Can Mental Health Chatbots Help Chronic Disease Populations?
Study Details
Study Description
Brief Summary
Past research has shown that patients suffering from chronic health conditions tend to experience high levels of negative mental health symptoms (e.g., depression). The purpose of the current study is to evaluate whether an artificial intelligence (A.I.) mental health chatbot can be used to reduce negative mental health symptoms within this population. A minimum of 60 individuals with a chronic health condition (diabetes or arthritis) will be recruited. Participants will be randomly assigned to either a treatment group or a control group. Those assigned to the treatment group will use the mental health chatbot Wysa (Touchkin eServices, Bangalore) over a period of four weeks. Those assigned to the control group will receive no chatbot. Participants will complete measures of depression, anxiety, stress, and life satisfaction via Qualtrics at the outset of the study, two weeks into the study, and four weeks into the study (i.e., the final assessment point). Results from the treatment and control groups will be compared using ANOVA models. Participants in the treatment group will also be asked to complete some open-ended questions about their experiences with the chatbot program. A subset of participants from the treatment group may be asked to complete optional phone or video interviews to gain a better understanding of their experiences. Results will provide insight into the usefulness of chatbot programs for reducing negative mental health symptoms among patients with a chronic health condition. Results may also be used to inform policy decisions about the use of these programs for healthcare delivery, and to provide practical insight into how these programs can be best integrated into healthcare settings.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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N/A |
Detailed Description
People dealing with chronic health conditions are susceptible to mental health issues such as depression and anxiety. Providing conventional mental health services to all of these individuals is not practical given the limited resources of the healthcare system. Artificial intelligence (A.I.) mental health chatbots may be an accessible and cost-effective means by which people can receive some degree of mental health support while they cope with their conditions. These automated programs act as a source of virtual support, talking with individuals and providing them with therapeutic exercises to improve their mental wellbeing. Several chatbots have been designed to deliver interventions based on popular psychological therapies (e.g., Wysa, Woebot, and Tess). Research has shown that these programs can reduce symptoms of depression, anxiety, and stress in nonclinical populations. However, the effectiveness of these programs has not been tested in chronic disease populations.
The purpose of the current research is to gain a better understanding of the usefulness of mental health chatbots for chronic disease populations. This research will be guided by two fundamental objectives: (1) to determine whether a mental health chatbot can reduce or prevent negative mental health symptoms in individuals who are dealing with a chronic health condition, and (2) to learn more about how individuals with a chronic health condition view these programs, particularly in terms of their potential benefits or drawbacks when used in healthcare settings. This research will focus on two specific chronic disease populations that are prone to elevated levels of mental health symptoms: people with arthritis and diabetes.
Participants will be recruited through social media channels (including online groups), newspaper advertisements, and emails and newsletters from relevant organizations (e.g., the Arthritis Society, Diabetes Canada). After volunteering to participate, participants will set up a phone or video conferencing call with the primary investigator to orient them into the study. Participants will be randomly assigned to either a treatment group or control group. Those assigned to the treatment group will download the mental health chatbot Wysa (Touchkin eServices, Bangalore) on their smartphones. They will interact with the chatbot a minimum of two times per week over a period of four weeks, with each interaction lasting a minimum of five minutes. Participants assigned to the control group will receive no chatbot (i.e., they will be in a no-treatment control group).
Regardless of their group assignment, participants will complete online materials via Qualtrics at the outset of the study, two weeks into the study, and four weeks into the study (i.e., the final assessment point). At the outset of the study, participants will fill out an informed consent form, a demographic questionnaire, and four psychological assessments tools: measures of depression, anxiety, stress, and life satisfaction. Two weeks into the study, participants will complete the four psychological assessment tools a second time. Four weeks into the study, participants will complete the four assessment tools a final time, and those in the treatment group will be presented with a post-study questionnaire that contains qualitative questions regarding their experiences with the chatbot. Participants in both groups will be presented with a debriefing form providing more information about the study. Those in the control group will be given the opportunity to download and use the chatbot at this point.
