Technology-Based Health Promotion


Sheana Bull

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  • Dedication

    To my cherished husband, Pablo, with sincere acknowledgment of your unwavering support. (SB)

    To all those who have taught me—parents, teachers, husband, children, friends—with unending gratitude and my hope of passing on some of the great gifts you gave me. (MM)


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    We live in an era with a constantly evolving and ever-expanding landscape of opportunities to communicate and interact with others using technology. Public health, health science, and social science professionals run the risk of being perceived as behind the times if they cannot incorporate technological tools in the promotion of health and prevention of disease.

    This book was written to orient health professionals to the enormous potential that exists in using technology for health promotion and disease prevention. At the same time, it is intended as a caution against an uncritical consideration of technology. We should carefully consider ways to maximize technology for health promotion without sacrificing the critical and effective traditional strategies that we know can be effective to help people choose and sustain healthy behaviors. The book was written because of the perception that there is a gap in textbook material for students in the health sciences; they have very good textbooks on how to design and implement program evaluation. Students can also access good textbooks on how to design and implement effective health promotion programs. However, there is little available to students in one textbook that focuses on ways to

    • consider innovations using technology in health promotion;
    • critically examine ethical considerations related to use of technology in health promotion;
    • learn both the best practices and the challenges associated with developing, implementing, and evaluating technology-based health programs, with special consideration for how to do this for diverse audiences; and
    • be exposed to case studies of technology-based programs using computer kiosks, the Internet, and mobile phones.

    In Chapter 1, students and readers are introduced to a history of the use of technology for health promotion, as well as technology-based strategies and programs that have been developed related to numerous health outcomes. Chapter 2 offers an important consideration of ethics and their relationship to technology; just because we can do something technologically doesn't mean we should. The considerations for this chapter allow the reader to explore some unique issues that arise when using technology for health promotion. Chapter 3 focuses on how to develop a technology-based health promotion program, and focuses specifically on program development that is appropriate for diverse target audiences, disease conditions, and settings. In Chapter 4, the reader is introduced to issues and challenges that are specific to technology-based program implementation such as collection and management of data from large samples and using technology to communicate and follow up with program participants. Chapter 5 explores unique issues related to program evaluation using technology, including such important topics as making sure participants are who they say they are and harnessing the potential for sophisticated analyses given our opportunities to collect data from large samples via technology.

    Chapters 6 through 8 offer detailed case studies of technology-based health promotion using computer kiosks, the Internet, and mobile phones. These programs were designed to address heart disease, HIV, diabetes, and smoking and offer the reader a detailed description of program elements and technology-based features.

    In the Epilogue, the reader can consider the future of technology-based health promotion and the challenge related to being flexible enough to adopt new innovations as they emerge (such as using social networking sites for health promotion) while simultaneously taking the time to evaluate if we are reaching who we need to with messages and effective approaches to promote health.

    In each chapter the reader will find a resource section, which identifies additional reading and websites to explore. Readers can go to for regular updates to these resource lists. In addition, professors who assign this book for their undergraduate or graduate classes can access slide sets and notes that accompany the material presented in each chapter. Students and professors have exercises in most chapters that are designed for a more in-depth exploration of the material presented in each chapter.


    There are numerous people who have contributed to this book, and we owe them our sincere thanks and acknowledgment. First, many thanks to Erin Wright and Nora Lee, our research assistants, who helped edit, review tables, compile references, and track down permissions.

    We gratefully recognize the effort and work contributed by the many reviewers of this manuscript, and the constructive comments they offered to improve this work, including Eric G. Benotsch, Virginia Commonwealth University; David Daniel Bogumil, California State University, Northridge; Karen L. Carlson, The University of New Mexico; William R. Carpenter, University of North Carolina at Chapel Hill; S. Alan Fann, Emory University School of Medicine; Maria Gilson Sistrom, Oregon Health & Sciences University; Chanda Nicole Holsey, San Diego State University, Graduate School of Public Health; Jeffrey B. Kingree, Clemson University; Francesca M. Maresca, Rutgers University; Sheila M. Patterson, Cleveland State University; Roberta P. Pawlak, Edgewood College; Ralph Renger, University of Arizona; John G. Ryan, University of Miami Miller School of Medicine; Laurie Selz-Campbell, University of North Carolina at Chapel Hill; Manoj Sharma, University of Cincinnati; Jiunn-Jye (JJ) Sheu, University of Florida; Julie K. Suzuki-Crumly, University of Alabama at Birmingham; and Ken W. Watkins, University of South Carolina.

    Thank you also to all of the manuscript contributors—Anne Bowen, Russ Glasgow, Beau Gratzer, Deb Levine, Marguerita Lightfoot, Simon Rosser, Joel Selanikio and EpiSurveyor, and HSAGlobal. Your innovations and creative ideas offer wonderful examples for others interested in technology-based health promotion. We gratefully acknowledge Dr. John Douglas from the Centers for Disease Control and Prevention; Drs. Willo Pequegnat and Susannah Allison from the National Institute of Mental Health (NIMH); Dr. Patrice Desvigne-Nickens from the National Heart, Lung, and Blood Institute (NHLBI); and Dr. Jeanette Hosseini from the National Institute of Nursing Research (NINR) for their support as project officers and program directors.

