Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-23T04:08:46.906Z Has data issue: false hasContentIssue false
  • English
  • Français

Quitting smoking using health issue-specific Social Networking Sites (SNSs): What influences participation, social identification, and smoking cessation self-efficacy?

Published online by Cambridge University Press:  09 August 2013

Joe Phua
Joe Phua*
Affiliation:
University of Georgia
*
Address for Correspondence: Joe Phua, PhD, Assistant Professor, Grady College of Journalism and Mass Communication, University of Georgia, 120 Hooper Street, Athens, GA 30602, USA, E-mail: [email protected], Phone: (706) 542-4984
Get access Rights & Permissions [Opens in a new window]

Abstract

Introduction: This study examined members of health issue-specific social networking sites (SNSs) for smoking cessation, applying Social Identity Theory (SIT).

Aims: The aim of the study was to test the relationships between perceived verbal, affective, cognitive and physical intimacy on the sites, participation level, social identification and smoking cessation self-efficacy.

Methods: An online questionnaire (N = 252) assessed members of SNSs for smoking cessation. Confirmatory factor analysis (CFA), structural equation modelling (SEM), mediation analysis, MANOVA and ANOVA tests were used to test the hypotheses.

Results/Findings: Verbal, affective, cognitive and physical intimacy significantly predicted participation; participation significantly predicted social identification and smoking cessation self-efficacy; and social identification mediated between participation and smoking cessation self-efficacy. Active participants and lurkers differed significantly on perceived verbal, affective, cognitive and physical intimacy, social identification, and smoking cessation self-efficacy.

Conclusions: Health issue-specific SNSs for smoking cessation have a positive impact on members’ smoking cessation self-efficacy. Higher perceived intimacy facilitates participation online, which in turn influences smoking cessation self-efficacy, with social identification mediating this relationship.

