Prevalence and Incidence Studies of Mood Disorders: A Systematic Review of the Literature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To present the results of a systematic review of literature published between January 1, 1980, and December 31, 2000, that reports findings on the prevalence and incidence of mood disorders in both general population and primary care settings. METHOD: We conducted a literature search of epidemiologic studies of mood disorders, using Medline and HealthSTAR databases and canvassing English-language publications. Eligible publications were restricted to studies that examined subjects aged at least 15 years and over. We used a set of predetermined inclusion and exclusion criteria to identify relevant studies. We extracted and analyzed prevalence and incidence data for heterogeneity. RESULTS: Of general population studies, a total of 18 prevalence and 5 incidence studies met eligibility criteria. We found heterogeneity across 1-year and lifetime prevalence of major depressive disorder (MDD), dysthymic disorder and bipolar I disorder. The corresponding pooled rates for 1-year prevalence were 4.1 per 100, 2.0 per 100, and 0.72 per 100, respectively. For lifetime prevalence, the corresponding pooled rates were 6.7 per 100, 3.6 per 100, and 0. per 100, respectively. Significant variation was observed among 1-year incidence rates of MDD, with a correspond ing pooled rate of 2.9 per 100. CONCLUSIONS: The prevalence of mood disorders reported in high-quality studies is generally lower than rates commonly reported in the general psychiatric literature. When controlled for common methodological confounds, variation in prevalence rates persists across studies and deserves continued study. Methodological variation among studies that have examined the prevalence of depression in primary health care services is so large that comparative analyses cannot be achieved.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it