mHealth Applications: Potentials, Limitations, Current Quality and Future Directions

  • Eva-Maria MessnerEmail author
  • Thomas Probst
  • Teresa O’Rourke
  • Stoyan Stoyanov
  • Harald Baumeister
Part of the Studies in Neuroscience, Psychology and Behavioral Economics book series (SNPBE)


Due to the constant use of smartphones in daily life, mHealth apps might bear great potential for the use in health care support. In this chapter the potentials, limitations, current quality and future directions of mHealth apps will be discussed. First, we describe potential benefits like quicker facilitation of information, patient empowerment and inclusion of undersupplied population groups. Furthermore, the use of mHealth apps for diverse somatic and mental health conditions will be discussed. Beyond, the chapter provides the reader with a short overview on the efficacy of mHealth apps for different indications: Exemplary, we provide evidence for the efficacy of mHealth apps in the realm of asthmatic disease, depression and anxiety disorder. Despite the availability of mHealth solutions, the acceptance of among health care providers is still moderate to low. This represents a substantial problem, as health care providers are important gate keepers for intervention uptake. In this context we describe methods to foster acceptance. Furthermore, we address potential risks of mHealth app use including low responsiveness towards critical situations (e.g. self-harm) or the difficulty for users to assess the quality of the app’s content. Here we refer to standardized instruments to assess app quality. With respect to the massive amount of sensitive data already being collected through such mHealth apps, we also reflect on the latest current legal situation in Europe and the United States.


  1. Albrecht U-V (2016) Chancen und Risiken von Gesundheits-Apps (CHARISMHA). Universitätsbibliothek der Technischen Universität BraunschweigGoogle Scholar
  2. American Psychiatric Association (2019) App evaluation model. Accessed 02 Aug 2019
  3. Bakker D, Kazantzis N, Rickwood D, Rickard N (2016) Mental health smartphone apps: review and evidence-based recommendations for future developments. JMIR Ment Health 3(1):e7. Scholar
  4. Baumeister H, Nowoczin L, Lin J et al (2014) Impact of an acceptance facilitating intervention on diabetes patients’ acceptance of internet-based interventions for depression: a randomized controlled trial. Diabetes Res Clin Pract 105(1):30–39. Scholar
  5. Baumeister H, Seifferth H, Lin J et al (2015) Impact of an acceptance facilitating intervention on patients’ acceptance of internet-based pain interventions: a randomized controlled trial. Clin J Pain 31(6):528–535. Scholar
  6. Baumeister H, Lin J, Ebert DD (2017) Internet- und mobilebasierte Ansätze: Psychosoziale Diagnostik und Behandlung in der medizinischen Rehabilitation. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 60(4):436–444. Scholar
  7. Baumeister H, Pryss R, Baumel A, Messner E-M (2019) Persuasive e-health design for behavior change. In: Montag C, Baumeister H (eds) Mobile sensing and digital phenotyping: new developments in psychoinformatics. Springer, Berlin Google Scholar
  8. Baumel A, Faber K, Mathur N et al (2017) Enlight: a comprehensive quality and therapeutic potential evaluation tool for mobile and web-based eHealth interventions. J Med Internet Res 19(3):e82. Scholar
  9. Bendig E, Bauereiß N, Ebert DD et al (2018) Internet-based interventions in chronic somatic disease. Dtsch Arztebl Int 115(40).
  10. Beratarrechea A, Lee AG, Willner JM et al (2014) The impact of mobile health interventions on chronic disease outcomes in developing countries: a systematic review. Telemed J E Health 20(1):75–82. Scholar
  11. Bickmore T, Gruber A, Picard R (2005) Establishing the computer–patient working alliance in automated health behavior change interventions. Patient Educ Couns 59(1):21–30. Scholar
  12. BinDhim NF, Shaman AM, Trevena L et al (2015) Depression screening via a smartphone app: cross-country user characteristics and feasibility. J Am Med Inform Assoc 22(1):29–34. Scholar
  13. Bloomfield GS, Vedanthan R, Vasudevan L et al (2014) Mobile health for non-communicable diseases in sub-saharan africa: a systematic review of the literature and strategic framework for research. Glob Health 10(1):1–9. Scholar
  14. Dennison L, Morrison L, Conway G, Yardley L (2013) Opportunities and challenges for smartphone applications in supporting health behavior change: qualitative study. J Med Internet Res 15(4):e86. Scholar
  15. Devi BR, Syed-Abdul S, Kumar A et al (2015) mHealth: an updated systematic review with a focus on HIV/AIDS and tuberculosis long term management using mobile phones. Comput Methods Programs Biomed 122(2):257–265. Scholar
  16. Domhardt M, Steubl L, Baumeister H (2018) Internet- and mobile-based interventions for mental and somatic conditions in children and adolescents: a systematic review of meta-analyses. Z Kinder Jugendpsychiatr Psychother: 1–14.
