Analysis of the Effects of Smoking Desire and Self-Efficacy on Nicotine Use Levels During the Covid-19 Pandemic Period Using Machine Learning Techniques

In March 2020, when the first COVID-19 case was reported in Turkey, some regulations as minimum physical contact, staying at home, closed schools, and unstable working systems became a part of our lives. With these accusatory changes in lifestyle, it has become difficult for people to cope with this period. In this study, the effect of self-efficacy and desire to smoke on nicotine addiction during the COVID-19 pandemic was analyzed and classified by machine learning methods. Among the classification algorithms used, classification was made with a random forest classifier with an accuracy of 71.4%.