Suggesting a new alternative method of measuring mental disorders without the use of Paper-Pencil tests based on EEG

Publish Year: 1395
نوع سند: مقاله ژورنالی
زبان: English
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JR_INJER-3-1_007

تاریخ نمایه سازی: 22 خرداد 1400

Abstract:

Background and aims: Paper-pencil tests have always its own problems in the mental disorders evaluation, including learning questions, bad or good blazon are the problems with this methodology. This study aimed to propose a new alternative method of measuring mental disorders without paper-pencil test using EEG. Methods: The research society involved depressed patients referred the psychiatrist clinics in Tabriz. ۱۰۷ patients were selected as samples using a convenient sampling method. The Beck test was conducted. The EEG was recorded from the F۴ point concurrent with displaying the film of ۵ animated emotional images from Normed Images database (IAPS). The specialized screen of this recording was designed by the author in the Biograph Infinity software of device. Other software was written by the author in order to separate the αpeak frequency average associated with any image of the recorded EEG. Then the research variablesα۱peak , α۲peak , α۳peak , α۴peak , α۵peak of each patient were analyzed with SPSS. After all, another ۲۶ patients were selected to measure the Golden Standard, sensitivity, Positive predictability, Negative predictability and ROC. Results: The results of the multiple regression analysis showed that α۱peak associated with αpeakfrequancy of image ۱ had more explanatory power with a beta value of ۰.۲۸۹ compared with other variables. Then α۳peak had a high explanatory power. The regression equation for the predicting the score based on his/her EEG was found in terms of αpeak frequency. Discussion: This research showed that Beck's depression score was predictable without using any questionnaire but according to EEG with a high sensitivity (۱۰۰%), specificity (۳۰.۸%), PPV (۵۹.۱%), NPPV (۱۰۰%), and ROC (۵۷.۴%).  

Authors

Babak Mohammadzadeh

Psychology Dept., Tabriz University, I.R. Iran

Mehdi Khodabandelu

Psychology Dept., Tabriz University, I.R. Iran

Masoud Lotfizadeh

Social Health Determinants Research Center, Community Health Dept., Shahrekord University of Medical Sciences, Shahrekord, I.R. Iran.

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