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The “Long Tail” and Public Health: New Thinking for Addressing Health Disparities The prevailing approach to improving population health focuses on shifting population means through a few targeted and universal interventions. The success of this approach for eliminating health disparities depends on an assumption about the distribution of demand for such interventions. We explored whether long tail thinking from business might yield greater progress in eliminating disparities. We examined 2011 to 2013 data from 513 state and local health agency representatives in 47 states who used an online system to create 4351 small media and client reminder products promoting colorectal cancer screening. Products in the long tail were more likely to target minority groups with higher rates of colorectal cancer and lower rates of screening than Whites. Long tail thinking could help improve the public’s health and eliminate disparities. (Am J Public Health. 2014;104:2271–2278. doi:10.2105/AJPH.2014.302039)
Matthew W. Kreuter, PhD, MPH, Peter Hovmand, PhD, Debbie J. Pfeiffer, MA, Maggie Fairchild, MPH, Suchitra Rath, MS, Balaji Golla, MS, and Chris Casey, MPH
THE PREVAILING APPROACHES to improving population health emphasize “shifting the mean” through prevention efforts that target large groups at high risk or through mass environmental control interventions that encourage small but universal changes in individual behavior.1 This approach has led to the search for “blockbuster” public health interventions that can have the largest effects on determinants of population health and individual behavior. An underlying assumption in both approaches is that prevention opportunities tend to focus on a few groups or a generalized public. The implication is that people falling outside this limited number of groups either collectively have a small impact on population health or can effectively be lumped into one of the larger groups. In popular terms, we often see this as the “80/20” rule, in which 80% of a problem can be solved by understanding and solving 20% of the cases. Whether this holds for population health and the elimination of health disparities depends on understanding the shape of the underlying distribution of prevention opportunities. In a compelling critique, Frohlich and Potvin argue that the prevailing population approach may have the unintended consequence of exacerbating health disparities.2 Disease risk, they point out, varies not just by behavioral risk factors but also by socially defined groups that vary in their exposure to fundamental risks, for example, low
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education and low socioeconomic status. Broadly targeted population interventions that focus primarily on behavioral determinants may not be as effective under these conditions or with these groups. Frohlich and Potvin propose that population approaches be complemented by a “vulnerable subgroups” approach that is intersectoral to address core risks that lie outside the realm of health and that is participatory to involve vulnerable groups in developing appropriate, population-specific solutions. We have considered whether long tail thinking applied to public health might lead to vulnerable subgroup approaches that yield greater progress in reducing health disparities. Long tailed thinking stems from new business models that recognize that selling small quantities of many niche items can be more profitable than is selling a few blockbuster items. In The Long Tail, Anderson’s bestselling book on the future of business, he argues that (1) niche markets—subsets of consumers interested in particular products— are more accessible today than ever, and (2) although the demand for any given niche-focused product will be limited, there are so many niches that collectively these products make up a huge market.3 In business, the term “long tail” refers to a distribution of product sales in which a few products in the head of the distribution are blockbuster successes that have widespread appeal and generate
substantial sales, followed by a much greater number of niche products that each have narrower appeal and generate only nominal sales (i.e., the long tail of the distribution; Figure 1). Anderson demonstrates that in many cases this long tail of niche products generates sales and profits that rival those of products with mass appeal and explains how new thinking and new technologies make it possible to realize these profits. Understanding how and why businesses profit from this long tail of niche products has the potential to transform our thinking about strategies to improve the public’s health. Its implications are particularly profound for helping reduce health disparities—the inequalities in health outcomes that disproportionately affect a long and diverse “tail” of “niche” populations whose needs may not be adequately addressed by approaches designed for the general population. Focusing collectively on the universe of disparity niches may yield significant population health benefits. But it would also require new approaches and new tools, as the economies of scale in distributing a few products to many people are lost. We have described the long tail perspective, examined how its key tenets apply to public health using 2011 to 2013 data from a national online health communication system, and discussed the implications of both for public health.
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THE LONG TAIL AND PUBLIC HEALTH Anderson studied consumer economics, focusing on usage and sales patterns in media and entertainment companies such as iTunes, Netflix, eBay, Amazon, and Google. He observed, for example, that in the online music industry more than half of the inventory sold ranked below the top 5000 sellers, and many songs were downloaded by only a few people per week worldwide. Similarly, in a superstore bookseller, half of the top 10 000 books sold fewer than 1 copy per quarter. It would be unprofitable, if not physically impossible, for a bricksand-mortar store in 1 community to stock a music collection as extensive as a store that exists digitally online. The store could not generate enough local demand for songs in the long tail to justify keeping them in stock or devoting shelf space to them. But online, with digital inventory and access to customers everywhere not just in 1 community, there are no such constraints. Anderson and others showed that when consumers were given easy ways to find the niches that matched their interests, sales of niche products (collectively) could rival that of blockbuster hits.4 Although the Internet is invaluable in facilitating the distribution
of niche products, successful long tail businesses also make it easy for consumers to find niche products. In particular, filters, recommendation systems, and ratings help consumers navigate the universe of products in the long tail.5,6 For example, long tail businesses such as iTunes, Netflix, and Amazon use recommendation engines driven by pattern matching to help consumers discover niche products they might like and user ratings and reviews to amplify word of mouth about those products. The opportunity to sample an unfamiliar niche product before buying it—listen to part of a song, read a chapter from a book, watch an episode of a TV series—also lowers the consumer risk for trying it. Finally, the ability to customize a product to a single user’s needs or preferences can increase its appeal. Together, these strategies for connecting the supply of and demand for niche products are increasing user satisfaction and expanding the appeal and market share of niche products.5,7 As Anderson summarizes, the keys to a successful long tail business are “(1) make everything available; (2) help me find it.”3(p217) Similarly, we can think of health messages, campaigns, or other interventions as niche products targeted to specific population
Popularity
Blockbusters Long tail
Products
FIGURE 1—The long tail of niche-targeted products: 2011–2013.
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subgroups, particularly those affected by health disparities that bear a disproportionate burden of disease because of heightened exposure to a particular risk or unequal access to a beneficial or health-promoting resource. A general list of such subgroups might include some racial/ethnic minorities, populations with low income or low education, and those without health insurance. But the number and complexity of subgroups—niche markets in long tail terms—increases exponentially when considering how myriad maladies or preventive services uniquely affect different population subgroups. From this perspective, niche-specific solutions might be needed for groups as diverse as Alaska natives aged 50 years and older, low-income pregnant women, parents of children with asthma, Hispanic girls and young women, migrant farm workers in rural communities, women with a family history of breast cancer, and thousands of other permutations of demographic, geographic, psychographic, and health status risk factors. The idea of creating effective and audience-appropriate health resources for a near-infinite number of combinations of subgroups and health issues is daunting. At a national level, there are occasional examples of blockbuster approaches designed to have wide reach and mass appeal across many audience subgroups. More commonly though, funding is dispersed to and used by local agencies to implement smaller, targeted efforts. Yet funds distributed across localities are not limitless and will eventually run out before the needs of some subgroups can be addressed. This is true in part because there are no economies of scale for local agencies to address niches, to say
nothing of an agency’s capacity to create from scratch effective niche-specific solutions. Most importantly, what if niche populations do not benefit from general population or broadly targeted approaches as much as do other groups? Might this approach inadvertently exacerbate inequalities in health knowledge that contribute to health disparities? Decades of research examining the knowledge gap hypothesis8 suggest it could.9---11 Instead, might a long tail approach that also makes available niche-specific resources for a wide range of disparity subgroups have greater impact on population health and health disparities? To consider this possibility, we examined key tenets of long tail thinking in the context of health communication and vulnerable niche populations using national data from users of the Make It Your Own (MIYO) system.
