Abstract
Mass media have changed dramatically over the past 25 years, yet they still remain an important channel for substance use prevention messages. Unfortunately, the large mass media substance use prevention campaigns, especially the National Youth Anti-drug Media Campaign, have not been found to be generally effective. Inadequacy of current theories of behavior change, creation of reactance and norms of psychoactive substance use, and failure to target youth at the right age have been offered as explanations. Exposure to messaging is an important issue for campaigns. High exposure to substance use prevention campaigns was often achieved and associated with effectiveness in some studies. Online and social media have added new media platforms for substance use campaigns. Evaluations of web-based interventions show some promise for substance use prevention, although the effects appear modest. Less is known about the effectiveness of social media in substance use campaigns, especially the influence of user-generated content. Many challenges to deploying social media in substance use prevention exist deserving further research, including theory development, measures of effects, selection of appropriate social media formats, and user engagement. Social media also can promote substance use through user-generated content and commercial advertising. Furthermore, monitoring social media can provide insights into new substance use trends that should be addressed in future mass media campaigns.
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References
Albert, R., Jeong, H., & Barabási, A.-L. (2000). Error and attack tolerance of complex networks. Nature, 406(6794), 378–382.
Allara, E., Ferri, M., Bo, A., Gasparrini, A., & Faggiano, F. (2015). Are mass-media campaigns effective in preventing drug use? A Cochrane systematic review and meta-analysis. BMJ Open, 5(9), e007449.
Anderson, D. M. (2010). Does information matter? The effect of the Meth Project on meth use among youths. Journal of Health Economics, 29(5), 732–742.
Barry, A. E., Johnson, E., Rabre, A., Darville, G., Donovan, K. M., & Efunbumi, O. (2015). Underage access to online alcohol marketing content: A YouTube case study. Alcohol and Alcoholism, 50(1), 89–94.
Beaudoin, C. E., & Thorson, E. (2004). Testing the cognitive mediation model: The roles of news reliance and three gratifications sought. Communication Research, 31(4), 446–471.
Bellis, M. A., Hughes, K., & Lowey, H. (2002). Healthy nightclubs and recreational substance use. From a harm minimisation to a healthy settings approach. Addictive Behaviors, 27(6), 1025–1035.
Bellis, M. A., Hughes, K., Thomson, R., & Bennett, A. (2004). Sexual behaviour of young people in international tourist resorts. Sexually Transmitted Infections, 80(1), 43–47.
Bellis, M. A., Hughes, K. E., Dillon, P., Copeland, J., & Gates, P. (2007). Effects of backpacking holidays in Australia on alcohol, tobacco and drug use of UK residents. BMC Public Health, 7, 1.
Benotsch, E. G., Nettles, C. D., Wong, F., Redmann, J., Boschini, J., Pinkerton, S. D., Ragsdale K., Mikytuck, J. J. (2007). Sexual risk behavior in men attending Mardi Gras celebrations in New Orleans, Louisiana. Journal of Community Health, 32(5), 343–356.
Bierut, T., Krauss, M. J., Sowles, S. J., & Cavazos-Rehg, P. A. (2016). Exploring marijuana advertising on Weedmaps, a popular online directory. Prevention Science, 18, 183–192.
Bryant, M. (2011). 20 years ago today, the World Wide Web opened to the public. Insider. Retrieved from http://thenextweb.com/insider/2011/08/06/20-years-ago-today-the-world-wide-web-opened-to-the-public/
Burke-Garcia, A., & Scally, G. (2014). Trending now: Future directions in digital media for the public health sector. Journal of Public Health, 36(4), 527–534.
Cabrera-Nguyen, E. P., Cavazos-Rehg, P., Krauss, M., Bierut, L. J., & Moreno, M. A. (2016). Young adults’ exposure to alcohol-and marijuana-related content on Twitter. Journal of Studies on Alcohol and Drugs, 77(2), 349–353.
Carpenter, C. S., & Pechmann, C. (2011). Exposure to the Above the Influence antidrug advertisements and adolescent marijuana use in the United States, 2006–2008. American Journal of Public Health, 101(5), 948–954.
