1. Mobile Health Applications for Low Socio-Economic Communities July 2011

3. How can mobile apps be leveraged to combat obesity-related health issues?

4. What apps are currently available to address prevention and remediation of obesity-related health problems? How comprehensive are they?

6. How can A4G play a role in furthering the study of its constituents’ needs and the efficacy of targeted mobile app interventions?

8. Detecon is a global consulting company which unites classic management consulting with a high level of information and telecommunication technology expertise.

11. Superior design and visualization techniques will also expand the appeal and potential benefits of mobile health apps to low literacy and numeracy populations.There is also an opportunity for A4G to broker collaborative efforts among researchers, nonprofits and corporations to develop, promote and distribute applications designed to impact health outcomes among low SES communities.

12. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix

14. In 1990, among states participating in the Behavioral Risk Factor Surveillance System, ten states had a prevalence of obesity less than 10% and no states had prevalence equal to or greater than 15%.

15. In 2009, only one state (Colorado) and the District of Columbia had a prevalence of obesity less than 20%. Thirty-three states had a prevalence equal to or greater than 25%; nine of these states had a prevalence of obesity equal to or greater than 30%.Source: Behavioral Risk Factor Surveillance System, CDC

16. Frame Template 1. Obesity and Nutrition in America The target audience for A4G anti-obesity initiatives are Americans of low SES. Higher obesity rates among this population are due to a variety of complex factors. US Obesity Rate by Income US Obesity Rate by Education US Poverty Rate by Ethnicity 33.8% 32.8% 25.8% 25.3% 31.8% 30.4% 29.6% 29.7% 29.5% 24.6% 21.5% 9.4% >$50k $35k-$50k $25k-$35k $15k-$25k <$15k Some college High school graduate only Did not graduate high school College grad African American White Hispanic Low-income individuals are less likely to have access to affordable, nutritious food. Lower levels of education are associated with both lower SES and poorer understanding of health and nutrition. Poverty is significantly more prevalent among African American and Hispanic communities. US Adult Obesity Rate by Ethnicity US Childhood Obesity Rate by Ethnicity African
American African
American 35.7% 23.9% Hispanic 28.7% Hispanic 23.4% White 23.7% White 13.0% Sources: US Census Bureau 2010; CDC 2011; JAMA 2010; The Trust for America's Health and the Robert Wood Johnson Foundation, 2011

18. Administered by the U.S. Department of Agriculture

19. As of June 2009, the average monthly benefit was $133.12 per person

20. As of May 2011, 44 million Americans get a portion of their meals using food stamps

22. Food stamp usage is typically at supermarkets, superstores and convenience stores which partially impacts dietary quality.Sources: US Department of Agriculture, 2011; Diet Quality of Americans by Food Stamp Participants, July 2008; S.N.A.P. Benefit Redemption Division Annual Report 2010

24. Hampden County is a mix of twenty-seven urban, suburban and rural cities and towns and approximately 50,000 SNAP households

25. Objective is to rigorously evaluate the impact of financial incentives provided at point-of-sale for the purchase of fruits, vegetables and other healthy foods on the diet of SNAP participants

26. Funded by a $20 million grant in the US Farm Bill of 2008

27. Campaign to end childhood obesity in the United States

28. Launched by First Lady, Michelle Obama on February 9, 2010

29. Key components include:

30. Eating healthier

31. Being more active

33. In 2008, all obesity-related medical expenses were estimated at $140 billion.Indiana 15.7% Delaware 13.8% Arizona 13.5% 12.9% Louisiana 12.9% Maryland New York 8.5% Wyoming 8.5% Alaska 8.2% All figures in million dollars (2003 dollars) Massachusetts 7.8% 7.7% Rhode Island Sources: RTI, CDC

34. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix

36. Smartphone penetration is growing rapidly and this year is estimated to grow by 4 percentage points.Sources: CTIA, eMarketer 2010 * estimates

39. The data demonstrated that minorities are comfortable using the mobile internet, making it a legitimate medium for health interventions.Source: Pew Research Center Mobile Access 2010

