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Published on in Vol 5, No 7 (2017): July

Photoaging Mobile Apps as a Novel Opportunity for Melanoma Prevention: Pilot Study

Photoaging Mobile Apps as a Novel Opportunity for Melanoma Prevention: Pilot Study

Photoaging Mobile Apps as a Novel Opportunity for Melanoma Prevention: Pilot Study

Authors of this article:

Titus Josef Brinker1, 2, 3 Author Orcid Image ;   Dirk Schadendorf1, 2, 3 Author Orcid Image ;   Joachim Klode1, 2, 3 Author Orcid Image ;   Ioana Cosgarea1, 2, 3 Author Orcid Image ;   Alexander Rösch1, 2, 3 Author Orcid Image ;   Philipp Jansen1, 2, 3 Author Orcid Image ;   Ingo Stoffels1, 2, 3 Author Orcid Image ;   Benjamin Izar4, 5 Author Orcid Image
Article Authors Cited by (27) Tweetations (16) Metrics

    Original Paper

    1Department of Dermatology, Venerology and Allergology, University-Hospital Essen, University of Duisburg-Essen, Essen, Germany

    2West German Cancer Center, University of Duisburg-Essen, Essen, Germany

    3German Cancer Consortium (DKTK), Heidelberg, Germany

    4Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States

    5Broad Institute of MIT and Harvard, Cambridge, MA, United States

    Corresponding Author:

    Titus Josef Brinker, MD

    Department of Dermatology, Venerology and Allergology

    University-Hospital Essen

    University of Duisburg-Essen

    Hufelandstrasse 55

    Essen, 45147

    Germany

    Phone: 49 15175084347

    Fax:49 15175084347

    Email: titus.brinker@gmail.com


    Background: Around 90% of melanomas are caused by ultraviolet (UV) exposure and are therefore eminently preventable. Unhealthy tanning behavior is mostly initiated in early adolescence, often with the belief that it increases attractiveness; the problems related to skin atrophy and malignant melanoma are too far in the future to fathom. Photoaging desktop programs, in which an image is altered to predict future appearance, have been successful in positively influencing behavior in adiposity or tobacco prevention settings.

    Objective: To develop and test a photoaging app designed for melanoma prevention.

    Methods: We harnessed the widespread availability of mobile phones and adolescents’ interest in appearance to develop a free mobile app called Sunface. This app has the user take a self-portrait (ie, a selfie), and then photoages the image based on Fitzpatrick skin type and individual UV protection behavior. Afterward, the app explains the visual results and aims at increasing self-competence on skin cancer prevention by providing guideline recommendations on sun protection and the ABCDE rule for melanoma self-detection. The underlying aging algorithms are based on publications showing UV-induced skin damage by outdoor as well as indoor tanning. To get a first impression on how well the app would be received in a young target group, we included a total sample of 25 students in our cross-sectional pilot study with a median age of 22 (range 19-25) years of both sexes (11/25, 44% female; 14/25, 56% male) attending the University of Essen in Germany.

    Results: The majority of enrolled students stated that they would download the app (22/25, 88%), that the intervention had the potential to motivate them to use sun protection (23/25, 92%) and that they thought such an app could change their perceptions that tanning makes you attractive (19/25, 76%). Only a minority of students disagreed or fully disagreed that they would download such an app (2/25, 8%) or that such an app could change their perceptions on tanning and attractiveness (4/25, 16%).

    Conclusions: Based on previous studies and the initial study results presented here, it is reasonable to speculate that the app may induce behavioral change in the target population. Further work is required to implement and examine the effectiveness of app-based photoaging interventions within risk groups from various cultural backgrounds.

