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临床试验/NCT07362823
NCT07362823尚未招募不适用

A Study on the Efficacy of the Metaverse Lifestyle Health Education Model Based on the Transtheoretical Model for Improving Quality of Life and Modifying Lifestyle in Colorectal Cancer Survivors

Qu Shen0 个研究点目标入组 174 人开始时间: 2026年1月20日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
尚未招募
发起方
入组人数
174
主要终点
Change in Health-Related Quality of Life Assessed by the Functional Assessment of Cancer Therapy-Colorectal (FACT-C) Scale

研究概览

简要总结

Colorectal cancer is a globally prevalent malignant tumor. Postoperative patients often face physical discomfort, psychological stress, and lack of healthy lifestyles. However, traditional health education models have limitations such as insufficient targeting and poor interactivity, making it difficult to meet their needs for full-cycle health management. This study is a multicenter randomized controlled trial, which plans to enroll 174 patients aged 18 years and above who have undergone radical resection for colorectal cancer, and randomly divide them into an experimental group and a control group at a ratio of 1:1. The experimental group will receive Transtheoretical Model (TTM)-based metaverse lifestyle health education (including phased course learning, metaverse immersive interaction, and WeChat group check-in supervision) with an intervention cycle of 1 months and follow-up until 3 months after the intervention; the control group will only receive routine paper-based education and outpatient follow-up. The study aims to verify the improvement effect of this metaverse intervention model on the quality of life and healthy lifestyle of colorectal cancer survivors, and explore its role in improving patients' self-efficacy, so as to provide empirical evidence for optimizing long-term health management programs for cancer survivors.

详细描述

  1. Study Background Colorectal cancer ranks 2nd in incidence and 4th in mortality among malignant tumors in China, with 517,000 new cases and 240,000 deaths in 2022, and the number of patients is expected to increase to 910,000 by 2040. Surgical and other treatment methods have prolonged patients' survival, transforming the disease into a chronic condition requiring long-term management. However, postoperative patients generally experience physical symptoms such as pain and gastrointestinal disorders, as well as psychological problems such as fear of recurrence and anxiety, and have low compliance with healthy lifestyle behaviors such as balanced diet and regular exercise. Traditional health education mainly relies on paper manuals and verbal guidance, lacking phased behavioral interventions and continuous interactive support, which cannot effectively promote the development of long-term healthy behaviors in patients.

The Transtheoretical Model (TTM) divides behavior change into 5 stages (pre-contemplation, contemplation, preparation, action, maintenance) and can provide targeted behavioral intervention strategies; metaverse technology has the advantages of immersion and high interactivity, which can break the temporal and spatial limitations of traditional education. This study integrates TTM theory, lifestyle medicine (including six pillars such as diet, exercise, and stress management) and metaverse technology to build a new health education model, aiming to address the core pain points of health management for colorectal cancer survivors. 2. Study Design

This is a prospective multicenter randomized controlled trial conducted in 3 Grade A tertiary hospitals: The First Affiliated Hospital of Xiamen University, Zhongshan Hospital Affiliated to Xiamen University, and Xiang'an Hospital Affiliated to Xiamen University. The study is divided into 3 phases:

2.1 Theoretical Construction Phase: Develop phased lifestyle health education courses based on TTM through literature research and expert consultation, and complete the functional adaptation of the metaverse platform (including modules such as graphic and text education, course learning, health challenges, and patient communities); 2.2 Intervention Implementation Phase: After signing the informed consent form, eligible patients are randomly grouped by tumor stage and age through the central randomization system (REDCap platform). The experimental group receives 3-month metaverse intervention (3 days for pre-contemplation stage, 4 days for contemplation stage, 7 days for preparation stage, 14 days for action stage, 14 days for maintenance stage, with a daily intervention duration of 20-30 minutes), and completes daily check-ins and medical Q&A through WeChat groups; the control group receives routine health education (distribute the Postoperative Rehabilitation Manual for Colorectal Cancer and complete postoperative follow-up according to hospital procedures); 2.3 Effect Evaluation Phase: Collect patients' quality of life (FACT-C scale), healthy lifestyle (HPLP II scale), self-efficacy (SUPPH scale), and physiological indicators such as BMI and CEA before intervention (T0), 1 month after intervention (T1), and 3 months after intervention (T2). Meanwhile, record the usage compliance of the metaverse platform and adverse events. 3. Study Endpoints 3.1 Primary Endpoints: Changes in standardized scores of the FACT-C scale and scores of the HPLP II scale in patients at 3 months after intervention (T2) compared with baseline (T0); 3.2 Secondary Endpoints: Changes in SUPPH scale scores, progress of behavior change stages, improvement of physiological indicators, platform usage compliance and satisfaction of patients during T0-T2; 3.3 Safety Endpoints: Incidence and severity of adverse events (such as exercise-related muscle soreness and platform operation discomfort) during the intervention period. 4. Quality Control The research team will conduct a unified baseline assessment of enrolled patients, and intervention personnel will take up their posts after passing GCP and platform operation training and assessment; double independent data entry is adopted, and missing values are handled by multiple imputation; meanwhile, a monitoring group is established to verify data from each center every 2 months to ensure the accuracy and completeness of research data.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Supportive Care
盲法
Double (Participant, Outcomes Assessor)

