Standardized evaluation of the quality and persuasiveness of mobile health applications for diabetes management

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Standardized evaluation of the quality and persuasiveness of mobile health applications for diabetes management
  • Tamayo, T. et al. Diabetes in Europe: an update. Diabetes Res. Clin. Pract. 103, 206–217 (2014).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • World Health Organization. Data and statistics. https://www.euro.who.int/en/health-topics/noncommunicable-diseases/diabetes/data-and-statistics.

  • Beck, J., Greenwood, D. A., Blanton, L., Bollinger, S. T., Butcher, M. K. & Condon, J. E. National Standards for Diabetes Self-Management Education and Support (2017).

  • Peyrot, M., Peeples, M., Tomky, D., Charron-Prochownik, D. & Weaver, T. Development of the American association of diabetes educators’ diabetes self-management assessment report tool. Diabetes Educ. 33, 818–826 (2007).

    Article 
    PubMed 

    Google Scholar 

  • Lange, K., Swift, P., Pańkowska, E. & Danne, T. ISPAD clinical practice consensus guidelines 2014. Diabetes education in children and adolescents. Pediatr. Diabetes 15(Suppl 20), 77–85 (2014).

    Article 
    PubMed 

    Google Scholar 

  • Kitsiou, S., Paré, G., Jaana, M. & Gerber, B. Effectiveness of mHealth interventions for patients with diabetes: an overview of systematic reviews. PLoS ONE 12, e0173160 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Cui, M., Wu, X., Mao, J., Wang, X. & Nie, M. T2DM self-management via smartphone applications: a systematic review and meta-analysis. PLoS ONE 11, e0166718 (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Bonoto, B. C. et al. Efficacy of mobile apps to support the care of patients with diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials. JMIR mHealth uHealth 5, e4 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Huang, Z., Soljak, M., Boehm, B. O. & Car, J. Clinical relevance of smartphone apps for diabetes management: a global overview. Diabetes Metab. Res. Rev. 34, e2990 (2018).

    Article 
    PubMed 

    Google Scholar 

  • Moumtzoglou, A. Mobile Health Applications for Quality Healthcare Delivery (IGI Global, 2019).

    Book 

    Google Scholar 

  • Whitehead, L. & Seaton, P. The effectiveness of self-management mobile phone and tablet apps in long-term condition management: a systematic review. J. Med. Internet Res. 18, e97 (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Klonoff, D. C. The current status of mHealth for diabetes: will it be the next big thing?. J. Diabetes Sci. Technol. 7, 749–758 (2013).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Hood, M. et al. What do we know about mobile applications for diabetes self-management? A review of reviews. J. Behav. Med. 39, 981–994 (2016).

    Article 
    PubMed 

    Google Scholar 

  • Eng, D. S. & Lee, J. M. The promise and peril of mobile health applications for diabetes and endocrinology. Pediatr. Diabetes 14, 231–238 (2013).

    Article 
    PubMed 

    Google Scholar 

  • Arnhold, M., Quade, M. & Kirch, W. Mobile applications for diabetics: a systematic review and expert-based usability evaluation considering the special requirements of diabetes patients age 50 years or older. J. Med. Internet Res. 16, e104 (2014).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Gong, E. et al. Quality, functionality, and features of Chinese mobile apps for diabetes self-management: systematic search and evaluation of mobile apps. JMIR mHealth uHealth 8, e14836 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Chavez, S. et al. Mobile apps for the management of diabetes. Diabetes Care 40, e145–e146 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Stoyanov, S. R. et al. Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR mHealth uHealth 3, e27 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Kelders, S. M., Kok, R. N., Ossebaard, H. C. & van Gemert-Pijnen, J. E. W. C. Persuasive system design does matter: a systematic review of adherence to web-based interventions. J. Med. Internet Res. 14, e152 (2012).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ryan, J. C. et al. Identifying critical features of type two diabetes prevention interventions: a Delphi study with key stakeholders. PLoS ONE 16, e0255625 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Oinas-Kukkonen, H. & Harjumaa, M. Persuasive system design: key issues, process model, and system features. CAIS 24, 28 (2009).

    Article 

    Google Scholar 

  • Baumeister, H., Kraft, R., Baumel, A., Pryss, R. & Messner, E. M. Persuasive e-health design for behavior change. In Digital phenotyping and mobile sensing (eds Baumeister, H. & Montag, C.) (Springer Nature, 2019).