    JMIR Mhealth Uhealth 2017;5(7):e101

    doi:10.2196/mhealth.8231

    Keywords

    melanoma; skin cancer; prevention; mobile apps; smartphones; photoaging 


    Melanoma accounts for the majority of skin cancer-related deaths worldwide [1]. The implementation of next-generation sequencing has uncovered key oncogenic drivers of metastatic melanoma, such as mutations in the BRAF gene, which are present in around 50% of patients [2,3]. Development of therapies targeting the products of these genetic alterations, namely BRAF and MEK inhibitors, led to the first therapeutic revolution in melanoma care. These advances changed the prognosis of metastatic melanoma from a uniformly fatal disease with median survival of about 9 months to a treatable disease with median overall survival rates of more than 24 months, including some long-term responders [4-7].

    In parallel, an improved understanding of mechanisms of tumor immune evasion, namely through interactions with immune checkpoints, such as cytotoxic T-lymphocyte-associated antigen 4 and programmed cell death protein 1, provided the rationale for the second therapeutic revolution. Conceptually, immune checkpoint inhibitors disrupt tumor-mediated T-cell dysfunction, and enable reactivation and effective immune-mediated tumor lysis. Up to 1 in 3 patients with metastatic melanoma may derive durable responses to these therapies [8-11].

    Despite these disruptive changes in the therapeutic landscape, the majority of patients will still die from their disease. Several institutions and entities therefore emphasize and fund programs to improve preventive measures. Around 90% of melanomas are related to ultraviolet (UV) radiation [12], and recent data indicate that especially people with lower genetic risk for melanoma benefit from avoiding cumulative UV exposure, which is known as the divergent pathway hypothesis [13,14].

    Unhealthy tanning behavior (including sunbed use) is mostly initiated in early adolescence [15], often with the belief that it increases attractiveness [16-18]; the problems related to skin atrophy and malignant melanoma are too far in the future to fathom.

    To target populations at risk for such behaviors, implementation of programs that are embedded in frequently used media, such as the Internet or mobile phone apps, may be useful. Indeed, a recent randomized controlled trial by Burford et al demonstrated the effectiveness of photoaging desktop programs, in which an image is altered to predict future appearance, for behavioral change in young target groups in the field of smoking cessation [19]. Furthermore, a quasi-experimental study showed significantly higher scores for predictors of sun protection behavior in young women from the United Kingdom using such programs [20], which were also effective in changing young adults’ suntanning intentions in both sexes [21]. However, the investigated desktop-based programs only reach a small audience and are not freely available. To improve melanoma prevention in the larger population by leveraging frequently used technologies, we developed a freely available phone app aimed at enhancing sun protective behaviors.


    We harnessed the widespread availability of mobile phones and adolescents’ interest in appearance to develop a free mobile app. The Sunface app has the user take a self-portrait (ie, a selfie), and then photoages the image based on Fitzpatrick skin type (Figure 1) and individual UV protection behavior (Figure 2, Figure 3, Figure 4).

    Afterward, the app explains the visual results (Figure 5) and increases self-competence on skin cancer prevention by providing guideline recommendations on sun protection and the ABCDE rule for melanoma self-detection (assess border irregularity, color variety, diameter, and evolution [22]). By means of sharing tools of the animated image as a video (Multimedia Appendix 1) or photo, the user’s social network may be informed about the various beauty-reducing effects of tanning and about the app.

    The underlying aging algorithms are based on publications showing UV-induced skin damage caused by outdoor as well as indoor tanning [23]. As no trials with 25 years of follow-up were available, we had to extrapolate the current evidence on UV-induced skin damage for the specific skin types.

    To get a first impression of how well the app would be received in a young target group, we included a total sample of 25 students in our cross-sectional pilot study with a median age of 22 (range 19-25) years of both sexes (11/25, 44% female; 14/25, 56% male) attending the University of Essen in Germany.

    An interviewer walked up to each individual student, asked for oral consent, let them use the app once by handing them an iPod Touch (Apple Inc) with the app preinstalled, and then measured their reactions to the 1-time use of the app (no longer than 2 minutes) via a paper-and-pencil questionnaire. The items used in the questionnaire captured sociodemographic data (sex, age) and their reactions toward the app, on 5-point Likert scales, directly after using it. All items used wording and a structure similar to those of a previously published questionnaire evaluating a photoaging app for tobacco use prevention [24]. Each selfie was deleted directly after the individual test persons had tested the app for data protection reasons.