Casacolumbia. (2011). National survey of American attitudes on substance abuse XVI: Teens and parents. Retrieved from http://www.casacolumbia.org/addiction-research/reports/national-survey-american-attitudes-substance-abuse-teens-parents-2011
Casacolumbia. (2012). National survey on American attitudes on substance abuse XVII: Teens. Retrieved from http://www.casacolumbia.org/addiction-research/reports/national-survey-american-attitudes-substance-abuse-teens-2012
Cavazos-Rehg, P., Krauss, M., Grucza, R., & Bierut, L. (2014). Characterizing the followers and tweets of a marijuana-focused Twitter handle. Journal of Medical Internet Research, 16(6), e157.
Chou, W. Y. S., Prestin, A., Lyons, C., & Wen, K. Y. (2013). Web 2.0 for health promotion: Reviewing the current evidence. American Journal of Public Health, 103(1), e9–e18.
Cloud, R. N., & Peacock, P. L. (2001). Internet screening and interventions for problem drinking: Results from the www.carebetter.com. Alcoholism Treatment Quarterly, 19(2), 23–44.
Cohen, J. (2001). Defining identification: A theoretical look at identification of audiences with media characters. Mass Communication and Society, 4(3), 245–264.
Cole-Lewis, H., Perotte, A., Galica, K., Dreyer, L., Griffith, C., Schwarz, M., … Augustson, E. (2016). Social network behavior and engagement within a smoking cessation Facebook page. Journal of Medical Internet Research, 18(8), e205.
Cunningham, J. A., Humphreys, K., & Koski-Jännes, A. (2000). Providing personalized assessment feedback for problem drinking on the Internet: A pilot project. Journal of Studies on Alcohol, 61(6), 794–798.
David, C., Cappella, J. N., & Fishbein, M. (2006). The social diffusion of influence among adolescents: Group interaction in a chat room environment about antidrug advertisements. Communication Theory, 16(1), 118–140.
Diao, F., & Sundar, S. S. (2004). Orienting response and memory for web advertisements: Exploring effects of pop-up window and animation. Communication Research, 31(5), 537–567.
Egan, K. G., & Moreno, M. A. (2011). Alcohol references on undergraduate males' Facebook profiles. American Journal of Men's Health, 5(5), 413–420.
Eiser, J., & Ford, N. (1995). Sexual relationships on holiday: A case of situational disinhibition. Journal of Social and Personal Relationships, 12(3), 323–339.
Erceg-Hurn, D. M. (2008). Drugs, money, and graphic ads: A critical review of the Montana Meth Project. Prevention Science, 9(4), 256–263.
Erickson, B. H. (1988). The relational basis of attitudes. In B. Wellman & S. D. Berkowitz (Eds.), Social structures: A network approach. (pp. 99–121). Cambridge: Cambridge University Press.
Evans, W. D. (2016). Social marketing research for global public health. New York, NY: Oxford University Press.
Eveland, W. P. (2001). The cognitive mediation model of learning from the news. Communication Research, 28(5), 571–601.
Eveland, W. P., & Dunwoody, S. (2002). An investigation of elaboration and selective scanning as mediators of learning from the web versus print. Journal of Broadcasting & Electronic Media, 46(1), 34–53.
Eysenbach, G. (2009). Infodemiology and infoveillance: Framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet. Journal of Medical Internet Research, 11(1), e11.
Fang, L., & Schinke, S. P. (2013). Two-year outcomes of a randomized, family-based substance use prevention trial for Asian American adolescent girls. Psychology of Addictive Behaviors, 27(3), 788–798.
Farrelly, M. C., Davis, K. C., Haviland, M. L., Messeri, P., & Healton, C. G. (2005). Evidence of a dose-response relationship between “truth” antismoking ads and youth smoking prevalence. American Journal of Public Health, 95(3), 425–431.
Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7(2), 117–140.
