Are Social Networking Sites Making Health Behavior Change Interventions More Effective? A Meta-Analytic Review

Journal of Health Communication

Volumn 22, Issue 3, 2017, Pages 223-233

  Yang, Qinghua ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HEALTH BEHAVIOR; HEALTH PROMOTION; HUMAN; INTERNET; META ANALYSIS; PROGRAM EVALUATION; RANDOMIZED CONTROLLED TRIAL (TOPIC); SOCIAL NETWORK;

HEALTH BEHAVIOR; HEALTH PROMOTION; HUMANS; INTERNET; PROGRAM EVALUATION; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SOCIAL NETWORKING;

EID: 85013113191     PISSN: 10810730     EISSN: 10870415     Source Type: Journal    
DOI: 10.1080/10810730.2016.1271065     Document Type: Article

References (75)

1. * References marked with an asterisk indicate studies included in the meta-analysis
2. Ajzen, I., (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179–211. doi:10.1016/0749-5978(91)90020-T
3. Andreasen, A., (1994). Social marketing:Definition and domain. Journal of Public Policy & Marketing, 13 (1), 108–114.
4. Bandura, A., (1986). Social foundations of thought and action:A social cognitive theory. Upper Saddle River, NJ:Prentice-Hall, Inc.
5. *Baskerville, N. B., Azagba, S., Norman, C., McKeown, K., & Brown, K. S., (2015). Effect of a digital social media campaign on young adult smoking cessation. Nicotine & Tobacco Research, 1–10. doi:10.1093/ntr/ntv119
6. Behrstock-Sherratt, E., & Coggshall, J. G., (2010). Realizing the promise of Generation Y. Educational Leadership, 67 (8), 28–34.
7. Berger, J., (2013). Contagious:Why things catch on. New York, NY:Simon and Schuster.
8. BI Intelligence. (2015, August 25). Women dominate most of social media, but men are more active on these two networks. The Business Insider. Retrieved from http://www.businessinsider.com/demographics-of-social-media-by-gender-8-2015
9. Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R., (2009). Introduction to meta-analysis. Oxford, UK:John Wiley & Sons.
10. Boyd, D., & Ellison, N. B., (2007). Social network sites:Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13 (1), 210–230. doi:10.1111/j.1083-6101.2007.00393.x
11. *Brindal, E., Freyne, J., Saunders, I., Berkovsky, S., Smith, G., & Noakes, M., (2012). Features predicting weight loss in overweight or obese participants in a web-based intervention:Randomized trial. Journal of Medical Internet Research, 14 (6), e173. doi:10.2196/jmir.2156.
12. *Bull, S. S., Levine, D. K., Black, S. R., Schmiege, S. J., & Santelli, J., (2012). Social media–delivered sexual health intervention:A cluster randomized controlled trial. American Journal of Preventive Medicine, 43 (5), 467–474. doi:10.1016/j.amepre.2012.07.022
13. *Cavallo, D. N., Tate, D. F., Ries, A. V., Brown, J. D., DeVellis, R. F., & Ammerman, A. S., (2012). A social media–based physical activity intervention:A randomized controlled trial. American Journal of Preventive Medicine, 43 (5), 527–532. doi:10.1016/j.amepre.2012.07.019
14. *Cobb, N. K., & Poirier, J., (2014). Effectiveness of a multimodal online well-being intervention:A randomized controlled trial. American Journal of Preventive Medicine, 46 (1), 41–48. doi:10.1016/j.amepre.2013.08.018
15. Cohen, J., (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ:Lawrence Erlbaum.
16. Cohen, S., & Wills, T. A., (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98, 310–357. doi:10.1037/0033-2909.98.2.310
17. Cooper, H. M., Hedges, L. V., & Valentine, J. C., (Eds.). (2009). The handbook of research synthesis and meta-analysis (2nd ed.). New York, NY:Russell Sage Foundation.
18. Danaher, B. G., & Seeley, J. R., (2009). Methodological issues in research on web-based behavioral interventions. Annals of Behavioral Medicine, 38 (1), 28–39. doi:10.1007/s12160-009-9129-0
19. De Bruyn, A., & Lilien, G. L., (2008). A multi-stage model of word-of-mouth influence through viral marketing. International Journal of Research in Marketing, 25 (3), 151–163. doi:10.1016/j.ijresmar.2008.03.004
20. Duggan, M., Ellison, N. B., Lampe, C., Lenhart, A., & Madden, M., (2015, January 9). Demographics of key social networking platforms. Pew Research Center. Retrieved from http://www.pewinternet.org/2015/01/09/demographics-of-key-social-networking-platforms-2
