The impacts of social media on youth self-image
In the age of smartphones and constant connectivity, social media has become an integral part of the lives of today's youth. While social media platforms provide various benefits, they also wield a profound influence on youth self-image. Clinical therapists Samantha Gonzalez AMFT, APCC, and Alyssa Acosta, APCC, lead the Adolescent Partial Hospital Program at Loma Linda University Behavioral Health. Together, they break down the impact of social media on the self-perception and mental well-being of young individuals, shedding light on the challenges they face in maintaining a healthy self-image in a digital age.
The Illusion of Perfection
One of the primary ways social media affects youth self-image is through the propagation of an idealized and often unattainable standard of beauty.
"Social media platforms are flooded with meticulously curated profiles, showcasing seemingly perfect lives, flawless appearances, and ideal bodies,” Acosta says. “This constant exposure to images of seemingly perfect individuals can lead young people to develop unrealistic expectations about their own appearance and life achievements.”
She says comparing oneself to these distorted representations can lead to feelings of inadequacy, lowered self-esteem, and even body dysmorphia.
Seeking Validation and Social Approval
The proliferation of social media has also fueled the need for validation and social approval among young people. The number of likes, comments, and followers has become a measure of self-worth, amplifying the pressure to present an idealized version of oneself online. Acosta says the desire for external validation can lead to the adoption of unhealthy behaviors such as excessive self-promotion, seeking attention through provocative images or posts, and even resorting to online bullying or negative comparisons to others.
Cyberbullying and Negative Feedback Loops
Reports show 16% of high school students experienced cyberbullying. Social media platforms can provide grounds for cyberbullying and negative feedback loops, which can have devastating consequences for youth self-image, according to Gonzalez Unlike face-to-face interactions, online platforms enable anonymity and distance, emboldening individuals to engage in hurtful behavior. Gonzalez says negative comments, cyberbullying, and online harassment can have a profound impact on a young person's self-esteem, leading to feelings of worthlessness, depression, and anxiety. The constant exposure to such negativity can create a toxic cycle, further exacerbating their mental well-being.
Comparison and Fear of Missing Out
Youth today are bombarded with constant updates on the lives of their peers through social media. The fear of missing out can intensify when scrolling through posts about parties, travel, achievements, or milestones.
“This incessant comparison can foster a sense of dissatisfaction with one's own life and accomplishments, leading to a negative self-perception,” Acosta says. “The curated nature of social media feeds often fails to represent the full spectrum of experiences and emotions, reinforcing an unrealistic sense of what a ‘successful’ or ‘fulfilled’ life should look like.”
Nurturing a Healthy Self-Image
While social media can have detrimental effects on youth self-image, it is important to remember that it is not inherently negative. Gonzalez and Acosta say there are ways to mitigate the negative impacts and promote a healthier self-perception among young individuals:
- Media literacy: Educating youth about the influence of social media and promoting critical thinking skills can help them discern between reality and the illusion of perfection.
- Setting boundaries: Encouraging young people to set limits on their social media usage and prioritize offline activities can foster a healthier balance.
- Positive reinforcement: Recognizing and celebrating achievements, talents, and qualities beyond social media metrics can reinforce a sense of self-worth based on internal validation.
- Promoting open communication: Creating a safe space where young people feel comfortable discussing their concerns about self-image and social media can provide valuable support.
- Diverse representation: Encouraging the promotion and celebration of diverse body types, ethnicities, abilities, and accomplishments on social media can challenge narrow beauty standards and inspire a more inclusive self-image.
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The Impact of Social Media on Body Image, Eating, and Health
Emerging research suggests social media may be more harmful than we realize..
Posted February 8, 2022 | Reviewed by Hara Estroff Marano
- Social media use is on the rise, with over 70 percent of Americans regularly online.
- Social media and dating apps are potentially harmful to users, both emotionally and physically.
- Researchers have found negative effects on body image, eating behavior, mood, and physical health.
- Future research is required to better understand current findings and to determine how to safeguard healthy use of social media..
Social media captivates like nothing else, drawing us into a kaleidoscope of digitally mediated relationships, information and disinformation, and an endless experience of virtual window shopping. We don't always know what we are buying, however.
We’ve embarked on a vast social experiment without giving much thought to how it will play out. The scope of the problem is hard to overstate—between 2005 and 2021, as reported by the Pew Research Center, the average number of Americans regularly using social media has gone from 5 percent to over 70 percent, and rising.
Mirror, Mirror
As the science-fiction quality of the metaverse (described by Neal Stephenson in his classic 1992 novel Snow Crash ) becomes a reality, there is no question that what it means to be human is shifting, with uncertainty, promise, and peril.
More than anything, social media has become a mirror through which we catch a glimpse of ourselves, literally through selfies and photos taken by others, and through how we react to one another, through our experience of online connectedness both on major social media platforms as well as through dating apps and live interactive online events—and through the prospect of fully immersive experiences in virtual reality, within which we can take on any identity we wish in a world freed from the laws of physics and logic.
Researchers, too, have been paying attention to social media, how the digital migration to living online more than in the real world is affecting people. From concerns that we are becoming more pathologically narcissistic , immersed in our smartphone realities where we present a sugar-coated version of ourselves while comparing ourselves to impossibly perfect, processed images of others and their glamorous lives, to getting ground down through the virtual meat market of online dating, to losing critical attachment skills required for intimate relationships, to the potential effect on physical health, to the effects on political systems and global stability, the need to understand what social media is doing to us is more pressing now than ever before.
With the above in mind, four recent studies highlight emerging correlations between social media and dating app use and health outcomes.
Mathew and colleagues (2022) sought to understand how social media use may lead to body dissatisfaction. Following a group of over 6,000 adults (about 60 percent women, average age in their early 50s, ranging from 19-92 years old) and using standardized measures, researchers asked participants about social media use, body dissatisfaction, body mass index (BMI), and a range of demographic variables. They followed them over the course of several years, starting in 2015, to determine whether social media use predicted future body dissatisfaction.
They found that increased social media use predicted body dissatisfaction one year later, and body dissatisfaction also predicted greater social media use, with a small but significant effect size. There were differences between men and women: Social media use and body dissatisfaction worked both ways for women, but for men, while body satisfaction predicted social media use, the reverse was not true in this sample. Being younger, female, and having a higher BMI were associated with greater body image dissatisfaction.
Portingalea and colleagues focused on how women’s dating app use affected daily mood, body image, and eating behavior. Nearly 300 women ranging in age from 18 to 48 participated in this study, completing a baseline survey of lifetime dating app use, partner preference with a focus on whether they sought idealized or realistic partners in terms of physical traits, and the degree of their own rejection sensitivity related to looks. Researchers followed them with a smartphone-based assessment daily for one week, rating daily experiences of body dissatisfaction, disordered eating urges (e.g. to binge eat), and mood.
One-third of participants showed a correlation between lifetime dating app use and both disordered eating urges and negative mood. Neither idealized partner preference nor rejection sensitivity were correlated with eating or mood in this study.
Carter and colleagues looked at whether the coherence of sense of self, known as “ self-concept clarity”, influenced social media users to compare themselves with online depictions of idealized slender bodies. Near 500 women aged 18 to 25 participated in this study, completing a measure of self-concept clarity and body image dissatisfaction, rating experimental images showing either idealized bodies or neutral comparisons.
Participants with lower self-concept clarity compared themselves more with idealized body images and consequently reported greater body image dissatisfaction. The findings suggest that having a less well-developed sense of self increases the risk of negative reactions when browsing social media.
Lee and colleagues recruited 251 undergraduate students for a landmark early study looking at how physical health may be affected by the stress associated with social media use. In addition to demographic information, participants completed a composite measure of social media use, focusing on Snapchat, Instagram, Twitter, and Facebook, to estimate total social media load.
The Patient Health Questionnaire (PHQ15) was used for somatic symptoms (such as headache, body aches, and chest pain), as well as depression . Participants' use of health care was assessed based on how many times they’d visited a health center or physician’s office, or otherwise sought medical care for a medical condition, in the prior three months. Data were collected before the COVID-19 pandemic. Finally, participants’ blood was drawn and tested for C-reactive protein (CRP), a common marker of inflammation.
They found that greater social media use was associated with increased somatic symptoms, regardless of depression symptoms. Greater social media use was associated with more healthcare visits, also independent of depression. Finally, controlling for other factors (demographics, birth control use, depression, healthcare use), CRP levels were significantly elevated among those reporting greater social media use.
A Call to Action?
Emerging research on social media use is concerning. Social media use is associated with negative psychological and general health outcomes, ranging from body-image dissatisfaction, problematic eating, greater healthcare utilization for physical symptoms, and potential negative effects on physiology (e.g. increased inflammatory blood markers). The observation that low self-concept clarity leaves users vulnerable to body-image dissatisfaction is noteworthy; low self-concept clarity has also been associated with difficulty leaving unsatisfying relationships .
Future research is needed to replicate or refute these findings, to map out the exact mechanisms by which social media may adversely impact health, and to work out ways in which social media may be useful and even help improve physical and emotional health.
Social media and internet dating companies interested in the public good can use these data to ensure that the tools they provide are not causing harm—and preferably to improve users' health. As the public becomes more aware of the pros and cons of social media use, market forces are likely to increase the demand for companies to work on behalf of customers while also looking to the bottom line.
As families and individuals make choices about social media, it is of critical importance that they be armed with up-to-date information about the impact of such behavior on health and well-being. For parents, this research adds to the growing body of cautionary information and is a call to get educated and manage social media immersion. For healthcare providers, assessing patients for social media use is a key element of treatment planning.
This research shows that it’s not only younger folks who are at risk from social media but also adults across the lifespan. There's no denying that social media and all the other promises of evolving information technology and machine learning hold great potential to improve quality of life, but only if we slow down and study the effect of these spectacular new tools and learn to use them wisely.
Mathew D. Marques, Susan J. Paxton, Siân A. McLean, Hannah K. Jarman, Chris G. Sibley, A prospective examination of relationships between social media use and body dissatisfaction in a representative sample of adults, Body Image, Volume 40, 2022, Pages 1-11, ISSN 1740-1445, https://doi.org/10.1016/j.bodyim.2021.10.008 .
Jade Portingale, Matthew Fuller-Tyszkiewicz, Shanshan Liu, Sarah Eddy, Xinyue Liu, Sarah Giles, Isabel Krug, Love me Tinder: The effects of women’s lifetime dating app use on daily body dissatisfaction, disordered eating urges, and negative mood, Body Image, Volume 40, 2022, Pages 310-321, ISSN 1740-1445, https://doi.org/10.1016/j.bodyim.2022.01.005 .
David S. Lee, Tao Jiang, Jennifer Crocker, and Baldwin M. Way.Cyberpsychology, Behavior, and Social Networking.ahead of print http://doi.org/10.1089/cyber.2021.0188
Jeanne J. Carter, Lenny R. Vartanian, Self-concept clarity and appearance-based social comparison to idealized bodies, Body Image, Volume 40, 2022, Pages 124-130, ISSN 1740-1445, https://doi.org/10.1016/j.bodyim.2021.12.001 .
Grant Hilary Brenner, M.D., a psychiatrist and psychoanalyst, helps adults with mood and anxiety conditions, and works on many levels to help unleash their full capacities and live and love well.
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How social media can crush your self-esteem
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Sabrina Laplante does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.
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We all have a natural tendency to compare ourselves to others, whether intentionally or not, online or offline. Such comparisons help us evaluate our own achievements , skills, personality and our emotions. This, in turn, influences how we see ourselves.
But what impact do these comparisons have on our well-being? It depends on how much comparing we do.
Comparing ourselves on social media to people who are worse off than we are makes us feel better . Comparing ourselves to people who are doing better than us, however, makes us feel inferior or inadequate instead . The social media platform we choose also affects our morale, as do crisis situations like the COVID-19 pandemic.
As a PhD student in psychology, I am studying incels — men who perceive the rejection of women as the cause of their involuntary celibacy. I believe that social comparison, which plays as much a role in these marginal groups as it does in the general population, affects our general well-being in the age of social media.
An optimal level of comparison
The degree of social comparison that individuals carry out is thought to affect the degree of motivation they have. According to a study by researchers at Ruhr University in Bochum, Germany, there is an optimal level of perceived difference between the self and others that maximizes the effects of social comparison.
Specifically, if we see ourselves as vastly superior to others, we will not be motivated to improve because we already feel that we are in a good position. Yet, if we perceive ourselves as very inferior, we will not be motivated to improve since the goal seems too difficult to achieve.
In other words, the researchers note, beyond or below the optimal level of perceived difference between oneself and another, a person no longer makes any effort. By perceiving oneself as inferior, the individual will experience negative emotions, guilt and lowered pride and self-esteem.
Unrealistic comparisons on social media
Social comparisons therefore have consequences both for our behaviour and for our psychological well-being. However, comparing yourself to others at a restaurant dinner does not necessarily have the same effect as comparing yourself to others on Facebook. It is easier to invent an exciting existence or embellish certain aspects of things on a social media platform than it is in real life .
The advent of social media, which allows us to share content where we always appear in our best light, has led many researchers to consider the possibility that this amplifies unrealistic comparisons.
Research shows that the more time people spend on Facebook and Instagram, the more they compare themselves socially. This social comparison is linked, among other things, to lower self-esteem and higher social anxiety.
A study conducted by researchers at the National University of Singapore explains these results by the fact that people generally present positive information about themselves on social media. They can also enhance their appearance by using filters, which create the impression that there is a big difference between themselves and others.
In turn, researchers working at Facebook observed that the more people looked at content where people were sharing positive aspects of their lives on the platform, the more likely they were to compare themselves to others .
COVID-19: Less negative social comparison
However, could the effect of this comparison in a particularly stressful context like the COVID-19 pandemic be different?
A study from researchers at Kore University in Enna, Italy, showed that before lockdowns, high levels of online social comparison were associated with greater distress, loneliness and a less satisfying life. But this was no longer the case during lockdowns .
One reason for this would be that by comparing themselves to others during the lockdown, people felt they were sharing the same difficult experience. That reduced the negative impact of social comparisons. So, comparing oneself to others online during difficult times can be a positive force for improving relationships and sharing feelings of fear and uncertainty.