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Patients with first diagnosed colorectal cancer who have undergone radical surgical treatment
  • Aged ≥18 years old and non-pregnant
  • Have basic communication, reading and comprehension abilities, and can proficiently use smartphones and WeChat
  • Voluntarily sign the informed consent form and promise to cooperate in completing all interventions and follow-up assessments

排除标准

  • Patients with other types of malignant tumors
  • Patients with incompletely resected tumors or distant metastases
  • Patients with dysfunction of important organs such as heart, liver and kidney, or with unstable/rapidly deteriorating conditions
  • Patients with severe cognitive impairment who cannot communicate normally and cooperate with the intervention

研究组 & 干预措施

TTM-Based Metaverse Lifestyle Health Education Arm

Experimental

Administer TTM-phased lifestyle health education via metaverse platform (including health courses, immersive interactions, peer communities) and WeChat group check-in/medical Q&A. Assess indicators at baseline, 1-month, 3-month post-intervention.

干预措施: TTM-Based Metaverse Lifestyle Health Education (Behavioral)

Routine Colorectal Cancer Postoperative Health Education Arm

No Intervention

Provide paper-based postoperative rehabilitation manual and verbal lifestyle guidance; conduct routine telephone/outpatient follow-up per hospital protocol. Assess indicators at the same time points as the intervention arm.

结局指标

主要结局

Change in Health-Related Quality of Life Assessed by the Functional Assessment of Cancer Therapy-Colorectal (FACT-C) Scale

时间窗: Baseline (T0), 1 month after intervention (T1), 3 months after intervention (T2)

The FACT-C scale, a colorectal cancer-specific validated instrument, comprises 36 items across 5 domains (physical, social/family, emotional, functional well-being, and colorectal cancer-specific subscale). Scores are standardized to a 0-100 range, with higher scores indicating better quality of life. The outcome measures the change in standardized scores from baseline to 1 mouth and 3 months post-intervention.

Improvement in Health-Promoting Behaviors Assessed by the Health-Promoting Lifestyle Profile II (HPLP II) Scale

时间窗: Baseline (T0), 1 month after intervention (T1), 3 months after intervention (T2)

The HPLP II scale includes 52 items across 6 domains (self-actualization, health responsibility, physical activity, nutrition, interpersonal support, stress management). Scores range from 52 to 208, with higher scores reflecting more consistent health-promoting behaviors. The outcome measures the change in total scores from baseline to 1 month and 3 months post-intervention.

次要结局

  • Change in Self-Efficacy Assessed by the Strategies Used by People to Promote Health (SUPPH) Scale(Baseline (T0), 1 month after intervention (T1), 3 months after intervention (T2))
  • Progression of Health Behavior Change Stages Assessed by the Transtheoretical Model (TTM) Stage Scale(Baseline (T0), 1 month after intervention (T1), 3 months after intervention (T2))
  • Change in BMI(Baseline (T0), 1 month after intervention (T1), 3 months after intervention (T2))
  • Change in CEA(Baseline (T0), 1 month after intervention (T1), 3 months after intervention (T2))
  • Change in Blood Glucose(Baseline (T0), 1 month after intervention (T1), 3 months after intervention (T2))
  • Change in Blood Lipids(Baseline (T0), 1 month after intervention (T1), 3 months after intervention (T2))
  • Intervention Adherence Rate of Metaverse Platform Usage(Weekly during the 3-month intervention period; summarized at 3 months after intervention (T2))
  • Participant Satisfaction with the Metaverse Health Education Platform(1 month after intervention (T1), 3 months after intervention (T2))

研究者

发起方
Qu Shen
申办方类型
Other
责任方
Sponsor Investigator
主要研究者

Qu Shen

Associate Professor

Xiamen University

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