    We acknowledge the help and inspiration of longtime collaborators and colleagues, Dr. Kees Rietmeijer, Dr. Rachel Kachur, and Mr. Stephan Adelson. Finally, the information offered here was generated in part with support from the following federally sponsored research grants: R01 MH63690 and MH63690S, R21 MH083318, HL079208, and R01NR010492.

    About the Authors

    Sheana Bull, PhD, MPH, is trained in public health and sociology and works as an associate professor with appointments in the Department of Community and Behavioral Health at the Colorado School of Public Health and in the Department of Health and Behavioral Sciences, both at the University of Colorado Denver. She has been researching the use of technology for health promotion for over a decade and has developed and tested numerous technology-based interventions to facilitate prevention of sexually transmitted infections, including HIV, and to promote improvements in physical activity and nutrition. Her work includes collaborations with researchers and public health experts in Colorado, Wyoming, California, Pennsylvania, Virginia, Kentucky, and Texas, and she is involved in technology-based research for HIV prevention in Uganda, East Africa. She has published over four dozen research articles related to public health and is nationally and internationally recognized as a leader and innovator in the field of technology-based health promotion.

    Mary McFarlane, PhD, was trained as a quantitative psychologist at the University of North Carolina at Chapel Hill. Since 1996, she has held positions in the Division of STD Prevention at the U.S. Centers for Disease Control and Prevention in Atlanta, Georgia. She originally served as a research behavioral scientist and is now the prevention partnerships coordinator, working to ensure that the field of public health continues to engage with partners in innovation, technology, communication, policy, and health promotion. She is widely published in the field of STD prevention and technology-based disease control and prevention, and continues to investigate new technologies and innovations for the advancement of public health.

  • Epilogue

    Review of the Unique and Beneficial Elements of all Technology-Based Health Promotion Programs

    Technology-based health promotion has tremendous promise, as could be inferred from the tremendous growth in the field over the past decade. Consider how quickly we have adopted computers, the Internet, and mobile phones—and you can imagine how much opportunity there is to integrate health promotion into our daily lives through technology.

    In Chapter 1 we offered specific detail on ways in which technology-based health promotion offers advantages over standard face-to-face health promotion. We reiterate these advantages, in summary, in Table 9.1.

    Table 9.1 Relative advantages offered by technology-based health promotion
    Advantage of technology-based health promotionDefinitionRelated references
    ReachBecause technology is available in so many places, via computer, Internet, and cell phone, there is opportunity to reach many more people with a health promotion program than you otherwise may be able to through clinical or institutional sites (e.g., schools).Bull, Gaglio, McKay, & Glasgow, 2005; Glasgow, Klesges, Dzewaltowski, Estabrooks, & Vogt, 2006; Glasgow et al., 2006, 2007
    ImpactWith greater reach, it is possible to see greater impact of program efficacy, even when effects are small—programs with small effects delivered to large numbers of people will have greater impact on disease outcomes than those with large effects that can reach only small numbers of people.Estabrooks & Gyurcsik, 2003; Glasgow et al., 2006; Gustafson et al., 2005; Heller & Dobson, 2000 Ironson et al., 2005; Joffe & Mindell, 2002
    Standardized program deliveryTechnology allows for uniformity in program delivery—for example, the same message, delivered in the same order using the same content, means programs aren't dependent on an individual staff member for program success.Glasgow et al., 1997; Prochaska, DiClemente, Velicer, & Rossi, 1993; Strecher et al., 1994; Taylor, Houston-Miller, Killen, & DeBusk, 1990
    TailoringResponses and messages can be tailored to individual needs using algorithms that generate preprogrammed responses. Tailoring can help make program messages more personally relevant (e.g., when a message is delivered by a role model that matches participant age, gender, or race) and more clinically relevant (e.g., by focusing on a behavior directly relevant for an individual).Clark et al., 2004; Etter, 2005; Gore-Felton et al., 2005; Kukafka, Lussier, Eng, Patel, & Cimino, 2002; Scholes et al., 2003; Smeets, Brug, & De, 2008; Strecher, Shiffman, & West, 2005
    InteractiveParticipants can respond to questions, post their own opinions, play games, and get engaged with technology.Booth, Nowson, & Matters, 2008; Glasgow, Bull, Piette, & Steiner, 2004; Glasgow, Christiansen, Smith, Stevens, & Toobert, 2008; King et al., 2004; Leeman-Castillo et al., 2007; Linke, Murray, Butler, & Wallace, 2007; Noar, Clark, Cole & Lustria, 2006; Rotondi, Sinkule, & Spring, 2005
    PrivateFor health promotion that is sensitive or personal (e.g., sexual health, addiction intervention) users can engage with program content without having to disclose sensitive information to a health educator or clinician.Bull, Pratte, Whitesell, & Rietmeijer, 2009; Turner et al., 1998
    AutonomyUsers in technology-based health promotion may be able to move around at will to various program elements and choose to engage with those they find most interesting or relevant.Pew Internet & American Life Project, 2000
    PortabilityTechnology is ubiquitous, and programs can be as well. Using cell phones and the Internet, it is possible to reach people in places and at times that haven't been possible before.Brendryen & Kraft, 2008; Cellular News, n.d.; Curioso & Kurth, 2007; Krishna, Boren, & Balas, 2009; Logan et al., 2007; Harris Interactive, 2008; Hurling et al., 2007;Ybarra & Bull, 2007
    Cost-effectivenessIf we can achieve all the other advantages described here, it may result in a substantial cost savings—by making programs reach more people, standardized and relevant, we could cut delivery costs.Boase, Horrigan, Wellman, & Rainie, 2006; Booth et al., 2008; Brendryen & Kraft, 2008; Bull et al., 2005; Cassell, Jackson, & Cheuvront, 1998; Feil, Glasgow, Boles, & McKay, 2000; Formica, Kabbara, Clark, & McAlindon, 2004; Glasgow et al., 2007
    Review of the Challenges of Technology-Based Health Promotion Programs

