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%).

In this study, an effort is made to classify the significant aspect of mismatch between education and job among graduates. The exactness of the equivalent between employee's abilities, talents, skills and those demanded by the institutes, rarely tackled in the literature. Freeman was the former who elevated his apprehensions above this extension in his study named 'Overeducated Americans'. The data of 220 respondents collected from the administrative staff, lab assistants from the University of Gujrat using well-structured questionnaire. The Multilayer Perceptron Neural Network technique has been used for analysis purpose. Results revealed that overall correct classification is almost 100% on the basis of limited resources, family responsibility, Family forced, job advertisement and distance from work.