  17. Domhardt M, Geßlein H, von Rezori RE, Baumeister H (2019) Internet- and mobile-based interventions for anxiety disorders: a meta-analytic review of intervention components. Depress Anxiety 36(3):213–224. Scholar
  18. Donner J (2008) Research approaches to mobile use in the developing world: a review of the literature. Inf Soc 24(3):140–159. Scholar
  19. East ML, Havard BC (2015) Mental health mobile apps: from infusion to diffusion in the mental health social system. JMIR Ment Health 2(1):e10. Scholar
  20. Ebert DD, Berking M, Cuijpers P et al (2015) Increasing the acceptance of internet-based mental health interventions in primary care patients with depressive symptoms. A randomized controlled trial. J Affect Disord 176:9–17. Scholar
  21. Ebert DD, Cuijpers P, Muñoz RF, Baumeister H (2017) Prevention of mental health disorders using internet- and mobile-based interventions: a narrative review and recommendations for future research. Front Psychiatry 8:116. Scholar
  22. Ebert DD, Van Daele T, Nordgreen T et al (2018) Internet- and mobile-based psychological interventions: applications, efficacy, and potential for improving mental health. Eur Psychol 23(2):167–187. Scholar
  23. Firth J, Torous J, Nicholas J et al (2017a) The efficacy of smartphone-based mental health interventions for depressive symptoms: a meta-analysis of randomized controlled trials. World Psychiatry 16(3):287–298. Scholar
  24. Firth J, Torous J, Nicholas J et al (2017b) Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials. J Affect Disord 218:15–22. Scholar
  25. Gagnon M-P, Ngangue P, Payne-Gagnon J, Desmartis M (2016) m-Health adoption by healthcare professionals: a systematic review. J Am Med Inform Assoc 23(1):212–220. Scholar
  26. Gurman TA, Rubin SE, Roess AA (2012) Effectiveness of mHealth behavior change communication interventions in developing countries: a systematic review of the literature. J Health Commun 17(sup1):82–104. Scholar
  27. Hamine S, Gerth-Guyette E, Faulx D et al (2015) Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. J Med Internet Res 17(2):e52. Scholar
  28. Hennemann S, Rudolph FM, Waldeck E et al (2016) Online-Gesundheitsprogramme in der stationären Rehabilitation: Akzeptanz und Bedarf bei Mitarbeitern und Rehabilitanden. In: Deutsche Rentenversicherung Bund (ed) 25. Rehabilitationswissenschaftliches Kolloquium, 109th edn. Deutsche Rentenversicherung Bund, Berlin, pp 141–143Google Scholar
  29. International Organisation for Standardization (2016) IEC 82304-1: Health software—part 1 general requirements for product safety. Accessed 02 Aug 2019
  30. Kargl F, Van der Heijden RW, Erb B, Bösch C (2019) Privacy in mobile sensing. In: Montag C, Baumeister H (eds) Mobile sensing and digital phenotyping: new developments in psychoinformatics. Springer, BerlinGoogle Scholar
  31. Klein DN, Schwartz JE, Santiago NJ et al (2003) Therapeutic alliance in depression treatment: controlling for prior change and patient characteristics. J Consult Clin Psychol 71(6):997–1006. Scholar
  32. Krebs P, Duncan DT (2015) Health app use among US mobile phone owners: a national survey. JMIR mHealth uHealth 3(4):e101. Scholar
  33. Kubiak T, Smyth JM (2019) Connecting domains—ecological momentary assessment in a mobile sensing framework. In: Montag C, Baumeister H (eds) Mobile sensing and digital phenotyping: new developments in psychoinformatics. Springer, BerlinGoogle Scholar
  34. Lin J, Faust B, Ebert DD et al (2018) A web-based acceptance-facilitating intervention for identifying patients’ acceptance, uptake, and adherence of internet- and mobile-based pain interventions: randomized controlled trial. J Med Internet Res 20(8):e244. Scholar
  35. Liu L, Miguel Cruz A, Rios Rincon A et al (2014) What factors determine therapists’ acceptance of new technologies for rehabilitation—a study using the unified theory of acceptance and use of technology (UTAUT). Disabil Rehabil 37(5):447–455. Scholar
  36. Marcolino MS, Oliveira JAQ, D’Agostino M et al (2018) The impact of mHealth interventions: systematic review of systematic reviews. JMIR mHealth uHealth 6(1):e23. Scholar
  37. Messner E-M, Terhorst Y, Baumeister H (in prep.) When the fear kicks in. A systematic review and evaluation of apps that tackle anxiety. J Anxiety DisordGoogle Scholar
  38. Montag C, Błaszkiewicz K, Sariyska R et al (2015) Smartphone usage in the 21st century: who is active on WhatsApp? BMC Res Notes 8(1):331. Scholar
  39. Nasi G, Cucciniello M, Guerrazzi C (2015) The role of mobile technologies in health care processes: the case of cancer supportive care. J Med Internet Res 17(2):e26. Scholar
