Yongcheng Zhan1, Jean-François Etter2, Scott Leischow3, Daniel Zeng1. 1. Department of Management Information Systems, University of Arizona, Tucson, Arizona, USA. 2. Institute of Global Health, Faculty of Medicine, University of Geneva, Switzerland. 3. College of Health Solutions, Arizona State University, Phoenix, Arizona, USA.
Abstract
Objective: To identify who were social media active e-cigarette users, to compare the use patterns from both survey and social media data for data triangulation, and to jointly use both datasets to conduct a comprehensive analysis on e-cigarette future use intentions. Materials and Methods: We jointly used an e-cigarette use online survey (n = 5132) and a social media dataset. We conducted analysis from 3 different perspectives. We analyzed online forum participation patterns using survey data. We compared e-cigarette use patterns, including brand and flavor types, ratings, and purchase approaches, between the 2 datasets. We used logistic regression to study intentions to use e-cigarettes using both datasets. Results: Male and younger e-cigarette users were the most likely to participate in e-cigarette-related discussion forums. Forum active survey participants were hardcore vapers. The e-cigarette use patterns were similar in the online survey data and the social media data. Intention to use e-cigarettes was positively related to e-liquid ratings and flavor ratings. Social media provided a valuable source of information on users' ratings of e-cigarette refill liquids. Discussion: For hardcore vapers, social media data were consistent with online survey data, which suggests that social media may be useful to study e-cigarette use behaviors and can serve as a useful complement to online survey research. We proposed an innovative framework for social media data triangulation in public health studies. Conclusion: We illustrated how social media data, combined with online survey data, can serve as a new and rich information source for public health research.
Objective: To identify who were social media active e-cigarette users, to compare the use patterns from both survey and social media data for data triangulation, and to jointly use both datasets to conduct a comprehensive analysis on e-cigarette future use intentions. Materials and Methods: We jointly used an e-cigarette use online survey (n = 5132) and a social media dataset. We conducted analysis from 3 different perspectives. We analyzed online forum participation patterns using survey data. We compared e-cigarette use patterns, including brand and flavor types, ratings, and purchase approaches, between the 2 datasets. We used logistic regression to study intentions to use e-cigarettes using both datasets. Results: Male and younger e-cigarette users were the most likely to participate in e-cigarette-related discussion forums. Forum active survey participants were hardcore vapers. The e-cigarette use patterns were similar in the online survey data and the social media data. Intention to use e-cigarettes was positively related to e-liquid ratings and flavor ratings. Social media provided a valuable source of information on users' ratings of e-cigarette refill liquids. Discussion: For hardcore vapers, social media data were consistent with online survey data, which suggests that social media may be useful to study e-cigarette use behaviors and can serve as a useful complement to online survey research. We proposed an innovative framework for social media data triangulation in public health studies. Conclusion: We illustrated how social media data, combined with online survey data, can serve as a new and rich information source for public health research.
Authors: Jennifer L Pearson; Amanda Richardson; Raymond S Niaura; Donna M Vallone; David B Abrams Journal: Am J Public Health Date: 2012-07-19 Impact factor: 9.308
Authors: George W Rutherford; William McFarland; Hilary Spindler; Karen White; Sadhna V Patel; John Aberle-Grasse; Keith Sabin; Nathan Smith; Stephanie Taché; Jesus M Calleja-Garcia; Rand L Stoneburner Journal: BMC Public Health Date: 2010-07-29 Impact factor: 3.295
Authors: Yongcheng Zhan; Ruoran Liu; Qiudan Li; Scott James Leischow; Daniel Dajun Zeng Journal: J Med Internet Res Date: 2017-01-20 Impact factor: 5.428