Note: In 2013, Health Games Research completed its work. This web site is now an archive and will not be updated. Please visit the web site of the Center for Digital Games Research www.cdgr.ucsb.edu at UC Santa Barbara to find current information about health games and the broader field of digital games, and to use the Health Games Research online searchable database.

A Brief Overview of the Use of New Media in Health Campaigns and Interventions

By Ronald E. Rice, Ph.D.

Arthur N. Rupe Chair in the Social Effects of Mass Communication, Co-Director, Carsey-Wolf Center, Department of Communication, University of California, Santa Barbara, CA

December 2012

Health communication campaigns are purposive attempts to raise awareness of, improve knowledge about, or influence behavior related to, health issues in large audiences within a specified time period using an organized set of communication activities and featuring an array of mediated messages in multiple channels generally to produce noncommercial benefits to individuals and society (Atkin & Rice, 2013b).  Health interventions are typically more narrowly focused on specific programs or tools designed to achieve more individual-level goals, typically without mass media support, though some campaigns are referred to as interventions.  Campaigns use a wide variety of media technologies (TV, mobile phone, computer, video game console, radio, etc.), media formats (soap operas, text messages, games, social games, virtual worlds, web sites), and environments (home, school, work, play, waiting rooms) to encourage people to improve their health behavior.

Example health communication campaigns include Parents: The Anti-Drug (http://www.theantidrug.com/) which helps parents teach their children about the dangers of drug use; First Lady Michelle Obama's Let's Move! campaign (http://www.letsmove.gov/) to encourage children to be more active; the Hit Me With Your Flu Shot campaign (http://www.arkansasbluecross.com/employers/FluShot.aspx), which provides materials for workplace flu shot programs; the (RED) Campaign (http://www.joinred.com/), using consumption to provide 50% donations to the Global Fund to purchase anti-retroviral medicine for people with AIDS in Africa, suppress the disease, provide prevention education, and offer training for local doctors and midwives; and the Campaign to End Obesity (http://www.obesitycampaign.org/) which emphasizes policy change.

The research literature on health campaigns is rich and vast (Abroms & Maibach, 2008; Atkin & Wallack, 1990; Backer, et al., 1992; Cho, 2012; Edgar, et al., 2008; Green & Tones, 2010; Hornik, 2002; Maibach & Parrott, 1995; McKenzie, et al., 2012; Noar, 2006; Rice & Atkin, 2013b; Witte, et al., 2001). Design and implementation resources are diverse and widely accessible.  For example, The National Cancer Institute’s Making health communication programs work: A planner’s guide (http://www.cancer.gov/cancertopics/cancerlibrary/pinkbook) is extremely useful, organizing materials, strategies, cases, and sources on planning and strategy development; developing and pretesting concepts, messages, and materials; implementing the program including media promotion plans; and assessing effectiveness and making refinements. The non-profit Health Communication Materials Network (http://www.m-mc.org/hcmn/) lists an international network of professionals, international case studies, and media materials for public health campaigns. A fuller discussion would cover the main strategies and principles of communication campaigns, emphasizing the media dimension: campaign design framework, formative evaluation, dual approaches, types and mix of messages, message content and style, mass media and online/digital communication channels, quantitative media dissemination factors, and summative and process evaluation (Atkin & Rice, 2013a).

