The Impact of Chatbot-aid on Promoting Self-management of Men's Health in the Post COVID-19 Era

Overview

The AI chatbot as an artificial intelligence technology provides disease information and health care through digital assistance. However, the effectiveness of chatbot in promoting men's health in the field of urology needs further research to evaluate its actual results. The purpose of this study is to explore the impact of AI chatbot-aid intervention on enhancing self-management, and decision self-efficacy among men with lower urinary tract symptoms (LUTS) due to an enlarged prostate, and with or without erectile dysfunction (ED) in the post COVID-19 era.

1. Background and objectives : After the age of 50 years, men's health may be impacted by various disorders such as lower urinary tract symptoms (LUTS) and erectile dysfunction (ED). Due to a lack of understanding and awareness, patients often fail to recognize early signs and are not compliant with medical advice. As they are hesitant to discuss these issues related to urination and erectile functions, they avoid seeking medical help, especially due to the restrictions and concerns brought by the COVID-19 pandemic. Consequently, worsening symptoms can adversely affect their quality of life and dignity. Studies have found that providing men with self-management health programs results in better symptom management and medical decisions. Therefore, work is underway to develop artificial intelligence (AI) platforms to allow men to manage their health before consulting a doctor. Chatbots are used for various medical decisions and healthcare management, and can now provide men with various healthcare information to help improve the effectiveness of self-care and medical treatments in the post COVID-19 period. The purpose of this study is to explore the impact of AI chatbot aid intervention on enhancing self-management, and decision self-efficacy among men with lower urinary tract symptoms (LUTS) due to an enlarged prostate, with or without erectile dysfunction (ED) in the post COVID-19 era. 2. Materials and Methods: 2.1. Trial design and ethical approval This was a 1:1 two groups randomized controlled trial (RCT) with pre- and post-test experimental design. This study was approved by the Institutional Review Board (IRB) of Cheng Hsin General Hospital in Taipei, Taiwan (approval number CHGH-IRB (988)111A-66-2) and participants were provided with informed consent. Both groups had similar demographics. One hundred male patients will be recruited from the Urology outpatient clinic, with 50 patients randomly assigned to the experimental group and 50 patients to the control group. 2.2 Participants Patients diagnosed with health-related diseases by urologists were included in this study. The conditions were as follows:(1) male, (2) age between 45-80 years old, (3) prostate enlargement with lower urinary tract symptoms, (4) need a mobile phone and willing to download the line chatbot. The exclusion criterion was a history of psychosis. 2.3 Intervention The study uses a chatbot in collaboration with the Taiwan Urological Association (TUA) and the Taiwan Continence Society (TCS), which is deployed on the line app for mobile devices. The chatbot uses an AI model integrated with the line developer platform to predict risks for men's health conditions such as urinary symptoms and erectile dysfunction. Patients can access the chatbot for free by scanning a QR code. It provides self-management advice on issues such as prostate enlargement, urinary symptoms, and erectile dysfunction. It also provides patient-centered decision-making aids that support and encourage patients, especially in improving urination and erectile dysfunction. 2.4 Research instruments The patients in both groups were asked to complete a basic personal information form, as well as several questionnaires including the International Prostate Symptom Score (IPSS), International Index of Erectile Function-5 (IIEF-5), Men's Health knowledge score, Partners in Health (PIH), and Decision Self-Efficacy Scale (DSES) before and 2-4 weeks after receiving the intervention measures. Additional examination data, such as prostate-specific antigen (PSA), uroflowmetry, and prostate sonography, were collected from medical records. A satisfaction questionnaire was also administered to the patients. 2.5 Statistical methods SPSS was used for statistical analysis, including McNemar's test and independent sample t-test were used to compare and analyze the difference in the knowledge score, self-management, and decision-making self-efficacy between the experimental group and control group before and after the intervention; paired t-test was used to compare individuals before and after receiving intervention measures; Pearson's correlation was used to analyze the relationship among LUTS, knowledge score, self-management, and decision self-efficacy; Finally, multiple regression analysis to analyze the impact of using the chatbot on satisfaction.