social media causing depression and anxiety essay

Loyola University > Center for Digital Ethics & Policy > Research & Initiatives > Essays > Archive > 2018 > The Role of Social Media in Adolescent/Teen Depression and Anxiety

The role of social media in adolescent/teen depression and anxiety, april 3, 2018.

The adolescent and teen years have always been a challenging time. Peer pressure, insecurity and hormones are just some of the issues facing those in these age groups. But does social media exacerbate these problems?

For example, researchers from the Alberta Teachers’ Association, the University of Alberta, Boston Children’s Hospital and Harvard Medical School released a  study  that found significant changes in students at every grade level as a result of digital technology. In the past three to five years, 90 percent of teachers at the University of Alberta saw increases in emotional challenges, 85 percent saw social challenges and 77 percent observed cognitive challenges. Also, 56 percent of teachers report an increase in the number of kids sharing stories about online harassment and/or cyberbullying. There are increases in other areas as well. The majority of teachers say there has been an increase in students diagnosed with the following conditions: anxiety disorders (85 percent), ADD and ADHD (75 percent), and such mood disorders as depression (73 percent).

Also, a recent  study  by researchers at the Royal Society for Public Health and Young Health Movement found that 91 percent of those between the ages of 16 and 24 said Instagram was the worst social media platform as it relates to mental health. Instagram was most likely to cause negative effects such as poor body image, fear of missing out and sleep deprivation. Snapchat came in second place, followed by Facebook, Twitter and YouTube. The researchers theorize that Instagram and Snapchat are image-focused platforms and users compare themselves to others.

A  review  of 36 social media studies, published in JAMA Pediatrics, found that 23 percent of kids are victims of cyberbullying. The review also found that cyberbullying results in low self-esteem, depression, self-harm and behavioral problems — in both the victims and the bullies. In addition, cyberbullying was more likely to produce suicidal thoughts than traditional bullying.

Another  study , conducted by researchers at Glasgow University found that kids (some of whom were pre-teens) were on social media until the wee morning hours, and some were on more than one device (for example, a phone and a tablet) so they could simultaneously view multiple sites. These individuals reported lower sleep quality rates in addition to higher levels of depression and anxiety.

In a  survey  by the National Campaign to Support Teen and Unplanned Pregnancy, almost 20 percent of teens admitted to participating in "sexting" or sending nude photos.

The pressure these adolescents and teens feel can be intensified by the time they get to college. Stanford University coined the phrase “ Duck syndrome ” to describe the erroneous attitude of incoming freshmen that they’re struggling while everyone else is gliding along smoothly — but in reality, the gliders are also “paddling furiously under the water just to keep up.” Adolescents and teens become accustomed to creating the impression that everything is perfect to match the equally perfect posts of their friends. But it becomes too difficult to maintain this façade, resulting in  suicide  among college students who appear to be well-adjusted, but are actually experiencing mental and emotional problems.

Another  report , published in the American Journal of Preventive Medicine, reveals that among young adults between the ages of 19 and 32, those with high social media usage (those logging on for more than 2 hours a day and checking their accounts 58 times a week) were more likely to deal with feelings of isolation than those with low social media use (they logged on for 30 minutes and checked their accounts 9 times a week). 

In light of these studies, who is responsible for the role of social media in adolescent/teen depression and anxiety?

Many tech leaders seem to understand the unhealthy, addictive nature of technology in general and social media in particular. As far back as 2010, New York Times reporter Nick Bilton  interviewed  the late Steve Jobs of Apple. Jobs told Bilton that he limited the amount of technology that his kids use. Bill Gates  shared  that he didn’t let his kids have mobile devices until they were 14 years old, and he sets a time for them to turn off the devices at night.  

Evan Williams, one of the founders of Twitter, Medium and Blogger, told Bilton that his kids read physical books instead of using iPads. Dick Costolo, former CEO of Twitter, told Bilton that his teenagers had to be in the living room when they used their tech devices.

But, perhaps the most shocking revelation came from Sean Parker, former president of Facebook, in an  interview  with Axios. Referring to Facebook, Parker said, “God only knows what it’s doing to our children’s brains.”

But there’s more. Parker also said, “ . . . How do we consume as much of your time and conscious attention as possible? . . . And that means that we need to sort of give you a little dopamine hit every once in a while, because someone liked or commented on a photo or a post or whatever . . . And that's going to get you to contribute more content, and that's going to get you ... more likes and comments . . . It's a social-validation feedback loop ... exactly the kind of thing that a hacker like myself would come up with, because you're exploiting a vulnerability in human psychology . . . The inventors, creators — it's me, it's Mark [Zuckerberg], it's Kevin Systrom on Instagram, it's all of these people — understood this consciously . . . And we did it anyway.”

So, if Parker confessed that social media was designed to be addictive, should social media companies be responsible for depression, anxiety, bullying and other issues among adolescents and teens?

Donna Shea, director of  The Peter Pan Center  for Social and Emotional Growth, and Nadine Briggs, director of  Simply Social Kids , are passionate about helping kids make and keep friends, and together have formed How to Make and Keep Friends, LLC. Shea and Briggs both lead community-based social groups at their centers in Massachusetts and have also formed the Social Success in School initiative. The two have also written several books for kids and teens, including, “Tips for Teens on Life and Social Success” .

Both Shea and Briggs believe that it is the job of parents to monitor their kid’s social media activity. “You wouldn’t allow your teen to put a lock on their bedroom door, but your teen is not only now interacting with peers at school or in your neighborhood, they are interacting with the entire world,” Shea said. “It is a parent’s job to be as involved in their teen’s online life as they are in their offline life.”

In fact, she is not in favor of giving adolescents and teens a phone as a gift. “Mobile devices belong to the parent and the teen is being  allowed  to use it,” Shea said. “A contract can be a useful tool before putting a device in the hands of your teen which would allow parents to have access to the phone.”

She believes that parents should monitor their adolescent/teen’s activity — and teens should know this is being done. “Parents do not need to be sneaky about that — tell your child to hand over the phone,” she said. Shea also recommends that parents use subscription services to view all of their teens’ activities. “Teens should be prepared to be monitored until they are of legal adult age,” she said.

However, Briggs admits that apps change so quickly that it’s almost impossible to keep up with them. “Other than doing your best to monitor your teen’s activity —  and it won’t be 100% effective - it’s important from the very beginning that you teach your child and teen to be good consumers of what is available to them,” Briggs said. “This is the new norm, and we think it’s the parent’s responsibility to be involved in their teen’s online life.”

She compares giving kids a phone or device to putting them behind the wheel of a car. “Both can be dangerous in their own way, but teens can learn the responsibilities that go along with these more adult activities.”

But, do parents bear sole responsibility? For example, everyone knows that tobacco is bad for your health, and people consume it willingly; however, they continue to sue and win lawsuits against tobacco companies. In 2014, one plaintiff was  awarded $23.6 billion  when her husband died of lung cancer as a result of smoking up to three packs of cigarettes a day. He started smoking at the age of 13 and died at the age of 36. The plaintiff (his widow) argued that the tobacco company willfully deceived consumers with addictive products.

How is this scenario different from what social media companies are doing? And speaking of willful deception, what about companies that make  secretive apps  that allow teens to hide their sexting?

If someone trips and falls on your property, you could be sued. If someone gets harmed at your nightclub, you could be held liable for not having “adequate security.” If one of your employees sexually harasses a colleague, you would be held responsible — even if you didn’t know about it. If you sell alcohol, you’re responsible for making sure it doesn’t get into the hands of a minor. In fact, according to the Dram Shop Law, if you let an adult have too many drinks and this individual is involved in an accident, you could be responsible.

However, if kids become addicted to a communication platform that was designed to be addictive, if they’re bullied online, if there are no safeguards to stop them from utilizing the types of secretive apps that encourage risky behavior, shouldn’t these companies be held responsible?

I think they should be, but this is not likely to happen until society holds them responsible. Since most adults are also addicted to social media — and some of them are internet bullies and engage in sexting, it seems unlikely that they would advocate for changes.

In the aforementioned study by the Royal Society for Public Health and Young Health Movement, researchers offered several ways to reduce some of the problems adolescents and teens face online. For example, one of the reasons kids feel so much pressure to look perfect is because of the doctored photos they see. The researchers recommend that social media companies include some sort of notification, such as a watermark, when photos have been digitally manipulated (68 percent of surveyed students support this action).

Another suggestion is to create a social media cap. Users would be logged out if they went over a pre-determined usage level (30 percent of surveyed students agree with this suggestion).

The majority of surveyed students (84 percent) approve of schools having classes on safe social media. 

Another suggestion by the researchers (which did not include student responses) was to use social media posts to identify kids and teens who might be at risk for mental health problems. However, problems have already been identified with  using Facebook to identity potential problem drinkers .

In addition, it was suggested that youth workers be trained in digital media. 

These are nice Band-Aid solutions. But they don’t address the addictive nature of social media and the incredible amount of peer pressure that it involves. Parents can provide guidance, but history has shown that their values rarely outweigh the pressure of peers.

Albert Einstein once said, “We can’t solve our problems with the same thinking we used to create them.” But in this situation, the social media giants can solve these problems with the exact same thinking they used to create them. Just as they figured out what it would take to make these platforms addictive, they can figure out what it would take to make the platforms less addictive. But don’t hold your breath because the person who creates the problem and profits from the problem has no incentive to solve the problem.

Terri Williams  writes for a variety of clients including USA Today , Yahoo , U.S. News & World Report , The Houston Chronicle , Investopedia , and Robert Half . She has a Bachelor of Arts in English from the University of Alabama at Birmingham. Follow her on Twitter @Territoryone .

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Odgers, C. L. & Jensen, M. R. J. Child Psychol. Psychiatry 61 , 336–348 (2020).

Article   PubMed   Google Scholar  

Orben, A. Soc . Psychiatry Psychiatr. Epidemiol. 55 , 407–414 (2020).

Valkenburg, P. M., Meier, A. & Beyens, I. Curr. Opin. Psychol. 44 , 58–68 (2022).

Vuorre, M. & Przybylski, A. K. R. Sci. Open Sci. 10 , 221451 (2023).

Miller, J., Mills, K. L., Vuorre, M., Orben, A. & Przybylski, A. K. Cortex 169 , 290–308 (2023).

Martínez-Alés, G., Jiang, T., Keyes, K. M. & Gradus, J. L. Annu. Rev. Publ. Health 43 , 99–116 (2022).

Danziger, S. Ann. Am. Acad. Pol. Soc. Sci. 650 , 6–24 (2013).

US Department of Education. State Nonfiscal Public Elementary/Secondary Education Survey 2022–2023 (National Center for Education Statistics, 2024).

Google Scholar  

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How Does Social Media Play a Role in Depression?

Verywell / Catherine Song

What to Know About Clinical Depression

Causation or correlation.

• Less Social Media, Less FOMO

Why Young People Are at Risk

• Bad News and ‘Doomscrolling’

Safely Using Social Media

By some estimates, roughly 4 billion people across the world use networking websites such as Facebook, Twitter, and Instagram. This usage has prompted mental health experts to investigate whether the enormous popularity of social media plays a role in depression.

Research suggests that people who limit their time on social media tend to be happier than those who don’t. Studies also indicate that social media may trigger an array of negative emotions in users that contribute to or worsen their depression symptoms.

U.S. Surgeon General Warning

In May 2023, U.S. Surgeon General Dr. Vivek Murthy released an advisory to call attention to the effects of social media on youth mental health. He notes that at crucial periods of adolescent brain development, social media use is predictive of decreases in life satisfaction, as well as additional concerns around body image, sleep issues, and much more.

Given that essentially all adolescents are now using social media in some form, he stresses the importance of further research.

Clinical depression or major depressive disorder is a mood disorder characterized by ongoing feelings of sadness and loss of interest in activities that an individual once enjoyed.

Depression can be mild or severe and make it difficult for those with the condition to concentrate, sleep or eat well, make decisions, or complete their normal routines.

People with depression may contemplate death or suicide, feel worthless, develop anxiety or have physical symptoms such as fatigue or headaches. Psychotherapy and medication are some of the treatments for depression. Limiting time on social media and prioritizing real-world connections can be beneficial to mental health.

The Facts on Social Media and Depression

• Social media has never been more popular, with more than half of the world's population active on these networking sites that roll out nonstop news, much of it negative.
• A Lancet study publbished in 2018 found that people who check Facebook late at night were more likely to feel depressed and unhappy.
• Another 2018 study found that the less time people spend on social media, the less symptoms of depression and loneliness they felt.
• A 2015 study found that Facebook users who felt envy while on the networking site were more likely to develop symptoms of depression.