    It is critical to consider the challenges inherent in technology-based health promotion programs before implementing them. Just because you can use technology doesn't mean you should use it. Indeed, it may be argued that the seduction of technological advances that are intriguing, fun, or captivating may overshadow program decisions, and health promoters may make errors in developing programs without careful attention to the needs, desires, and practices of their target audience vis-à-vis technology.

    Although technology does offer many advantages in health promotion, there remain fundamental challenges to technology-based programs. These are also detailed in Chapter 1, and summarized here in Table 9.2.

    Table 9.2 Relative advantages offered by technology-based health promotion
    ChallengeDefinitionRelated references
    SamplingThere is no good sampling frame for users of the Internet or cell phones, so finding ways to generalize positive effects from a program to a larger population may be difficult.Pequegnat et al., 2007
    Confidentiality/securityConcerns abound related to computer security and data transfers over the Internet. While security systems are very sophisticated and can be employed in ways to substantially reduce breaches in confidentiality, this requires a level of technical expertise and oversight from information systems experts on projects.King & Miles, 1995
    Attention spanUsers may be accustomed to shorter periods of engagement with technology, so programs may need to achieve effects with less contact time.Ross, 2002
    Competing attentionAs the Internet continues to grow and the use of technology becomes more ubiquitous, we face ongoing challenges to competition for the attention of participants. Why would they want to participate in your health promotion program if they can be playing a fun game online?Lavoie & Pychyl, 2001
    Digital divideWhile shrinking, the digital divide still exists and persists. Program planners need to pay careful attention to delivering content using technology that is accessible, affordable, and familiar to their audience.Bernhardt, 2000
    ObsolescenceComputer technology will continue to evolve, and may do so rapidly. We need methods to quickly develop and test interventions so that our findings aren't obsolete by the time we generate them.Pequegnat et al., 2007
    Review of the Emerging Trends and Future Directions in Technology-Based Health Promotion Programs

    There are multiple technological advances that are regularly identified in the media and through peer-reviewed literature that have potential for advancing the field of health promotion. Trying to predict the next waves of technology is difficult at best, and to some extent, it is a questionable practice for public health interventions. Given that there is a digital divide between high-and low-income individuals, and considering that the majority of public health messages are aimed at people of reduced income, it is not likely that the target audience for many messages will be the early adopters of new technology. The exception to this rule is adolescents, who are the primary target audience of most new communications technology and advertising. Even in this case, however, it is difficult to predict which technologies will “catch on” and which will be less successful. When trying to decide on a modality or innovation to use for a research study, it seems a risky gamble to use the newest, most cutting-edge device. There is, however, a concern that it takes so long to study new technologies that the results of the studies are available only when the technology is obsolete, or at least no longer new. Clearly there are benefits and downsides to predicting the future of communications innovations. There are, however, several categories in which innovations are emerging or are currently developing, and these emergent technologies may prove extremely helpful to moving forward the field of health communications. We will enumerate them here, with the caveat that this is a snapshot in time, and one that must be revisited often to provide the nearest view of the future.

    Gathering Information Online
    Gathering Data across the Internet

    In previous chapters, we have discussed online surveys, interviews, focus group-type chats, and similar methods for gathering data from study participants or potential participants. What if, on the other hand, we want to gather data about a broader group of people or about the Internet itself? For example, let us suppose that a new treatment becomes available for malaria, a widespread and deadly disease in many parts of the world. As health communications researchers, we may be interested in the way in which Internet users discuss the new treatment. Are users outside of the developed world aware of it? Do they know the risks and implications? Are the people who are most at risk for malaria aware of the treatment, or is it simply being discussed on medical sites? Are there concerns about side effects or misuse of the treatment? Are there socioeconomic impacts being discussed (e.g., the potential for reduced infant mortality and the effects of a healthier population on world economic development)? All of these bits of information would probably be discussed in various parts of the online world. How can we learn about these conversations without having to spend days and weeks online? The answer involves a web crawler (also called web robot or web bot, web spider, or combinations of these terms). The purpose of a web crawler is to search the web for pages on which a particular word or topic is discussed. Think of the web crawler finding all of the possible pages with malaria mentioned, creating a copy of those pages, and storing those copies in a folder. Once the pages are stored, the crawler can then search through the folder for pages that are similar to each other, pages that contain particular messages about malaria, or pages with other attributes determined by the crawler or its programmer. The amount of effort it takes to program a useful web crawler is considerable, because the goals of the user are often complex and require the crawler to process language found on websites. Detecting a particular word on a website is easy; deciphering the language to determine whether the site discusses the issue positively or negatively, for example, is difficult. Despite the complexity involved in programming a crawler, there are several in existence at this time, and no doubt there are more to come. One example of a web crawler can be found at and is aimed at public health researchers. The crawler searches for medical events mentioned on news sites and on sites where doctors post questions and answers for one another. Based on the data gathered from the “crawl,” EpiSpider can generate maps and reports describing medical events occurring all over the world. Each image generated, of course, is a snapshot of the time period over which the data were gathered. Still, the system is valuable for detecting possible outbreaks or emerging disease situations.