A different effect depending on the social media
There are distinctions to be made depending on which social media platform a person is using. Researchers at the University of Lorraine, France, consider that social media platforms should not be all lumped together .
For example, the use of Facebook and Instagram is associated with lower well-being, while Twitter is associated with more positive emotions and higher life satisfaction. One possible explanation: Facebook and Instagram are known to be places for positive self-presentation, unlike Twitter, where it is more appropriate to share one’s real opinions and emotions.
Trying to get social support on social media during the COVID-19 pandemic may reactivate negative emotions instead of releasing them, depending on which social media platform a person is using.
Many things motivate us to compare ourselves socially. Whether we like it or not, social media exposes us to more of those motivations. Depending on the type of content that is being shared, whether it is positive or negative, we tend to refer to it when we are self-evaluating. Sharing content that makes us feel good about ourselves and garners praise from others is nice, but you have to consider the effect of these posts on others.
Yet overall, I believe that sharing your difficulties in words, pictures or videos can still have positive effects and bring psychological benefits.
This article was originally published in French
- Social media
- Relationships
- Life satisfaction
- Social anxiety disorder
- Coronavirus
- Self-esteem
- Uncertainty
- psychological well-being
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Social Media Use and Adolescents’ Self-Esteem: Heading for a Person-Specific Media Effects Paradigm
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Patti Valkenburg, Ine Beyens, J Loes Pouwels, Irene I van Driel, Loes Keijsers, Social Media Use and Adolescents’ Self-Esteem: Heading for a Person-Specific Media Effects Paradigm, Journal of Communication , Volume 71, Issue 1, February 2021, Pages 56–78, https://doi.org/10.1093/joc/jqaa039
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Eighteen earlier studies have investigated the associations between social media use (SMU) and adolescents’ self-esteem, finding weak effects and inconsistent results. A viable hypothesis for these mixed findings is that the effect of SMU differs from adolescent to adolescent. To test this hypothesis, we conducted a preregistered three-week experience sampling study among 387 adolescents (13–15 years, 54% girls). Each adolescent reported on his/her SMU and self-esteem six times per day (126 assessments per participant; 34,930 in total). Using a person-specific, N = 1 method of analysis (Dynamic Structural Equation Modeling), we found that the majority of adolescents (88%) experienced no or very small effects of SMU on self-esteem (−.10 < β < .10), whereas 4% experienced positive (.10 ≤ β ≤ .17) and 8% negative effects (−.21 ≤ β ≤ −.10). Our results suggest that person-specific effects can no longer be ignored in future media effects theories and research.
An important developmental task that adolescents need to accomplish is to acquire self-esteem, the positive and relative stable evaluation of the self. Adolescents’ self-esteem is an important predictor of a healthy peer attachment ( Gorrese & Ruggieri, 2013 ), psychological well-being ( Kernis, 2005 ), and success later in life ( Orth & Robins, 2014 ). In the past decade, a growing number of studies have investigated how adolescents’ social media use (SMU) may affect their self-esteem. Adolescents typically spend 2–3 hours per day on social media to interact with their peers and exchange feedback on their messages and postings ( Valkenburg & Piotrowski, 2017 ). Peer interaction and feedback on the self, both bedrock features of social media, are important predictors of adolescent self-esteem ( Harter, 2012 ). Therefore, understanding the effects of SMU on adolescents’ self-esteem is both important and opportune.
To our knowledge, 18 earlier studies have tried to assess the relationship between SMU and adolescents’ general self-esteem (e.g., Woods & Scott, 2016 ) or their domain-specific self-esteem (e.g., social self-concept; Blomfield Neira & Barber, 2014 ; Košir et al., 2016 ; Valkenburg et al., 2006 ). The ages of the adolescents included in these studies ranged from eight to 19 years. Fifteen of these studies are cross-sectional correlational (e.g., Cingel & Olsen, 2018 ; Meeus et al., 2019 ), two are longitudinal ( Boers et al., 2019 ; Valkenburg et al., 2017 ), and one is experimental ( Thomaes et al., 2010 ). Some of these studies have reported positive effects of SMU on self-esteem (e.g., Blomfield Neira & Barber, 2014 ), others have yielded negative effects (e.g., Woods & Scott, 2016 ), and yet others have found null effects (e.g., Košir et al., 2016 ). It is no wonder that the two meta-analyses on the relationship of SMU and self-esteem have identified their pooled relationships as “close to 0” ( Huang, 2017 , p. 351), “puzzling,” and “complicated” ( Liu & Baumeister, 2016 , p. 85).
While this earlier work has yielded important insights, it leaves two important gaps that may explain these weak effects and inconsistent results. A first gap involves the time frame in which SMU and self-esteem have been assessed in previous studies. Inherent to their design, the cross-correlational studies have measured SMU and self-esteem concurrently, at a single point in time. The two longitudinal studies have assessed both variables at three or four times, with one-year lags, with the aim to establish the potential longer-term effects of SMU on self-esteem ( Boers et al., 2019 ; Valkenburg et al., 2017 ). However, both developmental (e.g., Harter, 2012 ) and self-esteem theories (e.g., Rosenberg, 1986 ) argue that, in addition to such longer-term effects, adolescents’ self-esteem can fluctuate on a daily or even hourly basis as a result of their positive or negative experiences. These theories consider the momentary effects of SMU on self-esteem as the building blocks of its longer-term effects. Investigating such momentary effects of SMU on adolescents’ self-esteem is the first aim of this study.
A second gap in the literature that may explain the weak and inconsistent results in earlier work is that individual differences in susceptibility to the effects of SMU on self-esteem have hardly been taken into account. Studies that did investigate such differences have mostly focused on gender as a moderating variable, without finding any effect ( Kelly et al., 2018 ; Košir et al., 2016 ; Meeus et al., 2019 ; Rodgers et al., 2020 ). However, these null findings may be due to the high variance in susceptibility to the effects of SMU within both the boy and girl groups. After all, if differential susceptibility leads to positive effects among some girls and boys and to negative effects among others, the moderating effect of gender at the aggregate level would be close to zero. Therefore, the time is ripe to investigate differential susceptibility to the effects of SMU at the more fine-grained level of the individual rather than by including group-level moderators. Such an investigation would not only benefit media effects theories (e.g., Valkenburg & Peter, 2013 ), but also self-esteem theories that emphasize that the effects of environmental influences may differ from person to person (e.g., Harter & Whitesell, 2003 ). Investigating such person-specific susceptibility to the effects of SMU is, therefore, the second aim of this study.
To investigate the momentary effects of SMU on self-esteem (first aim), and to assess heterogeneity in these effects (second aim), we employed an experience sampling (ESM) study among 387 middle adolescents (13–15 years), whom we surveyed six times a day for three weeks (126 measurements per person). We measured SMU by asking adolescents on each measurement moment how much time in the past hour they had spent on the three most popular social media platforms among Dutch adolescents ( van Driel et al., 2019 ): Instagram, WhatsApp, and Snapchat. We focused on middle adolescence because this is the period of most significant fluctuations in self-esteem ( Harter, 2012 ). By employing a novel, person-specific method to analyze our intensive longitudinal data, we were able, for the first time, to assess the effects of SMU at the level of the individual adolescent, and to assess how these effects differ from adolescent to adolescent.
Social Media Use and Self-Esteem Level
Personality and social psychological research into the antecedents, consequences, and development of self-esteem has mostly focused on two aspects of self-esteem: self-esteem level and self-esteem instability. Most of this research has focused on self-esteem level, that is, whether it is high or low ( Crocker & Brummelman, 2018 ). This also holds for studies into the effects of SMU. For example, all of the 15 correlational studies have investigated whether adolescents who spend more time with social media report a lower (or higher) level of self-esteem compared to their peers who spend less time with social media (e.g., Apaolaza et al., 2013 , 12–17 years; Barthorpe et al., 2020 , 13–15 years; Bourke, 2013 , 12–16 years; Cingel & Olsen, 2018 , 12–18 years; Kelly et al., 2018 , 14 years; Morin-Major et al., 2016 , 12–17 years; O'Dea & Campbell, 2011 , M age 14; Rodgers et al., 2020 , M age 12.8; Thorisdottir et al., 2019 , 14–16 years; Valkenburg et al., 2006 , 10–19 years; van Eldik et al., 2019 , 9–13 years). In statistical terms, these studies have investigated the between -person relationship of SMU and self-esteem.
The majority of studies into the between-person relationship of SMU and self-esteem used Rosenberg’s (1965) self-esteem scale, which is the most commonly used survey measure to assess general, trait-like levels of self-esteem. These studies asked adolescents at one point in time to evaluate their selves in general or across a certain period in the past (e.g., in the past year). In the current study, we also investigated the between-person relationship between SMU and adolescents’ general levels of self-esteem. But unlike earlier studies, we assessed their levels of SMU and self-esteem by averaging the 126 momentary assessments of both variables across a three-week period. Such in situ assessments generally produce data with greater ecological validity because they are made in the natural flow of daily life, which reduces recall bias ( van Roekel et al., 2019 ). Given the inconsistent results in previous studies, the literature does not allow us to formulate a hypothesis on the between-person association between SMU and self-esteem level. Therefore, we investigated the following research question:
(RQ1) Do adolescents who spend more time with social media report a lower or higher level of self-esteem compared to adolescents who spend less time with social media?
Social Media Use and Self-Esteem Fluctuations
A second strand of personality and social psychological research has focused on the instability of self-esteem. Self-esteem instability refers to the extent to which self-esteem fluctuates within persons ( Kernis, 2005 ). Whereas research into the level of self-esteem has predominantly tried to establish differences in self-esteem between persons, work on self-esteem instability has focused on fluctuations in self-esteem within persons. Rosenberg (1986) distinguishes between two types of within-person self-esteem fluctuations: baseline and barometric instability. Baseline instability refers to potential within-person changes in levels of self-esteem that occur slowly and over an extended period of time. It has been shown, for example, that self-esteem decreases in early adolescence after which it may slowly and steadily increase again in later adolescence ( Harter & Whitesell, 2003 ). Barometric fluctuations, in contrast, reflect short-term within-person fluctuations in self-esteem as a result of one’s everyday positive and negative experiences. Rosenberg (1986) argued that such barometric fluctuations are particularly evident during adolescence, when adolescents typically experience enhanced uncertainty about their identity (i.e., how to define who they are and will become), intimacy (i.e., how to form and maintain meaningful relationships), and sexuality (e.g., how to cope with sexual desire and define their sexual orientation; Steinberg, 2011 ).
One of the aims of the current study is to investigate how SMU may induce within-person fluctuations in barometric self-esteem. Two earlier social media effects studies have focused on within-person effects, one longitudinal study ( Boers et al., 2019 , M age 17.7) and one experiment ( Thomaes et al., 2010 , 8–12 years). Using Rosenberg’s self-esteem scale, Boers et al. found negative within-person effects of SMU on baseline self-esteem. However, because the assessments of SMU and self-esteem were one year apart, and because short-term fluctuations can hardly be derived from designs with longer-term measurement intervals ( Keijsers & van Roekel, 2018 ), this study, although important, may not inform a hypothesis on the influences of SMU on barometric self-esteem.
A within-person experiment by Thomaes et al. (2010) does confirm self-esteem instability theories in the context of SMU. Thomaes et al. based their experiment on Leary and Baumeister’s (2000) Sociometer theory. Like Rosenberg’s theory of self-esteem, Sociometer theory proposes that self-esteem serves as a sociometer (cf. barometer) that gauges the degree of approval and disapproval from one’s social environment. An important proposition of Sociometer theory is that self-esteem changes are accompanied by changes in affect (mood and emotions). Self-esteem (and affect) goes up when people succeed or when others accept them, and it drops when people fail or when others reject them. The results of Thomaes et al. confirmed Sociometer theory: When preadolescents’ online social media profiles were approved by others, their self-esteem increased, and when their online profiles were disapproved, their self-esteem dropped.
In Thomaes et al.’s study, peer approval was experimentally manipulated so that one group of preadolescents (8-13 years) received positive feedback and an equally sized group received negative feedback on their online profiles. In reality, however, peer approval and disapproval in social media interactions are typically not as neatly balanced. In fact, studies have often reported a positivity bias in social media-based interactions (e.g., Reinecke & Trepte, 2014 ; Waterloo et al., 2017 ), meaning that social media users tend to share and receive more positive than negative information. This positivity bias also strongly holds for adolescent social media users. For example, among a national sample of adolescents, only 8% “sometimes” received negative feedback on their posts, whereas 91% “never” or “almost never” received such feedback ( Koutamanis et al., 2015 ). Therefore, on the basis of Sociometer theory, the positivity bias of social media interactions, and the findings of Thomaes et al., we expect an overall positive within-person effect of time spent with social media on adolescents’ self-esteem:
(H1) Overall, adolescents’ self-esteem will increase as a result of their time spent with social media in the past hour.
Heterogeneity in the Effects of Social Media Use on Self-esteem
Most media effects theories that have been developed during and after the 1970s agree that media effects are conditional, meaning that they do not equally hold for all media users (for a review see Valkenburg et al., 2016 ). These theories have sparked numerous media effects studies trying to uncover how certain dispositional, environmental, and contextual variables may enhance or reduce the cognitive, affective, and behavioral effects of media. In the past decade, this media effects research has resulted in an upsurge in meta-analyses of media effects, which not only helped integrating the findings in this vastly growing literature, but also pointed at the moderators that may explain differential susceptibility to media effects.
Despite their undeniable value, the effect sizes for both the main and moderating effects of media use that these meta-analyses have yielded typically range between r = .10 and r = .20 ( Valkenburg et al., 2016 ). Although small to medium effect sizes are common in many neighboring disciplines, some media scholars have argued that such small media effects defy common sense because everyday experience offers anecdotal evidence of strong media effects for some individuals ( Valkenburg et al., 2016 ). Moreover, qualitative studies have repeatedly confirmed that media users differ greatly in their responses to (social) media (e.g., Rideout & Fox, 2018 ). And studies on the emotional reactions to scary media content have reported extreme responses for particular individuals ( Cantor, 2009 ).