Some studies about social media and mental health reveal that there’s a correlation between networking sites and depression. Other research goes a step further, finding that social media may very well cause depression. A landmark study—“No More FOMO: Limiting Social Media Decreases Loneliness and Depression”—was published in the Journal of Social and Clinical Psychology in 2018.

The study found that the less people used social media, the less depressed and lonely they felt.

This indicates a relationship between lower social media use and emotional wellbeing. According to the researchers, the study marked the first time scientific research established a causal link between these variables.

“Prior to this, all we could say was that there is an association between using social media and having poor outcomes with wellbeing,” said study coauthor Jordyn Young in a statement.

To establish the link between social media and depression, the researchers assigned 143 University of Pennsylvania students to two groups: one could use social media with no restrictions, while the second group had their social media access limited to just 30 minutes on Facebook, Instagram, and Snapchat combined over a three-week period.

Each study participant used iPhones to access social media and the researchers monitored their phone data to ensure compliance. The group with restricted social media access reported lower severity of depression and loneliness than they had at the beginning of the study.

Both groups reported a drop in anxiety and fear of missing out (FOMO), apparently because joining the study made even the group with unrestricted access to social media more cognizant of how much time they were spending on it.

Less Social Media, Less FOMO 

It’s not certain why participants who only spent 30 minutes daily on social media experienced less depression, but researchers suggest that these young people were spared from looking at content—such as a friend’s beach vacation, grad school acceptance letter, or happy family—that might make them feel bad about themselves.

Taking in the photos or posts of people with seemingly “perfect” lives can make social media users feel like they just don’t measure up. A 2015 University of Missouri study found that regular Facebook users were more likely to develop depression if they felt feelings of envy on the networking site.

Social media can also give users a case of FOMO, for example, if they were invited on their friend’s beach vacation but couldn’t go for some reason. Or if the friend didn’t ask them on the trip at all, users might feel hurt and left out to see that others in their social circle were. It can lead them to question their friendships or their own self-worth.

Social media users who visit an ex’s social media page and see pictures of their former partner wining and dining a new love interest can also experience FOMO. They might wonder why their ex never took them to such fancy restaurants or lavished them with gifts.

Ultimately, limiting one’s time on social media can mean less time spent comparing oneself to others. This can extend to not thinking badly of oneself and developing the symptoms that contribute to depression.

Prior to social media and the internet, children only had to worry about bullying on school grounds, for the most part. But social media has given bullies a new way to torment their victims.

With just one click, bullies can circulate a video of their target being ridiculed, beaten up, or otherwise humiliated. People can swarm a peer’s social media page, leaving negative comments or spreading misinformation. In some cases, victims of bullying have committed suicide.

While many schools have anti-bullying policies and rules about online student conduct, it can still be difficult for educators and parents to monitor abusive behavior on social media.

Worsening matters is that the victims of bullies often fear that the bullying will increase if they speak to a parent, teacher, or administrator about their mistreatment. This can make a child feel even more isolated and go without the emotional support they need to handle a toxic and potentially volatile situation. 

If you or someone you care about is having suicidal thoughts, contact the  National Suicide Prevention Lifeline  at  988  for support and assistance from a trained counselor. If you or a loved one are in immediate danger, call 911.

For more mental health resources, see our  National Helpline Database .

Bad News and ‘Doomscrolling’ 

One in five Americans now get their news from social media—a larger proportion than those who get their news from traditional print media.

For heavy social media users, people who log in for multiple hours at a time or multiple times a day, this means frequent exposure news, including bad news. Headlines related to natural disasters, terrorist attacks, political strife, and celebrity deaths frequently top lists of social media trends.

Before the advent of social media and the internet generally, one’s exposure to bad news was limited. The public got news from broadcasts that aired at certain times of the day or from newspapers.

The habit of binging bad news on social media sites or elsewhere online is known as “doomscrolling,” and it can adversely affect one’s mental health, leading to development or heightening of anxiety or depression symptoms. 

A 2018 Lancet Psychiatry study of 91,005 people found that those who logged onto Facebook before bedtime were 6% likelier to have major depressive disorder and rated their happiness level 9% lower than those with better sleep hygiene did.

Psychologist Amelia Aldao told NPR that doomscrolling locks the public into a “vicious cycle of negativity.” The cycle continues because “our minds are wired to look out for threats,” she said. “The more time we spend scrolling, the more we find those dangers, the more we get sucked into them, the more anxious we get.” Before long, the world appears to be an altogether gloomy place, making doomscrollers feel increasingly hopeless.

Press Play for Advice On Limiting Social Media Use

This episode of The Verywell Mind Podcast shares effective ways to reduce your screen time. Click below to listen now.

Follow Now : Apple Podcasts / Spotify / Google Podcasts / Amazon Music

Using social media comes with mental health risks, but that doesn’t mean it should be completely avoided. Experts recommend using these networking websites in moderation.

Set a timer when you’re on social media or install an app on your phone or computer that tracks how long you’ve spent on a networking site.

Without these timers or apps, it’s easy to spend hours on social media before you know it. To limit your time on social media, you can also plan real-world activities that help you focus on your immediate surroundings and circumstances. Read a book, watch a movie, go for a stroll, play a game, bake some bread, or have a phone conversation with a friend. Make the time to enjoy life offline.  

Kemp S. More than half of the people on Earth now use social media .

" Social Media and Youth Mental Healt h," The US Surgeon General's Advisory, May 2023.

Lyall LM, Wyse CA, Graham N, et al. Association of disrupted circadian rhythmicity with mood disorders, subjective wellbeing, and cognitive function: A cross-sectional study of 91 105 participants from the UK Biobank . Lancet Psychiatry.  2018;5(6):507-514. doi:10.1016/S2215-0366(18)30139-1

Hunt MG, Marx R, Lipson C, Young J. No more FOMO: Limiting social media decreases loneliness and depression . J Soc Clin Psychol.  2018;37(10):751-768. doi:10.1521/jscp.2018.37.10.751

Tandoc EC, Ferrucci P, Duffy M. Facebook use, envy, and depression among college students: Is facebooking depressing? Comput Hum Behav. 2015;43:139-146. doi:10.1016/j.chb.2014.10.053

Limbana T, Khan F, Eskander N, Emamy M, Jahan N. The association of bullying and suicidality: Does it affect the pediatric population?   Cureus . 2020;12(8). doi:10.7759/cureus.9691

Shearer E. Social media outpaces print newspapers in the U.S. as a news source . Pew Research Center.

Garcia-Navarro L. National Public Radio. Your 'doomscrolling' breeds anxiety. Here's how to stop the cycle .

By Nadra Nittle Nadra Nittle is a Los Angeles-based journalist and author. She has covered a wide range of topics, including health, education, race, consumerism, food, and public policy, throughout her career.  

Every print subscription comes with full digital access

Science News

Social media harms teens’ mental health, mounting evidence shows. what now.

Understanding what is going on in teens’ minds is necessary for targeted policy suggestions

Most teens use social media, often for hours on end. Some social scientists are confident that such use is harming their mental health. Now they want to pinpoint what explains the link.

Carol Yepes/Getty Images

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By Sujata Gupta

February 20, 2024 at 7:30 am

In January, Mark Zuckerberg, CEO of Facebook’s parent company Meta, appeared at a congressional hearing to answer questions about how social media potentially harms children. Zuckerberg opened by saying: “The existing body of scientific work has not shown a causal link between using social media and young people having worse mental health.”

But many social scientists would disagree with that statement. In recent years, studies have started to show a causal link between teen social media use and reduced well-being or mood disorders, chiefly depression and anxiety.

Ironically, one of the most cited studies into this link focused on Facebook.

Researchers delved into whether the platform’s introduction across college campuses in the mid 2000s increased symptoms associated with depression and anxiety. The answer was a clear yes , says MIT economist Alexey Makarin, a coauthor of the study, which appeared in the November 2022 American Economic Review . “There is still a lot to be explored,” Makarin says, but “[to say] there is no causal evidence that social media causes mental health issues, to that I definitely object.”

The concern, and the studies, come from statistics showing that social media use in teens ages 13 to 17 is now almost ubiquitous. Two-thirds of teens report using TikTok, and some 60 percent of teens report using Instagram or Snapchat, a 2022 survey found. (Only 30 percent said they used Facebook.) Another survey showed that girls, on average, allot roughly 3.4 hours per day to TikTok, Instagram and Facebook, compared with roughly 2.1 hours among boys. At the same time, more teens are showing signs of depression than ever, especially girls ( SN: 6/30/23 ).

As more studies show a strong link between these phenomena, some researchers are starting to shift their attention to possible mechanisms. Why does social media use seem to trigger mental health problems? Why are those effects unevenly distributed among different groups, such as girls or young adults? And can the positives of social media be teased out from the negatives to provide more targeted guidance to teens, their caregivers and policymakers?

“You can’t design good public policy if you don’t know why things are happening,” says Scott Cunningham, an economist at Baylor University in Waco, Texas.

Increasing rigor

Concerns over the effects of social media use in children have been circulating for years, resulting in a massive body of scientific literature. But those mostly correlational studies could not show if teen social media use was harming mental health or if teens with mental health problems were using more social media.

Moreover, the findings from such studies were often inconclusive, or the effects on mental health so small as to be inconsequential. In one study that received considerable media attention, psychologists Amy Orben and Andrew Przybylski combined data from three surveys to see if they could find a link between technology use, including social media, and reduced well-being. The duo gauged the well-being of over 355,000 teenagers by focusing on questions around depression, suicidal thinking and self-esteem.

Digital technology use was associated with a slight decrease in adolescent well-being , Orben, now of the University of Cambridge, and Przybylski, of the University of Oxford, reported in 2019 in Nature Human Behaviour . But the duo downplayed that finding, noting that researchers have observed similar drops in adolescent well-being associated with drinking milk, going to the movies or eating potatoes.

Holes have begun to appear in that narrative thanks to newer, more rigorous studies.

In one longitudinal study, researchers — including Orben and Przybylski — used survey data on social media use and well-being from over 17,400 teens and young adults to look at how individuals’ responses to a question gauging life satisfaction changed between 2011 and 2018. And they dug into how the responses varied by gender, age and time spent on social media.

Social media use was associated with a drop in well-being among teens during certain developmental periods, chiefly puberty and young adulthood, the team reported in 2022 in Nature Communications . That translated to lower well-being scores around ages 11 to 13 for girls and ages 14 to 15 for boys. Both groups also reported a drop in well-being around age 19. Moreover, among the older teens, the team found evidence for the Goldilocks Hypothesis: the idea that both too much and too little time spent on social media can harm mental health.

“There’s hardly any effect if you look over everybody. But if you look at specific age groups, at particularly what [Orben] calls ‘windows of sensitivity’ … you see these clear effects,” says L.J. Shrum, a consumer psychologist at HEC Paris who was not involved with this research. His review of studies related to teen social media use and mental health is forthcoming in the Journal of the Association for Consumer Research.

Cause and effect

That longitudinal study hints at causation, researchers say. But one of the clearest ways to pin down cause and effect is through natural or quasi-experiments. For these in-the-wild experiments, researchers must identify situations where the rollout of a societal “treatment” is staggered across space and time. They can then compare outcomes among members of the group who received the treatment to those still in the queue — the control group.

That was the approach Makarin and his team used in their study of Facebook. The researchers homed in on the staggered rollout of Facebook across 775 college campuses from 2004 to 2006. They combined that rollout data with student responses to the National College Health Assessment, a widely used survey of college students’ mental and physical health.

The team then sought to understand if those survey questions captured diagnosable mental health problems. Specifically, they had roughly 500 undergraduate students respond to questions both in the National College Health Assessment and in validated screening tools for depression and anxiety. They found that mental health scores on the assessment predicted scores on the screenings. That suggested that a drop in well-being on the college survey was a good proxy for a corresponding increase in diagnosable mental health disorders. 

Compared with campuses that had not yet gained access to Facebook, college campuses with Facebook experienced a 2 percentage point increase in the number of students who met the diagnostic criteria for anxiety or depression, the team found.

When it comes to showing a causal link between social media use in teens and worse mental health, “that study really is the crown jewel right now,” says Cunningham, who was not involved in that research.

A need for nuance

The social media landscape today is vastly different than the landscape of 20 years ago. Facebook is now optimized for maximum addiction, Shrum says, and other newer platforms, such as Snapchat, Instagram and TikTok, have since copied and built on those features. Paired with the ubiquity of social media in general, the negative effects on mental health may well be larger now.

