1932

Abstract

Mobile health applications (apps) have transformed the possibilities for health promotion and disease self-management; however, their promise is not fully realized owing to their reliance on commercial ecosystems for development and distribution. This review provides an overview of the types of mobile health apps and describes key stakeholders in terms of how apps are used, developed, and regulated. I outline key challenges facing consumers, public health professionals, and policy makers in evaluating the quality of health apps and summarize what is known about the impact of apps on health outcomes and health equity. I suggest that factors within the wider mobile ecosystem largely define the impact of health apps and, most notably, practices around the collection and commercialization of user data. Finally, I suggest that upstream public health strategies, grounded in an understanding of corporate influences on health, are necessary to promote healthy digital environments in which mobile health app innovation can flourish.

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2022-04-05
2024-03-29
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Literature Cited

  1. 1. 
    Abraham C, Michie S 2008. A taxonomy of behavior change techniques used in interventions. Health Psychol. 27:379–87
    [Google Scholar]
  2. 2. 
    Adam R, McMichael D, Powell D, Murchie P 2019. Publicly available apps for cancer survivors: a scoping review. BMJ Open 9:e032510
    [Google Scholar]
  3. 3. 
    Akbar S, Coiera E, Magrabi F 2020. Safety concerns with consumer-facing mobile health applications and their consequences: a scoping review. JAMIA 27:330–40
    [Google Scholar]
  4. 4. 
    Alessa T, Hawley MS, Hock ES, de Witte L. 2019. Smartphone apps to support self-management of hypertension: review and content analysis. JMIR mHealth uHealth 7:e13645
    [Google Scholar]
  5. 5. 
    AMA Staff News Writer 2016. Medical innovation and digital snake oil: AMA CEO speaks out. AMA Wire June 17. https://www.ama-assn.org/practice-management/digital/medical-innovation-and-digital-snake-oil-ama-ceo-speaks-out
    [Google Scholar]
  6. 6. 
    Ancker JS, Witteman HO, Hafeez B, Provencher T, Van de Graaf M, Wei E. 2015.. “ You get reminded you're a sick person”: personal data tracking and patients with multiple chronic conditions. J. Med. Internet Res. 17:e202
    [Google Scholar]
  7. 7. 
    Anthes E. 2016. Pocket psychiatry. Nature 532:20–23
    [Google Scholar]
  8. 8. 
    Apple Inc 2021. App Store review guidelines. Developer https://developer.apple.com/app-store/review/guidelines/#advertising
    [Google Scholar]
  9. 9. 
    Arigo D, Jake-Schoffman DE, Wolin K, Beckjord E, Hekler EB, Pagoto SL. 2019. The history and future of digital health in the field of behavioral medicine. J. Behav. Med. 42:67–83
    [Google Scholar]
  10. 10. 
    Atske S, Perrin A 2021. Home broadband adoption, computer ownership vary by race, ethnicity in the U.S. Pew Research Center July 16. https://www.pewresearch.org/fact-tank/2021/07/16/home-broadband-adoption-computer-ownership-vary-by-race-ethnicity-in-the-u-s/
    [Google Scholar]
  11. 11. 
    Azad-Khaneghah P, Neubauer N, Miguel Cruz A, Liu L 2021. Mobile health app usability and quality rating scales: a systematic review. Disabil. Rehabil. Assist. Technol. 16:712–21
    [Google Scholar]
  12. 12. 
    Benjumea J, Ropero J, Rivera-Romero O, Dorronzoro-Zubiete E, Carrasco A. 2020. Assessment of the fairness of privacy policies of mobile health apps: scale development and evaluation in cancer apps. JMIR mHealth uHealth 8:e17134
    [Google Scholar]
  13. 13. 
    Benjumea J, Ropero J, Rivera-Romero O, Dorronzoro-Zubiete E, Carrasco A. 2020. Privacy assessment in mobile health apps: scoping review. JMIR mHealth uHealth 8:e18868
    [Google Scholar]
  14. 14. 
