Ali, GC, Ryan, G and De Silva, MJ. 2016. Validated Screening Tools for Common Mental Disorders in Low and Middle Income Countries: A Systematic Review. [Online]. Figshare. Available from: https://doi.org/10.1371/journal.pone.0156939.
Ali, GC, Ryan, G and De Silva, MJ. Validated Screening Tools for Common Mental Disorders in Low and Middle Income Countries: A Systematic Review. [Internet] LSHTM Data Compass. Figshare; 2016. Available from: https://doi.org/10.1371/journal.pone.0156939.
Ali, GC, Ryan, G and De Silva, MJ (2016). Validated Screening Tools for Common Mental Disorders in Low and Middle Income Countries: A Systematic Review. [Data Collection]. Figshare. https://doi.org/10.1371/journal.pone.0156939.
Description
A wide range of screening tools are available to detect common mental disorders (CMDs), but few have been specifically developed for populations in low and middle income countries (LMIC). Cross-cultural application of a screening tool requires that its validity be assessed against a gold standard diagnostic interview. Validation studies of brief CMD screening tools have been conducted in several LMIC, but until now there has been no review of screening tools for all CMDs across all LMIC populations. A systematic review with broad inclusion criteria was conducted, producing a comprehensive summary of brief CMD screening tools validated for use in LMIC populations. For each validation, the diagnostic odds ratio (DOR) was calculated as an easily comparable measure of screening tool validity. Average DOR results weighted by sample size were calculated for each screening tool, enabling us to make broad recommendations about best performing screening tools. 153 studies fulfilled our inclusion criteria. Because many studies validated two or more screening tools, this corresponded to 273 separate validations against gold standard diagnostic criteria. We found that the validity of every screening tool tested in multiple settings and populations varied between studies, highlighting the importance of local validation. Many of the best performing tools were purposely developed for a specific population; however, as these tools have only been validated in one study, it is not possible to draw broader conclusions about their applicability in other contexts. Of the tools that have been validated in multiple settings, the authors broadly recommend using the SRQ-20 to screen for general CMDs, the GHQ-12 for CMDs in populations with physical illness, the HADS-D for depressive disorders, the PHQ-9 for depressive disorders in populations with good literacy levels, the EPDS for perinatal depressive disorders, and the HADS-A for anxiety disorders. We recommend that, wherever possible, a chosen screening tool should be validated against a gold standard diagnostic assessment in the specific context in which it will be employed.
Data capture method | Compilation/Synthesis | ||||
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Data Collection Period |
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Date (Published in a 3rd party system) | 16 June 2016 | ||||
Language(s) of written materials | English |
Data Creators | Ali, GC, Ryan, G and De Silva, MJ |
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LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Population Health (2012- ) |
Participating Institutions | University of Cambridge, London School of Hygiene & Tropical Medicine, Wellcome Trust, Centre for Global Mental Health |
Funders |
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Depositor | Gareth Knight |
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Date Deposited | 21 Jun 2016 19:58 |
Last Modified | 08 Nov 2018 17:56 |
Publisher | Figshare |
Downloads
Data
Filename: S1_Results_Database.XLSX
Description: Complete database of results extracted from the included studies
Content type: Dataset
File size: 59kB
Mime-Type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
Filename: S2_Included_Studies.DOCX
Description: Basic characteristics and references for all included studies
Content type: Dataset
File size: 268kB
Mime-Type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
Filename: S3_Quality_Appraisal.XLSX
Description: Quality criteria met and missed by each of the included studies
Content type: Dataset
File size: 16kB
Mime-Type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
Filename: S4_Screening_Tool_Acronyms.DOCX
Description: Acronyms for all screening tools listed in the results database
Content type: Dataset
File size: 17kB
Mime-Type: application/vnd.openxmlformats-officedocument.wordprocessingml.document