Clinical trial NCT05694507: Evaluation of Chatbot for Mental Well-being
Official title: Evaluation of Chatbot for Mental Well-being: A Randomized Controlled Trial
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Mental Well-being
Mental Health Literacy
Lead sponsor: Chinese University of Hong Kong
Sponsor class: OTHER
First posted: 2023-01-23
Enrollment: 293
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Experimental and waitlist control groups
Primary purpose: OTHER

Brief summary: 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

Detailed description: 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

Participants

Participants will be recruited through (1) advertising at popular online networking platforms (e.g., Facebook and Instagram), mass mailing at investigator's institutions, and snowball sampling.

Procedure Upon completing the screening and pre-evaluation questionnaire, participants will be randomly assigned to the experimental group or waitlist control group, with and without notifications based on computer-generated random digits. They will complete 2 more sets of questionnaires, including a post-evaluation 11 days after group allocation, and a follow-up questionnaire 21 days after group allocation. In the experimental group, participants will go through one assigned chatbot each day for 10 days, with the sequence of the assigned chatbot randomized. The chatbot contents are developed by clinical psychologists and well-being promotion officers. Content includes relationships, stress, value, emotion, and positive psychology. Each chatbot can only be assessed on the day of distribution. The access link will expire upon completion and the day after distribution to prevent repeat and delay in completion. Experimental group participants can freely access all chatbots after the completion of post-evaluation and before the follow-up questionnaire is sent to them. In the waitlist control group, participants are to refrain from using the chatbot until they finished the follow-up questionnaire. All participants will be able to access the chatbot materials in an online platform after they have completed the research.

Eligibility criteria: Inclusion Criteria:

* Adults aged 18 years old or above
* Able to read and understand Chinese and spoken Cantonese
* Have access to the Internet

Exclusion Criteria:

* 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.

Primary outcomes:
measure: Self-Care Self-efficacy - Strategies Used by People to Promote Health (SUPPH)
timeFrame: Day 10
measure: Self-Care Self-efficacy - Strategies Used by People to Promote Health (SUPPH)
timeFrame: Day 20
measure: Self-Care - Self-Care Behavior Inventory
timeFrame: Day 10
measure: Self-Care - Self-Care Behavior Inventory
timeFrame: Day 20
measure: Mental Health Literacy
timeFrame: Day 10
measure: Mental Health Literacy
timeFrame: Day 20
Secondary outcomes:
measure: Depressive symptoms - Patient Health Questionnaire (PHQ-9)
timeFrame: Day 10 and 20
measure: Anxiety symptoms - Generalized Anxiety Disorder Assessment (GAD-7)
timeFrame: Day 10 and 20
measure: Mindfulness - Mindful Awareness Attention Scale (MASS)
timeFrame: Day 10 and 20
measure: Well-being - PERMA-Profiler (PERMA)
timeFrame: Day 10 and 20
measure: Behavioral Intention - a subscale in the E-therapy Attitude and Process Questionnaire (eTAP)
timeFrame: Day 10 and 20
measure: Attitude towards chatbot
timeFrame: Day 10 and 20
measure: Credibility and Expectancy. The Credibility and Expectancy Questionnaire (CEQ)
timeFrame: Day 10 and 20
measure: Usability
timeFrame: Day 10 and 20
measure: Usage
timeFrame: Day 10 and 20
Other outcomes:
Locations:
city: Sha Tin
country: Hong Kong
facility: Diversity and Well-being Lab, CUHK
state: N.t.
Study officials:
affiliation: Professor
name: Winnie WS MAK
role: PRINCIPAL_INVESTIGATOR
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