This paper is in the following e-collection/theme issue:

Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps (374) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1399)

Published on in Vol 6, No 5 (2018): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10512, first published .
Supply and Demand in mHealth Apps for Persons With Multiple Sclerosis: Systematic Search in App Stores and Scoping Literature Review

Supply and Demand in mHealth Apps for Persons With Multiple Sclerosis: Systematic Search in App Stores and Scoping Literature Review

Supply and Demand in mHealth Apps for Persons With Multiple Sclerosis: Systematic Search in App Stores and Scoping Literature Review

Authors of this article:

Guido Giunti1, 2 Author Orcid Image ;   Estefanía Guisado Fernández3 Author Orcid Image ;   Enrique Dorronzoro Zubiete4 Author Orcid Image ;   Octavio Rivera Romero4 Author Orcid Image
Article Authors Cited by (53) Tweetations (30) Metrics

Journals

  1. Richardson B, Dol J, Rutledge K, Monaghan J, Orovec A, Howie K, Boates T, Smit M, Campbell-Yeo M. Evaluation of Mobile Apps Targeted to Parents of Infants in the Neonatal Intensive Care Unit: Systematic App Review. JMIR mHealth and uHealth 2019;7(4):e11620 View
  2. Vo V, Auroy L, Sarradon-Eck A. Patients’ Perceptions of mHealth Apps: Meta-Ethnographic Review of Qualitative Studies. JMIR mHealth and uHealth 2019;7(7):e13817 View
  3. Giunti G, Rivera-Romero O, Kool J, Bansi J, Sevillano J, Granja-Dominguez A, Izquierdo-Ayuso G, Giunta D. Evaluation of More Stamina, a Mobile App for Fatigue Management in Persons with Multiple Sclerosis: Protocol for a Feasibility, Acceptability, and Usability Study. JMIR Research Protocols 2020;9(8):e18196 View
  4. Apolinário-Hagen J, Menzel M, Hennemann S, Salewski C. Acceptance of Mobile Health Apps for Disease Management Among People With Multiple Sclerosis: Web-Based Survey Study. JMIR Formative Research 2018;2(2):e11977 View
  5. Xie B, Champion J, Kwak J, Fleischmann K. Mobile Health, Information Preferences, and Surrogate Decision-Making Preferences of Family Caregivers of People With Dementia in Rural Hispanic Communities: Cross-Sectional Questionnaire Study. Journal of Medical Internet Research 2018;20(12):e11682 View
  6. Fernandez-Luque L, Labarta J, Palmer E, Koledova E. Content Analysis of Apps for Growth Monitoring and Growth Hormone Treatment: Systematic Search in the Android App Store. JMIR mHealth and uHealth 2020;8(2):e16208 View
  7. Benjumea J, Ropero J, Rivera-Romero O, Dorronzoro-Zubiete E, Carrasco A. Assessment of the Fairness of Privacy Policies of Mobile Health Apps: Scale Development and Evaluation in Cancer Apps. JMIR mHealth and uHealth 2020;8(7):e17134 View
  8. Babbage D, van Kessel K, Drown J, Thomas S, Sezier A, Thomas P, Kersten P. MS Energize: Field trial of an app for self-management of fatigue for people with multiple sclerosis. Internet Interventions 2019;18:100291 View
  9. Martinez-Millana A, Zettl A, Floch J, Calvo-Lerma J, Sevillano J, Ribes-Koninckx C, Traver V. The Potential of Self-Management mHealth for Pediatric Cystic Fibrosis: Mixed-Methods Study for Health Care and App Assessment. JMIR mHealth and uHealth 2019;7(4):e13362 View
  10. Schleimer E, Pearce J, Barnecut A, Rowles W, Lizee A, Klein A, Block V, Santaniello A, Renschen A, Gomez R, Keshavan A, Gelfand J, Henry R, Hauser S, Bove R. A Precision Medicine Tool for Patients With Multiple Sclerosis (the Open MS BioScreen): Human-Centered Design and Development. Journal of Medical Internet Research 2020;22(7):e15605 View