    BinDhim NF, Freeman B, Trevena L 2014. Pro-smoking apps for smartphones: the latest vehicle for the tobacco industry?. Tob. Control 23:e4
    [Google Scholar]
  15. 15. 
    Blenner SR, Köllmer M, Rouse AJ, Daneshvar N, Williams C, Andrews LB 2016. Privacy policies of android diabetes apps and sharing of health information. JAMA 315:1051–52
    [Google Scholar]
  16. 16. 
    Bondaronek P, Alkhaldi G, Slee A, Hamilton FL, Murray E 2018. Quality of publicly available physical activity apps: review and content analysis. JMIR mHealth uHealth 6:e53
    [Google Scholar]
  17. 17. 
    Brewer LC, Fortuna KL, Jones C, Walker R, Hayes SN et al. 2020. Back to the future: achieving health equity through health informatics and digital health. JMIR mHealth uHealth 8:e14512
    [Google Scholar]
  18. 18. 
    Buckingham SA, Williams AJ, Morrissey K, Price L, Harrison J 2019. Mobile health interventions to promote physical activity and reduce sedentary behaviour in the workplace: a systematic review. Digit. Health 5:2055207619839883
    [Google Scholar]
  19. 19. 
    Carroll JK, Moorhead A, Bond R, LeBlanc WG, Petrella RJ, Fiscella K. 2017. Who uses mobile phone health apps and does use matter? A secondary data analytics approach. J. Med. Internet Res. 19:e125
    [Google Scholar]
  20. 20. 
    Carter DD, Robinson K, Forbes J, Hayes S 2018. Experiences of mobile health in promoting physical activity: a qualitative systematic review and meta-ethnography. PLOS ONE 13:e0208759
    [Google Scholar]
  21. 21. 
    Chan KL, Chen M. 2019. Effects of social media and mobile health apps on pregnancy care: meta-analysis. JMIR mHealth uHealth 7:e11836
    [Google Scholar]
  22. 22. 
    Choi J, Chung C, Woo H 2021. Diet-related mobile apps to promote healthy eating and proper nutrition: a content analysis and quality assessment. Int. J. Environ. Res. Public Health 18:73496
    [Google Scholar]
  23. 23. 
    Choi YK, Demiris G, Lin SY, Iribarren SJ, Landis CA et al. 2018. Smartphone applications to support sleep self-management: review and evaluation. J. Clin. Sleep Med. 14:1783–90
    [Google Scholar]
  24. 24. 
    Coorey GM, Neubeck L, Mulley J, Redfern J 2018. Effectiveness, acceptability and usefulness of mobile applications for cardiovascular disease self-management: systematic review with meta-synthesis of quantitative and qualitative data. Eur. J. Prev. Cardiol. 25:505–21
    [Google Scholar]
  25. 25. 
    de la Vega R, Miró J. 2014. mHealth: a strategic field without a solid scientific soul. A systematic review of pain-related apps. PLOS ONE 9:e101312
    [Google Scholar]
  26. 26. 
    De Souza R, Butt D, Jethani S, Marmo C 2021. Participatory research methods for investigating digital health literacy. Conjunctions 8: https://doi.org/10.7146/tjcp.v8i1.117800
    [Crossref] [Google Scholar]
  27. 27. 
    Dehling T, Gao F, Schneider S, Sunyaev A. 2015. Exploring the far side of mobile health: information security and privacy of mobile health apps on iOS and Android. JMIR mHealth uHealth 3:e8
    [Google Scholar]
  28. 28. 
    DeSouza R. 2016. Wearable devices and the potential for community health improvement. Nurse Click August 19 14–15 http://www.ruthdesouza.com/2016/08/19/wearable-devices-and-the-potential-for-community-health-improvement/
    [Google Scholar]
  29. 29. 
    Direito A, Carraça E, Rawstorn J, Whittaker R, Maddison R 2017. mHealth technologies to influence physical activity and sedentary behaviors: behavior change techniques, systematic review and meta-analysis of randomized controlled trials. Ann. Behav. Med. 51:226–39
    [Google Scholar]
  30. 30. 
