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  1. Technion—Israel Institute of Technology, Faculty of Data and Decision Sciences, Haifa, Israel
  2. Mrs Badian and Dr Ophir contributed equally to the article.
  3. Technion—Israel Institute of Technology, Faculty of Data and Decision Sciences, Haifa, Israel
  4. University of Cambridge, Centre for Human Inspired Artificial Intelligence, Cambridge, UK
  5. Corresponding Author: Yaakov Ophir, PhD, Technion—Israel Institute of Technology, Technion City, Haifa 3200003 ([email protected]).
  6. Mrs Badian and Dr Ophir contributed equally to the article.
  7. Technion—Israel Institute of Technology, Faculty of Data and Decision Sciences, Haifa, Israel
  8. Technion—Israel Institute of Technology, Faculty of Data and Decision Sciences, Haifa, Israel
  9. Reichman University, Baruch Ivcher School of Psychology, Herzliya, Israel
  10. Technion—Israel Institute of Technology, Rappaport Faculty of Medicine, Haifa, Israel
  11. Technion—Israel Institute of Technology, Faculty of Data and Decision Sciences, Haifa, Israel
  1. Turecki G, Brent DA, Gunnell D, et al. Suicide and suicide risk. Nat Rev Dis Primers. 2019;5(1):74. PubMed CrossRef
  2. Hedegaard H, Curtin SC, Warner M. Suicide Rates in the United States Continue to Increase. Hyattsville, MD: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics; 2018.
  3. Moutier C. Suicide prevention in the COVID-19 era: transforming threat into opportunity. JAMA Psychiatry. Published online October 16, 2020. PubMed
  4. Klomek AB. Suicide prevention during the COVID-19 outbreak. Lancet Psychiatry. 2020;7(5):390. PubMed CrossRef
  5. Banerjee D, Kosagisharaf JR, Sathyanarayana Rao TS. ‘The dual pandemic’ of suicide and COVID-19: a biopsychosocial narrative of risks and prevention. Psychiatry Res. 2021;295:113577. PubMed CrossRef
  6. Gunnell D, Appleby L, Arensman E, et al; COVID-19 Suicide Prevention Research Collaboration. Suicide risk and prevention during the COVID-19 pandemic. Lancet Psychiatry. 2020;7(6):468–471. PubMed CrossRef
  7. Samji H, Wu J, Ladak A, et al. Review: mental health impacts of the COVID‐19 pandemic on children and youth–a systematic review. Child Adolesc Ment Health. 2022;27(2):173–189. PubMed
  8. Zaninotto P, Iob E, Demakakos P, et al. Immediate and longer-term changes in the mental health and well-being of older adults in england during the COVID-19 pandemic. JAMA Psychiatry. 2022;79(2):151–159. PubMed CrossRef
  9. Vizheh M, Qorbani M, Arzaghi SM, et al. The mental health of healthcare workers in the COVID-19 pandemic: a systematic review. J Diabetes Metab Disord. 2020;19(2):1967–1978. PubMed CrossRef
  10. Yao H, Chen J-H, Xu Y-F. Patients with mental health disorders in the COVID-19 epidemic. Lancet Psychiatry. 2020;7(4):e21. PubMed CrossRef
  11. Li LZ, Wang S. Prevalence and predictors of general psychiatric disorders and loneliness during COVID-19 in the United Kingdom. Psychiatry Res. 2020;291:113267. PubMed CrossRef
  12. Ren X, Huang W, Pan H, et al. Mental health during the Covid-19 outbreak in China: a meta-analysis. Psychiatr Q. 2020;91(4):1033–1045. PubMed CrossRef
  13. Taquet M, Geddes JR, Husain M, et al. 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records. Lancet Psychiatry. 2021;8(5):416–427. PubMed CrossRef
  14. Ellis WE, Dumas TM, Forbes LM. Physically isolated but socially connected: psychological adjustment and stress among adolescents during the initial COVID-19 crisis. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement. 2020;52(3):177–187. CrossRef
  15. Murata S, Rezeppa T, Thoma B, et al. The psychiatric sequelae of the COVID-19 pandemic in adolescents, adults, and health care workers. Depress Anxiety. 2021;38(2):233–246. PubMed CrossRef
  16. Zhang L, Zhang D, Fang J, et al. Assessment of mental health of Chinese primary school students before and after school closing and opening during the COVID-19 pandemic. JAMA Netw Open. 2020;3(9):e2021482. PubMed CrossRef
  17. Sakamoto H, Ishikane M, Ghaznavi C, et al. Assessment of suicide in Japan during the COVID-19 pandemic vs previous years. JAMA Netw Open. 2021;4(2):e2037378. PubMed CrossRef
  18. Dubé JP, Smith MM, Sherry SB, et al. Suicide behaviors during the COVID-19 pandemic: a meta-analysis of 54 studies. Psychiatry Res. 2021;301:113998. PubMed CrossRef
  19. Bruffaerts R, Demyttenaere K, Hwang I, et al. Treatment of suicidal people around the world. Br J Psychiatry. 2011;199(1):64–70. PubMed CrossRef
  20. Franklin JC, Ribeiro JD, Fox KR, et al. Risk factors for suicidal thoughts and behaviors: a meta-analysis of 50 years of research. Psychol Bull. 2017;143(2):187–232. PubMed CrossRef