MAKE IT YOUR OWN MIYO is an online tool that helps users create their own versions of evidence-based health communication materials for the specific populations they serve. Users “build” these materials by choosing from a menu of evidence-based approaches recommended by the Guide to Community Preventive Services12 then customize them by choosing from a library of images, messages, and graphic designs.13 MIYO then renders their creations into electronic documents that can be printed, e-mailed, texted, used online, or distributed in other ways to target audiences. MIYO fits the long tail model because its component parts—the images, messages, and graphic designs used for customization—were selected to appeal not just to mass
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audiences but also to niche populations that experience a disproportionate burden of health problems. Depending on the choices a user makes, MIYO can create a vast number of niche-targeted information resources, for example, spiritually based communications for African American women aged 40 years and older, Spanish-language communications for Hispanic men with busy lives, or hopeful communications for low-income single White mothers in rural United States. By studying the choices that actual MIYO users have made, we can better understand the extent to which a long tail of niche options is necessary (i.e., in demand) in public health and whether public health products in the long tail are more likely than are the blockbuster hits to reach populations most affected by health disparities.
from 370 organizations in 47 states, the District of Columbia, and Ontario, Canada, registered to use MIYO. They represented CRCCP grantee organizations (n = 187; 36% of all users) or partners of CRCCP grantees (n = 123; 24%) or were unaffiliated with CRCCPs but heard about MIYO through word of mouth (n = 203; 40%). Collectively they used MIYO to create 4351 small media or client reminders that were rendered into digital documents for distribution. Of these, detailed data were available about the contents of 905 of the documents. We examined the types and attributes of small media and client reminder documents created. The unit of analysis is the document, and the sample size is 4351 for analyses of document type and 905 for analyses of document attributes.
METHODS Data The test case for these analyses is a MIYO module for promoting colorectal cancer (CRC) screening. In July 2009, the US Centers for Disease Control and Prevention established the Colorectal Cancer Control Program (CRCCP), which funds states and tribal organizations to increase population screening rates to 80% by 2014.14 The CRCCPs are encouraged to promote screening using evidencebased approaches such as small media and client reminders from the Guide to Community Preventive Services.14--16 To assist grantees in using these strategies, they were given access to the MIYO CRC module, which was designed with their input through needs expressed in 2 national surveys.17
Sample From March 2011 through February 2013, 513 individuals
In MIYO’s CRC module, users choose from 24 design alternatives for 6 different types of small media and client reminders. Next they customize the design by choosing from a subset of images (from a library of 447 images) and messages (from a library of 350 messages, 100 in Spanish). To simplify the search task, evidence-based strategies are organized by type of small media (flyers, inserts, posters, question cards) and client reminders (postcards, text messages), and users can narrow their design choices with filters for image type (American Indian/Alaska Native [AI/AN], African American, Asian, natives of India, White, Hispanic/Latino, multiple race/ethnicity, women, men, rural, medical personnel, couples, family, faith, work, symbols of faith, older than 65 years)
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and message theme (family, family history, role model, busy lives, embarrassment, afraid, aged 50 years or older, doctor, health care provider, screen, test, colon, testimonial, community, Spanish, AI/AN). This filtering is made possible by tagging each image and message with labels corresponding to different image types and message themes. Because MIYO records the design, image, and message choices for documents created within the system, we can view the distribution of these choices and the corresponding tags to examine their long tail properties.
Analyses We aimed to answer 2 questions. (1) Do the products created in MIYO reflect a long tail distribution? (2) If so, are the products in the long tail more likely to target niche populations with lower rates of screening or higher rates of incidence and mortality from CRC than do products found in the head and middle of the distribution? We answered the first question in 2 stages. First, we showed the distribution of MIYO creations across the 24 design alternatives of small media and client reminders. According to Anderson the long tail is fractal, meaning that no matter at what level you examine it, it still looks like a long tail.3 To examine this microstructure, a second stage of analysis shows the distribution of images and messages selected for the most commonly created design alternative from stage 1. To answer the second question, we examined the contents of 905 MIYO documents, specifically the race/ethnicity of the images chosen by users. We combined all documents that used the same image and ordered them in
a distribution from the most to least frequently used images. We then identified subgroups with rates of CRC screening that were lower than the US average, CRC incidence or mortality rates higher than the US averages, or 5-year CRC survival rates lower than the US average.18---20 These included African Americans, Asian/Pacific Islanders, AI/ANs, and Hispanics; we considered these groups at higher risk for CRC disparities. Using the descriptive tags associated with each MIYO image, we determined whether an image targeted high-risk population subgroups and whether the proportion of such images varied from the head to middle to tail of the distribution. We have reported the number, proportion, and diversity of high-risk populations targeted in each tercile of the distribution.
RESULTS Analyses indicated both a long tail distribution of MIYO products and disproportionate targeting of high-risk minority groups in the long tail.
Long Tail Distribution During the 18-month observation period, users created 4351 small media and client reminders using MIYO and rendered them into digital documents. Figure 2 shows the number of times each of the 24 document types was created. Each document type is represented by a column on the x-axis and is a distinct combination of evidence-based strategy (small media or client reminder), subtype (e.g., flyer, poster, postcard, insert), and design version. For example, the leftmost column represents the most popular small media document that was created and rendered 761 times, accounting for 17% of all documents created.
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Targeting High-Risk Populations in the Long Tail Every MIYO document includes a user-selected image. By examining the specific contents of 905 small media and client reminder documents created in MIYO, we found that users
a 800 700
Documents
600 500
24 docments types 4351 documents created
400 300 200 100 0 Most popular small media document
b 20
Image Uses
15
10
76 images used 223 times
5
0
c 35 30
Message Uses
Of the 24 document types, the top 3 accounted for 39% of all documents created, and the top 8 accounted for 72% of documents. By contrast, each of the remaining 16 document types accounted for only a minimal proportion of all created (< 1%---5%), although collectively they made up more than one quarter (28%) of the total. In further analysis we found that users customized the most commonly created small media document with some combination of 76 different images and 61 different messages (Figure 2). Of the 76 images, the 5 most popular choices accounted for more than one quarter (27%) of all documents created. By contrast, there were 28 images chosen only once, 13 chosen twice, and 19 chosen just 3 times. Together these 60 images in the long tail accounted for more than half (52%) of the flyers made. Of the 61 messages, the 5 most popular choices accounted for more than one third (35%) of all flyers created, roughly the same as the proportion accounted for by the 44 least commonly chosen messages. In past research we introduced a metric of the value MIYO added over a 1 size fits all approach.21 Applying it here, we found that 158 different combinations of message and image were selected by users creating this document; 81% of these were created by 1 organization only; and 94% of documents used a different combination than the most commonly occurring combination.
