6,509
Views
89
CrossRef citations to date
0
Altmetric
ARTICLES

Exploring the Potential of Web 2.0 to Address Health Disparities

, , , , &
Pages 77-89 | Published online: 15 Aug 2011

Abstract

This article addresses use of the Internet and Web 2.0 technologies by racial and ethnic minorities and explores the potential opportunities and challenges in leveraging Web 2.0 approaches to impact health disparities. These opportunities and challenges include developing approaches and methods to (a) identify strategies for integrating social media into health promotion interventions focused on major health-related issues that affect members of medically underserved groups; (b) amalgamate techniques to leverage and connect social-media technologies to other evidence-informed online resources; (c) integrate health communication best practices, including addressing health literacy issues; (d) capitalize on social networking to enhance access and communication with health care providers; and (e) advance current efforts and ongoing expansion of research participation by individuals from underserved communities.

According to the 2010 National Healthcare Disparities Report, disparities related to race, ethnicity, and socioeconomic status remain pervasive in the American health care system. The report highlighted the fact that health care quality and access are suboptimal, especially for minority and low-income groups, regardless of state or region of the country where one resides. Health disparities across many conditions such as cancer, diabetes, heart disease, mental health and substance abuse, and respiratory diseases reflect uneven demographic patterns. These patterns are generally characterized by poorer quality health and reduced access to the breadth and quality of health services for disadvantaged individuals as compared with the scope and quality of services typically available to persons from more affluent and/or majority culture backgrounds. In addition to persons from racial and ethnic minority backgrounds and low-income families, others affected by health disparities include women, older adults, residents of rural areas, and individuals with disabilities and other special health care needs (Agency for Healthcare Research and Quality, Citation2011).

Among approaches ranging from efforts to change individual behaviors to much broader systems and/or policy changes formulated to address health disparities, health communications strategies remain important. Such strategies can be implemented using traditional media (e.g., print, broadcast, telephone service) or new media, including Web 2.0 communication channels. The expanding use of health information technology and Internet-based interventions encompasses electronic health (e-health) phenomenon. E-health has been defined as follows:

… an emerging field in the intersection of medical informatics, public health and business, referring to health services and information delivered or enhanced through the Internet and related technologies. In a broader sense, the term characterizes not only a technical development, but also a state-of-mind, a way of thinking, an attitude, and a commitment for networked, global thinking, to improve health care locally, regionally, and worldwide by using information and communication technology (Eysenbach, Citation2001).

The e-health definition alone, with its references to “way of thinking,” “attitudes,” and “commitment to networked, global thinking” would appear to be a natural arena in which to apply Web 2.0 technologies. The Pew Internet & American Life Project (Pew Internet) defines Web 2.0 as “an umbrella term that is used to refer to a new era of web-enabled applications that are built around user-generated or user-manipulated content, such as wikis, blogs, podcasts and social networking sites” (Pew Internet & American Life Project, Citation2011b). Perhaps more important, members of minority groups have embraced Web 2.0 technologies much more rapidly than has the White majority. As noted in a Pew Internet report published in late 2010, minority adults are much more likely than their White counterparts to use the full range (e.g., sending text messages, accessing the Internet, participating in social networking) of cell phone capabilities (Smith, Citation2010b). The increased use of Web 2.0, especially among racial and ethnic minorities, provides potential opportunities to engage people in health-related issues, stimulate an active role in their own health care, connect them with others and evidence-based interventions, and create social action focused on the social determinants of health disparities. Web 2.0 has the potential to connect underserved and underrepresented populations to important health information resources and to build social support for those affected by health care issues.

Although the approaches suggested by Web 2.0 technologies and e-health applications hold great promise, they also raise many questions. Among the questions requiring answers are the following:

How are these emerging technologies being used by persons who have been historically disadvantaged in accessing health services? What research should be undertaken to better define usage of Web 2.0 and e-health technologies in addressing the needs of historically underserved populations?

What opportunities are available and what challenges need to be overcome in using Web 2.0 and e-health technologies to engage those most affected by health disparities in appropriate activities that improve understanding of health and disease, link them to health providers and resources, and heighten awareness of and participation in clinical research and application of findings to personal health?

How can we optimize efforts to capitalize on Web 2.0 and e-health technologies to enhance delivery of comprehensive, evidence-based and culturally and linguistically appropriate instructional and informational resources to individuals from groups historically underserved?