Each potential communication channel has a variety of advantages and disadvantages, often highly dependent on the underlying theoretical model, the goals of the campaign, the message content, and the nature of the subaudiences (including issues such as economic and cultural status, literacy, and location).  Here we briefly review online and interactive media for health campaigns and interventions. Public communication campaigns increasingly emphasize digital/online media technologies (Lieberman, 2013; Lustria, et al., 2009; Murero & Rice, 2006; Noar & Harrington, 2012; Parker & Thorson, 2009; Strecher, 2007). These new media offer the additional channel dimensions of interactivity, anonymity, narrowcasting, and tailoring, among others (Walther, et al., 2005). Interactivity uses the capabilities of computers to provide an ongoing engaging process, like a conversation, that takes advantage of this programmable technology's ability to request information from the user, monitor the user's choices and behaviors, and generate messages that respond specifically to those inputs." Anonymity is especially valuable for goal audiences dealing with highly private or stigmatizing topics.  Narrowcasting provides messages through specific media channels used by specific goal audiences (e.g., a cable channel or a twitter feed), thus allowing for segmentation and targeting.  Tailoring is a form of interactivity that involves using the underlying computing power of digital media to assess the individual's interests and abilities through the information they divulge (such as the user's demographic characteristics) and through the user's online performance, and then using that information to present individualized messages that are most personally relevant to the user and that best align with the user's skills and preferences (see Kreuter, et al., 2000).  Lustria et al.’s (2009) review identified 30 studies of computer-based tailoring interventions covering four general health areas: nutrition and diet, physical activity, alcoholism, and smoking cessation, most emphasizing risk prevention and health maintenance. Noar, et al. (2007) found that studies basing tailoring on stages of change (identified by the trans-theoretical model which argues that people are in different stages of readiness for change, so messages must be designed accordingly), or self-efficacy (one’s perception of their ability to accomplish the change or the behavior), were significantly more effective than those campaigns that did not.

The Internet in general is a major source for online health information, support, discussion, therapy, support, prescriptions, and access to physicians (Murero & Rice, 2006; Rice, 2006). Websites can provide the primary infrastructure for an integrated multi-media campaign. An effective example is the CDC’s national VERB campaign designed to promote exercise among pre-teens; this campaign attained wide-scale engagement (based on a hierarchy-of-effects framework) in website activities (Bauman et al., 2008; Berkowitz et al., 2008). A meta-analysis (statistically analyzing and comparing results from a large number of studies; for rigorous examples analyzing computer-based health interventions, see Cugelman et al., 2011, and Rains & Young, 2009) comparing web-based to non-web-based interventions in 22 articles involving nearly 12,000 participants found improved health knowledge and/or behavioral outcomes in all but one of the studies (Wantland, et al., 2004). Campaigns can utilize the Internet for low-cost message dissemination via online public service promos and spots and long-form video messages. For example, YouTube organ donation videos (with very supportive readers’ comments) stimulate actual organ donor registration (Tian, 2010). Paid health promotion ads on social media sites have greater potential for impact because of more prominent placement and more precise targeting.  Add to that the more interactive, networked, and collaborative capabilities of Web 2.0.  For example, one study found that these features, when used in health promotion ads online, increased user engagement and participation in the recommended health behaviors (Thackeray, et al., 2008).

Computer-delivered intervention (including tailoring) improves knowledge, attitudes, intentions, health behaviors and general health maintenance, social support, quality of life, and self-efficacy, across a variety of health domains (Cugelman, et al., 2011; Portnoy, et al., 2008; Rains & Young, 2009; Webb, et al., 2010). The interventions may apply a wide array of design features, media format, and implementation forms, such as user feedback as the basis for message intervention (i.e., tailoring), personalization, source characteristics (e.g., attractiveness, credibility, demographics), extent of asynchroneity, etc. Media formats may range from CD-Rom, USB stick, intranet, pedometers, websites, online support groups, instant messaging, and online chat, to single or multiple media.  Implementation forms included experiments with or without control groups, with or without human interaction single or multiple or sequential interventions, shorter or longer duration of the intervention, short-term or long-term impacts, individual or group settings.

