A Systematic Review of Validated Screening Tools for Anxiety Disorders and PTSD in Low to Middle Income Countries
Bibliographic record
Abstract
Abstract Background: Anxiety and post-traumatic stress disorder (PTSD) contribute significantly to disability adjusted life years in low- to middle-income countries (LMICs). Screening has been proposed to improve identification and management of these disorders, but little is known about the validity of screening tools for these disorders. We conducted a systematic review of validated screening tools for detecting anxiety and PTSD in LMICs. Methods: MEDLINE, EMBASE, Global Health and PsychINFO were searched (inception-January 10, 2019). Eligible studies (1) screened for anxiety disorders and/or PTSD; (2) reported sensitivity and specificity for a given cut-off value; (3) were conducted in LMICs; and (4) compared screening results to diagnostic classifications based on a reference standard. Screening tool, cut-off, disorder, region, country, and clinical population were extracted for each included study. We assed quality using a modified version of Greenhalgh’s ten item checklist. Accuracy results were organized based on screening tool, cut-off, and specific disorder. Accuracy estimates for the same cut-off for the same screening tool and disorder were combined via meta-analysis.ResultsOf 5343 unique citations identified, 57 articles including 75 screening tools were included. There were 44, 20 and 11 validations for anxiety, PTSD, and combined depression and anxiety, respectively. Continentally, Asia had the most validations (34). Regionally, South Asia (10) had the most validations, followed by West Asia (9) and South Africa (9). The Kessler-10 (7) and the Generalized Anxiety Disorder-7 item scale (GAD-7) (6) were the most commonly validated tools for anxiety disorders, while the Harvard Trauma Questionnaire (3) and Posttraumatic Diagnostic Scale (3) were the most commonly validated tools for PTSD. Most studies (27) had the lowest quality rating (unblinded) followed by good (21). Due to incomplete reporting, we combined only two sets of accuracy values in meta-analysis (GAD-7 cut-off ≥10; sensitivity: 76%, specificity: 64%).ConclusionUse of brief screening instruments can bring much needed attention and research opportunities to various at-risk LMIC populations, yet many have been validated in inadequately designed studies. Locally validated screening tools for anxiety and PTSD need further evaluation and well-designed studies, including clinical trials, to determine whether their use can reduce the burden of disease. PROSPERO registry number: CRD42019121794
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".