There is an apparent discrepancy between the magnitude of conditional media effects sizes reported in quantitative studies and meta-analyses on the one hand and the results of qualitative studies and anecdotal examples on the other. By focusing on group-level moderator effects, meta-analyses (and the studies on which they are based) invariably gloss over more subtle individual differences between people ( Pearce & Field, 2016 ). Diving deeper into these subtle individual differences, however, is only possible with research designs that are able to detect differences in person-specific effects. Such designs require a large number of assessments per person to derive conclusions about processes within single persons, as well as a sufficient number of participants for bottom-up generalization to sub-populations ( Voelkle et al., 2012 ).
An important aim of this study is to capture such person-specific susceptibilities to the effects of SMU by employing a novel method of analysis: Dynamic Structural Equation Modeling (DSEM). DSEM is an advanced modeling technique that is suitable for analyzing intensive longitudinal data, that is, data with 20 to more than 100 repeated measurements that are typically closely spaced in time ( McNeish & Hamaker, 2020 ). DSEM combines the strengths of multilevel analysis and Structural Equation Modeling (SEM) with N = 1 time-series analysis. N = 1 time-series analysis enables researchers to establish the longitudinal (lagged) associations between SMU and self-esteem within single persons. The multilevel part of DSEM provides the opportunity to test whether the person-specific effect sizes of SMU on self-esteem differ between persons. Combining the power of a large number of assessments of single persons with a large sample, DSEM may help us answer the question: For how many adolescents does SMU support their self-esteem, for how many does it hinder their self-esteem, and for how many does it not affect their self-esteem?
Not only media effects theories, but also self-esteem theories give reason to assume person-specific effects of environmental influences on self-esteem. These theories agree that some individuals experience significant boosts (or drops) in self-esteem when they experience minor disapproval (or approval) from their peers, whereas the self-esteem of others may fluctuate only in case of serious self-relevant experiences ( Crocker & Brummelman, 2018 ). For example, a study by Harter and Whitesell (2003) showed that 59% of adolescents were prone to self-esteem fluctuations, whereas 41% were not or less prone to such fluctuations. Based on these insights of self-esteem theories, it is likely that the effects of SMU will also differ from adolescent to adolescent. Due to the positivity bias of social media interactions, we expect that most adolescents will experience increases in self-esteem as a result of their SMU in the past hour, whereas a smaller group will experience decreases in self-esteem, and for another smaller group of adolescents their SMU will be unrelated to their self-esteem. Therefore, we hypothesize:
(H2) The effect of time spent with social media on self-esteem will vary from adolescent to adolescent.
Participants
This preregistered study is part of a larger project on the psychosocial consequences of SMU. The present study uses data from the first three-week experience sampling method (ESM) wave of this project that took place in December 2019. The sample consisted of 387 early and middle adolescents (13- to 15-year-olds; 54% girls; M age = 14.11, SD = .69) from a large secondary school in the southern area of The Netherlands. Participants were enrolled in three different levels of education: 44% were in lower prevocational secondary education (VMBO), 31% in intermediate general secondary education (HAVO), and 26% in academic preparatory education (VWO). Of all participants, 96% was born in The Netherlands and self-identified as Dutch, 2% was born in another European country, and 2% in a country outside Europe. The sample was representative of this area in The Netherlands in terms of educational level and ethnic background ( Statistics Netherlands, 2020 ).
The study was approved by the Ethics Review Board of the University of Amsterdam. Before the start of the study parents gave written consent for their child’s participation in the study, after they had been extensively informed about the goals of the study. At the end of November 2019, participants took part in a baseline session during school hours. Researchers informed participants of the aims and procedure of the study and assured them that their responses would be treated confidentially. Participants were provided with detailed instructions about the ESM study that started in the week following upon the baseline survey. They were instructed on how to install the ESM software application (Ethica Data) on their phones, and how to answer the different types of ESM questions. At the end of the baseline session, participants completed an initial ESM survey on their use of different social media platforms, which we used to personalize subsequent ESM surveys. In case of questions or problems with the installment of the software, three researchers were present to help out.
ESM study . In the three-week ESM study, participants completed six 2-minute surveys per day in response to notifications from their mobile phones. The first and last ESM surveys contained 24 questions, whereas each of the other four ESM surveys consisted of 23 questions. Each ESM survey assessed, among other variables not reported in this study, participants’ self-esteem and their SMU. Participants received questions about their time spent with Instagram, WhatsApp, and Snapchat if they had indicated in the baseline session that they used these platforms more than once per week. In case participants did not use any of these platforms more than once a week, they were surveyed about other platforms that they did use (e.g., YouTube or gaming). If they did not use any other platforms either, they received other questions to ensure that each participant received the same number of questions. In total, 375 (97%) participants received questions about WhatsApp, 345 participants (89%) about Instagram, and 285 (73%) about Snapchat.
Sampling scheme . In total, participants received 126 ESM surveys (i.e., 21 days * 6 assessments a day) at random time points within fixed intervals. The sampling scheme was tailored to the school’s schedule and participants’ weekday and weekend routines to avoid that participants received notifications during class hours and while sleeping in on the weekends. Five to ten minutes after each ESM notification, participants received an automatic reminder. We have uploaded our entire notification scheme with the response windows on OSF .
Monitoring plan/incentives. We regularly messaged adolescents to check whether we could help with any technical issues and to motivate them to fill out as many ESM surveys as possible. Adolescents received a small gadget for participating in the baseline session, and a compensation of €0.30 for each completed ESM survey. In addition, each day we held a lottery, in which four participants who had completed all six ESM surveys the day before could win €25.
Compliance. We sent out 48,762 surveys (i.e., 387 × 126) to participants. Due to unforeseen technical problems with the Ethica software, 862 ESM surveys did not reach participants. As a result, 47,900 ESM surveys were received, and 34,930 surveys were completed. This led to a compliance rate of 73%, which is good in comparison with previous ESM studies among adolescents ( van Roekel et al., 2019 ). On average, participants completed 90.26 ESM surveys ( SD = 23.84).
A priori power-analyses. The number of assessments was determined based on the fact that a minimum of 50–100 assessments per participant is recommended to conduct N = 1 time-series analyses ( Voelkle et al., 2012 ). In order to obtain at least 50 assessments per participant, we took a conservative approach and scheduled for a total of 126 assessments. A priori power analyses indicated that a number of 300 participants would suffice to reliably detect small effect sizes with a minimum power of .80 and significance levels of p = .05.
Time spent with social media . To obtain an ecologically valid ESM assessment of time spent with social media, we asked participants at each assessment how much time in the past hour they had spent with the three most popular platforms: WhatsApp, Instagram, and Snapchat. For each platform, we selected the most popular activities ( van Driel et al., 2019 ). For Instagram, we asked: How much time in the past hour have you spent… (1) sending direct messages on Instagram? (2) reading direct messages on Instagram? (3) viewing posts/stories of others on Instagram? For WhatsApp, we asked: How much time in the past hour have you spent… (4) sending messages on WhatsApp? (5) reading messages on WhatsApp? For Snapchat we asked: How much time in the past hour have you spent… (6) viewing snaps of others on Snapchat? (7) viewing stories of others on Snapchat? (8) sending snaps on Snapchat? Response options for each of these activities were measured with a Visual Analog Scale (VAS) that ranged from 0 to 60 minutes with one-minute intervals.
Participants’ scores on these activities were summed for each of the three platforms. For some assessments this summation led to time estimations exceeding 60 min. For WhatsApp this pertained to 0.85% of all 34,127 assessments, for Instagram to 2.40% of all 31,718 assessments, and for Snapchat to 3.87% of all 26,533 assessments. As indicated in our preregistration , these scores were recoded to 60 min. In a next step, the indicated times spent with WhatsApp, Instagram, and Snapchat were summed to create a variable “time spent with social media.” The summation of the three platforms again led to some estimations exceeding 60 min (i.e., 10.64% of all 34,686 estimations). In accordance with our preregistration, these scores were recoded to 60 min.
Self-esteem. Based on Rosenberg’s (1965) self-esteem scale, and studies establishing the validity of single-item measures of self-esteem (e.g., Robins et al., 2001 ), we presented participants with the question: “How satisfied do you feel about yourself right now?” We used a 7-point response scale ranging from 0 (not at all) to 6 (completely), with 3 (a little) as the midpoint.
Method of Analysis
As preregistered , we employed Dynamic Structural Equation Modeling (DSEM) for intensive longitudinal data in Mplus Version 8.4. Following the recommendations of McNeish and Hamaker (2020) , we estimated a two-level autoregressive lag-1 model (AR[1] model) with self-esteem as the outcome. At the within-person level (level 1), we specified SMU in the past hour as the time-varying covariate of self-esteem (to investigate H1), while controlling for the autoregressive effect of self-esteem (i.e., self-esteem predicted by lag-1 self-esteem). At the between-person level (level 2), we included the latent mean level of self-esteem and the latent mean of SMU in the past hour, and the correlation between these mean levels (to investigate RQ1). Finally, we included the between-person variances around the within-person effects of SMU on self-esteem (i.e., random effects to investigate H2).
Before estimating the model, we checked the required assumption of stationarity, that is, whether the mean of the outcome did not systematically change during the study ( McNeish & Hamaker, 2020 ). To do so we compared a two-level fixed effect model with day of study predicting self-esteem with an intercept-only model (i.e., a model without predictors). The assumption of stationarity was confirmed: Day of the study explained only 0.82% of the within-person variance in self-esteem.
Model specifications . By default, DSEM uses Bayesian Markov Chain Monte Carlo (MCMC) for model estimation. We followed our preregistered plan of analyses and ran the DSEM model with a minimum of 5,000 iterations. Before interpreting the estimates, we checked whether the model converged following the procedure of Hamaker et al. (2018) . Model convergence is considered successful when the Potential Scale Reduction (PSR) values are very close to 1 ( Gelman & Rubin, 1992 ), and the trace plots for each parameter look like fat caterpillars. We interpreted the parameters with the Bayesian credible intervals (CIs), as well as the Bayesian p- values. The hypotheses are confirmed if the 95% CIs for the effect of SMU on self-esteem (within-level; H1) and for the variance around this effect (between-level; H2) do not contain 0. Further details of the analytical strategy can be found in the preregistration of the study.
Correlations and Descriptives
Table 1 presents the means, standard deviations (SDs), ranges, and the within-person, between-person, and intra-class correlations (ICCs) of time spent with social media (SMU) and self-esteem. As the table shows, the average level of self-esteem was high ( M = 4.09, SD = 1.12, range = 0–6). Participants spent on average almost 17 minutes (range 0–60 min.) with social media in the hour before each measurement occasion. The between-person association of the mean level of SMU with the mean level of self-esteem was significantly negative ( r = −.14, p = .005). The within-person correlation was close to zero ( r = −.01, p = .028), but significant (due to the high power of the study).
Descriptive Statistics and Within-Person, Between-Person, and Intra-Class Correlations of Time Spent with Social Media (SMU) and Self-Esteem
Mean scores reflect average number of minutes spent with social media in the past hour.
Within-person association ( p = .028) between SMU and self-esteem.
between-person association ( p = .005) between SMU and self-esteem.
The Intra-Class Correlations (ICCs) were .45 for self-esteem and .48 for SMU, which means that 45% of the variance in self-esteem and 48% of the variance in SMU was explained by differences between participants (i.e., between-person variance), whereas the larger part of these variances (55% and 52%) was explained by fluctuations within participants (i.e., within-person variance). These ICCs confirm that our sampling scheme of six assessments a day was appropriate for assessing within-person fluctuations in self-esteem and SMU and led to data with sufficient within-person variance for DSEM analyses.
DSEM Results
In all the steps of the analysis strategy, we followed our preregistered plan . We first ran a DSEM model with a minimum of 5,000 iterations (and a default maximum of 50,000 iterations) and one-hour time intervals (TINTERVAL = 1). This model did not converge: The Potential Scale Reduction (PSR) convergence criterion reached 1.354, which is not close enough to 1. As recommended by McNeish and Hamaker (2020) , in a next step, we improved the model setup by increasing the time interval from 1 to 2 hours (TINTERVAL = 2). This model converged well and before the 5,000 iterations. The PSR for this model was 1.006. Visual inspection of the trace plots confirmed that convergence was successful. Finally, we also ran a model with 10,000 iterations to exclude the possibility that the PSR value of 5,000 iterations was close to 1 by chance ( Schultzberg & Muthén, 2018 ). This model reached a PSR of 1.002, and its results did not deviate from the model with 5,000 iterations.
Investigating Research Question and Hypotheses
To answer our research question (RQ1), we investigated the between-person association between SMU and self-esteem. The DSEM analyses revealed a significantly negative association of −.147 between SMU and participants’ level of self-esteem, meaning that participants who spent more time with social media across the three weeks had a lower average level of self-esteem compared to participants who spent less time with social media across this period ( Table 2 ).
DSEM Results of the Between-Person Associations and Within-Person Effects of Time Spent with Social Media (SMU) and Self-Esteem (S-E)
The relationship between SMU and β rβ reflects the extent to which the within-person effect of momentary SMU on momentary S-E depends on the average level of adolescents’ SMU;
The relationship between S-E and β β reflects the extent to which the within-person effect of momentary SMU on momentary S-E depends on adolescents’ average level of S-E;
The 95% Credible Interval of the variance around the effect of SMU on S-E indicates that the within-person effect of SMU on S-E differed among participants. b ’s are unstandardized; β β’s are standardized using the STDYX Standardization in Mplus; p -values are one-tailed Bayesian p -values ( McNeish & Hamaker, 2020 ).
Our first hypothesis (H1) predicted an overall positive within-person effect of SMU on self-esteem. This within-person effect represents the average changes in self-esteem (i.e., self-esteem controlled for self-esteem at t −1) as a result of SMU in the previous hour. This hypothesis did not receive support. Despite the high power of the study, the within-person effect was nonsignificant (β = −.009), meaning that, on average, participants’ self-esteem did not increase nor decrease as a result of their SMU in the previous hour ( Table 2 ).
