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. 2015 Feb 23;17(2):e50.
doi: 10.2196/jmir.3772.

Development of a Twitter-based intervention for smoking cessation that encourages high-quality social media interactions via automessages

Cornelia Pechmann  1 , Li Pan, Kevin Delucchi, Cynthia M Lakon, Judith J Prochaska
Affiliations

Development of a Twitter-based intervention for smoking cessation that encourages high-quality social media interactions via automessages

Cornelia Pechmann et al. J Med Internet Res. .

Abstract

Background: The medical field seeks to use social media to deliver health interventions, for example, to provide low-cost, self-directed, online self-help groups. However, engagement in online groups is often low and the informational content may be poor.

Objective: The specific study aims were to explore if sending automessages to online self-help groups encouraged engagement and to see if overall or specific types of engagement related to abstinence.

Methods: We conducted a Stage I Early Therapy Development Trial of a novel social media intervention for smoking cessation called Tweet2Quit that was delivered online over closed, 20-person quit-smoking groups on Twitter in 100 days. Social media such as Twitter traditionally involves non-directed peer-to-peer exchanges, but our hybrid social media intervention sought to increase and direct such exchanges by sending out two types of autocommunications daily: (1) an "automessage" that encouraged group discussion on an evidence-based cessation-related or community-building topic, and (2) individualized "autofeedback" to each participant on their past 24-hour tweeting. The intervention was purposefully designed without an expert group facilitator and with full automation to ensure low cost, easy implementation, and broad scalability. This purely Web-based trial examined two online quit-smoking groups with 20 members each. Participants were adult smokers who were interested in quitting and were recruited using Google AdWords. Participants' tweets were counted and content coded, distinguishing between responses to the intervention's automessages and spontaneous tweets. In addition, smoking abstinence was assessed at 7 days, 30 days, and 60 days post quit date. Statistical models assessed how tweeting related to abstinence.

Results: Combining the two groups, 78% (31/40) of the members sent at least one tweet; and on average, each member sent 72 tweets during the 100-day period. The automessage-suggested discussion topics and participants' responses to those daily automessages were related in terms of their content (r=.75, P=.012). Responses to automessages contributed 22.78% (653/2867) of the total tweets; 77.22% (2214/2867) were spontaneous. Overall tweeting related only marginally to abstinence (OR 1.03, P=.086). However, specific tweet content related to abstinence including tweets about setting of a quit date or use of nicotine patches (OR 1.52, P=.024), countering of roadblocks to quitting (OR 1.76, P=.008) and expressions of confidence about quitting (OR 1.71, SE 0.42, P=.032). Questionable, that is, non-evidence-based, information about quitting did not relate to abstinence (OR 1.12, P=.278).

Conclusions: A hybrid social media intervention that combines traditional online social support with daily automessages appears to hold promise for smoking cessation. This hybrid approach capitalizes on social media's spontaneous real-time peer-to-peer exchanges but supplements this with daily automessages that group members respond to, bolstering and sustaining the social network and directing the information content. Highly engaging, this approach should be studied further.

Trial registration: Clinicaltrials.gov NCT01602536; https://clinicaltrials.gov/ct2/show/NCT01602536 (Archived by WebCite at http://www.webcitation.org/6WGbt0o1K).

Keywords: smoking cessation; social media; text messaging.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Tweeting volume and duration in Group 1.
Figure 2
Figure 2
Tweeting volume and duration in Group 2.
Figure 3
Figure 3
Tweeting by time of day in Group 1.
Figure 4
Figure 4
Tweeting by time of day in Group 2.
See this image and copyright information in PMC

References

    1. Baumann P. PhilBaumann.com. 2009. [2015-02-13]. 140 health care uses for Twitter http://philbaumann.com/140-health-care-uses-for-twitter/
    1. Duggan M, Smith A. 42% of online adults use multiple social networking sites, but Facebook remains the platform of choice December 30. 2013. Dec 30, [2015-02-13]. http://www.pewinternet.org/files/2014/01/Social_Networking_2013.pdf.
    1. Gruzd A, Wellman B, Takhteyev Y. Imagining Twitter as an imagined community. American Behavioral Scientist. 2011;55(10):1294–1318. doi: 10.1177/0002764211409378. - DOI
    1. Gruzd A, Haythornthwaite C. Enabling community through social media. J Med Internet Res. 2013;15(10):e248. doi: 10.2196/jmir.2796. http://www.jmir.org/2013/10/e248/ - DOI - PMC - PubMed
    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. http://www.jmir.org/2006/3/e15/ - DOI - PMC - PubMed

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