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
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 38
- 主要终点
- Radiodermatitis Severity (Radiation Therapy Oncology Group Skin Toxicity Scale)
研究概览
简要总结
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).
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Prevention
- 盲法
- Single (Outcomes Assessor)
盲法说明
Radiodermatitis severity will be assessed by a trained clinical healthcare professional who will be blinded to group allocation. The outcome assessor will not know whether participants are assigned to the intervention or control group.
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- Female
- 接受健康志愿者
- 否
入选标准
- •Women aged 18 years or older diagnosed with primary breast cancer who have completed surgical treatment and are scheduled to receive adjuvant radiotherapy.
- •Patients who will receive radiotherapy for the first time.
- •Patients whose general health condition is suitable for participation in the study and follow-up assessments.
- •Patients who are able to read, understand, and communicate in Turkish.
- •Patients who have access to the internet and are able to use a smartphone, tablet, or computer to access the digital education program.
- •Patients who voluntarily agree to participate in the study and provide written informed consent.
排除标准
- •Previous radiotherapy to the same treatment area.
- •Presence of an active infection, open wound, or severe dermatological disease within the radiation treatment field.
- •History of a chronic skin condition that may affect radiation-induced skin reactions.
- •Cognitive or psychiatric conditions that may prevent participants from following the educational program or complying with the study procedures and data collection process.
研究组 & 干预措施
Intervention Group
Participants will receive access to an artificial intelligence-supported digital education program based on the Neuman Systems Model. Educational modules include radiotherapy information, recognition of radiodermatitis symptoms, preventive skin care practices, symptom management, psychological adaptation, and post-treatment care.
干预措施: Neuman-Based AI-Supported Digital Education Program (Behavioral)
Control Group
Participants will receive routine nursing care and standard patient education provided in the clinical setting.
干预措施: Standard Care (in control arm) (Other)
结局指标
主要结局
Radiodermatitis Severity (Radiation Therapy Oncology Group Skin Toxicity Scale)
时间窗: Weekly during radiotherapy (5 weeks) and 2 weeks after completion of radiotherapy.
Radiodermatitis severity will be assessed using the Radiation Therapy Oncology Group (RTOG) Skin Toxicity Scale. The scale classifies acute radiation-induced skin reactions from Grade 0 (no skin reaction) to Grade 4 (ulceration, necrosis, or severe skin toxicity). Higher scores indicate more severe skin toxicity. Assessments will be performed weekly during radiotherapy and two weeks after completion of treatment by a trained clinical healthcare professional blinded to group allocation.
次要结局
- European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-BR23(Baseline and 2 weeks after completion of radiotherapy.)
研究者
Kübra TEMÜR
Lecturer, Doctoral Candidate, Department of Internal Medicine Nursing, Atatürk University
Ataturk University