Saturday, April 13, 2024

Social Networks Reflect How Pandemic Has Damaged The Mental Health

Social networks have already become a repository that stores how citizens are experiencing historical moments. In the case of the pandemic, they have served as an outlet for millions of users who have used them to share their concerns, concerns and discomfort in the face of such a dramatic and uncertain situation.

Based on this idea, several teams from MIT and Harvard University have analyzed the conversations that have been published during these months to find out how the mental health of users has been affected.

Their research, published in the Journal of Medical Internet Research , concludes that users make more references to their anxiety and talk more about suicide than before the coronavirus.

This conclusion also fits with the perception that psychologists have about the consultations that their patients have made so far this year.

Since the confinement began, the most common consultations that mental health professionals have are focused on anxiety, grief management and relationship problems.

“We have seen, above all, difficulties with grief, due to the death of relatives or acquaintances, loss of work and deep feelings of loneliness,” explains Martín Villanueva, co-founder of iFeel, one of the mobile applications that offer psychological help.

Given the recommendations to reduce social contact as much as possible, the use of these apps has skyrocketed. Since March, iFeel, with more than 300,000 users, has noticed an increase in queries of 203%, 90% of them from Spain.

These changes in the needs of patients have been noticed in the networks. Using machine learning techniques to analyze the content of more than 800,000 posts, Harvard researchers found changes in the tone and content of the language that citizens were using as the first wave of the pandemic progressed, from January to April.

Their analysis revealed several key changes in conversations about mental health: They found a general increase in references to anxiety and suicide.

“We discovered that threads related to suicide and loneliness emerged. The number of posts in these groups doubled during the pandemic compared to the same months last year, which is a great concern,” says Daniel Low, graduate student of the Harvard and MIT Speech and Hearing Technology and Bioscience Program and lead author of the study.

Although the authors clarify that they cannot point to the pandemic as the sole cause of the observed linguistic changes, they point out that there was a much more significant change during the period from January to April 2020 than in the same months of 2019 and 2018, ” indicating that the changes cannot be explained by normal annual trends. “

Using various types of natural language processing algorithms, the researchers measured the frequency of words associated with topics such as anxiety, death, isolation, and substance abuse, and grouped posts based on similarities in the language used.

They found that most users started talking about COVID-19 in March, but those who said they had health anxiety started much earlier, in January. As the pandemic progressed, the language used by all users began to look more alike.

The analysis also revealed the impact of the coronavirus on people who already suffered from some type of mental illness before the pandemic. The mental health groups most adversely affected at the beginning of the pandemic were those related to ADHD and eating disorders.

Researchers hypothesize that without their usual social support systems, due to quarantine, people with these disorders find it much more difficult to control their conditions. In those groups, the researchers found posts about hyperfocus on the news and relapse into anorexia-like behaviors, as other people were not monitoring meals.

The findings could help professionals, and even those responsible for different social networks, to better identify and help users who are suffering from some type of problem related to mental health, the researchers say.

“This type of analysis could help mental health care providers identify the segments of the population that are most vulnerable when something serious happens, like a pandemic or natural disaster,” says Low.

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