Our second hypothesis (H2), which predicted that the within-person effect of SMU on changes in self-esteem would differ from participant to participant, did receive support ( Table 2 : random effect = 0.006, p = .000). This random effect means that there was significant variance between participants in the extent to which their SMU in the previous hour predicted changes in their self-esteem.
Figure 1 shows the distribution of the person-specific standardized effect sizes for the effect of SMU on changes in self-esteem. These effect sizes ranged from β = −.21 to β = +.17 across participants. As the bar graph shows, the majority of participants (88%) experienced no or very small positive or negative effects of their SMU (i.e., −.10 < β < .10) on changes in self-esteem, whereas a small group of participants (4%) experienced positive (.10 ≤ β ≤ .17), and another small group (8%) experienced negative effects (−.21 ≤ β ≤ -.10) of SMU on changes in self-esteem. Figure 2 presents the N = 1 time-series plots of three participants, one who experienced a positive, one who experienced a negative, and one who experienced a null-effect of SMU on self-esteem.
Range of the Standardized Person-Specific Effects of SMU on in Self-Esteem.
Note. The vertical black line represents the mean of the person-specific effects ( β = −.009).
Three N = 1 time-series plots picturing the effects of SMU on self-esteem (S-E).
Note . The x -axes represent the measurement moments (range 1–126). The y -axes represent the co-fluctuations in SMU (blue lines, range 0–60 minutes/10) and S-E (yellow lines, range 0–6). The top plot belongs to a participant who experienced a positive effect of SMU on S-E ( β = .174). The SMU and S-E of this participant regularly co-fluctuated (e.g., around moment 40 and around moment 41). The middle plot is from a participant who experienced a negative effect ( β β = −.196): When the SMU of this participant increased, his/her S-E dropped (e.g., around moment 56), and vice versa (e.g., around moment 21). The bottom plot is from a participant who experienced no effects ( β = .013): At some moments, the S-E of this participant increased after his/her SMU increased (e.g., around moment 45), at othermoments her/his S-E dropped after his/her SMU went up (e.g., moment 72), resulting in a net effect close to zero.
Exploratory Analyses
In addition to our preregistered hypotheses, we ran four exploratory analyses. In a first step, we investigated potential platform differences. Because earlier studies into the relationship between SMU and self-esteem did not investigate differential effects of different platforms, we summed adolescents’ use of Instagram, Snapchat, and WhatsApp to create our SMU measure. To explore potential platforms differences, we reran our analyses separately for each of the three platforms. Our results did not show significant differences in the between-person relationships and within-person effects of the use of these platforms on self-esteem (see Supplement 1).
In a second step, we ran a multilevel model without controlling for self-esteem at the previous assessment. Given that DSEM models are rather stringent and that sizeable differences in effect sizes between lagged and non-lagged media effects have been reported ( Adachi & Willoughby, 2015 ), we wanted to get insight into these differences. All other model specifications of the multilevel model were identical to the initial DSEM model. The associations between SMU and self-esteem in the multilevel model ranged from β = −.34 to β = +.33. Consistent with the DSEM model, the average within-person association of SMU and self-esteem was close to zero (β = −.007, p = .162, CI = [−0.022, 0.007] compared to β = −.009 in the DSEM model).
In a third step, we explored whether the person-specific within-person effects of SMU on self-esteem (i.e., the βs) differed for adolescents with different mean levels of SMU or different mean levels of self-esteem. As Table 2 shows, the cross-level interaction of participants’ mean levels of SMU with the β’s was non-significant, indicating that adolescents with higher mean levels of SMU did not experience a more negative (or positive) within-person effect of SMU on their self-esteem than their peers with lower SMU. The cross-level interaction of self-esteem and the βs did reveal that the within-person effect of SMU on self-esteem depended on adolescents’ mean level of self-esteem: Adolescents with lower average levels of self-esteem had a more positive within-person effect of SMU on self-esteem than adolescents with higher average levels of self-esteem, and vice versa.
In a final step, we investigated a between-person hypothesis of one of the anonymous reviewers, who suggested to check whether adolescents with moderate SMU would experience higher trait levels of self-esteem than those with low and high SMU. We investigated this potential inverted U-shaped relationship between SMU and self-esteem by following the two-step hierarchical regression analysis used by Cingel and Olsen (2018) . At step 1 of this regression analysis, we found a negative linear relationship between SMU and self-esteem (β = − .145, p = .005; R 2 = .021, see also Table 1 ). At step 2, we found no significant curvilinear relationship between SMU and self-esteem, because the added squared SMU term did not result in a significant change in the explained variance (Δ R 2 = .001, Δ F (1, 380) = .516, p = .473).
Sensitivity Analysis
As preregistered , we conducted a validation check to examine whether participants’ answers were trustworthy according to the following criteria: (1) inconsistency of participants’ within-person response patterns, (2) outliers, (3) unserious responses (e.g., gross comments) to the open question in the ESM study. Based on these criteria, we considered the responses of eight participants as potentially untrustworthy, because they violated criterion 1 and 2 ( n = 4) or criterion 1 and 3 ( n = 4). As a sensitivity analysis, we reran the DSEM analysis without these eight participants. The results of both the between-person and within-person associations did not deviate from those of the full sample.
The two existing meta-analyses on the relationship of SMU and self-esteem assessed the effects of their included empirical studies as weak and their results as mixed ( Huang, 2017 ; Liu & Baumeister, 2016 ). The between-person associations reported in empirical studies on SMU and self-esteem ranged from +.22 ( Apaolaza et al., 2013 ) to − .28 ( Rodgers et al., 2020 ). In the current study, the between-person association between SMU and self-esteem fits within this range: We found a negative relationship of r = − .15 between SMU and self-esteem (RQ1), meaning that adolescents who spent more time on social media across a period of three weeks reported a lower level of self-esteem than adolescents who spent less time on social media. This negative relationship pertained to the summed usage of Instagram, Snapchat, and WhatsApp, but did not differ for the usage of each of the separate platforms.
In addition, although we hypothesized a positive overall within -person effect of SMU on self-esteem (H1), we found a null effect. However, this overall null effect must be interpreted in light of the supportive results for our second hypothesis (H2), which predicted that the effect of SMU on self-esteem would differ from adolescent to adolescent. We found that the majority of participants (88%) experienced no or very small positive or negative effects of SMU on changes in self-esteem ( − .10 < β < .10), whereas one small group (4%) experienced positive effects (.10 ≤ β ≤ .17), and another small group (8%) negative effects of SMU ( − .21 ≤ β ≤ − .10) on self-esteem.
The person-specific effect sizes reported in the current study pertain to SMU effects on changes in self-esteem (i.e., self-esteem controlled for previous levels of self-esteem). As Adachi and Willoughby (2015 , p. 117) argue, such effect sizes are often “dramatically” smaller than those for outcomes that are not controlled for their previous levels. Indeed, when we checked this assumption of Adachi & Willoughby, the associations between SMU and self-esteem not controlled for its previous levels resulted in a considerably wider range of effect sizes (β = − .34 to β = +.33) than those that did control for previous levels (β = − . 21 to β = +.17). To account for a potential undervaluation of effect sizes in autoregressive models, Adachi and Willoughby (2015 , p. 127) proposed “a more liberal cut-off for small effects in autoregressive models (e.g., small = .05).” In this study, we followed our preregistration and interpreted effect sizes ranging from − .10 < β < +.10 as non-existent to very small. However, if we would apply the guideline proposed by Adachi and Willoughby (2015) to our results, the distribution of effect sizes would lead to 21% negative susceptibles, 16% positive susceptibles, and 63% non-susceptibles.
Our results showed that the effects of SMU on self-esteem are unique for each individual adolescent, which may, in turn, explain why the two meta-analyses evaluated the effects of their included studies as weak and their results as inconsistent. First, our results suggest that these effects were weak because they were diluted across a heterogeneous sample of adolescents with different susceptibilities to the effects of SMU. This suggestion is supported by comparing our overall within-person effect (β = − .01, ns) with the full range of person-specific effects, which ranged from moderately negative to moderately positive. Second, the effects reported in earlier studies may have been inconsistent because these studies may, by chance, have slightly oversampled either “positive susceptibles” or “negative susceptibles.” After all, if a sample is somewhat biased towards positive susceptibles, the results would yield a moderately positive overall effect. Conversely, if a sample is somewhat biased towards negative susceptibles the results would report a moderately negative overall effect.
It may seem reassuring at first sight that the far majority of participants in our study did not experience sizeable negative effects of SMU on their self-esteem. However, as illustrated in the bottom N = 1 time-series plot in Figure 2 , for some participants, their non-significant within-person effect may result from strong social media-induced ups and downs in self-esteem, which cancelled each other out across time, resulting in a net null effect. However, as the two upper time-series plots in Figure 2 show, not only the non-susceptibles, but also the positive and negative susceptibles sometimes experienced effects in the opposite direction: The positive susceptibles occasionally experienced negative effects, while the negative susceptibles occasionally experienced positive effects.
Although DSEM models enable researchers to demonstrate how within-person effects of SMU differ across persons, they do not (yet) allow us to statistically evaluate the presence of both positive and negative effects within one and the same person (Hamaker, 2020, personal communication). A possibility to analyze the combination of positive and negative effects within persons may soon be offered by even more advanced modeling strategies than DSEM, which are currently undergoing a rapid development. Among those promising developments are regime switching models ( Lu et al., 2019 ), which provide the opportunity to establish the co-occurrence of both positive and negative effects of SMU within single persons.
Explanatory Hypotheses and Avenues for Future Research
Although our study allowed us to reveal the prevalence of positive susceptibles, negative susceptibles, and non-susceptibles among participants, it did not investigate why and when some adolescents are more susceptible to SMU than others. Our exploratory results did show that adolescents with a lower mean level of self-esteem, experienced a more positive within-person effect of SMU on self-esteem than adolescents with a higher mean level of self-esteem. This latter result may point to a social compensation effect ( Kraut et al., 1998 ), indicating that adolescents who are low in self-esteem may successfully seek out social media to enhance their self-esteem. Our DSEM analysis did not reveal differences in the within-person effects of SMU on self-esteem among adolescents with high and low SMU, suggesting that the positive effects among some adolescents cannot be attributed to modest SMU, whereas the negative effects among other adolescents cannot be attributed to excessive SMU.
An important next step is to further explain why adolescents differ in their susceptibility to SMU. A first explanation may be that adolescents differ in the valence (the positivity or negativity) of their experiences while spending time on social media. It is, for example, possible that the positive susceptibles experience mainly positive content on social media, whereas the negative susceptibles experience mainly negative content. In this study, we focused on time as a predictor of momentary ups and downs in self-esteem. However, most self-esteem theories emphasize that it is the valence rather than the duration of social experiences that results in self-esteem fluctuations. It is assumed that self-esteem goes up when we succeed or when others accept us, and drops when we fail or when others reject us ( Leary & Baumeister, 2000 ). Future research should, therefore, extend our study by investigating to what extent the valence of experiences on social media accounts for differences in susceptibility to the effects of SMU above and beyond adolescents’ time spent on social media.
A second explanation as to why adolescents differ in their susceptibility to the effects of SMU may lie in person-specific susceptibilities to the positivity bias in SM. Our first hypothesis was based on the idea that the sharing of positively biased information would elicit reciprocal positive feedback from fellow users, which, in turn, would lead to overall improvements in self-esteem. However, our results suggest that, for some adolescents, this positivity bias may lead to decreases in self-esteem, for example, because of their tendency to compare themselves to other social media users who they perceive as more beautiful or successful. This tendency towards social comparison may lead to envy (e.g., Appel et al., 2016 ) and decreases in self-esteem ( Vogel et al., 2014 ).
Until now, studies investigating the positive feedback hypothesis have mostly focused on the positive effects of feedback on self-esteem (e.g., Valkenburg et al., 2017 ), whereas studies examining the social comparison hypothesis have mainly focused on the negative effects of social comparison on self-esteem (e.g., Vogel et al., 2014 ). However, both the positive feedback hypothesis and the social comparison hypothesis are more complex than they may seem at first sight. First, although most adolescents receive positive feedback while using social media, a minority frequently receives negative feedback ( Koutamanis et al., 2015 ), and may experience resulting decreases in self-esteem. Likewise, although social comparison may lead to envy, it may also lead to inspiration (e.g., Meier & Schäfer, 2018 ), and resulting increases in self-esteem. Future research should attempt to reconcile these explanatory hypotheses by investigating who is particularly susceptible to positive and/or negative feedback, and who is particularly susceptible to the positive (e.g., inspiration) and/or negative (e.g., envy) effects of social comparison on social media.
Another possible explanation for differences in person-specific effects of SMU on self-esteem may lie in differences in the specific contingencies on which adolescents’ self-esteem is based. Self-esteem contingency theory ( Crocker & Brummelman, 2018 ) recognizes that people differ in the areas of life that serve as the basis of their self-esteem ( Jordan & Zeigler-Hill, 2013 ). For example, for some adolescents their physical appearance may serve as the basis of their self-esteem, whereas others may base their self-esteem on peer approval. Different contexts may also activate different self-esteem contingencies ( Crocker & Brummelman, 2018 ). On the soccer field, athletic ability is valued, which may activate the athletic ability contingency in this context. On social media, physical appearance and peer approval may be relevant, so that these contingencies may particularly be triggered in the social media context. It is conceivable that adolescents who base their self-esteem on appearance or peer approval may be more susceptible to the effects of SMU than adolescents who base their self-esteem less on these contingencies, and this is, therefore, another important avenue for future research.
Stimulating Positive and Mitigating Negative Effects
Our results suggest that for the majority of adolescents the momentary effects of SMU are small or negligible. As discussed though, all adolescents—whether they are positive susceptibles, negative susceptibles, or non-susceptibles—may occasionally experience social media-induced drops in self-esteem. Social media have become a fixture in adolescents’ social life, and the use of these media may thus result in negative experiences among all adolescents. Therefore, not only the negative susceptibles, but all adolescents need their parents or educators to help them prevent, or cope with, these potentially negative experiences. Parents and educators can play a vital role in enhancing the positive effects of SMU and combatting the negative ones. Helping adolescents prevent or process negative feedback and explaining that the social media world may not be as beautiful as it often appears, are important ingredients of media-specific parenting as well as school-based media literacy programs.
