Intelligent Sexual Health LillyBot Information Support System for Gynecological Cancer Patients: Development, Test and Evaluation of Longitudinal Effects
Intelligent Sexual Health LillyBot Information Support System for Gynecological Cancer Patients: Development, Test and Evaluation of Longitudinal Effects
This study aims to develop the LillyBot Smart Sexual Health Consultation System, designed to meet the sexual health learning and consultation needs of gynecological cancer (GC) patients in Taiwan. Grounded in the Transtheoretical Model (TTM), this system integrates AI chatbot technology and mobile health (mHealth) to provide real-time, personalized sexual health education and consultations, ultimately improving the overall sexual well-being of GC patients.
In the first year, the study established the mHealth-assisted Patient-Reported Outcome Measurement (mHealth-assisted PROM) module and conducted a comprehensive sexual health needs assessment. Based on these findings, the second-year study focuses on designing and developing the LillyBot system, ensuring its responsiveness to the specific needs of GC patients. The third-year study will employ a prospective pretest-posttest randomized control group design with a single-blind approach. A total of 90 GC patients will be recruited from a medical center in northern Taiwan and randomly assigned through stratified randomization into three groups. The first experimental group will receive LillyBot-based sexual health consultations, while the second experimental group will receive online consultations with sexual health professionals. The control group will receive online consultations with non-specialists. Data will be collected at baseline (T0), one month post-intervention (T1), and three months (T2) to evaluate the intervention's effectiveness. Primary outcomes will include sexual distress, sexual knowledge, sexual attitudes, sexual self-efficacy, sexual behaviors, and sexual satisfaction, allowing for a comprehensive assessment of changes over time.
Inclusion Criteria:
Exclusion Criteria:
jtlee@gap.cgu.edu.tw886-03-2118800 ext. 5197