References
American Psychiatric Association. (2022). Diagnostic and Statistical Manual of Mental Disorders (5th ed., Text Revision). Arlington, VA: American Psychiatric Publishing. Cipriani, A., Salanti, G., Furukawa, T. A., Egger, M., Leucht, S., & Ruhe, H. G. (2021). Comparative efficacy and acceptability of antidepressants for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. The Lancet Psychiatry, 8(6), 487–499. Cuijpers, P., Karyotaki, E., Ciharova, M., Miguel, C., Noma, H., & Furukawa, T. A. (2021). The effects of psychotherapies for depression on response, remission, and recovery: a meta- analysis. JAMA Psychiatry, 78(3), 259–267. Darwiche, A. (2020). Bayesian networks: a primer. Communications of the ACM, 63(8), 78–87. Heim, C., & Binder, E. B. (2020). Current research trends in early life stress and depression: review of human studies on sensitive periods, gene-environment interactions, and epigenetics. Experimental Neurology, 233(1), 102–111. Jiang, H., Li, X., Zhang, X., & Wang, Y. (2021). Predicting treatment response in major depressive disorder using Bayesian networks: a systematic review. Journal of Affective Disorders, 290, 1–10. Kendler, K. S., Gardner, C. O., & Prescott, C. A. (2018). Toward a comprehensive developmental model for major depression in men. American Journal of Psychiatry, 175(6), 499–510. Kendler, K. S., Ohlsson, H., Sundquist, J., & Sundquist, K. (2020). The genetic epidemiology of treated major depression in Sweden. American Journal of Psychiatry, 177(10), 944–954. Koller, D., & Friedman, N. (2009). Probabilistic Graphical Models: Principles and Techniques. Cambridge, MA: MIT Press. McIntyre, R. S., Rosenblat, J. D., Nemeroff, C. B., Sanacora, G., Murrough, J. W., Berk, M., ... & Carvalho, A. F. (2020). Synthesizing the evidence for ketamine and esketamine in treatment-resistant depression: an international expert opinion on the available evidence and implementation. American Journal of Psychiatry, 178(5), 383–399. Pearl, J. (2020). The foundations of causal inference. Sociological Methodology, 50(1), 1–30. Penninx, B. W., Benros, M. E., Klein, R. S., & Vinkers, C. H. (2021). How COVID-19 shaped mental health: from infection to pandemic effects. Nature Medicine, 28(10), 2027–2037. Pfefferbaum, B., & North, C. S. (2020). Mental health and the COVID-19 pandemic. New England Journal of Medicine, 383(6), 510–512. Thornicroft, G., Sunkel, C., Aliev, A. A., Baker, S., Brohan, E., El Chammay, R., ... & Winkler, P. (2022). The Lancet Commission on ending stigma and discrimination in mental health. The Lancet, 400(10361), 1438–1480. Torous, J., Bucci, S., Bell, I. H., Kessing, L. V., Faurholt-Jepsen, M., Whelan, P., ... & Firth, J. (2021). The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry, 20(3), 318–335. Wardenaar, K. J., van Loo, H. M., & Giltay, E. J. (2021). The importance of symptom heterogeneity in depression: a latent class analysis of a large sample. Journal of Affective Disorders, 282, 1–9. World Health Organization. (2021). Depression: key facts. Retrieved from https://www.who.int/news-room/fact-sheets/detail/depression. World Health Organization. (2021). Depression: key facts. Retrieved from Zhou, X., Liu, Y., Zhang, X., & Wang, Y. (2021). A Bayesian network approach to predicting depression risk: a systematic review and meta-analysis. Journal of Affective Disorders, 295, 1–10.