    Ebeling M. 2016. Healthcare and Big Data: Digital Specters and Phantom Objects New York: Palgrave Macmillan US
  31. 31. 
    Ernsting C, Dombrowski SU, Oedekoven M, O'Sullivan JL, Kanzler M et al. 2017. Using smartphones and health apps to change and manage health behaviors: a population-based survey. J. Med. Internet Res. 19:e101
    [Google Scholar]
  32. 32. 
    Fed. Trade Comm 2016. What are the laws?. Mobile Health Apps Interactive Tool. https://www.ftc.gov/tips-advice/business-center/guidance/mobile-health-apps-interactive-tool
    [Google Scholar]
  33. 33. 
    Fedele DA, Cushing CC, Fritz A, Amaro CM, Ortega A. 2017. Mobile health interventions for improving health outcomes in youth: a meta-analysis. JAMA Pediatr. 171:461–69
    [Google Scholar]
  34. 34. 
    Ferretti A, Ronchi E, Vayena E 2019. From principles to practice: benchmarking government guidance on health apps. Lancet Digit. Health 1:e55–57
    [Google Scholar]
  35. 35. 
    Firth J, Torous J, Nicholas J, Carney R, Rosenbaum S, Sarris J. 2017. Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials. J. Affect. Disord. 218:15–22
    [Google Scholar]
  36. 36. 
    Fleming T, Bavin L, Lucassen M, Stasiak K, Hopkins S, Merry S. 2018. Beyond the trial: systematic review of real-world uptake and engagement with digital self-help interventions for depression, low mood, or anxiety. J. Med. Internet Res. 20:e199
    [Google Scholar]
  37. 37. 
    Free C, Phillips G, Galli L, Watson L, Felix L et al. 2013. The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLOS Med. 10:e1001362
    [Google Scholar]
  38. 38. 
    Freudenberg N. 2005. Public health advocacy to change corporate practices: implications for health education practice and research. Health Educ. Behav. 32:298–319
    [Google Scholar]
  39. 39. 
    Freudenberg N. 2021. At What Cost? Modern Capitalism and the Future of Health Oxford, UK: Oxford Univ. Press
  40. 40. 
    Furlong L, Morris M, Serry T, Erickson S. 2018. Mobile apps for treatment of speech disorders in children: an evidence-based analysis of quality and efficacy. PLOS ONE 13:e0201513
    [Google Scholar]
  41. 41. 
    Google 2021. Developer policy center. Google Play https://play.google.com/about/developer-content-policy/
    [Google Scholar]
  42. 42. 
    Grossman MR, Zak DK, Zelinski EM 2018. Mobile apps for caregivers of older adults: quantitative content analysis. JMIR mHealth uHealth 6:e162
    [Google Scholar]
  43. 43. 
    Grundy Q, Chiu K, Held F, Continella A, Bero L, Holz R. 2019. Data sharing practices of medicines related apps and the mobile ecosystem: traffic, content, and network analysis. BMJ 364:l920
    [Google Scholar]
  44. 44. 
    Grundy Q, Held F, Bero L. 2017. A social network analysis of the financial links backing health and fitness apps. Am. J. Public Health 107:1783–88
    [Google Scholar]
  45. 45. 
    Grundy Q, Held FP, Bero LA. 2017. Tracing the potential flow of consumer data: a network analysis of prominent health and fitness apps. J. Med. Internet Res. 19:e233
    [Google Scholar]
  46. 46. 
    Grundy QH, Wang Z, Bero LA 2016. Challenges in assessing mobile health app quality: a systematic review of prevalent and innovative methods. Am. J. Prev. Med. 51:1051–59
    [Google Scholar]
  47. 47. 
    Hernandez Silva E, Lawler S, Langbecker D 2019. The effectiveness of mHealth for self-management in improving pain, psychological distress, fatigue, and sleep in cancer survivors: a systematic review. J. Cancer Surviv. 13:97–107
    [Google Scholar]
  48. 48. 
