ArticleJMIR human factors2025
Understanding Dermatologists' Acceptance of Digital Health Interventions: Cross-Sectional Survey and Cluster Analysis.
Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Digital health applications, telemedicine and large language models in dermatology: results of a Germany-wide survey.Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Digital health interventions (DHIs) have the potential to enhance dermatological care by improving quality, patient empowerment, and efficiency. However, adoption remains limited, particularly in Germany. Objective: This study explores German dermatologists' attitudes toward DHIs, clustering them by acceptance levels and analyzing differences in sociodemographics and current and future DHI use. Methods: We conducted a cross-sectional survey, randomly inviting 1000 dermatologists in Germany to participate. The questionnaire consisted of Likert scale items rating the acceptability of DHIs from 1 to 5. Items on the current and future use of DHIs were also included. Exploratory factor analysis was used to identify factors and reduce data as input for a 2-step clustering algorithm. Results: The survey with 170 dermatologists (mean age 50.8, SD 10.3 y; 74/167, 55.7% female) identified four factors through the exploratory factor analysis: (1) "Positive Expectancies and Acceptability of DHIs," (2) "Dermatologists' Digital Competencies," (3) "Negative Expectancies and Barriers," and (4) "Dermatologists' Perspectives on Patients' Acceptability and Competencies." The analysis identified three distinct clusters: (1) Indecisives (n=69)-moderate intentions to use DHIs and moderate negative expectations toward them; (2) Adopters (n=60)-high intentions to use DHIs and high digital competencies; and (3) Rejectors (n=26)-low intentions to use DHIs and low digital competencies. Adopters were significantly younger, more often based in urban centers, and exhibited the highest adoption rates of DHIs compared to the other clusters. Across all clusters, inadequate reimbursement and perceived structural barriers were cited as significant challenges to DHI adoption. Still, only one-third of the Adopters used DHIs including teledermatology or artificial intelligence. Conclusions: Dermatologists in Germany exhibited varied levels of acceptance and readiness for DHIs, with demographic and structural factors influencing adoption. Addressing barriers such as reimbursement and investing in digital literacy could promote wider use, potentially reducing health inequalities by improving access to digital health care.
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