Published on in Vol 6, No 2 (2018): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/8996, first published .
Exploring the Specific Needs of Persons with Multiple Sclerosis for mHealth Solutions for Physical Activity: Mixed-Methods Study

Exploring the Specific Needs of Persons with Multiple Sclerosis for mHealth Solutions for Physical Activity: Mixed-Methods Study

Exploring the Specific Needs of Persons with Multiple Sclerosis for mHealth Solutions for Physical Activity: Mixed-Methods Study

Journals

  1. Giunti G, Guisado Fernández E, Dorronzoro Zubiete E, Rivera Romero O. Supply and Demand in mHealth Apps for Persons With Multiple Sclerosis: Systematic Search in App Stores and Scoping Literature Review. JMIR mHealth and uHealth 2018;6(5):e10512 View
  2. 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
  3. Mirkovic J, Jessen S, Kristjansdottir O, Krogseth T, Koricho A, Ruland C. Developing Technology to Mobilize Personal Strengths in People with Chronic Illness: Positive Codesign Approach. JMIR Formative Research 2018;2(1):e10774 View
  4. Giunti G, Mylonopoulou V, Rivera Romero O. More Stamina, a Gamified mHealth Solution for Persons with Multiple Sclerosis: Research Through Design. JMIR mHealth and uHealth 2018;6(3):e51 View
  5. Rossmann C, Riesmeyer C, Brew-Sam N, Karnowski V, Joeckel S, Chib A, Ling R. Appropriation of Mobile Health for Diabetes Self-Management: Lessons From Two Qualitative Studies. JMIR Diabetes 2019;4(1):e10271 View
  6. 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
  7. Pardhan S, Nakafero G, Raman R, Sapkota R. Barriers to diabetes awareness and self-help are influenced by people's demographics: perspectives of South Asians with type 2 diabetes. Ethnicity & Health 2020;25(6):843 View
  8. 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
  9. Van Geel F, Geurts E, Abasıyanık Z, Coninx K, Feys P. Feasibility study of a 10-week community-based program using the WalkWithMe application on physical activity, walking, fatigue and cognition in persons with Multiple Sclerosis. Multiple Sclerosis and Related Disorders 2020;42:102067 View
  10. Molina-Recio G, Molina-Luque R, Jiménez-García A, Ventura-Puertos P, Hernández-Reyes A, Romero-Saldaña M. Proposal for the User-Centered Design Approach for Health Apps Based on Successful Experiences: Integrative Review. JMIR mHealth and uHealth 2020;8(4):e14376 View
  11. Minen M, Schaubhut K, Morio K. Smartphone based behavioral therapy for pain in multiple sclerosis (MS) patients: A feasibility acceptability randomized controlled study for the treatment of comorbid migraine and ms pain. Multiple Sclerosis and Related Disorders 2020;46:102489 View
  12. Flors-Sidro J, Househ M, Abd-Alrazaq A, Vidal-Alaball J, Fernandez-Luque L, Sanchez-Bocanegra C. Analysis of Diabetes Apps to Assess Privacy-Related Permissions: Systematic Search of Apps. JMIR Diabetes 2021;6(1):e16146 View
  13. Simblett S, Evans J, Greer B, Curtis H, Matcham F, Radaelli M, Mulero P, Arévalo M, Polhemus A, Ferrao J, Gamble P, Comi G, Wykes T. Engaging across dimensions of diversity: A cross-national perspective on mHealth tools for managing relapsing remitting and progressive multiple sclerosis. Multiple Sclerosis and Related Disorders 2019;32:123 View
  14. Floch J, Vilarinho T, Zettl A, Ibanez-Sanchez G, Calvo-Lerma J, Stav E, Haro P, Aalberg A, Fides-Valero A, Bayo Montón J. Users’ Experiences of a Mobile Health Self-Management Approach for the Treatment of Cystic Fibrosis: Mixed Methods Study. JMIR mHealth and uHealth 2020;8(7):e15896 View
  15. Giunti G. 3MD for Chronic Conditions, a Model for Motivational mHealth Design: Embedded Case Study. JMIR Serious Games 2018;6(3):e11631 View
  16. 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
  17. Monteiro-Guerra F, Signorelli G, Tadas S, Dorronzoro Zubiete E, Rivera Romero O, Fernandez-Luque L, Caulfield B. A Personalized Physical Activity Coaching App for Breast Cancer Survivors: Design Process and Early Prototype Testing. JMIR mHealth and uHealth 2020;8(7):e17552 View
  18. 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
  19. 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
  20. Benjumea J, Ropero J, Rivera-Romero O, Dorronzoro-Zubiete E, Carrasco A. Privacy Assessment in Mobile Health Apps: Scoping Review. JMIR mHealth and uHealth 2020;8(7):e18868 View
  21. 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