25 20 15
61 messages used 223 times
10 5 0
FIGURE 2—Long tails in colorectal cancer screening small media and client reminders by (a) documents created using Make It Your Own, (b) images used in the most popular small media document, and (c) messages used in the most popular small media document: 2011–2013.
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DISCUSSION As predicted by long tail thinking, a few of MIYO’s health information products had wide appeal, with many organizations from across the United States choosing the same designs, images, or messages to promote CRC screening. Less widely popular, but far greater in number, was
a diverse range of products promoting CRC screening, each created by only 1 or 2 organizations. The latter accounted for a proportion of total products that was equivalent to or greater than that of the blockbuster hits. More importantly, these less commonly
selected resources in the long tail were significantly more likely to target racial and ethnic minority groups with a greater need for CRC screening. In The Long Tail, Anderson observed, “If you offer people a choice of ten things, they will
choose one of the ten. If you offer them a thousand things, demand will be less concentrated in the top ten.”3(p135) Correspondingly, if public health agencies can only develop a select number of solutions to improve CRC screening (or address any other population
35 30
Image Uses
selected 235 different images. Using a tercile split, we divided the frequency distribution of these images into 3 sections reflecting the head, middle, and tail of the distribution (Figure 3). In the head, 27 different images accounted for 339 total documents (i.e., each image was used an average of 12---13 times); in the middle, 57 images accounted for 292 documents (5 uses per image); in the long tail, 151 images accounted for 274 documents (< 2 uses per image). Compared with the head and middle of the distribution, the tail included images targeting a greater number of racial/ethnic groups and groups at higher risk for CRC and had a higher proportion of images that targeted these high-risk groups (Figure 3). In the head of the distribution, a majority of the images selected targeted Whites (52%), whereas the remainder was split among 3 racial/ethnic minority groups classified as high risk. In the middle of the distribution, images targeted 5 different groups. Whites were targeted in 35% of images, whereas 4 high-risk racial or ethnic minority groups accounted for the remaining 65% of documents. In the tail, only 25% of images targeted Whites, 6 different racial/ethnic groups were represented, of which 4 were classified as at high risk for CRC.
25 20
235 images used 905 times
15 10 5 0
Tercile Split of Distribution
Race/Ethnicity of Images*
Head
Middle
Tail
% White
52
35
25
% African America
19
28
32
% Hispanic
22
16
6
% American Indian/Alaska Native
7
18
24
% Asian/Pacific Islander
0
4
11
% Indian
0
0
1
Distinct images used
27
57
151
Total documents created
339
292
274
Mean documents created per image
12.6
5.1
1.8
Small Media and Client Reminders
*P < .005 (n = 235; v2 = 25.9; df = 10).
FIGURE 3—Race/ethnicity of images used in Make It Your Own documents by head, middle, and long tail of the distribution: 2011–2013.
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health need), it is reasonable to assume that many niche populations would not be a central focus of those efforts. This is not so much a criticism of current practices as it is recognition of their inherent limitations. Just as a single store in St. Louis, Missouri, cannot possibly stock every DVD movie that local consumers might want to watch, neither can most local, state, or even national health organizations create distinctive interventions or information products for every population they serve. Yet our analyses of MIYO usage showed that when many choices were available, organizations indeed chose and created a broad range of small media and client reminders. Without a centralized source of proven public health solutions that can be customized for diverse niche populations, we rely on local organizations, often focused on particular population subgroups, to create audience-appropriate solutions for the groups’ members. Although these organizations may be uniquely positioned to understand a specific target population, the smaller the niche, the less likely it is that they will have the funding, capacity, and infrastructure to execute and deliver solutions, at least relative to larger organizations. There are at least 2 potential challenges with expecting them to fill this role. First, many organizations will lack the technical expertise, experience, or tools to carry out certain solutions effectively. In a survey of state and local public health agencies, both reported needing more and better quality health information materials, but the need was significantly greater among the local agencies.16 Second, because there are few established mechanisms for networked
sharing among niche-serving organizations, many may be duplicating effort by creating similar solutions without the benefit of learning or seeing how others like them across the nation are handling a similar challenge. For example, 1 study identified 116 different types of printed cancer education materials that targeted African Americans21,22; local, state, or national organizations had created them all. Another study found that 69% of state and local cancer control planners reported that they had developed their own programs in the past 12 months.23 Thus the current approach to creating many population-specific and disparity-focused public health solutions often relies on passionate but resource-poor organizations with a limited technical repertoire and uses their precious resources inefficiently. Even if this model was effective, it is highly questionable that public health systems can afford or sustain it. How can we help local agencies do this important work more effectively and efficiently? Public health leaders should consider developing systems that make better use of existing technology to help local agencies adopt, adapt, and deliver proven solutions to pressing problems. A key aspect of companies being able to take advantage of the long tail is developing the technology for efficiently helping customers find the products within their niche and distributing the products to the customers. Amazon and Netflix do this by having online reviews and rating systems and automated ordering and shipping systems using warehouses strategically placed near their markets. Having a central hub of solutions reduces labor costs at an organizational level and
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allows more rapid spread and implementation of new products. Technology also is changing the producer---user relationship by allowing cocreation of products and solutions, like customization of a core product for use in different contexts.24 Establishing feedback loops that share promising nichefocused solutions among a community of users can help drive demand for specially targeted products. Such an approach could help address barriers to accessing health information that contribute to health disparities. The MIYO data we analyzed for this study come from a large and national sample of state and local organizations whose public health responsibilities include outreach, education, and communication. This is the first time, to our knowledge, that data from MIYO users have been examined and reported on in this much detail, and our analysis reveals what Anderson calls “the natural shape of demand”3(p53) without the bias of limited choice. When given a wide range of options, it seems clear that these organizations will use them. We cannot say, on the basis of this analysis, whether a more diverse range of products will be more effective than a less diverse one, but our results certainly reflect what practitioners believe will be most effective for the populations they serve. Use of these data has clear limitations. They demonstrate only 1 problem (CRC screening) that is relevant to only some population subgroups (adults aged 50 years and older). Although we expect the general pattern of findings would apply to other problems and populations, it has not been demonstrated. In addition, the specific solutions users create—small media and client reminders—are information and
