AI Article Synopsis
- The diagnosis of mental disorders in psychology and psychiatry often relies on the subjective interpretations of patient descriptions, using tools like questionnaires and interviews.
- The subjectivity in this process can hinder the reliability of diagnoses.
- The study proposes a new method using double cluster analysis to improve diagnostic accuracy by ensuring that different data sets that cluster differently are recognized as distinct.
Article 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.
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| http://dx.doi.org/10.1016/j.cmpb.2013.05.016 | DOI Listing |
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