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METRIKAMIND - Development of a Digital Mental Health Ecosystem for Workplace Environments

NCT06650176 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 400

Last updated 2025-03-27

No results posted yet for this study

Summary

The goal of this observational study is to develop and validate a digital ecosystem designed to assess and manage mental health in workplace environments. The primary purpose is to understand how digital tools can contribute to better mental health management and to gauge their effectiveness in a typical work setting. The study also aims to enhance the prediction of mental health outcomes and the course of mental health conditions through more accurate assessments. The main questions it aims to answer are:

1. How do digital assessments improve the detection and management of mental health issues like depression and anxiety in the workplace?
2. Can a digital ecosystem effectively reduce the overall cost and impact of mental health issues on productivity and employee well-being?
3. How effective are bifactor models in detecting and mitigating the impact of faking in self-reported mental health assessments in occupational settings?

Participants will:

1. Engage with the Metrikamind platform to complete periodic mental health assessments.
2. Provide feedback on their experience and any changes in their mental health status, with particular attention to the accuracy and honesty of self-reported data facilitated by the implementation of bifactor models.
3. Participate in follow-up surveys to gauge long-term effects of using the digital tools on their mental health and workplace productivity.

This study involves adult participants currently employed in various sectors undergoing a sick leave, who will use the Metrikamind platform over a six-month period. The research aims to collect data on the usability and effectiveness of the platform, analyzing changes in participants\' mental health through their interaction with the digital tools provided. By incorporating advanced psychometric techniques like bifactor models, the study seeks to enhance the reliability of data and improve the prediction of mental health outcomes, providing a solid foundation for potential wider application in corporate health strategies.

Conditions

Interventions

BEHAVIORAL

Lifestyle Management

The Metrikamind intervention features a unique digital ecosystem designed to manage mental health specifically in workplace contexts, with a focus on aiding recovery and facilitating the return to work for employees on sick leave. This innovative tool employs bifactor models to enhance the accuracy of self-reported data, effectively countering potential faking behaviors. Through continuous, real-time data collection on a user-friendly platform, Metrikamind tracks and assesses various mental health conditions, including stress, anxiety, and depression. The intervention\'s advanced analytics enable personalized feedback and targeted interventions, improving the detection, management, and ultimately, the mitigation of mental health issues. By focusing on individuals currently unable to work due to mental health challenges, Metrikamind aims to support their recovery and accelerate their readiness to return to work, thus addressing both immediate and long-term recovery trajectories.

Sponsors & Collaborators

  • David Gallardo-Pujol

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
70 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-09-30
Primary Completion
2026-04-30
Completion
2026-04-30

Countries

  • Spain

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06650176 on ClinicalTrials.gov