An Artificial Neural Networks Approach for Psychometric Assessment of Stress, Anxiety, and Depression in Women
DOI:
https://doi.org/10.58575/3784k278Keywords:
Anxiety, Artificial Neural Network, Depression, Illness, StressAbstract
This study was carried out to classify, and predict the presence and absence of illness among women of Wazirabad city based on stress, anxiety, and depression. A questionnaire of Depression, Anxiety and Stress Scale (DASS-21) was used to collect data. Two-stage cluster sampling was used, and size of sample was 334. In this study, 57 respondents were those who were suffering some illness whereas 277 respondents were those who reported the absence of illness. Results showed that 87.7%, 56%, and 49% cases of illness were with moderate and above levels of anxiety, stress, and depression respectively. The findings of the research supported the significant relationship of demographic variables and psychological factors with illness. Artificial Neural Network technique was used to assess the classification and prediction, and our model showed good classification in both categories of illness. Overall, correctly classified illness in women was 89.4%. Anxiety level was more contributory factor to perceive the illness in women among all the independent variables. Our model predicted that there is 94% chance of presence of illness within a woman, having extremely severe level of anxiety, and moderate levels of stress and depression.
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