21. Eysenbach, G., (2005). The law of attrition. Journal of Medical Internet Research, 7 (1), e11. doi:10.2196/jmir.7.1.e11
22. Falk, A., & Heckman, J., (2009). Lab experiments are a major source of knowledge in the social sciences. Science, 326 (5952), 535–538. doi:10.1126/science.1168244
23. Festinger, L., (1954). A theory of social comparison processes. Human Relations, 7 (2), 117–140. doi:10.1177/001872675400700202
24. Fishbein, M., & Ajzen, I., (2011). Predicting and changing behavior:The reasoned action approach. New York, NY:Taylor & Francis.
25. Floyd, R. L., Sobell, M., Velasquez, M. M., Ingersoll, K., Nettleman, M., Sobell, L., & #X0026; Project CHOICES Efficacy Study Group. (2007). Preventing alcohol-exposed pregnancies:A randomized controlled trial. American Journal of Preventive Medicine, 32 (1), 1–10.
26. *Foster, D., Linehan, C., Kirman, B., Lawson, S., & James, G., (2010, October). Motivating physical activity at work:Using persuasive social media for competitive step counting. In Proceedings of the 14th International Academic MindTrek Conference:Envisioning Future Media Environments (pp. 111–116). doi:10.1145/1930488.1930510
27. Fox, S., (2011). The social life of health information. Pew Internet & American Life Project. Retrieved from http://www.pewinternet.org/2011/05/12/the-social-life-of-health-information-2011/
28. *Freyne, J., Berkovsky, S., Kimani, S., Baghaei, N., & Brindal, E., (2010, October). Improving health information access through social networking. Computer-Based Medical Systems (CBMS), 2010 IEEE 23rd International Symposium (pp. 334–339). doi:10.1109/CBMS.2010.6042666
29. Glanz, K., Rimer, B. K., & Viswanath, K., (Eds). (2008). Health behavior and health education:Theory, research, and practice. San Francisco, CA:John Wiley & Sons.
30. Hedges, L. V., & Olkin, I., (1985). Statistical methods for meta-analysis. Orlando, FL:Academic.
31. Higgins, J. P., Thompson, S. G., Deeks, J. J., & Altman, D. G., (2003). Measuring inconsistency in meta-analyses. BMJ, 327 (7414), 557–560. doi:10.1136/bmj.327.7414.557
32. House, J. S., (1981). Work stress and social support. Reading, MA:Addison-Wesley.
33. Hughes, A., (2010). Using social media platforms to amplify public health message:An examination of principles and best practices. Retrieved from http://smexchange.ogilvypr.com/wp-content/uploads/2010/11/OW_SM_WhitePaper.pdf
34. Hunter, J. E., & Schmidt, F. L., (2004). Methods of meta-analysis:Correcting error and bias in research findings (2nd ed.). Thousand Oaks, CA:Sage.
35. Kohl, L. F., Crutzen, R., & de Vries, N. K., (2013). Online prevention aimed at lifestyle behaviors:A systematic review of reviews. Journal of Medical Internet Research, 15 (7), e146. doi:10.2196/jmir.2665
36. *Kuwata, S., Taniguchi, S. I., Kato, A., Inoue, K., Yamamoto, N., Ohkura, T., & Kondoh, H., (2010). Metaboli-Net:Online groupware system providing counseling guidance for patients with metabolic syndrome. Studies in Health Technology and Informatics, 156, 65–70.
37. Laranjo, L., Arguel, A., Neves, A. L., Gallagher, A. M., Kaplan, R., Mortimer, N., … Lau, A. Y., (2015). The influence of social networking sites on health behavior change:A systematic review and meta-analysis. Journal of the American Medical Informatics Association, 22 (1), 243–256.
38. *Livingston, J. D., Cianfrone, M., Korf-Uzan, K., & Coniglio, C., (2014). Another time point, a different story:One year effects of a social media intervention on the attitudes of young people towards mental health issues. Social Psychiatry and Psychiatric Epidemiology, 49 (6), 985–990. doi:10.1007/s00127-013-0815-7
39. *Livingston, J. D., Tugwell, A., Korf-Uzan, K., Cianfrone, M., & Coniglio, C., (2013). Evaluation of a campaign to improve awareness and attitudes of young people towards mental health issues. Social Psychiatry and Psychiatric Epidemiology, 48 (6), 965–973. doi:10.1007/s00127-012-0617-3
40. Lustria, M., Brown, L., & Davis, R., (2007, November). 10 Years of consumer health informatics:What have we learned about how to design successful web-based interventions? Paper presented at the National Communication Association annual conference, Chicago, IL.