communication products that can easily be generated and transmitted in digital form. Although such products can be an important part of disparity-reducing strategies, alone they will be insufficient. It is worth exploring, therefore, whether a long tail approach could work for other evidence-based public health solutions as well (e.g., policies, campaigns, social marketing, behavioral interventions, worksite and school-based programs, point-of-decision prompts, provider assessment and feedback, home visitation education, training). For example, users might choose from and adapt model tobacco policies. We would expect heterogeneity of demand and political feasibility for the scores of different policies. Some, such as workplace bans or point-of-sale restrictions may have wider appeal than do more narrowly focused policies such as restrictions in Section 8 public housing or on college campuses. Yet even within these policies there is likely important variability (e.g., by type of workplace) across potential adopters. A long tail solution could accommodate such diversity. At the same time, there are many public health challenges that require environmental, social, or political solutions that digital products and information alone cannot provide. We must guard against the potential unintended consequence that a solution such as MIYO might create a false sense of security that health disparities have been adequately addressed. Although our focus in this analysis was on users’ selection of images representing different racial/ethnic groups, we found similarly interesting patterns in users’ choices of messages. For
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example, a closer examination of message content for the small media document described in Figure 2 showed that nearly 30% of messages in the long tail addressed either faith (11%), American Indian culture (10%), or embarrassment (8%), whereas no messages from these categories appeared in the head of the distribution. Similarly, message themes of family and busy lives accounted for 87% of messages in the head of the distribution but only 51% in the long tail. These data suggest that nichetargeted interventions in MIYO were not built simply by putting an ethnic face on a generic message but rather by custom combinations of image and content. An alternative explanation for the findings shown in Figure 3 is that the proportion of MIYO creations that target each racial/ ethnic group simply reflects the image choices that are available in MIYO. But this was not the case. Images of Whites make up 29% of the MIYO image library but accounted for 42% of all documents created. Moreover, the proportions of all available images that at least 1 MIYO user selected for use were very similar across groups: Whites (72 of 124 images; 58%), African Americans (69 of 121; 57%), Hispanics (24 of 38; 63%), and AI/ANs (48 of 80; 60%). In other words, the differences were not so much in the number of different products created for each target population but rather where they appeared in the distribution—that is, how many organizations chose them. The exception to this, a relatively higher proportion of Latino images in the head of the distribution, likely reflects the smaller number of such images to
choose from, thus the most popular of these were selected repeatedly. On the surface, it may seem like we are advocating a high-risk versus population approach, in Geoffrey Rose’s classic sense of the distinction.25 But Anderson is clear that successful long tail businesses “need to have both hits and niches,”3(p148) with hits drawing masses of customers who will then become exposed to niches. Likewise, Frolich and Potvin insist their vulnerable population approach would complement, not replace, a population approach.2 The latter seeks to change broad environmental conditions to shift the overall population mean to a lower level of risk exposure; the former is focused on changing social and environmental conditions that uniquely and disproportionately affect exposure to multiple risks among socially defined subgroups. Think of MIYO as a long tail system employing a vulnerable populations approach, albeit one that addresses a relatively simple exposure—lack of access to culturally appropriate and populationspecific health information. Tackling the root causes of health disparities is obviously more complex and cannot be solved with a Web site. Yet the idea that public health might develop a centralized source of evidencebased vulnerable population approaches in which agencies could find and customize nichefocused solutions is a logical extension of this model. Although we are hardly the first to call for a combination of population-wide and vulnerable population strategies, long tail thinking and advances in technology have opened a promising new path to achieve it. j
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About the Authors Matthew W. Kreuter, Debbie J. Pfeiffer, Maggie Fairchild, Suchitra Rath, Balaji Golla, and Chris Casey are with the Health Communication Research Laboratory, Washington University in St. Louis, St. Louis, MO. Peter Hovmand is with The Brown School, Washington University in St. Louis. Correspondence should be sent to Matthew W. Kreuter, PhD, MPH, Health Communication Research Laboratory, Campus Box 1009, Washington University in St. Louis, 700 Rosedale Avenue, St. Louis, MO 63112-1408 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link. This article was accepted March 30, 2014.
Contributors M. W. Kreuter and P. Hovmand conceptualized and outlined the article and wrote the initial draft. D. J. Pfeiffer and M. Fairchild wrote sections of the article and worked with S. Rath, B. Golla, and C. Casey to conceptualize and carry out data analyses and design the information displays. All authors provided critical review on draft, final, and revised versions of the article.
Acknowledgments This research was supported by the National Cancer Institute (grant P50CA095815) and the Centers for Disease Control and Prevention (grant IU48DP001903).
Human Participant Protection The study was judged exempt by the Washington University institutional review board.
References 1. Rose G. Sick individuals and sick populations. Int J Epidemiol. 1985;14 (1):32---38. 2. Frohlich KL, Potvin L. Transcending the known in public health practice. Am J Public Health. 2008;98(2):216---221. 3. Anderson C. The Long Tail: Why the Future of Business Is Selling Less of More. 2nd ed. New York, NY: Hyperion; 2008. 4. Brynjolfsson E, Hu Y, Simester D. Goodbye Pareto principle, hello long tail: the effect of search costs on the concentration of product sales. Manage Sci. 2011;57(8):1373---1386. 5. Oestreicher-Singer G, Sundararajan A. Recommendation networks and the long tail of electronic commerce. 2010. Available at: http://papers.ssrn.com/ sol3/papers.cfm?abstract_id=1324064. Accessed July 1, 2014.
6. Goel S, Broder A, Gabrilovich E, Pang B. Anatomy of the long tail: ordinary people with extraordinary tastes. Paper presented at: The Proceedings of the Third ACM International Conference on Web Search and Data Mining; February 3---6, 2010; New York, NY. 7. Tichenor PJ, Olien CN, Harrison A, Donohue G. Mass communication systems and communication accuracy in science news reporting. Journal Q. 1970; 47(4):673---683. 8. Gaziano C. The knowledge gap: an analytical review of media effects. Communic Res. 1983;10(4):447---486. 9. Gaziano C. Forecast 2000: widening knowledge gaps. Journalism Mass Commun Q. 1997;74(2):237---264. 10. Hwang Y, Jeong S-H. Revisiting the knowledge gap hypothesis: a metaanalysis of thirty-five years of research. Journalism Mass Commun Q. 2009;86 (3):513---532. 11. US Centers for Disease Control and Prevention. The community guide to preventive services. Available at: http:// www.thecommunityguide.org/cancer/ screening/client-oriented/index.html. Accessed April 22, 2013. 12. Kreuter MW, Fernandez ME, Richert M, et al. Increasing informationseeking about HPV vaccination through community partnerships in African American and Hispanic communities. Fam Community Health. 2012;35(1): 15---30. 13. Joseph DA, DeGroff AS, Hayes NS, Wong FL, Plescia M. The Colorectal Cancer Control Program: partnering to increase population level screening. Gastrointest Endosc. 2011;73(3): 429---434. 14. Baron RC, Rimer BK, Coates RJ, et al. Client-directed interventions to increase community access to breast, cervical, and colorectal cancer screening: a systematic review. Am J Prev Med. 2008;35(1):S56--S66. 15. Task Force on Community Preventive Services. Recommendations for client- and provider-directed interventions to increase breast, cervical, and colorectal cancer screening. Am J Prev Med. 2008;35(1 suppl): S21---S25. 16. Kreuter MW, Garibay L, Pfeiffer D, et al. Small media and client reminders for colorectal cancer screening: current use and gap areas in CDC’s Colorectal Cancer Control Program. Prev Chronic Dis. 2012;9:E131. 17. Centers for Disease Control and Prevention. Colorectal cancer screening— United States, 2002, 2004, 2006, and 2008. MMWR Surveill Summ. 2011;60 (suppl 1):S42---S46.
