Developing a Digital Mental Health Ecosystem for Workplaces: Rationale, Objectives, and Methods of the MetrikaMind Project

Background: Depression and anxiety are among the leading causes of disability worldwide, significantly impacting workplace productivity through absenteeism and presenteeism. The MetrikaMind platform offers a scalable, digital solution for addressing these challenges by providing personalized, AI-driven mental health assessments and real-time monitoring in workplace settings. Methods: This one-arm pre-post study will recruit 1,000 participants from the general population and 600 participants from a sick leave population in Spain. The primary outcomes will assess changes in depression and anxiety symptoms using validated tools, with weekly assessments for up to 6 months. Secondary outcomes include measures of personality, workplace engagement, and perceived occupational stress, alongside platform engagement metrics. Data will be analyzed using bifactor models to account for response biases such as social desirability and to predict mental health outcomes more accurately. Ethics: The study complies with the Declaration of Helsinki and Oviedo Convention. Informed consent will be obtained, and data confidentiality will follow GDPR standards. The protocol has been approved by the Institutional Review Board (IRB 00003099). Discussion: MetrikaMind is expected to improve the accuracy of mental health assessments in the workplace, reducing response biases and enabling earlier detection of changes in anxiety and depression symptoms. The platform's predictive capabilities may also lead to innovations in workplace mental health policies and interventions. This project has the potential to improve employee well-being and workplace productivity by offering precise, real-time mental health assessments. The platform's integration of active and passive data sources enhances its ability to provide tailored, effective support, setting the foundation for future digital mental health innovations. Trial Registration: ClinicalTrials.gov Identifier: NCT06650176