    Gathering Data about Your Website

    In nearly every case, the owners of a website are interested in knowing the number, demographics, and interests of people who view their site. Are teens viewing their page? What do they click on most often? How much time do older women spend reading their blog? Where are men going on their site, and what information do they seek out? Does anyone click on the advertisements? How many pages “deep” do people get into the website before abandoning it? This kind of information is called web analytics or web metrics and is key to the evaluation of a website or communications tool. Generally, acquiring this information requires installing a program that counts the visitors to the websites and records “click streams” (the paths followed by the users as they navigate the site) and time spent on the site. The most popular of the web analytics software programs is currently Google Analytics, which also links to Google Website Optimizer, a program that uses Google Analytics to determine what combination of layouts, content, and so forth are likely to provide the most successful viewing experience (as measured by the time spent on the site, the number of people who buy a product, or other metric). To assess the characteristics of the people who visit your website and to gauge which users are most likely to achieve what goals, a web analytics program is highly recommended.

    Virtual Experiences

    As the ability to play long videos and interact quickly with the computer becomes more pervasive, many organizations will be developing online, interactive simulations of real-life experiences. Online “virtual worlds” are websites in which users can create simulated structures, tools, clothing, food, creatures, and any number of other objects. In Second Life (Linden Lab), for example, people create avatars (graphical representations of themselves), purchase virtual buildings or islands or other properties, and create their own environments in which to interact. Virtual worlds of this type easily accommodate the enterprising health communicator who may wish to build, for instance, a virtual clinic. The virtual clinic can demonstrate the process of a physical exam, or perhaps a counseling session or another health-related experience. Such virtual experiences can mitigate the anxiety that patients often experience before a medical procedure. Of course, the inhabitants of virtual worlds are only a tiny fraction of the people who need assistance with potential health care visits. How can such simulated experiences be made available to a wider, more general audience?

    The answer lies in the application of this innovation to more general websites where people search for information about the health conditions or procedures they are experiencing. Consider a hypothetical teenager who is diagnosed with diabetes. Much information is available regarding diabetes, but how can the adolescent sort through it? How can he learn about the various medical excursions he will be required to embark upon? Perhaps a website that shows an avatar (a virtual patient) learning to measure his own blood sugar, monitor his diet, exercise appropriately, carry requisite supplies with him, go to school and explain his condition to friends and teachers, and attend regular medical visits would help such a patient. To add interactivity to the program, the teen could make choices for his avatar and see the consequences of those choices. Small subprograms could require the user to interactively move the virtual glucose monitor into position to perform sugar tests, pack a bag of supplies to take on vacation, or keep track of symptoms and activities. Adolescents may be an ideal target audience for such an innovation due to their comfort and familiarity with technological products and because they may face anxieties that they are not comfortable expressing to peers or parents. This makes a virtual environment that can be experienced privately even more valuable to the patient.

    Mobile phones can be a part of a virtual medical excursion and can help with the in-person medical care as well. Reminders to attend the virtual (and real-life) clinic can appear via text messages. Video or audio notes (short video or audio recordings that can be sent to mobile phones in a manner similar to text messaging) and related features can help ensure that insulin shots are administered properly, or diet and exercise are recorded, by providing brief video reminders of the process. Ideally, such a program would also be supported by the doctor's office at some level; perhaps the teenager could have regular question-and-answer contact with an office nurse or other staff member. Finally, blood sugar measurements can be entered into a mobile device and sent to the doctor's office so that a regular record of blood sugar is kept and periodically examined by the practitioner. If the readings are not submitted, or if the readings are indicative of problems, the office staff can contact the patient immediately.

    The benefits of virtual excursions are not limited to patients. Rather, such virtual environments are useful for a whole range of communications and training. Clinician education programs can assist student nurses with learning the layout of hospital rooms, performing basic operations with the various monitors and machines that are at the patient's bedside, or learning the order of instruments on a surgical tray. A student nurse may be able to use software to learn to assist the clinician with an exam, take medical history and physical information from an unyielding patient, or learn a whole host of scenarios that can occur in medical settings. Virtual experience cannot, of course, take the place of in-person experience, but can provide the health worker with some basic tools to assist in training and education.