Although this study was designed to contribute to (social) media effects theories and research, our analytical approach may also have social benefits. After all, N = 1 time-series plots could not only be helpful for theory building, but also for person-specific advice to adolescents. These plots give a comprehensive snapshot of each adolescent’s experiences and responses across more or less prolonged time periods. Such information could greatly help tailoring prevention and intervention strategies to different adolescents. After all, only if we know which adolescents are more or less susceptible to the negative and positive effects of social media, are we able to adequately target prevention and intervention strategies at these adolescents.
Towards a Personalized Media Effects Paradigm
Insights into person-specific susceptibilities to certain environmental influences is burgeoning in several disciplines. For example, in medicine, personalized medicine is on the rise. In education, personalized learning is booming. And in developmental psychology, differential susceptibility theories are among the most prominent theories to explain heterogeneity in child development. Although N = 1 or idiographic research is now progressively embraced in multiple disciplines, spurred by recent methodological developments, it has a long history behind it. In fact, in the first two decades of the 20th century, scholars such as Piaget, Pavlov, and Thorndike often conducted case-by-case research to develop and test their theories bottom up (i.e., from the individual to the population; Robinson, 2011 ). However, in the 1930s, idiographic research soon lost ground to nomothetic approaches, certainly after Francis Galton attached the term nomothetic to the aggregated group-based methodology that is still common in quantitative research ( Robinson, 2011 ). However, due to technological advancements, it has become feasible to collect masses of intensive longitudinal data from masses of individuals on the uses and effects of social media (e.g., through ESM, tracking). Moreover, rapid developments in data mining and statistical methods now also enable researchers to analyze highly complex N = 1 data, and by doing so, to develop and investigate media effects and other communication theories bottom-up rather than top-down (i.e., from the population to the individual). We hope that this study may be a very first step to a personalized media effects paradigm.
Additional Supporting Information may be found in the online version of this article.
This study was funded by an NWO Spinoza Prize and a Gravitation grant (NWO Grant 024.001.003; Consortium on Individual Development) awarded to Patti Valkenburg by the Dutch Research Council (NWO). Additional funding was received from a VIDI grant (NWO VIDI Grant 452.17.011) awarded to Loes Keijsers.
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How do “selfies” impact adolescents' well-being and body confidence? A narrative review
Siân a mclean, hannah k jarman, rachel f rodgers.
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Correspondence: Siân A McLean Institute for Health and Sport, Victoria University, Ballarat Road, Melbourne, 8001, Victoria, Australia, Phone: Tel +61 39 919 5867 Email [email protected]
Received 2019 Apr 16; Accepted 2019 Jun 7; Collection date 2019.
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Social media use has grown rapidly in recent years, with one of the most popular activities for young people being the taking, sharing, and browsing of digital self-photos, known as selfies. However, research has only recently begun to investigate selfies, and little is known about selfie practices in adolescents, or the associations between these practices and well-being and body confidence. This paper aimed to address this gap and conduct a narrative review of selfie practices and the relationships with well-being and body confidence in adolescents. No studies were found reporting on selfie practices and these relationships among children. However, taking selfies appears to be common practice among adolescents, although posting selfies online is less frequent. The studies reviewed indicate that certain aspects of selfie behaviors may be more problematic than others. Specifically, viewing selfies online appears to have a negative impact on adolescents' well-being and body confidence, at least in the short term in experimental contexts. Moreover, seeking and placing importance on feedback from others may also be a harmful aspect of selfie practices. Finally, consistent with research examining social media, social comparison has been identified in this emerging body of research as a potential mechanism which links selfie engagement to well-being and body confidence. To further advance understanding of the correlates and effects of selfie practices, research with children and with boys, and research focused on a wider range of indicators of well-being, is needed. Most importantly, prospective research is required to examine the directionality of links between selfie practices and well-being and body confidence.
Keywords: selfies, social media, adolescents, well-being, body image, social comparison
Introduction
Social media use among young people has burgeoned in recent years, 1 , 2 with a doubling of the proportion of teenagers who use social media reported over a 6-year period. 3 One of the most popular activities is sharing and viewing selfies. 4 , 5 Selfies are typically defined as self-photos taken with a hand-held device that are usually shared on social media. 6 However, more recent definitions also recognize the centrality of the photographer in the image, in that the body or face is the main focus of the image, and incorporate the notion that selfies are “consciously created, modified, and shared with others to varying degrees”. 7 This extended conceptualization recognizes multiple actions involved in taking (preparation, staging, posing), modifying (editing, selection), and posting photos, as well as viewing (browsing) and evaluating others’ selfies through “likes” and comments as being encompassed under the umbrella of selfie-related practices. 8 , 9 Despite the popularity of selfie practices on social media, in light of emerging evidence of harms associated with social media use, 10 – 12 including among children, showing a link between social media use and poorer psychological functioning, depression, and body dissatisfaction, 13 – 15 increasing our understanding of the association between different types of social media use and outcomes in children is important. In particular, young people’s recognition of the negative impact of photo-sharing social media platforms on well-being and body image 16 highlights selfie practices as an important area of investigation. Increasing our understanding of these effects in adolescents is particularly important, as this is a significant developmental period for identity, self-image, and social interactions, all of which are likely to be impacted by selfie practices. This article reviews research that has examined the relationships between, and impact of, selfie practices on adolescents’ well-being and body confidence, with the aim of providing a narrative summary of these effects and suggestions for future priorities for research in this area.
Owing to the relatively recent uptake of selfie practices, the impact of selfies has only recently become the subject of scientific studies. 17 Furthermore, relatively few selfie studies have focused on adolescents and, to our knowledge, no studies have been published that have examined this topic in children. This is despite the fact that social media platforms that have as their primary purpose sharing and browsing photos, such as Instagram and Snapchat, are particularly favored by young people. 2 In light of the small body of research examining selfies in adolescents, this paper will comprise a narrative, rather than systematic, review of the literature. A narrative review was deemed most appropriate because of the limited number of studies in this area, and the fact that the literature that does exist is still formative and in its early stages. In contrast to a systematic review, a narrative review affords a broader scope to provide a comprehensive synthesis of evidence and contextualization of the extant research. 18 Searches of relevant databases and reference lists were conducted to identify relevant papers. The authors determined which articles were most pertinent for this review using their expertise in this field.
The review focused on outcomes related to well-being and body confidence, which are considered to be particularly relevant for adolescents, as these are formative years for the development of self-identify, 19 of which appearance and body image are important components. 20 Well-being is traditionally defined as encompassing optimal psychological functioning. 21 Consistent with this definition, in the current paper, well-being has been conceptualized to focus specifically on elements of psychological functioning, such as affect and self-esteem. Physical well-being and impact on other domains of functioning important in this developmental phase, such as cognitive development and educational attainment, are considered outside the scope of the paper. In addition, although the focus of this review is on body confidence, considered to reflect positive feelings about one’s body, including but not limited to appearance, 22 studies that have assessed other related outcomes, including body satisfaction, and indicators of low body confidence, body dissatisfaction, and self-objectification, will also be considered.
Selfie practices
Emerging research suggests that children and adolescents engage with a range of selfie practices, although less is known about the frequency of engagement with selfies than with social media use more generally. For example, a 2018 report indicates that the most popular social media platforms for adolescents are YouTube, Instagram, and Snapchat, with between 69% and 85% of adolescents from the USA using these platforms. 2 However, the extent to which these sites are used specifically for selfie posting and viewing is not clear at present. Furthermore, some of these platforms may be geared toward selfie practices to a greater extent than others.
Although anecdotally it has been observed that children and adolescents frequently take selfies using smartphone devices, 23 , 24 research is only beginning to investigate the extent to which young people engage with online selfie practices, versus taking pictures of themselves that are not designed to be used for online self-presentation. Research indicates that selfie taking, with or without the intention to share the selfie on social media, is very common among adolescents, with 97% of Italian adolescents having taken selfies. 25 However, frequency of selfie taking, as opposed to selfie posting and sharing, is less clear. In regard to offline selfies (those taken but not shared online), McLean et al, 9 in their study of social media, body image, and disordered eating, found that on average, Australian early adolescent girls (mean age 13.13 years) took selfies once per week. Dhir et al 26 examined gender differences in selfie taking of Norwegian adolescents (mean age 16.96 years) and found a higher frequency of selfie taking in girls compared with boys. In contrast, Indian mid-adolescent boys and girls were found to take selfies at a similar frequency. 27 Although studies have also examined offline selfies in young adults (eg, Srivastava et al 28 ), to our knowledge, no studies have examined this practice in children.
In contrast to offline selfies, more is known about the frequency of selfie posting, or online selfies, although the use of different assessment tools for collecting frequency data hampers comparisons across samples. Singaporean early- and mid-adolescent girls were found to post selfies at a rate of approximately once per week. 8 However, their selfie posting was evaluated only through the number of selfies posted on Instagram, 8 which could reflect an underestimation of the total number of selfies posted, as adolescents are also known to post to multiple platforms including Facebook, Snapchat, and WhatsApp. 27 , 29 Indeed, Boursier and Manna 25 reported that 82% of 14–19-year-old Italian adolescents shared selfies through Facebook and other social network sites and 60.2% shared selfies through WhatsApp groups. In investigations of Chinese adolescents' online selfies, Guo et al 30 and Zheng et al 31 also examined posting to single platforms, the Chinese services WeChat friends’ circle and Qzone, respectively. The studies reported noticeably discrepant levels of selfie posting, with greater frequency of posting to WeChat friends’ circle (12–13 selfies posted per month) than to Qzone (with the total sample posting on average a little more than once per month, and a smaller proportion [42.15%] posting more than once per week). The difference in reported posting frequency may be accounted for by different data collection methods. Although self-report was used in both studies, data collected on postings to WeChat friends’ circle 30 provide a somewhat objective measure of selfie posting, as adolescents were asked to check their phones to report how many selfies they had posted to this platform in the previous month. It is possible that when asked to recall their frequency of selfie posting, the method employed by many studies, including Zheng et al, 31 adolescents may underreport their posting, because of either social desirability or inaccuracy of recall. Other studies have also examined frequency of selfie-taking behavior but either they did not report mean responses 32 or responses were in a format (ie, never to always) which precluded conversion to number of selfies posted within a given time-frame. 9 , 26 However, findings from these studies suggest that greater clarity is needed into gender disparities in online selfies, with Dhir et al 26 reporting that girls posted selfies more frequently than boys, which contrasted with the similar rates of posting between boys and girls reported by Guo et al. 30 Additional investigation of online selfies has indicated that adolescents are more active in their selfie posting than young or older adults, 26 , 32 highlighting the need to examine the effects of selfie practices in this population.
Some studies have reported on both offline and online selfies. It has been found that these behaviors are highly positively correlated in early adolescent girls. 9 The average frequency of taking selfies was higher than posting selfies for Norwegian boys and girls, 26 although the difference in frequency of taking and posting selfies was not tested with inferential statistics. Should this discrepancy be formally tested and confirmed in future studies, it may be that this ratio reflects low confidence in sharing selfies on social media, or concerns about appearance, such that adolescents may feel compelled to take many selfies before finding the “right” one to post. This process of taking and curating selfies as part of online self-presentation has been observed in young adult women. 33 The suggestion that adolescents may be concerned about sharing selfies online is also supported by the finding from Dutta et al, 27 that only 30.4% of adolescents felt confident while posting their selfies online. Alternatively, a higher proportion of offline to online selfies may be unrelated to well-being or body confidence, in that adolescents may prefer taking selfies for personal reasons and have no intention of sharing those photos online. For example, Balakrishnan and Griffiths 34 found that young adults have varying motives for selfie taking, some of which were more personally oriented, such as creating memories or enhancing mood. These motives may also apply for adolescents and account for the higher frequency of offline selfies. Further research is required to confirm the consistency of these observations and also to determine whether a difference in the ratio of offline to online selfies is innocuous, or indicative of body image or other concerns.
In addition to selfie taking and posting, engagement in practices to enhance self-presentation in selfies, such as editing and applying filters, has been investigated. A small number of studies have consistently indicated that adolescent girls and boys edit photos to improve appearance, but that they do this only rarely. 8 , 9 , 26 , 35 In addition, when gender comparisons have been conducted, it has been shown that girls edit selfies more frequently than boys through the use of techniques such as filters and cropping 26 and making direct alterations to appearance. 35 Mascheroni et al 36 also found that it is not uncommon for adolescent boys and girls to report editing their social network profile picture, typically of their face, to present an ideal appearance. Furthermore, although quantitative studies indicate that adolescents edit their selfies infrequently, these qualitative findings suggest that adolescents recognize selfie editing performed by others, but appear to be somewhat more reticent to disclose their own editing practices. 36
An intriguing qualitative study of Singaporean girls’ selfie-editing practices shed some light on the motivations behind the use of selfie editing. 37 Girls reflected on selfie editing as a necessary practice to achieve ideal self-presentation to impress one’s peers. Moreover, selfie editing was used as a means to manage insecurity and low self-esteem. Along with editing selfies, planning and staging of selfies, as well as careful selection of the best photo to post, was reported by these adolescent girls and all of these practices were viewed to be important for optimal self-presentation. 37 Similarly, girls from European countries also reported the use of editing and photo-selection practices prior to posting. 36 These observations of co-occurrence of staging, editing, and selecting selfies for posting are consistent with quantitative reports in which planning and photo selection, known as investment in selfies, have been found to be positively correlated with photo editing. 9 , 35 Although the frequency of photo editing has not been found to be high, as touched on here and discussed in more detail below in the body confidence section, emerging findings suggest that such practices appear to be important for well-being and body confidence.
Impact of selfie practices on well-being and body confidence
Selfie viewing.