Disparities in the United States

Documentation of disparities in health care delivery and health outcomes in the United States originated with the release of the Surgeon General's report, Health US 1983, and the subsequent release of the Report of the Surgeon General's Task Force on Black and Minority Health in 1985 (Agency for Healthcare Research and Quality, Citation2010). Evidence of the effect of health disparities has continued to mount over the ensuing years, fueled by the rapid growth in the scientific literature evaluating disparities, the work of the Institute of Medicine culminating in the report, Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare (Smedley, Stith, & Nelson, Citation2003), and the establishment of the National Healthcare Disparities Report, which has monitored national health care disparities trends since 2003 (Fox & Jones, Citation2009; Fox & Rainie, Citation2002; Hesse et al., Citation2005; Murray et al., Citation2003; Risk & Dzenowagis, Citation2001; Ybarra & Suman, Citation2006). Recent literature on health care disparities indicates that unequal treatment associated with varied demographic factors continues to be pervasive and persistent in the U.S. health care system (2010 National Healthcare Disparities Report, 2011). The effects of disparities can be identified at almost every point across the lifespan, within every type of health care delivery setting, and across every type of health care provider. Although most often described in terms of race and ethnicity, significant health care disparities have also been described at every socioeconomic level and across populations defined by age, gender, geography, and disability status.

The Emergence of E-Health and Web 2.0

Worldwide Internet usage is growing rapidly, increasing by 300% since 2008 (http://www.internetworldstats.com/stats.htm). In the United States, 77% of adults report using the Internet (Pew Internet & American Life Project, Citation2011a), with more than 80% of these (61% of all adults) seeking health information via the Internet (Rainie, Citation2011). A recent study found that, among Internet users, the Internet was second only to health care providers as an information source important in their health decisions (Couper et al., Citation2010). Earlier research had shown that the Internet may empower patients to improve their health behaviors and to take a more active role in their health care (Horrigan, Rainie, & Fox, Citation2001).

For many, even from the earliest days of the Internet, the importance of going online has been more closely related to the social aspects of doing so than any information-seeking needs that users might have. As early as 2001, researchers found that the online world was not merely a digitized library, but rather a vibrant social universe where many Internet users enjoy serious and satisfying contact with online communities. These online groups were made up of tens of millions of Americans who shared information about passions, beliefs, hobbies or lifestyles online (O'Reilly, Citation2005). As online consumers and electronic applications matured, the focus of web use began to shift from primarily information seeking to online interaction with goods, services and others who were online.

In 2004, the term Web 2.0 was introduced to describe this shift in consumer demand and application functionality (Van De Belt, Engelen, Berben, & Schoonhoven, Citation2010). Although there are different definitions, most have several aspects in common, with the main difference between Web 1.0 (the first generation of the Internet) and Web 2.0 related to interactivity (Van De Belt et al., Citation2010). Web 1.0 was mostly unidirectional information seeking, whereas Web 2.0 allowed the user to add information or content to the web, thus enabling interaction, information sharing, and collaboration (Pew Internet & American Life Project, Citation2009). The terms social media and social networking increasingly began being used to describe the essential attributes of Web 2.0 tools, applications, and functions.

The use of Web 2.0 technologies is rapidly changing. The November 2010 Pew Internet survey revealed that 61% of American adult Internet users age 18 and older use a social networking site such as MySpace, Facebook, or LinkedIn (Pew Internet & American Life Project, 2011a); up from 8% in February 2005. The most popular is Facebook, with almost three fourths of those online having an account, followed by MySpace with 48% having an account. At the present time, it is estimated that about 14% of online adults have a LinkedIn account with smaller percentages having accounts with networking sites including Yahoo!, YouTube, Tagged, Flickr, and Classmates.com (Smith, Citation2010a). Chou and colleagues (Chou, Hunt, Beckjord, Moser, & Hesse, Citation2009) found that among Internet users, approximately 27% reported using at least one form of social media. Social networking was reported by 23% of survey respondents, followed by blogging (7%) and online support groups (5%). It is worth noting that those with poorer self-reported health status had higher rates of using online support groups. One study found that 35% of online adults reported use of a social networking site within the past 12 months (Kontos, Emmons, Puleo, & Viswanath, Citation2010). The study found that younger age was the most significant predictor of social networking use.

Web 2.0 and Health Care Disparities

The emerging data highlights variations in broadband Internet access and use of mobile technology among racial and ethnic minorities and other underserved groups, but less variations in use of social networking sites. In 2010, 87% of families making $75,000 or more had broadband at home, compared with only 45% of those making $30,000 or less. With regard to racial differences, 67% of Caucasians and 56% of African Americans were broadband users in 2010, whereas about 66% of Caucasians and only 46% of African Americans had broadband in 2009 (Smith, Citation2010a). African Americans and Latinos are more likely than Whites to view a lack of broadband access as a major disadvantage in using the web (Smith, Citation2010a). Last, 86% of people with college degrees had broadband access, whereas only 33% of those with less than a high school diploma had such access (Wang, Bennett, & Probst, Citation2011). Chou and colleagues (Citation2009) found similar results in an analysis of the Health Information National Trends Study, where non-Internet users were more likely to be ethnic minorities, older, less educated, less healthy, more distressed, and to report a history of a cancer diagnosis. Another study (Wang et al., Citation2011) also found that minorities (African Americans and Hispanics) and those with diagnosed medical conditions were less likely to use the Internet. They also found that rural/urban differences disappeared when adjusting for demographic variables, suggesting occupational variation as the key determinant.

