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. 2023 Apr 25:12:e44607.
doi: 10.2196/44607.

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

Juan Martínez-Miranda #  1 , Martha Janet Meza Magallanes #  2 , Cándido Silva-Peña #  3 , Martha Xitlali Mercado Rivas #  4 , María Del Rocío Figueroa-Varela #  3 , Magda Lidiana Sánchez Aranda #  3
Affiliations

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

Juan Martínez-Miranda et al. JMIR Res Protoc. .

Abstract

Background: According to the World Health Organization, approximately 15% of the global population is affected by mental health or substance use disorders. These conditions contribute significantly to the global disease burden, which has worsened because of the direct and indirect effects of COVID-19. In Mexico, a quarter of the population between the ages of 18 and 65 years who reside in urban areas present a mental health condition. The presence of a mental or substance abuse disorder is behind a significant percentage of suicidal behaviors in Mexico, where only 1 in 5 of those who have 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 in secondary and high schools as well as primary care units. The platform also aims to facilitate monitoring, treatment, and epidemiological surveillance ultimately helping specialized health units at the secondary level of care.

Methods: The development and evaluation of the proposed computational platform will run during 3 stages. In stage 1, 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, 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: The screening process has started, and 6 schools have been currently enrolled. As of February 2023, a total of 1501 students have undergone screening, and the referral of those students presenting a risk in mental health or substance use to primary care units has also started. The development, deployment, and evaluation of all the modules of the proposed platform are expected to be completed by late 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.

International registered report identifier (irrid): DERR1-10.2196/44607.

Keywords: IVDU; addict; addiction; computational platform; digital screening; epidemiological surveillance; intravenous drug; level of health care; mHealth; mental health; mental health and addiction; opioid; substance abuse; substance use; substance use disorder; suicidal behavior.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Functional architecture of the computational platform.
Figure 2
Figure 2
Overview of the work packages defined for the development of the computational platform. WP: work package.
See this image and copyright information in PMC

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