ArticleDigital health
Personalized online intervention based on a risk algorithm for the universal prevention of anxiety disorders: Design and development of the prevANS intervention.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Application of user profiling in mental health management: a scoping review.BMC psychology · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To describe the design and development of prevANS, a personalized online intervention for the universal prevention of anxiety disorders based on a predictive risk algorithm. A user-centered approach was followed, considering the feedback of potential users and mental health professionals. Methods: The study had three phases: (a) designing the intervention based on existing scientific literature; (b) piloting and evaluating the beta version involving potential users and health professionals; and (c) refining the intervention based on participants' suggestions. This iterative process aimed to refine the prevANS intervention before testing in a randomized controlled trial. Results: The prevANS intervention provides personalized anxiety risk reports and components tailored to individuals' needs. Participants at low risk receive psychoeducation had access to a set of tools enhance protective factors. Moderate/high-risk individuals also receive cognitive-behavioral training. Both groups have access to a reward system and forum. Results from the design evaluation indicate that the prevANS interface is attractive and user-friendly and the psychoeducational materials helpful and engaging. The cognitive-behavioral training module received positive feedback. Participants suggested changes related to usability, content clarity, attractiveness, and engagement, which were implemented afterwards. Conclusions: This article describes the development of a personalized intervention for preventing anxiety disorders using a validated risk prediction algorithm. The prevANS intervention was designed based on current scientific literature by a team of experts employing a user-centered approach. Research on the effectiveness of information and communication technologies in mental health prevention interventions considering user needs and preferences is warranted.
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