Prevalence and Incidence Studies of Anxiety Disorders: A Systematic Review of the Literature
Bibliographic record
Abstract
OBJECTIVE: To present the results of a systematic review of literature published between 1980 and 2004 reporting findings of the prevalence and incidence of anxiety disorders in the general population. METHOD: A literature search of epidemiologic studies of anxiety disorders was conducted, using Medline and HealthSTAR databases, canvassing English-language publications. Eligible publications were restricted to studies that examined age ranges covering the adult population. A set of predetermined inclusion and exclusion criteria were used to identify relevant studies. Prevalence and incidence data were extracted and analyzed for heterogeneity. RESULTS: A total of 41 prevalence and 5 incidence studies met eligibility criteria. We found heterogeneity across 1-year and lifetime prevalence rates of all anxiety disorder categories. Pooled 1-year and lifetime prevalence rates for total anxiety disorders were 10.6% and 16.6%. Pooled rates for individual disorders varied widely. Women had generally higher prevalence rates across all anxiety disorder categories, compared with men, but the magnitude of this difference varied. CONCLUSION: The international prevalence of anxiety disorders varies greatly between published epidemiologic reports. The variability associated with all anxiety disorders is considerably smaller than the variability associated with individual disorders. Women report higher rates of anxiety disorders than men. Several factors were found to be associated with heterogeneity among rates, including diagnostic criteria, diagnostic instrument, sample size, country studied, and response rate.
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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 | 0.013 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.023 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".