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Accepted for/Published in: JMIR Human Factors

Date Submitted: Dec 13, 2021
Date Accepted: Mar 6, 2022
Date Submitted to PubMed: Mar 7, 2022

The final, peer-reviewed published version of this preprint can be found here:

Evaluating User Feedback for an Artificial Intelligence–Enabled, Cognitive Behavioral Therapy–Based Mental Health App (Wysa): Qualitative Thematic Analysis

Malik T, Ambrose AJ, Sinha C

Evaluating User Feedback for an Artificial Intelligence–Enabled, Cognitive Behavioral Therapy–Based Mental Health App (Wysa): Qualitative Thematic Analysis

JMIR Hum Factors 2022;9(2):e35668

DOI: 10.2196/35668

PMID: 35249886

PMCID: 9044157

User Feedback Analysis of an AI-Enabled CBT Mental Health Application (Wysa)

  • Tanya Malik; 
  • Adrian Jacques Ambrose; 
  • Chaitali Sinha

ABSTRACT

Background:

Digital mental health applications (apps) are rapidly becoming a common source of accessible support across the world, but their effectiveness is often influenced by limited helpfulness and engagement. There is currently a scarcity of research exploring user engagement in digital mental health applications, especially in the space of artificial intelligence (AI) guided applications.

Objective:

The study’s primary objective was to analyze feedback content to understand the user’s experiences of engaging with a digital mental health app. As a secondary objective, an exploratory analysis captured the types of mental health app users.

Methods:

This study utilized a user-led approach to understanding factors for engagement and helpfulness in digital mental health by analyzing feedback (n=7,929) reported on Google Play Store about Wysa, a mental health app (1 year period). The analysis of keywords in user feedback categorized and evaluated the reported user experience into the core domains of acceptability, usability, usefulness, and integration. The study also captured key deficits and strengths of the app, and explored salient characteristics of the types of users who benefit from accessible digital mental health support.

Results:

The analysis of user feedback found the app to be overwhelmingly positively reviewed (84.4% 5-star rating). The themes of engaging exercises, interactive interface and AI-conversational ability indicated the acceptability of the app, while the non-judgementality and ease of conversation highlighted its usability. The app’s usefulness was portrayed by themes such as improvement in mental health, convenient access and cognitive restructuring exercises. Themes of Privacy and Confidentiality underscored users’ preference for the integrated aspects of the app. Further analysis revealed 4 predominant types of individuals who shared app feedback on the store.

Conclusions:

Users reported therapeutic elements of a comfortable, safe, and supportive environment through using the digital mental health app. Digital mental health apps may expand mental health access to those unable to access traditional forms of mental health support and treatments.


 Citation

Please cite as:

Malik T, Ambrose AJ, Sinha C

Evaluating User Feedback for an Artificial Intelligence–Enabled, Cognitive Behavioral Therapy–Based Mental Health App (Wysa): Qualitative Thematic Analysis

JMIR Hum Factors 2022;9(2):e35668

DOI: 10.2196/35668

PMID: 35249886

PMCID: 9044157

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