Emails providing strategies, reminders, and links to online resources can complement mass media and workplace health campaigns (for example, a worksite campaign designed to increase physical activity and fruit/vegetable consumption; Franklin, et al., 2006). A meta-analysis concluded that health outcomes and care processes can by improved through complementing standard care with reminders, monitoring and managing diseases, and education via mobile phone voice and text messages (Krishna, et al., 2009). For example, a mobile-phone game for adolescents used a virtual pet’s positive and negative feedback about a player’s photos of their breakfast meals to improve their breakfast nutritional choices (Byrne, et al., 2012). Meta-analyses and reviews show significant effects of text messaging as a tool for health behavior change (Cole-Lewis, & Kershaw, 2010; Fjeldsoe, et al., 2009). Advantages include interactive and broadcast modes, convenient asynchroneity (e.g., being able to process and reply to the message later), less selective perception (people’s tendency to filter and interpret messages in ways that support their existing beliefs) due to short messages, tailoring, and both physical and economic accessibility.

Podcasts can provide relevant audio information (e.g., social support, persuasive messages, or news items) to motivated audiences at their convenience, and would be especially relevant to low-literacy or non-English speaking audiences. Blogs link users with similar information needs and concerns to share their views and experiences (Rains & Keating, 2011), while wikis support group collaboration. Twitter provides updates and protocol reminders to campaign-specific followers; however, tweets (like much Internet content) may include considerable misunderstandings or misuses of health information and medicines (Scanfeld, et al., 2010). Social bookmarking allows online communities to develop and share useful online resources (Thackeray, et al., 2008).

Voice response systems, interactive video, DVD and CD-ROM, mobile phones and computer games can be especially effective in reaching young people.  Game players can acquire skills and improve self-efficacy from role-playing, modeling, and vicarious experiences. More broadly, a review of 27 articles on 25 video games shows a positive impact of video game interventions on health behaviors such as chronic disease management, exercise, and diet (Baranowski, et al., 2008).  Lieberman (2006, 2012, 2013) recommends that health videogames incorporate compelling health-related challenges and goals, support information seeking, use genres and technologies that appeal to the target user group, involve learning-by-doing in the experiential environment of a videogame, and facilitate social interaction. Peng (2009) provides a very impressive example of a complete design-through-evaluation of a computer game (the RightWay Café) which taught young adults, through role playing, about healthy eating, weight management, self-efficacy, health eating benefits, and intention to follow a healthy diet (Peng, 2009).  Guided by several theories, the game design applied structural features such as interactive tailoring, role playing, fun, and branching (thus tailored) narrative to a simulation of a reality TV show, where the competition was based on managing one’s daily eating choices.  The game had significant  positive effects, over-time, and compared to a control group, on all outcomes except reducing perceived barriers (obstacles to performing the advocated behaviors such as lack of awareness about healthy food choices, perceptions of higher cost and lower taste, difficult access or inconvenience, and negative group norms about eating choices).

As more campaigns implement online components, designers are becoming more attuned to website and online credibility (e.g., positive trust, authority, and evaluation of online sources, media and messages) (Metzger, et al., 2003). In addition to traditional audience ratings and circulation data, online designers and evaluators must use newer sources for identifying goal audiences, their media usage and thus channels for communicating the campaign messages or interventions, and for evaluating the process and outcomes. These resources include social media links, likes, followers or retweets (Alexa Internet, Google analytics, Twitalyzer), Email prompts, participant visits (number, duration, and pattern of use over time), Web page viewing (number of views, types of pages viewed, and Web forum postings), and inward and outward links (Danaher, et al., 2006). For guidelines on using social media (blogs, video-sharing, mobile applications, RSS feeds, facebook, twitter, buttons and badges, e-cards, text messaging, widgets) for health campaign interventions, see Centers for Disease Control and Prevention (http://www.cdc.gov/healthcommunication/ToolsTemplates/index.html).

Portions adapted from Atkin and Rice (2013a).

References

Atkin, C. K. & Rice, R. E. (2013a). Strategies and principles for using mass, online, and mobile media in health communication campaigns. In K. Kim, A. Singhal, & G. Kreps (Eds.), Global health communication strategies in the 21st century: Design, implementation, and evaluation. NY: Peter Lang.

Atkin, C. K. & Rice, R. E. (2013b). Theory and principles of public communication campaigns. In R. E. Rice & C. K. Atkin (Eds.), Public communication campaigns (4th ed., Chapter 1, pp. 3-19). Thousand Oaks, CA: Sage.

