Application of Artificial Intelligence Software to Identify Emotions of Lung Cancer Patients in Preoperative Health Education: A Cross-Sectional Study.

Abstract

Aim(s): To determine the correlation between preoperative health education and the emotions of lung cancer patients, artificial intelligence software was used.

Design: This was a cross-sectional study.

Methods: This study included 210 lung cancer patients from Sun Yat-sen University Cancer Center and examined the impact of health education on patient emotions using an AI-based emotion analysis tool.

Results: This study indicated a significant relationship between the tone and emotional content of health education materials and patient emotions. Specifically, educational materials with an explanatory tone and negative sentiment appeared to impact patients' emotional states.

Conclusion: Quality improvements in health education can potentially benefit lung cancer patients' emotional well-being by minimizing the use of both explanatory tone and negative sentiment in educational content.

Implications for the profession and/or patient care: This research suggests that the careful crafting of health education materials, taking into consideration tone and emotional expressions, can have a tangible positive effect on the emotional state of lung cancer patients.

Reporting method: The study was reported in accordance with the STROBE guidelines.

Patient or public contribution: No patients, service users, caregivers, or members of the public were involved in the design, conduct, collection, analysis, or interpretation of the data for this study, nor were they involved in writing the manuscript.