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dc.contributor.authorAbbate, Kristopher J
dc.contributor.authorHingle, Melanie D
dc.contributor.authorArmin, Julie
dc.contributor.authorGiacobbi Jr, Peter
dc.contributor.authorGordon, Judith S
dc.date.accessioned2017-12-21T16:41:20Z
dc.date.available2017-12-21T16:41:20Z
dc.date.issued2017-11-03
dc.identifier.citationRecruiting Women to a Mobile Health Smoking Cessation Trial: Low- and No-Cost Strategies 2017, 6 (11):e219 JMIR Research Protocolsen
dc.identifier.issn1929-0748
dc.identifier.pmid29101091
dc.identifier.doi10.2196/resprot.7356
dc.identifier.urihttp://hdl.handle.net/10150/626269
dc.description.abstractBackground: Successful recruitment of participants to mobile health (mHealth) studies presents unique challenges over in-person studies. It is important to identify recruitment strategies that maximize the limited recruitment resources available to researchers. Objective: The objective of this study was to describe a case study of a unique recruitment process used in a recent mHealth software app designed to increase smoking cessation among weight-concerned women smokers. The See Me Smoke-Free app was deployed to the Google Play Store (Alphabet, Inc., Google, LLC), where potential participants could download the app and enroll in the study. Users were invited in-app to participate in the study, with no in-person contact. The recruitment activities relied primarily on earned (free) and social media. Methods: To determine the relationship between recruitment activities and participant enrollment, the researchers explored trends in earned and social media activity in relation to app installations, examined social media messaging in relation to reach or impressions, and described app users' self-reported referral source. The researchers collected and descriptively analyzed data regarding recruitment activities, social media audience, and app use during the 18-week recruitment period (March 30, 2015-July 31, 2015). Data were collected and aggregated from internal staff activity tracking documents and from Web-based data analytics software such as SumAll, Facebook Insights (Facebook, Inc.), and Google Analytics (Alphabet, Inc., Google, LLC). Results: Media coverage was documented across 75 publications and radio or television broadcasts, 35 of which were local, 39 national, and 1 international. The research team made 30 Facebook posts and 49 tweets, yielding 1821 reaches and 6336 impressions, respectively. From March 30, 2015 to July 31, 2015, 289 unique users downloaded the app, and 151 participants enrolled in the study. Conclusions: Research identifying effective online recruitment methods for mHealth studies remains minimal, and findings are inconsistent. We demonstrated how earned media can be leveraged to recruit women to an mHealth smoking cessation trial at low cost. Using earned media and leveraging social media allowed us to enroll 3 times the number of participants that we anticipated enrolling. The cost of earned media resides in the staff time required to manage it, particularly the regular interaction with social media. We recommend communication and cooperation with university public affairs and social media offices, as well as affiliate programs in journalism and communications, so that earned media can be used as a recruitment strategy for mHealth behavior change interventions. However, press releases are not always picked up by the media and should not be considered as a stand-alone method of recruitment. Careful consideration of an intervention's broad appeal and how that translates into potential media interest is needed when including earned media as part of a comprehensive recruitment plan for mHealth research.
dc.description.sponsorshipNational Cancer Institute [1R21CA174639]en
dc.language.isoenen
dc.publisherJMIR PUBLICATIONS, INCen
dc.relation.urlhttp://www.researchprotocols.org/2017/11/e219/en
dc.rights©Kristopher J Abbate, Melanie D Hingle, Julie Armin, Peter Giacobbi Jr, Judith S Gordon. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 03.11.2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License.en
dc.subjectsmoking cessationen
dc.subjectmobile applicationsen
dc.subjectsocial mediaen
dc.subjectwomenen
dc.subjectmHealthen
dc.titleRecruiting Women to a Mobile Health Smoking Cessation Trial: Low- and No-Cost Strategiesen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Coll Meden
dc.contributor.departmentUniv Arizona, Coll Agr & Life Sci, Dept Nutr Scien
dc.contributor.departmentUniv Arizona, Dept Family & Community Meden
dc.contributor.departmentUniv Arizona, Coll Nursingen
dc.identifier.journalJMIR Research Protocolsen
dc.description.noteOpen access journal.en
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
refterms.dateFOA2018-09-12T00:40:15Z
html.description.abstractBackground: Successful recruitment of participants to mobile health (mHealth) studies presents unique challenges over in-person studies. It is important to identify recruitment strategies that maximize the limited recruitment resources available to researchers. Objective: The objective of this study was to describe a case study of a unique recruitment process used in a recent mHealth software app designed to increase smoking cessation among weight-concerned women smokers. The See Me Smoke-Free app was deployed to the Google Play Store (Alphabet, Inc., Google, LLC), where potential participants could download the app and enroll in the study. Users were invited in-app to participate in the study, with no in-person contact. The recruitment activities relied primarily on earned (free) and social media. Methods: To determine the relationship between recruitment activities and participant enrollment, the researchers explored trends in earned and social media activity in relation to app installations, examined social media messaging in relation to reach or impressions, and described app users' self-reported referral source. The researchers collected and descriptively analyzed data regarding recruitment activities, social media audience, and app use during the 18-week recruitment period (March 30, 2015-July 31, 2015). Data were collected and aggregated from internal staff activity tracking documents and from Web-based data analytics software such as SumAll, Facebook Insights (Facebook, Inc.), and Google Analytics (Alphabet, Inc., Google, LLC). Results: Media coverage was documented across 75 publications and radio or television broadcasts, 35 of which were local, 39 national, and 1 international. The research team made 30 Facebook posts and 49 tweets, yielding 1821 reaches and 6336 impressions, respectively. From March 30, 2015 to July 31, 2015, 289 unique users downloaded the app, and 151 participants enrolled in the study. Conclusions: Research identifying effective online recruitment methods for mHealth studies remains minimal, and findings are inconsistent. We demonstrated how earned media can be leveraged to recruit women to an mHealth smoking cessation trial at low cost. Using earned media and leveraging social media allowed us to enroll 3 times the number of participants that we anticipated enrolling. The cost of earned media resides in the staff time required to manage it, particularly the regular interaction with social media. We recommend communication and cooperation with university public affairs and social media offices, as well as affiliate programs in journalism and communications, so that earned media can be used as a recruitment strategy for mHealth behavior change interventions. However, press releases are not always picked up by the media and should not be considered as a stand-alone method of recruitment. Careful consideration of an intervention's broad appeal and how that translates into potential media interest is needed when including earned media as part of a comprehensive recruitment plan for mHealth research.


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