After the data from the four-week study are analyzed, a subset of participants from the treatment group may be asked to complete optional phone or video interviews to gain more insight into their experiences with and opinions on the chatbot program. Approximately 15 to 20 participants will be sought for the interviews. The questions for these interviews will be developed based on the collective results from the quantitative and qualitative analysis described above.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Treatment Group (Wysa)
|
Device: Wysa
Wysa is an AI-based mental health chatbot. It uses evidence-based techniques to help users build mental resilience skills and improve their mental health.
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| No Intervention: Control Group
|
Outcome Measures
Primary Outcome Measures
- Changes in depression as measured by the Patient Health Questionnaire (PHQ-9) [Participants are assessed at baseline, two weeks into the study, and four weeks into the study.]
The Patient Health Questionnaire (PHQ-9) contains nine items, each of which is rated on a scale of 0 to 3. Higher scores indicate higher levels of depression.
- Changes in anxiety as measured by the Generalized Anxiety Disorder Scale (GAD-7) [Participants are assessed at baseline, two weeks into the study, and four weeks into the study.]
The Generalized Anxiety Disorder Scale (GAD-7) contains seven items, each of which is rated on a scale of 0 to 3. Higher scores indicate higher levels of anxiety.
- Changes in stress as measured by the Perceived Stress Scale (PSS-10) [Participants are assessed at baseline, two weeks into the study, and four weeks into the study.]
The Perceived Stress Scale (PSS-10) contains ten items, each of which is rated on a scale of 0 to 4. Higher scores indicate higher levels of stress.
Secondary Outcome Measures
- Changes in life satisfaction as measured by the Satisfaction with Life Scale [Participants are assessed at baseline, two weeks into the study, and four weeks into the study.]
The Satisfaction with Life Scale contains five items, each of which is rated on a scale of 1 to 7. Higher scores indicate higher levels of life satisfaction.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Participants must have a diagnosis of diabetes (type 1 or type 2 diabetes) or arthritis (osteoarthritis, rheumatoid arthritis, or another type of arthritis).
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Participants must have a phone with an active Internet connection.
Exclusion Criteria:
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Participants must not be receiving ongoing treatment from a mental health professional.
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Participants must not be using a mental health chatbot (i.e., prior to the study).
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Participants must not have started or experienced a dosage change in a psychopharmacological drug within the previous month.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Centre for Research in Integrated Care, University of New Brunswick | Saint John | New Brunswick | Canada | E2L4L5 |
Sponsors and Collaborators
- Luke MacNeill
- New Brunswick Innovation Foundation
- Touchkin eServices Private Limited
Investigators
- Principal Investigator: Luke MacNeill, PhD, Centre for Research in Integrated Care, University of New Brunswick
Study Documents (Full-Text)
None provided.More Information
Publications
- Clarke DM, Currie KC. Depression, anxiety and their relationship with chronic diseases: a review of the epidemiology, risk and treatment evidence. Med J Aust. 2009 Apr 6;190(S7):S54-60.
- Fitzpatrick KK, Darcy A, Vierhile M. Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial. JMIR Ment Health. 2017 Jun 6;4(2):e19. doi: 10.2196/mental.7785.
- Fulmer R, Joerin A, Gentile B, Lakerink L, Rauws M. Using Psychological Artificial Intelligence (Tess) to Relieve Symptoms of Depression and Anxiety: Randomized Controlled Trial. JMIR Ment Health. 2018 Dec 13;5(4):e64. doi: 10.2196/mental.9782.
- Inkster B, Sarda S, Subramanian V. An Empathy-Driven, Conversational Artificial Intelligence Agent (Wysa) for Digital Mental Well-Being: Real-World Data Evaluation Mixed-Methods Study. JMIR Mhealth Uhealth. 2018 Nov 23;6(11):e12106. doi: 10.2196/12106.
- Ly KH, Ly AM, Andersson G. A fully automated conversational agent for promoting mental well-being: A pilot RCT using mixed methods. Internet Interv. 2017 Oct 10;10:39-46. doi: 10.1016/j.invent.2017.10.002. eCollection 2017 Dec.
- REB 036-2020