Moreover, social media research tends to focus on young adults — an easier cohort to study than minors. That needs to change, Cunningham says. “Most of us are worried about our high school kids and younger.” 

And so, researchers must pivot accordingly. Crucially, simple comparisons of social media users and nonusers no longer make sense. As Orben and Przybylski’s 2022 work suggested, a teen not on social media might well feel worse than one who briefly logs on. 

Researchers must also dig into why, and under what circumstances, social media use can harm mental health, Cunningham says. Explanations for this link abound. For instance, social media is thought to crowd out other activities or increase people’s likelihood of comparing themselves unfavorably with others. But big data studies, with their reliance on existing surveys and statistical analyses, cannot address those deeper questions. “These kinds of papers, there’s nothing you can really ask … to find these plausible mechanisms,” Cunningham says.

One ongoing effort to understand social media use from this more nuanced vantage point is the SMART Schools project out of the University of Birmingham in England. Pedagogical expert Victoria Goodyear and her team are comparing mental and physical health outcomes among children who attend schools that have restricted cell phone use to those attending schools without such a policy. The researchers described the protocol of that study of 30 schools and over 1,000 students in the July BMJ Open.

Goodyear and colleagues are also combining that natural experiment with qualitative research. They met with 36 five-person focus groups each consisting of all students, all parents or all educators at six of those schools. The team hopes to learn how students use their phones during the day, how usage practices make students feel, and what the various parties think of restrictions on cell phone use during the school day.

Talking to teens and those in their orbit is the best way to get at the mechanisms by which social media influences well-being — for better or worse, Goodyear says. Moving beyond big data to this more personal approach, however, takes considerable time and effort. “Social media has increased in pace and momentum very, very quickly,” she says. “And research takes a long time to catch up with that process.”

Until that catch-up occurs, though, researchers cannot dole out much advice. “What guidance could we provide to young people, parents and schools to help maintain the positives of social media use?” Goodyear asks. “There’s not concrete evidence yet.”

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The truth about teens, social media and the mental health crisis.

Michaeleen Doucleff

For years, the research picture on how social media affects teen mental health has been murky. That is changing as scientists find new tools to answer the question. Olivier Douliery/AFP via Getty Images hide caption

For years, the research picture on how social media affects teen mental health has been murky. That is changing as scientists find new tools to answer the question.

Back in 2017, psychologist Jean Twenge set off a firestorm in the field of psychology.

Twenge studies generational trends at San Diego State University. When she looked at mental health metrics for teenagers around 2012, what she saw shocked her. "In all my analyses of generational data — some reaching back to the 1930s — I had never seen anything like it," Twenge wrote in the Atlantic in 2017.

Twenge warned of a mental health crisis on the horizon. Rates of depression, anxiety and loneliness were rising. And she had a hypothesis for the cause: smartphones and all the social media that comes along with them. "Smartphones were used by the majority of Americans around 2012, and that's the same time loneliness increases. That's very suspicious," Twenge told NPR in 2017.

But many of her colleagues were skeptical. Some even accused her of inciting a panic with too little — and too weak — data to back her claims.

Now, six years later, Twenge is back. She has a new book out this week, called Generations , with much more data backing her hypothesis. At the same time, several high-quality studies have begun to answer critical questions, such as does social media cause teens to become depressed and is it a key contributor to a rise in depression?

In particular, studies from three different types of experiments, altogether, point in the same direction. "Indeed, I think the picture is getting more and more consistent," says economist Alexey Makarin , at the Massachusetts Institute of Technology.

Shots - Health News

How to help young people limit screen time — and feel better about how they look, a seismic change in how teens spend their time.

In Generations , Twenge analyzes mental health trends for five age groups, from the Silent Generation, who were born between 1925 and 1945, to Gen Z, who were born between 1995 and 2012. She shows definitively that "the way teens spend their time outside of school fundamentally changed in 2012," as Twenge writes in the book.

Take for instance, hanging out with friends, in person. Since 1976, the number of times per week teens go out with friends — and without their parents — held basically steady for nearly 30 years. In 2004, it slid a bit. Then in 2010, it nosedived.

"It was just like a Black Diamond ski slope straight down," Twenge tells NPR. "So these really big changes occur."

At the same time, around 2012, time on social media began to soar. In 2009, only about half of teens used social media every day, Twenge reports. In 2017, 85% used it daily. By 2022, 95% of teens said they use some social media, and about a third say they use it constantly, a poll from Pew Research Center found .

"Now, in the most recent data, 22% of 10th grade girls spend seven or more hours a day on social media," Twenge says, which means many teenage girls are doing little else than sleeping, going to school and engaging with social media.

Not surprisingly, all this screen time has cut into many kids' sleep time. Between 2010 and 2021, the percentage of 10th and 12th graders who slept seven or fewer hours each night rose from a third to nearly one-half. "That's a big jump," Twenge says. "Kids in that age group are supposed to sleep nine hours a night. So less than seven hours is a really serious problem."

Teen girls and LGBTQ+ youth plagued by violence and trauma, survey says

On its own, sleep deprivation can cause mental health issues. "Sleep is absolutely crucial for physical health and for mental health. Not getting enough sleep is a major risk factor for anxiety and depression and self-harm," she explains. Unfortunately, all of those mental health problems have continued to rise since Twenge first sounded the alarm six years ago.

"Nuclear bomb" on teen social life

"Every indicator of mental health and psychological well-being has become more negative among teens and young adults since 2012," Twenge writes in Generations . "The trends are stunning in their consistency, breadth and size."

Across the board, since 2010, anxiety, depression and loneliness have all increased . "And it's not just symptoms that rose, but also behaviors," she says, "including emergency room visits for self-harm, for suicide attempts and completed suicides." The data goes up through 2019, so it doesn't include changes due to COVID-19.

All these rapid changes coincide with what, Twenge says, may be the most rapid uptake in a new technology in human history: the incorporation of smartphones into our lives, which has allowed nearly nonstop engagement with social media apps. Apple introduced the first iPhones in 2007, and by 2012, about 50% of American adults owned a smartphone, the Pew Research Center found .

The timing is hard to ignore, says data scientist Chris Said , who has a Ph.D. in psychology from Princeton University and has worked at Facebook and Twitter. "Social media was like a nuclear bomb on teen social life," he says. "I don't think there's anything in recent memory, or even distant history, that has changed the way teens socialize as much as social media."

Murky picture becomes clearer on causes of teen depression

But the timing doesn't tell you whether social media actually causes depression in teens.

In the past decade, scientists have published a whole slew of studies trying to answer this question, and those studies sparked intense debate among scientists and in the media. But, Said says, what many people don't realize is scientists weren't using — or didn't even have — the proper tools to answer the question. "This is a very hard problem to study," he says. "The data they were analyzing couldn't really solve the problem."

Mental Health

The mental health of teen girls and lgbtq+ teens has worsened since 2011.

So the findings have been all over the place. They've been murky, noisy, inconclusive and confusing. "When you use tools that can't fully answer the question, you're going to get weak answers," he says. "So I think that's one reason why really strong evidence didn't show up in the data, at least early on."

On top of it, psychology has a bad track record in this field, Said points out. For nearly a century, psychologists have repeatedly blamed new technologies for mental and physical health problems of children, even when they've had little — or shady — data to back up their claims.

For example, in the 1940s, psychologists worried that children were becoming addicted to radio crime dramas, psychologist Amy Orben at the University of Cambridge explains in her doctoral thesis. After that, they raised concerns about comic books, television and — eventually — video games. Thus, many researchers worried that social media may simply be the newest scapegoat for children's mental health issues.

A handful of scientists, including MIT's Alexey Makarin, noticed this problem with the data, the tools and the field's past failures, and so they took the matter into their own hands. They went out and found better tools.

Hundreds of thousands of more college students depressed

Over the past few years, several high-quality studies have come that can directly test whether social media causes depression. Instead of being murky and mixed, they support each other and show clear effects of social media. "The body of literature seems to suggest that indeed, social media has negative effects on mental health, especially on young adults' mental health," says Makarin, who led what many scientists say is the best study on the topic to date.

In that study, Makarin and his team took advantage of a once-in-a-lifetime opportunity: the staggered introduction of Facebook across U.S. colleges from 2004 to 2006. Facebook rolled out into society first on college campuses, but not all campuses introduced Facebook at the same time.

For Makarin and his colleagues, this staggered rollout is experimental gold.

"It allowed us to compare students' mental health between colleges where Facebook just arrived to colleges where Facebook had not yet arrived," he says. They could also measure how students' mental health shifted on a particular campus when people started to spend a bunch of their time on social media.

Luckily, his team could track mental health at the time because college administrators were also conducting a national survey that asked students an array of questions about their mental health, including diagnoses, therapies and medications for depression, anxiety and eating disorders. "These are not just people's feelings," Makarin says. "These are actual conditions that people have to report."

They had data on a large number of students. "The data comes from more than 350,000 student responses across more than 300 colleges," Makarin says.

This type of study is called a quasi-experiment, and it allows scientists to estimate how much social media actually changes teens' mental health, or as Makarin says, "We can get causal estimates of the impact of Facebook on mental health."

So what happened? "Almost immediately after Facebook arrives on campus, we see an uptick in mental health issues that students report," Makarin says. "We especially find an impact on depression rates, anxiety disorders and other questions associated with depression in general."

And the effect isn't small, he says. Across the population, the rollout of Facebook caused about 2% of college students to become clinically depressed. That may sound modest, but with more than 17 million college students in the U.S. at the time, that means Facebook caused more than 300,000 young adults to suffer from depression.

For an individual, on average, engaging with Facebook decreases their mental health by roughly 22% of the effect of losing one's job, as reported by a previous meta-analysis, Makarin and his team found.

Facebook's rollout had a larger effect on women's mental health than on men's mental health, the study showed. But the difference was small, Makarin says.

He and his colleagues published their findings last November in the American Economic Review . "I love that paper," says economist Matthew Gentzkow at Stanford University, who was not involved in the research. "It's probably the most convincing study I've seen. I think it shows a clear effect, and it's really credible. They did a good job of isolating the effect of Facebook, which isn't easy."

Of course, the study has limitations, Gentzkow says. First off, it's Facebook, which teens are using less and less. And the version of Facebook is barebones. In 2006, the platform didn't have a "like" button" or a "newsfeed." This older version probably wasn't as "potent" as social media now, says data scientist Chris Said. Furthermore, students used the platform only on a computer because smartphones weren't available yet. And the study only examined mental health impacts over a six-month period.

Nevertheless, the findings in this study bolster other recent studies, including one that Gentzkow led.

Social media is "like the ocean" for kids

Back in 2018, Gentzkow and his team recruited about 2,700 Facebook users ages 18 or over. They paid about half of them to deactivate their Facebook accounts for four weeks. Then Gentzkow and his team looked to see how a Facebook break shifted their mental health. They reported their findings in March 2020 in the American Economic Review.

This type of study is called a randomized experiment, and it's thought of as the best way to estimate whether a variable in life causes a particular problem. But with social media, these randomized experiments have big limitations. For one, the experiments are short-term — here only four weeks. Also, people use social media in clusters, not as individuals. So having individuals quit Facebook won't capture the effect of having an entire social group quit together. Both of these limitations could underestimate the impact of social media on an individual and community.

Nevertheless, Gentzkow could see how deactivating Facebook made people, on average, feel better. "Being off Facebook was positive across well-being outcomes," he says. "You see higher happiness, life satisfaction, and also lower depression, lower anxiety, and maybe a little bit lower loneliness."

Gentzkow and his team measured participants' well-being by giving them a survey at the end of the experiment but also asking questions, via text message, through the experiment. "For example, we sent people text messages that say, 'Right now, would you say you're feeling happy or not happy,'" he explains.

Again, as with Makarin's experiment, the effect was moderate. Gentzkow and his colleagues estimate that temporarily quitting Facebook improves a person's mental health by about 30% of the positive effect seen by going to therapy. "You could view that meaning these effects are pretty big," he explains, "or you could also see that as meaning that the effects of therapy are somewhat small. And I think both of those things are true to an extent."

Scientists still don't know to what extent social media is behind the rising mental health issues among teenagers and whether it is the primary cause. "It seems to be the case — like it's a big factor," says MIT's Alexey Makarin, "but that's still up for debate."