Only a few studies have examined the impact of viewing selfies on well-being and body confidence in adolescents. Studies have generally found that viewing selfies is associated with poorer outcomes. Cross-sectional studies have shown that in adolescent girls from the USA, relative to overall Facebook use, greater exposure to appearance-related photo use of Facebook, which included engaging in selfie activities such as viewing friends’ selfies and updating one’s profile photo, as well as other non-selfie-related appearance activities including commenting on friends’ photos, posting a photo, and untagging oneself in friends’ photos, was related to a number of indicators of lower body confidence. 38 Similarly, a greater extent of browsing of Instagram selfies was found to be related to lower body confidence in Singaporean girls .8 Furthermore, the relationship between browsing Instagram selfies and lower body confidence was mediated by appearance comparison. 8 Comments by adolescents from the UK in a qualitative study offer some insight into the effects of appearance comparison. Viewing selfies posted to social media by peers could result in the participants experiencing low body confidence or desires to change appearance after comparing how they looked with the posted images. 39
Consistent with these correlational findings, experimental research has demonstrated negative effects on well-being and body confidence of viewing Instagram feeds. For example, following browsing of simulated Instagram feeds which featured gender-matched profiles of a teen model (female) or teen athlete (male), mid-adolescent American girls and boys experienced adverse effects on their positive and negative affect. 40 Specifically, participants who engaged in negative social comparisons while viewing the Instagram profiles had lower positive affect and higher negative affect after viewing the images. 40 Although the proportion of images that were selfies versus non-selfie profile images on these Instagram feeds was not specified in this research, it is likely that they contained a high number of selfies, as this is typically the case with Instagram profiles. 41 Similarly, negative effects on body satisfaction, an important index of body confidence, were reported for mid-adolescent girls from the Netherlands who viewed Instagram selfies of a teenage girl when the selfies had been manipulated (by the researchers) to be closer to appearance ideals. Furthermore, body satisfaction was reduced to a greater degree for participants who had a higher, compared to lower, general tendency to compare themselves with others. 42 It should be noted that this latter study collected only post-exposure measures of body satisfaction. The lack of control for pre-exposure levels suggests that the findings should be interpreted cautiously.
Taken together, these preliminary findings appear to mirror previous research demonstrating a negative impact on mood and body confidence in adolescents from exposure to traditional media 43 , 44 and among adults following exposure to social media. 45 , 46 Importantly, these initial findings of negative outcomes from selfie viewing in adolescents also point to the importance of social comparison as a moderator or predictor of negative effects, consistent with research examining outcomes for adult participants. 47 Thus, individuals with higher tendencies to compare their appearance to that of others seem to be at increased risk of experiencing negative effects of engaging in selfie practices.
Selfie posting and sharing
Research into the impact of selfie taking and posting is slightly more advanced than research on selfie viewing in terms of the volume of studies that have been conducted. Accordingly, a wider range of outcomes has been examined, although there has been greater focus on body image than on well-being.
Social acceptance
In relation to well-being, one area that has been explored is social acceptance. Social acceptance is highly important during the adolescent period 48 and qualitative studies have indicated the extent to which selfie posting, and responses and feedback, particularly in terms of the number of likes received, plays a role in social acceptance for adolescent girls. 36 , 37 In support of this, Boursier and Manna 25 reported that the extent to which adolescent boys and girls expected selfie posting to improve their self-confidence, through increasing popularity and self-esteem, was positively related to the frequency of taking and posting selfies. Despite the importance of peer acceptance in adolescence, teens are critical of attempts to seek acceptance through selfie posting. In this way, early adolescent girls from the USA reported disparaging attitudes to posting selfies, perceiving that the only purpose for doing so was to attempt to seek praise or validation from others. 29 These findings demonstrate the challenging balance that adolescents must negotiate, between pressure to attain peer affirmation through “likes” and simultaneously not appearing to be striving for such affirmation. Although this has not been investigated, it is likely that this double bind may place adolescents under increased stress, particularly those for whom self-esteem is strongly linked to external validation.
The study of the impact of selfies on well-being in adolescents is, to date, limited, and conclusions about the degree to which engagement with selfies has a positive or negative effect on well-being cannot be made. Although research with young adults has been conducted to examine relationships between selfie taking and posting on a range of outcomes, such as self-esteem, 49 mood, 50 and concern about social judgment by others, 51 these outcomes have yet to be explored with adolescents. The emerging evidence in adults has suggested that these relationships may be somewhat complex depending on the timescale of assessments, and the characterization of outcomes as traits or states. For example, while selfie posting may be associated with positive self-esteem at the trait level, it seems that over the shorter term, 49 selfie posting may have more variable effects depending on the feedback received. 52 In light of the centrality of social media for identity development in adolescence, 53 particularly as expressed through self-presentation in selfies, 25 further research on the impact of selfies on well-being in adolescents is needed.
Body confidence
In contrast to the limited focus on selfies and global well-being, further advances have been made in examining the relationship between and the impact of selfies on body confidence, more specifically in adolescents, although only a few studies have been conducted with boys. In studies with adolescent girls, findings have converged on certain points, although other contradictory results have emerged. For both Australian and Singaporean girls, univariate relationships between selfie practices and body image revealed that greater engagement in editing of selfies was associated with lower body confidence. Neither browsing nor posting in Singaporean girls, nor a combined variable reflecting taking and posting selfies in Australian girls, was significantly associated with body image variables. 8 , 9 However, when Singaporean girls’ selfie practices were examined in a multivariate path model, selfie editing was no longer directly related to lower body confidence. In contrast, it was indirectly related via appearance comparisons, whereas a direct positive relationship from selfie posting to body confidence emerged, indicating that higher frequency of selfie posting was associated with greater body confidence. 8 Findings from this study again suggest the importance of appearance comparisons. Selfie posting may activate appearance comparisons with internalized standards of appearance, such that adolescents may compare their selfies to idealized images seen in corporate media, or other digitally modified user-generated content. In addition, the editing and posting of digitally modified selfies may generate social comparisons with an ideal, but unrealistic, online self-presentation. However, in light of the lack of univariate relationship between selfie posting and body confidence, the positive relationship between posting and body confidence in the path model should be interpreted cautiously. As noted by the authors, it is possible that selfie posting was associated with body confidence under circumstances where careful selection of selfies took place, or where positive feedback to the posted selfies was received. 8 These possibilities both have some support from the literature where, as noted previously in the selfie practices section, it has been demonstrated that adolescent girls engage in selective processes for selfie posting, 9 , 35 , 36 and in adult women, positive associations between selfie posting and both body confidence and self-esteem were found to be mediated by the provision of positive feedback received for the selfies. 49
Self-objectification
In addition to examining body confidence outcomes, other studies have examined relationships between selfie practices and self-objectification, that is, the extent to which individuals internalize an external, observer’s perspective of their body. 54 Higher levels of self-objectification reflect a stronger focus on appearance, relative to physical function. The consequences of this focus can be greater attention to or monitoring of appearance, known as body surveillance, and negative evaluation of one’s body, known as body shame. 55 Body shame refers particularly to shame about not achieving an ideal appearance, and is indicative of low body confidence. Zheng et al 31 examined the relationship between frequency of selfie posting to Qzone and self-objectification, namely the importance of appearance relative to body function. They found that Chinese adolescent girls aged 12–18 years with a higher frequency of selfie posting had higher levels of self-objectification. In addition, this relationship was moderated by imaginary audience ideation, which is the extent to which participants assume that others are looking at and thinking about them, such that the relationship between selfie posting and self-objectification was stronger in participants with high relative to low imaginary audience ideation. In a cross-sectional study with boys and girls in early adolescence, greater engagement with appearance-focused social media, including posting selfies alone, with other people, and displaying varying physical features (self only, body and face, body only), was indirectly associated with higher body shame. 56 The association was mediated by body surveillance, such that more appearance-focused social media posting statistically predicted body surveillance, which, in turn, predicted body shame. 56
Peer interactions and feedback
Extending from the discussion on social acceptance above, qualitative work among adolescent girls has suggested that peer interactions are a critical element of selfie posting, and to a large extent moderate the effects of selfie posting on well-being and body confidence. Adolescent girls described how peer recognition motivated selfie posting and engaging in selfie practices, and how the amount and valence of peer feedback play a predominant role in self-esteem and feelings of acceptance. 37 They also described the existence of “social norms” related to the reactions to selfie posting, for example, expectations for receiving a certain number of likes when they post content on social media. 37 However, when this is not achieved, it can result in poorer well-being outcomes among adolescents. 57 Insights from neural responses to feedback on selfies through neuroimaging studies emphasize the role of peer interactions with selfies for social acceptance. Sherman et al 58 found that when adolescents viewed their own selfies that had been manipulated to be presented with a high number of likes, greater neural activity was recorded in areas of the brain implicated in social cognition, reward learning, and motivation relative to viewing selfies with a low number of likes. The authors speculated that receipt of positive feedback in the form of likes is socially rewarding and this behavioral reinforcement operates to motivate further engagement with selfie posting. 58
Positive feedback can indicate popularity and approval from peers (especially on aspects of appearance) and, therefore, this practice may be an important aspect of sharing selfies online. Cross-sectional research by Li et al 59 found that Singaporean adolescent girls place high importance on peer feedback, especially those with low self-esteem. Moreover, this importance is positively associated with depressed mood. 59 Similarly, Nesi and Prinstein 60 examined feedback seeking among US adolescents across one year and found it to be associated with higher levels of depressive symptoms. This effect was moderated by popularity and gender, whereby the effect was stronger among females and less popular adolescents. However, positive feedback from selfie posting may reinforce self-confidence and self-esteem among adolescents when expectations are met. 25 Although the literature examining these relationships in children and young adolescents is still scant, these findings parallel those of studies in adults reporting on the importance of feedback to online postings. 52 , 61 – 63 Thus, consistent with work describing the poorer outcomes of contingent self-esteem, that is, self-esteem that is indexed to the positive feedback received from others, and its association with appearance comparisons, 64 it appears that placing importance on, or seeking, feedback from others on social media may have an overall negative impact on well-being over the longer term.
Additional work has examined the role of appearance comparisons in the effects of engaging in selfie practices among adolescents. Qualitative research has found that adolescent girls explicitly rejected appearance comparisons as a valid means of achieving self-esteem and body confidence, yet at the same time described how such comparisons were difficult to regulate and remained impactful. 29 , 37 In addition, Nesi and Prinstein 60 examined online social comparisons and feedback seeking among adolescents across one year. Their results revealed that social comparisons and feedback seeking were associated with depressive symptoms. Therefore, despite recognizing the pitfalls of engaging in appearance comparisons with images of peers on social media, adolescents reported engaging in such comparisons, which suggests that comparison may constitute a mechanism for the harmful effects of selfie practices on well-being and body confidence.
Thus, the emerging evidence related to the effects and correlates of engaging in selfie practices suggests that social processes, and peer recognition and feedback, may play an important role in both motivating engagement in selfie practices, as well as modulating the impact of these practices on well-being and body confidence. In addition, these findings highlight how overall these practices may be detrimental to sustaining positive self-image, particularly among those who place high importance on peer feedback and recognition.
Future directions
The literature reviewed above represents an emerging area of investigation and a number of important gaps still exist. The first and most critical gap is the near absence of research in children before they reach adolescence. Given the increase in the number of youth who own or have access to a mobile device and a social media account, 2 , 3 extending research to children is critical. Including boys as well as girls in these efforts will also be crucial. A second area of future investigation includes increasing the understanding of the prevalence, function, and impact of engaging with selfies that are not intended for social media, ie, offline selfies. Understanding differences in the motivations and impacts of offline selfies relative to online selfies will be important for orienting future research and practices in settings such as schools or clinical services. Third, while some of the work reviewed above has started to identify vulnerability factors, it would be helpful to identify factors that might also play a role in buffering children from the harmful effects of engaging in selfie practices. Among adults and to a lesser extent adolescents, media literacy specific to social media, as well as dimensions of positive body image, have emerged as promising protective facors. 45 , 65 – 69 Extending this work to include selfie-related initiatives, such as the promotion of “no-makeup selfies”, 70 positively focused selfies, 71 and potentially humor in self presentations, 72 will be necessary to ensure its relevance for adolescents and to combat the harmful aspects of selfie practices. Finally, the overwhelming majority of the existing research, across age groups, is currently cross-sectional, which precludes examination of the directionality of the underlying relationships. Developing experimental and longitudinal designs that can provide support for the directionality of the pathways proposed will be an important target. Overall, future research focused on identifying which types of practices, among which groups, are most harmful for well-being and body confidence among children and adolescents will have the largest impact in terms of moving this field of inquiry forward.
Selfies are a novel, but increasingly widespread phenomenon which has only recently received attention from scholars. The initial evidence suggests that some aspects of selfie practices may be more tightly associated with well-being and body confidence outcomes, namely curating them, and seeking and placing importance on the feedback from peers. In addition, preliminary support has emerged for the moderating effect of some psychological processes such as appearance comparisons. Given the popularity of selfies, further characterizing the effects of engaging in selfie practices is an important area for future research. In addition, investigating how selfies can be used positively, as identity exploration, for fun, or to increase self-esteem, would be highly useful.
The authors report no conflicts of interest in this work.
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Pros & cons: impacts of social media on mental health
- Ágnes Zsila 1 , 2 &
- Marc Eric S. Reyes ORCID: orcid.org/0000-0002-5280-1315 3
BMC Psychology volume 11 , Article number: 201 ( 2023 ) Cite this article
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The use of social media significantly impacts mental health. It can enhance connection, increase self-esteem, and improve a sense of belonging. But it can also lead to tremendous stress, pressure to compare oneself to others, and increased sadness and isolation. Mindful use is essential to social media consumption.
Social media has become integral to our daily routines: we interact with family members and friends, accept invitations to public events, and join online communities to meet people who share similar preferences using these platforms. Social media has opened a new avenue for social experiences since the early 2000s, extending the possibilities for communication. According to recent research [ 1 ], people spend 2.3 h daily on social media. YouTube, TikTok, Instagram, and Snapchat have become increasingly popular among youth in 2022, and one-third think they spend too much time on these platforms [ 2 ]. The considerable time people spend on social media worldwide has directed researchers’ attention toward the potential benefits and risks. Research shows excessive use is mainly associated with lower psychological well-being [ 3 ]. However, findings also suggest that the quality rather than the quantity of social media use can determine whether the experience will enhance or deteriorate the user’s mental health [ 4 ]. In this collection, we will explore the impact of social media use on mental health by providing comprehensive research perspectives on positive and negative effects.