  21. Sejnowski TJ. The deep learning revolution. Mit Press; 2018.
  22. Roy A, Nikolitch K, McGinn R, et al. A machine learning approach predicts future risk to suicidal ideation from social media data. NPJ Digit Med. 2020;3(1):78. PubMed CrossRef
  23. Coppersmith G, Leary R, Crutchley P, et al. Natural language processing of social media as screening for suicide risk. Biomed Inform Insights. 2018;10:1178222618792860. PubMed CrossRef
  24. Ophir Y, Tikochinski R, Asterhan CSC, et al. Deep neural networks detect suicide risk from textual Facebook posts. Sci Rep. 2020;10(1):16685. PubMed CrossRef
  25. Zirikly A, Resnik P, Uzuner O, et al. CLPsych 2019 shared task: predicting the degree of suicide risk in Reddit posts. Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology. 2019 2019:24-33.
  26. Zheng L, Wang O, Hao S, et al. Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records. Transl Psychiatry. 2020;10(1):72. PubMed CrossRef
  27. Bernert RA, Hilberg AM, Melia R, et al. Artificial intelligence and suicide prevention: a systematic review of machine learning investigations. Int J Environ Res Public Health. 2020;17(16):5929. PubMed CrossRef
  28. Burke TA, Ammerman BA, Jacobucci R. The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: a systematic review. J Affect Disord. 2019;245:869–884. PubMed CrossRef
  29. Resnik P, Foreman A, Kuchuk M, et al. Naturally occurring language as a source of evidence in suicide prevention. Suicide Life Threat Behav. 2021;51(1):88–96. PubMed
  30. Ji S, Pan S, Li X, et al. Suicidal ideation detection: a review of machine learning methods and applications. IEEE Trans Comput Soc Syst. 2021;8(1)214–226.
  31. Ophir Y, Tikochinski R, Brunstein Klomek A, et al. The Hitchhiker’s Guide to computational linguistics in suicide prevention. Clin Psychol Sci. 2022;10(2):212–235. CrossRef
  32. Ophir Y, Rosenberg H, Lipshits-Braziler Y, et al. “Digital Adolescence”: The Effects of Smartphones and Social Networking Technologies on Adolescents’ Well-Being. Online Peer Engagement in Adolescence. Routledge; 2020:122–139.
  33. Stravynski A, Boyer R. Loneliness in relation to suicide ideation and parasuicide: a population-wide study. Suicide Life Threat Behav. 2001;31(1):32–40. PubMed CrossRef
  34. Bennardi M, Caballero FF, Miret M, et al. Longitudinal relationships between positive affect, loneliness, and suicide ideation: age-specific factors in a general population. Suicide Life Threat Behav. 2019;49(1):90–103. PubMed CrossRef
  35. Rogers ML, Joiner TE. Rumination, suicidal ideation, and suicide attempts: a meta-analytic review. Rev Gen Psychol. 2017;21(2):132–142. CrossRef
  36. Ribeiro JD, Joiner TE. The interpersonal-psychological theory of suicidal behavior: current status and future directions. J Clin Psychol. 2009;65(12):1291–1299. PubMed CrossRef
  37. Joiner T. Why People Die by Suicide. Harvard University Press; 2009.
  38. Bretherton I. The Origins of Attachment Theory: John Bowlby and Mary Ainsworth. Attachment Theory. Routledge; 2013:45–84.
