شناسایی مؤثرترین پیش‌بینی‌کننده‌های افسردگی در دانشجویان زن با استفاده از تکنیک‌های انتخاب ویژگی

Abdollahi, A., Taheri, A., Khobroo, M., & Shadloo, D. (2021). Investigating the psychometric properties of the cognitive rumination scale of errors. Psychological Science, 103, 1117-1130. https://doi.org/10.52547/JPS.20.103.1117

Ahmed, G., Negash, A., Kerebih, H., Alemu, D., & Tesfaye, Y. (2020). Prevalence and associated factors of depression among Jimma University students. A cross-sectional study. International Journal of Mental Health Systems, 14, 1-10. https://doi.org/10.1186/s13033-020-00384-5

Al Omari, O., Al Sabei, S., Al Rawajfah, O., Abu Sharour, L., Aljohani, K., Alomari, K., & Alhalaiqa, F. (2020). Prevalence and predictors of depression, anxiety, and stress among youth at the time of COVID‐19: An online cross‐sectional multicountry study. Depression research and treatment, 2020, 1-8887727. https://doi.org/10.1155/2020/8887727

Ali Akbari, M., Sharifi, A. A., & Sahra Gard, M. (2013). Psychometric properties of the Big Five Personality Inventory for Children (BFQ-C) in an Iranian sample. Psychological Achievements, 79-90. https://psychac.scu.ac.ir/author.index?vol=0&vl=%D9%87%D9%85%D9%87%20%D8%AF%D9%88%D8%B1%D9%87%20%D9%87%D8%A7

Awadalla, S., Davies, E. B., & Glazebrook, C. (2020). A longitudinal cohort study to explore the relationship between depression, anxiety and academic performance among Emirati university students. BMC psychiatry, 20, 1-10. https://doi.org/10.1186/s12888-020-02854-z

Barbayannis, G., Bandari, M., Zheng, X., Baquerizo, H., Pecor, K. W., & Ming, X. (2022). Academic stress and mental well-being in college students: correlations, affected groups, and COVID-19. Frontiers in psychology, 13, 886344. https://doi.org/10.3389/fpsyg.2022.886344

Bashlideh, K., Yousefi, N., Haghighi, J., & Behroozi, N. (2012). Investigating the factor structure of the Rosenberg Self-Esteem Scale with three forms of positive, negative, and half-positive and half-negative items in students of Shahid Chamran University of Ahvaz. Educational Psychology Studies, 15, 41-66. https://jeps.usb.ac.ir/article_686.html

Chikersal, P., Doryab, A., Tumminia, M., Villalba, D. K., Dutcher, J. M., Liu, X., & Dey, A. K. (2021). Detecting depression and predicting its onset using longitudinal symptoms captured by passive sensing: a machine learning approach with robust feature selection. ACM Transactions on Computer-Human Interaction (TOCHI), 28(1), 1-41. https://doi.org/10.1145/3422821

Chung, J., & Teo, J. (2022). Mental health prediction using machine learning: taxonomy, applications, and challenges. Applied Computational Intelligence and Soft Computing, 2022(1), 9970363. https://doi.org/10.1155/2022/9970363

Eslami, A., Mahmoudi, A., Khabiri, M., & Najafian Ravari, S. M. (2013). The role of socio-economic status (SES) in motivating citizens to participate in recreational sports. Applied Research in Sport Management, 7, 89. https://arsmb.journals.pnu.ac.ir/article_682_61.html?lang=en

Eslami, N., Alizadeh, F., Mohammadzadeh, N., & Mohammad, S. (2023). Investigating the mental health of Mashhad dental school students using the SCL-90 questionnaire in the academic year 2020-2021. Journal of Mashhad Dental School, 47(4), 352-370. https://jmds.mums.ac.ir/article_23485.html

Farokhi, A., Motasharei, E., Zeydabadi, R., Aghasi, S., & Parsa, G. R. (2013). Determining the validity and reliability of the Persian version of the sport perfectionism scale in Iranian athletes. Motor Learning and Sport Development, 11, 55-76. https://jsmdl.ut.ac.ir/article_35004.html