Still, though, other specifics are beginning to crystallize. Scientists are narrowing in on what aspects of social media are most problematic. And they can see that social media won't hurt every teen — or hurt them by the same amount. The data suggests that the more hours a child devotes to social media, the higher their risk for mental health problems.

Finally, some adolescents are likely more vulnerable to social media, and children may be more vulnerable at particular ages. A study published in February 2022 looked to see how time spent on social media varies with life satisfaction during different times in a child's life (see the graphic).

The researchers also looked to see if a child's present use of social media predicted a decrease of life satisfaction one year later. That data suggests two windows of time when children are most sensitive to detrimental effects of social media, especially heavy use of it. For girls, one window occurs at ages 11 through 13. And for boys, one window occurs at ages 14 and 15. For both genders, there's a window of sensitivity around age 19 — or near the time teenagers enter college. Amy Orben and her team at the University of Cambridge reported the findings in Nature Communications .

This type of evidence is known as a correlative. "It's hard to draw conclusions from these studies," Gentzkow says, because many factors contribute to life satisfaction, such as environmental factors and family backgrounds. Plus, people may use social media because they're depressed (and so depression could be the cause, not the outcome of social media use).

"Nevertheless, these correlative studies, together with the evidence from the causal experiments, paint a picture that suggests we should take social media seriously and be concerned," Gentzkow adds.

Psychologist Orben once heard a metaphor that may help parents understand how to approach this new technology. Social media for children is a bit like the ocean, she says, noting that it can be an extremely dangerous place for children. Before parents let children swim in any open water, they make sure the child is well-prepared and equipped to handle problems that arise. They provide safety vests, swimming lessons, often in less dangerous waters, and even then parents provide a huge amount of supervision.

Alyson Hurt created the graphic. Jane Greenhalgh and Diane Webber edited the story.

• mental health
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Does social media use cause depression.

How heavy Instagram and Facebook use may be affecting kids negatively

Writer: Caroline Miller

Clinical Experts: Jerry Bubrick, PhD , Alexandra Hamlet, PsyD

What You'll Learn

• What do we know about the connection between social media use and depression?
• How can using social media affect kids negatively?
• How can parents help kids build healthy social media habits?

Studies show that depression among teenagers and young adults has gotten more common over the past decade. Social media use has also increased during the same time. It’s hard to say for sure that social media causes depression. Still, there are several ways that using social media could harm kids.

Some experts think that connecting with peers online is less emotionally fulfilling than connecting in person. Research shows that teenagers who spend more time on social media also feel more isolated. It could be that kids who already feel isolated use social media more. But it could be that using social media actually makes kids feel isolated.

Another theory is that social media is bad for teenagers’ self-esteem. Seeing lots of perfect pictures online might make kids (especially girls) view themselves negatively. Feeling bad about themselves can lead to depression.

Social media can also cut into the time that kids spend on activities that make them feel good, like exercise and hobbies. Additionally, it can distract from important tasks like homework. Having to juggle those responsibilities can increase kids’ stress. Studies also suggest that using social media at night interferes with restful sleep for many teenagers.

It’s important for parents to check in with kids about their social media use and help them develop healthy habits. You can encourage kids to turn off notifications, spend plenty of time on offline activities that make them feel good, and put phones away before bedtime. You can also set a good example by modeling balance in your own use of social media.

Finally, be sure to keep an eye out for signs of depression and get professional help if you’re worried. It’s especially important to check on kids who are under a lot of stress.

Is using social media making our kids unhappy? Evidence is mounting that there is a link between social media and depression . In several studies, teenage and young adult users who spend the most time on Instagram, Facebook and other platforms were shown to have a substantially (from 13 to 66 percent) higher rate of reported depression than those who spent the least time.

Does that mean that Instagram and TikTok are actually causing depression? These studies show a correlation, not causation. But it’s worth a serious look at how social media could be affecting teenagers and young adults negatively.

One reason the correlation seems more than coincidental is that an increase in depression occurred in tandem with the rise in smartphone use .

A 2017 study of over half a million eighth through 12th graders found that the number exhibiting high levels of depressive symptoms increased by 33 percent between 2010 and 2015. In the same period, the suicide rate for girls in that age group increased by 65 percent.

Smartphones were introduced in 2007, and by 2015 fully 92 percent of teens and young adults owned a smartphone . The rise in depressive symptoms correlates with smartphone adoption during that period, even when matched year by year, observes the study’s lead author, San Diego State University psychologist Jean Twenge, PhD.

Over that same time period there was a sharp spike in reports of students seeking help at college and university counseling centers, principally for depression and anxiety. Visits jumped 30 percent between 2010 and 2015 , and they’ve continued to rise since the pandemic.

Social media and depression

One of the biggest differences in the lives of current teenagers and young adults, compared to earlier generations, is that they spend much less time connecting with their peers in person and more time connecting electronically, principally through social media.

Some experts see the rise in depression as evidence that the connections social media users form electronically are less emotionally satisfying, leaving them feeling socially isolated.

“The less you are connected with human beings in a deep, empathic way, the less you’re really getting the benefits of a social interaction,” points out Alexandra Hamlet, PsyD, a clinical psychologist. “The more superficial it is, the less likely it’s going to cause you to feel connected, which is something we all need.”

Indeed, one exception to the depression correlation is girls who are high users of social media but also keep up a high level of face-to-face social interaction. The Twenge study showed that those girls who interact intensely offline as well as through social media don’t show the increase in depressive symptoms that those who interact less in person do.

And there are some teenagers who aren’t successful in connecting with peers offline, because they are isolated geographically or don’t feel accepted in their schools and local communities. For those kids, electronic connection can be lifesaving.

Social media and perceived isolation

Another study of a national sample of young adults (age 19-32) showed correlation between the time spent on social media and perceived social isolation (PSI). The authors noted that directionality can’t be determined. That is, “Do people feeling socially isolated spend more time on social media, or do more intense users develop PSI?”

If it’s the latter, they noted, “Is it because the individual is spending less time on more authentic social experiences that would decrease PSI? Or is it the nature of observing highly curated social feeds that they make you feel more excluded?”

Which brings us what we now call FOMO, or fear of missing out.

Jerry Bubrick , PhD, a clinical psychologist at the Child Mind Institute, observes that “FOMO is really the fear of not being connected to our social world, and that need to feel connected sometimes trumps whatever’s going on in the actual situation we’re in. The more we use social media, the less we think about being present in the moment.”

Instead we might be occupied with worrying why we weren’t invited to a party we’re seeing on Instagram, or making sure we don’t miss a single post from a friend. But if we’re always playing catch-up to endless online updates, we’re prioritizing social interactions that aren’t as emotionally rewarding and can actually make us feel more isolated.

Social media and self-esteem

Another theory about the increase in depression is the loss of self-esteem , especially in teenage girls, when they c ompare themselves negatively with artfully curated images of those who appear to be prettier, thinner, more popular and richer.

“Many girls are bombarded with their friends posting the most perfect pictures of themselves, or they’re following celebrities and influencers who do a lot of Photoshopping and have makeup and hair teams,” explains Dr. Hamlet. “If that’s their model for what is normal, it can be very hard on their self-confidence.”

Indeed, image-driven Instagram shows up in surveys as the platform that most leads young people to report feeling anxiety, depression and worries about body image.

Curation of a perfect image may not only make others feel inadequate, it’s unhealthy even for those who appear to be successful at it, notes Dr. Bubrick. “Kids spend so much time on social media trying to post what they think the world will think is a perfect life. Look at how happy I am! Look how beautiful I am! Without that they’re worried that their friends won’t accept them. They’re afraid of being rejected.” And if they are getting positive feedback from their social media accounts, they might worry that what their friends like isn’t the “real” them.

Less healthy activity

Another possible source of depression may be what teenagers are not doing during while they’re spending time on social media, including physical activity and things that generate a sense of accomplishment, like learning new skills and developing talents.

“If you’re spending a lot of time on your phone, you have less time for activities that can build confidence, a sense of achievement and connectedness,” explains Dr. Hamlet.

Kids who are spending a lot of time on devices are not getting much in return to make them feel good about themselves, she adds. “Yes, you get a little dopamine burst whenever you get a notification, or a like on a picture, or a follow request. But those things are addicting without being satisfying.”

Disrupted concentration

Another thing disrupted by social media is the process of doing homework and other tasks that require concentration. It’s become common for teenagers to engage with friends on social media at the same time they are studying. They take pride in being able to multi-task, but evidence shows that it cuts down on learning and performance.

“Basically, multitasking isn’t possible,” Dr. Hamlet notes. “What you end up doing is really just switching back and forth between two tasks rather quickly. There is a cost to the brain.” And with poorer concentration and constant interruption, homework takes substantially longer than it should, cutting into free time and adding to stress.

Sleep deprivation and depression

Some of the ways in which social media use impacts mood may be indirect. For instance, one of the most common contributors to depression in teenagers is sleep deprivation , which can be caused, or exacerbated, by social media.

Research shows that 60 percent of adolescents are looking at their phones in the last hour before sleep, and that they get on average an hour less sleep than their peers who don’t use their phones before bed. Blue light from electronic screens interferes with falling asleep ; on top of that, checking social media is not necessarily a relaxing or sleep-inducing activity. Scrolling on social media, notes Dr. Hamlet, can easily end up causing stress.

“Social media can have a profound effect on sleep,” adds Dr. Bubrick. “You have the intention to check Instagram or watch TikTok videos for 5 minutes, and the next thing you know 50 minutes are gone. You’re an hour behind in sleep, and more tired the next day. You find it harder to focus. You’re off your game, and it spirals from there .”

How to minimize negative effects of social media use

While we don’t yet have conclusive evidence that social media use actually causes depression, we do have plenty of warning signs that it may be affecting our kids negatively. So it’s smart for parents to check in regularly with kids about their social media use, to make sure it’s positive and healthy, and guide them towards ways to change it , if you think it’s not.

Also, be alert for symptoms of depression .  If you notice signs that your child might be depressed, take them seriously. Ask your child how they are doing, and don’t hesitate to set up an appointment with a mental health provider .

Steps you can take to ensure healthy social media use:

• Focus on balance: Make sure your kids are also engaging in social interaction offline, and have time for activities that help build identity and self-confidence.
• Turn off notifications: App developers are getting more and more aggressive with notifications to lure users to interrupt whatever they’re doing to engage constantly with their phones. Don’t let them.
• Look out for girls at higher risk of depression: Monitor girls who are going through a particularly tough time or are under unusual stress. Negative effects of social media can have more impact when confidence is down.
• Teach mindful use of social media : Encourage teenagers to be honest with themselves about how time spent on social media makes them feel, and disengage from interactions that increase stress or unhappiness.
• Model restraint and balance in your own media diet: Set an example by disengaging from media to spend quality family time together, including phone-free dinners and other activities. Kids may resist, but they’ll feel the benefits.
• Phone-free time before sleep: Enforce a policy of no smartphones in the bedroom after a specific time and overnight. Use an old-fashioned alarm clock to wake up.

Frequently Asked Questions

Social media has been shown to be correlated with anxiety and depression. This correlation could have to do with teens connecting more online rather than in person, leaving them feeling socially isolated. Teens are also looking at carefully curated images online, which may cause anxiety, low self-esteem, and body image issues.

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Social Networking and Depression Argumentative Essay

• To find inspiration for your paper and overcome writer’s block
• As a source of information (ensure proper referencing)
• As a template for you assignment

Studies show that social networking has a potential of causing depression and the more individuals use social sites, such as Facebook and Twitter, the more they are filled with anxiety leading to depression. In the University of Michigan, a study was conducted with a sample of eighty-two Facebook users in a period of two weeks.

The findings of the study confirmed that once an individual engages in social networking, his or her feeling of safety goes down and depression mood emerges meaning that a correlation between depression and social networking exists (Harris 81). Unlike other forms of social networking, such as chatting with friends, social sites offer invaluable data that are incapable of fulfilling an individual needs, such as security and safety.

If an individual spends more time on Facebook, he or she might end up depressed the whole day because of anxiety (Myers 17). Apart from causing depression, social networking may cause the fear of missing out because an individual feels rejected and neglected once his or her message or information is not taken positively. Some users may criticize the views of an individual, yet no chance is given to defend the idea.

While on Facebook or Twitter, an individual feels inadequate or insufficient because one person might post a good picture showing magnificent vacation, luxurious purchases, and gorgeous children. In case an individual does not have the means to achieve his or her ambitions, he or she might be jealous and might be resentful since good things are happening in the lives of others while suffering might be the characteristic of his or her life.