Keywords

social networking sitessocial identity theorysmoking cessation self-efficacyparticipationlurking
Type
Articles
Information
Journal of Smoking Cessation , Volume 9 , Issue 1 , June 2014 , pp. 39 - 51
Copyright
Copyright © The Author(s), published by Cambridge University Press on behalf of Australian Academic Press Pty Ltd 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Balmford, J., Borland, R. & Benda, P. (2008). Patterns of use of an automated interactive personalized coaching program for smoking cessation. Journal of Medical Internet Research, 10 (5), e54. doi:10.2196/jmir.1016Google Scholar
Barker, V. (2009). Older adolescents’ motivations for social network site usage: The influence of gender, group identity, and collective self-esteem. Cyber Psychology & Behavior, 12 (2), 209–213. doi:10.1089/cpb.2008.0228.CrossRefGoogle Scholar
Bishop, J. (2007). Increasing participation in online communities: A framework for human-computer interaction. Computers in Human Behavior, 23, 1881–1893. doi:10.1016/j.chb.2005.11.004Google Scholar
Boulos, M. & Wheeler, S. (2007). The emerging Web 2.0 social software: An enabling suite of sociable technologies in health and health care education. Health Information and Libraries Journal, 24, 2–23. doi:0.1111/j.1471-1842.2007.00701.xGoogle Scholar
boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13, article 11. doi:10.1111/j.1083-6101.2007.00393.xCrossRefGoogle Scholar
Brandtzaeg, P. B. & Heim, J. (2011). A typology of social networking sites users. International Journal of Web-Based Communities, 7 (1), 28–51. doi:10.1504/IJWBC.2011.038124Google Scholar
Byrne, B. M. (1998). Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Basic Concepts, Applications, and Programming. Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Butler, B., Sproull, L., Kiesler, S. & Kraut, R. (2002). Community effort in online groups: Who does the work and why? In Weisband, S. & Atwater, L. (Eds). Leadership at a Distance. Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Centers for Disease Control and Prevention (2013). Smoking and Tobacco Use. Retrieved from: http://www.cdc.gov/tobacco/data_statistics/fact_sheets/fast_facts/#tollGoogle Scholar
Christofides, E., Muise, A. & Desmarais, S. (2009). Information disclosure and control on Facebook: Are they two sides of the same coin or two different processes? Cyberpsychology and Behavior, 12 (3), 341–345. doi:10.1089/cpb.2008.0226.Google Scholar
Cobb, N. K., Graham, A. L. & Abrams, D. B. (2010). Social network structure of a large online community for smoking cessation. American Journal of Public Health, 100 (7), 1282–1289. doi:10.2105/AJPH.2009.165449Google Scholar
Cullum, J., O'Grady, M., Sandoval, P., Armeli, S. & Tennen, H. (2013). Ignoring norms with a little help from my friends: Social support reduces normative influence on drinking behavior. Journal of Social & Clinical Psychology, 32 (1), 17–33. doi:10.1521/jscp.2013.32.1.17.Google Scholar
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook ‘Friends:’ social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12 (4), 1143–1168. doi:10.1111/j.1083-6101.2007.00367.xGoogle Scholar
Etter, J., Bergman, M., Humair, J. & Perneger, T.V. (2000). Development and validation of a scale measuring self-efficacy of current and former smokers. Addiction, 95 (6), 901–913. doi:10.1046/j.1360-0443.2000.9569017.xGoogle Scholar
Han, J. Y., Kim, J. H., Yoon, H. J., Shim, M. S., McTavish, F. & Gustafson, D. (2012). Social and psychological determinants of levels of engagement with an online breast cancer support group: Posters, lurkers and non-users. Journal of Health Communication, 17 (3), 356–371. doi:10.1080/10810730.2011.585696Google Scholar
Harman, H. (1976). Modern Factor Analysis: 3rd Edition. Chicago, IL: Chicago University Press.Google Scholar
Hoe, S. L. (2008). Issues and procedures in adopting structural equation modeling technique. Journal of Applied Quantitative Methods, 3 (1), 76–83.Google Scholar
Hogg, M. A. (2003). Social Identity. In Leary, M. R. & Tangney, J. P. (Eds). Handbook of Self and Identity. Chapter 23. New York, NY: Guilford Press.Google Scholar
Hogg, M. A. & Reid, S. A. (2006). Social identity, Self-categorization and the communication of group norms. Communication Theory, 16, 7–30. doi:10.1111/j.1468-2885.2006.00003.xGoogle Scholar
Hughes, B., Joshi, I. & Wareham, J. (2008). Health 2.0 and medicine 2.0: Tensions and controversies in the field. Journal of Medical Internet Research, 10 (3), e23. doi:10.2196/jmir.1056CrossRefGoogle Scholar
Kobus, K. (2003). Peers and adolescent smoking. Addiction, 98 (s1), 37–55. doi:10.1046/j.1360-0443.98.s1.4.xGoogle Scholar