Although the gap between non-Whites (Black/Latino) and Whites in access to the Internet and broadband at home continues to exist, it should be noted that the gap in cell phone ownership is negligible and African Americans and Latinos actually report higher levels of wireless Internet (Smith, Citation2010b). According to the Pew Internet and American Life project, African Americans and Latinos are leading the way in using cell phones and mobile devices to access the Internet, use instant messaging, engage social networking sites, look up health information, and track or manage their health with specialized applications (Smith, Citation2011). Of those who own a cell phone, 51% of English-speaking Hispanics, 46% of African Americans, and 33% of White non-Hispanics use their phone to access the Internet. A similar pattern is seen for use of phones to access a social networking site (Smith, Citation2010c). Of note, 25% of English speaking Hispanics, 19% of African Americans and 15% of White, non-Hispanics use their mobile phone to access health information. However, African Americans reported a higher percentage of having applications to track or manage health (15%), compared with Latinos (11%) or Whites (7%).

Regarding the use of social networking sites, Kontos and colleagues (Citation2010) did not find significant differences by race, ethnicity, or socioeconomic status. They found that younger age was the most significant predictor of social networking site use. These findings are somewhat at odds with those of Chou and colleagues (Citation2009), who did find differences in social media use on the basis of racial/ethnic characteristics. Their analysis of the 2007 Health Information National Trends Survey indicated that among Internet users, African Americans were more likely than non-Hispanic Whites to use a social networking site.

Perhaps of most interest in determining opportunities to address health status disparities is that African Americans and Latinos agreed more than Whites that it was “very important” for the government to use online social networks to help people be more informed and to make government more accessible (Epsilon Company, Citation2010). Given the current documented difference in levels of participation in social media by persons from minority populations compared with their counterparts in the majority population, as well as more limited access to broadband at home for ethnic minority individuals, social media applications using mobile platforms may represent an important channel for delivering relevant and timely health information and information-based clinical support services to underserved populations.

Potential Opportunities and Challenges for Web 2.0 to Address Disparities

This growing increase in the use of Web 2.0 technologies, especially among racial and ethnic minorities, provides potential opportunities to engage people in health-related issues, engage them in their own care, connect them with others who have similar interests and with evidence-based interventions, and even create community action focused on the social determinants of health disparities (Roblin, Houston, Allison, Joski, & Becker, Citation2009). Although mobile technology is more widely used by racial and ethnic minorities, and social networking has been embraced by these populations, the digital divide persists, including differential access to broadband Internet service that has the potential to expand the range and relevancy of information targeted to specific groups (Viswanath, Citation2011; Viswanath & Ackerson, Citation2011). This situation reduces opportunities for members of underserved populations to access information and services that might support efforts to realize healthier lifestyles and enhanced decision making about health care options and treatments that may be offered for consideration.

The opportunities and challenges of Web 2.0 technologies to address health disparities range across the spectrum from patient focused interventions, patient–provider communication, health care delivery, community and societal change. Here we highlight and discuss (a) the integration of social media approaches into health-promotion interventions focused on major health-related issues that affect underserved groups; (b) the amalgamation of approaches to leverage and connect social media technologies to other evidence-informed online resources (e.g., evidence from comparative effectiveness reviews); (c) the use of health communications best practices, including addressing health literacy; (d) the potential use of social networking to enhance access and communication with health care providers; and (e) the expanded participation of persons from historically underserved groups in research.

Integrating Social Media Approaches into Health Promotion Interventions

Emerging evidence suggests that the potential of social networking and Web 2.0 applications to improve health outcomes lies not only in their ability to provide clinical information to a broad array of patients, but also in their social and supportive functions that may appear absent in the traditional health care system. A report by the Epsilon company indicates that individuals who use social networking and Web 2.0 applications for health, among other things, do so not simply to learn about treatment options, but also because (a) they find comfort knowing they are not alone; (b) they are able to find answers from other patients/people with similar ailments; (c) they find it empowering; and (d) it enables them to engage more deeply in the management of their health concerns (Richardson et al., Citation2010). In particular, Web 2.0 technologies and social networking applications may help improve one or more aspects of patient engagement. A randomized study among 324 adults who were either overweight, had Type 2 diabetes, or coronary heart disease included the use of pedometers and a web-based walking program. Individuals in one of two intervention arms were also assigned to an online community and could post and read messages from other participants. Although individuals in both study arms increased their average steps, the online community participants were more likely to stay engaged in the program over a longer period of time (Ferguson, Citation2007).

