Development of a Mental Health Apps Recommender Platform

Area of Science:

• Digital Health
• Mental Healthcare Technology
• Health Informatics

Background:

• The increasing demand for mental health services necessitates innovative solutions for patient support.
• Patients often experience delays in accessing formal mental health treatment, leading to a need for effective self-management tools.

Purpose of the Study:

• To define the requirements and methodology for creating a recommender system for mental health applications.
• To support patients in self-managing their mental health conditions during treatment waiting periods.

Main Methods:

• A user-centered design approach was employed, involving literature reviews and stakeholder interviews.
• Software modeling and prototype development were conducted.
• The prototype underwent rigorous testing with health experts and end-users.

Main Results:

• A curated library of trusted mental health apps was established based on user requirements, standards, and regulations.
• A recommendation engine was developed to create user profiles and deliver personalized health suggestions.
• The system is undergoing further testing to ensure the quality and reliability of recommendations.

Conclusions:

• Developing a robust mental health recommender system requires clear requirements and a methodology addressing data security, confidentiality, safety, and reliability.
• Future research should evaluate the system's impact on mental health outcomes and user well-being to guide further improvements.