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    Figure 1. Start of the app: the user picks their Fitzpatrick skin type.
    View this figure
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    Figure 2. Effect view of the app: 25 years of aging with applied sun protection.
    View this figure
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    Figure 3. Effect view of the app: weekly tanning for 25 years (maximum effect) with a total of 3 actinic keratoses visible, multiple solar lentigines, age spots, and prominent solar elastosis.
    View this figure
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    Figure 4. Effect view of the app: 5 years of normal aging with daily sun protection applied.
    View this figure
    ‎
    Figure 5. Explanatory graphic within the app explaining the shown effects. UV: ultraviolet.
    View this figure

    The majority of enrolled students stated that they would download the app (22/25, 88%), that the intervention had the potential to motivate them to use sun protection (23/25, 92%), and that they thought such an app could change their perceptions that tanning makes you attractive (19/25, 76%). Only a minority of students disagreed or fully disagreed that they would download such an app (2/25, 8%) or that such an app could change their perceptions on tanning and attractiveness (4/25, 16%).

    In line with our small survey, the app was installed on over 1000 Android and 500 iOS smartphones within 14 days after its release in Germany (May 30, 2017 to June 17, 2017). We thus expect it to reach a similar popularity with an estimated 30,000 users within 1 year, which is comparable with our photoaging app on tobacco-induced skin changes [25]. As smartphone use in Germany declines with age, we assume that the largest fraction of app users will be in the vulnerable age group of 35 years or younger.


    The implementation of novel technologies and computational algorithms has the potential to substantially change the landscape of cancer prevention and early melanoma detection [19,20,24,26-30], and thereby reduce its disease-specific mortality. Here, we propose the use of a mobile phone app, Sunface, as a means to implement interventions that encourage sun protective behavior. The effectiveness of such approaches has been demonstrated in recent studies, and could be complimentary to early detection programs by dermatologists and recently developed artificial intelligence programs [31]. Phone apps in the field of dermatology are of increasing relevance [32-44] and may be particularly effective in reaching a large number of people, given the increasing use of mobile phones, which is projected to increase to more than 6 billion subscriptions by 2021 [45], and their integration into daily living habits by these customers.

    Based on previous studies and the initial study results presented here, it is reasonable to speculate that the app may induce behavioral change in the target population. Further work is required to implement and examine the effectiveness of app-based photoaging interventions within risk groups from various cultural backgrounds.

    Conflicts of Interest

    None declared.

    Authors' Contributions

    DS, JK, IC, AR, PJ, IS, and BI contributed to the design and conduct of the pilot study, as well as the analysis of its data, and proofread the manuscript.

    ‎

    Multimedia Appendix 1

    Shared video of the Sunface app with 15 years of no sun protection shown in a 3-dimensional animated selfie.