Flaudias, V., de Chazeron, I., Zerhouni, O., Boudesseul, J., Begue, L., Bouthier, R., … Brousse, G. (2015). Preventing alcohol abuse through social networking sites: A first assessment of a two-year ecological approach. Journal of Medical Internet Research, 17(12), e278.
GfK Inc. (2015). The common sense census. Retrieved from https://www.commonsensemedia.org/the-common-sense-census-media-use-by-tweens-and-teens-infographic#
Green, M. C. (2006). Narratives and cancer communication. The Journal of Communication, 56(1), S163–S183.
Green, M. C., & Brock, T. C. (2000). The role of transportation in the persuasiveness of public narratives. Journal of Personality and Social Psychology, 79(5), 701–721.
Green, M. C., & Brock, T. C. (2002). In the mind’s eye: Transportation-imagery model of narrative persuasion. In M. C. Green, J. J. Strange, & T. C. Brock (Eds.), Narrative impact: Social and cognitive foundations (pp. 315–341). Mahwah, NJ: Erlbaum.
Gupta, H., Pettigrew, S., Lam, T., & Tait, R. J. (2016). A systematic review of the impact of exposure to internet-based alcohol-related content on young people’s alcohol use behaviours. Alcohol and Alcoholism, 51, 763–771. https://doi.org/10.1093/alcalc/agw050
Hanson, C. L., Cannon, B., Burton, S., & Giraud-Carrier, C. (2013). An exploration of social circles and prescription drug abuse through Twitter. Journal of Medical Internet Research, 15(9), e189.
Hawkins, R. P., & Pingree, S. (1986). Activity in the effects of television on children. In J. Bryant & D. Zillman (Eds.), Perspectives on media effects (pp. 233–250). Hillsdale, NJ: Lawrence Erlbaum and Associates.
Hornik, R., & Jacobsohn, L. (2007). The best laid plans: Disappointments of the National Youth Anti-Drug Media Campaign. LDI Issue Brief, 14(2), 1–4.
Hornik, R., Jacobsohn, L., Orwin, R., Piesse, A., & Kalton, G. (2008). Effects of the national youth anti-drug media campaign on youths. American Journal of Public Health, 98(12), 2229–2236.
Huang, J., Kornfield, R., & Emery, S. L. (2016). 100 million views of electronic cigarette YouTube videos and counting: Quantification, content evaluation, and engagement levels of videos. Journal of Medical Internet Research, 18(3), e67.
Hughes, K., Bellis, M. A., Calafat, A., Juan, M., Schnitzer, S., & Anderson, Z. (2008). Predictors of violence in young tourists: A comparative study of British, German and Spanish holidaymakers. European Journal of Public Health, 18(6), 569–574.
Internet User Demographics. (2014). Retrieved from http://www.pewinternet.org/data-trend/internet-use/latest-stats/
Jernigan, D. H., & Rushman, A. E. (2014). Measuring youth exposure to alcohol marketing on social networking sites: Challenges and prospects. Journal of Public Health Policy, 35(1), 91–104.
Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54(3), 241–251.
Kim, A., Hansen, H., Duke, J., Davis, K., Alexander, R., Rowland, A., & Mitchko, J. (2016). Does digital ad exposure influence information-seeking behavior online? Evidence from the 2012 Tips From Former Smokers National Tobacco Prevention Campaign. Journal of Medical Internet Research, 18(3), e64.
Kim, J., & Rubin, A. M. (1997). The variable of audience activity on media effects. Communication Research, 24(2), 107–135.
Korda, H., & Itani, Z. (2011). Harnessing social media for health promotion and behavior change. Health Promotion Practice, 14(1), 15–23.
Kreuter, M. W., Green, M. C., Cappella, J. N., Slater, M. D., Wise, M. E., Storey, D., … Woolley, S. (2007). Narrative communication in cancer prevention and control: A framework to guide research and application. Annals of Behavioral Medicine, 33(3), 221–235.
Lang, A. (2000). The limited capacity model of mediated message processing. The Journal of Communication, 50(1), 46–67.
