Clinical Research Directory

Artificial Intelligence Powered Digital Education Based on the Neuman Systems Model for Breast Cancer Patients Receiving Radiotherap

Sponsor: Ataturk University

Summary

The purpose of this clinical trial is to evaluate the effect of an artificial intelligence-supported digital education program developed based on the Neuman Systems Model on radiodermatitis severity and quality of life in women with breast cancer receiving radiotherapy. The intervention was developed based on the Neuman Systems Model, which served as the theoretical framework of the study. Educational content was structured according to the principles of the model and was designed to strengthen patients' flexible lines of defense, support resistance resources, facilitate adaptation to radiotherapy-related stressors, and promote system stability through primary, secondary, and tertiary prevention strategies. The study aims to answer the following questions: * Is a Neuman Systems Model-based AI-supported digital education program effective in reducing the severity of radiotherapy-induced radiodermatitis? * Is a Neuman Systems Model-based AI-supported digital education program effective in improving quality of life among women receiving radiotherapy for breast cancer? Participants assigned to the intervention group will be provided with access to the AI-supported digital education program developed in accordance with the Neuman Systems Model, whereas participants assigned to the control group will receive standard care. Differences between the groups with respect to radiodermatitis severity and quality of life outcomes will be evaluated. Participants will complete a Patient Information Form to collect sociodemographic and clinical characteristics prior to the initiation of radiotherapy. Radiodermatitis severity will be assessed using the Radiation Therapy Oncology Group (RTOG) Acute Radiation Dermatitis Scale, and quality of life will be evaluated using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) and the breast cancer-specific module (EORTC QLQ-BR23). Following these assessments, participants will be randomly allocated to either the intervention group or the control group. Radiodermatitis severity will be evaluated weekly throughout the radiotherapy period using the RTOG scale and reassessed two weeks after completion of radiotherapy. Quality of life will be evaluated before radiotherapy and reassessed two weeks after completion of radiotherapy using the EORTC QLQ-C30 and EORTC QLQ-BR23 questionnaires. Participants assigned to the intervention group will be provided with access to an AI-supported digital education platform incorporating educational modules, personalized educational recommendations, reminder notifications, and motivational messages. In addition, system usability will be evaluated at the end of the intervention period using the System Usability Scale (SUS).

Official title: The Effect of Artificial Intelligence-Powered Digital Education Based on the Neuman Systems Model on Radiodermatitis Severity and Quality of Life in Breast Cancer Patients

Key Details

Conditions

Interventions