A senior researcher who predicts mental health issues using artificial intelligence has developed a new system capable of identifying mental health risks among adolescents before symptoms appear. The system highlights the importance of sleep as a predictive tool.
For decades, the researcher, a senior clinical psychologist and renowned mental health expert, has conducted studies tracking large groups of people from birth to adulthood.
Her research initially focused on connections between mental and physical health during youth.
Now, with participants in their 50s, the research provides insight into the impact of mental health on aging.
She developed a theory identifying two types of youths who encounter legal troubles.
One type, persistent throughout life, engages in antisocial behavior from childhood and repeatedly harms others.
Fortunately, they are rare.
The second, more common type, experiences temporary issues with the law, grows out of them, and becomes normal citizens.
These findings have influenced juvenile justice systems, law enforcement, and courts in many countries.
Recently, her team created a blood test measuring an individual’s biological aging rate called DunedinPACE, which is used in biotechnology to evaluate interventions aimed at slowing aging and preventing disease in clinical trials.
Her latest breakthrough involves using artificial intelligence to predict mental health risks in adolescents before any symptoms appear.
The goal is early intervention to prevent deterioration into serious clinical conditions.
She explains that adolescent mental health risks are rising sharply, though the causes remain debated.
Factors may include social media, smaller family sizes increasing parental anxiety, higher availability of psychiatric medications, and greater academic and social pressures on youth.
Despite these uncertainties, one finding stands out: most adults with mental health issues experienced them beginning in adolescence, highlighting the importance of monitoring adolescent mental health.
Sleep emerged as the most accurate predictor of future mental health risks.
The research found that sleep patterns were stronger indicators than trauma history or brain scan data.
Poor sleep may worsen mental health or signal early brain function problems.
Additionally, sleep is easier to measure reliably compared with trauma, which people may forget or hesitate to report, making it an excellent early warning tool.
The artificial intelligence model was developed using data from 10,000 American adolescents.
It has shown high accuracy in predicting mental health risks and is now being tested across diverse populations, income levels, and conditions to assess its limits.
The model’s real-world application in schools remains complex due to ethical and privacy considerations.