In a different study conducted in Sweden at the University of Gothenburg that interviewed 111 Facebook users, it was established that internet networking has an effect on the self-esteem of an individual, as well as his relationships with others (Noor and Hendricks 64). Individuals spending more time on Facebook and other social sites have low sense of worth.

Additionally, social networking causes narcissism because users spend too much time and resources for decoration of their pictures and modifying their profiles in order to gain approval and praise. If an individual posts a status update on Facebook or Twitter and no person is interested in commenting, there would be a high likelihood that an individual will be worried because he will not understand some of the reasons why others are reluctant to respond.

Scholars, artists, politicians, and other professionals might be tempted to post something related to their achievements, such as published works or won award. Such individuals would be affected greatly in case someone decides to post something negative (Noor and Hendricks 67). Many people end up spending sleepless nights because of a negative comment that someone posted on Facebook or Twitter.

Continued usage of the social media contributes to the erosion of true relationships because it is difficult for individuals to interact face-to-face, as the traditional form of interaction is being replaced by shallow and meaningless online connections. Studies show that this is damaging the well-being of society since human need for true relationship is difficult to find (Myers 48).

Since individuals are incapable of finding authentic relationships and love, they tend to turn to the social sites for consolation. Instead of being comforted, the social media only serves one purpose that is related to depression and mental illnesses. In the modern society, it is common to find an idle person on Fcaebook or Twitter since it is believed to keep a person active.

The modern society is characterized by uncertainties and disappointments and people report all these in the social sites. For instance, of all the internet users, one or two people will report losing a job or breaking up a relationship. Again, the death of an individual will always be noticed, particularly when the person is famous.

Through the social sites, an individual realizes that it is so easy to lose a job or break up in a relationship, something that brings about anxiety. If the death of a famous person is reported, sadness mood comes in because there would be a feeling of loss. Some internet users develop a culture of judging others, irrespective of whether their post is accurate or not. In other words, they simply spread propaganda and falsehood once they realize that their ambition cannot be realized (Myers 75).

For instance, one person might fail to convince another to enter into a deal or relationship. Instead of accepting the outcome and moving on, he or she would go a notch higher to comment negatively on the social media, something that might attract a penalty or revenge. In many parts of the world, online wars are widespread whereby individuals are unwilling to concede defeat and continue with lives.

This has brought about many challenges because a negative comment is given to an individual with children and a stable family. Recently, a picture of a famous politician engaging extra marital relationships was posted on the social media, yet the leader has children and a good family (Kaplan and Haenlein 68). This causes depression to many people who feel disappointed and cheated. Even though the information posted might be inaccurate, it would be difficult for other users to change their minds once they have the picture.

In order to network with a friend, a social media user must send a friend request and wait for a response. An individual will definitely be depressed in case a response is not sent in time. Social networking isolates an individual from the rest of the community because most of the time is spent chatting with online friends who might have nothing to add to an individual’s life. Many young people are simply interested with popularity and they believe that having many friends in Facebook or Twitter makes them more famous.

In reality, this does not add any value to life because friendship has to be of high quality meaning that adequate assistance can be offered when necessary. An individual with many friends on Twitter or Facebook tends to believe that he or she is illustrious, but most likely will be disappointed in a time of need because not all online friends will ever care about what is happening to the life of one member (Harris 101).

They will simply express their sadness, which might not be genuine, yet the individual would be in need of emotional and psychological support. Therefore, social networking is believed to be harmful to the well-being of the individual in society because it does not add value to life (Myers 88). Additionally, it is established that a strong correlation between social networking and depression exists and it is upon the individual to control internet usage.

Works Cited

Harris, Kandace. “Using Social Networking Sites as Student Engagement Tools.” Diverse Issues in Higher Education, 25.18 (2008): 88-112. Print.

Kaplan, Andreas, and Haenlein, Michael. “Users of the world, unite! The challenges and opportunities of social media”. Business Horizons, 53.1 (2010): 61-98. Print.

Myers, David. Social Psychology . New York: McGraw-Hill Higher Education, 2012. Print.

Noor, Al-Deen, and Hendricks, John. Social Media: Usage and Impact . Lanham: Lexington Books, 2012. Print.

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Does Social Media Use Increase Depressive Symptoms? A Reverse Causation Perspective

Andree hartanto.

1 Singapore Management University, Singapore, Singapore

Frosch Y. X. Quek

Germaine y. q. tng, jose c. yong.

2 Nanyang Technological University, Singapore, Singapore

According to the World Health Organization ( 1 ), 264 million individuals worldwide suffer from depression—a condition characterized by feelings of low self-worth, impaired concentration, and disturbed sleep, among various other maladaptive symptoms ( 2 ). Adolescents between 13 and 18 years of age are also vulnerable ( 3 ), with a 52% increase in the prevalence of depression among adolescents from 2005 to 2017 ( 4 ). Depression is tied to many serious problems including failure to complete education, higher unplanned parenthood rates, poorer interpersonal relations, and heightened risk of substance abuse and suicidality ( 5 – 7 ).

Researchers seeking to understand this prevalence of depression in modern society have identified social media use as a key risk factor ( 8 , 9 ). Underscoring the ubiquity of social media in people's lives today, 3.8 billion people in the world are active users of at least one social networking site ( 10 ). Cross-sectional and correlational trend analyses appear to show increases in depression rates alongside increased social media engagement [( 9 , 11 – 14 ); also see ( 15 ), for a contrasting result]. Although the link between social media use and depression is contentious ( 16 , 17 ), several have nonetheless implicated social media as pervasive and detrimental to psychological well-being. For instance, some studies have been argued that social media may harm users by exposing them to negative stimuli such as unwholesome content, cyberbullying, unhealthy social comparisons, and feelings of inferiority ( 18 , 19 ).

However, there are good reasons to suspect that these conclusions are premature or incorrect. For instance, the haste to pass social media a guilty verdict might stem from moral panic brought about by the fear of contemporary technology ( 20 ), where the third-person effect in which individuals overattribute certain behaviors to the influence of mass communication ( 21 ) is a possible catalyst. Having such a convenient culprit for depression seriously oversimplifies our understanding of the etiology surrounding social media and depression ( 12 ).

Several lines of reasoning also suggest that the direction of social media causing depression might instead be reversed. The heavy reliance on correlational data severely limits our ability to infer directionality and argue that exposure to social media causes depression ( 11 , 22 ). Some theories also indicate that depressive symptoms drive social media use. According to the theory of compensatory internet use ( 23 ), people may view online activities such as social media as a means to alleviate negative feelings or fulfill unmet psychosocial needs. For example, an individual suffering from depressive symptoms may turn to social networking sites for social validation through gaining likes and followers. The sociocognitive model of internet addiction ( 24 ) similarly proposes that because online and social media stimuli can be psychologically rewarding, people are incentivized to stay engaged, but those with poorer self-regulation (e.g., individuals with psychological disorders) are especially susceptible to developing harmful social media habits. The tendency for social media use to be precipitated by psychosocial problems like low self-esteem, insecurity, and depression also makes sense from an evolutionary perspective. As highly social creatures, humans evolved a desire for belonging and social acceptance ( 25 ), which is facilitated by social monitoring motives to detect cues for social approval or rejection ( 26 ). Individuals who are insecure about being accepted are motivated to seek information that may reaffirm their social status, leading to an obsession with social comparisons and other social diagnostic cues ( 27 ). Thus, the evolutionary perspective suggests that social media can hijack our evolved tendency to monitor for social cues and perceive social information as rewarding ( 28 ), and depressed individuals are especially vulnerable to being sucked in by social media as they experience a stronger need to alleviate feelings of insecurity, low self-worth, or hopelessness. These arguments from multiple perspectives provide compelling justification to take the reverse association more seriously.

Evidence for Reverse Causality in the Relationship between Social Media and Depressive Symptoms

Considering that increased social media use may be an outcome of depressiveness rather than an antecedent, what does the available data show? Here, we critically examine the literature and consider the evidence from longitudinal and experimental studies.

Longitudinal Findings

While longitudinal designs alone do not provide grounds for causal conclusions, they at least allow the temporal ordering of key variables to be determined ( 29 ). Several recent longitudinal studies show null or even disconfirming evidence for social media as a precedent of depression. For instance, Jensen et al. ( 30 ) found that baseline frequency of social media use did not predict increased daily depressive symptoms at 1- to 2-year follow-up in a demographically representative sample of adolescents. More prolonged studies spanning 8 or 9 years have further corroborated the view that frequency of social media use does not longitudinally predict depressive symptoms in adolescents even when studied across developmental periods from adolescence to young adulthood ( 31 , 32 ). Further, using a longitudinal panel design on a sample of American adults, Hampton ( 33 ) showed that social media use was in fact associated with reduced psychological distress due to the social opportunities afforded by social networking sites.

Some recent longitudinal studies have also shown that depressive symptoms may precede escalated social media use. For instance, Heffer et al. ( 34 ) followed samples of adolescents and undergraduates over 2 and 6 years, respectively, and demonstrated that depressive symptoms preceded increased social media use among female adolescents, while social media usage did not precede depressive symptoms across both samples. Similarly, Raudsepp and Kais's ( 35 ) 2-year study of adolescent girls revealed that baseline levels of depressive symptoms predicted problematic social media use, whereas prior social media use did not predict depressive symptoms. Examining the within-person effects of depressive symptoms on increased social media use over 6 years during early and late adolescence, Puukko et al. ( 36 ) found that depressive symptoms predicted increases in social media use for both boys and girls. Conversely, social media use was not found to predict depressive symptoms.

A bidirectional relationship may also exist due to a cascading feedback loop whereby depression engenders compensatory social media use, which in turn aggravates depressive symptoms due to unhealthy social comparisons and other detrimental forms of social interaction ( 37 , 38 ). Raudsepp ( 39 ) pointed to this bidirectionality by showing that problematic social media use (i.e., using social media in an unhealthy or maladaptive manner) predicted depressive symptoms over a span of 2 years. Thus, researchers who focus only on the depressive effect of social media use may neglect important predisposing factors that cause certain individuals to use social media problematically. Together, the longitudinal evidence suggests that claims that exposure to social media leads to depressive symptoms might be exaggerated, and the reverse relationship whereby depressiveness prompts more (and unhealthy) social media use has been overlooked.

Experimental Findings

Although longitudinal designs can ascertain temporal ordering, they do not rule out confounding or third variables that may influence or obscure the relationship between depressive symptoms and social media engagement. Meta-analyses of cross-sectional studies on social media use and depression also report small pooled effect sizes ( 9 , 11 , 12 ), suggesting the presence of extraneous variables. To address issues of causality and control, we consider experimental research on the social media-depression link.

Most if not all experimental studies of this relationship have manipulated social media use to isolate their effects on depression-related outcomes, probably because (1) this is easier to do than the reverse—manipulating participants' depressiveness and observing their social media behavior, and (2) the approach of blaming social media dominates over other theoretical approaches. However, experimental results do not support the view that social media use increases depression-related outcomes. For instance, Hall et al. ( 40 ) manipulated social media use by randomly assigning undergraduates to varying durations of abstinence (0, 2, 3, and 4 weeks) and found that social media abstention did not account for changes in loneliness or subjective well-being [see ( 41 ) for similar finding]. Moreover, Vally and D'Souza ( 42 ) showed that a week-long abstinence from social media led to reduced life satisfaction and increased negative affect and perceived stress.

Other experiments suggest that regulated usage rather than complete abstinence may be key to managing the psychological effects of social media. For example, Hunt et al. ( 43 ) demonstrated that limiting social media use to 30 min daily alleviated loneliness and depressive symptoms over a span of 3 weeks. Pointing to the modulating role of individual differences, Turel et al. ( 44 ) found that a week of social media abstinence reduced perceived stress levels, but only for excessive social media users. This result highlights the importance of accounting for antecedents of problematic social media use, such as depressive tendencies or other predispositions, otherwise psychological outcomes as a function of social media use remains unclear.

Discussion and Future Directions

The modern pervasiveness of social media use has prompted considerable research effort to understand its psychological repercussions. Much of this work is lamentably correlational, but despite the inability to deduce causality from such data, many researchers have proceeded to point at social media for today's increased rates of depression while ignoring the reverse possibility that depressiveness may, in fact, explain increased social media use. As we described, longitudinal and experimental methods that allow us to probe temporality and causality reveal not so much that social media triggers depressive symptoms, but more so that (1) initial levels of depression-related symptoms predict prospective social media use, and (2) social media engagement that is already problematic (i.e., unhealthy usage caused by some other antecedent factor) exacerbates depression-related outcomes.

