Artificial intelligence generated visual communication improves comprehension and adherence in cervical cancer screening: a randomized controlled study.
rct · Level II
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- Record sourced from PubMed, PMID 41066921.
- Also identified by DOI 10.1016/j.ijmedinf.2025.106134.
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Abstract
Cervical cancer is preventable, yet poor comprehension of Pap smear results and non-adherence to follow-up major barriers, particularly in low health literacy settings. In Georgia, where screening coverage is below 20%, innovative communication strategies are needed. Artificial intelligence (AI) offers opportunities to strengthen patient communication through adaptive, emotionally expressive visual tools. To evaluate whether AI-generated visual explanations, paired with simplified text, improve comprehension, satisfaction, and follow-up adherence after cervical cancer screening compared with conventional text reporting. A randomized controlled trial enrolled 3,000 women aged 21-65 who underwent Pap smear testing between March and October 2024. Participants were randomized to three groups: Control (standard text), Text-only (enhanced plain-language text), and Intervention (AI-generated visuals plus text). Visuals were created with Craiyon, refined through expert and patient feedback, and aligned with Bethesda categories. Surveys assessed comprehension, satisfaction, and follow-up intent, while electronic records verified adherence. Analyses included chi-square tests, Kruskal-Wallis conformation for ordinal outcomes, and logistic regression for demographics and health literacy. The Intervention group achieved superior outcomes across all metrics. Comprehension reached 90 % versus 78 % in Text-only and 65 % in Control (χ<sup>2</sup>(2) = 131.8, p < 0.001). Satisfaction was 90 % in the Intervention group, compared with 78 % and 65 %. Follow-up adherence was 75 % with AI visuals, 65 % with Text-only, and 50 % with Control, corresponding to a threefold increase in odds of adherence (OR = 3.0; 95 % CI: 2.5-3.6; H(2) = 136.3, p < 0.001). Gains were most pronounced for abnormal results, including ASCUS, LSIL, and HSIL. AI-generated visual communication significantly improved comprehension, satisfaction, and follow-up adherence in cervical cancer screening. This study demonstrates a scalable informatics solution for patient engagement, though challenges remain regarding long-term behavioral impact, cross-cultural adaptation, and integration into routine health information systems.
Medical subject headings
- Uterine Cervical Neoplasms
- Artificial Intelligence
- Early Detection of Cancer
- Comprehension
- Patient Compliance