    Telemedicine is a field of medical practice that relies on high-speed communications devices and software, and often video equipment, to allow medical personnel to conduct examinations or even perform some procedures from a distance. Both synchronous (real-time) and asynchronous versions of telemedicine exist. In the asynchronous form of telemedicine, information about a patient or medical situation is stored and sent to a distant expert; for example, a mammogram may be saved by a technician in Botswana and forwarded to a radiologist in New Jersey for assessment. Similarly, a nurse practitioner may send case files to a specialist for review and consultation. The patient need not be present when the information is transmitted.

    Synchronous telemedicine is far more complex. In one example, a counselor may consult with a patient who is physically inaccessible, perhaps on a ship in the middle of the ocean, or in a prison or another facility. Simple videoconferencing can allow such an encounter to proceed. More complex is a procedure in which an onsite clinician examines the patient with medical tools that transmit the data to a distant consultant. For example, imagine an endoscope examining a patient's sinuses in one location, while a doctor in another location sees the video from the endoscope and studies the anatomy while talking to both the patient and the onsite staff. Further, imagine that a distant doctor controls a robot as it performs surgery on a patient.

    These forms of telemedicine are obviously incredibly high-tech and are evolving rapidly. For health communications and intervention purposes, however, there are obvious implications of this technology. Interventions that are begun in a doctor's office can be extended using mobile video notes, text messages, or online virtual excursions. Various drug dependency interventions can be supported by monitors that detect and transmit the physical symptoms of drug cravings and allow “sponsors” or counselors to immediately contact the patient to provide support.

    Hybrid Programs—Technology as an Adjunct to Clinical and Community Health Promotion

    This book has focused largely on the endeavor of delivering health promotion through technology, and we have assumed many if not most of these efforts to be stand-alone technology-based programs.

    It is overly simplistic to think about technology-based programs as stand-alone efforts, however. It may also be misguided to do so. Hospitals, clinics, schools, employers, and other institutions that regularly come in contact with large segments of the population are well positioned to consider the delivery of technology-based health promotion through their institutional channels to large numbers of people. Thus, we anticipate that hybrid efforts to connect technology to existing organizations and programs are an important focus for future program development. Indeed, linking technology to existing programs may be a way to overcome the fundamental challenge of getting and holding people's attention. With an ever-crowded Internet and technology-dominated environment, people may need to have a credible referral in order to engage with a technology-based program. We certainly cannot expect people to stumble onto the latest evidence-based smoking cessation or weight loss program on their own.

    Hybrid programs have the potential to take many forms. They can serve as extensions of existing programs—say, for example, a busy clinic is trying to offer “booster” sessions for a group-level diabetes self-management program. Offering adjunctive and enhancing activities online to persons enrolled in the program has the potential for reinforcing and expanding program exposure. Such activities can be a way to offer social support and/or a “buddy” system, linking people engaged in a face-to-face program in a virtual world where they can offer testimonials or real-life personal stories, for example, to encourage and support others in behavior change efforts. We anticipate such uses of technology will be forthcoming and of interest for clinical and institutional providers of care.

    Systems-Level Efforts—Using Technology to Improve Care Delivery at the Provider and Systems Level

    The field of health promotion has been criticized for an overemphasis on individual-level behavior change, and policymakers have made urgent calls for interventions that go beyond the individual to affect social, organizational, and environmental factors contributing to healthy behaviors (Hardy, 2004; McCormack, Laska, Larson, & Story, 2010; Piot, Bartos, Larson, Zewdie, & Mane, 2008).

    How can technologies be utilized to facilitate interventions operating beyond the individual? We have considered one here—STD Prevention Online, which seeks to establish networks of care providers to facilitate more timely adoption and sharing of best practices for sexually transmitted infection prevention and care. STD Prevention Online operates at the provider level. Changing community and social norms to facilitate behavior change may be augmented via the telephone—consider following an individual on Twitter as he or she attempts to lose weight through improved nutrition and physical activity—can the individual's “tweets” to his or her social network have an impact the behaviors of others? Using Internet blogs and camera phones could facilitate policy change—imagine asking people to take and post pictures online of areas in their physical environment that limit or represent a barrier to physical activity—for example, lack of sidewalks, or no bike lanes, or few curb cuts. Collective action to document physical barriers in the environment may be a powerful tool to influence policymakers to assist in creating a physical environment more conducive to physical activity. These are just a few of the ways we can utilize technology to go beyond the individual and facilitate health promotion.

    Concluding Thoughts
    Use of Technology as Adjunctive and Hybrid

    While much of this book focuses on the use of technology for health promotion programs that are intended to be stand-alone efforts, this overlooks the fundamental opportunities to utilize technology to enhance and expand programs. We look forward in coming years to the integration of technology more consistently into primary care and other health promotion programs; we are confident that there are multiple opportunities to streamline and standardize care delivery for primary prevention and general health promotion within care settings (Glasgow, Bull, Piette, & Steiner, 2004).

    In addition to the use of hybrid programming within clinic settings, we also anticipate development of strategic partnerships between community-based agencies serving persons at risk of negative health outcomes and clinical delivery systems. Primary care providers could potentially greatly expand their reach by partnering with communities to access their clients through technologies such as kiosks, the Internet, and cell phones.

