JMIR Publications

ABSTRACT

Background:

Skin cancer incidence is rising globally, increasing pressure on dermatology services and making efficient triage increasingly important. AI-driven skin cancer mobile health apps may help address this need, but their usefulness depends on whether users trust the advice and intend to follow it.

Objective:

To test whether teledermatologist supervision in an AI-driven skin cancer app affects patient trust and adherence intentions, compared with AI-only advice, and whether these effects differ by motivational context and risk assessment level.

Methods:

The randomised, controlled, vignette online experiment with repeated measures was conducted in May–June 2025 as a Single-centre study among Dutch adults via an academic hospital-based patient panel. Participants completed four simulated mobile app scenarios varying in advice source (AI-only vs Hybrid Teledermatologist & AI) and risk assessment level (high vs low). The primary outcomes were trust in the advice (0–100 scale), and adherence intention (recoded 3-level ordinal scale). Mixed-effects models were used to analyse the data.

Results:

Of the 2,707 patient panel members, 879 participated (response rate: 32.5%). Participants were aged 18–93 (mean age: 62.5), 50.4% female, 21.4% with prior skin cancer. Participants were randomly allocated by the survey software to motivation conditions (Concern (n=438) vs Curiosity (n=441)). Trust was higher for hybrid advice than AI-only advice (mean=76.9, SE = 0.73 vs mean = 65.7, SE = 0.73; estimated difference 11.98; P<.001; partial η²=.22). The odds of adherence were 1.7 times greater with hybrid versus AI-only (OR=1/0.59=1.7, 95% CI [1.28, 2.22], p<.001). High-risk assessments increased adherence (OR=2.9, 95% CI [2.2, 3.8], p<.001), with a moderated effect by motivation (p=.033), showing stronger adherence with concern versus curiosity. The effect of advice source on adherence was fully mediated by trust.

Conclusions:

Teledermatologist supervision of the AI-based advice in the vignette experiment robustly increased patient trust and adherence intentions, particularly for high-risk assessments and concerned users. . Our online experiment is innovative in testing teledermatologist supervision in a population-level AI skin cancer app and in examining how motivational context shapes responses to advice. Unlike prior studies focused on post-referral teledermatology or chatbot-based advice, this study isolates the effect of hybrid AI-human advice in a store-and-forward screening context. These findings suggest that developers and healthcare implementers may consider integrating teledermatologist supervision to maximise patient trust of and adherence to advice, potentially improving triaging efficiency and safety. Clinical Trial: The study was preregistered on the Open Science Framework [1] (https://osf.io/64pjn/) in May 2025.