To achieve a fuller picture of the social media-depression link as well as a better understanding of how to combat depression, research needs to move toward a deeper analysis of the factors underlying problematic social media activity, such as risk factors for depression that lead to unhealthy social media use. Some considerations include the tendency for individuals with certain predispositions (e.g., depression, low self-esteem, perfectionism) to view social media as a means to reaffirm their self-worth through social comparisons and seeking social validation ( 23 ). More severely depressed or stressed individuals may also view social media as a means of escape and spend excessive periods of time aimlessly browsing social networking sites ( 45 ). It is thus necessary to understand the factors that push individuals toward unhealthy social media behavior, in which social media use is more a symptom than a cause.

Although emerging research hints at the role of depression in maladaptive social media use, the available data is meager given the lack of studies guided by the reverse causal direction. Aside from broadly calling for more tests of the effects of depressive symptoms on social media use, we also offer several specific suggestions for further research. First, longitudinal studies should go beyond general measures of social media use (e.g., frequency) and examine more fine-grained, qualitative features of social media participation, such as purposes of use, active vs. passive engagement, and degree of addiction or problematic use, which have exhibited asynchronous associations with depressive symptoms ( 46 ). For instance, depressive mood has been found to be associated less with active social media use (e.g., commenting, messaging) and more with passive social media use [e.g., scrolling; ( 47 )]. Second, although retrospective self-reports of adolescents' social media use are most commonly employed, they may be biased and suffer from underestimation ( 48 ). Hence, future longitudinal work should employ objective data logs or screen-time apps as measures of social media frequency ( 49 ). Third, longitudinal studies should follow participants over a longer time span and incorporate multiple time points ( 50 ) to provide a sufficient window for substantive changes in social media use. Fourth, experimental studies manipulating social media abstention should include an equivalent “placebo abstinence” condition to adjust for extraneous confounds, such as expectancies and loss of personal control ( 51 ). Lastly, given the considerable implications of findings from this research direction for adolescents' technology-use regulations and mental health, it is crucial that scholars embrace open scientific practices, such as pre-registration and utilization of the open science framework, to encourage future replications and rigorous reviews that can advance our understanding of how social media use and depressive symptoms are connected ( 52 ).

In conclusion, the current paper argued that the reverse causal view that depressiveness drives social media use has been neglected in current research. By emphasizing the need for longitudinal and experimental approaches to ascertain directionality, a better grasp of the dynamics that govern depressive symptoms and maladaptive social media use can be attained.

Author Contributions

AH conceptualized the manuscript. AH, FQ, GT, and JY wrote the manuscript and contributed to critical revision of the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding. This research was supported by the Ministry of Education Academy Research Fund Tier 1, awarded to AH by Singapore Management University (20-C242-SMU-001).

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The Dark Side of Social Media: An Overview

Extended usage of social networking sites (SNS) could be linked to depressive symptoms and indicators. Read below to know more.

Dr. Ayushi Yogendra Singh

Medically reviewed by

Dr. Vipul Chelabhai Prajapati

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Introduction

Social media is a powerful ally for FOMO (fear of missing out) in the digital era. Social media sites provide well-controlled peeks into the lives of others, ranging from glamorous social gatherings to jealously inciting holiday photographs, which can exacerbate feelings of inadequacy and isolation. Psychologists must comprehend the relationship between FOMO, social media, anxiety, and depression. This investigation explores the various facets, impacts, advantages and disadvantages, coping mechanisms, and the critical need for intervention to promote a positive connection with social media.

What Are the Fear of Missing Effects on Mental Health?

Although there is undoubtedly a benefit to it, namely

Social Connectivity: Social media makes connections easier and keeps users informed about their friends' lives and happenings. However, it has a drawback known as unrealistic comparisons. Social media's selective nature encourages erroneous social comparisons, which heightens feelings of inadequacy.

Digital Addiction: Constantly checking social media can lead to digital addiction , which can have a detrimental effect on mental health.

What Is the Connection Between Depression, Anxiety, FOMO, and Social Media?

Social Comparison Theory: People often judge themselves by the accomplishments of others, a tendency that is exacerbated by social media and causes worry.

The Highlight Reel Effect: Seeing other people's greatest events all the time distorts perspective and exacerbates depression symptoms.

The Significance of FOMO: FOMO is a psychological phenomenon with significant effects on mental health, not merely a fad. Persistent FOMO can worsen anxiety and despair, which can set off a vicious cycle of dissatisfaction and social disengagement.

What Are the Busting Myths About Depression, Anxiety, Social Media, and FOMO?

Many myths have surfaced, spreading false beliefs about the complex relationship between social media , anxiety, depression , and FOMO, as the nuanced interplay between these factors continues to be explored. To promote a more sophisticated understanding of the influence of social media on mental health, these fallacies must be dispelled.

Myth 1: FOMO is Just a Trend and Not Very Important.

FOMO the reality of missing out is not a fleeting fad. It is a real psychological phenomenon that has significant effects on mental health and frequently exacerbates despair and anxiety.

Myth 2: FOMO Is Exclusive to Teens

FOMO, or the reality of missing out, is ageless. Fear of losing out on social occasions, chances, and experiences affects adults, professionals, and people of all ages.

Myth 3: There Is No Neutral Place for Social Media.

Social media is not an impartial platform. These platforms' carefully chosen material and incessant comparison-making lead to increased anxiety and depression symptoms.

Myth 4: Social Media Is the Only Source of FOMO.

Social media exacerbates the fear of missing out (FOMO), but it also affects other facets of life, including opportunities for career advancement, personal experiences, and social gatherings.

Myth 5: Envy is Not the Cause of Anxiety or Depression.

FOMO-induced envy can lead to anxiety and melancholy. Regular exposure to allegedly idealized lifestyles exacerbates mental health problems and fosters a poor self-image.

Myth 6: FOMO Is Exclusive to Extroverts.

The fear of missing out impacts both introverted and outgoing people. A common issue is the fear of social marginalization or missing out on important events.

Myth 7: Happiness Is Found on Social Media.

The edited version of reality shown on social media is the reality of missing out. People may put up a happy front while going through difficult times on the inside, which can lead to a skewed view of other people's lives.

Myth 8: Reducing Screen Time Alleviates FOMO.

Although digital detoxes have their advantages, the underlying causes of FOMO are not always addressed by them. It necessitates a more thorough strategy that incorporates mental health techniques and mindful consumption.

Myth 9: Quit feeling FOMO; It Is a Choice.

The actuality of being left out of FOMO is a complicated emotional reaction that is shaped by both personal vulnerabilities and cultural forces. It is not as easy as picking whether or not to feel it.

Myth 10: Using Social Media To Combat Loneliness.

Social media makes people connected, but it does not always make loneliness go away. When people contrast their lives with those of others, it might exacerbate social isolation. In order to address the complex relationship between FOMO, social media, anxiety, and depression, it is imperative to comprehend the truth underlying these beliefs. Psychologists can help people navigate the digital world more intelligently and compassionately while putting their mental health first by busting these myths.

How to Reduce the Bad Impacts of Using Social Media?

Although there is not enough proof to say that using social media leads to depression just yet, there are many indicators that our children may be suffering as a result of it. Thus, it is a good idea for parents to periodically enquire about their children's usage of social media to ensure that it is constructive and healthy and to help them find alternatives if necessary. Keep an eye out for depressive signs as well. It is important to take the child's depression seriously if one has any symptoms. Enquire about the child's well-being, and do not be afraid to schedule a meeting with a mental health professional.

What One Can Do to Make Sure Social Media Use Is In Moderation?

Maintain a balance by ensuring that the children participate in offline social interactions and make time for activities that foster self-worth and identity development.

Switch off the notifications. App developers are becoming more and more pushy with their notifications, hoping to entice users to drop what they are doing and spend all of their time on their phones. Keep them from doing so.

Be mindful of girls who are more susceptible to depression: Keep an eye on girls who seem to be experiencing extra stress or a particularly difficult period in their lives. When confidence is low, the negative effects of social media can be more pronounced.

Instruct them in the thoughtful use of social media: Ask them to be frank with themselves about how using social media makes them feel.

Practice moderation and harmony in the media intake: Set a good example by putting down the phone during dinners and other family events and spending time together without it.

Before going to bed, establish a rule prohibiting the use of cell phones in the bedroom after a certain hour and all night. To wake up, set the alarm clock back in time.

In conclusion, the last ten years have seen a substantial shift in how individuals engage and communicate, thanks to online social networking. Whether some of these alterations impact typical facets of human behavior and result in mental illnesses is unknown, though. Further investigation is required to determine and characterize any possible association between the usage of social networking sites and different mental health problems in the future.

Social Media and Mental Health

https://www.helpguide.org/articles/mental-health/social-media-and-mental-health.htm

Online Social Networking and Mental Health

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4183915/

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The effect of social anxiety on student interactions in asynchronous online discussion forums as mediated by social presence and moderated by anonymity

• Published: 29 August 2024

Cite this article

• Omer Demir   ORCID: orcid.org/0000-0002-4178-0221 1 ,
• Sinan Keskin   ORCID: orcid.org/0000-0003-0483-3897 2 &
• Murat Cinar   ORCID: orcid.org/0000-0003-4012-4174 3  

2 Altmetric

Pervasive internet use in higher education has rendered social anxiety a lesser problem in circumventing interactions. However, the attenuation of vitality in interactions still remains a contentious issue, especially in asynchronous online discussions. This study aims to elucidate how anonymity and social presence affect the relationship between avoidance of interaction and peer and content interaction in online discussions. In the true experimental study, we recruited 123 first-year university students, of which 62 were randomly assigned to the anonymous group, and 61 to the identified group. This paper adopts a moderated mediation model, in which anonymity and social presence are included as moderator and mediator, respectively. We revealed that the “straightforward” relationship between avoidance of interaction and peer and content interaction is actually highly complex. The results substantiate a full mediation of social presence and moderation of anonymity in favor of disclosed identity. This study accentuates the critical role of social presence in fostering interactions. The results also suggest that disclosing discussants’ identities might be useful during asynchronous interactions in online discussions for increasing social presence only if their avoidance of interaction is low; in the case of a high avoidance of interaction, anonymity should be preferred.

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All data analyzed during the current study are available from the corresponding author upon reasonable request.

Afolabi, R. O. (2016). Emphasizing instructor presence in digital learning environments. In S. D’Agustino (Ed.), Creating teacher immediacy in online learning environments (pp. 37–54). IGI Global Press. https://doi.org/10.4018/978-1-4666-9995-3.ch003

Aguinis, H., Beaty, J. C., Boik, R. J., & Pierce, C. A. (2005). Effect size and power in assessing moderating effects of categorical variables using multiple regression: A 30-year review. Journal of Applied Psychology , 90 , 94–107. https://doi.org/10.1037/0021-9010.90.1.94

Article   Google Scholar  

Altman, D. G., & Bland, J. M. (2011). How to obtain the P value from a confidence interval. Bmj , 343 . https://doi.org/10.1136/bmj.d2304 . Article d2304.

Alwin, D. F., & Hauser, R. M. (1975). The decomposition of effects in path analysis. American Sociological Review , 40 , 37–47. https://doi.org/10.2307/2094445

American Psychiatric Association (APA). (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington.

Anderson, T. (2005, January). Distance learning—Social software’s killer app? [Paper presentation] Proceedings of the Open & Distance Learning Association (ODLAA) of Australia, Adelaide, Australia. https://auspace.athabascau.ca/handle/2149/2328

Andrews, J. (1980). The verbal structure of teacher questions: Its impact on class discussion. POD Quarterly: Journal of Professional and Organizational Development Network in Higher Education , 2 (3 & 4), 129–163.

Google Scholar  

Arbaugh, J. B., Cleveland-Innes, M., Diaz, S. R., Garrison, D. R., Ice, P., Richardson, J. C., & Swan, K. P. (2008). Developing a community of inquiry instrument: Testing a measure of the community of inquiry framework using a multi-institutional sample. The Internet and Higher Education , 11 (3–4), 133–136. https://doi.org/10.1016/j.iheduc.2008.06.003

Archbell, K. A., & Coplan, R. J. (2021). Too anxious to talk: Social anxiety, academic communication, and students’ experiences in higher education. Journal of Emotional and Behavioral Disorders . https://doi.org/10.1177/10634266211060079

Baggetun, R., & Mjelstad, S. (2006). eLogg: Facilitating ownership and openness in virtual learning environments. Educational Informational Technology , 11 , 357–369. https://doi.org/10.1007/s10639-006-9006-4

Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology , 51 (6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173

Berry, W. D. (1993). Understanding regression assumptions . Sage. https://psycnet.apa.org/record/1993-97970-000

Bradley, M. E., Thom, L. R., Hayes, J., & Hay, C. (2008). Ask and you will receive: How question type influences quantity and quality of online discussions. British Journal of Educational Technology , 39 (5), 888–900. https://doi.org/10.1111/j.1467-8535.2007.00804.x

Chang, J. (2008). The role of anonymity in deindividuated behavior: A comparison of deindividuation theory and the social identity model of deindividuation effects (SIDE). The Pulse: Undergraduate Journal of Baylor University , 6 (1), 1–8.