    Use of Theory

    While we have outlined a theoretical framework in Chapter 1, we still lack a cohesive theoretical understanding of linkages between technology and health promotion generally. There are opportunities to develop theoretical perspectives that can better elucidate how to capitalize on technological reach, how to engage and retain people's participation in programs, and how to incorporate rapidly evolving technologies into health promotion programs. We look forward to contributions from social scientists and other theorists in theory development for technology-based health promotion in coming years.

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    Gustafson, D. H., McTavish, F. M., Stengle, W., Ballard, D., Hawkins, R., Shaw, B. R., et al. (2005). Use and impact of eHealth system by low-income women with breast cancer. Journal of Health Communication, 10(Suppl. 1), 195–218.
    Hardy, G. E., Jr. (2004). The burden of chronic disease: The future is prevention. Introduction to Dr. James Marks's presentation, “The Burden of Chronic Disease and the Future of Public Health.” Preventing Chronic Disease, 1, A04.
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    Hurling, R., Catt, M., De Boni, M., Fairley, B. W., Hurst, T., Murray, P., et al. (2007). Using internet and mobile phone technology to deliver an automated physical activity program: randomized controlled trial. Journal of Medical Internet Research, 9(2), 1–12.
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    Joffe, M., & Mindell, J. (2002). A framework for the evidence base to support health impact assessment. Journal of Epidemiology and Community Health, 56, 132–138.
    King, D., Bull, S., Christiansen, S., Nelson, C., Stryker, L., Toobert, D., et al. (2004). Developing and using interactive health CD-ROMs as a complement to primary care-lessons from two research studies. Diabetes Spectrum, 17, 234–242.
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    Lavoie, J. A., & Pychyl, T. A. (2001). Cyberslacking and the procrastination superhighway: A web-based survey of online procrastination, attitudes, and emotion. Social Science Computer Review, 19, 431–444.
    Leeman-Castillo, B. A., Corbett, K. K., Aagaard, E. M., Maselli, J. H., Gonzales, R., & MacKenzie, T. D. (2007). Acceptability of a bilingual interactive computerized educational module in a poor, medically underserved patient population. Journal of Health Communication., 12, 77–94.
    Linke, S., Murray, E., Butler, C., & Wallace, P. (2007). Internet-based interactive health intervention for the promotion of sensible drinking: Patterns of use and potential impact on members of the general public. Journal of Medical Internet Research, 9, e10. doi:10.2196/jmir.9.2.e10
    Logan, A. G., McIsaac, W. J., Tisler, A., Irvine, M. J., Saunders, A., Dunai, A., et al. (2007). Mobile phone-based remote patient monitoring system for management of hypertension in diabetic patients. American Journal of Hypertension, 20, 942–948.
    McCormack, L. A., Laska, M. N., Larson, N. I., & Story, M. (2010). Review of the nutritional implications of farmers’ markets and community gardens: A call for evaluation and research efforts. Journal of the American Dietetic Association, 110, 399–408.
    Noar, S. M., Clark, A., Cole, C., & Lustria, M. L. A. (2006). Review of interactive safer sex websites: Practice and potential. Health Communication, 20(3), 233–241.
    Pequegnat, W., Rosser, B. R., Bowen, A. M., Bull, S. S., Diclemente, R. J., Bockting, W. O., et al. (2007). Conducting Internet-based HIV/STD prevention survey research: Considerations in design and evaluation. AIDS and Behavior, 11, 505–521.
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    Piot, P., Bartos, M., Larson, H., Zewdie, D., & Mane, P. (2008). Coming to terms with complexity: A call to action for HIV prevention. The Lancet, 372(9641), 845–859.
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    Rotondi, A. J., Sinkule, J., & Spring, M. (2005). An interactive Web-based intervention for persons with TBI and their families: Use and evaluation by female significant others. Journal of Head Trauma and Rehabilitation, 20, 173–185.
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    Appendix: Technology-Based Health Promotions