Another example involves African American women. GirlTrek: A Challenge to Black Women and Girls (http://www.girltrek.org/#!) is a nonprofit online community. GirlTrek focuses on getting Black women and girls to get physically active by joining the GirlTrek walking campaign. The GirlTrek site encourages women to walk with teams or train for 5 K races by sharing stories and connecting with other healthy Black women and girls. The site includes real testimonies from and photographs of women who have joined the campaign. The site also includes a way to connect through Facebook, the GirlTrek blog, and Twitter.

The GirlTrek, or Healthy Black Women and Girls Facebook page, (http://www.facebook.com/HealthyBlackWomenandGirls) has more than 24,000 “likes” and a large number of user-generated comments. Most of the comments from these women relate to their progress with training or physical activity. Social relationships have been shown to be important in managing disease (The Huffington Post, Citation2010). The example of Healthy Black Women and Girls shows that social media could be a powerful tool in using these relationships to impact disease management and maintain health.

A third example involves efforts to influence tobacco use. Among tobacco users, smokers attempting to quit are increasingly turning to Web 2.0 applications for help. The New York City Quits – I Quit Because Facebook page (http://www.facebook.com/nycquits) has more than 5,000 fans only one year since its launch, while Qwitter, a Twitter-inspired smoking cessation tool run by the Florida Department of Health, has more than 400 followers (The Huffington Post, Citation2010). Other online Web 2.0 smoking cessation resources, including the National Cancer Institute's Smokefree.gov and proprietary sites such as QuitNet and Habitchanger.com, offer a variety of services that include step-by-step guides, expert advice, forums and chat rooms where people can share information, support and tips (Gibbons et al., Citation2009).

Last, location-based Web 2.0 services such as Foursquare, BrightKite, CitySense, GyPsii, or Plazes are all based on the premise that people want to know the whereabouts, activities and preferences of friends and associates. Latinos are leading the way in use of these applications. Of the social media users, 10% of Latinos, 5% of African Americans, and 3% of Caucasians use location-based applications (Smith, Citation2011). The Text 2 Survive project, run through the Illinois Department of Public Health, used a text messaging service to provide minority youth with accurate information about HIV/AIDS (Agency for Healthcare Research and Health Care Innovations Exchange, Citation2010). One component of this program was that participants could receive a listing of nearby clinics with the entry of a zip code from a cell phone. Depending on the application, the program sponsors provide user incentives in the form of social capital and sometimes money (discounts on goods and services) to encourage use of the applications and venues. Although these apps are generally being used to show self-defined networks of users and the places frequented by others in their networks, one could imagine using these media to form disease-, condition-, behavior-, or goal-oriented networks of patients and health consumers who use these apps to locate needed health services or resources, learn who is using these resources and accumulate or build social or economic capital in a way that promotes health and healthy behaviors. For example, applications such as Whrrl and Yelp, which currently are used to locate stores and eateries, could be used to encourage patronization of healthier food establishments, parks, gyms, clinical services or any other health resource within a defined community of targeted consumers, patients or caregivers.

The Amalgamation of Various Media to Address Health Disparities

Given that a higher percentage of racial and ethnic minorities, compared with the general population, report accessing the Internet through mobile devices, it is important to explore how to leverage this technology as a gateway to more in-depth resources and existing evidence-based interventions. A number of recent articles indicate that those participating in the research may not be using web-based health promotion interventions. In a study with rural women who were participating in a colorectal cancer screening intervention, only 24% logged on to the website (Fleisher, Citation2011). Sarkar and colleagues (Citation2011) found similar results in a study of 14,102 diverse patients in Northern California. Of the 5,671 who agreed to participate in a patient portal on diabetes, African-Americans and Latinos, as well as Whites and others without college degrees, were more likely to have never logged on. Perhaps the integration of these web-based applications through social networking sites would promote their enhanced credibility and use. In addition, for those groups who primarily rely on mobile devices to access the Internet, it may be difficult to use more complex health-related, web-based applications, such as treatment decision support tools. Although the nature of Web 2.0 applications supports user engagement and participation, we still face the issue of how to make health-related information relevant and interesting and create modular interventions that can be easily deployed via mobile technology.

The Application of Health Communications Best Practices, Including Addressing Health Literacy in Web 2.0 Approaches

Despite the potential capacity of using these new applications, there are challenges that need to be considered. Issues of information accuracy and validity, limited consumer access to more complex interventions and resources, and the whether the content is culturally and linguistically appropriate may serve as deterrents to more effective health-related uses of Web 2.0 technologies. For example, current Web 2.0 technologies, such as blogs, may provide important social networks regarding health issues, but, in most cases, do not offer unbiased or complete information that is needed to activate and inform patients. A recent study by Pew Internet found that 97% of respondents to the survey said the health information online did not harm them or they did not know whether it harmed them, but only 30% said it helped them (Fox, Citation2011).