  22. Bhattacharyya O, Mossman K, Gustafsson L, Schneider E. Using Human-Centered Design to Build a Digital Health Advisor for Patients With Complex Needs: Persona and Prototype Development. Journal of Medical Internet Research 2019;21(5):e10318 View
  23. Wendrich K, van Oirschot P, Martens M, Heerings M, Jongen P, Krabbenborg L. Toward Digital Self-monitoring of Multiple Sclerosis. International Journal of MS Care 2019;21(6):282 View
  24. Jessen S, Mirkovic J, Ruland C. Creating Gameful Design in mHealth: A Participatory Co-Design Approach. JMIR mHealth and uHealth 2018;6(12):e11579 View
  25. 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
  26. 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
  27. van Oirschot P, Heerings M, Wendrich K, den Teuling B, Martens M, Jongen P. Symbol Digit Modalities Test Variant in a Smartphone App for Persons With Multiple Sclerosis: Validation Study. JMIR mHealth and uHealth 2020;8(10):e18160 View
  28. Pratap A, Grant D, Vegesna A, Tummalacherla M, Cohan S, Deshpande C, Mangravite L, Omberg L. Evaluating the Utility of Smartphone-Based Sensor Assessments in Persons With Multiple Sclerosis in the Real-World Using an App (elevateMS): Observational, Prospective Pilot Digital Health Study. JMIR mHealth and uHealth 2020;8(10):e22108 View
  29. 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
  30. Meshgin D, Kersten-Oertel M. Multiple sclerosis image-guided subcutaneous injections using augmented reality guided imagery. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 2021;9(4):370 View
  31. van Kessel K, Babbage D, Kersten P, Drown J, Sezier A, Thomas P, Thomas S. Design considerations for a multiple sclerosis fatigue mobile app MS Energize: A pragmatic iterative approach using usability testing and resonance checks. Internet Interventions 2021;24:100371 View
  32. 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
  33. 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
  34. 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
  35. Lam H, Ho G, Mo D, Tang V. Enhancing data-driven elderly appointment services in domestic care communities under COVID-19. Industrial Management & Data Systems 2021;121(7):1552 View
  36. REMY C, VALET M, STOQUART G, EL SANKARI S, VAN PESCH V, DE HAAN A, LEJEUNE T. Telecommunication and rehabilitation for patients with multiple sclerosis: access and willingness to use. A cross-sectional study. European Journal of Physical and Rehabilitation Medicine 2020;56(4) View
  37. Velez M, Lugo-Agudelo L, Patiño Lugo D, Glenton C, Posada A, Mesa Franco L, Negrini S, Kiekens C, Spir Brunal M, Roberg A, Cruz Sarmiento K. Factors that influence the provision of home-based rehabilitation services for people needing rehabilitation: a qualitative evidence synthesis. Cochrane Database of Systematic Reviews 2023;2023(2) View
  38. Petracca F, Tempre R, Cucciniello M, Ciani O, Pompeo E, Sannino L, Lovato V, Castaman G, Ghirardini A, Tarricone R. An Electronic Patient-Reported Outcome Mobile App for Data Collection in Type A Hemophilia: Design and Usability Study. JMIR Formative Research 2021;5(12):e25071 View
  39. van Beek J, Lehnick D, Pastore-Wapp M, Wapp S, Kamm C, Nef T, Vanbellingen T. Tablet app-based dexterity training in multiple sclerosis (TAD-MS): a randomized controlled trial. Disability and Rehabilitation: Assistive Technology 2024;19(3):889 View
  40. Galliford N, Yin K, Blandford A, Jung J, Lau A. Patient Work Personas of Type 2 Diabetes—A Data-Driven Approach to Persona Development and Validation. Frontiers in Digital Health 2022;4 View
  41. 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
  42. Tedesco Triccas L, Maris A, Lamers I, Calcius J, Coninx K, Spooren A, Feys P. Do people with multiple sclerosis perceive upper limb improvements from robotic-mediated therapy? A mixed methods study. Multiple Sclerosis and Related Disorders 2022;68:104159 View
  43. Wendrich K, Krabbenborg L. Digital Self-monitoring of Multiple Sclerosis: Interview Study With Dutch Health Care Providers on the Expected New Configuration of Roles and Responsibilities. JMIR mHealth and uHealth 2022;10(4):e30224 View
  44. Polhemus A, Sieber C, Haag C, Sylvester R, Kool J, Gonzenbach R, von Wyl V, Li-Jessen N. Non-equivalent, but still valid: Establishing the construct validity of a consumer fitness tracker in persons with multiple sclerosis. PLOS Digital Health 2023;2(1):e0000171 View
