Prediction of Individuals' Religious Coping Levels in the Coronavirus (Covid-19) Process by Using Artificial Neural Networks

In this study, it is aimed to develop a model that predicts religious coping with the data that include age, gender, marital status, educational status, monthly income, place of residence, occupation, chronic disease status of individuals, number of family members, access to computer and internet, loneliness and the meaning of life during the coronavirus (Covid-19) pandemic. The study group of this research includes individuals in the 2020 Covid-19 process. The research was carried out on 783 individuals on a random sampling basis. The data were obtained through the demographic information form developed by the researcher. In the study, it was created a prediction model developed by Artificial Neural Networks method, which includes 15 variables including 14 variable inputs and 2 sub-dimensions 1 output. While the development of the model was carried out by using the age, gender, marital status, educational status, monthly income, place of residence, occupation, chronic disease status of the individuals, number of family members, computer and internet access, loneliness and meaning of life, religious coping situations were estimated by the newly developed model. The predicted and observed results obtained were verified and compared. According to the findings, it was seen that the predicted positivenegative religious coping situations were significantly similar to the observed positive-negative religious coping classification.