Lang, A., Borse, J., Wise, K., & David, P. (2002). Captured by the world wide web: Orienting to structural and content features of computer-presented information. Communication Research, 29(3), 215–245.
Lenhart, A. (2015, April 9). Teens, social media & technology overview 2015. Retrieved from http://www.pewinternet.org/2015/04/09/teens-social-media-technology-2015/
Lenz, E. R. (1984). Information seeking: A component of client decisions and health behavior. Advances in Nursing Science, 13(6), 59–72.
Magura, S. (2012). Failure of intervention or failure of evaluation: A meta-evaluation of the National Youth Anti-Drug Media Campaign evaluation. Substance Use & Misuse, 47(13–14), 1414–1420.
McNaughton, E. C., Coplan, P. M., Black, R. A., Weber, S. E., Chilcoat, H. D., & Butler, S. F. (2014). Monitoring of internet forums to evaluate reactions to the introduction of reformulated OxyContin to deter abuse. Journal of Medical Internet Research, 16(5), e119.
McQueen, A., Kreuter, M. W., Kalesan, B., & Alcaraz, K. I. (2011). Understanding narrative effects: The impact of breast cancer survivor stories on message processing, attitudes, and beliefs among African American women. Health Psychology, 30(6), 674–682.
Miller, W. R., Toscova, R. T., Miller, J. H., & Sanchez, V. (2000). A theory-based motivational approach for reducing alcohol/drug problems in college. Health Education & Behavior, 27(6), 744–759.
Moreno, M. A., Kota, R., Schoohs, S., & Whitehill, J. M. (2013). The Facebook influence model: A concept mapping approach. Cyberpsychology, Behavior, and Social Networking, 16(7), 504–511.
Moreno, M. A., & Whitehill, J. M. (2014). Influence of social media on alcohol use in adolescents and young adults. Alcohol Research: Current Reviews, 36(1), 91–100.
Mundt, M. P. (2011). The impact of peer social networks on adolescent alcohol use initiation. Academic Pediatrics, 11(5), 414–421.
Nash, C. M., Vickerman, K. A., Kellogg, E. S., & Zbikowski, S. M. (2015). Utilization of a Web-based vs integrated phone/Web cessation program among 140,000 tobacco users: An evaluation across 10 free state quitlines. Journal of Medical Internet Research, 17(2), e36.
Newton, R. L., Jr., Han, H., Stewart, T. M., Ryan, D. H., & Williamson, D. A. (2011). Efficacy of a pilot Internet-based weight management program (H.E.A.L.T.H.) and longitudinal physical fitness data in Army Reserve soldiers. Journal of Diabetes Science and Technology, 5(5), 1255–1262.
Nicholls, J. (2012). Everyday, everywhere: Alcohol marketing and social media—Current trends. Alcohol and Alcoholism, 47(4), 486–493.
Pagoto, S., Waring, M. E., May, C. N., Ding, E. Y., Kunz, W. H., Hayes, R., & Oleski, J. L. (2016). Adapting behavioral interventions for social media delivery. Journal of Medical Internet Research, 18(1), e24.
Palmgreen, P., Donohew, L., Lorch, E. P., Hoyle, R. H., & Stephenson, M. T. (2001). Television campaigns and adolescent marijuana use: Tests of sensation seeking targeting. American Journal of Public Health, 91(2), 292–296.
Palmgreen, P., Lorch, E. P., Stephenson, M. T., Hoyle, R. H., & Donohew, L. (2007). Effects of the Office of National Drug Control Policy’s Marijuana Initiative Campaign on high-sensation-seeking adolescents. American Journal of Public Health, 97(9), 1644–1649.
Perrin, A. (2015, October 8). Social media usage 2005–2015. Retrieved from http://www.pewinternet.org/2015/10/08/social-networking-usage-2005-2015
Pescosolido, B. (1992). Beyond rational choice: The social dynamics of how people seek help. American Journal of Sociology, 97(4), 1096–1138.
Petraglia, J. (2007). Narrative intervention in behavior and public health. Journal of Health Communication, 12(5), 493–505.
