1(1):53–71. doi: 10.1007/s13142-011-0021-7.
    1. Free C, Whittaker R, Knight R, Abramsky T, Rodgers A, Roberts IG. Txt2stop: a pilot randomised controlled trial of mobile phone-based smoking cessation support. Tob Control. 2009 Apr;18(2):88–91. doi: 10.1136/tc.2008.026146.
    1. Rodgers A, Corbett T, Bramley D, Riddell T, Wills M, Lin R, Jones M. Do u smoke after txt? Results of a randomised trial of smoking cessation using mobile phone text messaging. Tob Control. 2005 Aug;14(4):255–61. doi: 10.1136/tc.2005.011577.
    1. Whittaker R, McRobbie H, Bullen C, Rodgers A, Gu Y. Mobile phone-based interventions for smoking cessation. Cochrane Database Syst Rev. 2016;4:CD006611. doi: 10.1002/14651858.CD006611.pub4.
    1. Graham AL, Jacobs MA, Cohn AM, Cha S, Abroms LC, Papandonatos GD, Whittaker R. Optimising text messaging to improve adherence to web-based smoking cessation treatment: a randomised control trial protocol. BMJ Open. 2016 Mar 30;6(3):e010687. doi: 10.1136/bmjopen-2015-010687.
    1. Pfaeffli DL, Dobson R, Whittaker R, Maddison R. The effectiveness of mobile-health behaviour change interventions for cardiovascular disease self-management: a systematic review. Eur J Prev Cardiol. 2016 May;23(8):801–17. doi: 10.1177/2047487315613462.
    1. Haskins BL, Lesperance D, Gibbons P, Boudreaux ED. A systematic review of smartphone applications for smoking cessation. Transl Behav Med. 2017 Jun;7(2):292–9. doi: 10.1007/s13142-017-0492-2.
    1. Klasnja P, Pratt W. Healthcare in the pocket: mapping the space of mobile-phone health interventions. J Biomed Inform. 2012 Feb;45(1):184–98. doi: 10.1016/j.jbi.2011.08.017.
    1. Pew RC. Pew Research Center. 2018. Internet/Broadband fact sheet
    1. Google. 2012. The new multi-screen world: Understanding cross-platform consumer behavior .
    1. Danaher BG, Brendryen H, Seeley JR, Tyler MS, Woolley T. From black box to toolbox: outlining device functionality, engagement activities, and the pervasive information architecture of mHealth interventions. Internet Interv. 2015 Mar 1;2(1):91–101. doi: 10.1016/j.invent.2015.01.002.
    1. Danaher BG, McKay HG, Seeley JR. The information architecture of behavior change websites. J Med Internet Res. 2005;7(2):e12. doi: 10.2196/jmir.7.2.e12.
    1. Pugatch J, Grenen E, Surla S, Schwarz M, Cole-Lewis H. Information architecture of web-based interventions to improve health outcomes: systematic review. J Med Internet Res. 2018 Mar 21;20(3):e97. doi: 10.2196/jmir.7867.
    1. Danaher BG, Severson HH, Crowley R, van Meter N, Tyler MS, Widdop C, Lichtenstein E, Ebbert Jo. Randomized controlled trial examining the adjunctive use of nicotine lozenges with MyLastDip: an eHealth smokeless tobacco cessation intervention. Internet Interv. 2015 Mar;2(1):69–76. doi: 10.1016/j.invent.2014.12.004.
    1. Danaher BG, Severson HH, Andrews JA, Tyler MS, Lichtenstein E, Woolley TG, Seeley JR. Randomized controlled trial of MyLastDip: a Web-based smokeless tobacco cessation program for chewers ages 14-25. Nicotine Tob Res. 2013 Sep;15(9):1502–10. doi: 10.1093/ntr/ntt006.
    1. Nielsen J. Nielsen Norman Group. [2019-01-02]. How many test users in a usability study?
    1. Nielsen J. Nielsen Norman Group. 2012. [2019-01-02]. Thinking aloud: The #1 usability tool
    1. Nielsen Norman Group. 2014. [2019-01-02]. Turn user goals into task scenarios for usability testing
    1. . [2019-01-02]. Use case scenarios .
    1. Lew GS. What do users really do? Experience sampling in the 21st century. In: Jacko JA, editor. Human-Computer Interaction. New Trends: 13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings, Part I (Lecture Notes in Computer Science) Berlin: Springer; 2009.
    1. Lew G. User Experience Magazine. [2019-01-02]. The truth is out there: using mobile technology for experience sampling
    1. Fagerstrom KO, Schneider NG. Measuring nicotine dependence: a review of the Fagerstrom Tolerance Questionnaire. J Behav Med. 1989 Apr;12(2):159–82.
    1. Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO. The Fagerström Test for Nicotine Dependence: a revision of the Fagerström Tolerance Questionnaire. Br J Addict. 1991 Sep;86(9):1119–27.