42. The probability of being a cell-only wireless internet user is higher among low SES communities.Source: Pew Research Center

44. Android is a logical platform choice for developing applications intended to address the needs of low SES communities.Source: Pew Research Center, July 2011

45. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix

48. “Behavioral Intervention for Overweight Women”, University of California – San Diego: Researchers assessed depressive symptoms in 401 participants in a randomized control trial of a 12-month primary care, phone and internet-based behavioral intervention for overweight women. Results showed that a 1-year primary care-based phone and internet diet and exercise intervention can improve depressive symptoms.Source: “Medication Adherence and m-Health“, George Washington University;“Behavioral Intervention for Overweight Women”, University of California – San Diego

50. Are there free clinics or Medicaid providers nearby?

52. Exercise: How to incorporate more exercise into your daily routine

58. These apps tend to command a higher selling price than the average app.

59. Medical apps tend to be of higher quality than health & fitness apps, as rated by users.Sources: Detecon Analysis, July 2011; www.appbrain.com

61. Relatively few enabling apps available (probably due to lack of appropriate or sufficient data) and relatively few intervening apps available (probably due to complexities of app design involving intervention time, manner etc.)Source: Detecon Analysis, July 2011

63. The most popular obesity-relevant Android apps are informational in nature. However, they are simple and lack the more sophisticated personalization, social and gaming features necessary to motivate people to adopt long-term change.Source: Detecon Analysis, July 2011

65. Based on this criteria, Detecon evaluated the availability and functionality of apps in the Android Market that target:

66. Obesity Causes

67. Nutrition

68. Exercise

69. Lifestyle (e.g. stress)

70. Weight Control

71. Obesity Consequences

72. Diabetes

73. Heart disease

74. Hypertension

75. Low SES Communities

76. The chart below reflects the current distribution of Android Market apps relevant for obesity-related use cases.

78. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix

80. Are there other or new strategies we might look to in the future?

81. How can A4G overcome the challenges of app discovery and increase awareness of relevant app resources among its target audience?

82. What app functionality is most needed, or missing, among currently available apps?

83. Educating

84. Enabling

85. Monitoring

86. Intervening

87. What types of app features will help improve health outcomes?

88. What types of app features are currently missing among available apps?

89. What considerations, specific to A4G‘s target population, must developers bear in mind?Detecon interviewed healthcare and information design researchers, as well as app developers, to explore the questions above and gain insight into needs, trends and potential solutions.

90. Frame Template 5. Preliminary Gap Analysis Apps targeting low SES communities and obesity consequences are notably missing from the market. Apps that act as enablers or intervention tools are also needed. App Availability by Functionality Intervening Educating Monitoring Enabling Comments Obesity Causes App Availability by Focus Area Obesity Consequences Low SES Groups Comments Source: Detecon Analysis, July 2011 Very few apps; Low quality Many apps; High quality

92. Self-monitoring skills are the most critical (weight, eating, exercise, mood)

93. Skills to set up an environment that is conducive to maintaining healthy habits

94. Goal-setting

95. Ongoing support

96. App usability must be designed to be inclusive of users with low literacy and numeracy.

97. Interventions must balance everyday realities: can users really afford to research, find and follow healthy recipes (from both a time and money perspective)? If not, what are the options?

99. How can we predict when a patient is going to relapse?

100. How do you know when to prompt a patient? When is the optimal time for a reminder (for example, to exercise) to pop up so that the patient is most receptive to the message?

101. Personalization: delivering relevant content (even if personalization options are bucketed into a finite number of options)

102. Customization: patients prefer the ability to tailor the type and frequency of contact they receive from the app

103. Accountability: patients enjoy receiving feedback and feeling accountable, but they want to control how/when the app interacts

104. Human touch: patients enjoy themselves and are more responsive if they believe there is a real person behind the communication.

105. Some programs sign all correspondence (even if the automated ones) with the name of the provider that the patient interacted with during the initial program set-up.