Atkin, C. K. & Wallack, L. (Eds.) (1990). Mass communication and public health: Com­plexities and conflicts. Newbury Park, CA: Sage.

Backer, T., Rogers, E., & Sopory, P. (1992). Designing health communication campaigns: What works? Newbury Park, CA: Sage.

Baranowski, T., Buday, R., Thompson, D. I., & Baranowski, J. (2008). Playing for real: Video games and stories for health-related behavior change. American Journal of Preventive Medicine, 34(1), 74-82.

Bauman, A., Bowles, H. R., Huhman, M., Heitzler, C. D., Owen, B., Smith, B., & Reger-Nash, B. (2008). Testing a Hierarchy-of-Effects model: Pathways from awareness to outcomes in the VERB™ campaign 2002-2003. American Journal of Preventive Medicine, 34(6), S249-S256.

Berkowitz, J., Huhman, M., Heitzler, C., Potter, L., Nolin, M., & Banspach, S. (2008). Overview of formative, process, and outcome evaluation methods used in the VERB™ campaign. American Journal of Preventive Medicine, 34(6), S222-S229.

Byrne, S., Gay, G., Pollack, J. P., Gonzales, A. Retelny, D., Lee, T., & Wasink, B. (2012). Caring for mobile phone-based virtual pets can influence youth eating behaviors. Journal of Children and Media, 6(1), 83-99.

Cho, H. (Ed.) (2012). Health communication message design: Theory and practice. Thousand Oaks, CA: Sage.

Cole-Lewis, H., & Kershaw, T. (2010). Text messaging as a tool for behavior change in disease prevention and management. Epidemiologic Reviews, 32(1), 56-69.

Cugelman, B., Thelwall, M., & Dawed, P. (2011).  Online interventions for social marketing health behavior change campaigns: A meta-analysis of psychological architectures and adherence factors. Journal of Medical Internet Research, 13(1), e17. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3221338/

Danaher, B. G., Boles, S. M., Akers, L., Gordon, J. S., & Severson, H. H. (2006).  Defining participant exposure measures in web-based health behavior change programs. Journal of Medical Internet Research, 8(3):e15 http://www.jmir.org/2006/3/e15/

Edgar, T. M., Noar, S. M., & Freimuth, V. S. (Eds.) (2008). Communication perspectives on HIV/AIDS for the 21st Century. New York: Lawrence Erlbaum.

Fjeldsoe, B. S., Marshall, A. L., & Miller, Y. D. (2009). Behavior change interventions delivered by mobile telephone short-message service. American Journal of Preventive Medicine, 36(2), 165-173.

Franklin, P. D., Rosenbaum, P. F., Carey, M. P., & Roizen, M. F. (2006). Using sequential email messages to promote health behaviors: Evidence of feasibility and reach in a worksite sample. Journal of Medical Internet Research, 8(1):e3 http://www.jmir.org/2006/1/e3/

Green, G., & Tones, K. (2010). Health promotion: Planning and strategies (2nd ed.). London: Sage.

Hornik, R. (Ed.) (2002). Public health communication: Evidence for behavior change. Mahwah, NJ: Lawrence Erlbaum Associates. 

Kreuter, M., Farrell, D., Olevitch, L., & Brennan, L. (2000). Tailoring health messages. Mahwah, NJ: Lawrence Erlbaum Associates.

Krishna, S., Boren, S. A., & Balas, E. A. (2009). Healthcare via cell phones: A systematic review. Telemedicine and e-Health, 15(3), 231-240.

Lieberman, D. A. (2006). What can we learn from playing interactive games? In P. Vorderer & J. Bryant (Eds.), Playing video games: Motives, responses, and consequences (pp. 379-397). Mahwah, NJ: Lawrence Erlbaum Associates.

Lieberman, D. A. (2012).  Digital games for health behavior change: Research, design, and future directions. In S. M. Noar & N.G. Harrington (Eds.), eHealth applications: Promising strategies for behavior change (pp. 110-127).  New York: Routledge.