41. *Mackenzie, K., Goyder, E., & Eves, F., (2015). Acceptability and feasibility of a low-cost, theory-based and co-produced intervention to reduce workplace sitting time in desk-based university employees. BMC Public Health, 15 (1), 1–13. doi:10.1186/s12889-015-2635-z
42. *Maher, C., Ferguson, M., Vandelanotte, C., Plotnikoff, R., De Bourdeaudhuij, I., Thomas, S., … Olds, T. (2015). A web-based, social networking physical activity intervention for insufficiently active adults delivered via Facebook app:randomized controlled trial. Journal of Medical Internet Research, 17 (7), e174. doi:10.2196/jmir.4086
43. Maher, C. A., Lewis, L. K., Ferrar, K., Marshall, S., De Bourdeaudhuij, I., & Vandelanotte, C., (2014). Are health behavior change interventions that use online social networks effective? A systematic review. Journal of Medical Internet Research, 16 (2), e40. doi:10.2196/jmir.2952
44. Maibach, E. W., Rothschild, M. L., & Novelli, W. D., (2002). Social marketing. In K., Glanz, B. K., Rimer, & F. M., Lewis (Eds.), Health behavior and health education (3rd ed.). San Francisco, CA:Jossey-Bass.
45. McGowan, B. S., Wasko, M., Vartabedian, B. S., Miller, R. S., Freiherr, D. D., & Abdolrasulnia, M., (2012). Understanding the factors that influence the adoption and meaningful use of social media by physicians to share medical information. Journal of Medical Internet Research, 14 (5), e117. doi:10.2196/jmir.2138
46. Morgan, A. J., Jorm, A. F., & Mackinnon, A. J., (2013). Internet-based recruitment to a depression prevention intervention:Lessons from the Mood Memos study. Journal of Medical Internet Research, 15 (2), e31. doi:10.2196/jmir.2262.
47. *Muntaner-Mas, A., Vidal-Conti, J., Borras, P. A., Ortega, F. B., & Palou, P., (2017). Effects of a Whatsapp-delivered physical activity intervention to enhance health-related physical fitness components and cardiovascular disease risk factors in older adults. Journal of Sports Medicine and Physical Fitness, 57 (1–2), 90–102. doi:10.23736/S0022-4707.16.05918-1
48. *Napolitano, M. A., Hayes, S., Bennett, G. G., Ives, A. K., & Foster, G. D. (2013). Using Facebook and text messaging to deliver a weight loss program to college students. Obesity, 21 (1), 25–31. doi:10.1038/oby.2012.107
49. Neiger, B. L., Thackeray, R., Van Wagenen, S. A., Hanson, C. L., West, J. H., Barnes, M. D., & Fagen, M. C., (2012). Use of social media in health promotion purposes, key performance indicators, and evaluation metrics. Health Promotion Practice, 13 (2), 159–164. doi:10.1177/1524839911433467
50. Noar, S. M., (2006). In pursuit of cumulative knowledge in health communication:The role of meta-analysis. Health Communication, 20 (2), 169–175. doi:10.1207/s15327027hc2002_8
51. Noar, S. M., Benac, C. N., & Harris, M. S., (2007). Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychological Bulletin, 133 (4), 673. doi:10.1037/0033-2909.133.4.673
52. *Pechmann, C., Pan, L., Delucchi, K., Lakon, C. M., & Prochaska, J. J., (2015). Development of a Twitter-based intervention for smoking cessation that encourages high-quality social media interactions via automessages. Journal of Medical Internet Research, 17, 2. doi:10.2196/jmir.3772
53. Pew Research Center. (2014). Social networking fact sheet. Retrieved from http://www.pewinternet.org/fact-sheets/social-networking-fact-sheet/
54. Poirier, J., & Cobb, N. K., (2012). Social influence as a driver of engagement in a web-based health intervention. Journal of Medical Internet Research, 14 (1), e36. doi:10.2196/jmir.1957
55. Prochaska, J. O., DiClemente, C. C., & Norcross, J. C., (1992). In search of how people change:Applications to addictive behaviors. American Psychologist, 47 (9), 1102. doi:10.1037/0003-066X.47.9.1102
56. *Ramo, D. E., Thrul, J., Chavez, K., Delucchi, K. L., & Prochaska, J. J., (2015). Feasibility and quit rates of the tobacco status project:A Facebook smoking cessation intervention for young adults. Journal of Medical Internet Research, 17 (12), e291. doi:10.2196/jmir.5209
57. Raudenbush, S. W., (2009). Analyzing effect sizes:Random-effects models. In B. S., Cooper, L. V., Hedges, & J. C., Valentine (Eds.), The handbook of research synthesis and meta-analysis (pp. 295–316). New York, NY:Russell Sage Foundation.
58. Richardson, A., Graham, A. L., Cobb, N., Xiao, H., Mushro, A., Abrams, D., & Vallone, D., (2013). Engagement promotes abstinence in a web-based cessation intervention:Cohort study. Journal of Medical Internet Research, 15 (1), e14. doi:10.2196/jmir.2277