Social media can provide opportunities to enhance the mental health of users by facilitating social connections and peer support [ 5 ]. Indeed, online communities can provide a space for discussions regarding health conditions, adverse life events, or everyday challenges, which may decrease the sense of stigmatization and increase belongingness and perceived emotional support. Mutual friendships, rewarding social interactions, and humor on social media also reduced stress during the COVID-19 pandemic [ 4 ].
On the other hand, several studies have pointed out the potentially detrimental effects of social media use on mental health. Concerns have been raised that social media may lead to body image dissatisfaction [ 6 ], increase the risk of addiction and cyberbullying involvement [ 5 ], contribute to phubbing behaviors [ 7 ], and negatively affects mood [ 8 ]. Excessive use has increased loneliness, fear of missing out, and decreased subjective well-being and life satisfaction [ 8 ]. Users at risk of social media addiction often report depressive symptoms and lower self-esteem [ 9 ].
Overall, findings regarding the impact of social media on mental health pointed out some essential resources for psychological well-being through rewarding online social interactions. However, there is a need to raise awareness about the possible risks associated with excessive use, which can negatively affect mental health and everyday functioning [ 9 ]. There is neither a negative nor positive consensus regarding the effects of social media on people. However, by teaching people social media literacy, we can maximize their chances of having balanced, safe, and meaningful experiences on these platforms [ 10 ].
We encourage researchers to submit their research articles and contribute to a more differentiated overview of the impact of social media on mental health. BMC Psychology welcomes submissions to its new collection, which promises to present the latest findings in the emerging field of social media research. We seek research papers using qualitative and quantitative methods, focusing on social media users’ positive and negative aspects. We believe this collection will provide a more comprehensive picture of social media’s positive and negative effects on users’ mental health.
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Not applicable.
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Ágnes Zsila was supported by the ÚNKP-22-4 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund.
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- Published: 06 October 2020
Authentic self-expression on social media is associated with greater subjective well-being
- Erica R. Bailey ORCID: orcid.org/0000-0002-2924-2500 1 na1 ,
- Sandra C. Matz ORCID: orcid.org/0000-0002-0969-4403 1 na1 ,
- Wu Youyou 2 &
- Sheena S. Iyengar 1
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Social media users face a tension between presenting themselves in an idealized or authentic way. Here, we explore how prioritizing one over the other impacts users’ well-being. We estimate the degree of self-idealized vs. authentic self-expression as the proximity between a user’s self-reported personality and the automated personality judgements made on the basis Facebook Likes and status updates. Analyzing data of 10,560 Facebook users, we find that individuals who are more authentic in their self-expression also report greater Life Satisfaction. This effect appears consistent across different personality profiles, countering the proposition that individuals with socially desirable personalities benefit from authentic self-expression more than others. We extend this finding in a pre-registered, longitudinal experiment, demonstrating the causal relationship between authentic posting and positive affect and mood on a within-person level. Our findings suggest that the extent to which social media use is related to well-being depends on how individuals use it.
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Introduction.
Social media can seem like an artificial world in which people’s lives consist entirely of exotic vacations, thriving friendships, and photogenic, healthy meals. In fact, there is an entire industry built around people’s desire to present idealistic self-representations on social media. Popular applications like FaceTune, for example, allow users to modify everything about themselves, from skin tone to the size of their physical features. In line with this “self-idealization perspective”, research has shown that self-expressions on social media platforms are often idealized, exaggerated, and unrealistic 1 . That is, social media users often act as virtual curators of their online selves 2 by staging or editing content they present to others 3 .
A contrasting body of research suggests that social media platforms constitute extensions of offline identities, with users presenting relatively authentic versions of themselves 4 . While users might engage in some degree of self-idealization, the social nature of the platforms is thought to provide a degree of accountability that prevents individuals from starkly misrepresenting their identities 5 . This is particularly true for platforms such as Facebook, where the majority of friends in a user’s network also have an offline connection 6 . In fact, modern social media sites like Facebook and Instagram are far more realistic than early social media websites such as Second Life, where users presented themselves as avatars that were often fully divorced from reality 7 . In line with this authentic self-expression perspective, research has shown that individuals on Facebook are more likely to express their actual rather than their idealized personalities 8 , 9 .
The desire to present the self in a way that is ideal and authentic is not mutually exclusive; on the contrary, an individual is likely to desire both simultaneously 10 . This occurs in part because self-idealization and authentic self-expression fulfill different psychological needs and are associated with different psychological costs. On the one hand, self-idealization has been called a “fundamental part of human nature” 11 because it allows individuals to cultivate a positive self-view and to create positive impressions of themselves in others 12 . In addition, authentic self-expression allows individuals to verify and affirm their sense of self 13 , 14 which can increase self-esteem 15 , and a sense of belonging 16 . On the other hand, self-idealizing behavior can be psychologically costly, as acting out of character is associated with feelings of internal conflict, psychological discomfort, and strong emotional reactions 17 , 18 ; individuals may also possess characteristics that are more or less socially desirable, bringing their desire to present themselves in an authentic way into conflict with their desire to present the best version of themselves.
Here, we explore the tension between self-idealization and authentic self-expression on social media, and test how prioritizing one over the other impacts users’ well-being. We focus our analysis on a core component of the self: personality 19 . Personality captures fundamental differences in the way that people think, feel and behave, reflecting the psychological characteristics that make individuals uniquely themselves 20 , 21 . Building on the Five Factor Model of personality 22 , we test the extent to which authentic self-expression of personality characteristics are related to Life Satisfaction, hypothesizing that greater authentic self-expression will be positively correlated with Life Satisfaction. In exploratory analyses, we also consider whether this relationship is moderated by the personality characteristics of the individual. That is, not all individuals might benefit from authentic self-expression equally. Given that some personality traits are more socially desirable than others 23 , individuals who possess more desirable personality traits are likely to experience a reduced tension between self-idealization and authentic self-expression. Consequently, individuals with more socially desirable profiles might disproportionality benefit from authentic self-expression because the motivational pulls of self-idealization and authentic self-expression point in the same—rather than the opposite—direction.
Previous literature on authentic self-expression has predominantly relied on self-reported perceptions of authenticity as (i) a state of feeling authentic 24 , or (ii) a judgement about the honesty or consistency of one’s self 25 . However, such self-reported measures have been shown to be biased by valence states, and social desirability 26 , 27 . To overcome these limitations, in Study 1 we introduce a measure of Quantified Authenticity. If authenticity is most simply defined as the unobstructed expression of one’s self 28 , then authenticity can be estimated as the proximity of an individual’s self-view and their observable self-expression. We calculate Quantified Authenticity by comparing self-reported personality to personality judgements made by computers on the basis of observable behaviors on Facebook (i.e., Likes and status updates).
By observing self-presentation on social media and comparing it to the individual’s self-view, we are able to quantify the extent to which an individual deviates from their authentic self. That is, we locate each individual on a continuum that ranges from low authenticity (i.e., large discrepancy between the self-view and observable self-expression) to high authenticity (i.e., perfect alignment between the self-view and observable self-expression). Importantly, our approach rests on the assumption that any deviation from the self-view on social media constitutes an attempt to present oneself in a more positive light, and therefore a form of self-idealization. While a deviation could theoretically indicate both self-idealization and self-deprecation, it is unlikely that users will deviate from their true selves in a way that makes them look worse in the eyes of others. A strength of our measures is that we do not postulate that self-idealization takes a particular form of deviation from the self or is associated with striving for a particular profile. Although research suggests that there are certain personality traits that are more desirable on average 29 , 30 , the extent to which a person sees scoring high or low on a given trait is likely somewhat idiosyncratic and depends—at least in part—on other people in their social network. For example, behaving in a more extraverted way might be self-enhancing for most people; however, there might be individuals for whom behaving in a more introverted way might be more desirable (e.g. because the norm of their social network is more introverted). Hence, our conceptualization of Quantified Authenticity allows for deviations in different directions (see Supplementary Information for more detail).
Quantified Authenticity and subjective well-being
In Study 1, we analyzed the data of 10,560 Facebook users who had completed a personality assessment and reported on their Life Satisfaction through the myPersonality application 31 , 32 . To estimate the extent to which their Facebook profiles represent authentic expressions of their personality, we compared their self-ratings to two observational sources: predictions of personality from Facebook Likes ( N = 9237) 33 and predictions of personality from Facebook status updates ( N = 3215) 34 . These are based on recent advances in the automatic assessment of psychological traits from the digital traces they leave on Facebook 35 . For each of the observable sources, we calculated Quantified Authenticity as the inverse Euclidean distance between all five self-rated and observable personality traits. Our measure of Quantified Authenticity exhibits a desirable level of variance, ranging all the way from highly authentic self-expression to considerable levels of self-idealization (see ridgeline plot of Quantified Authenticity calculated for self-language and Self-Likes in Supplementary Fig. 3 , see Supplementary Tables 1 and 2 for zero-order correlations among variables).
To test the extent to which authentic self-expression is related to Life Satisfaction, we ran linear regression analyses predicting Life Satisfaction from the two measures of Quantified Authenticity (Likes, status updates). The results support the hypothesis that higher levels of authenticity (i.e. lower distance scores) are positively correlated with Life Satisfaction (Table 1 , Model 1 without controls). These effects remained statistically significant when controlling for self-reported personality traits. Additionally, we included a control variable for the overall extremeness of an individual’s personality profile (deviation from the population mean across all five traits), as people with more extreme personality profiles might find it more difficult to blend into society and therefore experience lower levels of well-being 36 (see Table 1 , Model 2 with controls; the results are largely robust when controlling for gender and age, see Supplementary Table 3 ; see Supplementary Figs. 1 and 2 for interactions between individual self-reported and predicted personality traits).
To further explore the mechanisms of Quantified Authenticity, we conducted analyses that distinguished between normative self-enhancement (i.e., rating oneself as more Extraverted, Agreeable, Conscientiousness, Emotionally Stable, and Open-minded than is indicated by one’s Facebook behavior) from self-deprecation (i.e., rating oneself lower on all of these traits). While normative self-enhancement has a negative effect on well-being, normative self-deprecation has no effect. These findings suggest that self-enhancement specifically, rather than overall self-discrepancy/lack of authenticity, is detrimental to subjective well-being (see Supplementary Fig. 4 ).
To test the robustness of our effects, we regressed Life Satisfaction on three additional measures of Quantified Authenticity (i.e., calculated using Manhattan Distance, Cosine Similarity, and Correlational Similarity; see SI for details on these measures). In both comparison sets (likes and status updates), we found significant and positive correlations between the various ways of estimating Quantified Authenticity (see Supplementary Tables 1 and 2 ). The standardized beta-coefficients across all four metrics of Quantified Authenticity and observable sources are displayed in Fig. 1 . Despite variance in effect sizes across measures and model specifications, the majority of estimates are statistically significant and positive (11 out of 16). Importantly, no coefficients were observed in the opposite direction. These results suggest that those who are more authentic in their self-expression on Facebook (i.e., those who present themselves in a way that is closer to their self-view) also report higher levels of Life Satisfaction.
Figure 1 presents standardized beta coefficients for Quantified Authenticity using ordinary least squares regressions in 16 individual regressions predicting Life Satisfaction. Quantified Authenticity is significantly associated with Life Satisfaction in 11 out of the 16 models. Quantified Authenticity is measured as the consistency between self-reported personality and two other sources of personality data: language and Likes, respectively, (indicated in red and blue color). Quantified Authenticity is defined using four distance metrics, respectively: Manhattan, Euclidean, correlation, and cosine similarity (indicated with a letter in the dots). Models with and without control variables are indicated with dashed and solid line, respectively.
In exploratory analyses, we considered whether authenticity might benefit individuals of different personalities differentially. In order to examine this, we regressed Life Satisfaction on the interactions between Quantified Authenticity and each of the five personality traits (e.g., Quantified Authenticity × Extraversion). The results of these interaction analyses did not provide reliable evidence for the proposition that individuals with socially desirable profiles (i.e., high openness, conscientiousness, extraversion, agreeableness, and low neuroticism) benefit from authentic self-expression more than individuals with less socially desirable profiles (see Table 1 , Model 3). While the interactions of the five personality traits with Quantified Authenticity reached significance for some traits and measures, the results were not consistent across both observable sources of self-expression (Likes-based and Language-based). Consequently, we did not find reliable evidence that having a socially desirable personality profile boosts the effect of authenticity on well-being. Instead, individuals reported increased Life Satisfaction when they presented authentic self-expression, regardless of their personality profile.
The findings of Study 1 provide evidence for the link between authenticity on social media and well-being in a setting of high external validity. However, given the correlational nature of the study, we cannot make any claims about the causality of the effects. While we hypothesize that expressing oneself authentically on social media results in higher levels of well-being, it is also plausible that individuals who experience higher levels of well-being are more likely to express themselves authentically on social media. To provide evidence for the directionality of authenticity on well-being, we conducted a pre-registered, longitudinal experiment in Study 2 (see Fig. 2 for an illustration of the experimental design).
Figure 2 presents the longitudinal experimental study design for Study 2 with key timepoints, interventions, and surveys.
Experimental manipulation of authentic self-expression on well-being
We recruited 90 students and social media users at a Northeastern University to participate in a 2-week study ( M age = 22.98, SD age = 4.17, 72.22% female). The sample size deviates from our pre-registered sample size of 200. The reason for this is that the behavioral research lab of the university was shut down after the first wave of data collection due to the COVID-19 pandemic.
All participants completed two intervention stages during which they were asked to post on their social media profiles in a way that was: (1) authentic for 7 days and (2) self-idealized for 7 days. The order in which participants completed the two interventions was randomly assigned. This experimental set-up allowed us to study the effects of authentic versus idealized self-expression on social media in between-person (week 1) and within-person analyses (comparison between week 1 and week 2). All analyses were pre-registered prior to data collection 37 . Given the reduced sample size, the effects reported in this paper are all as expected in effect size, but only partially reached significance at the conventional alpha = 0.05 level. Consequently, we also consider effects that reach significance at alpha = 0.10 as marginally significant.