Portnoy, D. B., Scott-Sheldon, L. A. J., Johnson, B. T., & Carey, M. P. (2008). Computer-delivered interventions for health promotion and behavioral risk reduction: A meta-analysis of 75 randomized controlled trials, 1988–2007. Preventive Medicine, 47(1), 3–16.
Ragsdale, K., Difranceisco, W., & Pinkerton, S. D. (2006). Where the boys are: Sexual expectations and behaviour among young women on holiday. Culture, Health & Sexuality, 8(2), 85–98.
Reach of leading social media and networking sites used by teenagers and young adults in the United States as of February 2016. 2016. Retrieved from https://www.statista.com/statistics/199242/social-media-and-networking-sites-used-by-us-teenagers/
Reagan, J., & Collins, J. (1987). Sources of health care information in two small communities. The Journalism Quarterly, 64(3), 560–563.
Reinhart, A. M., & Feeley, T. H. (2007). Comparing the persuasive effects of narrative versus statistical messages: A meta-analytic review. Paper presented at the 2007 NCA Annual Convention Communicating Worldviews: Faith-Intellect-Ethics, Chicago, IL. Retrieved from http://www.allacademic.com/meta/p194682_index.html
Rideout, V. (2013). Zero to eight: children’s media use in America 2013. San Francisco, CA: Common Sense Media Retrieved from https://www.commonsensemedia.org/research/zero-to-eight-childrens-media-use-in-america-2013
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.
Rooke, S., Copeland, J., Norberg, M., Hine, D., & McCambridge, J. (2013). Effectiveness of a self-guided web-based cannabis treatment program: Randomized controlled trial. Journal of Medical Internet Research, 15(2), e26.
Rudie, M. (2016). Results from the FY2015 NAQC Annual Survey of Quitlines. Retrieved from http://c.ymcdn.com/sites/www.naquitline.org/resource/resmgr/2015_Survey/finalweb2242016NAQCFY2015.pdf
Rus, H. M., & Cameron, L. D. (2016). Health communication in social media: Message features predicting user engagement on diabetes-related Facebook pages. Annals of Behavioral Medicine, 50(5), 678–689.
Schaub, M. P., Haug, S., Wenger, A., Berg, O., Sullivan, R., Beck, T., & Stark, L. (2013). Can reduce-the effects of chat-counseling and web-based self-help, web-based self-help alone and a waiting list control program on cannabis use in problematic cannabis users: A randomized controlled trial. BMC Psychiatry, 13(1), 305.
Scheier, L. M., Grenard, J. L., & Holtz, K. D. (2011). An empirical assessment of the Above the Influence advertising campaign. Journal of Drug Education, 41(4), 431–461.
Siebel, T. M., & Mange, S. A. (2009). The Montana meth project: Unselling a dangerous drug. Stanford Law and Policy Review, 20(2), 405–416.
Slater, M. D., Buller, D. B., Waters, E., Archibeque, M., & LeBlanc, M. (2003). A test of conversational and testimonial messages versus didactic presentations of nutrition information. Journal of Nutrition Education and Behavior, 35(5), 255–259.
Slater, M. D., Kelly, K. J., Edwards, R. W., Thurman, P. J., Plested, B. A., Keefe, T. J., … Henry, K. L. (2006). Combining in-school and community-based media efforts: Reducing marijuana and alcohol uptake among younger adolescents. Health Education Research, 21(1), 157–167.
Slater, M. D., Kelly, K. J., Lawrence, F. R., Stanley, L. R., & Comello, M. L. G. (2011). Assessing media campaigns linking marijuana non-use with autonomy and aspirations: “Be Under Your Own Influence” and ONDCP’s “Above the Influence”. Prevention Science, 12(1), 12–22.
Stephenson, M. T. (2003). Mass media strategies targeting high sensation seekers: What works and why. American Journal of Health Behavior, 27(3), S233–S238.
Suls, J. M., & Miller, R. L. (1977). Social comparison processes. New York, NY: Hemisphere.
