Views on Mobile Health Apps for Skin Cancer Screening in the General Population

An In-depth Qualitative Exploration of Perceived Barriers and Facilitators

T.E. Sangers; M. Wakkee; E.C. Kramer-Noels; T. Nijsten; M. Lugtenberg


The British Journal of Dermatology. 2021;185(5):961-969. 

In This Article


This in-depth qualitative study aimed to explore the Dutch general population's views towards mHealth apps for skin cancer screening. It revealed multiple barriers and facilitators related to using these apps as perceived by the general population.

Consistent with previous studies focusing on mHealth in general, a lack of perceived usefulness and trustworthiness, concerns over privacy and perceived high costs appeared to be important barriers to adoption.[25,33,34] However, we also identified new (sub-)barriers that seem to be unique to skin cancer, in which a perceived lack of screening accuracy is most prominent.[18,35] The expectations regarding the required minimal levels of accuracy seem to vary, ranging from GP-level skin cancer detection accuracy up to flawless screening capabilities.

With regard to facilitators, the general population appeared to value the benefits of mHealth apps in relation to skin cancer screening, such as the opportunity to perform a risk assessment at home and to self-monitor skin lesions in a standardized manner over time. They agreed that mHealth apps may lower the threshold at which patients seek care for a suspicious skin lesion, which may especially be important in rural areas. Simultaneously, these functionalities may reduce unnecessary consultations as they can advise users only to visit a doctor in case of a suspicious skin lesion.[9]

In line with existing literature, we also identified the endorsement of healthcare providers and government regulating bodies, the ease of use of an app, and low user costs as facilitators of use.[25,33,34] Low costs were reported to facilitate the adoption of mHealth if proportionate to a doctor visit or reimbursed by a healthcare insurer. As such, the minimal accepted amount paid for use may differ between healthcare systems, depending on the direct and indirect cost of a doctor visit. Whereas health insurers' willingness to reimburse mHealth largely depends on reducing direct medical costs (e.g. reducing the number of unnecessary visits, early diagnosis of malignant lesions to avoid expensive surgical and/or oncological treatment), our results emphasize that from a societal perspective, the potential savings of indirect medical costs (e.g. travel expenses and loss of work-related productivity) should also be taken into account when assessing the cost effectiveness of mHealth.

Under the current Medical Device Directive (MDD) of the European Union, mHealth apps for skin cancer screening can register as a class I CE-marked medical device. However, concerns have been raised about this classification, as there is no mandatory inspection by an independent notified body coupled to this classification.[18] In contrast to Europe, the US Food and Drug Administration has not approved any deep learning algorithms for skin cancer detection for consumer use. The Medical Device Regulation (MDR), set to replace the MDD in May 2021, may result in a new classification of mHealth apps as class II or III, instead of class I.[36] We expect the MDR to act as a facilitator towards the use of mHealth apps, as their adequate certification and regulation for skin cancer screening can increase the perception of trustworthiness of these apps.

Based on our findings, we make the following recommendations. (i) We recommend that mHealth app developers collaborate with, and seek endorsement from GPs and dermatologists, and their national societies. This will increase the adoption of mHealth among the general population and facilitate the integration of mHealth apps with skin cancer management. (ii) Furthermore, we recommend improving mHealth integration with healthcare systems in several ways. Firstly, patients should be offered the possibility of being referred directly to a dermatologist based on an app's assessment in countries with a closed healthcare system. Secondly, healthcare providers could offer the possibility of monitoring skin cancer lesions during and after skin cancer treatment. Thirdly, a high-risk rating by an mHealth app could be used as a triage system for dermatology outpatient clinics to select patients who need to be seen swiftly. Fourthly, ideally, the images and ratings from mHealth apps should be connected to patients' electronic healthcare records. Fifthly, mHealth could be promoted on existing eHealth webpages (e.g. NHS Health A-to-Z) that laypersons check when deciding if a doctor's visit is necessary. (iii) We encourage developers to build apps that provide a reliable risk indication for skin lesions, and use clear communication regarding their identity and the benefits and drawbacks of the technology. Moreover, an app's screening accuracy should be communicated to potential users, preferably in comprehensible plain language. (iv) In addition to mHealth's need to implement low-cost, privacy-friendly, easy-to-use apps, we encourage robust scientific evaluation in real-world settings.

In terms of limitations, firstly, our qualitative study focused on perceived barriers to and facilitators of mHealth for skin cancer screening, which depended on participants' perception of the situation. Although perceptions are of great importance as a starting point, they may not fully reflect the range of barriers and facilitators associated with the actual use of mHealth. Secondly, the characteristics such as age varied between the selected participants and did not allow subgroup analyses. Thirdly, the sample of study participants consisted of a customer panel from a Dutch health insurer, which was skewed in terms of age and previous experience. While we aimed to compensate for the skewed sample by performing additional sampling through social media, there needs to be some caution in extrapolating the findings to the entire Dutch population.

A strength of this study is that we explored both barriers and facilitators in relation to mHealth. Several of the identified facilitators (e.g. perceived high value, trustworthy identity of the developer, low costs of use) can potentially resolve the perceived barriers. However, our study also showed that some facilitators, such as endorsement by healthcare providers and government regulating bodies, do not logically follow from identified barriers. Similarly, the identified barriers of the preference for a doctor instead of an app and privacy concerns about mHealth apps could not be countered by the identified facilitators. Another strength of the study is that we could obtain a variable sample of participants in terms of relevant characteristics, such as age and previous experience with mHealth. The coding in multiple phases, the constant comparison technique,[27] and discussions of the identified results in a multidisciplinary group of researchers further contributed to the robustness and validity of our results.

Differences in perceived barriers and facilitators between specific age groups could be explored in future research, as previous work shows that young people are more likely to use mHealth.[37] Moreover, ethnographic research and other forms of qualitative observation may provide additional insights into understanding the use of mHealth apps for skin cancer screening. Furthermore, we recommend future research to explore the views of GPs and dermatologists towards mHealth apps for skin cancer screening.

In conclusion, as AI development in mHealth apps for skin cancer screening progresses rapidly, it is vital to consider the public's perspective on this innovative technology. The results of this study may be useful for app developers and healthcare professionals as they seek to improve acceptance and integration of mHealth in skin cancer care.