    MP4 File (MP4 Video), 1MB
    1. Karimkhani C, Green AC, Nijsten T, Weinstock MA, Dellavalle RP, Naghavi M, et al. The global burden of melanoma: results from the Global Burden of Disease Study 2015. Br J Dermatol 2017 Mar 30. [CrossRef] [Medline]
    2. Cancer Genome Atlas Network. Genomic classification of cutaneous melanoma. Cell 2015 Jun 18;161(7):1681-1696 [FREE Full text] [CrossRef] [Medline]
    3. Hodis E, Watson IR, Kryukov GV, Arold ST, Imielinski M, Theurillat J, et al. A landscape of driver mutations in melanoma. Cell 2012 Jul 20;150(2):251-263 [FREE Full text] [CrossRef] [Medline]
    4. Long GV, Grob J, Nathan P, Ribas A, Robert C, Schadendorf D, et al. Factors predictive of response, disease progression, and overall survival after dabrafenib and trametinib combination treatment: a pooled analysis of individual patient data from randomised trials. Lancet Oncol 2016 Dec;17(12):1743-1754. [CrossRef] [Medline]
    5. Grob JJ, Amonkar MM, Karaszewska B, Schachter J, Dummer R, Mackiewicz A, et al. Comparison of dabrafenib and trametinib combination therapy with vemurafenib monotherapy on health-related quality of life in patients with unresectable or metastatic cutaneous BRAF Val600-mutation-positive melanoma (COMBI-v): results of a phase 3, open-label, randomised trial. Lancet Oncol 2015 Oct;16(13):1389-1398. [CrossRef] [Medline]
    6. Long GV, Stroyakovskiy D, Gogas H, Levchenko E, de BF, Larkin J, et al. Dabrafenib and trametinib versus dabrafenib and placebo for Val600 BRAF-mutant melanoma: a multicentre, double-blind, phase 3 randomised controlled trial. Lancet 2015 Aug 01;386(9992):444-451. [CrossRef] [Medline]
    7. Robert C, Karaszewska B, Schachter J, Rutkowski P, Mackiewicz A, Stroiakovski D, et al. Improved overall survival in melanoma with combined dabrafenib and trametinib. N Engl J Med 2015 Jan 01;372(1):30-39. [CrossRef] [Medline]
    8. Hodi FS, Chesney J, Pavlick AC, Robert C, Grossmann KF, McDermott DF, et al. Combined nivolumab and ipilimumab versus ipilimumab alone in patients with advanced melanoma: 2-year overall survival outcomes in a multicentre, randomised, controlled, phase 2 trial. Lancet Oncol 2016 Nov;17(11):1558-1568. [CrossRef] [Medline]
    9. Robert C, Long GV, Brady B, Dutriaux C, Maio M, Mortier L, et al. Nivolumab in previously untreated melanoma without BRAF mutation. N Engl J Med 2015 Jan 22;372(4):320-330. [CrossRef] [Medline]
    10. Robert C, Schachter J, Long GV, Arance A, Grob JJ, Mortier L, KEYNOTE-006 investigators. Pembrolizumab versus ipilimumab in advanced melanoma. N Engl J Med 2015 Jun 25;372(26):2521-2532. [CrossRef] [Medline]
    11. Larkin J, Hodi FS, Wolchok JD. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med 2015 Sep 24;373(13):1270-1271. [CrossRef] [Medline]
    12. The Lancet Editorial Board. Skin cancer: prevention is better than cure. Lancet 2014 Aug 09;384(9942):470. [CrossRef] [Medline]
    13. Janda M, Soyer P. Greater precision in melanoma prevention. JAMA Dermatol 2017 Jan 01;153(1):18-19. [CrossRef] [Medline]
    14. Watts CG, Madronio C, Morton RL, Goumas C, Armstrong BK, Curtin A, et al. Clinical features associated with individuals at higher risk of melanoma: a population-based study. JAMA Dermatol 2017 Jan 01;153(1):23-29. [CrossRef] [Medline]
    15. Görig T, Diehl K, Greinert R, Breitbart EW, Schneider S. Prevalence of sun-protective behaviour and intentional sun tanning in German adolescents and adults: results of a nationwide telephone survey. J Eur Acad Dermatol Venereol 2017 Jun 02. [CrossRef] [Medline]
    16. Schneider S, Diehl K, Bock C, Schlüter M, Breitbart EW, Volkmer B, et al. Sunbed use, user characteristics, and motivations for tanning: results from the German population-based SUN-Study 2012. JAMA Dermatol 2013 Jan;149(1):43-49. [CrossRef] [Medline]