  11. van Beek J, van Wegen E, Rietberg M, Nyffeler T, Bohlhalter S, Kamm C, Nef T, Vanbellingen T. Feasibility of a Home-Based Tablet App for Dexterity Training in Multiple Sclerosis: Usability Study. JMIR mHealth and uHealth 2020;8(6):e18204 View
  12. Marrie R, Leung S, Tyry T, Cutter G, Fox R, Salter A. Use of eHealth and mHealth technology by persons with multiple sclerosis. Multiple Sclerosis and Related Disorders 2019;27:13 View
  13. Thomas S, Pulman A, Thomas P, Collard S, Jiang N, Dogan H, Davies Smith A, Hourihan S, Roberts F, Kersten P, Pretty K, Miller J, Stanley K, Gay M. Digitizing a Face-to-Face Group Fatigue Management Program: Exploring the Views of People With Multiple Sclerosis and Health Care Professionals Via Consultation Groups and Interviews. JMIR Formative Research 2019;3(2):e10951 View
  14. Jongen P, ter Veen G, Lemmens W, Donders R, van Noort E, Zeinstra E. The Interactive Web-Based Program MSmonitor for Self-Management and Multidisciplinary Care in Persons With Multiple Sclerosis: Quasi-Experimental Study of Short-Term Effects on Patient Empowerment. Journal of Medical Internet Research 2020;22(3):e14297 View
  15. van Haasteren A, Gille F, Fadda M, Vayena E. Development of the mHealth App Trustworthiness checklist. DIGITAL HEALTH 2019;5 View
  16. AL-Eitan L, Al Qudah M, Al Qawasmeh M. Association of Multiple Sclerosis Phenotypes with Single Nucleotide Polymorphisms of IL7R, LAG3, and CD40 Genes in a Jordanian Population: A Genotype-Phenotype Study. Biomolecules 2020;10(3):356 View
  17. Chien S, Islam M, Yeh C, Chien P, Chen C, Chin Y, Lin M. Mutual-Aid Mobile App for Emergency Care: Feasibility Study. JMIR Formative Research 2020;4(3):e15494 View
  18. Klaas V, Troster G, Walt H, Jenewein J. Remotely Monitoring Cancer-Related Fatigue Using the Smart-Phone: Results of an Observational Study. Information 2018;9(11):271 View
  19. Scholz M, Haase R, Schriefer D, Voigt I, Ziemssen T. Electronic Health Interventions in the Case of Multiple Sclerosis: From Theory to Practice. Brain Sciences 2021;11(2):180 View
  20. Gromisch E, Turner A, Haselkorn J, Lo A, Agresta T. Mobile health (mHealth) usage, barriers, and technological considerations in persons with multiple sclerosis: a literature review. JAMIA Open 2021;4(3) View
  21. Rahn A, Solari A, Beckerman H, Nicholas R, Wilkie D, Heesen C, Giordano A. “I Will Respect the Autonomy of My Patient”. International Journal of MS Care 2020;22(6):285 View
  22. Safian A, Davodvand S, Masoudi R, Sedehi M, Tahmasebian S, Jivad N. The effect of mobile-based self-care program on balance of people with Multiple Sclerosis. Iranian Journal of Rehabilitation Research in Nursing 2020;7(1):33 View
  23. Lobo E, Frølich A, Kensing F, Rasmussen L, Livingston P, Grundy J, Abdelrazek M. mHealth applications to support caregiver needs and engagement during stroke recovery: A content review. Research in Nursing & Health 2021;44(1):213 View
  24. Hsieh K, Fanning J, Frechette M, Sosnoff J. Usability of a Fall Risk mHealth App for People With Multiple Sclerosis: Mixed Methods Study. JMIR Human Factors 2021;8(1):e25604 View
  25. Palotai M, Wallack M, Kujbus G, Dalnoki A, Guttmann C. Usability of a Mobile App for Real-Time Assessment of Fatigue and Related Symptoms in Patients With Multiple Sclerosis: Observational Study. JMIR mHealth and uHealth 2021;9(4):e19564 View
