From prediction to risk assessment: What’s new in suicide prevention.

In this blog, Claudia García-Martínez, psychologist and PhD student in Psychology at the University of Zaragoza (Spain) discusses the role of social media in developing new approaches for suicide prevention.

Suicide has been defined as a global health priority by World Health Organization (2014). And it is not for less: it causes over 700,000 deaths every year in the world and is the fourth leading cause of death in young people aged 15-29 years. The reduction of suicide mortality is a global target and is included as an indicator in the United Nations Sustainable Development Goals (SDGs)1.

In some way, stigma and taboo have possibly hampered a greater development of prevention strategies for decades. Now we are talking more and more about suicide and therefore, we are seeing new prevention approaches that hopefully will lead to a better prevention and intervention programs.

Until a few decades ago, research efforts have been focused on curbing suicide deaths by trying to predict their occurrence. But suicide deaths are statistically a rare event. So it has been really complex to develop sensitive tools with sufficient predictive value. Recent reviews of these models advocate to shift from a model based on suicide prediction to a model that emphasizes the assessment and management of the risk of suicide2 3 4. This new approaches in suicide prevention would, in theory, help us to reduce suicide outcomes by detecting individuals in potential danger to give them adequate and individualise help and support.

In this “new suicide prevention era”, social media has become a great tool.  

We express our thoughts and feelings on social media5. And, sometimes, we even express contents that we wouldn’t be likely to express in face to face conversations. We communicate and we socialize in a virtual world which now is part of our lives. In that sense, social media has transformed our world.

To give you some numbers to support this statement6:

  • 4.66 billion people are active users of the Internet.
  • 4.2 billion people are active social media users in the world.
  • Global social network penetration rate in Western and North Europe is 79%.

For most people, social media has become part of their daily life. It means that, even if we are not fully aware of it, we are constantly informing about our psychological state in real time to our entire social network and sometimes even publicly.

One of the most interesting findings – and this breaks one of the myths that people always plan suicide before the attempt – is that around half of suicide attempts might start as an impulsive act7. Actually, recent studies suggest that severity of suicidal ideation can vary over short periods of time, even within hours8.

In that sense, the variable “time” seems to play an important role in suicidal behavior, and therefore, in its prevention.  Research using social media for suicide prevention is now more a more frequent. There are a number of recent studies related to this topic using different approaches. Systematic reviews on the subject9 10 collect information ranging from development of social media sites or online therapeutic interventions for suicide prevention, to real-time identification of individuals at risk using computer language processing systems. For me, these last methods are the most interesting development in the field. Some studies have implemented automatic machine learning classification systems that are able to efficiently differentiate people who are at suicidal risk from those who are not, only using what they communicate on their social media11. If further research continues to show such promising results, in the future we may be able to identify people at risk at the same moment they are feeling suicidal.

However, challenges in this new area go hand in hand with ethics: how to reach and help people at risk on social media without compromising their security and privacy. Whatever the form is, social media has become a whole new world of communication for us and therefore it might be able to provide important keys about human behavior and tools for health prevention.

 

About the author

Claudia García-Martínez is a PhD student in Psychology at the University of Zaragoza (Spain). She works as a psychologist in AFDA (Spain) and is specialised in depression and anxiety disorders and contextual therapies. Her research and practice interests are also related to suicide prevention, use of social media for prevention, community health, gender violence and gender determinants in health.

 



Cite this blog post
EUSPR Early Careers Forum (2022, March 20). From prediction to risk assessment: What’s new in suicide prevention. Preventing disease and ill health. Retrieved April 16, 2024, from https://doi.org/10.58079/omb9

  1. World Health Organisation. Fact sheets: Suicide. June 17, 2021. Retrieved from: https://www.who.int/news-room/fact-sheets/detail/suicide []
  2. Pisani, A. R., Murrie, D. C., & Silverman, M. M. (2016). Reformulating Suicide Risk Formulation: From Prediction to Prevention. Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry, 40(4), 623–629. https://doi.org/10.1007/s40596-015-0434-6 []
  3. Bryan, C. J., & Rudd, M. D. (2005). Advances in the assessment of suicide risk. Journal of Clinical Psychology, 62(2), 185–200. doi:10.1002/jclp.20222 []
  4. Kessler RC, Bossarte RM, Luedtke A, Zaslavsky AM, Zubizarreta JR. (2020). Suicide prediction models: a critical review of recent research with recommendations for the way forward. Mol Psychiatry. 25(1):168-179. doi: 10.1038/s41380-019-0531-0 []
  5. Paris, C., et al. Exploring Emotions in Social Media. In 2015 IEEE Conference on Collaboration and Internet Computing (CIC). 2015. []
  6. Statista Research Department. Social media – Statistics & Facts. Feb 25, 2021. Retrieved from: https://www.statista.com/topics/1164/social-networks/ []
  7. Rimkeviciene, J., O’Gorman, J., & De Leo, D. (2016). How do clinicians and suicide attempters understand suicide attempt impulsivity? A qualitative study. Death Studies, 40(3), 139–146. https://doi.org/10.1080/07481187.2015.1096314 []
  8. Kleinman EM, T.B. Fedor S, Beale EE, Huffman JC, Nock MK.  (2017) Examination of real-time fluctuations in suicidal ideation and its risk factors: results from two ecological momentary assessment studies. J Abnorm Psychol, 126(6): p. 726-738. []
  9. Christensen, H., Batterham, P.J., and O’Dea, B. (2014). E-health interventions for suicide prevention. International journal of environmental research and public health. 11(8): p. 8193-8212. []
  10. Robinson J, Cox G, Bailey E, Hetrick S, Rodrigues M, Fisher S, Herrman H.  (2015). Social media and suicide prevention: a systematic review. Early Interv Psychiatry. 10(2):103-21. doi: 10.1111/eip.12229. Epub 2015 Feb 19. PMID: 25702826. []
  11. Braithwaite SR, Giraud-Carrier C, West J, Barnes MD, Hanson CL. (2016) Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality. JMIR Ment Health. 16;3(2):e21. doi: 10.2196/mental.4822. []

One thought on “From prediction to risk assessment: What’s new in suicide prevention.

  1. Thank you Claudia for showing a positive use of Social Media. This is indeed a broad topic and many actions have to be developed to prevent suicide or attempt to commit suicide. Hopefully you will be able to share more discoveries with us during a future EUSPR conference or blog post 😉

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