    Chapter 

    Google Scholar 

  • Wozney, L. et al. How do eHealth programs for adolescents work? A realist review of persuasive system design components in internet-based psychological therapies. J. Med. Internet Res. 19, e266 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Radomski, A. D. et al. Design and delivery features that may improve the use of internet-based cognitive behavioral therapy for children and adolescents with anxiety: a realist literature synthesis with a persuasive systems design perspective. J. Med. Internet Res. 21, e11128 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Priesterroth, L., Grammes, J., Holtz, K., Reinwarth, A. & Kubiak, T. Gamification and behavior change techniques in diabetes self-management apps. J. Diabetes Sci. Technol. 13, 954–958 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wu, Y. et al. A comparison of functional features in Chinese and US mobile apps for diabetes self-management: a systematic search in app stores and content analysis. JMIR mHealth uHealth 7, e13971 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Stach, M. et al. Mobile health app database: a repository for quality ratings of mHealth apps, 427–432.

  • Terhorst, Y. et al. Systematic evaluation of content and quality of English and German pain apps in European app stores. Internet Interv. 24, 100376 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sander, L. B. et al. “Help for trauma from the app stores?” A systematic review and standardised rating of apps for Post-Traumatic Stress Disorder (PTSD). Eur. J. Psychotraumatol. 11, 1701788 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Terhorst, Y., Rathner, E.-M., Baumeister, H. & Sander, L. «Hilfe aus dem App-Store?»: Eine systematische Übersichtsarbeit und Evaluation von Apps zur Anwendung bei Depressionen. Verhaltenstherapie 28, 101–112 (2018).

    Article 

    Google Scholar 

  • Messner, E.-M. et al. The German version of the mobile app rating scale (MARS-G): development and validation study. JMIR mHealth uHealth 8, e14479 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Terhorst, Y. et al. Validation of the mobile application rating scale (MARS). PLoS ONE 15, e0241480 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wu, P. F. & Bernardi, R. Community attachment and emotional well-being: an empirical study of an online community for people with diabetes. ITP ahead-of-print (2020).

  • Hershcovitz, Y., Dar, S. & Feniger, E. Continuous reduction of blood glucose average during one year of glucose monitoring using a digital monitoring system in a high-risk population. Diabetes 67, 78-LB (2018).

    Article 

    Google Scholar 

  • Quinn, C. C. et al. Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control. Diabetes Care 34, 1934–1942 (2011).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Fu, H. N. C., Rizvi, R. F., Wyman, J. F. & Adam, T. J. Usability evaluation of four top-rated commercially available diabetes apps for adults with type 2 diabetes. Comput. Inform. Nurs. CIN 38, 274–280 (2020).

    PubMed 

    Google Scholar 

  • Osborn, C. Y. et al. One drop mobile: an evaluation of hemoglobin A1c improvement linked to app engagement. JMIR Diabetes 2, e21 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Deakin, T. The diabetes pandemic: Is structured education the solution or an unnecessary expense?. Pract. Diabetes 28, 1–14 (2011).

    Article 

    Google Scholar 

  • Portenhauser, A. A. et al. Mobile apps for older adults: systematic search and evaluation within online stores. JMIR Aging 4, e23313 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Domhardt, M. et al. Mobile-based interventions for common mental disorders in youth: a systematic evaluation of pediatric health apps. Child Adolesc. Psychiatry Mental Health 15, 49 (2021).

    Article 

    Google Scholar 

  • Mudambi, S. M. & Schuff, D. What makes a helpful online review? A study of customer reviews on amazon.com. MIS Q. 34, 185–200 (2010).

    Article 

    Google Scholar 

  • Ju, C. et al. Effect of peer support on diabetes distress: a cluster randomized controlled trial. Diabetic Med. J. Br. Diabetic Assoc. 35, 770–775 (2018).

    Article 
    CAS 

    Google Scholar 

  • Song, Y., Nam, S., Park, S., Shin, I.-S. & Ku, B. J. The impact of social support on self-care of patients with diabetes: what is the effect of diabetes type? Systematic review and meta-analysis. Diabetes Educ. 43, 396–412 (2017).

    Article 
    PubMed 

    Google Scholar 

  • Strom, J. L. & Egede, L. E. The impact of social support on outcomes in adult patients with type 2 diabetes: a systematic review. Curr. Diabetes Rep. 12, 769–781 (2012).

    Article 

    Google Scholar 

  • Sharkey, S. et al. Ethical practice in internet research involving vulnerable people: lessons from a self-harm discussion forum study (SharpTalk). J. Med. Ethics 37, 752–758 (2011).

    Article 
    PubMed 

    Google Scholar 

  • Vlahu-Gjorgievska, E., Alkorbi, A. S., Nushayli, M. M. & Win, K. W. Persuasive social support features in diabetes self-management mHealth applications.

  • Tang, P. Y. et al. Complementarity of digital health and peer support: “This Is What’s Coming”. Front. Clin. Diabetes Healthc. 2 (2021).

  • Jimenez, G. et al. Reminders for medication adherence in type 2 diabetes management apps. J. Pharm. Pract. Res. 50, 78–81 (2020).

