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View (E50) Sherif Badawy, Lisa Kuhns JMIR mHealth and uHealth Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health Volume 5 (2017), Issue 4 ISSN: 2291-5222 Contents Original Papers Usability of a Novel Mobile Health iPad App by Vulnerable Populations (e43) David Miller Jr, Kathryn Weaver, L Case, Donald Babcock, Donna Lawler, Nancy Denizard-Thompson, Michael Pignone, John Spangler. 3 Processes and Recommendations for Creating mHealth Apps for Low-Income Populations (e41) Laura Stephan, Eduardo Dytz Almeida, Raphael Guimaraes, Antonio Ley, Rodrigo Mathias, Maria Assis, Tiago Leiria. 14 Immediate Mood Scaler:Tracking Symptoms of Depression and Anxiety Using a Novel Mobile Mood Scale (e44) Mor Nahum, Thomas Van Vleet, Vikaas Sohal, Julie Mirzabekov, Vikram Rao, Deanna Wallace, Morgan Lee, Heather Dawes, Alit Stark-Inbar, Joshua Jordan, Bruno Biagianti, Michael Merzenich, Edward Chang. 23 Development and Testing of the MyHealthyPregnancy App: A Behavioral Decision Research-Based Tool for Assessing and Communicating Pregnancy Risk (e42) Tamar Krishnamurti, Alexander Davis, Gabrielle Wong-Parodi, Baruch Fischhoff, Yoel Sadovsky, Hyagriv Simhan. 38 Technology Use and Preferences for Mobile Phone±Based HIV Prevention and Treatment Among Black Young Men Who Have Sex With Men: Exploratory Research (e46) Ian Holloway, Terrell Winder, Charles Lea III, Diane Tan, Donte Boyd, David Novak. 49 Texting and Mobile Phone App Interventions for Improving Adherence to Preventive Behavior in Adolescents: A Systematic Review (e50) Sherif Badawy, Lisa Kuhns. 64 User Interest in Digital Health Technologies to Encourage Physical Activity: Results of a Survey in Students and Staff of a German University (e51) Annett Salzwedel, Sophie Rabe, Thomas Zahn, Julia Neuwirth, Sarah Eichler, Kathrin Haubold, Anne Wachholz, Rona Reibis, Heinz Völler. 81 Use of Fitness and Nutrition Apps: Associations With Body Mass Index, Snacking, and Drinking Habits in Adolescents (e58) Nathalie De Cock, Jolien Vangeel, Carl Lachat, Kathleen Beullens, Leentje Vervoort, Lien Goossens, Lea Maes, Benedicte Deforche, Stefaan De Henauw, Caroline Braet, Steven Eggermont, Patrick Kolsteren, John Van Camp, Wendy Van Lippevelde. 90 Clickotine, A Personalized Smartphone App for Smoking Cessation: Initial Evaluation (e56) Brian Iacoviello, Joshua Steinerman, David Klein, Theodore Silver, Adam Berger, Sean Luo, Nicholas Schork. 106 Development of a Culturally Tailored Text Message Maternal Health Program: TextMATCH (e49) Rosie Dobson, Robyn Whittaker, Hannah Bartley, Augusta Connor, Ruyan Chen, Mairead Ross, Judith McCool. 121 JMIR mHealth and uHealth 2017 | vol. 5 | iss. 4 | p.1 XSL·FO RenderX Designing Patient-Centered Text Messaging Interventions for Increasing Physical Activity Among Participants With Type 2 Diabetes: Qualitative Results From the Text to Move Intervention (e54) Gabrielle Horner, Stephen Agboola, Kamal Jethwani, Aswita Tan-McGrory, Lenny Lopez. 134 Design of a Mobile App for Nutrition Education (TreC-LifeStyle) and Formative Evaluation With Families of Overweight Children (e48) Silvia Gabrielli, Marco Dianti, Rosa Maimone, Marta Betta, Lorena Filippi, Monica Ghezzi, Stefano Forti. 146 Developing a Patient-Centered mHealth App: A Tool for Adolescents With Type 1 Diabetes and Their Parents (e53) Bree Holtz, Katharine Murray, Denise Hershey, Julie Dunneback, Shelia Cotten, Amanda Holmstrom, Arpita Vyas, Molly Kaiser, Michael Wood. 159 Assessing the Medication Adherence App Marketplace From the Health Professional and Consumer Vantage Points (e45) Lindsey Dayer, Rebecca Shilling, Madalyn Van Valkenburg, Bradley Martin, Paul Gubbins, Kristie Hadden, Seth Heldenbrand. 170 A Framework for the Study of Complex mHealth Interventions in Diverse Cultural Settings (e47) Marion Maar, Karen Yeates, Nancy Perkins, Lisa Boesch, Diane Hua-Stewart, Peter Liu, Jessica Sleeth, Sheldon Tobe. 182 The Physical Activity Tracker Testing in Youth (P.A.T.T.Y.) Study: Content Analysis and Children's Perceptions (e55) Brittany Masteller, John Sirard, Patty Freedson. 