Insights Beyond Functionality: Empowering Digital Mental Health User Experiences Through Participatory Engagement and Evaluation

Ngabo-Woods, Harold

doi:10.20944/preprints202311.1572.v1

Cited by 3 publications

(1 citation statement)

References 56 publications

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“…If the app is difficult to use or lacks user-friendliness, it may deter users from completing tasks, tracking progress, or seeking help when needed, potentially impeding their recovery journey. A user-centric design that prioritizes usability can potentially enhance patient engagement, adherence to therapeutic regimens, and overall treatment outcomes 49 . Conversely, poor usability can lead to frustration, non-compliance, and even exacerbation of mental health symptoms.…”

Section: Introductionmentioning

confidence: 99%

Perspectives on Mental Health Digital Platforms: A Usability Study with Ergonomics Design Students

Ngabo-Woods

2023

Preprint

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The prevalence of mental health issues has reached alarming levels globally. In response, the integration of technology in mental health care, particularly through mental health apps, has emerged as a promising frontier for delivering scalable and accessible therapeutic interventions. However, the effectiveness of these apps is contingent upon their usability. This study explores the critical link between the usability of mental health apps and their efficacy in managing mental health symptoms. Focusing on university students, the research investigates how usability influences user experience, engagement, and adherence to mental health interventions. It also examines the role of usability in reducing barriers to seeking professional help and the variations in usability perceptions. Through a usability study of a mental health app pilot platform, this research seeks to provide actionable insights for future design and development, emphasizing the need for user-friendly interfaces that effectively support mental health outcomes. The findings aim to contribute to the broader understanding of digital mental health interventions and their role in addressing the escalating mental health crisis.

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Section: Introductionmentioning

confidence: 99%

Perspectives on Mental Health Digital Platforms: A Usability Study with Ergonomics Design Students

Ngabo-Woods

2023

Preprint

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Ethics and Transparency in Secure Web Model Generation

Sindiramutty,

Prabagaran,

Jhanjhi

et al. 2024

Advances in Information Security, Privacy, and Ethics

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The chapter discusses how ethics and transparency relate to creating secure web models for AI. AI plays a role in secure web development, and the authors consider ethics and transparency as two critical aspects of this subject, which influences users, stakeholders, or society. The examination begins with AI principles, which include fairness, accountability, and privacy requirements. They then get into the problems with secure web models. In this chapter, they break down bias and fairness concerns at the source and find ways to resolve them in web models. This relates to trust and accountability, where transparency and explainability are highlighted. They also provide case studies showing the effectiveness of transparent and explainable AI in increasing user engagement. They also delve into decision-making frameworks to help navigate the ethical dilemmas in AI web development. It then represents the conversation on the atmospherics of empowerment tools, such as monitoring and evaluation guidelines for mobilisation implementation practice and governance. To sum up, the authors underline the ethical and transparent views for us to do AI-driven web development. Therefore, they urge all stakeholders to make ethics and transparency the cornerstones of responsible webs.

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Risk Assessment and Mitigation With Generative AI Models

Sindiramutty,

Jhanjhi,

Akbar

et al. 2024

Advances in Digital Crime, Forensics, and Cyber Terrorism

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Cybersecurity organisations constantly face a risky environment where threats are present. These dangers can jeopardise information, disrupt business operations, and erode trust. Risk assessment and mitigation strategies are crucial to tackling these challenges effectively. However, traditional approaches often need help to keep pace with the changing landscape of cyber threats that require judgments based on manual analysis. This section delves into how the adoption of AI techniques, like generative adversarial networks (GANs) or variational autoencoders (VAEs), can transform risk assessment methods by simulating scenarios to identify anomalies more efficiently than ever before and predicting potential future risks in real-time through unsupervised learning methods. By integrating threat intelligence into models, the authors improve understanding of contextual factors that help identify abnormal high-risk behaviours.

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Insights Beyond Functionality: Empowering Digital Mental Health User Experiences Through Participatory Engagement and Evaluation

Cited by 3 publications

References 56 publications

Perspectives on Mental Health Digital Platforms: A Usability Study with Ergonomics Design Students

Perspectives on Mental Health Digital Platforms: A Usability Study with Ergonomics Design Students

Ethics and Transparency in Secure Web Model Generation

Risk Assessment and Mitigation With Generative AI Models

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