Can Digital Technology Prevent Suicides?
Time to read: 4 minutes
Psychiatric disorders are strong predictors of a higher mortality risk and account for a significant number of years lost to premature mortality across most populations. The increased risk of mortality is due to the increased likelihood of suicide for which the Global Burden of Disease reports to be the 13th leading cause of death.
Although the presence of a psychiatric disorder is a major risk factor for suicidal behaviour, it isn’t the only risk factor. Studies have shown that suicidal behaviour can come about through an individual’s genetic disposition, the impact of stressful life events, or psychological factors such as feeling hopelessness or having high emotional reactivity.
For most psychiatric disorders there are evidence-based treatments available that can prevent or reduce the risk of suicide. However, suicide rates have remained unchanged and this is in part by the lack of understanding of how the complex interplay between mental illness, its comorbidities and other psychosocial and biological factors influence suicidal behaviour and suicide.
SUICIDE PREVENTION
Present measures to assess the risk of suicide are subjective and can involve a mental state examination by a relevant healthcare professional. However, suicidal behaviour can be a highly fluid state and external factors such as an acute life event can escalate the risk of suicidal behaviour at any given moment.
To better address suicide prevention, many researchers, innovators and next-gen technologists are attempting to develop an array of different digital technologies to assist in predicting and/or preventing suicide.
Digital technologies are able to collect and analyse large amounts of information including population and patient data which can then provide a greater predictive potential of an individual’s suicide risk. The aim is to better predict specific risks across different populations.
DIGITAL MEDICINE
To predict the risk of suicide, digital medicine is an innovative approach that aims to collect and utilise clinical data to objectively quantify and assess specific risk factors. Such a system would need to be automated and be able to objectively quantify an individual’s present and future risk of suicidal behaviour.
One such study by Kessler et al. analysed over 40,000 soldiers who required psychiatric hospitalisation, and by using a specialised machine learning system, the researchers devised a predictive suicide risk algorithm. The algorithm found that 52.9% of suicides occurred after the 5% of hospitalisations with the highest predicted risk.
AUTOMATED COGNITIVE BEHAVIOURAL THERAPY
Automated cognitive behavioural therapy (CBT) is a means to deliver therapy when a human therapist is not present. This type of automated CBT may involve a text message based system or an automated telephone program.
These types of services can also be used to make daily reports on an individual’s mood as well as a means to catalogue suicidal behaviour with specific risks. The evidence for CBT in suicide prevention to date is, however, limited.
DIGITAL SPEECH ANALYSIS
Recent proof-of-principle studies showed the use of speech analytics to successfully predict which individuals are susceptible to psychotic episodes. We had covered digital speech analysis in this and this article.
In addition, other studies have shown that individuals with depression have a reduced acoustic range. Given the significant clinical association between depression and suicide, this type of digital medicine system could be adapted to determine an individual’s suicide risk.
FACIAL EMOTION ANALYSIS
By digitally analysing facial expressions it is possible to determine suicidal thoughts based on how people react emotionally and physically to different stimuli.
This is particularly useful for those who are not verbal about suicidal ideation. If used in conjunction with measures such as skin conductance and heart rate, researchers are hopeful this may provide an accurate picture on whether an individual is a high risk or not.
There have also been proposals for the development of a Digital Mental State Examination (dMSE) that assesses a patient’s presentation by utilising a range of technologies including motion tracking, natural language processing, and speech analysis to produce quantitative, objective data that may be superior to the subjective reporting of the standard clinical MSE. [Vahabzadeh et al., 2016]
SMARTPHONE APPLICATIONS
There are many smartphone apps at present that offer a predictive platform for determining an individual’s mental health status.
However, the majority of these apps are just checklists with some actually offering harmful advice that could worsen a person’s mental status.
Researchers have also created a suicide prediction system that combines data from mood-focused smartphone apps and serum biomarkers to predict suicidality.
Although this technology is still in its infancy, the future could still hold a smartphone application that is a platform for delivering innovative healthcare technology in the mental health field.
WEARABLE SENSORS AND CLOUD BASED TECHNOLOGY
By attaching sensors to the body, real-time data can be collected, digitised and communicated to cloud-based computing systems.
Using a pre-determined algorithm and comparing against baseline clinical data, an individual’s mental state could be examined at any given moment.
The algorithm would then determine the suicide risk and report these real-time mental health changes to the user, psychiatrist, and their family members.
SUMMARY
Digital medicine is a new generation of technology that will allow researchers and doctors a platform to not only assess and prevent suicide but also to understand the specific risks that are associated with suicide.
These advances will not exclude mental health clinicians but rather compliment and augment the current practices that are currently in place. Involving individuals with lived experiences and suicidal thoughts will be important in the development of digital technologies.
Learn More: Using Data Science to Understand Suicide – Management of Suicidality
Want to learn more? Check out our series of articles and videos on Technology and mental health.
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