    17. Hillhouse J, Turrisi R, Scaglione NM, Cleveland MJ, Baker K, Florence LC. A web-based intervention to reduce indoor tanning motivations in adolescents: a randomized controlled trial. Prev Sci 2017 Feb;18(2):131-140. [CrossRef] [Medline]
    18. Hillhouse J, Turrisi R, Cleveland MJ, Scaglione NM, Baker K, Florence LC. Theory-driven longitudinal study exploring indoor tanning initiation in teens using a person-centered approach. Ann Behav Med 2016 Feb;50(1):48-57. [CrossRef] [Medline]
    19. Burford O, Jiwa M, Carter O, Parsons R, Hendrie D. Internet-based photoaging within Australian pharmacies to promote smoking cessation: randomized controlled trial. J Med Internet Res 2013 Mar 26;15(3):e64 [FREE Full text] [CrossRef] [Medline]
    20. Williams AL, Grogan S, Clark-Carter D, Buckley E. Impact of a facial-ageing intervention versus a health literature intervention on women's sun protection attitudes and behavioural intentions. Psychol Health 2013;28(9):993-1008. [CrossRef] [Medline]
    21. Lo PL, Chang P, Taylor MF. Young Australian adults' reactions to viewing personalised UV photoaged photographs. Australas Med J 2014;7(11):454-461 [FREE Full text] [CrossRef] [Medline]
    22. Robinson JK, Wayne JD, Martini MC, Hultgren BA, Mallett KA, Turrisi R. Early detection of new melanomas by patients with melanoma and their partners using a structured skin self-examination skills training intervention: a randomized clinical trial. JAMA Dermatol 2016 Sep 01;152(9):979-985 [FREE Full text] [CrossRef] [Medline]
    23. Kammeyer A, Luiten RM. Oxidation events and skin aging. Ageing Res Rev 2015 May;21:16-29. [CrossRef] [Medline]
    24. Brinker TJ, Seeger W, Buslaff F. Photoaging mobile apps in school-based tobacco prevention: the mirroring approach. J Med Internet Res 2016 Jun 28;18(6):e183 [FREE Full text] [CrossRef] [Medline]
    25. Brinker TJ, Seeger W. Photoaging mobile apps: a novel opportunity for smoking cessation? J Med Internet Res 2015 Jul 27;17(7):e186 [FREE Full text] [CrossRef] [Medline]
    26. Brinker TJ, Owczarek AD, Seeger W, Groneberg DA, Brieske CM, Jansen P, et al. A medical student-delivered smoking prevention program, education against tobacco, for secondary schools in Germany: randomized controlled trial. J Med Internet Res 2017 Jun 06;19(6):e199 [FREE Full text] [CrossRef] [Medline]
    27. Xavier LEDF, Bernardes-Souza B, Lisboa OC, Seeger W, Groneberg DA, Tran T, et al. A medical student-delivered smoking prevention program, education against tobacco, for secondary schools in Brazil: study protocol for a randomized trial. JMIR Res Protoc 2017 Jan 30;6(1):e16 [FREE Full text] [CrossRef] [Medline]
    28. Brinker TJ, Holzapfel J, Baudson TG, Sies K, Jakob L, Baumert HM, et al. Photoaging smartphone app promoting poster campaign to reduce smoking prevalence in secondary schools: the Smokerface Randomized Trial: design and baseline characteristics. BMJ Open 2016 Nov 07;6(11):e014288 [FREE Full text] [CrossRef] [Medline]
    29. Dorairaj JJ, Healy GM, McInerney A, Hussey AJ. Validation of a melanoma risk assessment smartphone application. Dermatol Surg 2017 Feb;43(2):299-302. [CrossRef] [Medline]
    30. Webster DE, Suver C, Doerr M, Mounts E, Domenico L, Petrie T, et al. The Mole Mapper Study, mobile phone skin imaging and melanoma risk data collected using ResearchKit. Sci Data 2017 Feb 14;4:170005 [FREE Full text] [CrossRef] [Medline]
    31. Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017 Dec 02;542(7639):115-118. [CrossRef] [Medline]
