Suicide Prevention: Maybe We’ve Been Focusing On Wrong Aspects For Prevention


Have we been trying to prevent suicides wrongly all this time?

Michael Kyron, The University of Western Australia and Andrew Page, The University of Western Australia

Staten Islander News has previously published a piece on suicide and some of its hidden causes, as well as announcements and events by NAMI to commemorate Suicide Prevention Awareness Month.  

Traditional approaches to preventing suicide have focused on “who is at risk?” The aim is to identify an individual and to help them get support.

But that approach doesn’t seem to be working. Australia’s suicide rates have remained stubbornly high. There was an increase in the rate of suicides from 2012 to 2022.

We often do not know who is most vulnerable to suicide, and if we do, we struggle to efficiently target resources to them when they need it most. So we need a fresh approach.

Maybe we’ve been asking the wrong question all this time. Rather than asking “who is at risk?” we should also ask “when is a person at risk?”

We know depression increases suicide risk, but on a given day most depressed people will not consider suicide. We need to know when a person’s risk has risen to help them access support immediately.

Our preliminary research conducted in a Perth psychiatric hospital, and published recently, suggests this might be worth pursuing.

What we did

We conducted a “proof of concept” study involving inpatients at the psychiatric hospital Perth Clinic. Patients were invited to complete questionnaires on iPads in each room. Over more than a decade, more than 20,000 patients participated in the study, resulting in about 350,000 completed questionnaires.

We then examined questionnaire data from 110 inpatients who attempted suicide in the hospital over an average 25-day period. These patients were typically female (78%) and had a diagnosis of major depression or an anxiety disorder. They were 14 to 77 years old.

Of note, nurses had rated roughly half as having “no” to “low risk” of suicide, based on interviews with patients.

We then looked for patterns in the data to see if we could see who and when someone was at increased short-term risk of attempting suicide.

What we found

We found that on the day of a suicide attempt, a person’s perception they were a burden to friends and family increased greatly.

The day before a suicide attempt, patients reported an increased loss of hope in their lives. They perceived they could not change things that mattered to them.

We used this data to develop an algorithm to monitor spikes in these and other key risk factors that may signal increased short-term risk of suicide attempts.

This algorithm, now live in the hospital, alerts staff to at-risk patients to facilitate targeted and immediate interventions when the risk of attempted suicide is at its highest.

How can we apply these findings?

Key signals we identified as indicators of short-term risk of suicide – perceptions of burden or hopelessness – are often not matched by reality.

While people may think they are a burden, their friends and family members disagree. Far from being burdened, those friends and family are the ones who struggle to know how and when to give the assistance they desperately want to provide. Likewise, a perception of hopelessness is often transient and doesn’t always reflect reality.

So clinical staff can work with patients to help them re-evaluate these misguided beliefs, and to collaboratively develop coping strategies.

For instance, a core belief of “I am a burden” is replaced by “I wouldn’t think a loved one was a burden if they were suffering.”

Nurse comforting patient, one hand on shoulder, one on hand on knee
Clinical staff work with patients to help them re-evaluate their perceptions.
Monkey Business Images/Shutterstock

Where to now?

The aim now is to trial our approach in a larger number of psychiatric patients, across multiple sites across Australia, to see if this gives staff enough time to intervene and prevent imminent suicides.

We’re also hoping to test our methods in the community. This includes predicting the risk of suicide among school students, and remotely monitoring people at risk of suicide who present to primary care, such as their GP.

For instance, we are working with GPs to extend Perth Clinic’s daily monitoring system to track the symptoms of GP patients between appointments. Through this approach the GPs can monitor the effectiveness of medications or identify periods of heightened risk that can be addressed at future appointments.

Our approach is just one aspect of suicide prevention. We also need to address the complex web of societal, socioeconomic and other factors that contribute to the type of distress we see in people contemplating suicide.

If this article has raised issues for you, or if you’re concerned about someone you know, call Lifeline on 13 11 14. In an emergency, call 000.The Conversation

Michael Kyron, Research Fellow, School of Psychological Science, The University of Western Australia and Andrew Page, Pro Vice-Chancellor (Research), The University of Western Australia

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Banner Image: Drowning in depression.  Image Credit – Stormseeker


Michael Kyron The Conversation

Michael Kyron is postdoctoral researcher and lecturer with the School of Psychological Science at the University of Western Australia. He is also the business support manager with the Suicide Prevention and Resilience Research Centre (SPARRC). Michael's work has primarily been focused on the application of innovative methods to predict and prevent suicide, including the application of dynamic modelling, machine learning, and wearable technology. He has extensive research experience with clinical and adolescent populations, and with ecological momentary assessment and large-scale longitudinal cohort research designs.

There are no comments yet

Why not be the first

Leave a Reply

Your email address will not be published. Required fields are marked *