Treatment gap for anxiety disorders is global: Results of the World Mental Health Surveys in 21 countries
Bibliographic record
Abstract
BACKGROUND: Anxiety disorders are a major cause of burden of disease. Treatment gaps have been described, but a worldwide evaluation is lacking. We estimated, among individuals with a 12-month DSM-IV (where DSM is Diagnostic Statistical Manual) anxiety disorder in 21 countries, the proportion who (i) perceived a need for treatment; (ii) received any treatment; and (iii) received possibly adequate treatment. METHODS: Data from 23 community surveys in 21 countries of the World Mental Health (WMH) surveys. DSM-IV mental disorders were assessed (WHO Composite International Diagnostic Interview, CIDI 3.0). DSM-IV included posttraumatic stress disorder among anxiety disorders, while it is not considered so in the DSM-5. We asked if, in the previous 12 months, respondents felt they needed professional treatment and if they obtained professional treatment (specialized/general medical, complementary alternative medical, or nonmedical professional) for "problems with emotions, nerves, mental health, or use of alcohol or drugs." Possibly adequate treatment was defined as receiving pharmacotherapy (1+ months of medication and 4+ visits to a medical doctor) or psychotherapy, complementary alternative medicine or nonmedical care (8+ visits). RESULTS: Of 51,547 respondents (response = 71.3%), 9.8% had a 12-month DSM-IV anxiety disorder, 27.6% of whom received any treatment, and only 9.8% received possibly adequate treatment. Of those with 12-month anxiety only 41.3% perceived a need for care. Lower treatment levels were found for lower income countries. CONCLUSIONS: Low levels of service use and a high proportion of those receiving services not meeting adequacy standards for anxiety disorders exist worldwide. Results suggest the need for improving recognition of anxiety disorders and the quality of treatment.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".