    Andrade, A. S. A., McGruder, H. F., Wu, A. W., Celano, S. A., Skolasky, R. L. Jr., Selnes, O. A., et al. (2005). A programmable prompting device improves adherence to highly active antiretroviral therapy in HIV-infected subjects with memory impairment. Clinical Infectious Diseases, 41, 875–882.
    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, 74–82.
    Bensley, R., Brusk, J., Anderson, J., Mercer, N. F., Rivas, J. F., & Broadbent, L. (2006). Impact of a stages of change-based Internet nutrition education program. Journal of Nutrition Education and Behavior, 38(4), 222–229.
    Bowen, A. M., Williams, M. L., Daniel, C. M., & Clayton, S. (2008). Internet based HIV prevention research targeting rural MSM: Feasibility, acceptability, and preliminary efficacy. Journal of Behavioral Medicine, 31(6), 463–477.
    Bull, S. S., Phibbs, S., Watson, S., & McFarlane, M. (2007). What do young adults expect when they go online? Lessons for development of an STD/HIV and pregnancy prevention website. Journal of Medical Systems, 31, 149–158.
    Christensen, H., Griffiths, K. M., Mackinnon, A. J., & Brittliffe, K. Y. (2006). Online randomized controlled trial of brief and full cognitive behaviour therapy for depression. Psychological Medicine, 36, 1737–1746.
    Clarke, G. F., Eubanks, D. F., Reid, E., Kelleher, C. F., O'Connor, E., DeBar, L. L., et al. (2005). Overcoming Depression on the Internet (ODIN) (2): A randomized trial of a self-help depression skills program with reminders. Journal of Medical Internet Research, 7(2), e16.
    Cornelius, J. B., & St. Lawrence, J. S. (2009). Receptivity of African American adolescents to an HIV-prevention curriculum enhanced by text messaging. Journal for Specialists in Pediatric Nursing, 14, 123–131.
    Cullen, K. W., & Thompson, D. (2010). Feasibility of an 8-week African American web-based pilot program promoting healthy eating behaviors: Family Eats. American Journal of Health Behavior, 3(1), 40–51.
    Curioso, W. H., & Kurth, A. (2007). Access, use and perceptions regarding Internet, cell phones and PDAs as a means for health promotion for people living with HIV in Peru. BMC Medical Informatics and Decision Making, 7, 24.
    De Bourdeaudhuij, I., Stevens, V., Vandelanotte, C., & Brug, J. (2007). Evaluation of an interactive computer-tailored nutrition intervention in a real-life setting. Annals of Behavioral Medicine, 33, 39–48.
    Downer, S. R., Meara, J. G., & Da Costa, A. C. (2005). Use of SMS text messaging to improve outpatient attendance. Medical Journal of Australia 18(7), 366–368.
    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, 165–173.
    Gilbert, P., Ciccarone, D., Gansky, S. A., Bangsberg, D. R., Clanon, K., McPhee, S. J., et al. (2008). Interactive “Video Doctor” counseling reduces drug and sexual risk behaviors among HIV-positive patients in diverse outpatient settings. Public Library of Science ONE, 3, 1–10.
    Glasgow, R. E., Boles, S. M., McKay, H. G., Feil, E. G., & Barrera, M., Jr. (2003). The D-Net diabetes self-management program: Long-term implementation, outcomes, and generalization results. Preventive Medicine, 36, 410–419.
    Grimley, D. M., & Hook, E. W. I. (2009). A 15-minute interactive, computerized condom use intervention with biological endpoints. Sexually Transmitted Diseases, 36, 73–78.
    Haug, S., Meyer, C., Schorr, G., Bauer, S., & John, U. (2009). Continuous individual support of smoking cessation using text messaging: A pilot experimental study. Nicotine and Tobacco Research, 11, 915–923.
    Huang, M. Z., Kao, S. C., Avery, M. D., Chen, W., Lin, K., & Gau, M.(2007). Evaluating effects of a prenatal web-based breastfeeding education programme in Taiwan. Journal of Clinical Nursing 16(8), 1571–1679.
    Hurling, R., Catt, M., De Boni, M., Fairley, B. W., Hurst, T., Murray, P., et al. (2007). Using Internet and mobile phone technology to deliver an automated physical activity program: Randomized controlled trial. Journal of Medical Internet Research, 9(2), e7.
    Jacobi, C. F., Morris, L. F., Beckers, C. F., Bronisch-Holtze, J. F., Winter, J. F., Winzelberg, A. J., et al. (2007). Maintenance of internet-based prevention: a randomized controlled trial. International Journal of Eating Disorders, 40(2), 114–119.
    Japuntich, S. J., Zehner, M. E., Smith, S. S., Jorenby, D. E., Valdez, J. A., Fiore, M. C., et al. (2006). Smoking cessation via the Internet: A randomized clinical trial of an Internet intervention as adjuvant treatment in a smoking cessation intervention. Nicotine Tobacco Research, 8, S59-S67.
    Kainth, A., Hewitt, A., Pattenden, J., Sowden, A., Duffy, S., Watt, I., et al. (2004). Systematic review of interventions to reduce delay in patients with suspected heart attack. Heart, 90, 1161.
    Kim, H. S., Yoo, Y. S., & Shim, H. S. (2005). Effects of an Internet-based intervention on plasma glucose levels in patients with type 2 diabetes. Journal of Nursing Care Quality, 20, 335–340.
    Kirk, S. F., Harvey, E., McConnon, A. F., Pollard J. E., Greenwood, D., Thomas, J., Ransley, J., et al. (2007). A randomised trial of an Internet weight control resource: The UK Weight Control Trial. BMC Health Services Research, 7, 206.