Kontos, E. Z., Emmons, K. M., Puleo, E. & Viswanath, K. (2010). Communication inequalities and public health implications of adult social networking site use in the United States. Journal of Health Communication, 15 (3), 216–235. doi:10.1080/10810730.2010.522689Google Scholar
Kollock, P. & Smith, M. (1996). Managing the virtual commons: Cooperation and conflict in computer communities. In Herring, S. C. (Ed.): Computer-Mediated Communication: Linguistic, Social, and Cross-Cultural Perspectives. pp. 109–128. Amsterdam, Netherlands: John Benjamin.Google Scholar
McLaughlin, M. L., Osborne, K. K., and Smith, C. B. (1995). Standards of conduct on Usenet. In Jones, S. G. (Ed.): CyberSociety. pp. 90–111. Thousand Oaks, CA: Sage Publications.Google Scholar
Miller, R. S. & Lefcourt, H. M. (1982). The assessment of social intimacy. Journal of Personality Assessment, 46 (5), 514–518. doi:10.1207/s15327752jpa4605_12Google Scholar
Mo, P. K. H. & Coulson, N. S. (2010). Empowering processes in online support groups among people living with HIV/AIDS: A comparative analysis of ‘lurkers’ and ‘posters’. Computers in Human Behavior, 26 (5), 1183–1193. doi:10.1016/j.chb.2010.03.028Google Scholar
Norman, C. D., McIntosh, S., Selby, P. & Eysenbach, G. (2008). Web-assisted tobacco interventions: Empowering change in the global fight for the public's (e)health. Journal of Medical Internet Research, 10 (5), e1. doi:10.2196/jmir.1171Google Scholar
Papacharissi, Z. & Rubin, A. M. (2000). Predictors of internet use. Journal of Broadcasting & Electronic Media, 44 (2), 175–196. doi:10.1207/s15506878jobem4402_2Google Scholar
Parks, R. M. & Floyd, K. (1996). Making friends in cyberspace. Journal of Computer-Mediated Communication, 1 (4). doi:10.1111/j.1083-6101.1996.tb00176.xGoogle Scholar
Preacher, K. J. & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40 (3), 879–891. doi:10.3758/BRM.40.3.879Google Scholar
Preece, J., Nonnecke, B. & Andrews, D. (2004). The top five reasons for lurking: Improving community experiences for everyone. Computers in Human Behavior, 20 (2), 201–223. doi:10.1016/j.chb.2003.10.015Google Scholar
Ramirez, A., Zhang, S., McGrew, C. & Lin, S. F. (2007). Relational communication in computer-mediated interaction revisited: A comparison of participant-observer perspectives. Communication Monographs, 74 (4), 492–516. doi:10.1080/03637750701716586Google Scholar
Rau, P. L. P., Gao, Q. & Ding, Y. (2008). Relationship between the level of intimacy and lurking in online social network services. Computers in Human Behavior, 24, 2757–2770. doi:10.1016/j.chb.2008.04.001CrossRefGoogle Scholar
Reed, M. B., Lange, J. E., Ketchie, J. M. & Clapp, J. D. (2007). The relationship between social identity, normative information and college student drinking. Social Influence, 2 (4), 269–294. doi:10.1080/15534510701476617Google Scholar
Schlosser, A. E. (2005). Posting versus lurking: Communicating in a multiple audience context. Journal of Consumer Research, 32 (2), 260–265. doi:10.1086/432235Google Scholar
Stretcher, V. J., Shiffman, S. & West, R. (2005). Randomized controlled trial of a web-based computer-tailored smoking cessation program as a supplement to nicotine patch therapy. Addiction, 100 (5), 682–688. doi:10.1111/j.1360-0443.2005.01093.xGoogle Scholar
Stoddard, J. L., Delucchi, K. L., Munoz, R. F., Collins, N. M., Perez-Stable, E. J. & Augustson, E. (2005). Smoking cessation research via the Internet: A feasibility study. Journal of Health Communication, 10 (1), 27–41. doi:10.1080/10810730590904562Google Scholar
Tajfel, H. & Turner, J. C. (1986). The social identity theory of intergroup behavior. In Stapel, D. A. & H, H. Blanton (Eds). Social Comparison Theories: Key Readings in Social Psychology. New York, NY: Taylor & Francis.Google Scholar
Valkenburg, P. M., Peter, J. & Schouten, A. P. (2006). Friend networking sites and their relationship to adolescents well-being and social self-esteem. CyberPsychology & Behavior, 9 (5), 584–590. doi:10.1089/cpb.2006.9.584Google Scholar
Van Uden-Kraan, C. F., Drossaert, C. H. C., Taal, E., Seydel, E. R. & Van de Laar, M. A. F. J. (2008). Self-reported differences in empowerment between lurkers and posters in online patient support groups. Journal of Medical Internet Research, 10 (2), e18. doi:10.2196/jmir.992Google Scholar
White, M. & Dorman, S. M. (2001). Receiving social support online: Implications for health education. Health Education Research, 16 (6), 693–707. doi:10.1093/her/16.6.693Google Scholar
World Health Organization (2013). Media Center: Tobacco Fact Sheets. Retrieved from: http://www.who.int/mediacentre/factsheets/fs339/en/Google Scholar