Tait, R. J., McKetin, R., Kay-Lambkin, F., Carron-Arthur, B., Bennett, A., Bennett, K., … Griffiths, K. M. (2015). Six-month outcomes of a web-based intervention for users of amphetamine-type stimulants: Randomized controlled trial. Journal of Medical Internet Research, 17(4), e105.
Tait, R. J., Spijkerman, R., & Riper, H. (2013). Internet and computer based interventions for cannabis use: A meta-analysis. Drug and Alcohol Dependence, 133(2), 295–304.
Three technology revolutions. (2012). Retrieved from http://pewinternet.org/Trend-Data-(Adults)/Whos-Online.aspx
The Total Audience Report: Q1 2016. (2016). Retrieved from http://www.nielsen.com/us/en/insights/reports/2016/the-total-audience-report-q1-2016.html
Turner, J. (1982). Towards a cognitive redefinition of the social group. In H. Tajfel (Ed.), Social identity and intergroup relations (pp. 15–40). New York, NY: Academic Press.
Turner, R. H., & Killian, L. M. (1992). Collective behavior (3rd ed.). Englewood Cliffs, NJ: Prentice-Hall.
Tutenges, S., & Hesse, M. (2008). Patterns of binge drinking at an international nightlife resort. Alcohol and Alcoholism, 43(5), 595–599.
The U.S. Digital Consumer Report. (2014). Retrieved from http://www.nielsen.com/us/en/insights/reports/2014/the-us-digital-consumer-report.html
Walther, J. B., Pingree, S., Hawkins, R. P., & Buller, D. B. (2005). Attributes of interactive online health information systems. Journal of Medical Internet Research, 7(3), e33.
Walther, J. B., Tong, S. T., DeAndrea, D. C., Carr, C., & Van Der Heide, B. (2011). A juxtaposition of social influences: Web 2.0 and the interaction of mass, interpersonal, and peer sources online. In Z. Birchmeier, B. Dietz-Uhler, & G. Strasser (Eds.), Strategic uses of social technology: An interactive perspective of social psychology. Cambridge. Cambridge: Cambridge University Press.
Wang, Z., Walther, J. B., Pingree, S., & Hawkins, R. P. (2008). Health information, credibility, homophily, and influence via the internet: Web sites versus discussion groups. Health Communication, 23(4), 358–368.
Werb, D., Mills, E. J., DeBeck, K., Kerr, T., Montaner, J. S., & Wood, E. (2011). The effectiveness of anti-illicit-drug public-service announcements: A systematic review and meta-analysis. Journal of Epidemiology and Community Health, 65(10), 834–840.
White, A., Kavanagh, D., Stallman, H., Klein, B., Kay-Lambkin, F., Proudfoot, J., … Hines, E. (2010). Online alcohol interventions: A systematic review. Journal of Medical Internet Research, 12(5), e62.
Woodall, W. G. (1986). Information-processing theory and television news. In J. P. Robinson & M. R. Levy (Eds.)., The main source: Learning from television news (pp. 133–158). Beverly Hills, CA: Sage.
Woodall, W. G., Buller, D. B., Saba, L., Zimmerman, D., Waters, E., Hines, J. M., … Starling, R. (2007). Effect of emailed messages on return use of a nutrition education website and subsequent changes in dietary behavior. Journal of Medical Internet Research, 9(3), e27.
Zillman, D., & Bryant, J. (1985). Select exposure to communication. Hillsdale, NJ: Lawrence Erlbaum Associates.
Zillman, D., Chen, L., Knobloch, S., & Callison, C. (2004). Effects of lead framing on selective exposure to internet news reports. Communication Research, 31(1), 58–81.
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Buller, D.B., Walkosz, B.J., Gill Woodall, W. (2019). Use of Media and Social Media in the Prevention of Substance Use. In: Sloboda, Z., Petras, H., Robertson, E., Hingson, R. (eds) Prevention of Substance Use. Advances in Prevention Science. Springer, Cham. https://doi.org/10.1007/978-3-030-00627-3_20
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