    Huckvale K, Car M, Morrison C, Car J. 2012. Apps for asthma self-management: a systematic assessment of content and tools. BMC Med. 10:144
    [Google Scholar]
  49. 49. 
    Huckvale K, Morrison C, Ouyang J, Ghaghda A, Car J 2015. The evolution of mobile apps for asthma: an updated systematic assessment of content and tools. BMC Med. 13:58
    [Google Scholar]
  50. 50. 
    Huckvale K, Prieto JT, Tilney M, Benghozi P-J, Car J. 2015. Unaddressed privacy risks in accredited health and wellness apps: a cross-sectional systematic assessment. BMC Med 13:214
    [Google Scholar]
  51. 51. 
    Huckvale K, Torous J, Larsen ME. 2019. Assessment of the data sharing and privacy practices of smartphone apps for depression and smoking cessation. JAMA Netw. Open 2:e192542
    [Google Scholar]
  52. 52. 
    IMDRF (Int. Med. Device Regul. Forum) 2021. Software as a medical device (SaMD). Work Items. http://www.imdrf.org/workitems/wi-samd.asp
    [Google Scholar]
  53. 53. 
    Iwaya LH, Ahmad A, Babar MA 2020. Security and privacy for mHealth and uHealth systems: a systematic mapping study. IEEE Access 8:150081–112
    [Google Scholar]
  54. 54. 
    Jongerius C, Russo S, Mazzocco K, Pravettoni G 2019. Research-tested mobile apps for breast cancer care: systematic review. JMIR mHealth uHealth 7:e10930
    [Google Scholar]
  55. 55. 
    Jutel A, Lupton D. 2015. Digitizing diagnosis: a review of mobile applications in the diagnostic process. Diagnosis 2:89–96
    [Google Scholar]
  56. 56. 
    Kaner EFS, Beyer FR, Garnett C, Crane D, Brown J et al. 2017. Personalised digital interventions for reducing hazardous and harmful alcohol consumption in community-dwelling populations. Cochrane Database Syst. Rev. 9:9CD011479
    [Google Scholar]
  57. 57. 
    Krebs P, Duncan DT. 2015. Health app use among US mobile phone owners: a national survey. JMIR mHealth uHealth 3:e101
    [Google Scholar]
  58. 58. 
    Lagan S, Emerson MR, King K, Matwin S, Chan SR et al. 2021. Mental health app evaluation: updating the American Psychiatric Association's framework through a stakeholder-engaged workshop. Psychiatr. Serv. 72:1095–98
    [Google Scholar]
  59. 59. 
    Larsen ME, Nicholas J, Christensen H 2016. Quantifying App Store dynamics: longitudinal tracking of mental health apps. JMIR mHealth uHealth 4:e96
    [Google Scholar]
  60. 60. 
    Lee TT, Kesselheim AS. 2018. U.S. Food and Drug Administration Precertification Pilot Program for digital health software: weighing the benefits and risks. Ann. Intern. Med. 168:730–32
    [Google Scholar]
  61. 61. 
    Li R, Liang N, Bu F, Hesketh T. 2020. The effectiveness of self-management of hypertension in adults using mobile health: systematic review and meta-analysis. JMIR mHealth uHealth 8:e17776
    [Google Scholar]
  62. 62. 
    Lupton D. 2014. Apps as artefacts: towards a critical perspective on mobile health and medical apps. Societies 4:606–22
    [Google Scholar]
  63. 63. 
    Lupton D. 2015. Health promotion in the digital era: a critical commentary. Health Promot. Int. 30:174–83
    [Google Scholar]
  64. 64. 
    Lupton D. 2018. ‘I just want it to be done, done, done!’ Food tracking apps, affects, and agential capacities. Multimodal Technol. Interact. 2:229
    [Google Scholar]
  65. 65. 
    Lupton D, Pedersen S. 2016. An Australian survey of women's use of pregnancy and parenting apps. Women Birth 29:368–75
    [Google Scholar]
  66. 66. 