  40. Neary M, Schueller SM (2018) State of the field of mental health apps. Cogn Behav Pract 25(4):531–537. Scholar
  41. Paganini S, Teigelkötter W, Buntrock C, Baumeister H (2018) Economic evaluations of internet- and mobile-based interventions for the treatment and prevention of depression: a systematic review. J Affect Disord 225:733–755. Scholar
  42. Papageorgiou A, Strigkos M, Politou E et al (2018) Security and privacy analysis of mobile health applications: the alarming state of practice. IEEE Access 6:9390–9403. Scholar
  43. Phillips CJ, Marshall AP, Chaves NJ et al (2015) Experiences of using the theoretical domains framework across diverse clinical environments: a qualitative study. J Multidiscip Healthc 8:139–146. Scholar
  44. Powell AC, Landman AB, Bates DW (2014) In search of a few good apps. JAMA 311(18):1851–1852. Scholar
  45. Proudfoot J, Parker G, Hadzi Pavlovic D et al (2010) Community attitudes to the appropriation of mobile phones for monitoring and managing depression, anxiety, and stress. J Med Internet Res 12(5):e64. Scholar
  46. Rabbi M, Klasnja P, Choudhury T et al (2019) Optimizing mHealth interventions with a bandit. In: Montag C, Baumeister H (eds) Mobile sensing and digital phenotyping: new developments in psychoinformatics. Springer, BerlinGoogle Scholar
  47. Rathner E-M, Djamali J, Terhorst Y et al (2018a) How did you like 2017? Detection of language markers of depression and narcissism in personal narratives. In: Proceedings Interspeech 2018. ISCA, pp 3388–3392Google Scholar
  48. Rathner E-M, Terhorst Y, Cummins N et al (2018b) State of mind: classification through self-reported affect and word use in speech. In: Proceedings Interspeech 2018. ISCA, pp 267–271Google Scholar
  49. Research2guidance (2016) mHealth App Developer Economics 2016Google Scholar
  50. Sariyska R, Rathner E-M, Baumeister H, Montag C (2018) Feasibility of linking molecular genetic markers to real-world social network size tracked on smartphones. Front Neurosci 12:945. Scholar
  51. Schueller SM, Neary M, O’Loughlin K, Adkins EC (2018) Discovery of and interest in health apps among those with mental health needs: survey and focus group study. J Med Internet Res 20(6):e10141. Scholar
  52. Singh K, Drouin K, Newmark LP et al (2016) Many mobile health apps target high-need, high-cost populations, but gaps remain. Health Aff 35(12):2310–2318. Scholar
  53. Statista (2019) Number of mHealth apps available in the Apple App Store from 1st quarter 2015 to 2nd quarter 2019 [Graph]. In Statista. Accessed 12 Aug 2019
  54. Stoyanov SR, Hides L, Kavanagh DJ et al (2015) Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR mHealth uHealth 3(1):e27. Scholar
  55. Surmann M, Bock EM, Krey E et al (2017) Einstellungen gegenüber eHealth-Angeboten in Psychiatrie und Psychotherapie: Eine Pilotumfrage auf dem DGPPN-Kongress 2014. Nervenarzt 88(9):1036–1043. Scholar
  56. Terhorst Y, Rathner E-M, Baumeister H, Sander L (2018) “Hilfe aus dem App-Store?”: Eine systematische Übersichtsarbeit und Evaluation von Apps zur Anwendung bei Depressionen. Verhaltenstherapie 28(2):101–112. Scholar
  57. Torous J, Friedman R, Keshavan M (2014) Smartphone ownership and interest in mobile applications to monitor symptoms of mental health conditions. JMIR mHealth uHealth 2(1):e2. Scholar
  58. Torous JB, Chan SR, Yellowlees PM, Boland R (2016) To use or not? Evaluating ASPECTS of smartphone apps and mobile technology for clinical care in psychiatry. J Clin Psychiatry 77(6):e734–e738. Scholar
  59. Webb TL, Joseph J, Yardley L, Michie S (2010) Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res 12(1):e4. Scholar
  60. Zanaboni P, Ngangue P, Mbemba GIC et al (2018) Methods to evaluate the effects of internet-based digital health interventions for citizens: systematic review of reviews. J Med Internet Res 20(6):e10202. Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Eva-Maria Messner
    • 1
    Email author
  • Thomas Probst
    • 2
  • Teresa O’Rourke
    • 2
  • Stoyan Stoyanov
    • 3
  • Harald Baumeister
    • 1
  1. 1.Clinical Psychology and PsychotherapyUlm UniversityUlmGermany
  2. 2.Psychotherapy and Biopsychosocial HealthDanube University KremsKrems an der DonauAustria
  3. 3.Centre for Children’s Health Research, Institute of Health and Biomedical Innovation and School of Psychology and Counselling, Queensland University of TechnologyBrisbaneAustralia

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