  39. Markowitz JC, Weissman MM. Interpersonal psychotherapy: principles and applications. World Psychiatry. 2004;3(3):136–139. PubMed
  40. Ewing ESK, Diamond G, Levy S. Attachment-based family therapy for depressed and suicidal adolescents: theory, clinical model and empirical support. Attach Hum Dev. 2015;17(2):136–156. PubMed CrossRef
  41. Diamond G, Diamond GM, Levy S. Attachment-based family therapy: theory, clinical model, outcomes, and process research. J Affect Disord. 2021;294:286–295. PubMed CrossRef
  42. Chancellor S, De Choudhury M. Methods in predictive techniques for mental health status on social media: a critical review. NPJ Digit Med. 2020;3(1):43. PubMed CrossRef
  43. Ophir Y, Asterhan CSC, Schwarz BB. The digital footprints of adolescent depression, social rejection and victimization of bullying on Facebook. Comput Human Behav. 2019;91:62–71. CrossRef
  44. Ophir Y. SOS on SNS: adolescent distress on social network sites. Comput Human Behav. 2017;68:51–55. CrossRef
  45. Brown TB, Mann B, Ryder N, et al. Language models are few-shot learners. arXiv preprint arXiv:2005.14165. 2020.
  46. Lee E, Lee J-A, Moon JH, et al. Pictures speak louder than words: motivations for using instagram. Cyberpsychol Behav Soc Netw. 2015;18(9):552–556. PubMed CrossRef
  47. Herring S, Dainas A. “Nice Picture Comment!” Graphicons in Facebook Comment Threads. 2017.
  48. Tang Y, Hew KF. Emoticon, emoji, and sticker use in computer-mediated communication: a review of theories and research findings. Int J Commun. 2019;13:27.
  49. Bai Q, Dan Q, Mu Z, et al. A systematic review of emoji: current research and future perspectives. systematic review. Front Psychol. 2019;10:2221. PubMed CrossRef
  50. Alishahi A, Chrupała G, Linzen T. Analyzing and interpreting neural networks for NLP: a report on the first BlackboxNLP workshop. Nat Lang Eng. 2019;25(4):543–557. CrossRef
  51. Posner K, Brown GK, Stanley B, et al. The Columbia-Suicide Severity Rating Scale: initial validity and internal consistency findings from three multisite studies with adolescents and adults. Am J Psychiatry. 2011;168(12):1266–1277. PubMed CrossRef
  52. Ophir Y, Sisso I, Asterhan CSC, et al. The turker blues: hidden factors behind increased depression rates among Amazon’s Mechanical Turkers. Clin Psychol Sci. 2020;8(1):65–83. CrossRef
  53. Radford A, Kim JW, Hallacy C, et al. Learning Transferable Visual Models From Natural Language Supervision. PMLR; 2021:8748–8763.
  54. He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. 2016:770–778.
  55. Ramírez-Cifuentes D, Freire A, Baeza-Yates R, et al. Detection of suicidal ideation on social media: multimodal, relational, and behavioral analysis. J Med Internet Res. 2020;22(7):e17758. PubMed CrossRef
  56. Ma Y, Cao Y. Dual Attention based Suicide Risk Detection on Social Media. IEEE; 2020:637–640.
  57. Huang Y, Li W, Macheret F, et al. A tutorial on calibration measurements and calibration models for clinical prediction models. J Am Med Inform Assoc. 2020;27(4):621–633. PubMed CrossRef
  58. Rodway C, Tham S-G, Turnbull P, et al. Suicide in children and young people: can it happen without warning? J Affect Disord. 2020;275:307–310. PubMed CrossRef
  59. Ribeiro JD, Huang X, Fox KR, et al. Predicting imminent suicidal thoughts and nonfatal attempts: the role of complexity. Clin Psychol Sci. 2019;7(5):941–957. CrossRef