    Mack H. 2016. Scoop: emails show FDA asked Apple to advise on software as a medical device. MobiHealth News Novemb. 28. https://www.mobihealthnews.com/content/scoop-emails-show-fda-asked-apple-advise-software-medical-device
    [Google Scholar]
  67. 67. 
    Mangone ER, Lebrun V, Muessig KE. 2016. Mobile phone apps for the prevention of unintended pregnancy: a systematic review and content analysis. JMIR mHealth uHealth 4:e6
    [Google Scholar]
  68. 68. 
    Marelli L, Lievevrouw E, Van Hoyweghen I 2020. Fit for purpose? The GDPR and the governance of European digital health. Policy Stud 41:447–67
    [Google Scholar]
  69. 69. 
    McCabe C, McCann M, Brady AM. 2017. Computer and mobile technology interventions for self-management in chronic obstructive pulmonary disease. Cochrane Database Syst. Rev. 5:5CD011425
    [Google Scholar]
  70. 70. 
    McCool J, Dobson R, Whittaker R, Paton C 2022. Mobile health (mHealth) in low- and middle-income countries. Annu. Rev. Public Health 43:525–39
    [Google Scholar]
  71. 71. 
    Melcher J, Torous J. 2020. Smartphone apps for college mental health: a concern for privacy and quality of current offerings. Psychiatr. Serv. 71:1114–19
    [Google Scholar]
  72. 72. 
    Millington B. 2014. Smartphone apps and the mobile privatization of health and fitness. Crit. Stud. Media Comm. 31:479–93
    [Google Scholar]
  73. 73. 
    Morrissey EC, Corbett TK, Walsh JC, Molloy GJ. 2016. Behavior change techniques in apps for medication adherence: a content analysis. Am. J. Prev. Med. 50:e143–46
    [Google Scholar]
  74. 74. 
    NHS (Natl. Health Serv.) 2021. NHS apps library. NHS https://www.nhs.uk/apps-library/
    [Google Scholar]
  75. 75. 
    Nicholas J, Fogarty AS, Boydell K, Christensen H. 2017. The reviews are in: a qualitative content analysis of consumer perspectives on apps for bipolar disorder. J. Med. Internet Res. 19:e105
    [Google Scholar]
  76. 76. 
    Nouri R, Niakan Kalhori SR, Ghazisaeedi M, Marchand G, Yasini M 2018. Criteria for assessing the quality of mHealth apps: a systematic review. JAMIA 25:1089–98
    [Google Scholar]
  77. 77. 
    Overdijkink SB, Velu AV, Rosman AN, van Beukering MD, Kok M, Steegers-Theunissen RP. 2018. The usability and effectiveness of mobile health technology-based lifestyle and medical intervention apps supporting health care during pregnancy: systematic review. JMIR mHealth uHealth 6:e109
    [Google Scholar]
  78. 78. 
    Papageorgiou A, Strigkos M, Politou E, Alepis E, Solanas A, Patsakis C 2018. Security and privacy analysis of mobile health applications: the alarming state of practice. IEEE Access 6:9390–403
    [Google Scholar]
  79. 79. 
    Parker L, Bero L, Gillies D, Raven M, Grundy Q 2019. The “hot potato” of mental health app regulation: a critical case study of the Australian policy arena. Int. J. Health Policy Manag. 8:168–76
    [Google Scholar]
  80. 80. 
    Parker L, Bero L, Gillies D, Raven M, Mintzes B et al. 2018. Mental health messages in prominent mental health apps. Ann. Fam. Med. 16:338–42
    [Google Scholar]
  81. 81. 
    Parker L, Karliychuk T, Gillies D, Mintzes B, Raven M, Grundy Q 2017. A health app developer's guide to law and policy: a multi-sector policy analysis. BMC Med. Inform. Decis. Mak. 17:141
    [Google Scholar]
  82. 82. 
    Pasquale F. 2015. The Black Box Society: The Secret Algorithms that Control Money and Information Cambridge, MA: Harvard Univ. Press
  83. 83. 
    Portenhauser AA, Terhorst Y, Schultchen D, Sander LB, Denkinger MD et al. 2021. Mobile apps for older adults: systematic search and evaluation within online stores. JMIR Aging 4:e23313
    [Google Scholar]
  84. 84. 