    Krishna, S., Boren, S. A., & Balas, E. A. (2009). Healthcare via cell phones: A systematic review. Telemedicine and e-Health, 15, 231–240.
    Leeman-Castillo, B., Raghunath, S., Beaty, B., Steiner, J., Bull, S. (2010). LUCHAR: Battling heart disease with computer technology for Latinos. American Journal of Public Health, 100(2), 272–275.
    Levine, D., McCright, J., Dobkin, L., Woodruff, A. J., & Klausner, J. D. (2008). SEXINFO: A sexual health text messaging service for San Francisco youth. American Journal of Public Health, 98, 393–395.
    Lim, M. S. C., Hocking, J. S., Hellard, M. E., & Aitken, C. K. (2008). SMS STI: A review of the uses of mobile phone text messaging in sexual health. International Journal of STD & AIDS, 19, 287–290.
    Logan, A. G., McIsaac, W. J., Tisler, A., Irvine, M. J., Saunders, A., Dunai, A., et al. (2007). Mobile phone-based remote patient monitoring system for management of hypertension in diabetic patients. American Journal of Hypertension, 20, 942–948.
    McKee, M. B., Picciano, J. F., Roffman, R. A., Swanson, F., & Kalichman, S. C. (2006). Marketing the “Sex Check”: Evaluating recruitment strategies for a telephone-based HIV prevention project for gay and bisexual men. AIDS Education and Prevention, 18, 116–131.
    Murray, E., McCambridge, J., Khadjesari, Z. F., White, I. R., Thompson, S., Godfrey, C. F., et al. (2007). The DYD-RCT protocol: An on-line randomised controlled trial of an interactive computer-based intervention compared with a standard information website to reduce alcohol consumption among hazardous drinkers. BMC Public Health, 7, 307.
    Noar, S., Black, H., & Pierce, L. (2009). Efficacy of computer technology-based HIV prevention interventions: A meta-analysis. AIDS, 23, 107–115.
    Papadaki, A., & Scott, J. A. (2005). The Mediterranean Eating in Scotland Experience project: Evaluation of an Internet-based intervention promoting the Mediterranean diet. British Journal of Nutrition, 94, 290–298.
    Patrick, K., Raab, F., Adams, M. A., Dillon, L., Zabinski, M., Rock, C. L., et al. (2009). A text message-based intervention for weight loss: Randomized controlled trial. Journal of Medical Internet Research, 11, e1.
    Paxton, S. J., McLean, S., Gollings, E. K., Faulkner, C., & Wertheim, E. H. (2006). How effective are synchronous online interventions for body dissatisfaction in adult women and adolescent girls? Paper presentation at Eating Disorders Research Society Conference, Port Douglas, Australia.
    Polzien, K. M., Jakicic, J. M., Tate, D. F., & Otto, A. D. (2007). The efficacy of a technology-based system in a short-term behavioral weight loss intervention. Obesity, 15, 825–830.
    Puccio, J. A., Belzer, M., Olson, J., Martinez, M., Salata, C., Tucker, D., et al. (2006). The use of cell phone reminder calls for assisting HIV-infected adolescents and young adults to adhere to highly active antiretroviral therapy: A pilot study. AIDS Patient Care and STDs, 2(6), 438–444.
    Reynolds, N. R., Testa, M. A., Su, M., Chesney, M. A., Neidig, J. L., Frank, I., et al. (2008). Telephone support to improve antiretroviral medication adherence. Journal of Acquired Immune Deficiency Syndrome, 4(7), 62–68.
    Rodgers, A., Corbett, T., Bramley, D., Riddell, T., Wills, M., Lin, R. B, et al. (2005). Do u smoke after txt? Results of a randomised trial of smoking cessation using mobile phone text messaging. Tobacco Control, 14, 255–261.
    Rosser, B., Miner, M., Bockting, W., Ross, M., Konstan, J., Gurak, L., et al. (2009). HIV risk and the Internet: Results of the Men's Internet Sex (MINTS) Study. AIDS and Behavior, 13, 746–756.
    Skinner, D., Rivette, U., & Bloomberg, C. (2007). Evaluation use of cellphones to aid compliance with drug therapy for HIV patients. AIDS Care, 19(5), 605–607.
    van Wier, M., Ariens, G., Dekkers, J., Hendriksen, I., Pronk, N., Smid, T., et al. (2006). ALIFE@Work: A randomised controlled trial of a distance counselling lifestyle programme for weight control among an overweight working population. BMC Public Health, 6, 140.
    Verheijden, M., Bakx, J. C., Akkermans, R., van den Hoogen, H., Godwin, N. M., Rosser, W., et al. (2004). Web-based targeted nutrition counselling and social support for patients at increased cardiovascular risk in general practice: Randomized controlled trial. Journal of Medical Internet Research, 6, e44.
    Vildrine, D. J., Arduino, R. C., & Gritz, E. (2006). Impact of a cell phone intervention on mediating mechanisms of smoking cessation in individuals living with HIV/AIDS. Nicotine and Tobacco Research, 8(1), S103-S108.
    VW Consulting. (2009). mHealth for development: The opportunity of mobile technology for healthcare in the developing world. Washington, DC, and Berkshire, UK: United Nations.
    Webber, K. H., Tate, D. F., & Quintiliani, L. M. (2008). Motivational interviewing in Internet groups: A pilot study for weight loss. Journal of the American Dietetic Association, 108, 1029–1032.
    Winett, R., Anderson, E., Wojcik, J., Winett, S., & Bowden, T. (2007). Guide to health: Nutrition and physical activity outcomes of a group-randomized trial of an Internet-based intervention in churches. Annals of Behavioral Medicine, 33, 251–261.

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