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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Nov 25, 2022
Date Accepted: Mar 23, 2023

The final, peer-reviewed published version of this preprint can be found here:

A Computational Platform to Support the Detection, Follow-up, and Epidemiological Surveillance of Mental Health and Substance Use Disorders: Protocol for a Development and Evaluation Study

Martínez-Miranda J, Meza M, Silva-Peña C, Mercado Rivas MX, Figueroa-Vela MdR, Sánchez Aranda ML

A Computational Platform to Support the Detection, Follow-up, and Epidemiological Surveillance of Mental Health and Substance Use Disorders: Protocol for a Development and Evaluation Study

JMIR Res Protoc 2023;12:e44607

DOI: 10.2196/44607

PMID: 37097718

PMCID: 10170360

A Computational Platform to Support the Detection, Follow-up and Epidemiological Surveillance of Mental Health and Substance Use Disorders: Development and Evaluation Protocol

  • Juan Martínez-Miranda; 
  • Martha Meza; 
  • Cándido Silva-Peña; 
  • Martha Xitlali Mercado Rivas; 
  • Ma. del Rocío Figueroa-Vela; 
  • Magda Lidiana Sánchez Aranda

ABSTRACT

Background:

The World Health Organization estimates that 15% of the world's population presents a mental health or substance use disorder. Health problems associated with these disorders constitute a relevant percentage of the global disease burden, which has worsened due to the direct and indirect effects of COVID-19. In Mexico, one-fourth of the population aged 18-65 and residents in urban areas present a mental health condition. The presence of a mental or substance abuse disorder is behind a significant percentage of suicidal behaviours in Mexico, where only one in five of those who suffer from these disorders receive any treatment.

Objective:

This study aims to develop, deploy and evaluate a computational platform to support the early detection and intervention of mental and substance use disorders at the scholarly community level and in primary care units to facilitate monitoring, treatment, and epidemiological surveillance at the second level of care.

Methods:

The development and evaluation of the proposed computational platform will run during three stages. In the first stage, the identification of the functional and user requirements and the implementation of the modules to support the screening, follow-up, treatment, and epidemiological surveillance will be performed. In stage 2, the initial deployment of the screening module will be carried out in a set of secondary and high schools, as well as the deployment of the modules to support the follow-up, treatment and epidemiological surveillance processes in primary and secondary care health units. In parallel, during stage 2, the development of patient applications to support early interventions and continuous monitoring will also be developed. Finally, during stage 3, the deployment of the complete platform will be performed jointly with a quantitative and qualitative evaluation.

Results:

This study has been funded by the Mexican National Council for Science and Technology (CONACyT), and the first stage started in July 2021. The complete development, deployment and evaluation are expected to be completed by 2024.

Conclusions:

The expected results of this study are to impact a better integration between the different levels of health care, from early detection to follow-up and epidemiological surveillance of mental and substance use disorders contributing to reducing the gap in the attention to these problems in the community.


 Citation

Please cite as:

Martínez-Miranda J, Meza M, Silva-Peña C, Mercado Rivas MX, Figueroa-Vela MdR, Sánchez Aranda ML

A Computational Platform to Support the Detection, Follow-up, and Epidemiological Surveillance of Mental Health and Substance Use Disorders: Protocol for a Development and Evaluation Study

JMIR Res Protoc 2023;12:e44607

DOI: 10.2196/44607

PMID: 37097718

PMCID: 10170360

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