ReviewGlobal mental health (Cambridge, England)2023
Opportunities for improving data sharing and FAIR data practices to advance global mental health.
Review in Global mental health (Cambridge, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Building the framework for ongoing discovery: coding practice elements in child traumatic stress intervention studies.European journal of psychotraumatology · 2026Article
- Pooling data from studies on prolonged grief: the Multi-region Archive of Research data on Bereavement and Loss from Empirical Studies (MARBLES) project.European journal of psychotraumatology · 2026Article
- Reconciling global collaboration and data sovereignty in neuroscience.Nature neuroscience · 2026Review
- Advancing PTSD-Substance Use Comorbidity Treatment Research Through Applying FAIR and FACT Data Science Frameworks inJournal of studies on alcohol and drugs · 2026Article
- Analyzing transdiagnostic internalizing symptoms in a global sample of trauma-exposed children using pooled individual participant data: a latent transition analysis.Journal of child psychology and psychiatry, and allied disciplines · 2026Article
- A maturity model framework for federated networks of trusted research environments.Frontiers in digital health · 2026Article
- Lessons learned from implementing FAIRification workflows in diabetes research in Germany.PLOS digital health · 2026Article
- Sharing traumatic stress research data: assessing and reducing the risk of re-identification.European journal of psychotraumatology · 2025Review
- A FAIR intensive longitudinal data archive on prolonged grief in daily life.European journal of psychotraumatology · 2025Article
- Mental health in the moment: protocol for an accelerated cohort measurement burst study of adolescent mental health.BMJ open · 2025Article
- Advances, challenges, and future directions in trauma-related Findable, Accessible, Interoperable, Reusable (FAIR) data efforts.Journal of traumatic stress · 2025Review
- Understanding Individual Differences in Happiness Sources and Implications for Health Technology Design: Exploratory Analysis of an Open Dataset.JMIR formative research · 2025Article
- Implementing Findable, Accessible, Interoperable, Reusable (FAIR) Principles in Child and Adolescent Mental Health Research: Mixed Methods Approach.JMIR mental health · 2024Article
- Erratum: Opportunities for improving data sharing and FAIR data practices to advance global mental health-Corrigendum.Global mental health (Cambridge, England) · 2023Article
- Data sharing and re-use in the traumatic stress field: An international survey of trauma researchers.European journal of psychotraumatology · 2023Article
- Review
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is crucial to optimize global mental health research to address the high burden of mental health challenges and mental illness for individuals and societies. Data sharing and reuse have demonstrated value for advancing science and accelerating knowledge development. The FAIR (Findable, Accessible, Interoperable, and Reusable) Guiding Principles for scientific data provide a framework to improve the transparency, efficiency, and impact of research. In this review, we describe ethical and equity considerations in data sharing and reuse, delineate the FAIR principles as they apply to mental health research, and consider the current state of FAIR data practices in global mental health research, identifying challenges and opportunities. We describe noteworthy examples of collaborative efforts, often across disciplinary and national boundaries, to improve Findability and Accessibility of global mental health data, as well as efforts to create integrated data resources and tools that improve Interoperability and Reusability. Based on this review, we suggest a vision for the future of FAIR global mental health research and suggest practical steps for researchers with regard to study planning, data preservation and indexing, machine-actionable metadata, data reuse to advance science and improve equity, metrics and recognition.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.