eHealth Literacy in German Skin Cancer Patients

Abstract

The global incidence of skin cancer has steadily increased in recent years, and malignant melanoma still has one of the fastest-growing incidence rates among all malignant tumors in the western world. Thus, newly diagnosed patients have an increased need for health information concerning their disease. Using a standardized questionnaire, our study aims to investigate our patients’ primary sources of health-related information as well as their self-proclaimed eHealth literacy. We received 714 questionnaires. Regardless of age, the primary source of information was the treating dermato-oncologist, followed by the treating general practitioner and the Internet. However, with increasing age, the usage of the Internet decreased. Hence, younger participants were better equipped to find health-related information while using the Internet. Additionally, comprehending health-related information and gaining medical knowledge was significantly increased in better-educated participants. Overall, our study shows that with increased use of eHealth services, accessing web-based information increased, correlating with a better eHealth literacy of our patients. eHealth technologies are increasingly becoming more prevalent as a primary source of information in our modern health care system. Thus, it is crucial to educate cancer patients in eHealth literacy to make autonomous, informed decisions and gain more confidence in dealing with their disease.

Assessing eHealth Literacy and Identifying Factors Influencing Its Adoption Among Cancer Inpatients: A Cross-Sectional Study in Guangdong Population

“…The study corresponded with the study of Milne et al 26 which has indicated that cancer patients high eHealth literacy correlated with the level of education received. This also aligns with previous research, 27 , 28 which has shown that patients with lower levels of education have greater difficulties in comprehending and utilizing eHealth information. These findings suggest that targeted and personalized educational interventions are needed to improve eHealth literacy among cancer patients, particularly those with lower levels of education.…”

“…The study corresponded with the study of Milne et al 26 which has indicated that cancer patients high eHealth literacy correlated with the level of education received. This also aligns with previous research, 27,28 which has shown that…”

Artificial intelligence in mobile health for skin cancer diagnostics at home (AIM HIGH): a pilot feasibility study

“…For example for those with a darker skin type, as multiple studies have demonstrated that algorithms tend to underperform due to bias in training data, 25 , 26 or for patients with low technological literacy who have difficulties using smartphones. 27 , 28 , 29 Additionally, some lesions might even never be suitable for this technology, such as lesions that are covered by hair, lie in a body fold and are difficult to photograph or where algorithms struggle with noise removal. 15 , 16 , 30 , 31 It is therefore important to be aware of these limitations and search for solutions through both algorithm improvements and ensuring that healthcare remains accessible to all patients.…”

The Effect of Remote Digital Services on Health Care Inequalities Among People Under Long-Term Dermatology Follow-Up: Cross-Sectional Questionnaire Study

“…Furthermore, there is minimal literature exploring user suitability for digital dermatology care. eHealth literacy has, however, previously been assessed by Stege et al [13] in a population of patients with skin cancer. Stege et al [13] report greater eHealth literacy in younger, well-educated participants, though we are unable to determine from their data the proportion of their participants who are at risk of digital exclusion.…”

“…eHealth literacy has, however, previously been assessed by Stege et al [13] in a population of patients with skin cancer. Stege et al [13] report greater eHealth literacy in younger, well-educated participants, though we are unable to determine from their data the proportion of their participants who are at risk of digital exclusion. Our comparative lack of demographic trends may be due to the broad inclusion criteria for the cluster analysis and limited sample size.…”