Health literacy has been identified as a determinant of health disparities that is associated with age, education, poverty, and culture. According to the 2003 National Assessment of Adult Literacy, more than 43% or 93 million U.S. adults had basic or below basic health literacy skills. Although the average reading grade level for adults in the United States is at or below eighth grade, more than 800 published studies indicate that many health materials are written at levels that exceed the reading skills of average high school graduates (Rudd, Moeykens, & Colton, Citation2000). Consequently, individuals with low health literacy know less about their health problems, are less likely to engage in certain preventive behaviors, are less likely to comply with self-management regimens for chronic health conditions, and are more likely to have frequent hospitalizations. Several studies have found that low health literacy was more prevalent among African Americans, persons with lower educational attainment and Spanish speakers (Institute of Medicine, Citation2004; Kutner, Greenberg, Jin, & Paulsen, Citation2006; Weiss, Citation2007). These issues remain relevant to the use of digital media. In the previously cited study on use of an Internet-based patient portal in managing diabetes, health literacy, along with race/ethnicity, language spoken, and educational attainment, factored into resource usage. Those with low health literacy had higher odds of never signing on to a diabetes-focused patient portal compared with those who did not report any health literacy limitations (Sarkar et al., Citation2011). More research is needed to understand the effect of health literacy on the use of Internet-based interventions and social media. It will also be important to develop content and technologies to address these health literacy issues in these new mediums.

The Potential Use of Social Networking to Enhance Access and Communication with Health Care Providers

Although some providers avoid the use of emerging technologies, others avidly embrace them (Gibbons, Citation2011). Health care innovations are emerging that combine information technology and social media, resulting in paperless practices that use a combination of telemedicine, e-mail, instant messaging, text messaging, video chats and Twitter to communicate with patients. These practices significantly increase the number of options patients may use to access and communicate with their providers while also enabling the providers to offer care to certain patients who cannot or prefer not to come into the office or clinic. For example, popular Web 2.0 sites such as Second Life could allow patients to interact through self-defined avatars, thereby enabling providers to provide virtual mental health counseling services to avatars (patients) who for personal reasons (e.g., embarrassment with the disease, condition, or question) choose to seek out medical professionals to discuss health problems in the context of a virtual world (Gorini, Gaggioli, Vigna, & Riva, Citation2008; Morie, Antonisse, Bouchard, & Chance, Citation2009). While the prevalence and/or efficacy of this form of “clinical practice” have not been definitively evaluated, it clearly is happening and may increase in the future.

On the other hand, provider organized networks and communities of patients engaged in health care oriented Web 2.0 and social networking activities could actually provide the physician with an amazing array of detailed information about an individual patient, all patients in the network as a whole, and the resources that are available within a given community to help patients address their health needs. Often providers have only general information about patients’ health-related activities or potentially helpful community resources, which at times may lead to care plans that do not approximate the realities in which patients live. The use of Web 2.0 tools and media by providers could enable a level of patient and community centeredness not possible at present, but that is increasingly suggested by reports in the literature as realistic in the near term (Beard, Wilson, Morra, & Keelan, Citation2009; Weitzel, Smith, de Deugd, & Yates, Citation2010).

The Potential Use of Social Networking to Enhance Knowledge and Participation in Research

Another way in which Web 2.0 tools and applications could enhance disparities research is by providing additional modalities to identify and recruit potential study participants (Allison, Citation2009), as well as facilitate ongoing participation and feedback (Wright et al., Citation2009). Identifying new networks of underserved and underrepresented populations and developing partnerships with these networks will be an important ongoing effort. It is possible to envision the emergence of a Web 2.0 enhanced community-based participatory research approach that could enable and facilitate participatory engagement even in the absence of more traditional face-to-face meetings. Thus, applications could preserve the critical elements of personal interaction, yet reduce or eliminate barriers related to geography, time, or transportation or other material resources. Envisioning the development of Research 2.0 that capitalizes on the potential of Web 2.0 applications, some people have gone as far as to suggest opportunities can be created to “engage with the population and begin to co-create the data” (Rathi & Given, Citation2010, p. 5).

The emerging Web 2.0 has the potential to generate new research ideas as well as facilitate health disparities research. Because Web 2.0 applications have the potential to reach and connect large numbers of individuals, it becomes possible to use the reach and scope of social networking on the Internet to find solutions to complex research problems. The online community PatientsLikeMe.com has about 102,000 patient members across more than 500 disease communities who share personal health information with each other. Among others, PatientsLikeMe members include a larger group of Lou Gehrig's disease (amyotrophic lateral sclerosis) sufferers than any registry or pharmaceutical company in the world (Singer, Citation2010). In 2008, after a small Italian study suggested that lithium could potentially slow the progression of amyotrophic lateral sclerosis, approximately 10% of PatientsLikeMe users who had the disease began taking the drug, refusing to wait for a larger, more definitive study. A Brazilian company provided online tools for patients to track their progress, while PatientsLikeMe founders used the data to build elaborate disease progression models incorporating the lithium data and data from the extensive PatientsLikeMe database. The results of tier analysis indicated that lithium had no effect on the progression of amyotrophic lateral sclerosis. The journal Lancet Neurology published a study showing the same result 18 months later (Wicks, Vaughan, Massagli, & Heywood, Citation2011). Although observational studies cannot be used to definitively characterize causal relationships, they can be very important in helping to elucidate important clues regarding causation. They can also assist researchers in generating critical hypotheses about important health issues.

