Journal article
Psychiatric Diagnostic Discriminations with Combinations of Quantitative EEG Variables
British journal of psychiatry, v 144(6), pp 581-592
Jun 1984
PMID: 6743925
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The possible psychiatric diagnostic utility of certain quantitative EEG measures was evaluated by further analysis of previously reported data from 242 unmedicated patients and 94 non-patients. Time series of amplitude, frequency and wave symmetry measures for 12-lead EEGs (eyes closed and open) were factor analyzed across leads. Factor scores meeting specified criteria in multivariate analyses were entered into discriminant analyses comparing pairs of the following groups: non-patients, neurotics, personality disorders, overt schizophrenics, latent schizophrenics, major depressives and manics. The following discriminations were obtained with at least 50 per cent sensitivity, and diagnostic confidence rates from 69 to 92 per cent: (a) non-psychotic patients (neuroses, personality disorders) from overt schizophrenics, latent schizophrenics or manics; (b) major depressives from latent schizophrenics or manics; (c) non-patients from schizophrenics (overt and latent), depressives or manics. Most discriminations were replicable in split-half analyses. Possible utility of EEG measures in differential diagnosis is supported.
Metrics
Details
- Title
- Psychiatric Diagnostic Discriminations with Combinations of Quantitative EEG Variables
- Creators
- Charles Shagass - Temple UniversityRichard A. Roemer - Temple UniversityJohn J. Straumanis - Temple UniversityRichard C. Josiassen - Temple University
- Publication Details
- British journal of psychiatry, v 144(6), pp 581-592
- Publisher
- Cambridge University Press
- Number of pages
- 12
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychiatry
- Web of Science ID
- WOS:A1984SX42800003
- Scopus ID
- 2-s2.0-0021154356
- Other Identifier
- 991021889905504721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Psychiatry