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10 of the most important things we learned about mental health this year

Published by Business Insider on Tue, 11 Dec 2018

In 2018, researchers around the world worked tirelessly to combat a range of mental health issues.Scientists found more effective treatments for post-traumatic stress disorder and further delved into the relationship between sleep and depression.Previously under-researched drugs such as ketamine, marijuana, and ecstasy became the main focus for many researchers when seeking potential treatments for anxiety and depression, among other mental health concerns. Approximately one in five adults in the US43.8 millionexperiences mental illness in a given year, according to The National Alliance on Mental Illness. That being said, it's no surprise that each and every year researchers put time and enormous amounts of money into tackling the growing mental health crisis.It seems in 2018, much of their hard work paid offaround the world researchers crumbled myths and opened new doors as they aimed to better comprehend the complicated world of invisible illnesses.Here are 10 of the most important things we learned about mental health in 2018.Scientists discovered "master keys" that could help better them to understand schizophrenia and autism spectrum disorder.In 2018, researchers at Emory and the Chinese Academy of Sciences aimed to better understand complex brain disorders such as schizophrenia and autism spectrum disorder (ASD). To do so, the researchers identified a few "master keys," risk genes important for brain function and then created mice partially lacking one of those master keys, called MIR-137.They found that the mice lacking MIR-137, a gene thatregulates hundreds of other genes, displayed learning and memory deficits, repetitive behaviors and impaired sociability.But when treated with papaverine, a vasodilator and Pde10a inhibitor, these scientists could improve the mice's performance on social tests and maze navigation.The research is especially as important as it has previously been found that people with too much MIR-137 exhibit symptoms of schizophrenia while those with too little exhibit symptoms of autism."It's interesting to think about in the context of precision medicine," said senior author Peng Jin, Ph.D., professor of human genetics at Emory University School of Medicine. "Individuals with a partial loss of MIR137either genomic deletions or reduced expression could potentially be candidates for treatment with Pde10a inhibitors."Written exposure therapy was found to help some patients with PTSD.Post-traumatic stress disorder (PTSD) is "a disorder that develops in some people who have experienced a shocking, scary, or dangerous event." The condition affects 5% of Americans at any given time and can be debilitatingcausing people to disconnect from their lives and have extreme emotional or physical reactions.Research supported by the National Institute of Mental Health (NIMH) aimed to find a more efficient way to treat PTSD, as current treatments require extensive training for therapists and burdensome work for patients. Their solution was written exposure therapy (WET), a treatment including five sessions during which patients write about their specific traumatic event.The researchers found that treating PTSD patients using WET was as successful as treating them with cognitive processing therapy (CPT), a widely accepted treatment consisting of 12 weekly therapy sessions.The research was important as it made clear that PTSD can be effectively treated with a five-session psychotherapy.Researchers may have found a better way to prevent suicide.Suicide accounted for nearly45,000 deaths in the United States in 2016. In an attempt to address the issue, researchers looked at ways of using electronic health records to predict suicide attempts and deaths by suicide.Researchers used the fact that half of the people who die by suicide, and two-thirds of people who attempt suicide, received a mental health diagnosis or treatment in the previous year, to track individuals who might be at risk of suicide.Dr. Gregory Simon, M.P.H., a senior investigator at the Kaiser Permanente Washington Health Research Institute, and colleagues used data from electronic health records (EHRs) provided by seven major health systems to create a model that could determine at-risk people.The researchers found that using variables such as mental health diagnoses, substance use diagnoses, use of mental health emergency and inpatient care, history of self-harm, and scores on the Patient Health Questionnaire, they were successfully able to predict who is at risk for suicide attempt and death."By leveraging existing electronic health record data and advancements in statistical modeling, it is possible to significantly improve the prediction of death by suicide and suicide attempts over conventional self-report methods," said Michael Freed, Ph.D., chief of the Services Research and Clinical Epidemiology Branch in the NIMH Division of Services and Intervention Research."Valid and reliable suicide risk prediction models hold tremendous promise to reduce death by suicide, especially when integrated with evidence-supported approaches to suicide prevention."See the rest of the story at Business Insider
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