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24 April 2024 |
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Article overview
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An effective rating scale item reduction procedure | | W.W. Koczkodaj. T. Kakiashvili
; J. Montero-Marin
; R. Araya
; J. Garcia-Campayo
; K. Rutkowski
; J.Szybowski
; A. Szymanska
; | | Date: |
8 May 2015 | | Abstract: | The main goal of this study is to reduce the number of items with the
condition that the scale predictability is at least as good as of the original
version of the rating scale. Background: rating scales play important an role
in all kinds of psychological and psychiatric assessments. They are of
considerable importance for screening [Kim study in Korea]. BDI is one of the
most popular psychiatric scales for the major depression. It is consistent with
DSM IV, the Diagnostic and Statistical Manual of Mental Disorders (DSM) by the
American Psychiatric Association and ICD-11, a medical classification list by
the World Health Organization (WHO) as the diagnostic procedures for major
depression diagnosis. Method: A model has been proposed to improve computing
the subset of a rating scale by the "area under the receiver operator curve
method." The obtained results have been verified by GLM (generalized linear
model) method with is better known in statistics but does not provide the
proper sequence as our method does. Results: The commonly used Beck Depression
Inventory (BDI) has been used as a presentation case. The major achievement is
the reduction of variables from 21 to 6 with the increased data predictability
predictability. Conclusions: Our proposed method provides clinicians with a
method of reducing the data collection by approximately 300\%. Not only does it
save time but increases the scale predictability which is of considerable
importance, especially if the rating scale is used for screening since even a
small difference may "miss the boat" and (in case of autism) contribute to
suffering. | | Source: | arXiv, 1505.1886 | | Services: | Forum | Review | PDF | Favorites | |
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