Chen, L. T., & Liu, L. P. (2020). Social presence in multidimensional online discussion: The roles of group size and requirements for discussions. Computers in the Schools , 37 (2), 116–140. https://doi.org/10.1080/07380569.2020.1756648

Chen, B., & Poquet, O. (2023). Uncovering socio-temporal dynamics in online discussions: An event-based approach. Australasian Journal of Educational Technology , 39 (6), 1–16. https://doi.org/10.14742/ajet.8618

Christopherson, K. M. (2007). The positive and negative implications of anonymity in internet social interactions:On the internet, nobody knows you’re a. Dog Computers in Human Behavior , 23 (6), 3038–3056. https://doi.org/10.1016/j.chb.2006.09.001

Clark, D. M., & Wells, A. (1995). A cognitive model of social phobia. In R. Heimberg, M. Liebowitz, D. A. Hope, & F. R. Schneier (Eds.), Socialphobia: Diagnosis, assessment, and treatment (pp. 69–93). Guilford Press.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences . Erlbaum.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Erlbaum.

Covelli, B. J. (2017). Online discussion boards: The practice of building community for adult learners. Journal of Continuing Higher Education , 65 (2), 139–145. https://doi.org/10.1080/07377363.2017.1274616

Creed, A. T., & Funder, D. C. (1998). Social anxiety: From the inside and outside. Personality and Individual Differences , 25 (1), 19–33. https://doi.org/10.1016/S0191-8869(98)00037-3

Delahunty, J. (2012). Who am I?’: Exploring identity in online discussion forums. International Journal of Educational Research , 53 , 407–420. https://doi.org/10.1016/j.ijer.2012.05.005

Delgado, B., Ingles, C. J., & Garcia-Fernandez, J. M. (2013). Social anxiety and self-concept in adolescence. Revista De Psicodidactica , 18 (1), 179–195. https://doi.org/10.1387/RevPsicodidact.6411

DeSchryver, M., Mishra, P., Koehleer, M., & Francis, A. (2009, March 02). Moodle vs. Facebook: Does using Facebook for discussions in an online course enhance perceived social presence and student interaction? In I. Gibson, R. Weber, K. McFerrin, R. Carlsen, & D. Willis (Eds.), Proceedings of SITE 2009 - Society for information technology & teacher education international conference (pp. 329–336). Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA. https://www.learntechlib.org/p/30612.

Dron, J., Seidel, C., & Litten, G. (2004). Transactional distance in a blended learning environment. Research in Learning Technology , 12 (2), 163–174. https://doi.org/10.3402/rlt.v12i2.11249

Durlak, J. (2009). How to select, calculate, and interpret effect sizes. Journal of Pediatric Psychology , 34 (9), 917–928. https://doi.org/10.1093/jpepsy/jsp004

Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Methods , 12 (1), 1–22. https://doi.org/10.1037/1082-989X.12.1.1

Ellis, P. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results . Cambridge University Press.

Ensmann, S., Whiteside, A., Gomez-Vasquez, L., & Sturgill, R. (2021). Connections before curriculum: The role of social presence during COVID-19 emergency remote learning for students. Online Learning , 25 (3), 36–56. https://doi.org/10.24059/olj.v25i3.2868

Fehrman, S., & Watson, S. L. (2021). A systematic review of asynchronous online discussions in online higher education. American Journal of Distance Education , 35 (3), 200–213. https://doi.org/10.1080/08923647.2020.1858705

Felnhofer, A., Hlavacs, H., Beutl, L., Kryspin-Exner, I., & Kothgassner, O. D. (2019). Physical presence, social presence, and anxiety in participants with social anxiety disorder during virtual cue exposure. Cyberpsychology Behavior and Social Networking , 22 (1), 46–50. https://doi.org/10.1089/cyber.2018.0221

Fraenkel, J. R., Wallen, N. E., & Hyun, H. N. (2019). How to design and evaluate research in education (10th ed.). McGraw-Hill.

Freedman, L. S. (2001). Confidence intervals and statistical power of the Validation ratio for surrogate or intermediate endpoints. Journal of Statistical Planning and Inference , 96 , 143–153. https://doi.org/10.1016/S0378-3758(00)00330-X

Fritz, M. S., & MacKinnon, D. P. (2007). Required sample size to detect the mediated effect. Psychological Science , 18 (3), 233–239.

Fritz, C. O., Morris, P. E., & Richler, J. J. (2012). Effect size estimates: Current use, calculations, and interpretation. Journal of Experimental Psychology: General , 141 (1), 2–18. https://doi.org/10.1037/a0024338

Fritz, M. S., Kenny, D. A., & MacKinnon, D. P. (2016). The combined effects of measurement error and omitting confounders in the single-mediator model. Multivariate Behavioral Research , 51 (5), 681–697. https://doi.org/10.1080/00273171.2016.1224154

Zimbardo, P. G. (1969). The human choice: Individuation, reason, and order, vs deindividuation, impulse, and chaos. Nebraska Symposium on Motivation , 17 , 237–307. https://psycnet.apa.org/record/1971-08069-001

Garrison, D. R., & Arbaugh, J. B. (2007). Researching the community of inquiry framework: Review, issues, and future directions. The Internet and Higher Education , 10 (3), 157–172. https://doi.org/10.1016/j.iheduc.2007.04.001

Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education , 2 (2–3), 87–105. https://doi.org/10.1016/S1096-7516(00)00016-6

Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of Distance Education , 15 (1), 7–23. https://doi.org/10.1080/089236401095270710

Gerard, P. D., Smith, D. R., & Weerakkody, G. (1998). Limits of retrospective power analysis. Journal of Wildlife Management , 62 (2), 801–807. https://doi.org/10.2307/3802357

Giesbers, B., Rienties, B., Tempelaar, D. T., & Gijselaers, W. (2014). Why increased social presence through web video conferencing does not automatically lead to improved learning. E-Learning and Digital Media , 11 (1), 31–45. https://doi.org/10.2304/elea.2014.11.1.31

Gorsky, P., & Caspi, A. (2005). A critical analysis of transactional distance theory. Quarterly Review of Distance Education , 6 (1), 1–11.

Guo, C., Shea, P., & Chen, X. D. (2022). Investigation on graduate students’ social presence and social knowledge construction in two online discussion settings. Education and Information Technologies , 27 (2), 2751–2769. https://doi.org/10.1007/s10639-021-10716-8

Hasani, L. M., Santoso, H. B., & Junus, K. (2022). Designing asynchronous online discussion forum interface and interaction based on the community of inquiry framework. The International Review of Research in Open and Distributed Learning , 23 (2), 191–213. https://doi.org/10.19173/irrodl.v23i2.6016

Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs , 76 (4), 408–420. https://doi.org/10.1080/03637750903310360

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach . Guilford Press.

Hayes, A. F. (2015). An index and test of linear moderated mediation. Multivariate Behavioral Research , 50 (1), 1–22. https://doi.org/10.1080/00273171.2014.962683

Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis third edition a regression-based approach (3rd ed.). Guildford.

Hayes, A. F., & Cai, L. (2007). Using heteroskedasticity-consistent standard error estimators in OLS regression: An introduction and software implementation. Behavior Research Methods , 39 (4), 709–722. https://doi.org/10.3758/BF03192961

Hayes, A. F., & Preacher, K. J. (2013). Conditional process modeling: Using structural equation modeling to examine contingent causal processes. In G. R. Hancock, & R. O. Mueller (Eds.), Structural equation modeling: A second course (2nd ed., pp. 219–266). IAP Information Age.

Hayes, A. F., & Rockwood, N. J. (2020). Conditional process analysis: Concepts, computation, and advances in the modeling of the contingencies of mechanisms. American Behavioral Scientist , 64 (1), 19–54. https://doi.org/10.1177%2F0002764219859633

Hayes, A. F., & Scharkow, M. (2013). The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter? Psychological Science , 24 , 1918–1927. https://doi.org/10.1177/0956797613480187

Heimberg, R. G., Horner, K. J., Juster, H. R., Safren, S. A., Brown, E. J., Schneier, F. R., & Liebowitz, M. R. (1999). Psychometric properties of the Liebowitz Social Anxiety Scale. Psychological Medicine , 29 (1), 199–212. https://doi.org/10.1017/s0033291798007879

Hoey, R. (2017). Examining the characteristics and content of instructor discussion interaction upon student outcomes in an online course. Online Learning , 21 (4), 268–281. https://doi.org/10.24059/olj.v21i4.1075

Holland, S. J., Shore, D. B., & Cortina, J. M. (2017). Review and recommendations for integrating mediation and moderation. Organizational Research Methods , 20 (4), 686–720. https://doi.org/10.1177/1094428116658958

Horzum, M. B. (2015). Interaction, structure, social presence, and satisfaction in online learning. Eurasia Journal of Mathematics Science and Technology Education , 11 (3), 505–512. https://doi.org/10.12973/eurasia.2014.1324a

Hoyle, R. H., & Kenny, D. A. (1999). Statistical power and tests of mediation. In R. H. Hoyle (Ed.), Statistical strategies for small sample research (pp. 195–222). Sage.

Huang, X., Chandra, A., DePaolo, C. A., & Simmons, L. L. (2016). Understanding transactional distance in web-based learning environments: An empirical study. British Journal of Educational Technology , 47 (4), 734–747. https://doi.org/10.1111/bjet.12263

Hutchins, N., Allen, A., Curran, M., & Kannis-Dymand, L. (2021). Social anxiety and online social interaction. Australian Psychologist , 56 (2), 142–153. https://doi.org/10.1080/00050067.2021.1890977

Igartua, J. J., & Hayes, A. F. (2021). Mediation, moderation, and conditional process analysis: Concepts, computations, and some common confusions. The Spanish Journal of Psychology , 24 . https://doi.org/10.1017/SJP.2021.46 . Article e49.

Jhangiani, R. S., Chiang, I. C. A., Cuttler, C., & Leighton, D. C. (2019). Research methods in psychology (4th Ed.). Kwantlen Polytechnic University. https://kora.kpu.ca/islandora/object/kora%3A640/datastream/PDF/view

Johnson, C. S. (2017). Collaborative technologies, higher order thinking and self-sufficient learning: A case study of adult learners. Research in Learning Technology , 25 . https://doi.org/10.25304/rlt.v25.1981

Johnston, R., Jones, K., & Manley, D. (2018). Confounding and collinearity in regression analysis: A cautionary tale and an alternative procedure, illustrated by studies of British voting behaviour. Quality & Quantity , 52 (4), 1957–1976. https://doi.org/10.1007/s11135-017-0584-6

Jong, B. S., Lai, C. H., Hsia, Y. T., & Lin, T. W. (2012). Effects of anonymity in group discussion on peer interaction and learning achievement. IEEE Transactions on Education , 56 (3), 292–299. https://doi.org/10.1109/TE.2012.2217379

Kang, X., & Zhang, W. (2023). An experimental case study on forum-based online teaching to improve student’s engagement and motivation in higher education. Interactive Learning Environments , 31 (2), 1029–1040. https://doi.org/10.1080/10494820.2020.1817758

Kashdan, T. B. (2002). Social anxiety dimensions, neuroticism, and the contours of positive psychological functioning. Cognitive Therapy and Research , 26 (6), 789–810. https://doi.org/10.1023/A:1021293501345

Kashdan, T. B., Elhai, J. D., & Breen, W. E. (2008). Social anxiety and disinhibition: An analysis of curiosity and social rank appraisals, approach-avoidance conflicts, and disruptive risk-taking behavior. Journal of Anxiety Disorder , 22 (6), 925–939. https://doi.org/10.1016/j.janxdis.2007.09.009

Kenny, D. A. (2018). Moderator variables: Introduction. https://davidakenny.net/cm/moderation.htm

Kenny, D. A. (2021). Mediation. https://davidakenny.net/cm/mediate.htm#COMP

Kenny, D. A., & Judd, C. M. (2014). Power anomalies in testing mediation. Psychological Science , 25 , 334–339. https://doi.org/10.1177/0956797613502676

Keskin, S., Şahin, M., Uluç, S., & Yurdugul, H. (2023). Online learners’ interactions and social anxiety: The social anxiety scale for e-learning environments (SASE). Interactive Learning Environments , 31 (1), 201–213. https://doi.org/10.1080/10494820.2020.1769681

Kobayashi, M. (2020). Does anonymity matter? Examining quality of online peer assessment and students’ attitudes. Australasian Journal of Educational Technology , 36 (1), 98–110. https://doi.org/10.14742/ajet.4694

Kreijns, K., Xu, K., & Weidlich, J. (2022). Social presence: Conceptualization and measurement. Educational Psychology Review , 34 , 139–170. https://doi.org/10.1007/s10648-021-09623-8

Lance, C. E., Butts, M. M., & Michels, L. C. (2006). The sources of four commonly reported cutoff criteria: What did they really say? Organizational Research Methods , 9 (2), 202–220. https://doi.org/10.1177/1094428105284919

Lasekan, O. A., Pachava, V., Godoy Pena, M. T., Golla, S. K., & Raje, M. S. (2024). Investigating factors influencing students’ engagement in sustainable online education. Sustainability , 16 (2), 689. https://doi.org/10.3390/su16020689

Leary, M. R., & Kowalski, R. M. (1997). Social anxiety . Guilford Press.