106. Timeliness: Technical interventions need to be a presence and resource for in-the-moment decision-makingEmerging Features for Health-Related Apps Questions for Further Investigation

108. Combining principles of information design with those of persuasion design to better motivate users to adopt and sustain healthy habits. Leveraging:

109. Fogg’s persuasion theory

110. Maslow’s Theory of Human Motivation and hierarchy of needs

111. It is important to offer users small ways to begin a program and ramp incrementally so they do not become overwhelmed and resort to excuses as to why they cannot take on such a daunting undertaking.

112. App usability must be designed to be inclusive of users with low literacy and numeracy.

113. It can be challenging to figure out what the right portion size & nutrient mix is, given the skills required to interpret & utilize label information

114. Use less words, more images.

116. What are the optimal ways to leverage information design and persuasion techniques to achieve behavioral change?

117. Instruction: include tips in games and wherever possible to educate and increase awareness

118. Comprehensive, searchable database: increases the value of the tool and its educational potential (nutritional info, store locations, etc)

119. Fun: entertaining and enjoyable apps increase stickiness

120. Games: are fun but also incorporate other important features:

121. Incentives & rewards (virtual or real): motivate people

122. Competitiveness/goal-setting: another significant motivator

123. Social: sense of community and points of comparison are important

124. Multiple data-entry options (type, scan labels, etc): ease of use

125. Consequences: use predictions of future health consequences to build awareness and motivate users to make changes nowEmerging Features for Health-Related Apps Questions for Further Investigation

127. Retention

128. Referrals

129. Revenue

130. The absence of feedback in this area underscores how little developers are thinking about catering to needs specific to communities with low SES.

132. How do you migrate users from casual to high-value?

133. Simplicity: tasks can’t be too burdensome or people won’t stick with it

134. Usability: must be top notch to stand out and drive retention

135. Social: integration with social networks is important for driving engagement; ‘a sense of community means you’re not alone’

136. One developer reported that adding photo thumbnails to his app made it more personalized and drove up engagement.

137. Personalization: critical for relevance, engagement and stickiness

138. Comprehensiveness: a strong, frequently updated, backend database is needed to power high-quality tools and accurate

139. Fun: fulfills user wishes and contributes to stickiness

140. Feedback loop: app store reviews, comments on community boards, and emails provide helpful sources of user feedback for developersEmerging Features for Health-Related Apps Questions for Further Investigation

142. Promoting and distributing a variety of high-quality applications (by)

143. Gaining traction as a valuable partner among developers

144. One option would be to create a dedicated app store for apps that cater to low SES communities.

146. How will the role of app stores evolve relative to marketing and curating apps?

147. In-app advertising should not be overly intrusive.

148. A paid version of a freemium app has to offer more than just the same app absent advertising. There has to be real value offered to the consumer.

149. Successful apps are well-designed and look nice, in addition to offering valued functionality.

150. While developers have historically been fairly poor marketers, the ability to promote one’s app, stand out and garner attention from users has become increasingly critical to the success of an app.

151. The importance of frictionless payment options (such as carrier billing) is fast increasing.Emerging Features for Health-Related Apps Questions for Further Investigation

152. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix

154. Monitoring: There is also a need for high-quality monitoring apps that are user-friendly and sticky enough to motivate users to continue using them over long periods of time to maintain healthy regimens.

155. Intervening: Because mobile phones are in close proximity to users at all times, there is tremendous potential for apps to be used as intervening mechanisms to promote good habits and, potentially, discourage bad ones. (For example: reminders to take medication; prompts to exercise at regular intervals, etc) New sensor technologies embedded in phones may further enable the development of apps with targeted behavioral interventions.

157. Initiate market research to better understand the specific challenges, needs, motivators and preferences of the low SES target segment.

158. Partner with developers of market-leading apps to add supplemental enabling functionality targeted to low SES communities.

159. Partner with developers to build new apps designed to meet the needs of low SES communities that offer enabling, monitoring and intervening functionality.Key Findings Next Steps for A4G

161. Next generation apps will differentiate themselves and boost quality by integrating a host of features that will improve their value proposition, stickiness and effectiveness. For example:

162. Personalization to increase relevance;

163. Social components to increase sense of community;

164. Gaming to leverage users‘ competitiveness and increase fun factor, retention and motivation.

165. Goal-setting can be a powerful technique for behavior change. Apps that help users set realistic goals, develop plans and skills needed to reach those goals, and monitor progress along the way, are positioned to offer formidable tools for instilling healthy habits.

