ArticleEpidemiology and psychiatric sciences2025
Is there a mental health diagnostic crisis in primary care? Current research practices in global mental health cannot answer that question.
Article in Epidemiology and psychiatric sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- An App-Based WHO Mental Health Guide for Depression Detection: A Cluster Randomized Clinical Trial.JAMA network open · 2025Trial
- Understanding the nature-wellbeing relationship in adults: a qualitative metasynthesis review.Wellbeing, space and society · 2026Review
- Tools used to estimate the prevalence of generalized anxiety disorder in populations: a scoping review.Epidemiology and psychiatric sciences · 2026Article
- Breaking down barriers: A qualitative study of demand- and supply-side barriers to depression care in Nepal.Global mental health (Cambridge, England) · 2026Article
- Recognition of depression by nurses in primary healthcare in Zimbabwe: Cross-sectional study.Global mental health (Cambridge, England) · 2026Article
- Recruitment strategies and participant motivations in a digital randomized controlled trial for the prevention of anxiety disorders: the prevANS study.Frontiers in digital health · 2026Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
In low- and middle-income countries, fewer than 1 in 10 people with mental health conditions are estimated to be accurately diagnosed in primary care. This is despite more than 90 countries providing mental health training for primary healthcare workers in the past two decades. The lack of accurate diagnoses is a major bottleneck to reducing the global mental health treatment gap. In this commentary, we argue that current research practices are insufficient to generate the evidence needed to improve diagnostic accuracy. Research studies commonly determine accurate diagnosis by relying on self-report tools such as the Patient Health Questionnaire-9. This is problematic because self-report tools often overestimate prevalence, primarily due to their high rates of false positives. Moreover, nearly all studies on detection focus solely on depression, not taking into account the spectrum of conditions on which primary healthcare workers are being trained. Single condition self-report tools fail to discriminate among different types of mental health conditions, leading to a heterogeneous group of conditions masked under a single scale. As an alternative path forward, we propose improving research on diagnostic accuracy to better evaluate the reach of mental health service delivery in primary care. We recommend evaluating multiple conditions, statistically adjusting prevalence estimates generated from self-report tools, and consistently using structured clinical interviews as a gold standard. We propose clinically meaningful detection as 'good-enough' diagnoses incorporating multiple conditions accounting for context, health system and types of interventions available. Clinically meaningful identification can be operationalized differently across settings based on what level of diagnostic specificity is needed to select from available treatments. Rethinking research strategies to evaluate accuracy of diagnosis is vital to improve training, supervision and delivery of mental health services around the world.
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