Lee, S. J., & Huang, K. (2018). Online interactions and social presence in online learning. Journal of Interactive Learning Research , 29 (1), 113–128. https://www.learntechlib.org/primary/p/173242

Lefcheck, J. (2021). Composite variables . https://jslefche.github.io/sem_book/index.html

Lord, G., & Lomicka, L. (2007). Foreign language teacher preparation and asynchronous CMC: Promoting reflective teaching. Journal of Technology and Teacher Education , 15 (4), 513–532. https://eric.ed.gov/?id=EJ774184

McCarney, R., Warner, J., Iliffe, S., Van Haselen, R., Griffin, M., & Fisher, P. (2007). The Hawthorne effect: A randomised, controlled trial. BMC Medical Research Methodology , 7 (30), 1–8. https://doi.org/10.1186/1471-2288-7-30

McClelland, G. H., & Judd, C. M. (1993). Statistical difficulties of detecting interactions and moderator effects. Psychological Bulletin , 114 , 376–390. https://doi.org/10.1037/0033-2909.114.2.376

Miyazoe, T., & Anderson, T. (2011). Anonymity in blended learning: Who would you like to be? Journal of Educational Technology & Society , 14 (2), 175–187. https://www.jstor.org/stable/jeductechsoci.14.2.175

Moore, M. G. (1993). Theory of transactional distance. In D. Keegan (Ed.), Theoretical principles of distance education (pp. 22–38). Routledge.

Moore, M. G., & Kearsley, G. (2013). Distance education: A systems view of online learning (3rd ed.). Cengage Learning.

Morse, M. L. (2021). Increase engaged student learning using Google Docs as a discussion platform. Teaching & Learning Inquiry , 9 (2). https://doi.org/10.20343/teachlearninqu.9.2.20

Nakagawa, S., & Foster, T. M. (2004). The case against retrospective statistical power analyses with an introduction to power analysis. Acta Ethologica , 7 (2), 103–108. https://doi.org/10.1007/s10211-004-0095-z

Nor, N. F. M., Hamat, A., & Embi, M. A. (2012). Patterns of discourse in online interaction: Seeking evidence of the collaborative learning process. Computer Assisted Language Learning , 25 (3), 237–256. https://doi.org/10.1080/09588221.2012.655748

Oh, C. S., Bailenson, J. N., & Welch, G. F. (2018). A systematic review of social presence: Definition, antecedents, and implications. Frontiers in Robotics and AI , 5 , e114. https://doi.org/10.3389/frobt.2018.00114

Oh, H. J., Kim, J., Chang, J. J. C., Park, N., & Lee, S. (2023). Social benefits of living in the metaverse: The relationships among social presence, supportive interaction, social self-efficacy, and feelings of loneliness. Computers in Human Behavior , 139 , 107498. https://doi.org/10.1016/j.chb.2022.107498

Oztok, M., Zingaro, D., Brett, C., & Hewitt, J. (2013). Exploring asynchronous and synchronous tool use in online courses. Computers & Education , 60 (1), 87–94. https://doi.org/10.1016/j.compedu.2012.08.007

Öztürk, E. (2012). An adaptation of the community of inquiry index: The study of validity and reliability. Elementary Education Online , 11 (2), 408–422. https://dergipark.org.tr/en/download/article-file/90583

Pais Marden, M., & Herrington, J. (2022). Asynchronous text-based communication in online communities of foreign language learners: Design principles for practice. Australasian Journal of Educational Technology , 38 (2), 83–97. https://doi.org/10.14742/ajet.7370

Pala, F. K., & Erdem, M. (2020). Development of a participation style scale for online instructional discussions. Educational Technology Research and Development , 68 (6), 3213–3233. https://doi.org/10.1007/s11423-020-09817-x

Paul, R. C., Swart, W., Zhang, A. M., & MacLeod, K. R. (2015). Revisiting Zhang’s scale of transactional distance: Refinement and validation using structural equation modeling. Distance Education , 36 (3), 364–382. https://doi.org/10.1080/01587919.2015.1081741

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology , 88 (5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Polat, N., Mancilla, R., & Mahalingappa, L. (2013). Anonymity and motivation in asynchronous discussions and L2 vocabulary learning. Language Learning & Technology , 17 (2), 57–74.

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods , 40 , 879–891. https://doi.org/10.3758/BRM.40.3.879

Preacher, K. J., & Kelley, K. (2011). Effect size measures for mediation models: Quantitative strategies for communicating indirect effects. Psychological Methods , 16 (2), 93–115. https://doi.org/10.1037/a0022658

Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research , 42 (1), 185–227. https://doi.org/10.1080/00273170701341316

Quong, J., Snider, S. L., & Early, J. (2018). Reducing transactional distance in online and blended courses through the use of a closed social media platform. Journal of Educational Technology Systems , 47 (1), 79–100. https://doi.org/10.1177/0047239518766654

Rapee, R. M., & Heimberg, R. G. (1997). A cognitive-behavioral model of anxiety in social phobia. Behavior Research and Therapy , 35 (8), 741–756. https://doi.org/10.1016/s0005-7967(97)00022-3

Rinck, M., Rörtgen, T., Lange, W. G., Dotsch, R., Wigboldus, D. H. J., & Becker, E. S. (2010). Social anxiety predicts avoidance behaviour in virtual encounters. Cognition and Emotion , 24 (7), 1269–1276. https://doi.org/10.1080/02699930903309268

Roach, V. A., & Attardi, S. M. (2021). Twelve tips for applying Moore’s theory of transactional distance to optimize online teaching. Medical Teacher . https://doi.org/10.1080/0142159X.2021.1913279

Roberts, L. D., & Rajah-Kanagasabai, C. J. (2013). I’d be so much more comfortable posting anonymously: Identified versus anonymous participation in student discussion boards. Australasian Journal of Educational Technology , 29 (5), 612–625. https://doi.org/10.14742/ajet.452

Ryu, E., & Cheong, J. (2017). Comparing indirect effects in different groups in single-group and multi-group structural equation models. Frontiers in Psychology , 8 . https://doi.org/10.3389/fpsyg.2017.00747 . Article e747.

Samuels-Peretz, D. (2014). Ghosts, stars, and learning online: Analysis of interaction patterns in student online discussions. International Review of Research in Open and Distributed Learning , 15 (3), 50–71. https://doi.org/10.19173/irrodl.v15i3.1641

Savin, N. E., & White, K. J. (1977). The Durbin-Watson test for serial correlation with extreme sample sizes or many regressors. Econometrica: Journal of the Econometric Society , 45 (8), 1989–1996. https://doi.org/10.2307/1914122

Schaefer, T., Rahn, J., Kopp, T., Fabian, C. M., & Brown, A. (2019). Fostering online learning at the workplace: A scheme to identify and analyse collaboration processes in asynchronous discussions. British Journal of Educational Technology , 50 (3), 1354–1367. https://doi.org/10.1111/bjet.12617

Sharma, S., Durand, R. M., & Gur-Arie, D. (1981). Identification and analysis of moderator variables. Journal of Marketing Research , 18 , 291–300. https://doi.org/10.2307/3150970

Siemsen, E., Roth, A., & Oliveira, P. (2010). Common method bias in regression models with linear, quadratic, and interaction effects. Organizational Research Methods , 13 (3), 456–476. https://doi.org/10.1177/1094428109351241

Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. In S. Leinhart (Ed.), Sociological methodology (pp. 290–312). Jossey-Bass.

Spencer, S. J., Zanna, M. P., & Fong, G. T. (2005). Establishing a causal chain: Why experiments are often more effective than mediational analyses in examining psychological processes. Journal of Personality and Social Psychology , 89 (6), 845–851. https://doi.org/10.1037/0022-3514.89.6.845

Sung, E., & Mayer, R. E. (2012). Five facets of social presence in online distance education. Computers in Human Behavior , 28 (5), 1738–1747. https://doi.org/10.1016/j.chb.2012.04.014

Suresh, K. P. (2011). An overview of randomization techniques: An unbiased assessment of outcome in clinical research. Journal of Human Reproductive Sciences , 4 (1), 8–11.  https://doi.org/10.4103/0974-1208.82352

Swan, K., Garrison, D. R., & Richardson, J. C. (2009). A constructivist approach to online learning: The community of inquiry framework. In C. Payne (Ed.), Information technology and constructivism in higher education: Progressive learning frameworks (pp. 43–57). IGI Global. https://doi.org/10.4018/978-1-60566-654-9.ch004

Topham, P., & Russell, G. (2012). Social anxiety in higher education. The Psychologist , 25 (4), 280–282.

Vanek, J., King, K., & Bigelow, M. (2018). Social presence and identity: Facebook in an English language classroom. Journal of Language Identity & Education , 17 (4), 236–254. https://doi.org/10.1080/15348458.2018.1442223

Veerman, A. (2000). Computer-supported collaborative learning through argumentation. (Doctoral dissertation). Universiteit Utrecht.

Vygotsky, L. (1978). Mind in society: Development of higher psychological processes . Harvard University Press.

Wang, D. C., Jeng, Y. L., Chiang, C. M., & Huang, Y. M. (2022). Exploring the cohesion of classroom community from the perspectives of social presence and social capital. Journal of Computing in Higher Education , 34 (1), 39–59. https://doi.org/10.1007/s12528-021-09277-z

Williams, M. N., Grajales, C. A. G., & Kurkiewicz, D. (2013). Assumptions of multiple regression: Correcting two misconceptions. Practical Assessment Research and Evaluation , 18(1) . https://doi.org/10.7275/55hn-wk47

Ye, D., & Pennisi, S. (2022). Analysing interactions in online discussions through social network analysis. Journal of Computer Assisted Learning , 38 (3), 784–796. https://doi.org/10.1111/jcal.12648

Yilmaz, R., & Olpak, Y. Z. (2016). The adaptation study of revised scale of transactional distance. Bartın University Journal of Faculty of Education , 5 (3), 718–731. https://dergipark.org.tr/tr/pub/buefad/issue/24921/263076

Yoon, C., & Rolland, E. (2012). Knowledge-sharing in virtual communities: Familiarity, anonymity and self-determination theory. Behaviour & Information Technology , 31 (11), 1133–1143. https://doi.org/10.1080/0144929X.2012.702355

Yzerbyt, V., Muller, D., Batailler, C., & Judd, C. M. (2018). New recommendations for testing indirect effects in mediational models: The need to report and test component paths. Journal of Personality and Social Psychology , 115 , 929–943. https://doi.org/10.1037/pspa0000132

Zhao, H., Sullivan, K. P., & Mellenius, I. (2014). Participation, interaction and social presence: An exploratory study of collaboration in online peer review groups. British Journal of Educational Technology , 45 (5), 807–819. https://doi.org/10.1111/bjet.12094

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Demir, O., Keskin, S. & Cinar, M. The effect of social anxiety on student interactions in asynchronous online discussion forums as mediated by social presence and moderated by anonymity. J Comput High Educ (2024). https://doi.org/10.1007/s12528-024-09412-6

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