Discussion

It is clear that elimination of health care and health disparities will require concerted efforts to address the major categories of determinants which include clinical and health care system factors, but also must include nonclinical, social, behavioral, and environmental factors, which, at times, profoundly affect health outcomes. Web 2.0, given its foundation of social networking and its acceptance within minority populations through certain technologies (e.g., cell phones, smart phones), holds great promise in our efforts to address health disparities. Web 2.0 tools and applications have the potential to enable a new genre of multilevel investigation and research that could catalyze the fusion of medical and population research into what has been termed Populomics (Gibbons, Citation2008), to provide a more integrated understanding of disparities causation while providing a robust foundation for further intervention development.

Web 2.0 technologies and social media offer the promise of significant advances in the field of health care disparities. To realize this goal, we will need to take an ecological view, addressing individual, provider and system issues. On the individual level, it is important to address significant challenges including health literacy, language, integration of evidence-based information and resources, as well as access to more complex interventions. And as the emerging evidence suggests, minority populations may be more responsive to social media and have a higher uptake of mobile technology. There is a need to develop Web 2.0 resources and messages that can be effectively delivered through mobile devices, but that are also based on sound health communication best practices and link to more comprehensive and evidence-based content. Moreover, limited health literacy may be a barrier to using these technologies for health-related activities. In the future, these technologies may enhance clinical practice by providing clinicians with rich clinical, environmental, and behavioral data at the individual and group levels that could improve provider decision support at the point of care and enhance disparities research. Instead of seeking one or more “killer apps” and relying on social media primarily for marketing and informational purposes, providers and the health care systems should seek to proactively deploy these technologies to improve clinical care, facilitate greater patient participation in the care process and enhance health care disparities research. A far better approach would be to identify the critical needs among health disparities target populations and then seek to determine whether a Web 2.0 tool/application can help meet the need or be harnessed in a way that contributes to addressing a key health disparities problem. In the same way, few would support a goal of developing one medicine to treat all patients, the goal here should be to understand the needs and realities of providers, health care systems, patients and caregivers and then identify and develop appropriate Web 2.0 tools that match the new applications with the correct user populations, leading to a 21st-century way to address persistent health disparities and contribute to desired health outcomes.

Acknowledgments

The Eisenberg Conference Series 2010 Meeting on The Prospects for Web 2.0 Technologies for Engagement, Communication and Dissemination in the Era of Patient-Centered Outcome Research was conducted by the John M. Eisenberg Center for Clinical Decisions and Communications Science at Baylor College of Medicine, Houston, Texas, under contract to the Agency for Healthcare Research and Quality Contract HHSA290200810015C, Rockville, MD. The authors of this article are responsible for its content. No statement may be construed as the official position of the Agency for Healthcare Research and Quality of the U.S. Department of Health and Human Services.

