title: A note on relevance of diagnostic classification and rating scales used in psychiatry.
abstract: In the clinical practice of psychology and psychiatry, presence or absence of particular disorder or syndromes is based on the subjective interpretation of mental and behavioral descriptions offered by the patient. This is often done by questionnaires (also called instruments or scales) or by interviews. This subjectivity of the diagnostic decision-making process may limit the reliability of diagnosis. In the present study, a new method of scale relevance, based on double cluster analysis, is proposed as it is important to verify what we are trying to find with the proposed scale. If two data sets cluster differently, we must consider them as different.
authors.affiliation: Peking University, China.
authors.forename: Yiqun
authors.initials: Y
authors.lastname: Gan
authors.forename: Tamar
authors.initials: T
authors.lastname: Kakiashvili
authors.forename: Waldemar W
authors.initials: WW
authors.lastname: Koczkodaj
authors.forename: Feng
authors.initials: F
authors.lastname: Li
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D016000:Cluster Analysis; D016208:Databases, Factual / Q000706:statistics & numerical data; D003936:Diagnosis, Computer-Assisted / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D001523:Mental Disorders / Q000145:classification* / Q000175:diagnosis*; D008875:Middle Aged; D011569:Psychiatric Status Rating Scales / Q000706:statistics & numerical data*; D011570:Psychiatry / Q000706:statistics & numerical data*; D055815:Young Adult
keywords: Cluster analysis; Machine learning; Relevance; Scale; Unsupervised learning