Is there a mental health diagnostic crisis in primary care? Current research practices in global mental health cannot answer that question
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...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2025-01-01
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| Series: | Epidemiology and Psychiatric Sciences |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2045796025000010/type/journal_article |
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| Summary: | 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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| ISSN: | 2045-7960 2045-7979 |