The effectiveness, feasibility and acceptability of a data-supported treatment with the NiceDay therapy platform for mood and anxiety disorders

Objective and Scope

This research project aims to rigorously assess the effectiveness, feasibility, and acceptability of data-supported treatments provided through the NiceDay therapy platform, specifically targeting mood and anxiety disorders. The project seeks to understand how digital therapy practices and specific factors contribute to successful treatment outcomes, laying the groundwork for extensive experimental research on the NiceDay digital platform’s potential in mental health care.

Project Timeline and Funding

Start Date: To Be Confirmed (TBC)
Expected End Date: TBC
Funding: Open
Project Partners: Open

Background and Significance

Mental health issues significantly diminish individuals’ quality of life and represent a substantial societal challenge characterized by high prevalence rates and escalating economic and social costs. Despite various interventions developed over time, a notable portion of individuals remains inadequately served by traditional psychotherapy methods. Digital Mental Health Interventions (DMHIs) have emerged as a promising solution to enhance accessibility and efficacy of mental health care, leveraging technology to optimize therapeutic outcomes on a broad scale. The digitization of health services, as advocated by the European Commission Expert Panel, demands a robust evidence base to demonstrate their innovative contributions to improved care outcomes.

Innovative Treatment Approaches

The NiceDay platform’s approach to data-supported treatment includes several cutting-edge practices aimed at enriching traditional therapy methods:

Ecological Momentary Assessment (EMA): This involves the real-time collection of experiential data from clients to capture the nuanced dynamics of experiences, affect, cognition, and behavior within their natural environments.
Ecological Momentary Interventions (EMI): Building on EMA, EMI utilizes collected data to tailor interventions that clients can apply in their daily lives, enhancing the immediacy and relevance of therapeutic support.
Feedback-Informed Treatment (FIT): FIT systematically incorporates outcome measures into the treatment process, enabling ongoing adjustments to therapy based on real-time feedback.

Engagement and Future Prospects

The project team commits to regular updates on research progress and findings via the project page, fostering transparency and ongoing dialogue with interested stakeholders. We invite inquiries and potential collaborations from those interested in advancing research in digital mental health interventions.

Objectives

By evaluating the NiceDay platform’s data-supported treatments for mood and anxiety disorders, this project positions itself at the forefront of integrating technology with mental health care. The findings aim to contribute significantly to the evidence base required for the successful implementation of DMHIs, promising to revolutionize accessibility and effectiveness of mental health treatments.

Want to know more?

We will keep you updated with the developments and results of this research on the project page. Would you like to know more about research being conducted at NiceDay or are you interested in collaborating with us on this project? Do not hesitate to contact us!