Clinical Investigation of Wysa

Study Overview
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Brief Summary
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Mental health concerns are a large burden for individuals, healthcare systems, and the economy. Over a million people are referred to UK mental health services each year, but more than half only receive one session of workbook-based support. Many others have to wait over 12 weeks for assessment and treatment. Wysa is a digital health app with over 3 million users that uses an artificial intelligence (AI) chatbot and a series of self-care exercises to provide mental health support and to help people develop strategies to manage their mental health and improve their resilience. This project aims to examine the impact of using Wysa on patients' symptoms of anxiety and depression during the referral process for standard UK mental health services. Patients will be given access to Wysa at the point of referral to the Improving Access to Psychological Therapies (IAPT) programme and can begin to explore the self-support tools, while they are on the waitlist for assessment and treatment. The investigators will gather a group of patients and members of the public to contribute to the recruitment of patients for the study, the methods we use to evaluate Wysa, and to provide insights on how best to share the results of our study with the general public. The investigators will use the standard IAPT measures of anxiety and depression to look at the effect of using Wysa patients' mental well-being. These questionnaires will be provided through the app and the results will be compared with a waitlist control group. The investigators will examine whether Wysa can identify people who are experiencing severe mental health difficulties so that they can be provided with additional support. Users' levels of engagement with Wysa will be assessed and some participants will be randomly selected to do an interview so the investigators can get a better understanding of what people liked and disliked about using the app and why. Finally, the investigators will be evaluating the cost-effectiveness of Wysa compared with usual care. The investigators expect that the study will show that Wysa helps reduce symptoms of anxiety and depression in people who are on the waiting list for IAPT. If the study shows this positive impact, this will provide evidence to support the use of Wysa to improve the accessibility of mental health support in clinical pathways. The investigators will be publishing the results of our study in academic journals as well as in more generally accessible platforms.

Official Title
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Real World Testing of an Artificial Intelligence-enabled App as an Early Intervention and Support Tool in the Mental Health Referral Care Pathway

Conditions
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Mental Health Issue, Anxiety, Depressive Symptoms

Intervention / Treatment
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* Device: Wysa AI chatbot mental health app


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Willing and able to provide informed consent; Aged 18 years or older; Ability to speak English to a secondary school standard; Own a mobile device capable of supporting Wysa; A valid email address; Referred or self-referred to proceed through the standard IAPT care pathway. Exclusion Criteria: Patients ineligible for the standard IAPT care pathway; Patients with previous and current known major mental illness such as Schizophrenia, severe depression, any co-morbid neurological or neuro-psychiatric condition such as epilepsy; Patients with current psychosis or a history of psychotic symptoms within the last 6 months; Patients with suicidal ideation; Patients scoring > 15 points on PHQ 9; Patients scoring > 15 points on GAD-7; Patients with significant cognitive disorders; Patients with noted neurodevelopmental conditions such as autism or ADHD; Patients previously diagnosed with a personality disorder; Patients who been under the care of CMHT or a specialised mental health services in the last 2 years; Patients who failed IAPT previously; Patients with referrals for specialist presentations of pre-existing, diagnosed conditions requiring a specialised assessment beyond the standard clinical pathway; Incapable of self-consent; In a dependent/unequal relationship with the research or care teams or any PPI representatives.

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Treatment
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: Participants will be randomly allocated to the intervention condition or a standard care waitlist control condition.
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Wysa AI chatbot mental health app<br>Wysa is a guided self-help and triaging tool delivered to patients via an app or widget. It uses Natural Language Processing to understand individuals' written inputs but not to generate responses. Wysa makes use of a wide range of clinically underpinned modules whilst gamification, clinical outcome measures and AI promotes engagement, improving efficacy and triage and reducing the cost of scale. | Device: Wysa AI chatbot mental health app<br>* Wysa is a guided self-help and triaging tool delivered to patients via an app. It includes a chatbot and makes use of a wide range of clinically underpinned modules to provide mental health support.<br>|
| No Intervention: Waitlist control<br>The intervention will be compared against a waitlist group. This comparator was selected to compare Wysa to the current standard of care for patients waiting for standard IAPT assessment and treatment. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Depression severity | Score on the PHQ-9, total scores range from 0 to 27 (higher scores indicated more severe depression) | 3 months post-randomisation | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Anxiety severity | Score on the GAD-7, total scores range from 0 to 21 (higher scores indicated more severe anxiety) | 3 months post-randomisation | 
| Crisis identification | Number of users identified by the app for escalation of care compared to the number of patients in the control group who access A&E or out-of-hours services while waiting for treatment | Over 9 month intervention period | 
| Uptake rates | Uptake rates of participants randomised into intervention group | Over 9 month intervention period | 
| Dropout rates | Dropout rates of participants who are randomised into intervention group and start using the app | Over 9 month intervention period | 
| App usage data | Frequency and duration of app use | Over 9 month intervention period | 
| Engagement | Qualitative feedback from semi-structured interviews about engagement with the app | Over 9 month intervention period | 
| Patient perceptions of acceptability | Qualitative feedback from semi-structured interviews about the acceptability of the app | Over 9 month intervention period | 
| Self-reported acceptability through the app | Automated review questions periodically requested during general use of the tool | Over 9 month intervention period | 
| General health state | Assessed using the EQ-5D-5L, total scores ranging from 5 to 125 (higher scores indicate more severe health problems) | Measured at baseline and 3 months post-randomisation | 
| Impact of health on everyday life | Assessed using the Short Form 12 (SF-12) health survey, total scores ranging from 0 to 100 (higher scores indicate better physical and mental functioning) | Measured at baseline and 3 months post-randomisation | 
| Cost-analysis | Assessed using compiled cost data relating to health and social care service use, medication and treatment use, Wysa's implementation, and patients' personal payments or related productivity losses | Over 9 month intervention period | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Artificial Intelligence, Mental Health, Telemedicine, Conversational Agent