166. Robust apps that offer some of the most valuable tools for both education and behavioral change incorporate comprehensive databases which provide a rich source of information from which users can draw as they improve their own skills and decision-making.

168. Expert knowledge of A4G’s target market preferences, behaviors and challenges will help A4G collaborate with developers to design appropriate solutions, user experiences and applications to drive positive behavioral change.

169. A4G might also consider sponsoring studies to research optimal tactics to overcome the challenges of low literacy and numeracy.

170. Usability and features designed with these users in mind will expand mobile app access to a broader population.Key Findings Next Steps for A4G

172. App discovery is a significant challenge across the mobile ecosystem and even more acute for applications targeting a smaller, often-marginalized group of users.

173. Increasingly, app developers are testing a variety of marketing avenues for efficacy and ROI, including:

174. Mobile advertising (usually a pay-per-download model)

175. Offline advertising

176. PR for apps (which includes everything from building a more attractive app store icon to wrangling press coverage for the app)

177. SEO (search engine optimization) for mobile app stores

179. The Beehive has a health section which is targeted to users of low SES. Market-leading and low SES-targeted apps could be promoted effectively via this outlet.

180. One Economy‘s partners in bringing broadband to underserved communities (particularly in public housing projects) could also be tapped to help promote awareness of leading health apps.

181. Additionally, A4G could create a ‘Featured Apps‘ page on its website and promote the page among target groups to boost awareness. This central clearinghouse could serve as a destination for A4G‘s target audience looking for a curated list of apps well-suited to their needs.

182. A4G could develop a list of marketing guidelines or best practices for developers seeking to serve A4G‘s constituents.

183. A4G could also develop partnerships with corporate entities (such as insurance, pharmaceutical and food companies) to develop co-marketing campaigns.Key Findings Next Steps for A4G

185. In-app advertising

186. In-app purchases

188. Health insurance companies might benefit from subsidizing app development and distribution costs if apps can help reduce other costs such as hospitalizations resulting from drug non-compliance or poor health conditions as a result of unhealthy (nutrition or exercise) choices.

189. Example: State Farm sponsored an app called On the Move that sends automatic text message replies while the user is driving. The company hopes the app will help users avoid distracted driving, thereby saving the company money by reducing the number of accident claims.Key Findings Next Steps for A4G

190. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix

192. automatically scan a product barcode

193. see product highlights (both good and bad)

194. select better alternatives

195. Fooducate analyzes information found in each product's nutrition panel and ingredient list

196. You get to see the stuff manufacturers don't want you to notice

197. Recipe suggestions personalized for health conditions

198. Links and directions to grocery outlets that carry suggested products and accept food stamps

199. Matching suggested products with store discounts or coupons

201. OnTrack helps diabetics manage their diabetes by tracking various items such as blood glucose, food, medication, blood pressure (BP), pulse, exercise and weight.

202. Features include:

203. Add multiple entries simultaneously, for example add glucose and medication at one time quickly and easily & a variety of detailed graphs and reports

204. a detailed log book with tables and graphs suitable for sharing with your doctor

205. activate reminders (e.g. remind yourself to test two hours after eating food)

206. Community forums for diabetics to share tips, support and information

207. Information for low-income diabetics to get medication and treatment ideas

209. Sergey OreshkoCEO, 4Technologies Corporation (MyNetDiary)

210. Mike PrinceCo-founder, AlltheCooks

211. J. Graham Thomas, PhD Assistant Professor (Research), Weight Control & Diabetes Research Center, The Miriam Hospital & Brown Medical School

212. Hemi WeingartenCo-Founder & CEO, Fooducate

213. Rena Wing, PhDDirector, Weight Control & Diabetes Research Center at the Miriam Hospital, RIProfessor, Department of Psychiatry and Human Behavior, Brown University Medical School

214. Brian HickeyDeveloper Relations, GetJar