Mohs Chatbot Instructions Supplementary Material

The study hypothesized that an interactive chatbot, programmed using the Landbot no-code platform, would improve patient understanding of postoperative care instructions after Mohs micrographic surgery (MMS) compared to standard written instructions. The chatbot was designed to deliver information via multiple-choice prompts and hardcoded if-then logic, potentially enhancing engagement and retention without relying on AI. The data consists of quantitative results from a randomized controlled study with 50 English-speaking adult MMS patients (≥18 years) at the Desai Sethi Medical Center, University of Miami. Participants were divided into two groups: 25 received standard written instructions (control), and 25 used the chatbot (intervention). Data was gathered post-surgery via a 10-question multiple-choice comprehension quiz testing knowledge of wound care, activity restrictions, infection prevention, and emergencies (scored as percentage correct) and secondary outcomes assessed with 0–100 sliders for ease of understanding, ease of use, satisfaction, confidence in wound care, and likelihood of contacting staff. Data collection followed IRB approval and informed consent. Instructions were authored by board-certified surgeons and mirrored in both formats. The chatbot used hardcoded flows based on uploaded instructions, with no patient data input to ensure ethical compliance. Supplementary materials include:
Comprehension Questionnaire: The 10 questions with answers and scoring rubric
Chatbot Flow Diagram: Visual of the decision-tree structure. Use this to understand chatbot navigation.
Postoperative Instructions: Full text covering daily wound care (e.g., "Clean with gentle soap and water"), restrictions (e.g., "No swimming"), bruising/bleeding management, and infection signs. This is the content used in both written and chatbot formats.
The chatbot group scored 72.0% on comprehension (vs. 64.4% control), but the difference was not statistically significant (p=0.10, unpaired t-test). Secondary outcomes favored the chatbot: ease of understanding (mean: 10.5/100, low difficulty), ease of use (12.24), satisfaction (77.3), confidence (82.4), and moderate clarification likelihood (50.0). No adverse events reported.
The data suggests chatbots are feasible for MMS education, maintaining comprehension while boosting satisfaction/confidence, potentially reducing non-emergent inquiries. Non-significance may stem from small sample size (n=50) or self-selection bias (tech-literate participants). Interpret p>0.05 as inconclusive for superiority, but positive trends support chatbot supplements to written instructions.