Lieberman, D. A. (2013). Using interactive media in communication campaigns for children and adolescents. In R. E. Rice & C. K. Atkin (Eds.), Public communication campaigns (4th ed., pp. 273-287). Thousand Oaks, CA: Sage.

Lustria, M. L. A., Cortese, J., Noar, S. M., & Glueckauf, R. L. (2009).  Computer-tailored health interventions delivered over the web: Review and analysis of key components. Patient Education and Counseling, 74(2), 156-173.

Maibach, E., & Parrott, R. (Eds.) (1995). Designing health messages: Approaches from communication theory and public health practice. Newbury Park, CA: Sage.

McKenzie, J. F., Neiger, B. L., & Thackeray, R. (2012). Planning, implementing, and evaluating health promotion programs: A primer (6th ed.). San Francisco: Benjamin Cummings.

Metzger, M., Flanagin, A., Eyal, K., Lemus, D., & McCann, R. (2003).  Credibility for the 21st century: Integrating perspectives on source, message, and media credibility in the contemporary media environment.  In P. Kalbfleisch (Ed.), Communication yearbook 27 (pp. 293-335).   Mahwah, NJ: Lawrence Erlbaum.

Murero, M. & Rice, R. E. (Eds.) (2006).  The Internet and health care: Theory, research and practice.  Mahwah, NJ: Lawrence Erlbaum Associates.

Noar, S. M. (2006). A 10-year retrospective of research in health mass media campaigns: Where do we go from here? Journal of Health Communication, 11(1), 21-42.

Noar, S. M., & Harrington, N. G. (Eds.) (2012). eHealth applications: Promising strategies for behavior change. NY: Routledge.

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), 673-693. doi: 10.1037/0033-2909.133.4.673

Parker, J. C. & Thorson, E. (2009). Health communication in the new media landscape. NY: Springer Publishing Co.

Peng, W. (2009). Design and evaluation of a computer game to promote a healthy diet for young adults. Health Communication, 24, 115-127.

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.

Rains, S. A., & Keating, D. M. (2011). The social dimension of blogging about health: Health blogging, social support, and well-being. Communication Monographs, 78(4), 511-534.

Rains, S. A., & Young, V. (2009). A meta-analysis of research on formal computer-mediated support groups: Examining group characteristics and health outcomes. Human Communication Research, 35, 309-336.

Rice, R. E. (2006). Influences, usage, and outcomes of Internet health information searching: Multivariate results from the Pew surveys. International Journal of Medical Informatics, 75(1), 8-28.

Rice, R. E., & Atkin, C. K. (Eds.) (2013). Public communication campaigns (4th ed.). Sage, Thousand Oaks, CA.

Scanfeld, D., Scanfeld, V., & Larson, E. L. (2010).

Strecher, V. (2007). Internet methods for delivering behavioral and health-related interventions (eHealth). Annual Review of Clinical Psychology, 3, 53-76.

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.

Tian, Y. (2010). Organ donation on Web 2.0: Content and audience analysis of organ donation videos on YouTube. Health Communication, 25(3), 238-246.

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 http://www.jmir.org/2005/3/e33/

Wantland, D. J., Portillo, C. J., Holzemer, W. L., Slaughter, R., & McGhee, E. M. (2004). The effectiveness of web-based vs. non-web-based interventions: A meta-analysis of behavioral change outcomes. Journal of Medical Internet Research, 6(4,:e40 http://www.jmir.org/2004/4/e40/

Webb, T. L., Joseph, J., Yardley, L., & Michie, S. (2010). Using the Internet to promote health behavior change: A systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. Journal of Medical Internet Research, 12(1):e4. http://www.jmir.org/2010/1/e4

Witte, K., Meyer, G., & Martell, D. P. (2001). Effective health risk messages: A step-by-step guide.  Thousand Oaks, CA: Sage.