| چکیده انگلیسی مقاله |
Objective: The coronavirus pandemic has presented a significant challenge and brought about dramatic changes for universities and their students. This study aimed to evaluate machine learning algorithms for estimating COVID-19 stress levels among Iranian university students.
Methods: We conducted an online survey from May 10th to November 20th, 2021, to determine how Iranian university students responded to the COVID-19 outbreak in Iran. The survey invitations were sent to Iranian university students via e-mail, forums, and social media platforms, such as internet advertisements. We collected data from 3,490 university students, using sociodemographic characteristics and the COVID-19 Stress Scale (CSS; Nooripour et al. (2022)). The statistical methods used for data analysis in this paper include the Adaptive Neuro-Fuzzy Inference System (ANFIS) network for prediction and fuzzy logic-based rules. For classification, eight machine learning algorithms were employed: Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest, Multilayer Perceptron, Decision Tree, and Passive-Aggressive algorithm. These algorithms were selected based on their principles and suitability for stress detection in the desired category.
Results: Among the algorithms, the decision tree algorithm showed the best performance in accurately classifying the data into the correct stress intensity categories. Moreover, analysis revealed that gender, age group, and education significantly influenced stress intensity levels, with men experiencing less stress, stress intensity decreasing with age, and higher education being associated with lower stress levels. The results indicated that education and marital status were the most influential parameters for all three top-performing algorithms (random forest, MLP, and decision tree).
Conclusions: Our research suggests that innovative methods, such as machine learning algorithms, can be used to evaluate psychological distress caused by the COVID-19 outbreak, such as stress. Evaluating stress levels can help prevent mental health problems and enhance students' coping capabilities. |
| نویسندگان مقاله |
| Roghieh Nooripour
Department of Counseling, Faculty of Education and Psychology, Alzahra University, Tehran, Iran.
| Hossein Ilanloo
Kharazmi University, Tehran, Iran.
| Mohammad Naveshki
Reservoir Engineering Oil and Gas Faculty, Sahand University of Technology, Tabriz , Iran.
| Saeid Naveshki
Remote Sensing and Geographic Information System Geographic Faculty, Kharazmi University, Tehran, Iran.
| Mojtaba Amiri Majd
Department of Psychology,Faculty of Humanities Abhar Branch, Islamic Azad University, Abhar, Iran.
| Sverker Sikströmnian
Chair of the Cognitive Division, Department of Psychology, Lund university, Sweden.
| Farnaz Jafari
Department Of Educational Sciences, Farhangian University, Shiraz, Iran.
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