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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
76
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.
University of Plymouth
Plymouth, Devon, United Kingdom
Central North West London NHS
London, United Kingdom
Depression Severity
Score on the PHQ-9, total scores range from 0 to 27 (higher scores indicated more severe depression)
Time frame: 3 months post-randomisation
Anxiety Severity
Score on the GAD-7, total scores range from 0 to 21 (higher scores indicated more severe anxiety)
Time frame: 3 months post-randomisation
Crisis Identification
Planned to compare 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; this was not possible, data reported reflect risk events triggered by Wysa or the participant in-app
Time frame: 3 months post-randomisation
Uptake Rates
Uptake rates of participants randomised into intervention group
Time frame: 3 months post-randomisation
Dropout Rates
Dropout rates of participants who are randomised into intervention group and start using the app
Time frame: 3 months post-randomisation
Use of the App
Participant engagement with the app (whether it was used at all based on app usage data)
Time frame: 3-7 months post-randomisation
Engagement
Qualitative feedback from semi-structured interviews about engagement with the app
Time frame: 3-7 months post randomisation
Patient Perceptions of Acceptability
Qualitative feedback from semi-structured interviews about the acceptability of the app
Time frame: 3-7 months post randomisation
General Health State
5-level EQ-5D version (EQ-5D-5L) which measures health-related quality of life via 5 dimensions (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) and a visual scale - total survey scores were calculated and can range from 5 to 125 (higher scores indicate more severe health problems). A single index was obtained by transforming the ordinal survey responses using the 'eq5d' package in R. Range: The EQ-5D index score typically ranges from -0.594 to 1 (depending on the country-specific value set used). Interpretation: 1.000 represents full health (the best possible outcome). 0.000 represents a health state equivalent to death (neutral point). Negative values (e.g., -0.594) indicate health states perceived as worse than death. Higher index values indicate better health outcomes, while lower values represent poorer health states. https://euroqol.org/wp-content/uploads/2023/11/EQ-5D-5LUserguide-23-07.pdf
Time frame: Measured at baseline and 3 months post-randomisation
Type of App Usage - Exercises Completed
Frequency and duration of app use
Time frame: 3 months post-randomisation
Type of App Usage - Sessions Completed
Frequency and duration of app use
Time frame: 3 months post-randomisation
Type of App Usage - Messages to Chatbot
Frequency and duration of app use
Time frame: 3 months post-randomisation
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