  26. Chassan C, Jost C, Sévène M, Cras O, De Broucker T, Archambault D. Encouraging physical activities at home for people with multiple sclerosis with mHealth tools: A literature review. Technology and Disability 2021;33(2):87 View
  27. De Angelis M, Lavorgna L, Carotenuto A, Petruzzo M, Lanzillo R, Brescia Morra V, Moccia M. Digital Technology in Clinical Trials for Multiple Sclerosis: Systematic Review. Journal of Clinical Medicine 2021;10(11):2328 View
  28. Schwab J, Schobel J, Werle S, Furstberger A, Ikonomi N, Szekely R, Thiam P, Huhne R, Jahn N, Schuler R, Kuhn P, Holderried M, Steger F, Reichert M, Kaisers U, Kestler A, Seufferlein T, Kestler H. Perspective on mHealth Concepts to Ensure Users’ Empowerment–From Adverse Event Tracking for COVID-19 Vaccinations to Oncological Treatment. IEEE Access 2021;9:83863 View
  29. Mokhberdezfuli M, Ayatollahi H, Naser Moghadasi A, Taiar R. A Smartphone-based Application for Self-Management in Multiple Sclerosis. Journal of Healthcare Engineering 2021;2021:1 View
  30. Polhemus A, Simblett S, Dawe Lane E, Elliott B, Jilka S, Negbenose E, Burke P, Weyer J, Novak J, Dockendorf M, Temesi G, Wykes T. Experiences of health tracking in mobile apps for multiple sclerosis: A qualitative content analysis of user reviews. Multiple Sclerosis and Related Disorders 2023;69:104435 View
  31. Chute C, French T, Raman S, Bradley J. User Requirements for Comanaged Digital Health and Care: Review. Journal of Medical Internet Research 2022;24(6):e35337 View
  32. Ouwerkerk M, Eijssen I, van der Linden M, Wijnands I, Dorssers F, Rietberg M, Beckerman H, de Groot V. A Smartphone Application to Assess Real-Time and Individual-Specific Societal Participation: A Development and Usability Study. Archives of Physical Medicine and Rehabilitation 2022;103(10):1958 View
  33. Gonzales A, Custodio R, Lapitan M, Ladia M. Mobile applications in the Philippines during the COVID-19 pandemic: systematic search, use case mapping, and quality assessment using the Mobile App Rating Scale (MARS). BMC Digital Health 2023;1(1) View
  34. Warsinsky S, Schmidt-Kraepelin M, Rank S, Thiebes S, Sunyaev A. Conceptual Ambiguity Surrounding Gamification and Serious Games in Health Care: Literature Review and Development of Game-Based Intervention Reporting Guidelines (GAMING). Journal of Medical Internet Research 2021;23(9):e30390 View
  35. Sippel A, Riemann-Lorenz K, Pöttgen J, Wiedemann R, Drixler K, Bitzer E, Holmberg C, Lezius S, Heesen C. Validation of the German eHealth impact questionnaire for online health information users affected by multiple sclerosis. BMC Medical Informatics and Decision Making 2022;22(1) View
  36. Salimzadeh Z, Damanabi S, Ferdousi R, Shaafi S, Kalankesh L. A mobile app (IDoThis) for multiple sclerosis self-management: development and initial evaluation. BMC Medical Informatics and Decision Making 2022;22(1) View
  37. Burrell A, Zrubka Z, Champion A, Zah V, Vinuesa L, Holtorf A, Di Bidino R, Earla J, Entwistle J, Boltyenkov A, Braileanu G, Kolasa K, Roydhouse J, Asche C, Redekop K, Pfeiffer C, Le L, Janodia M, Sharkawy M, Şaylan M, Lee S, Glynn S, Ganguli A, Badawy S, Carvalho L, Ernst F, Seal B, van Steen C, Patel N, Lee H, Doe A, Strouss L, Angelillo L, Patel C, Paul S. How Useful Are Digital Health Terms for Outcomes Research? An ISPOR Special Interest Group Report. Value in Health 2022;25(9):1469 View
  38. Schwab P, Karlen W. A Deep Learning Approach to Diagnosing Multiple Sclerosis from Smartphone Data. IEEE Journal of Biomedical and Health Informatics 2021;25(4):1284 View