    32. Kim S, Cho D, Kim J, Kim M, Youn S, Jang JE, et al. Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis. Biomed Opt Express 2016 Dec 01;7(12):5294-5307 [FREE Full text] [CrossRef] [Medline]
    33. Moreno-Ramírez D, Argenziano G. Teledermatology and mobile applications in the management of patients with skin lesions. Acta Derm Venereol 2017 Jul 05 [FREE Full text] [CrossRef] [Medline]
    34. MacKinnon N, Vasefi F, Booth N, Farkas D. Melanoma detection using smartphone and multimode hyperspectral imaging. In: Farkas DL, Nicolau DV, Leif RC, editors. Proceedings of SPIE 9711: Imaging, Manipulation, and Analysis for Biomolecules, Cells, and Tissues IX. Bellingham, WA: SPIE International Society for Optics and Photonics; 2016:971117.
    35. Lofgreen SJ, Ashack K, Burton KA, Dellavalle RP. Mobile device use in dermatologic patient care. Curr Dermatol Rep 2016 Mar 21;5(2):77-82. [CrossRef]
    36. Resneck JS, Abrouk M, Steuer M, Tam A, Yen A, Lee I, et al. Choice, transparency, coordination, and quality among direct-to-consumer telemedicine websites and apps treating skin disease. JAMA Dermatol 2016 Jul 01;152(7):768-775. [CrossRef] [Medline]
    37. Kochmann M, Locatis C. Direct to consumer mobile teledermatology apps: an exploratory study. Telemed J E Health 2016 Aug;22(8):689-693. [CrossRef] [Medline]
    38. Zink A, Kolbinger A, Leibl M, Leon-Suarez I, Gloning J, Merkel C, et al. The value of teledermatology using a mobile app compared to conventional dermatology. Eur J Dermatol 2017 May 16. [CrossRef] [Medline]
    39. Hawkins SD, Barilla S, Feldman SR. Web app based patient education in psoriasis - a randomized controlled trial. Dermatol Online J 2017 Apr 15;23(4). [Medline]
    40. Thissen M, Udrea A, Hacking M, von Braunmuehl BT, Ruzicka T. mHealth app for risk assessment of pigmented and nonpigmented skin lesions—a study on sensitivity and specificity in detecting malignancy. Telemed J E Health 2017 May 31. [CrossRef] [Medline]
    41. Nabil R, Bergman W, Kukutsch NA. Conflicting results between the analysis of skin lesions using a mobile-phone application and a dermatologist's clinical diagnosis: a pilot study. Br J Dermatol 2017 Mar 10. [CrossRef] [Medline]
    42. Morelli M, Masini A, Simeone E, Khazova M. Validation and in vivo assessment of an innovative satellite-based solar UV dosimeter for a mobile app dedicated to skin health. Photochem Photobiol Sci 2016 Sep 31;15(9):1170-1175. [CrossRef] [Medline]
    43. Gonzalez M, Carlino M, Zielinski R, Smith J, Saw R, Hong A, et al. An app to increase cross-referral and recruitment to melanoma clinical trials. J Clin Oncol 2016;34(suppl):a. [CrossRef]
    44. Taufiq M, Hameed N, Anjum A, Hameed F. m-Skin Doctor: a mobile enabled system for early melanoma skin cancer detection using support vector machine. In: Giokas K, Bokor L, Hopfgartner F, editors. eHealth 360°: International Summit on eHealth, Budapest, Hungary, June 14-16, 2016, Revised Selected Papers. Cham, Switzerland: Springer; 2017:468-475.
    45. Cerwall P. Ericsson mobility report on the pulse of the networked society. Stockholm, Sweden: Ericsson; 2016 Jun.   URL: https://wwwericssoncom/res/docs/2016/ericsson-mobility-report-2016pdf [accessed 2017-07-09] [WebCite Cache]

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    UV: ultraviolet

    Edited by G Eysenbach; submitted 18.06.17; peer-reviewed by O Burford, P Giacobbi, Jr., J Makin; comments to author 03.07.17; revised version received 03.07.17; accepted 12.07.17; published 26.07.17

    Copyright

    ©Titus Josef Brinker, Dirk Schadendorf, Joachim Klode, Ioana Cosgarea, Alexander Rösch, Philipp Jansen, Ingo Stoffels, Benjamin Izar. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 26.07.2017.

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