Tag: depression diagnosis

  • Depression Rates Increase, Especially Among Young Workers

    Depression Rates Increase, Especially Among Young Workers

    Depression rates among employed Americans rose 18% from 2014-2018.

    Rates of depression have increased greatly over the past four years, with young workers seeing the largest surge, according to a recent study. 

    The study, conducted by wellness technology company Happify Health, found that depression rates among employed Americans rose 18% from 2014-2018. Among 18- to 24-year-olds the rate of depression increased 39%. Women in that group saw their depression rates increase 44%. 

    Ran Zilca, the chief data scientist at Happify Health, told SHRM that entering the workforce can be a vulnerable time for young people. 

    “Young adulthood is a transitional time when we’re often just entering the workforce, figuring out who we are and what we want to do with our lives, which can be very challenging and, for some, can cause very negative psychological reactions while not having yet developed the skills to combat those feelings,” Zilca said. “While this analysis doesn’t tell us if the causes are internal or external to their employment, we know from prior Happify research that younger adults tend to be more stressed and worried about job-related matters than older workers.”

    In fact, the oldest workers surveyed (ages 55-64) saw an improvement in their mental health during the time studied.

    Acacia Parks, chief scientist at Happify Health, said that young people can sometimes feel overwhelmed by all the options they have available to them. 

    “[People] going to college now face so many more options in terms of where to go to school, what to major in and what job to aim for. They have access to so much information via the Internet—a universe where the possibilities are endless—which can be both exciting and overwhelming,” Parks said. 

    Some young people also feel daunted by how the workforce is changing, and the uncertainty that brings to their professional and financial lives. 

    “Because technology has upped the pace of everything, college students are preparing for jobs that do not yet exist but will by the time they graduate,” Parks said. “Young adults in previous generations may have easily chosen a profession as they finished high school. Nowadays, preparing for a job is like trying to sail to an island that’s moving. Being a young adult in 2019 means accepting a greater amount of uncertainty than young adults of previous generations, and intolerance of uncertainty is linked to numerous psychological difficulties.”

    Dan Schawbel, author of Back to Human: How Great Leaders Create Connection in the Age of Isolation, said that no one factor can explain such a dramatic increase in depression. 

    “It’s never one thing; it’s the combination of many things happening at once,” he said, pointing out that student loan debt, social media and financial concerns can all burden young workers, who don’t always have the interpersonal capital to ask for help. 

    “If you’re lacking relationships, you feel isolated and lonely, which leads to depression,” he said. 

    View the original article at thefix.com

  • Can Social Media Predict Depression?

    Can Social Media Predict Depression?

    A new study examined whether social media data could be used to find markers for depression.

    Social media could be an accurate predictor of depression, new research has found.

    According to Medical News Today, researchers utilized an algorithm to examine data from social media that could pick out “linguistic cues that might predict depression.” 

    “We’re increasingly understanding that what people do online is a form of behavior we can read with machine learning algorithms, the same way we can read any other kind of data in the world,” lead author Johannes Eichstaedt, founding research scientist at the World Well-Being Project (WWBP) in Philadelphia, told Wired

    Eichstaedt’s team, co-led by H. Andrew Schwartz, a principal investigator of the WWBP, studied data from nearly 1,200 social media users who agreed to grant access to both their posts and their electronic medical records (EMR). Of those who participated, only 114 had dealt with depression in the past. 

    “For each of these 114 patients, we identified 5 random control patients without a diagnosis of depression in the EMR, examining only the Facebook data they created before the corresponding depressed patient’s first date of a recorded diagnosis of depression,” study authors wrote. “This allowed us to compare depressed and control patients’ data across the same time span and to model the prevalence of depression in the larger population.”

    Researchers were then able to determine whether what they refer to as “depression-associated language markers” depicted “emotional and cognitive cues.” These included sadness, loneliness, hostility, rumination and increased self-reference. 

    The linguistic markers, according to researchers, could predict depression fairly accurately as soon as three months before the individual received a diagnosis.

    Still, Eichstaedt says, there is a different method before turning to social media as a reliable tool to diagnose depression. “It would be irresponsible to take this tool and use it to say: You’re depressed, you’re not depressed,” he told Wired

    Eichstaedt also stated that the social media algorithm is comparable to a DNA analysis. 

    “Social media data contain markers akin to the genome,” Eichstaedt said, according to Medical News Today. “With surprisingly similar methods to those used in genomics, we can comb social media data to find these markers. Depression appears to be something quite detectable in this way; it really changes people’s use of social media in a way that something like skin disease or diabetes doesn’t.”

    Eichstaedt says he is hopeful one day that this type of information could prove helpful in making diagnoses and treatments. 

    “The hope is that one day, these screening systems can be integrated into systems of care,” he said. “This tool raises yellow flags; eventually the hope is that you could directly funnel people it identifies into scalable treatment modalities.”

    The report was published in the journal Proceedings of the National Academy of Sciences

    View the original article at thefix.com