References

  • Agency for Healthcare Research and Quality . ( 2010 ). 2009 National healthcare disparities and quality report (No. 10–0004) . Washington DC : U.S. Department of Health and Human Services .
  • Agency for Healthcare Research and Quality . ( 2011 ). 2010 National healthcare disparities and quality report (No. 11–0005) . Rockville , MD : U.S. Department of Health and Human Services .
  • Agency for Healthcare Research and Quality Health Care Innovations Exchange . ( 2010 ). Innovation profile: Texting service enhances minority youth access to HIV/AIDS information and testing . In: AHRQ Health Care Innovations Exchange . Rockville , MD . Retrieved March 2011 from http://www.innovations.ahrq.gov
  • Allison , M. ( 2009 ). Can Web 2.0 reboot clinical trials? Nature Biotechnology , 27 , 895 – 902 .
  • Beard , L. , Wilson , K. , Morra , D. , & Keelan , J. ( 2009 ). A survey of health-related activities on second life . Journal of Medical Internet Research , 11 ( 2 ), e17 .
  • Chou , W. Y. , Hunt , Y. M. , Beckjord , E. B. , Moser , R. P. , & Hesse , B. W. ( 2009 ). Social media use in the United States: Implications for health communication . Journal of Medical Internet Research , 11 ( 4 ), e48 .
  • Couper , M. P. , Singer , E. , Levin , C. A. , Fowler , F. J. Jr. , Fagerlin , A. , & Zikmund-Fisher , B. J. ( 2010 ). Use of the Internet and ratings of information sources for medical decisions: results from the DECISIONS survey . Medical Decision Making , 30 , 106S – 114S .
  • Epsilon Company . ( 2010 ). A prescription for customer engagement: An inside look at social media and the pharmaceutical industry . Irving , TX : Epsilon International .
  • Eysenbach , G. ( 2001 ). What is e-health? . Journal of Medical Internet Research , 3 ( 2 ), E20 .
  • Ferguson , T. ( 2007 ). e-patients: How they can help us heal healthcare . Retrieved April 2011 from http://e-patients.net/e-Patients_White_Paper.pdf
  • Fleisher , L. ( 2011 ). Patterns of use and perceptions of a decision support software tool for men with early stage prostate cancer . Unpublished doctoral dissertation, Temple University, Philadelphia, PA .
  • Fox , S. ( 2011 ). The social life of health information . Philadelphia : The Pew Charitable Trust .
  • Fox , S. , & Jones , S. (2009). The social life of health information . Pew Internet & American Life Project. Retrieved May 2011 from http://www.pewinternet.org/Reports/2009/8-The-Social-Life-of-Health-Information.aspx .
  • Fox , S. , & Rainie , L. ( 2002 ). How Internet users decide what information to trust when they or their loved ones are sick (Vital Decisions: A Pew Internet Health Report) . Washington , DC : Pew Internet & American Life Project .
  • Gibbons , M. C. ( 2008 ). Populomics . Studies in health technology and informatics , 137 , 265 – 268 .
  • Gibbons , M. C. ( 2011 ). Use of health information technology among racial and ethnic underserved communities . Perspectives in Health Information Management , 8 , 1 – 13 .
  • Gibbons , M. C. , Wilson , R. F. , Samal , L. , Lehman , C. U. , Dickersin , K. , et al. . ( 2009 ). Impact of consumer health informatics applications . Evidence Reports/Technology Assessments , 188 , 1 – 546 .
  • Gorini , A. , Gaggioli , A. , Vigna , C. , & Riva , G. ( 2008 ). A second life for eHealth: Prospects for the use of 3-D virtual worlds in clinical psychology . Journal of Medical Internet Research , 10 ( 3 ), e21 .
  • Hesse , B. W. , Nelson , D. E. , Kreps , G. L. , Croyle , R. T. , Arora , N. K. , et al. . ( 2005 ). Trust and sources of health information: The impact of the Internet and its implications for health care providers: Findings from the first Health Information National Trends Survey . Archives of Internal Medicine , 165 , 2618 – 2624 .
  • Horrigan , J. , Rainie , L. , & Fox , S. ( 2001 ). Online communities: Networks that nurture long-distance relationships and local ties . Washington , DC : The Pew Charitable Trusts .
  • Institute of Medicine . ( 2004 ). Health literacy: A prescription to end confusion . Washington , DC : The National Academy Press .
  • Kontos , E. Z. , Emmons , K. M. , Puleo , E. , & Viswanath , K. ( 2010 ). Communication inequalities and public health implications of adult social networking site use in the United States . Journal of Health Communication , 15 ( Suppl. 3 ), 216 – 235 .
  • Kutner , M. , Greenberg , E. , Jin , Y. , & Paulsen , C. ( 2006 ). The health literacy of America's adults: Results from the 2003 National Assessment of Adult Literacy . Washington , DC : National Center for Education Statistics .
  • Morie , J. F. , Antonisse , J. , Bouchard , S. , & Chance , E. ( 2009 ). Virtual worlds as a healing modality for returning soldiers and veterans . Studies in Health Technology and Informatics , 144 , 273 – 276 .
  • Murray , E. , Lo , B. , Pollack , L. , Donelan , K. , Catania , J. , et al. . ( 2003 ). The impact of health information on the internet on the physician–patient relationship: Patient perceptions . Archives of Internal Medicine , 163 , 1727 – 1734 .