    Research 2 Guidance 2017. mHealth app economics 2017—current status and future trends in mobile health Rep., Research 2 Guidance Berlin: https://research2guidance.com/product/mhealth-economics-2017-current-status-and-future-trends-in-mobile-health/
  85. 85. 
    Research 2 Guidance 2018. mHealth economics: how mHealth publishers are monetizing their apps Rep., Research 2 Guidance Berlin: https://research2guidance.com/product/mhealth-economics-how-mhealth-app-publishers-are-monetizing-their-apps/
  86. 86. 
    Rich E, Miah A. 2017. Mobile, wearable and ingestible health technologies: towards a critical research agenda. Health Soc. Rev. 26:84–97
    [Google Scholar]
  87. 87. 
    Robbins R, Krebs P, Jagannathan R, Jean-Louis G, Duncan DT. 2017. Health app use among US mobile phone users: analysis of trends by chronic disease status. JMIR mHealth uHealth 5:e197
    [Google Scholar]
  88. 88. 
    Robillard JM, Feng TL, Sporn AB, Lai J-A, Lo C et al. 2019. Availability, readability, and content of privacy policies and terms of agreements of mental health apps. Internet Interv. 17:100243
    [Google Scholar]
  89. 89. 
    Rosenfeld L, Torous J, Vahia IV. 2017. Data security and privacy in apps for dementia: An analysis of existing privacy policies. Am. J. Geriatr. Psychiatry 25:873–77
    [Google Scholar]
  90. 90. 
    Shuren J, Patel B, Gottlieb S 2018. FDA regulation of mobile medical apps. JAMA 320:337–38
    [Google Scholar]
  91. 91. 
    Singh K, Drouin K, Newmark LP, Lee J, Faxvaag A et al. 2016. Many mobile health apps target high-need, high-cost populations, but gaps remain. Health Aff. 35:2310–18
    [Google Scholar]
  92. 92. 
    Slater H, Campbell JM, Stinson JN, Burley MM, Briggs AM. 2017. End user and implementer experiences of mHealth technologies for noncommunicable chronic disease management in young adults: systematic review. J. Med. Internet Res. 19:e406
    [Google Scholar]
  93. 93. 
    Statista Res. Dep 2021. App stores—statistics & facts. Statista July 12. https://www.statista.com/topics/1729/app-stores/
    [Google Scholar]
  94. 94. 
    Sunyaev A, Dehling T, Taylor PL, Mandl KD 2015. Availability and quality of mobile health app privacy policies. JAMIA 22:e28–33
    [Google Scholar]
  95. 95. 
    Tangari G, Ikram M, Sentana IWB, Ijaz K, Kaafar MA, Berkovsky S. 2021. Analyzing privacy issues of Android mobile health and medical applications. BMJ 28:2074–84
    [Google Scholar]
  96. 96. 
    Terhorst Y, Philippi P, Sander LB, Schultchen D, Paganini S et al. 2020. Validation of the Mobile Application Rating Scale (MARS). PLOS ONE 15:e0241480
    [Google Scholar]
  97. 97. 
    Thompson SA, Warzel C. 2019. The privacy project: twelve million phones, one dataset, zero privacy. New York Times Dec. 19. https://www.nytimes.com/interactive/2019/12/19/opinion/location-tracking-cell-phone.html
    [Google Scholar]
  98. 98. 
    Tofighi B, Chemi C, Ruiz-Valcarcel J, Hein P, Hu L. 2019. Smartphone apps targeting alcohol and illicit substance use: systematic search in in commercial app stores and critical content analysis. JMIR mHealth uHealth 7:e11831
    [Google Scholar]
  99. 99. 
    Torous J, Firth J, Huckvale K, Larsen ME, Cosco TD et al. 2018. The emerging imperative for a consensus approach toward the rating and clinical recommendation of mental health apps. J. Nerv. Ment. Dis. 206:662–66
    [Google Scholar]
  100. 100. 