  39. Thomas S, Pulman A, Dogan H, Jiang N, Passmore D, Pretty K, Fairbanks B, Davies Smith A, Thomas P. Creating a Digital Toolkit to Reduce Fatigue and Promote Quality of Life in Multiple Sclerosis: Participatory Design and Usability Study. JMIR Formative Research 2021;5(12):e19230 View
  40. Nittas V, Zecca C, Kamm C, Kuhle J, Chan A, von Wyl V, Mbada C. Digital health for chronic disease management: An exploratory method to investigating technology adoption potential. PLOS ONE 2023;18(4):e0284477 View
  41. ÇETİN B, TEKEOĞLU TOSUN A, ONAY T. Multipl Skleroz’lu Bireylerin Sosyal Yaşam Kalitelerine Teknolojinin Etkisi. Ergoterapi ve Rehabilitasyon Dergisi 2021;8(3):221 View
  42. Guardado S, Mylonopoulou V, Rivera-Romero O, Patt N, Bansi J, Giunti G. An Exploratory Study on the Utility of Patient-Generated Health Data as a Tool for Health Care Professionals in Multiple Sclerosis Care. Methods of Information in Medicine 2023;62(05/06):165 View
  43. Üstündağ S, Yeşilbalkan Ö, Kabay S. The effect of a mobile education application (MobilMS) developed for multiple sclerosis patients in Turkey on symptom management and quality of life: A randomized controlled study. Multiple Sclerosis and Related Disorders 2024;81:105342 View
  44. Benjumea J, Ropero J, Dorronzoro-Zubiete E, Rivera-Romero O, Carrasco A. A Proposal for a Robust Validated Weighted General Data Protection Regulation-Based Scale to Assess the Quality of Privacy Policies of Mobile Health Applications: An eDelphi Study. Methods of Information in Medicine 2023;62(05/06):154 View
  45. Giunti G, Doherty C. Cocreating an Automated mHealth Apps Systematic Review Process With Generative AI: Design Science Research Approach. JMIR Medical Education 2024;10:e48949 View
  46. Vacchi L, Zirone E, Strina V, Cavaletti G, Ferrarese C. Mobile Applications to Support Multiple Sclerosis Communities: The Post-COVID-19 Scenario. Telemedicine and e-Health 2024;30(6):e1615 View
  47. Tea F, Groh A, Lacey C, Fakolade A. A scoping review assessing the usability of digital health technologies targeting people with multiple sclerosis. npj Digital Medicine 2024;7(1) View
  48. Ali S, Alizai H, Hagos D, Rubio S, Calabia D, Serrano Jimenez P, Senthil V, Appel L. mHealth Apps for Dementia, Alzheimer Disease, and Other Neurocognitive Disorders: Systematic Search and Environmental Scan. JMIR mHealth and uHealth 2024;12:e50186 View
  49. Solaiyan R, Dheeraj K, AGK S, Soundappan K, Ashok K, Rajni S. Development and Evaluation of a mHealth app - (ReMiT-MS app) for Rehabilitation of Individuals with Relapsing-remitting Multiple Sclerosis - A Mixed Methods, Pragmatic Randomized Controlled Trial - Study Protocol. Journal of Novel Physiotherapy and Rehabilitation 2024;8(2):022 View
  50. Zigdon A, Zwilling M, Zigdon O, Reges O. Health Maintenance Organization–mHealth Versus Face-to-Face Interaction for Health Care in Israel: Cross-Sectional Web-Based Survey Study. Journal of Medical Internet Research 2024;26:e55350 View
  51. Sarpourian F, Poursadeghfard M, Erfannia L, Khayami S, Sharifian R. Identifying and Validating Data Elements and Main Characteristics of a Teleconsultation and Televisit System for Patients with Multiple Sclerosis in Iran. Telemedicine and e-Health 2024 View

Books/Policy Documents

  1. Chassan C, Jost C, Sévène M, Cras O, De Broucker T, Archambault D. Computers Helping People with Special Needs. View