    Article 

    Google Scholar 

  • Duncan-Carnesciali, J., Wallace, B. C. & Odlum, M. An evaluation of a diabetes self-management education (DSME) intervention delivered using avatar-based technology: certified diabetes educators’ ratings and perceptions. Diabetes Educ. 44, 216–224 (2018).

    Article 
    PubMed 

    Google Scholar 

  • Faddoul G. & Chatterjee, S. The virtual diabetician: a prototype for a virtual avatar for diabetes treatment using persuasion through storytelling. Proceedings of the 25th Americas Conference on Information Systems (AMCIS’2019), Cancún, Mexico, 15–17 August 2019.

  • Wonggom, P., Kourbelis, C., Newman, P., Du, H. & Clark, R. A. Effectiveness of avatar-based technology in patient education for improving chronic disease knowledge and self-care behavior: a systematic review. JBI Database Syst. Rev. Implement. Rep. 17, 1101–1129 (2019).

    Article 

    Google Scholar 

  • Oinas-Kukkonen, H. Persuasive technology, in Third International Conference, PERSUASIVE 2008, Oulu, Finland, June 4–6, 2008 Proceedings 5033 (2008).

  • Cappon, G., Acciaroli, G., Vettoretti, M., Facchinetti, A. & Sparacino, G. Wearable continuous glucose monitoring sensors: a revolution in diabetes treatment. Electronics 6, 65 (2017).

    Article 

    Google Scholar 

  • Kim, M. T. et al. Motivating people to sustain healthy lifestyles using persuasive technology: a pilot study of Korean Americans with prediabetes and type 2 diabetes. Patient Educ. Couns. 102, 709–717 (2019).

    Article 
    PubMed 

    Google Scholar 

  • Christie, D. How do children and adolescents understand their diabetes?. Pract. Diab. 36, 117 (2019).

    Article 

    Google Scholar 

  • Geirhos, A. et al. Involving patients’ perspective in the development of an internet- and mobile-based CBT intervention for adolescents with chronic medical conditions: findings from a qualitative study. Internet Interv. 24, 100383 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Miller, K. M., Beck, R. W., Foster, N. C. & Maahs, D. M. HbA1c levels in type 1 diabetes from early childhood to older adults: a deeper dive into the influence of technology and socioeconomic status on HbA1c in the T1D exchange clinic registry findings. Diabetes Technol. Ther. 22, 645–650 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Swartwout, E., El-Zein, A., Deyo, P., Sweenie, R. & Streisand, R. Use of gaming in self-management of diabetes in teens. Curr. Diabetes Rep. 16, 59 (2016).

    Article 

    Google Scholar 

  • Domhardt, M., Schröder, A., Geirhos, A., Steubl, L. & Baumeister, H. Efficacy of digital health interventions in youth with chronic medical conditions: a meta-analysis. Internet Interv. 24, 100373 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Hermanns, N., Ehrmann, D., Finke-Groene, K. & Kulzer, B. Trends in diabetes self-management education: where are we coming from and where are we going? A narrative review. Diabetic Med. J. Br. Diabetic Assoc. 37, 436–447 (2020).

    CAS 

    Google Scholar 

  • Zhang, Y. et al. Exploration of users’ perspectives and needs and design of a type 1 diabetes management mobile app: mixed-methods study. JMIR mHealth uHealth 6, e11400 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Baptista, S. et al. What do adults with type 2 diabetes want from the “perfect” app? Results from the second diabetes MILES: Australia (MILES-2) study. Diabetes Technol. Ther. 21, 393–399 (2019).

    Article 
    PubMed 

    Google Scholar 

  • Bendig, E. et al. Internet-based interventions in chronic somatic disease. Deutsches Arzteblatt Int. 115, 659–665 (2018).

    Google Scholar 

  • Lunkenheimer, F. et al. Effectiveness and cost-effectiveness of guided Internet- and mobile-based CBT for adolescents and young adults with chronic somatic conditions and comorbid depression and anxiety symptoms (youthCOACHCD): Study protocol for a multicentre randomized controlled trial. Trials 21, 253 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Torous, J. B. et al. A hierarchical framework for evaluation and informed decision making regarding smartphone apps for clinical care. Psychiatr. Serv.  69, 498–500 (2018).

    Article 
    PubMed 

    Google Scholar 

  • Baumel, A., Faber, K., Mathur, N., Kane, J. M. & Muench, F. Enlight: A comprehensive quality and therapeutic potential evaluation tool for mobile and web-based eHealth interventions. J. Med. Internet Res. 19, e82 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Huckvale, K., Torous, J. & Larsen, M. E. Assessment of the data sharing and privacy practices of smartphone apps for depression and smoking cessation. JAMA Netw. Open 2, e192542 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

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