Researchers in the US have created an algorithm that they say can predict suicidal thoughts and behaviour among adolescents with a 91 per cent accuracy.
The study results show researchers can predict with high accuracy which adolescents will exhibit suicidal thoughts (consideration or planning) or suicidal behaviour (attempting) based on experiences they face.
The team analysed data from 179,384 junior high and high school students, along with those who took part in the Student Health and Risk Prevention survey from 2011 to 2017 – the dataset includes responses to over 300 survey questions and over 8,000 bits of demographic information, resulting in 1.2 billion data points that were processed.
After collection, the researchers then applied various algorithms to the data and found a machine-learning model that accurately predicted which adolescents went on to have suicidal thoughts and behaviours (STB) based on the data provided.
Researchers also found that the algorithm discovered which risk factors were the leading predictors of suicidal thoughts and behaviour: being threatened or harassed through digital media, being picked on or bullied by a student at school, and exposure/involvement in serious arguments and yelling at home.
“This analysis finds the most important root causes of suicidal thoughts and behaviour in adolescents and creates risk profiles that give us a clearer picture of adolescents that are at risk,” said study co-author Carl Hanson, professor of public health at BYU. “If you want to wrap your head around what you can do about it, these profiles are one good place to start.”
Although the researchers expected some of the risk factors, such as bullying and harassment, they were surprised to see the heavy influence of family factors. Three of the top 10 predictive factors for STB were tied directly to family situations: being in a family where there are serious arguments, being in a family that argues about the same things over and over, and being in a family that yells and insults each other.
The team said the implications of the research are critical for prevention programming and policymaking. Specifically, they hope policymakers use the STB risk profile and its associate rankings to prepare services, resources, and assessments aimed at school, community, and family settings.
“Clearly, the results speak to the need for prevention and schools may be the best place to start by helping to mitigate bullying and online harassment. The results also show a need to strengthen families,” Hanson said. “For communities, we need programming that can help support and strengthen the family.”
Source: E&T