59. Rosenthal, R., (1991). Meta-analytic procedures for social research (Rev. ed.). Newbury Park, CA:Sage.
60. *Rote, A. E., Klos, L. A., Brondino, M. J., Harley, A. E., & Swartz, A. M., (2015). The efficacy of a walking intervention using social media to increase physical activity:A randomized trial. Journal of Physical Activity & Health, 12 (6 Suppl 1), S18–25. doi:10.1123/jpah.2014-0279
61. Schmidt, F. L., & Hunter, J. E., (1999). Comparison of three meta-analysis methods revisited:An analysis of Johnson, Mullen, and Salas (1995). Journal of Applied Psychology, 84 (1), 144–148. doi:10.1037/0021-9010.84.1.144
62. Snyder, L. B., Hamilton, M. A., Mitchell, E. W., Kiwanuka-Tondo, J., Fleming-Milici, F., & Proctor, D., (2004). A meta-analysis of the effect of mediated health communication campaigns on behavior change in the United States. Journal of Health Communication, 9(S1), 71–96. doi:10.1080/10810730490271548
63. Statista (2016). Leading social networks worldwide as of April 2016, ranked by number of active users (in millions). Retrieved from http://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/
64. Stephenson, M. T., Holbert, R. L., & Zimmerman, R. S., (2006). On the use of structural equation modeling in health communication research. Health Communication, 20 (2), 159–167. doi:10.1207/s15327027hc2002_7
65. Stoddard, J., Augustson, E., & Moser, R., (2008). Effect of adding a virtual community (bulletin board) to smokefree. gov:Randomized controlled trial. Journal of Medical Internet Research, 10 (5), e53. doi:10.2196/jmir.1124
66. Sutton, A. J., (2009). Publication bias. In B. S., Cooper, L. V., Hedges, & J. C., Valentine (Eds.), The handbook of research synthesis and meta-analysis (pp. 435–452). New York, NY:Russell Sage Foundation.
67. Thackeray, R., Neiger, B. L., Hanson, C. L., & McKenzie, J. F., (2008). Enhancing promotional strategies within social marketing programs:Use of Web 2.0 social media. Health Promotion Practice, 9 (4), 338–343. doi:10.1177/1524839908325335
68. Thalheimer, W., & Cook, S., (2002). How to calculate effect sizes from published research:A simplified methodology. Work-Learning Research, 1–9. Retrieved from http://www.bwgriffin.com/gsu/courses/edur9131/content/Effect_Sizes_pdf5.pdf
69. *Turner-McGrievy, G., & Tate, D., (2011). Tweets, Apps, and Pods:Results of the 6-month mobile Pounds Off Digitally (Mobile POD) randomized weight-loss intervention among adults. Journal of Medical Internet Research, 13 (4), e120. doi:10.2196/jmir.1841.
70. *Valle, C. G., Tate, D. F., Mayer, D. K., Allicock, M., & Cai, J., (2013). A randomized trial of a Facebook-based physical activity intervention for young adult cancer survivors. Journal of Cancer Survivorship, 7 (3), 355–368. doi:10.1007/s11764-013-0279-5
71. Van Mierlo, T., Voci, S., Lee, S., Fournier, R., & Selby, P., (2012). Superusers in social networks for smoking cessation:Analysis of demographic characteristics and posting behavior from the Canadian Cancer Society’s smokers’ helpline online and StopSmokingCenter. net. Journal of Medical Internet Research, 14 (3), e66. doi:10.2196/jmir.1854
72. Vyas, A. N., Landry, M., Schnider, M., Rojas, A. M., & Wood, S. F., (2012). Public health interventions:Reaching Latino adolescents via short message service and social media. Journal of Medical Internet Research, 14 (4), e99. doi:10.2196/jmir.1854
73. Yang, Q., & Beatty, M. (2016). A meta-analytic review of health information credibility:Belief in physicians or belief in peers? Health Information Management Journal, 45 (2), 80–89. doi:10.1177/1833358316639432
74. *Young, S. D., Cumberland, W. G., Nianogo, R., Menacho, L. A., Galea, J. T., & Coates, T., (2015). The HOPE social media intervention for global HIV prevention in Peru:A cluster randomised controlled trial. The Lancet HIV, 2 (1), e27–e32. doi:10.1016/S2352-3018(14)00006-X
75. *Zhang, J., Brackbill, D., Yang, S., & Centola, D., (2015). Efficacy and causal mechanism of an online social media intervention to increase physical activity:Results of a randomized controlled trial. Preventive Medicine Reports, 2, 651–657. doi:10.1016/j.pmedr.2015.08.005