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18. Howlader N, Noone AM, Krapcho M, et al. SEER cancer statistics review, 1975---2009. 2012. Available at: http://seer.cancer.gov/csr/1975_ 2009_pops1909. Accessed April 22, 2013. 19. Ries LAG, Young JL, Keel GE, et al. SEER survival monograph: cancer survival among adults: US SEER program, 1988---2001, patient and tumor characteristics. Bethesda, MD: National Cancer Institute; 2007. NIH publication 07---6215. 20. Kreuter MW, Fernandez M, Richert M, et al. Increasing information-seeking about HPV vaccination through community partnerships in African American women. Fam Community Health. 2011; 35(1):1---16. 21. Guidry JJ, Fagan P. The readability levels of cancer-prevention materials targeting African Americans. J Cancer Educ. 1997;12(2):108---113. 22. Guidry JJ, Fagan P, Walker V. Cultural sensitivity and readability of breast and prostate printed cancer education materials targeting African Americans. J Natl Med Assoc. 1998; 90(3):165---169. 23. Hannon PA, Fernandez ME, Williams R, et al. Cancer control planners’ perceptions and use of evidence-based programs. J Public Health Manag Pract. 2010;16(3):E1---E8. 24. Prahalad CK, Ramaswamy V. Cocreation experiences: the next practice in value creation. J Interact Market. 2004;18(3):5---14. 25. Rose G. Reiteration: sick individuals and sick populations. Int J Epidemiol. 2001;30(3):427---432.
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The “Long Tail” and Public Health: New Thinking for Addressing Health Disparities The prevailing approach to improving population health focuses on shifting population means through a few targeted and universal interventions. The success of this approach for eliminating health disparities depends on an assumption about the distribution of demand for such interventions. We explored whether long tail thinking from business might yield greater progress in eliminating disparities. We examined 2011 to 2013 data from 513 state and local health agency representatives in 47 states who used an online system to create 4351 small media and client reminder products promoting colorectal cancer screening. Products in the long tail were more likely to target minority groups with higher rates of colorectal cancer and lower rates of screening than Whites. Long tail thinking could help improve the public’s health and eliminate disparities. (Am J Public Health. 2014;104:2271–2278. doi:10.2105/AJPH.2014.302039)
Matthew W. Kreuter, PhD, MPH, Peter Hovmand, PhD, Debbie J. Pfeiffer, MA, Maggie Fairchild, MPH, Suchitra Rath, MS, Balaji Golla, MS, and Chris Casey, MPH
THE PREVAILING APPROACHES to improving population health emphasize “shifting the mean” through prevention efforts that target large groups at high risk or through mass environmental control interventions that encourage small but universal changes in individual behavior.1 This approach has led to the search for “blockbuster” public health interventions that can have the largest effects on determinants of population health and individual behavior. An underlying assumption in both approaches is that prevention opportunities tend to focus on a few groups or a generalized public. The implication is that people falling outside this limited number of groups either collectively have a small impact on population health or can effectively be lumped into one of the larger groups. In popular terms, we often see this as the “80/20” rule, in which 80% of a problem can be solved by understanding and solving 20% of the cases. Whether this holds for population health and the elimination of health disparities depends on understanding the shape of the underlying distribution of prevention opportunities. In a compelling critique, Frohlich and Potvin argue that the prevailing population approach may have the unintended consequence of exacerbating health disparities.2 Disease risk, they point out, varies not just by behavioral risk factors but also by socially defined groups that vary in their exposure to fundamental risks, for example, low
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education and low socioeconomic status. Broadly targeted population interventions that focus primarily on behavioral determinants may not be as effective under these conditions or with these groups. Frohlich and Potvin propose that population approaches be complemented by a “vulnerable subgroups” approach that is intersectoral to address core risks that lie outside the realm of health and that is participatory to involve vulnerable groups in developing appropriate, population-specific solutions. We have considered whether long tail thinking applied to public health might lead to vulnerable subgroup approaches that yield greater progress in reducing health disparities. Long tailed thinking stems from new business models that recognize that selling small quantities of many niche items can be more profitable than is selling a few blockbuster items. In The Long Tail, Anderson’s bestselling book on the future of business, he argues that (1) niche markets—subsets of consumers interested in particular products— are more accessible today than ever, and (2) although the demand for any given niche-focused product will be limited, there are so many niches that collectively these products make up a huge market.3 In business, the term “long tail” refers to a distribution of product sales in which a few products in the head of the distribution are blockbuster successes that have widespread appeal and generate
substantial sales, followed by a much greater number of niche products that each have narrower appeal and generate only nominal sales (i.e., the long tail of the distribution; Figure 1). Anderson demonstrates that in many cases this long tail of niche products generates sales and profits that rival those of products with mass appeal and explains how new thinking and new technologies make it possible to realize these profits. Understanding how and why businesses profit from this long tail of niche products has the potential to transform our thinking about strategies to improve the public’s health. Its implications are particularly profound for helping reduce health disparities—the inequalities in health outcomes that disproportionately affect a long and diverse “tail” of “niche” populations whose needs may not be adequately addressed by approaches designed for the general population. Focusing collectively on the universe of disparity niches may yield significant population health benefits. But it would also require new approaches and new tools, as the economies of scale in distributing a few products to many people are lost. We have described the long tail perspective, examined how its key tenets apply to public health using 2011 to 2013 data from a national online health communication system, and discussed the implications of both for public health.