  45. Neal W, Richardson E, Motl R. Informing the development of a mobile application for the physical activity guidelines in multiple sclerosis: a qualitative, pluralistic approach. Disability and Rehabilitation: Assistive Technology 2022:1 View
  46. Thompson C, Pulido M, Babu S, Zenzola N, Chiu C. Communication between persons with multiple sclerosis and their health care providers: A scoping review. Patient Education and Counseling 2022;105(12):3341 View
  47. 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
  48. 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
  49. Torres-Castaño A, Abt-Sacks A, Toledo-Chávarri A, Suarez-Herrera J, Delgado-Rodríguez J, León-Salas B, González-Hernández Y, Carmona-Rodríguez M, Serrano-Aguilar P. Ethical, Legal, Organisational and Social Issues of Teleneurology: A Scoping Review. International Journal of Environmental Research and Public Health 2023;20(4):3694 View
  50. Bevens W, Reece J, Jelinek P, Weiland T, Nag N, Simpson-Yap S, Gray K, Jelinek G, Neate S. The feasibility of an online educational lifestyle program for people with multiple sclerosis: A qualitative analysis of participant semi-structured interviews. DIGITAL HEALTH 2022;8:205520762211237 View
  51. Li X, You K. Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system. Frontiers in Public Health 2022;10 View
  52. Lee J, Lee J. The Relationship Between the Characteristics of Self-Tracking Data and User Experience Factors for Data-Driven Product Service System Design. Archives of Design Research 2021;34(3):193 View
  53. Barrios L, Amon R, Oldrati P, Hilty M, Holz C, Lutterotti A. Cognitive fatigability assessment test (cFAST): Development of a new instrument to assess cognitive fatigability and pilot study on its association to perceived fatigue in multiple sclerosis. DIGITAL HEALTH 2022;8:205520762211177 View
  54. 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
  55. Reinhardt G, Schwarz P, Harst L. Non-use of telemedicine: A scoping review. Health Informatics Journal 2021;27(4):146045822110431 View
  56. Haase R, Voigt I, Scholz M, Schlieter H, Benedict M, Susky M, Dillenseger A, Ziemssen T. Profiles of eHealth Adoption in Persons with Multiple Sclerosis and Their Caregivers. Brain Sciences 2021;11(8):1087 View
  57. Polhemus A, Novak J, Majid S, Simblett S, Morris D, Bruce S, Burke P, Dockendorf M, Temesi G, Wykes T. Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User Perspectives. JMIR Mental Health 2022;9(4):e25249 View
  58. Sieber C, Haag C, Polhemus A, Sylvester R, Kool J, Gonzenbach R, von Wyl V. Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis. Frontiers in Digital Health 2023;5 View
  59. Alder G, Taylor D, Rashid U, Olsen S, Brooks T, Terry G, Niazi I, Signal N. A Brain Computer Interface Neuromodulatory Device for Stroke Rehabilitation: Iterative User-Centered Design Approach. JMIR Rehabilitation and Assistive Technologies 2023;10:e49702 View
  60. Lu Z, Signer T, Sylvester R, Gonzenbach R, von Wyl V, Haag C. Implementation of Remote Activity Sensing to Support a Rehabilitation Aftercare Program: Observational Mixed Methods Study With Patients and Health Care Professionals. JMIR mHealth and uHealth 2023;11:e50729 View
  61. 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
  62. 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
  63. Zhakhina G, Tapinova K, Kanabekova P, Kainazarov T. Pre-consultation history taking systems and their impact on modern practices: Advantages and limitations. Journal of Clinical Medicine of Kazakhstan 2023;20(6):26 View
  64. 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
  65. Lau S, Bright L, Connor L, Baum C. Experiences With Mobile Health-Enabled Ambulatory Monitoring Among Stroke Survivors: A Qualitative Study. OTJR: Occupational Therapy Journal of Research 2024 View
  66. Braun M, Carlier S, De Backere F, Van De Velde M, De Turck F, Crombez G, De Paepe A. Identifying app components that promote physical activity: a group concept mapping study. PeerJ 2024;12:e17100 View
  67. Simblett S, Dawe-Lane E, Gilpin G, Morris D, White K, Erturk S, Devonshire J, Lees S, Zorbas S, Polhemus A, Temesi G, Cummins N, Hotopf M, Wykes T. Data visualization preferences in remote measurement technology for individuals living with depression, epilepsy, and multiple sclerosis: a qualitative study (Preprint). Journal of Medical Internet Research 2022 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
  2. Dorronzoro-Zubiete E, Rivera-Romero O, Nuñez-Benjumea F, Cervera-Torres S. Personalized Health Systems for Cardiovascular Disease. View