Can Mental Health Chatbots Help Chronic Disease Populations?

NCT04620668 | Completed Results

• 1 other identifier: REB 036-2020
• Study Type: interventional
• Target: 79
• Locations: 1 country
• Sites: 1

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.

Conditions

Arthritis; Diabetes; Depression; Anxiety; Stress

Keywords

Arthritis; Diabetes; Depression; Anxiety; Stress; Chatbot; Conversational Agent

Outcome Measures

Primary Outcomes (3)

• Changes in Depression as Measured by the Patient Health Questionnaire (PHQ-9)

  The Patient Health Questionnaire (PHQ-9) contains nine items, each of which is rated on a scale of 0 to 3. Ratings are summed for a composite score; the minimum score is 0 and the maximum score is 27. Higher scores indicate higher levels of depression.

  Participants are assessed at baseline, two weeks into the study, and four weeks into the study.

• Changes in Anxiety as Measured by the Generalized Anxiety Disorder Scale (GAD-7)

  The Generalized Anxiety Disorder Scale (GAD-7) contains seven items, each of which is rated on a scale of 0 to 3. Ratings are summed for a composite score; the minimum score is 0 and the maximum score is 21. Higher scores indicate higher levels of anxiety.

  Participants are assessed at baseline, two weeks into the study, and four weeks into the study.

• Changes in Stress as Measured by the Perceived Stress Scale (PSS-10)

  The Perceived Stress Scale (PSS-10) contains ten items, each of which is rated on a scale of 0 to 4. Ratings are summed for a composite score; the minimum score is 0 and the maximum score is 40. Higher scores indicate higher levels of stress.

  Participants are assessed at baseline, two weeks into the study, and four weeks into the study.

Secondary Outcomes (1)

• 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.

Study Arms (2)

Treatment Group (Wysa)

EXPERIMENTAL

Device: Wysa

Control Group

NO INTERVENTION

Interventions

Wysa DEVICE

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.

Treatment Group (Wysa)

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Participants must have a diagnosis of diabetes (type 1 or type 2 diabetes) or arthritis (osteoarthritis, rheumatoid arthritis, or another type of arthritis).
• Participants must have a phone with an active Internet connection.

You may not qualify if:

• Participants must not be receiving ongoing treatment from a mental health professional.
• Participants must not be using a mental health chatbot (i.e., prior to the study).
• Participants must not have started or experienced a dosage change in a psychopharmacological drug within the previous month.

Sponsors & Collaborators

• Luke MacNeill: lead
• New Brunswick Innovation Foundation: collaborator
• Touchkin eServices Pvt. Ltd.: collaborator

Study Sites (1)

Centre for Research in Integrated Care, University of New Brunswick

Saint John, New Brunswick, E2L4L5, Canada

Location

Related Publications (6)

• 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.

  PMID: 28588005 BACKGROUND

• 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.

  PMID: 30545815 BACKGROUND

• 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.

  PMID: 30470676 BACKGROUND

• 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.

  PMID: 30135751 BACKGROUND

• 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. doi: 10.5694/j.1326-5377.2009.tb02471.x.

  PMID: 19351294 BACKGROUND

• MacNeill AL, Doucet S, Luke A. Effectiveness of a Mental Health Chatbot for People With Chronic Diseases: Randomized Controlled Trial. JMIR Form Res. 2024 May 30;8:e50025. doi: 10.2196/50025.

  PMID: 38814681 DERIVED

MeSH Terms

Conditions

Arthritis; Diabetes Mellitus; Depression; Anxiety Disorders

Condition Hierarchy (Ancestors)

Joint Diseases; Musculoskeletal Diseases; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Behavioral Symptoms; Behavior; Mental Disorders

Results Point of Contact

• Title: Luke MacNeill
• Organization: University of New Brunswick

luke.macneill@unb.ca

506-648-5500

Study Officials

• Luke MacNeill, PhD

  Centre for Research in Integrated Care, University of New Brunswick

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: Yes
• Restrictive Agreement: No

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Purpose: SUPPORTIVE CARE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Postdoctoral Fellow

Model Details: Participants will be assigned to one of two groups. The treatment group will use a mental health chatbot (Wysa) over a period of four weeks. The control group will receive no intervention.

Study Record Dates

• First Submitted: November 2, 2020
• First Posted: November 9, 2020
• Study Start: October 1, 2021
• Primary Completion: October 31, 2022
• Study Completion: October 31, 2022
• Last Updated: August 26, 2024
• Results First Posted: August 26, 2024

Record last verified: 2024-07

Data Sharing

• IPD Sharing: Will not share

Locations

CA (1)