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THE LONG TAIL AND PUBLIC HEALTH Anderson studied consumer economics, focusing on usage and sales patterns in media and entertainment companies such as iTunes, Netflix, eBay, Amazon, and Google. He observed, for example, that in the online music industry more than half of the inventory sold ranked below the top 5000 sellers, and many songs were downloaded by only a few people per week worldwide. Similarly, in a superstore bookseller, half of the top 10 000 books sold fewer than 1 copy per quarter. It would be unprofitable, if not physically impossible, for a bricksand-mortar store in 1 community to stock a music collection as extensive as a store that exists digitally online. The store could not generate enough local demand for songs in the long tail to justify keeping them in stock or devoting shelf space to them. But online, with digital inventory and access to customers everywhere not just in 1 community, there are no such constraints. Anderson and others showed that when consumers were given easy ways to find the niches that matched their interests, sales of niche products (collectively) could rival that of blockbuster hits.4 Although the Internet is invaluable in facilitating the distribution
of niche products, successful long tail businesses also make it easy for consumers to find niche products. In particular, filters, recommendation systems, and ratings help consumers navigate the universe of products in the long tail.5,6 For example, long tail businesses such as iTunes, Netflix, and Amazon use recommendation engines driven by pattern matching to help consumers discover niche products they might like and user ratings and reviews to amplify word of mouth about those products. The opportunity to sample an unfamiliar niche product before buying it—listen to part of a song, read a chapter from a book, watch an episode of a TV series—also lowers the consumer risk for trying it. Finally, the ability to customize a product to a single user’s needs or preferences can increase its appeal. Together, these strategies for connecting the supply of and demand for niche products are increasing user satisfaction and expanding the appeal and market share of niche products.5,7 As Anderson summarizes, the keys to a successful long tail business are “(1) make everything available; (2) help me find it.”3(p217) Similarly, we can think of health messages, campaigns, or other interventions as niche products targeted to specific population
Popularity
Blockbusters Long tail
Products
FIGURE 1—The long tail of niche-targeted products: 2011–2013.
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subgroups, particularly those affected by health disparities that bear a disproportionate burden of disease because of heightened exposure to a particular risk or unequal access to a beneficial or health-promoting resource. A general list of such subgroups might include some racial/ethnic minorities, populations with low income or low education, and those without health insurance. But the number and complexity of subgroups—niche markets in long tail terms—increases exponentially when considering how myriad maladies or preventive services uniquely affect different population subgroups. From this perspective, niche-specific solutions might be needed for groups as diverse as Alaska natives aged 50 years and older, low-income pregnant women, parents of children with asthma, Hispanic girls and young women, migrant farm workers in rural communities, women with a family history of breast cancer, and thousands of other permutations of demographic, geographic, psychographic, and health status risk factors. The idea of creating effective and audience-appropriate health resources for a near-infinite number of combinations of subgroups and health issues is daunting. At a national level, there are occasional examples of blockbuster approaches designed to have wide reach and mass appeal across many audience subgroups. More commonly though, funding is dispersed to and used by local agencies to implement smaller, targeted efforts. Yet funds distributed across localities are not limitless and will eventually run out before the needs of some subgroups can be addressed. This is true in part because there are no economies of scale for local agencies to address niches, to say
nothing of an agency’s capacity to create from scratch effective niche-specific solutions. Most importantly, what if niche populations do not benefit from general population or broadly targeted approaches as much as do other groups? Might this approach inadvertently exacerbate inequalities in health knowledge that contribute to health disparities? Decades of research examining the knowledge gap hypothesis8 suggest it could.9---11 Instead, might a long tail approach that also makes available niche-specific resources for a wide range of disparity subgroups have greater impact on population health and health disparities? To consider this possibility, we examined key tenets of long tail thinking in the context of health communication and vulnerable niche populations using national data from users of the Make It Your Own (MIYO) system.
MAKE IT YOUR OWN MIYO is an online tool that helps users create their own versions of evidence-based health communication materials for the specific populations they serve. Users “build” these materials by choosing from a menu of evidence-based approaches recommended by the Guide to Community Preventive Services12 then customize them by choosing from a library of images, messages, and graphic designs.13 MIYO then renders their creations into electronic documents that can be printed, e-mailed, texted, used online, or distributed in other ways to target audiences. MIYO fits the long tail model because its component parts—the images, messages, and graphic designs used for customization—were selected to appeal not just to mass
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audiences but also to niche populations that experience a disproportionate burden of health problems. Depending on the choices a user makes, MIYO can create a vast number of niche-targeted information resources, for example, spiritually based communications for African American women aged 40 years and older, Spanish-language communications for Hispanic men with busy lives, or hopeful communications for low-income single White mothers in rural United States. By studying the choices that actual MIYO users have made, we can better understand the extent to which a long tail of niche options is necessary (i.e., in demand) in public health and whether public health products in the long tail are more likely than are the blockbuster hits to reach populations most affected by health disparities.
from 370 organizations in 47 states, the District of Columbia, and Ontario, Canada, registered to use MIYO. They represented CRCCP grantee organizations (n = 187; 36% of all users) or partners of CRCCP grantees (n = 123; 24%) or were unaffiliated with CRCCPs but heard about MIYO through word of mouth (n = 203; 40%). Collectively they used MIYO to create 4351 small media or client reminders that were rendered into digital documents for distribution. Of these, detailed data were available about the contents of 905 of the documents. We examined the types and attributes of small media and client reminder documents created. The unit of analysis is the document, and the sample size is 4351 for analyses of document type and 905 for analyses of document attributes.
METHODS Data The test case for these analyses is a MIYO module for promoting colorectal cancer (CRC) screening. In July 2009, the US Centers for Disease Control and Prevention established the Colorectal Cancer Control Program (CRCCP), which funds states and tribal organizations to increase population screening rates to 80% by 2014.14 The CRCCPs are encouraged to promote screening using evidencebased approaches such as small media and client reminders from the Guide to Community Preventive Services.14--16 To assist grantees in using these strategies, they were given access to the MIYO CRC module, which was designed with their input through needs expressed in 2 national surveys.17
Sample From March 2011 through February 2013, 513 individuals
In MIYO’s CRC module, users choose from 24 design alternatives for 6 different types of small media and client reminders. Next they customize the design by choosing from a subset of images (from a library of 447 images) and messages (from a library of 350 messages, 100 in Spanish). To simplify the search task, evidence-based strategies are organized by type of small media (flyers, inserts, posters, question cards) and client reminders (postcards, text messages), and users can narrow their design choices with filters for image type (American Indian/Alaska Native [AI/AN], African American, Asian, natives of India, White, Hispanic/Latino, multiple race/ethnicity, women, men, rural, medical personnel, couples, family, faith, work, symbols of faith, older than 65 years)
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and message theme (family, family history, role model, busy lives, embarrassment, afraid, aged 50 years or older, doctor, health care provider, screen, test, colon, testimonial, community, Spanish, AI/AN). This filtering is made possible by tagging each image and message with labels corresponding to different image types and message themes. Because MIYO records the design, image, and message choices for documents created within the system, we can view the distribution of these choices and the corresponding tags to examine their long tail properties.
