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

mHealth for Patient Education (276) mHealth for Wellness, Behavior Change and Prevention (3156) Use and User Demographics of mHealth (372) Mobile Apps for Dermatology and Prevention (21) Skin Cancer and Melanoma Prevention (121)

Published on in Vol 7, No 7 (2019): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13844, first published .
Patient Attitudes and Their Awareness Towards Skin Cancer–Related Apps: Cross-Sectional Survey

Patient Attitudes and Their Awareness Towards Skin Cancer–Related Apps: Cross-Sectional Survey

Patient Attitudes and Their Awareness Towards Skin Cancer–Related Apps: Cross-Sectional Survey

Authors of this article:

Theresa Steeb1 Author Orcid Image ;   Anja Wessely1 Author Orcid Image ;   Sebastian Mastnik1 Author Orcid Image ;   Titus Josef Brinker2 Author Orcid Image ;   Lars Einar French1 Author Orcid Image ;   Anne-Charlotte Niesert1 Author Orcid Image ;   Carola Berking1 Author Orcid Image ;   Markus Vincent Heppt1 Author Orcid Image
Article Authors Cited by (19) Tweetations (8) Metrics

Journals

  1. Kaliyadan F, Ashique K. Use of mobile applications in dermatology. Indian Journal of Dermatology 2020;65(5):371 View
  2. Jutzi T, Krieghoff-Henning E, Holland-Letz T, Utikal J, Hauschild A, Schadendorf D, Sondermann W, Fröhling S, Hekler A, Schmitt M, Maron R, Brinker T. Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective. Frontiers in Medicine 2020;7 View
  3. Kong F, Horsham C, Ngoo A, Soyer H, Janda M. Review of smartphone mobile applications for skin cancer detection: what are the changes in availability, functionality, and costs to users over time?. International Journal of Dermatology 2021;60(3):289 View
  4. El Abbadi S, Susok L, Stockfleth E, Bechara F, Gambichler T, Herbrandt S, Goldschmidtböing L, Sand M. Comparison of the Skin Cancer Quality of Life Impact Tool and the Skin Cancer Index Questionnaire in Measurement of Health-Related Quality of Life and the Effect of Patient Education Brochures in Patients with Actinic Keratosis, Non-melanoma Skin Cancer, and Cutaneous Melanoma. Dermatology and Therapy 2021;11(3):929 View
  5. Girbig G, Augustin M, Krensel M, Andrees V. Gesetzliches Hautkrebsscreening in Deutschland. Der Hautarzt 2021;72(11):953 View
  6. Shlivko I, Garanina O, Klemenova I, Uskova K, Mironycheva A, Dardyk V, Laskov V. Artificial intelligence: how it works and criteria for assessment. Consilium Medicum 2021;23(8):626 View
  7. Marchetti M, Sar-Graycar L, Dusza S, Nanda J, Kurtansky N, Rotemberg V, Hay J. Prevalence and Age-Related Patterns in Health Information–Seeking Behaviors and Technology Use Among Skin Cancer Survivors: Survey Study. JMIR Dermatology 2022;5(2):e36256 View
  8. Toma A, Boeriu E, Decean L, Bloanca V, Bratosin F, Levai M, Vasamsetti N, Alambaram S, Oprisoni A, Miutescu B, Hemaswini K, Juganaru I, Bondar A, Moise M. The Effects of Lack of Awareness in Age-Related Quality of Life, Coping with Stress, and Depression among Patients with Malignant Melanoma. Current Oncology 2023;30(2):1516 View
  9. Ukharov A, Shlivko I, Klemenova I, Garanina O, Uskova K, Mironycheva A, Stepanova Y. Skin cancer risk self-assessment using AI as a mass screening tool. Informatics in Medicine Unlocked 2023;38:101223 View
  10. Haggenmüller S, Krieghoff-Henning E, Jutzi T, Trapp N, Kiehl L, Utikal J, Fabian S, Brinker T. Digital Natives’ Preferences on Mobile Artificial Intelligence Apps for Skin Cancer Diagnostics: Survey Study. JMIR mHealth and uHealth 2021;9(8):e22909 View
  11. Sgouros D, Milia-Argyti A, Arvanitis D, Polychronaki E, Kousta F, Panagiotopoulos A, Theotokoglou S, Syrmali A, Theodoropoulos K, Stratigos A, Rigopoulos D, Katoulis A. Actinic Keratoses (AK): An Exploratory Questionnaire-Based Study of Patients’ Illness Perceptions. Current Oncology 2022;29(7):5150 View
  12. Pang N, Lau J, Fong S, Wong C, Tan K. Telemedicine Acceptance Among Older Adult Patients With Cancer: Scoping Review. Journal of Medical Internet Research 2022;24(3):e28724 View
  13. Jahn A, Navarini A, Cerminara S, Kostner L, Huber S, Kunz M, Maul J, Dummer R, Sommer S, Neuner A, Levesque M, Cheng P, Maul L. Over-Detection of Melanoma-Suspect Lesions by a CE-Certified Smartphone App: Performance in Comparison to Dermatologists, 2D and 3D Convolutional Neural Networks in a Prospective Data Set of 1204 Pigmented Skin Lesions Involving Patients’ Perception. Cancers 2022;14(15):3829 View
  14. Steeb T, Wessely A, Heppt M, Erdmann M, Klug S, Berking C. Opportunities to inform German residents about the possibility of skin cancer screening and to inform stakeholders to take appropriate actions: A qualitative approach. Cancer Medicine 2023;12(9):10829 View
  15. Lai J, Bao A, McCaffrey T, Salman R, Gelderen E, Rizk E, Thompson K, Epstein J, Bibee K, Scott J. Predictor Variables Associated With Dermatology Referral Completion and the Impact on Surgical Treatment: A Retrospective Cohort Study. Dermatologic Surgery 2024;50(1):28 View
  16. Jagemann I, Wensing O, Stegemann M, Hirschfeld G. Acceptance of Medical Artificial Intelligence in Skin Cancer Screening: Choice-Based Conjoint Survey. JMIR Formative Research 2024;8:e46402 View
  17. De Santis K, Muellmann S, Pan C, Hoffmann S, Spallek J, Haug U, Zeeb H. Digitisation and health: Second nationwide survey of internet users in Germany. DIGITAL HEALTH 2024;10 View
  18. Shah S, Arecco D, Draper H, Tiribelli S, Harriss E, Matin R. Ethical implications of artificial intelligence in skin cancer diagnostics: use-case analyses. British Journal of Dermatology 2025;192(3):520 View
  19. Zhou L, Cheng K, Chen L, Hou X, Wan J. Effectiveness of eHealth for Medication Adherence in Renal Transplant Recipients: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2025;27:e73520 View