  • O'Reilly , T. ( 2005 ). What is Web 2.0: Design patterns and business models for the next generation of software . Retrieved April 2011 from http://oreilly.com/web2/archive/what-is-web-20.html .
  • Pew Internet & American Life Project . ( 2009 ). Adults on social network sites, 2005–2009 . Retrieved April 2011 from http://www.pewinternet.org/Infographics/Growth-in-Adult-SNS-Use-20052009.aspx .
  • Pew Internet & American Life Project. ( 2011a , May 2011 ). Trend data. Retrieved May 31, 2011, from http://www.pewinternet.org/Trend-Data/Whos-Online.aspx
  • Pew Internet, & American Life Project . ( 2011b ). Web 2.0. Retrieved May 2011, from http://www.pewinternet.org/topics/Web-20.aspx
  • Rainie , L. ( 2011 ). The rise of the e-patient: Understanding social networks and online health information-seeking . Philadelphia , PA : Pew Charitable Trusts .
  • Rathi , D. , & Given , L. ( 2010 , January 7). Research 2.0: Framework for qualitative and quantitative research in Web 2.0 environments. Paper presented at the 43rd Hawaii International Conference on System Sciences Poipu, Kauai, HI .
  • Richardson , C. R. , Buis , L. R. , Janney , A. W. , Goodrich , D. E. , Sen , A. , et al.. (2010). An online community improves adherence in an Internet-mediated walking program. Part 1: Results of a randomized controlled trial. Journal of Medical Internet Research , 12(4), e71.
  • Risk , A. , & Dzenowagis , J. ( 2001 ). Review of Internet health information quality initiatives . Journal of Medicine Internet Research , 3 ( 4 ), E28 .
  • Roblin , D. W. , Houston , T. K. II , Allison , J. J. , Joski , P. J. , & Becker , E. R. ( 2009 ). Disparities in use of a personal health record in a managed care organization . Journal of the American Medical Informatics Association , 16 , 683 – 689 .
  • Rudd , R. , Moeykens , B. A. , & Colton , T. C. ( 2000 ). Health and literacy: A review of medical and public health literature . In J. Comings , B. Garners , & C. Smith (Eds.), Annual review of adult learning and literacy (pp. 158 – 200 ). New York : Jossey-Bass .
  • Sarkar , U. , Karter , A. J. , Liu , J. Y. , Adler , N. E. , Nguyen , R. , et al. . ( 2011 ). Social disparities in Internet patient portal use in diabetes: Evidence that the digital divide extends beyond access . Journal of American Medical Informatics Association , 18 , 318 – 321 .
  • Singer , E. ( 2010 ). Patients’ social network predicts drug outcomes . Technology Review . Retrieved April 2011 from http://www.technologyreview.com/biomedicine/25276/ .
  • Smedley , B. D. , Stith , A. Y. , & Nelson , A. R. ( 2003 ). Unequal treatment: Confronting racial and ethnic disparities in health care . Washington , DC : The National Academies Press .
  • Smith , A. ( 2010a ). Home broadband . Philadelphia : Pew Charitable Trusts .
  • Smith , A. ( 2010b ). Mobile access . Philadelphia : Pew Charitable Trusts .
  • Smith , A. ( 2010c ). Technology trends among people of color . Philadelphia : Pew Charitable Trusts .
  • Smith , A. ( 2011 ). Who's on what: Social media trends among communities of color. Webinar Presentation for California Immunization Coalition on January 25, 2011 .
  • The Huffington Post . ( 2010 ). Smokers turn to social media for help kicking habit. Retrieved April 2011 from http://www.huffingtonpost.com/2010/06/22/smokers-turn-to-social-me_n_617579.html .
  • Van De Belt , T. H. , Engelen , L. J. , Berben , S. A. , & Schoonhoven , L. ( 2010 ). Definition of Health 2.0 and Medicine 2.0: A systematic review . Journal of Medical Internet Research , 12 ( 2 ), e18 .
  • Viswanath , K. ( 2011 ). Cyberinfrastructure: An extraordinary opportunity to bridge health and communication inequalities? American Journal of Preventive Medicine , 40 , S245 – S248 .
  • Viswanath , K. , & Ackerson , L. K. ( 2011 ). Race, ethnicity, language, social class, and health communication inequalities: A nationally-representative cross-sectional study . PLoS One , 6 ( 1 ), e14550 .
  • Wang , J. Y. , Bennett , K. , & Probst , J. ( 2011 ). Subdividing the digital divide: Differences in Internet access and use among rural residents with medical limitations . Journal of Medical Internet Research , 13 ( 1 ), e25 .
  • Weiss , B. D. ( 2007 ). Health literacy and patient safety: Help patients understand . Atlanta , GA : American Medical Association .
  • Weitzel , M. , Smith , A. , de Deugd , S. , & Yates , R. ( 2010 , July). A Web 2.0 model for patient-centered health informatics applications . Computer , 43 , 43 – 50 .
  • Wicks , P. , Vaughan , T. E. , Massagli , M. P. , & Heywood , J. ( 2011 ). Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm . Nature Biotechnology , 29 , 411 – 414 .
  • Wright , A. , Bates , D. , Middleton , B. , Hongsermeier , T. , Kashyap , V. , et al. ., ( 2009 ). Creating and sharing clinical decision support content with Web 2.0: Issues and examples . Journal of Biomedical Informatics , 42 , 334 – 346 .
  • Ybarra , M. L. , & Suman , M. ( 2006 ). Help seeking behavior and the Internet: A national survey . International Journal of Medical Informatics , 75 ( 1 ), 29 – 41 .

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.