193 JMIR mHealth and uHealth 2017 | vol. 5 | iss. 4 | p.2 XSL·FO RenderX JMIR MHEALTH AND UHEALTH Miller Jr et al Original Paper Usability of a Novel Mobile Health iPad App by Vulnerable Populations David P Miller Jr1, MD, MS; Kathryn E Weaver2, PhD, MPH; L Doug Case3, PhD; Donald Babcock4, PE; Donna Lawler2; Nancy Denizard-Thompson1, MD; Michael P Pignone5, MD, MPH; John G Spangler6, MD, MPH 1Wake Forest School of Medicine, Department of Internal Medicine, Winston-Salem, NC, United States 2Wake Forest School of Medicine, Department of Social Sciences & Health Policy, Winston-Salem, NC, United States 3Wake Forest School of Medicine, Department of Biostatistical Sciences, Winston-Salem, NC, United States 4Wake Forest Health Sciences, Enterprise Information Management, Winston-Salem, NC, United States 5University of Texas Dell Medical School, Department of Internal Medicine, Austin, TX, United States 6Wake Forest School of Medicine, Department of Family & Community Medicine, Winston-Salem, NC, United States Corresponding Author: David P Miller Jr, MD, MS Wake Forest School of Medicine Department of Internal Medicine Medical Center Boulevard Winston-Salem, NC, 27157 United States Phone: 1 336 713 4156 Fax: 1 336 716 7359 Email: [email protected] Abstract Background: Recent advances in mobile technologies have created new opportunities to reach broadly into populations that are vulnerable to health disparities. However, mobile health (mHealth) strategies could paradoxically increase health disparities, if low socioeconomic status individuals lack the technical or literacy skills needed to navigate mHealth programs. Objective: The aim of this study was to determine whether patients from vulnerable populations could successfully navigate and complete an mHealth patient decision aid. Methods: We analyzed usability data from a randomized controlled trial of an iPad program designed to promote colorectal cancer (CRC) screening. The trial was conducted in six primary care practices and enrolled 450 patients, aged 50-74 years, who were due for CRC screening. The iPad program included a self-survey and randomly displayed either a screening decision aid or a video about diet and exercise. We measured participant ability to complete the program without assistance and participant-rated program usability. Results: Two-thirds of the participants (305/450) were members of a vulnerable population (limited health literacy, annual income < US $20,000, or black race). Over 92% (417/450) of the participants rated the program highly on all three usability items (90.8% for vulnerable participants vs 96.6% for nonvulnerable participants, P=.006). Only 6.9% (31/450) of the participants needed some assistance to complete the program. In multivariable logistic regression, being a member of a vulnerable population was not associated with needing assistance. Only older age, less use of text messaging (short message service, SMS), and lack of Internet use predicted needing assistance. Conclusions: Individuals who are vulnerable to health disparities can successfully use well-designed mHealth programs. Future research should investigate whether mHealth interventions can reduce health disparities. (JMIR Mhealth Uhealth 2017;5(4):e43) doi:10.2196/mhealth.7268 KEYWORDS decision support techniques; technology assessment; primary care; health literacy; vulnerable populations http://mhealth.jmir.org/2017/4/e43/ JMIR Mhealth Uhealth 2017 | vol. 5 | iss. 4 | e43 | p.3 (page number not for citation purposes) XSL·FO RenderX JMIR MHEALTH AND UHEALTH Miller Jr et al navigate our program, which was designed under the assumption Introduction that users would have no prior experience with computers and Income, education, and race are powerful social determinants would have difficulty reading. We analyzed baseline data from of health. Low socioeconomic status (SES) individuals and an ongoing randomized controlled trial (Trial ID NCT02088333) underrepresented minorities are at heightened risk for a variety that is testing the effect of the intervention on completion of of poor health outcomes, including shorter life expectancy and CRC screening. We compared usability metrics between patients increased incidence of cancer and chronic diseases [1-4]. One vulnerable to health disparities (low income, limited health pathway by which limited income and education, in particular, literacy, or black race) and other patients in the primary care affect health negatively is by hampering the individuals' ability setting. to access, acquire, and understand health information needed to engage in preventive and self-care practices [5]. Some of this Methods effect is mediated by lower levels of health literacy [5,6]. Program Design Recent advances in mobile technologies have created new We designed a user-friendly mHealth iPad program for use by opportunities to reach broadly into vulnerable populations, older individuals, many of whom we assumed would have little potentially decreasing informational barriers. Over the last 10 prior technology experience. Because over one-third of years, the growing ownership of cell phones, smartphones, and Americans have limited literacy skills, we also assumed many tablet devices has shrunk the digital divide. Over 90% of users would have reading difficulties [18]. We chose a touch Americans own a cell phone with no significant differences screen interface, given its advantages over a mouse and seen by income, education, or race [7]. Additionally,
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