    Torous JB, Chan SR, Gipson SYT, Kim JW, Nguyen TQ et al. 2018. A hierarchical framework for evaluation and informed decision making regarding smartphone apps for clinical care. Psychiatr. Serv. 69:498–500
    [Google Scholar]
  101. 101. 
    Tucker L, Villagomez AC, Krishnamurti T. 2021. Comprehensively addressing postpartum maternal health: a content and image review of commercially available mobile health apps. BMC Pregnancy Childbirth 21:311
    [Google Scholar]
  102. 102. 
    US FDA (Food Drug Adm.) 2019. Policy for device software functions and mobile medical applications: guidance for industry and Food and Drug Administration staff Rep. US FDA, Silver Spring MD: https://www.fda.gov/media/80958/download
  103. 103. 
    Vallina-Rodriguez N, Sundaresan S, Razaghpanah A, Nithyanand R, Allman M et al. 2016. Tracking the trackers: towards understanding the mobile advertising and tracking ecosystem. arXiv1609.07190 (cs) https://arxiv.org/abs/1609.07190
  104. 104. 
    Veinot TC, Mitchell H, Ancker JS. 2018. Good intentions are not enough: how informatics interventions can worsen inequality. J. Am. Med. Inform. Assoc. 25:1080–88
    [Google Scholar]
  105. 105. 
    Vollmer Dahlke D,, Fair K, Hong YA, Beaudoin CE, Pulczinski J, Ory MG 2015. Apps seeking theories: results of a study on the use of health behavior change theories in cancer survivorship mobile apps. JMIR mHealth uHealth 3:e31
    [Google Scholar]
  106. 106. 
    Wagner JK. 2020. The Federal Trade Commission and consumer protections for mobile health apps. J. Law Med. Ethics 48:103–14
    [Google Scholar]
  107. 107. 
    Wang Y, Xue H, Huang Y, Huang L, Zhang D. 2017. A systematic review of application and effectiveness of mHealth interventions for obesity and diabetes treatment and self-management. Adv. Nutr. 8:449–62
    [Google Scholar]
  108. 108. 
    Wasil AR, Venturo-Conerly KE, Shingleton RM, Weisz JR 2019. A review of popular smartphone apps for depression and anxiety: assessing the inclusion of evidence-based content. Behav. Res. Ther. 123:103498
    [Google Scholar]
  109. 109. 
    Whittaker R, McRobbie H, Bullen C, Rodgers A, Gu Y, Dobson R. 2019. Mobile phone text messaging and app-based interventions for smoking cessation. Cochrane Database Syst. Rev. 10:10CD006611
    [Google Scholar]
  110. 110. 
    WHO (World Health Organ.) 2011. mHealth: new horizons for health through mobile technologies Rep. WHO Geneva: https://www.who.int/goe/publications/goe_mhealth_web.pdf
  111. 111. 
    WHO (World Health Organ.) 2017. mHealth: use of appropriate digital technologies for public health Rep. EB142/20 WHO Geneva:
  112. 112. 
    Wiist WH. 2010. The Bottom Line or Public Health: Tactics Corporations Use to Influence Health and Health Policy, and What We Can Do to Counter Them Oxford, UK: Oxford Univ. Press
  113. 113. 
    Zhao J, Freeman B, Li M 2017. How do infant feeding apps in China measure up? A content quality assessment. JMIR mHealth uHealth 5:e186
    [Google Scholar]
  114. 114. 
    Zhou C, Hu H, Wang C, Zhu Z, Feng G et al. 2020. The effectiveness of mHealth interventions on postpartum depression: a systematic review and meta-analysis. J. Telemed. Telecare. https://doi.org/10.1177/1357633X20917816
    [Crossref] [Google Scholar]
  115. 115. 
    Zuboff S. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future New York: PublicAffairs
  116. 116. 
    Zwingerman R, Chaikof M, Jones C 2020. A critical appraisal of fertility and menstrual tracking apps for the iPhone. J. Obstet. Gynaecol. Can. 42:583–90
    [Google Scholar]
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