Evaluation of Chatbot for Mental Well-being: A Randomized Controlled Trial
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 293
- 试验地点
- 1
- 主要终点
- Mental Health Literacy
研究概览
简要总结
The present study consists of two two-armed randomized controlled trials between experimental and waitlist control groups. It aims to evaluate the effectiveness of conversational chatbot in improving mental health literacy, uptake of self-care behaviors, and mental well-being, compared to the waitlist control, and the effectiveness of daily notification on adherence. This study will provide important findings for the future development and implementation of chatbots in mental health, which may increase public access to immediate mental health support. It is hypothesized that participants in the experimental condition will show (H1) better mental health literacy (H2) better improvement in self-care and self-efficacy in mental well-being, and (H3) better mental well-being, compared with participants in the control condition. Also, it is hypothesized that participants with daily reminders will show (H4) a better adherence rate in using chatbot compared with participants without daily reminders
详细描述
Background
In Hong Kong, insufficient resources in the current public health system cause a long waiting time. Mental health services provided by the public health system mainly rely on traditional one-to-one face-to-face sessions. In the past 12 months, there were 48,520 new bookings in public psychiatry outpatient clinics and the longest waiting time was 94 weeks. Priority is always given to people with more severe mental health issues, which causes long waiting time for people with mild mental health symptoms. Untreated mental health issues can be escalated to more severe symptoms. Thus, in addition to treating mental illness, preventing common mental health issues and fostering mental health self-care in the general population are crucial to promote public mental health and reduce illness burden in the society.
The Hong Kong Mental Morbidity Study found 1 in 7 individuals in Hong Kong has either depression, anxiety, or a mix of the two disorders; however, only a quarter of them sought professional help. Rather than resorting to mental health professionals for face-to-face service to treat common mental health concerns, digital technology provides a highly scalable and accessible means through which individuals can access mental health resources for self-care. Among these tools, conversational agent is one of the viable options. It has been applied in health care industries to cater to different health needs, including providing timely information and supporting mental health disorders. Healthcare conversational agents were found to be effective in reducing depression and anxiety symptoms and had higher engagement rate compared with standard industry metrics. Chatbot is a type of conversational agent. It is a rule-based computer algorithm that conducts an automatic conversation with people based on predefined instructions. Based on a self-guided approach, users can search for topics that they are interested in and engage with pre-designed computer algorithms at the convenience of their own space and time without the constraints of specialized care. Applying chatbots in mental health self-care provides an opportunity for individuals to directly learn about relevant mental health-related knowledge and tips as well as practice self-care exercises at anytime, anywhere.
The Present Study
The present study aims to evaluate the effectiveness of conversational chatbot in improving mental health literacy, uptake of self-care behaviors, and mental well-being, compared to the waitlist control, and the effectiveness of daily notification on adherence. This study will provide important findings for the future development and implementation of chatbots in mental health, which may increase public access to immediate mental health support. It is hypothesized that participants in the experimental condition will show (H1) better mental health literacy (H2) better improvement in self-care and self-efficacy in mental well-being, and (H3) better mental well-being, compared with participants in the control condition. Also, it is hypothesized that participants with daily reminders will show (H4) a better adherence rate in using chatbot compared with participants without daily reminders
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Adults aged 18 years old or above
- •Able to read and understand Chinese and spoken Cantonese
- •Have access to the Internet
排除标准
- •Under 18 years old
- •Unable to read and understand Chinese and spoken Cantonese
- •Unable to access the internet
- •Existing users of the Jockey Club TourHeart+ Project and people who have participated in related research projects will be excluded from this study, as chatbots in this study were extracted from this online platform.
结局指标
主要结局
Mental Health Literacy
时间窗: Day 20
Sixteen items were developed to measure the knowledge of various aspects to do with mental health. Items are rated on a 7-points scale from 1 (strongly disagree) to 7 (strongly agree). Items are designed according to the content of chatbots and a well-developed Mental Health Literacy Scale.
Self-Care - Self-Care Behavior Inventory
时间窗: Day 20
It includes 19 items to measure self-care behavior using a 5-point scale from 1 (very little) to 5 (quite a lot). Internal consistency if the scale was 0.83. One item regarding medication is removed, while two items related to time spent on things that respondents enjoy and feel interested in and time spent alone were added.
Self-Care Self-efficacy - Strategies Used by People to Promote Health (SUPPH)
时间窗: Day 20
The scale is reliable, with a Cronbach's alpha of internal consistency of 0.93 . It includes 29 items to measure self-care self-efficacy using a 6-point scale from 1 (very little confidence) to 5 (quite a lot of confidence). High scores reflect better self-care self-efficacy. The SUPPH includes three subscales, stress reduction, decision-making, and positive attitudes. This study only includes items on stress reduction and positive attitudes. Cronbach's alpha of stress reduction and positive attitudes were 0.92 and 0.92 respectively.
次要结局
- Mindfulness - Mindful Awareness Attention Scale (MASS)(Day 10 and 20)
- Credibility and Expectancy. The Credibility and Expectancy Questionnaire (CEQ)(Day 10 and 20)
- Anxiety symptoms - Generalized Anxiety Disorder Assessment (GAD-7)(Day 10 and 20)
- Usability(Day 10 and 20)
- Attitude towards chatbot(Day 10 and 20)
- Depressive symptoms - Patient Health Questionnaire (PHQ-9)(Day 10 and 20)
- Usage(Day 10 and 20)
- Well-being - PERMA-Profiler (PERMA)(Day 10 and 20)
- Behavioral Intention - a subscale in the E-therapy Attitude and Process Questionnaire (eTAP)(Day 10 and 20)
研究者
Winnie W.S. MAK
Professor
Chinese University of Hong Kong