Abstract:
:The present study is aimed at identifying the most prominent determinants of OCD along with their strength to classify the OCD patients from healthy controls. The data for this cross-sectional study were collected from 200 diagnosed OCD patients and 400 healthy controls. The respondents were selected through purposive sampling and interviewed by using the Y-BOCS scale with the addition of a factor, worth of an individual in his family. The validity and reliability of data were assessed through Cronbach's alpha and confirmatory factor analysis. Artificial Neural Network (ANN) modeling was adopted to determine threatening determinants along with their strength to predict OCD in an individual. The results of ANN modeling depicted 98% accurate classification of OCD patients from healthy controls. The most contributing factors in determining the OCD patients according to normalized importance were the contamination and cleaning (100%); symmetric and perfection (72.5%); worth of an individual in the family (71.1%); aggressive, religious, and sexual obsession (50.5%); high-risk assessment (46.0%); and somatic obsessions and checking (24.0%).
journal_name
Behav Neuroljournal_title
Behavioural neurologyauthors
Shahzad MN,Suleman M,Ahmed MA,Riaz A,Fatima Kdoi
10.1155/2020/2678718subject
Has Abstractpub_date
2020-06-22 00:00:00pages
2678718eissn
0953-4180issn
1875-8584journal_volume
2020pub_type
杂志文章abstract::We report a case of a blind woman, M.N., who experienced the Capgras delusion. She thought that her pet cat had been replaced by a replica which was "ill-intentioned" towards her. M.N.'s case shows that the basis of the Capgras delusion cannot lie exclusively in damage to the visual system. However, testing of M.N.'s ...
journal_title:Behavioural neurology
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