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Best Estimate of Lifetime Psychiatric Diagnosis: A Methodological Study
Abstract
It is important for genetic, epidemiologic, and nosological studies to determine accurate rates of lifetime psychiatric diagnoses in patient and nonpatient populations. As part of a case-control family study of major depression, lifetime psychiatric diagnoses were made for 1,878 individuals. Sources of information used in making diagnostic estimates included direct interview, medical records, and family history data systematically obtained from relatives. Diagnostic estimates were made by trained interviewers, experienced clinicians, and by computer program. The results indicate that it is possible to make lifetime best estimate diagnoses reliably among both interviewed and noninterviewed individuals for most diagnostic categories and that diagnoses based on interview data alone are an adequate substitute for best estimate diagnoses based on all available information in a limited number of diagnostic categories.
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Metadata
- Authors
- Leckman, J. F.
- Venue
- Archives of General Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 1982-08-01
- Volume
- 39
- Issue
- 8
- Pages
- 879
- ISSN
- 0003-990X (ISSN-L)
- OpenAlex
- W2063473805
- Cited by
- 1,425
- References
- 0
- FWCI
- 19.11
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.