Artificial intelligence can help to identify risk factors for suicide and self-harm, according to new research from UNSW Sydney.
risk when a young person enters a health care setting, like a hospital, with potential suicidal or self-harming behavior. Current risk assessment methods such as looking at past attempts can be unreliable, not taking into account the many other potential risk factors. Also, adolescents outside these health care settings fly under the radar.
Among the 2809 participants, 10.5% reported an act of self-harm and 5.2% reported attempting suicide at least once in the past 12 months.Identifying risk factors For suicide and self-harm, the most important risk factors were depressed feelings, emotional and behavioral difficulties, self-perceptions, and school and family dynamics. There were also unique factors specific to either suicide or self-harm.
"Parental support and school support is very important… We need to figure out how as a society we can support parenting and school education, to protect our younger generation."The researchers created ML models based on the top identified risk factors to predict suicide and self-harm in the study participants. These models were able to predict attempts more accurately than the standard approach, which only considers the person's history of previous attempts.
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