Analyses We aimed to answer 2 questions. (1) Do the products created in MIYO reflect a long tail distribution? (2) If so, are the products in the long tail more likely to target niche populations with lower rates of screening or higher rates of incidence and mortality from CRC than do products found in the head and middle of the distribution? We answered the first question in 2 stages. First, we showed the distribution of MIYO creations across the 24 design alternatives of small media and client reminders. According to Anderson the long tail is fractal, meaning that no matter at what level you examine it, it still looks like a long tail.3 To examine this microstructure, a second stage of analysis shows the distribution of images and messages selected for the most commonly created design alternative from stage 1. To answer the second question, we examined the contents of 905 MIYO documents, specifically the race/ethnicity of the images chosen by users. We combined all documents that used the same image and ordered them in
a distribution from the most to least frequently used images. We then identified subgroups with rates of CRC screening that were lower than the US average, CRC incidence or mortality rates higher than the US averages, or 5-year CRC survival rates lower than the US average.18---20 These included African Americans, Asian/Pacific Islanders, AI/ANs, and Hispanics; we considered these groups at higher risk for CRC disparities. Using the descriptive tags associated with each MIYO image, we determined whether an image targeted high-risk population subgroups and whether the proportion of such images varied from the head to middle to tail of the distribution. We have reported the number, proportion, and diversity of high-risk populations targeted in each tercile of the distribution.
RESULTS Analyses indicated both a long tail distribution of MIYO products and disproportionate targeting of high-risk minority groups in the long tail.
Long Tail Distribution During the 18-month observation period, users created 4351 small media and client reminders using MIYO and rendered them into digital documents. Figure 2 shows the number of times each of the 24 document types was created. Each document type is represented by a column on the x-axis and is a distinct combination of evidence-based strategy (small media or client reminder), subtype (e.g., flyer, poster, postcard, insert), and design version. For example, the leftmost column represents the most popular small media document that was created and rendered 761 times, accounting for 17% of all documents created.
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Targeting High-Risk Populations in the Long Tail Every MIYO document includes a user-selected image. By examining the specific contents of 905 small media and client reminder documents created in MIYO, we found that users
a 800 700
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24 docments types 4351 documents created
400 300 200 100 0 Most popular small media document
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Of the 24 document types, the top 3 accounted for 39% of all documents created, and the top 8 accounted for 72% of documents. By contrast, each of the remaining 16 document types accounted for only a minimal proportion of all created (< 1%---5%), although collectively they made up more than one quarter (28%) of the total. In further analysis we found that users customized the most commonly created small media document with some combination of 76 different images and 61 different messages (Figure 2). Of the 76 images, the 5 most popular choices accounted for more than one quarter (27%) of all documents created. By contrast, there were 28 images chosen only once, 13 chosen twice, and 19 chosen just 3 times. Together these 60 images in the long tail accounted for more than half (52%) of the flyers made. Of the 61 messages, the 5 most popular choices accounted for more than one third (35%) of all flyers created, roughly the same as the proportion accounted for by the 44 least commonly chosen messages. In past research we introduced a metric of the value MIYO added over a 1 size fits all approach.21 Applying it here, we found that 158 different combinations of message and image were selected by users creating this document; 81% of these were created by 1 organization only; and 94% of documents used a different combination than the most commonly occurring combination.
25 20 15
61 messages used 223 times
10 5 0
FIGURE 2—Long tails in colorectal cancer screening small media and client reminders by (a) documents created using Make It Your Own, (b) images used in the most popular small media document, and (c) messages used in the most popular small media document: 2011–2013.
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DISCUSSION As predicted by long tail thinking, a few of MIYO’s health information products had wide appeal, with many organizations from across the United States choosing the same designs, images, or messages to promote CRC screening. Less widely popular, but far greater in number, was
a diverse range of products promoting CRC screening, each created by only 1 or 2 organizations. The latter accounted for a proportion of total products that was equivalent to or greater than that of the blockbuster hits. More importantly, these less commonly
selected resources in the long tail were significantly more likely to target racial and ethnic minority groups with a greater need for CRC screening. In The Long Tail, Anderson observed, “If you offer people a choice of ten things, they will
choose one of the ten. If you offer them a thousand things, demand will be less concentrated in the top ten.”3(p135) Correspondingly, if public health agencies can only develop a select number of solutions to improve CRC screening (or address any other population
35 30
Image Uses
selected 235 different images. Using a tercile split, we divided the frequency distribution of these images into 3 sections reflecting the head, middle, and tail of the distribution (Figure 3). In the head, 27 different images accounted for 339 total documents (i.e., each image was used an average of 12---13 times); in the middle, 57 images accounted for 292 documents (5 uses per image); in the long tail, 151 images accounted for 274 documents (< 2 uses per image). Compared with the head and middle of the distribution, the tail included images targeting a greater number of racial/ethnic groups and groups at higher risk for CRC and had a higher proportion of images that targeted these high-risk groups (Figure 3). In the head of the distribution, a majority of the images selected targeted Whites (52%), whereas the remainder was split among 3 racial/ethnic minority groups classified as high risk. In the middle of the distribution, images targeted 5 different groups. Whites were targeted in 35% of images, whereas 4 high-risk racial or ethnic minority groups accounted for the remaining 65% of documents. In the tail, only 25% of images targeted Whites, 6 different racial/ethnic groups were represented, of which 4 were classified as at high risk for CRC.
25 20
235 images used 905 times
15 10 5 0
Tercile Split of Distribution
Race/Ethnicity of Images*
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Middle
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% White
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35
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% African America
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% Hispanic
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% American Indian/Alaska Native
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% Asian/Pacific Islander
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% Indian
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339
292
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Mean documents created per image
12.6
5.1
1.8
Small Media and Client Reminders
*P < .005 (n = 235; v2 = 25.9; df = 10).
FIGURE 3—Race/ethnicity of images used in Make It Your Own documents by head, middle, and long tail of the distribution: 2011–2013.
