eHealth Literacy in German Skin Cancer Patients

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

BACKGROUND

Given the expansion of remote digital dermatology services from the National Health Service, particularly during the COVID-19 pandemic, there is a need for methods that identify patients at risk of digital exclusion to guide equitable representation in service co-design processes and tailor remote services to the needs of their patient population.

OBJECTIVE

This quality improvement project aims to inform the redesign of remote services to optimally support the ongoing needs of patients with chronic skin diseases, ensuring that the services are tailored to patients' digital health literacy requirements.

METHODS

We profiled the digital health literacy of 123 people with chronic skin conditions who require long-term surveillance in 2 specialist clinics (London, United Kingdom) using the Multidimensional Readiness and Enablement Index for Health Technology (READHY) questionnaire alongside the Optimizing Health Literacy and Access (Ophelia) process for hierarchical cluster analysis.

RESULTS

The cluster analysis of READHY dimensions in responding participants (n=116) revealed 7 groups with distinct digital and health literacy characteristics. High READHY scores in groups 1 (n=22, 19%) and 2 (n=20, 17.2%) represent those who are confident with managing their health and using technology, whereas the lower-scoring groups, 6 (n=4, 3.4%) and 7 (n=12, 10.3%), depended on traditional services. Groups 3 (n=27, 23.3%), 4 (n=23, 19.8%), and 5 (n=8, 6.9%) had varying digital skills, access, and engagement, highlighting a population that may benefit from a co-designed dermatology service.

CONCLUSIONS

By identifying patient groups with distinguishable patterns of digital access and health literacy, our method demonstrates that 63.8% (n=74) of people attending specialist clinics in our center require support in order to optimize remote follow-up or need an alternative approach. Future efforts should streamline the READHY question profile to improve its practicality and use focus groups to elicit strategies for engaging patients with digital services.

Internet Use, eHealth Literacy, and Influencing Factors in Turkish Cancer Patients: A Descriptive and Correlational Study

OBJECTIVES

This study aimed to determine the Internet use, eHealth literacy levels, and influencing factors in Turkish cancer patients.

DATA SOURCES

A descriptive and correlational study was conducted in a single cancer center with 296 patients. Data were collected using a personal information form, an Internet Usage Form, and the eHealth Literacy Scale (eHEALS). The data were analyzed using descriptive statistics, the Mann‒Whitney U test, Kruskal‒Wallis test, and multiple linear regression analysis.

CONCLUSION

The participants received health-related information from the Internet (36.8%) with a mean total eHEALS score of 22.92 ± 9.67. In the multiple linear regression analysis, the descriptive characteristics of the participants were negatively affected by age (β = -0.143) and education level (β = 0.204). The use of the Internet to obtain information about cancer (β = 0.455) positively affected the level of eHealth literacy. The eHealth literacy of patients is at a level that needs to be improved and there are factors affecting it.

IMPLICATIONS FOR NURSING PRACTICE

Nurses should increase patients' eHealth literacy and guide them on how to access accurate information about cancer on the Internet. While doing this, it should be planned to consider the age, education level, and Internet use of the patients.

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

Purpose

The purpose of this study was to investigate the current state of eHealth literacy among cancer patients in a grade A tertiary hospital in Guangzhou, Guangdong Province, and to identify the factors that influence it, in order to provide a basis for improving the eHealth literacy of cancer patients.

Patients and Methods

From September to November 2021, a convenience sampling method was employed to survey cancer patients in the oncology department of a grade A tertiary hospital in Guangzhou, using a self-administered general information questionnaire and the eHealth literacy scale (eHEALS). A total of 130 questionnaires were distributed, and 117 valid questionnaires were returned.

Results

The mean total score of eHealth literacy among cancer patients was 21.32±8.35. Multiple linear regression analysis revealed that the frequency of searching for health information and education level were significant factors influencing eHealth literacy (p<0.05). Specifically, the education level (junior high school vs primary school or below) was found to have a significant association with eHealth literacy (beta=0.26, p=0.039).

Conclusion

The results of this study suggest that the eHealth literacy of cancer patients is relatively low, with low scores on the dimensions of judgment and decision-making ability. The government and relevant regulatory authorities should focus on strengthening the reliability of online health information and implementing targeted e-interventions to enhance the eHealth literacy of cancer patients.

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

Background

Artificial intelligence (AI)-based mobile phone apps (mHealth) have the potential to streamline care for suspicious skin lesions in primary care. This study aims to investigate the conditions and feasibility of a study that incorporates an AI-based app in primary care and evaluates its potential impact.

Methods

We conducted a pilot feasibility study from November 22nd, 2021 to June 9th, 2022 with a mixed-methods design on implementation of an AI-based mHealth app for skin cancer detection in three primary care practices in the Netherlands (Rotterdam, Leiden and Katwijk). The primary outcome was the inclusion and successful participation rate of patients and general practitioners (GPs). Secondary outcomes were the reasons, facilitators and barriers for successful participation and the potential impact in both pathways for future sample size calculations. Patients were offered use of an AI-based mHealth app before consulting their GP. GPs assessed the patients blinded and then unblinded to the app. Qualitative data included observations and audio-diaries from patients and GPs and focus-groups and interviews with GPs and GP assistants.

Findings

Fifty patients were included with a median age of 52 years (IQR 33.5-60.3), 64% were female, and 90% had a light skin type. The average patient inclusion rate was 4-6 per GP practice per month and 84% (n = 42) successfully participated. Similarly, in 90% (n = 45 patients) the GPs also successfully completed the study. GPs never changed their working diagnosis, but did change their treatment plan (n = 5) based on the app's assessments. Notably, 54% of patients with a benign skin lesion and low risk rating, indicated that they would be reassured and cancel their GP visit with these results (p < 0.001).

Interpretation

Our findings suggest that studying implementation of an AI-based mHealth app for detection of skin cancer in the hands of patients or as a diagnostic tool used by GPs in primary care appears feasible. Preliminary results indicate potential to further investigate both intended use settings.

Funding

SkinVision B.V.