The goal of this clinical trial is to evaluate the usefulness and effectiveness of a newly developed artificial intelligence (AI) chatbot for health education in thyroid cancer patients during the period around their surgery (the perioperative period). The main questions it aims to answer are: Does the AI chatbot improve patients' readiness for discharge, quality of recovery, and active engagement in their own healthcare compared to traditional education methods? How do patients rate the usability and friendliness of this new AI chatbot system? Researchers will compare a group of patients who receive traditional health education (the control group) with a subsequent group of patients who use the new AI chatbot built on the "Coze" platform (the intervention group) to see if the AI chatbot leads to better recovery experiences and higher patient engagement. Participants will be asked to: Access and interact with the AI chatbot to receive personalized health guidance, ask questions, and get instant feedback during their hospital stay. Complete a set of questionnaires on the morning of their hospital discharge to evaluate their recovery quality, readiness to leave the hospital, and level of engagement in their care. Complete an extra survey regarding the usability and acceptability of the chatbot system (only for participants in the AI chatbot group).
Background and Rationale: Thyroid cancer treatment and care involve long-term medication management and follow-up monitoring. While the application of Enhanced Recovery After Surgery (ERAS) protocols has significantly shortened the length of hospital stays, it has also reduced the time available for face-to-face clinician-patient communication. Traditional health education models often struggle to meet the continuous and diverse information needs of patients during the perioperative period. This study aims to develop a novel health education chatbot based on the "Coze" platform to provide personalized, instant, and interactive perioperative guidance for thyroid cancer patients, thereby exploring a new digital approach to patient education and supportive care. Study Design and Timeline: This study utilizes a non-randomized, sequentially controlled design (a before-after study) and consists of two consecutive phases: Control Phase (Traditional Education): Patients admitted during this period will receive standard, routine perioperative health education provided by the nursing staff. Intervention Phase (AI Chatbot Education): Following the control phase, the newly developed AI chatbot will be implemented. Patients admitted during this period will have access to the chatbot in addition to routine care. The AI Chatbot Intervention: The AI chatbot is designed to provide comprehensive, 24/7 interactive support. Its core function modules include pre-admission preparation, postoperative care guidance, medication management (such as thyroid hormone replacement therapy), diet and lifestyle advice, and follow-up scheduling. Patients can ask questions in natural language and receive immediate feedback tailored to their surgical stage. Data Collection Procedure: For both groups, clinical and survey data will be collected systematically. On the morning of hospital discharge, participants in both the control and intervention groups will be asked to complete a set of standardized questionnaires evaluating their quality of recovery, readiness for discharge, and level of patient activation. Additionally, participants in the intervention group will com
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
DOUBLE
Enrollment
150
Participants in this group will receive standard, traditional perioperative health education. The intervention is delivered orally by three certified senior oncology nurses at 5 predefined clinical timeline milestones. A standardized health education protocol is followed, which comprehensively covers general information about thyroid cancer, pre-admission preparation, surgical day and postoperative care, symptom management, discharge instructions, medication adherence guidance, and transitional care. After hospital discharge, participants will receive routine follow-up support through the hospital's official mini-program platform's health consultation portal.
In addition to the routine health education received by the control group, participants in this group will interact with a novel, interactive health education chatbot developed on the "Coze" AI platform. The chatbot intervention framework consists of three core components: User Guide \& Free Inquiry: Patients receive instructions on how to use the AI agent and can initiate unstructured, free-text inquiries in natural language based on their individual needs. Proactive Health Education Push: The chatbot automatically pushes targeted health education modules to patients at predefined clinical milestones throughout the perioperative journey. Interactive Precaution Explanations: The chatbot provides detailed, real-time explanations of postoperative precautions and self-care guidelines. Furthermore, a dedicated technical and clinical maintenance team will continuously optimize the system's prompt words and interaction designs based on patient feedback and user behavioral analysis to enha
Tianjin Medical University Cancer Institute and Hospital
Tianjin, Tianjin Municipality, China
RECRUITINGReadiness for Hospital Discharge
Measured using the Readiness for Hospital Discharge Scale (RHDS). The scale consists of 23 items across four dimensions: personal status (7 items), knowledge of the disease (8 items), coping ability (3 items), and expected support (4 items). Each item is scored on a 0-10 scale. The total score ranges from 0 to 220, with higher scores indicating a higher and more sufficient readiness for hospital discharge. The overall Cronbach's alpha of the scale is 0.97.
Time frame: On the morning of hospital discharge
Postoperative Quality of Recovery
Evaluated using the Chinese version of the 15-item Quality of Recovery Scale (QoR-15). It measures the patient's early postoperative recovery quality across five dimensions: physical comfort, independence, psychological support, emotional state, and pain. The total score ranges from 0 to 150, with higher scores representing a better and higher quality of recovery.
Time frame: On the morning of hospital discharge
System Usability of the AI Chatbot
Measured exclusively in the intervention group using the System Usability Scale (SUS) to evaluate the overall usability and user satisfaction of the chatbot. The scale consists of 10 items covering three dimensions: effectiveness, learnability, and satisfaction. The total score ranges from 0 to 100, with higher scores indicating better system usability. A total score greater than 60 is generally considered acceptable and indicates good usability. The content validity index (CVI) of the scale is 0.822.
Time frame: On the morning of hospital discharge.
Patient Activation and Self-Management Engagement
Assessed using the Patient Activation Measure (PAM) to evaluate the patients' proactive engagement and readiness for self-management. The scale encompasses 4 dimensions: knowledge, beliefs, skills, and actions. Total scores are typically converted to a standardized 0-100 scale, where higher scores reflect greater patient activation and better self-management capability. The Cronbach's alpha is 0.865.
Time frame: On the morning of hospital discharge
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