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health need), it is reasonable to assume that many niche populations would not be a central focus of those efforts. This is not so much a criticism of current practices as it is recognition of their inherent limitations. Just as a single store in St. Louis, Missouri, cannot possibly stock every DVD movie that local consumers might want to watch, neither can most local, state, or even national health organizations create distinctive interventions or information products for every population they serve. Yet our analyses of MIYO usage showed that when many choices were available, organizations indeed chose and created a broad range of small media and client reminders. Without a centralized source of proven public health solutions that can be customized for diverse niche populations, we rely on local organizations, often focused on particular population subgroups, to create audience-appropriate solutions for the groups’ members. Although these organizations may be uniquely positioned to understand a specific target population, the smaller the niche, the less likely it is that they will have the funding, capacity, and infrastructure to execute and deliver solutions, at least relative to larger organizations. There are at least 2 potential challenges with expecting them to fill this role. First, many organizations will lack the technical expertise, experience, or tools to carry out certain solutions effectively. In a survey of state and local public health agencies, both reported needing more and better quality health information materials, but the need was significantly greater among the local agencies.16 Second, because there are few established mechanisms for networked
sharing among niche-serving organizations, many may be duplicating effort by creating similar solutions without the benefit of learning or seeing how others like them across the nation are handling a similar challenge. For example, 1 study identified 116 different types of printed cancer education materials that targeted African Americans21,22; local, state, or national organizations had created them all. Another study found that 69% of state and local cancer control planners reported that they had developed their own programs in the past 12 months.23 Thus the current approach to creating many population-specific and disparity-focused public health solutions often relies on passionate but resource-poor organizations with a limited technical repertoire and uses their precious resources inefficiently. Even if this model was effective, it is highly questionable that public health systems can afford or sustain it. How can we help local agencies do this important work more effectively and efficiently? Public health leaders should consider developing systems that make better use of existing technology to help local agencies adopt, adapt, and deliver proven solutions to pressing problems. A key aspect of companies being able to take advantage of the long tail is developing the technology for efficiently helping customers find the products within their niche and distributing the products to the customers. Amazon and Netflix do this by having online reviews and rating systems and automated ordering and shipping systems using warehouses strategically placed near their markets. Having a central hub of solutions reduces labor costs at an organizational level and
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allows more rapid spread and implementation of new products. Technology also is changing the producer---user relationship by allowing cocreation of products and solutions, like customization of a core product for use in different contexts.24 Establishing feedback loops that share promising nichefocused solutions among a community of users can help drive demand for specially targeted products. Such an approach could help address barriers to accessing health information that contribute to health disparities. The MIYO data we analyzed for this study come from a large and national sample of state and local organizations whose public health responsibilities include outreach, education, and communication. This is the first time, to our knowledge, that data from MIYO users have been examined and reported on in this much detail, and our analysis reveals what Anderson calls “the natural shape of demand”3(p53) without the bias of limited choice. When given a wide range of options, it seems clear that these organizations will use them. We cannot say, on the basis of this analysis, whether a more diverse range of products will be more effective than a less diverse one, but our results certainly reflect what practitioners believe will be most effective for the populations they serve. Use of these data has clear limitations. They demonstrate only 1 problem (CRC screening) that is relevant to only some population subgroups (adults aged 50 years and older). Although we expect the general pattern of findings would apply to other problems and populations, it has not been demonstrated. In addition, the specific solutions users create—small media and client reminders—are information and
communication products that can easily be generated and transmitted in digital form. Although such products can be an important part of disparity-reducing strategies, alone they will be insufficient. It is worth exploring, therefore, whether a long tail approach could work for other evidence-based public health solutions as well (e.g., policies, campaigns, social marketing, behavioral interventions, worksite and school-based programs, point-of-decision prompts, provider assessment and feedback, home visitation education, training). For example, users might choose from and adapt model tobacco policies. We would expect heterogeneity of demand and political feasibility for the scores of different policies. Some, such as workplace bans or point-of-sale restrictions may have wider appeal than do more narrowly focused policies such as restrictions in Section 8 public housing or on college campuses. Yet even within these policies there is likely important variability (e.g., by type of workplace) across potential adopters. A long tail solution could accommodate such diversity. At the same time, there are many public health challenges that require environmental, social, or political solutions that digital products and information alone cannot provide. We must guard against the potential unintended consequence that a solution such as MIYO might create a false sense of security that health disparities have been adequately addressed. Although our focus in this analysis was on users’ selection of images representing different racial/ethnic groups, we found similarly interesting patterns in users’ choices of messages. For
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example, a closer examination of message content for the small media document described in Figure 2 showed that nearly 30% of messages in the long tail addressed either faith (11%), American Indian culture (10%), or embarrassment (8%), whereas no messages from these categories appeared in the head of the distribution. Similarly, message themes of family and busy lives accounted for 87% of messages in the head of the distribution but only 51% in the long tail. These data suggest that nichetargeted interventions in MIYO were not built simply by putting an ethnic face on a generic message but rather by custom combinations of image and content. An alternative explanation for the findings shown in Figure 3 is that the proportion of MIYO creations that target each racial/ ethnic group simply reflects the image choices that are available in MIYO. But this was not the case. Images of Whites make up 29% of the MIYO image library but accounted for 42% of all documents created. Moreover, the proportions of all available images that at least 1 MIYO user selected for use were very similar across groups: Whites (72 of 124 images; 58%), African Americans (69 of 121; 57%), Hispanics (24 of 38; 63%), and AI/ANs (48 of 80; 60%). In other words, the differences were not so much in the number of different products created for each target population but rather where they appeared in the distribution—that is, how many organizations chose them. The exception to this, a relatively higher proportion of Latino images in the head of the distribution, likely reflects the smaller number of such images to
choose from, thus the most popular of these were selected repeatedly. On the surface, it may seem like we are advocating a high-risk versus population approach, in Geoffrey Rose’s classic sense of the distinction.25 But Anderson is clear that successful long tail businesses “need to have both hits and niches,”3(p148) with hits drawing masses of customers who will then become exposed to niches. Likewise, Frolich and Potvin insist their vulnerable population approach would complement, not replace, a population approach.2 The latter seeks to change broad environmental conditions to shift the overall population mean to a lower level of risk exposure; the former is focused on changing social and environmental conditions that uniquely and disproportionately affect exposure to multiple risks among socially defined subgroups. Think of MIYO as a long tail system employing a vulnerable populations approach, albeit one that addresses a relatively simple exposure—lack of access to culturally appropriate and populationspecific health information. Tackling the root causes of health disparities is obviously more complex and cannot be solved with a Web site. Yet the idea that public health might develop a centralized source of evidencebased vulnerable population approaches in which agencies could find and customize nichefocused solutions is a logical extension of this model. Although we are hardly the first to call for a combination of population-wide and vulnerable population strategies, long tail thinking and advances in technology have opened a promising new path to achieve it. j
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About the Authors Matthew W. Kreuter, Debbie J. Pfeiffer, Maggie Fairchild, Suchitra Rath, Balaji Golla, and Chris Casey are with the Health Communication Research Laboratory, Washington University in St. Louis, St. Louis, MO. Peter Hovmand is with The Brown School, Washington University in St. Louis. Correspondence should be sent to Matthew W. Kreuter, PhD, MPH, Health Communication Research Laboratory, Campus Box 1009, Washington University in St. Louis, 700 Rosedale Avenue, St. Louis, MO 63112-1408 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link. This article was accepted March 30, 2014.
Contributors M. W. Kreuter and P. Hovmand conceptualized and outlined the article and wrote the initial draft. D. J. Pfeiffer and M. Fairchild wrote sections of the article and worked with S. Rath, B. Golla, and C. Casey to conceptualize and carry out data analyses and design the information displays. All authors provided critical review on draft, final, and revised versions of the article.
Acknowledgments This research was supported by the National Cancer Institute (grant P50CA095815) and the Centers for Disease Control and Prevention (grant IU48DP001903).
Human Participant Protection The study was judged exempt by the Washington University institutional review board.
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