Development and validation of a chatbot for managing leprosy lesions
Bibliographic Data
| ID | 21710399 |
|---|---|
| Authors | Regildo Max Gomes Martins (0000-0002-2516-0719, Universidade Estadual do Ceará), Dailon de Araújo Alves (0000-0001-8294-298X, Faculdade Brasil), Sabrina Alaide Amorim Alves (0000-0001-5831-4668, Universidade Estadual do Ceará), Francisca Juliana Grangeiro Martins (0009-0006-7502-0067, Universidade Regional do Cariri), Luiz Gustavo Alves Lima (0009-0007-8580-5463, Faculdade Brasil), Maria Lúcia Duarte Pereira (0000-0003-0079-5248, Universidade Estadual do Ceará) |
| Year | 2026 |
| Volume | 31 |
| Issue | 5 |
| Publication date | 2026-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Ciência & Saúde Coletiva (JOURNAL) |
| Journal identifiers | ISSN: 1413-8123 • E-ISSN: 1678-4561 |
| Publisher | FapUNIFESP (SciELO) (PUBLISHER) |
| DOI | 10.1590/1413-81232026315.01402026en |
| OpenAlex | W7166576871 |
| SciELO | S1413-81232026000501812 |
| Language | EN |
| References cited | 22 |
The objective was to develop, validate, and test the usability of a chatbot as a support tool for healthcare professionals in the management of leprosy lesions. This methodological study involved content and appearance validation conducted by ten healthcare professionals and seven Information and Communication Technology (ICT) specialists, respectively. The study followed the recommendations of the Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) and the principles of the Object-Oriented Hypermedia Design Method (OHDM), encompassing the phases of textual corpus development (modeling), design of the chatbot’s structure and operation (navigational design and abstract interface), and implementation, including validation procedures and usability testing. The ChatLinoHans chatbot achieved satisfactory results across all validation assessments. Expert evaluation yielded a Content Validity Index (CVI) of 0.98, ensuring the credibility and legitimacy of the chatbot. Appearance validation performed by technical judges resulted in agreement rates ranging from 85.7% to 100%, confirming its adequacy in terms of appearance. Usability testing scores ranged from 77.5 to 100, indicating above-average performance
Chatbot · Content validity · Credibility · eHealth · Health care · Quality (philosophy) · Test (biology) · Usability · AI in Service Interactions · Health Education and Validation · Mobile Health and mHealth Applications
| Highly cited | No |
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