Advancing Mental Health Research in Low-Resource Settings: Data, Measurement, and Emerging Approaches
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Behavioral and Mental Health".
Deadline for manuscript submissions: 1 May 2027 | Viewed by 134
Special Issue Editor
Special Issue Information
Dear Colleagues,
Mental health conditions are among the leading global contributors to disability worldwide, with substantial and persistent gaps in understanding their distribution, determinants, and trajectories, particularly in low-resource settings, limiting comparability, validity, and translation of findings.
This Special Issue invites original research, systematic reviews, and methodological contributions that advance mental health research through innovative data sources and analytical approaches. We welcome studies leveraging longitudinal cohorts, daily diaries, geospatial data, biomarkers, and digital tools to better characterize mental health risks, resilience, and contextual influences. Contributions may include emerging approaches such as artificial intelligence and machine learning, but should also encompass broader methodological innovations that improve measurement, analysis, and interpretation.
Priority areas include: (1) novel data collection strategies and measurement of mental health in low-resource settings; (2) longitudinal and multilevel analyses of mental health trajectories; (3) integration of environmental, social, and structural exposures; (4) methodological advances, including AI and data-driven approaches; and (5) mixed-methods and community-engaged research that enhances contextual understanding.
We particularly encourage submissions grounded in low-resource settings and real-world contexts. Contributions that emphasize rigorous epidemiologic design, innovative measurement, and contextually grounded insights are especially welcome. Submissions focused solely on clinical interventions or service delivery without a clear data, measurement, or methodological contribution are less aligned with the aims of this Special Issue.
By centering data, measurement, and methodological innovation, this Special Issue aims to strengthen the evidence base for understanding mental health in underrepresented populations and to advance more contextually grounded and scientifically robust research.
Prof. Dr. Monica Swahn
Guest Editor
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- mental health
- low-resource settings
- data science
- measurement
- epidemiology
- longitudinal research
- environmental exposures
- mixed methods
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