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Distinguishing schizophrenic patients from healthy controls by quantitative measurement of eye movement parameters

Volker Arolt*, Hans Martin Teichert, Dietmar Steege, Resekka Lencer, Wolfgang Heide

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

Background: Eye tracking dysfunction is a putative trait marker for susceptibility to schizophrenia; however, it cannot be recommended as an additional tool for the diagnosis of schizophrenia' due to low sensitivity and specificity. Methods: To assess the diagnostic potentials of combinations of eye movement paradigms, four smooth pursuit experiments (1; constant velocity of 15°/sec; 2 and 3: combination with either visual or auditory distractors; 4: constant velocity of 30°/sec) and two saccadic eye movement experiments (1: reflexive saccades; 2: voluntary saccades) were conducted. Fourteen patients with residual schizophrenia and 17 healthy controls were studied. Two sets of discriminant analyses (each with the resubstitution and with the 'leaving one out' method) were calculated. Results: In the first set, all 10 characteristic variables were included, whereas for the second set, the three most powerful parameters were selected (two from smooth pursuit tasks and one from a voluntary saccade experiment). This procedure provided the best classification results, regarding concordance between clinical diagnoses and eye movement dysfunction (κ = .67-.80). Conclusions: Schizophrenic patients of the residual subtype can be differentiated from healthy individuals with considerable criterion validity on the basis of paradigms from two different ocular motor systems.

OriginalspracheEnglisch
ZeitschriftBiological Psychiatry
Jahrgang44
Ausgabenummer6
Seiten (von - bis)448-458
Seitenumfang11
ISSN0006-3223
DOIs
PublikationsstatusVeröffentlicht - 15.09.1998

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 3 – Gesundheit und Wohlergehen
    SDG 3 – Gesundheit und Wohlergehen
  2. SDG 10 – Weniger Ungleichheiten
    SDG 10 – Weniger Ungleichheiten

Strategische Forschungsbereiche und Zentren

  • Forschungsschwerpunkt: Gehirn, Hormone, Verhalten - Center for Brain, Behavior and Metabolism (CBBM)

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