    1. Transdisciplinary Tobacco Use Research Center (TTURC) Tobacco Dependence. Baker TB, Piper ME, McCarthy DE, Bolt DM, Smith SS, Kim S, Colby S, Conti D, Giovino GA, Hatsukami D, Hyland A, Krishnan-Sarin S, Niaura R, Perkins KA, Toll BA. Time to first cigarette in the morning as an index of ability to quit smoking: implications for nicotine dependence. Nicotine Tob Res. 2007 Nov;9(Suppl 4):S555–70. doi: 10.1080/14622200701673480.
    1. Danaher BG, Smolkowski K, Seeley JR, Severson HH. Mediators of a successful web-based smokeless tobacco cessation program. Addiction. 2008 Oct;103(10):1706–12. doi: 10.1111/j.1360-0443.2008.02295.x.
    1. Biener L, Abrams DB. The Contemplation Ladder: validation of a measure of readiness to consider smoking cessation. Health Psychol. 1991;10(5):360–5.
    1. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Sep;16(9):606–13.
    1. Wells TS, Horton JL, LeardMann CA, Jacobson IG, Boyko EJ. A comparison of the PRIME-MD PHQ-9 and PHQ-8 in a large military prospective study, the Millennium Cohort Study. J Affect Disord. 2013 May 15;148(1):77–83. doi: 10.1016/j.jad.2012.11.052.
    1. Kroenke K, Strine TW, Spitzer RL, Williams JB, Berry JT, Mokdad AH. The PHQ-8 as a measure of current depression in the general population. J Affect Disord. 2009 Apr;114(1-3):163–73. doi: 10.1016/j.jad.2008.06.026.
    1. Kroenke K, Spitzer RL. The PHQ-9: a new depression diagnostic and severity measure. Psychiatric Annals. 2002 Sep 1;32(9):509–15. doi: 10.3928/0048-5713-20020901-06.
    1. Danaher BG, Boles SM, Akers L, Gordon JS, Severson HH. Defining participant exposure measures in Web-based health behavior change programs. J Med Internet Res. 2006;8(3):e15. doi: 10.2196/jmir.8.3.e15.
    1. ScientiaMobile. 2019. [2019-04-23].
    1. ScientiaMobile. [2019-04-23]. Device Detection
    1. Mungovan B. Adobe Blog. [2019-04-23]. Are tablets mobile devices? How will Google's changes in AdWords impact advertisers?
    1. Smolkowski K, Danaher BG, Seeley JR, Kosty DB, Severson HH. Modeling missing binary outcome data in a successful web-based smokeless tobacco cessation program. Addiction. 2010 Jun;105(6):1005–15. doi: 10.1111/j.1360-0443.2009.02896.x.
    1. Schulz KF, Altman DG, Moher D, CONSORT Group CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. PLoS Med. 2010 Mar 24;7(3):e1000251. doi: 10.1371/journal.pmed.1000251.
    1. McCrabb S, Baker AL, Attia J, Skelton E, Twyman L, Palazzi K, McCarter K, Ku D, Bonevski B. Internet-based programs incorporating behavior change techniques are associated with increased smoking cessation in the general population: a systematic review and meta-analysis. Ann Behav Med. 2018 May 10;:180–95. doi: 10.1093/abm/kay026.
    1. Glasgow RE, Mullooly JP, Vogt TM, Stevens VJ, Lichtenstein E, Hollis JF, Lando HA, Severson HH, Pearson KA, Vogt MR. Biochemical validation of smoking status: pros, cons, and data from four low-intensity intervention trials. Addict Behav. 1993;18(5):511–27.
    1. SRNT Subcommittee on Biochemical Verification Biochemical verification of tobacco use and cessation. Nicotine Tob Res. 2002 May;4(2):149–59. doi: 10.1080/14622200210123581.
    1. Cobb NK, Jacobs MA, Wileyto P, Valente T, Graham AL. Diffusion of an evidence-based smoking cessation intervention through Facebook: a randomized controlled trial. Am J Public Health. 2016 Jun;106(6):1130–5. doi: 10.2105/AJPH.2016.303106.
    1. Saul JE, Amato MS, Cha S, Graham AL. Engagement and attrition in Internet smoking cessation interventions: Insights from a cross-sectional survey of "one-hit-wonders". Internet Interv. 2016 Sep;5:23–29. doi: 10.1016/j.invent.2016.07.001.
    1. Eysenbach G. The law of attrition. J Med Internet Res. 2005;7(1):e11. doi: 10.2196/jmir.7.1.e11.
    1. Cobb CO, Graham AL. Use of non-assigned interventions in a randomized trial of internet and telephone treatment for smoking cessation. Nicotine Tob Res. 2014 Oct;16(10):1289–97. doi: 10.1093/ntr/ntu066.
    1. Ater T. Building Progressive Web Apps: Bringing the Power of Native to the Browser. Sebastopol, CA: O'Reilly Media; 2017.
    1. Greenfield A. Everyware: The Dawning Age Of Ubiquitous Computing. Berkeley, CA: New Riders Publishing; 2019.
    1. Resmini A, Rosati L. Pervasive Information Architecture: Designing Cross-Channel User Experiences. Burlington, MA: Morgan Kaufmann; 2011.

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