Hamzeh, M., & Narges Zal, N. (2022). Investigating the socio-economic status on attention, intelligence, and social growth of 8-9 year old girls. Journal of Curriculum Studies Research, 2, 60-70. https://jcdr.cfu.ac.ir/article_2711.html

Islam, S., Akter, R., Sikder, T., & Griffiths, M. D. (2020). Prevalence and factors associated with depression and anxiety among first-year university students in Bangladesh: a cross-sectional study. International journal of mental health and addiction, 1-14. https://doi.org/10.1007/s11469-020-00242-y

Jokar, B., & Salimi, A. (2011). Psychometric properties of the short form of the Social and Emotional Loneliness Scale for Adults. Behavioral Sciences, 4, 311-320. https://www.sid.ir/paper/502401/%D8%AE%D8%B1%DB%8C%D8%AF%20%D8%A7%D9%82%D8%B3%D8%A7%D8%B7%DB%8C%20%DA%AF%D9%88%D8%B4%DB%8C%20%D8%A2%DB%8C%D9%81%D9%88%D9%86%2014

Nayan, M. I. H., Uddin, M. S. G., Hossain, M. I., Alam, M. M., Zinnia, M. A., Haq, I., & Methun, M. I. H. (2022). Comparison of the performance of machine learning-based algorithms for predicting depression and anxiety among University Students in Bangladesh: A result of the first wave of the COVID-19 pandemic. Asian Journal of Social Health and Behavior, 5(2), 75-84. https://doi.org/10.4103/shb.shb_38_22

Nixdorf, I., Beckmann, J., & Nixdorf, R. (2020). Psychological predictors for depression and burnout among German junior elite athletes. Frontiers in psychology, 11, 601. https://doi.org/10.3389/fpsyg.2020.00601

Oswalt, S. B., Lederer, A. M., Chestnut-Steich, K., Day, C., Halbritter, A., & Ortiz, D. (2020). Trends in college students' mental health diagnoses and utilization of services, 2009-2015. Journal of American College Health, 68(1), 41-51. https://doi.org/10.1080/07448481.2018.1515748

Rafiei, M., & Seifi, A. (2013). Investigating the reliability and validity of the Beck Anxiety Inventory in students. Clinical Psychology and Cognitive Science, 27, 37. https://jtbcp.riau.ac.ir/article_13.html

Rocha, T. B. M., Fisher, H. L., Caye, A., Anselmi, L., Arseneault, L., Barros, F. C., & Kieling, C. (2021). Identifying adolescents at risk for depression: a prediction score performance in cohorts based in 3 different continents. Journal of the American Academy of Child & Adolescent Psychiatry, 60(2), 262-273. https://doi.org/10.1016/j.jaac.2019.12.004

Salimi, N., Gere, B., Talley, W., & Irioogbe, B. (2023). College students mental health challenges: Concerns and considerations in the COVID-19 pandemic. Journal of College Student Psychotherapy, 37(1), 39-51. https://doi.org/10.1080/87568225.2021.1890298

Shafiee, N. S. M., & Mutalib, S. (2020). Prediction of mental health problems among higher education student using machine learning. International Journal of Education and Management Engineering, 10(6), 1. https://doi.org/10.5815/ijeme.2020.06.01

Shahmohammadi, H., Jamali, S., & Mahdizadeh, M. (2010). Investigating the effect of emotional intelligence on the mental health of students at the Islamic Azad University of Tabriz. https://civilica.com/doc/95296/

Taheri Tanjani, P., Garmaroodi, G. R., Azad Bakht, M., Fekrizadeh, Z., Hamidi, R., Fathi Zadeh, S., & Ghaisvandi, E. (2015). Investigating the validity and reliability of the second version of the Beck Depression Inventory (BDI-II) in Iranian elderly. Sabzevar University of Medical Sciences and Health Services, 1, 189. https://journals.medsab.ac.ir/article_550.html