All participants completed a personality pre-screen (IPIP) 38 prior to beginning the study, and received personalized feedback report at the beginning of the treatment period (t0). Both the authentic and self-idealized interventions (see Methods for details) asked participants to reflect on that feedback report and identify specific ways in which they could alter their self-expression on social media to align their posts more closely with their actual personality profile (authentic intervention) or to align their posts more closely with how they wanted to be seen by others (see Supplementary Information for treatment text and examples of responses). The operationalization of the treatment follows our conceptualization of Quantified Authenticity in Study 1 in that it does not prescribe the direction of personality change (e.g. towards higher levels of extraversion). Instead, this design leaves it up to participants what posting in a more desirable way means in relation to their current profile.
Participants self-reported their subjective well-being as Life Satisfaction 39 , a single-item mood measure, and positive and negative affect 40 a week after the first intervention (t1), and a week after the second intervention (t2). This design allowed us to examine the causal nature of posting for a week in which participants posted authentically (“authentic, real, or true”), compared to a week in which they posted in a self-idealized way (“ideal, popular or pleasing to others”). Specifically, we hypothesized that individuals who post more authentically over the course of a week would self-report greater subjective well-being at the end of that week, both at the between and within-person level.
We examined the effect of authentic versus self-idealized expression at the between person level at t1 (see t1 in Fig. 3 ) using independent t -tests. Contrary to our expectations, we did not find any significant differences between the two conditions for any of the well-being indicators. This suggests that individuals in the authentic vs. self-idealized conditions did not differ from one another in their level of well-being after the first week of the study. However, when examining the effect within subjects using dependent t -tests we found that participants reported significantly higher levels of well-being after the week in which they posted authentically as compared to the week in which they posted in a self-idealized way. Specifically, the well-being scores in the authentic week were found to be significantly higher than in the self-idealized week for mood (mean difference = 0.19 [0.003, 0.374], t = 2.02, d = 0.43, p = 0.046) and for positive affect (mean difference = 0.17 [0.012, 0.318], t = 2.14, d = 0.45, p = 0.035), and marginally significant for negative affect (mean difference = −0.20 [−0.419, 0.016], t = −1.84, d = 0.39, p = 0.069). There was no significant effect on Life Satisfaction (mean difference = 0.09 [−0.096, 0.274], t = 0.96, d = 0.20, p = 0.342).
The bar chars illustrate the standardized mean of well-being indicators (mood, positive affect, negative affect, and Life Satisfaction) across two study time points by condition. The red bars indicate scores for the weeks in which participants were asked to post authentically, and the blue bars scores for the weeks in which they were asked to post in a self-idealized way. Error bars represent standard errors. The left-side panel presents Group A who received the authenticity treatment followed by the idealized treatment. The right-side panel presents Group B who received the idealized treatment followed by the authenticity treatment. This experiment was conducted once with independent samples in each group.
These findings are reflected in Fig. 3 which showcases the interactions between condition and time point. The graphs highlight that subjective well-being was higher in the weeks in which participants were asked to post authentically (red bars) compared to those in which they were asked to post in a self-idealized way (blue bars). While there was no difference in subjective well-being across conditions at t1, subjective well-being measures differed significantly between the authentic and self-idealized conditions at t2. We found no significant difference between conditions on Life Satisfaction (mean difference = 0.29 [−0.226, 0.798], t = 1.11, d = 0.23, p = 0.270), however, we found a significant difference between conditions such that the group which received the authenticity treatment had greater positive affect (mean difference = 0.45 [0.083, 0.825], t = 2.43, d = 0.51 , p = 0.017), lower negative affect (mean difference = −0.57 [−1.034, −0.113], t = −2.47, d = 0.52, p = 0.015), and higher overall mood (mean difference = 0.40 [0.028, 0.775], t = 2.14, d = 0.45 , p = 0.036).
The findings of the experiment provide support for the causal relationship between posting authentically, compared to posting in a self-idealized way, on the more immediate affective indicators of subjective-wellbeing, including mood and affect, but not on the more long-term, cognitive indicator of life satisfaction. This findings aligns with our pre-registration in that we had predicted mood and affect measures to be more sensitive to the treatment compared to Life Satisfaction, which is a broader global assessment one’s overall life 39 and less likely to change in the course of a week.
Additionally, the fact that we did not find significant effects in our between-subjects analysis in the first week of the study suggests that authentic self-expression might be difficult to manipulate in a one-off treatment as social media users are likely used to expressing themselves on social media both authentically and in a self-idealized way. Thus, when only one strategy is emphasized, participants might not shift their behavior. This is supported by the finding that participants did not differ significantly in their subjective experience of authenticity on social media at t1 (mean in authentic condition at t1 = 5.56, mean in self-idealized condition at t1 = 5.55, t = 0.05, d = 0.01, p = 0.958; Participants responded to a single item, which read “This past week, I was authentic on social media” on a 7-point scale where 1 = strongly disagree and 7 = strongly agree), indicating that the between-subjects manipulation was unsuccessful in getting people to shift their behaviors more toward self-idealized or authentic self-expression compared to their baseline. However, the contrast of the two strategies highlighted in the within-subjects part of the study seems to have successfully shifted participants’ behavior. When compared within person, students did indeed report higher levels of experienced authenticity in their posting during the week in which they were instructed to post authentically (mean difference = 0.30 [0.044, 0.556], t = 2.33, d = 0.49, p = 0.022).
We often hear the advice to just be ourselves. Indeed, psychological theories have suggested that behaving in a way that is consistent with the self-view is beneficial for individual well-being 41 . However, prior investigations of authenticity and well-being have relied solely on self-reported measures which can be confounded by valence and social desirability biases. We estimated authenticity as the proximity between the self-view and self-expression on social media—which we termed Quantified Authenticity—and found that authentic self-expression on social media was correlated with greater Life Satisfaction, an important component of overall well-being. This effect was robust across two comparison points, computer modeled personality based on Facebook Likes and status updates. Our findings suggest that if users engage in self-expression on social media, there may be psychological benefits associated with being authentic. We replicate this finding in a longitudinal experiment with university students; being prompted to post in an authentic way was associated with more positive mood and affect, and less negative mood within participants. Contrary to our second hypothesis, we did not find consistent support for interactions between personality traits and authenticity, such that individuals with more socially desirable traits would benefit more from behaving authentically. Instead, our findings suggest that all individuals regardless of personality traits could benefit from being authentic on social media.
Our findings contribute to the existing literature by speaking directly to conflicting findings on the effects of social media use on well-being. Some studies find that social media use increases self-esteem and positive self-view 42 , while others find that social media use is linked to lower well-being 43 . Still, others find that the effect of social media on well-being is small 44 or non-existent 45 . In an attempt to reconcile these mixed findings, researchers have suggested that the extent to which social media platforms related to lower or higher levels of well-being might depend not on whether people use them but on how they use them. For example, research has shown that active versus passive Facebook use has divergent effects on well-being. While passively using Facebook to consume the content share by others was negatively related to well-being, actively using Facebook to share content and communicate was not 46 . We add to this growing body of research by suggesting that effects of social media use on well-being may also be explained by individual differences in self-expression on social media.
Our study has a number of limitations that should be addressed by future research. First, our analyses focused exclusively on the effects of authentic social media use on well-being, and cannot speak to the question of whether an authentic social media use is better or worse than not using social media at all. That is, even though using social media authentically is better than using it in a more self-idealizing way, the overall effect of social media use on well-being might still be a negative. Future research could address this question by directly comparing no social media use to authentic social media use in both correlational and experimental settings.
Second, our findings do not provide any insights into why individuals might behave more or less authentically. For example, a deviation from the self-view might be explained by a lack of self-awareness, or an intentional misrepresentation of the self. It is possible that depending on whether deviation is driven by intent or not, authenticity might be more or less strongly related to well-being. That is, the psychological costs of deviating from one’s self-view might be stronger when they are intentional such that the individual is fully aware of the fact that they are behaving in a self-idealizing way. Future research should explore this factor empirically.
Finally, the effects of authentic self-presentation on social media on well-being are robust but small (max(β) = 0.11) when compared to compared to other important predictors of well-being such as income, physical health, and marriage 47 , 48 , 49 . However, we argue that the effects described here are meaningful when trying to understand a complex and multifaceted construct such as Life Satisfaction. First, Study 1 captures authenticity using observations of actual behavior rather than self-reports. Given that such behavioral data captured in the wild do not suffer from the same response biases as self-reports which can inflate relationships between variables (e.g. common method bias 50 ), and are often noisier than self-reports, their effect sizes cannot be directly compared 51 . In fact, the effect sizes obtained in Study 2 which was conducted in a much more controlled, experimental setting shows that the effect of authenticity on subjective well-being is substantially larger when measured with more traditional methods (max(d) = 0.45). In addition, while other factors such as employment and health are stronger predictors of well-being, they can be outside of the immediate control of the individual. In contrast, posting on social media in a way that is more aligned with an individual’s personality is both up to the individual and relatively easy to change.
Social media is a pervasive part of modern social life 52 . Nearly 80% of Americans use some form of social media, and three quarters of users check these accounts on a daily basis 53 . Many have speculated that the artificiality of these platforms and their trend towards self-idealization can be detrimental for individual well-being. Our results suggest that whether or not engaging with social media helps or hurts an individual’s well-being might be partly driven by how they use those platforms to express themselves. While it may be tempting to craft a self-enhanced Facebook presence, authentic self-expression on social media can be psychologically beneficial.
Study 1. Participants and procedure
Data were collected through the MyPersonality project, an application available on Facebook between 2007 and 2012 31 . Users of the app completed validated psychometric tests including a measure of the Big Five personality traits 22 , 54 , and received immediate feedback on their responses. A subsample of myPersonality users also agreed to donate their Facebook profile information—including their public profiles, their Facebook likes, their status updates, etc.—for research purposes. In addition, users could invite their Facebook friends to complete the personality questionnaire on their behalf, judging not their own personality but that of their friend.
To calculate authenticity, we developed a measure we refer to as Quantified Authenticity (QA). To compute this measure, we compared a person’s self-reported personality to two external criteria: (1) their personality as predicted from Facebook Likes, and (2) their personality as predicted from the language used in their status updates (see “Measures” section below for more information). The number of participants varied between the two samples based on exclusionary criteria. To be included in the Language-based model, individuals had to have posted at least 500 words of Facebook status updates ( N = 3215). In the Likes-based model, only participants with 20 or more Likes were included ( N = 9237).
Big Five personality
Participants’ personality was measured using the well-established Five Factor model of personality, also known as Big Five traits 54 , 55 . The Five Factor model posits five relatively stable, continuous personality traits: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. The Big Five personality traits have been found to be stable across cultures, instruments, and observers 56 . Additionally, years of research have linked them to a broad variety of behaviors, preferences and other consequential outcomes, including well-being 57 and behavior on Facebook 58 .
Self-reported personality
Participants’ views of their own personalities are based on the well-established International Personality Item Pool or IPIP 38 . Participants included in the analyses responded to 20–100 questions using a 5 point Likert-scale where 1 = strongly disagree to 5 = strongly agree.
Computer-based predictions of personality from likes and status updates
Recent methodological advances in machine learning have provided researchers with the ability to predict the personality of individuals from their social media profiles 33 , 34 , 35 . Here, we used personality prediction of personality from Facebook Likes and the language used in status updates. For Facebook Likes ( N = 9327), we obtained the personality predictions made by Youyou and colleagues 33 , who used a 10-fold cross-validated LASSO regression to predict Big Five personality traits out of sample. On average, the predictions captured personality with an accuracy of r = 0.56 (correlation between predicted and self-reported scores). For status updates ( N = 3215), we obtained the predictions made by Park et al. 34 , who used cross-validated Ridge regression to infer personality from language features, such as individual words, combinations of words (n-grams), and topics. On average, the predictions captured personality with an accuracy of r = 0.41 (correlation between predicted and self-reported scores).
Personality extremeness
We calculated extremeness of participants’ personality profiles as a control variable for our analyses by summing the absolute z -scores on all five traits. We include extremeness because extreme individual scores tend to produce larger absolute difference scores. Additionally, previous work has found that people with more extreme personality profiles might find it more difficult to blend into society and therefore experience lower levels of well-being 36 .
Self-ratings of well-being
Individuals reported their Life Satisfaction—a key component of subjective well-being—on a five-item scale 39 . The SWLS has been shown to be a meaningful psychological construct, correlated with a number of important life outcomes such as marital status and health 59 .
Quantified Authenticity
Quantified Authenticity was calculated in three steps. First, we z -standardized the personality scores on each of the three measures (self, Likes, language) to obtain a person’s relative standing on the five personality traits in comparison to the reference group. Second, we computed the distance between self-reported personality and each of the externally inferred personality profiles using Euclidean distance, a widely established distance measure, which has been used in previous psychological research 36 . To make our measure more intuitively interpretable, we finally subtracted the distance measure from zero to obtain a measure of Quantified Authenticity for which higher scores indicate higher levels of authenticity. See Eq. ( 1 ) below.
For individual i , x i is the Cartesian coordinate of the self-view in a 5 -dimensional personality space. For individual i, y i is the Cartesian coordinate of the language-, or likes-based personality. Our measure of Quantified Authenticity exhibited desirable level of variance, ranging all the way from highly authentic self-expression to considerable levels of self-idealization (see ridgeline plot of standardized Quantified Authenticity calculated based on Language and Likes in Supplementary Fig. 3 ). Additional information on the calculation of the three other metrics of Quantified Authenticity (i.e., Manhattan distance, correlational similarity, and cosine similarity) can be found in the SI.
Study 2. Participants and procedure
All study procedures were approved by the Columbia University Human Research Protection Office and informed consent was received from all study participants. Prior to completing the study, participants completed a pre-screening survey. This included a number of questions related to their social media activity and the BFI-2S as a measure of their Big Five personality traits 60 . Participants who qualified for the study were randomly assigned to one of two groups depicted as “Group A” and “Group B” in Fig. 3 ). Both groups received both interventions (authentic and self-idealized), however they received the treatments in a different order.
The study took place over the course of 2 weeks. On the first day of the study, participants received an email, which included the results of their personality test taken in the pre-screen. They then self-reported their baseline subjective well-being (t0). At the end of the survey, half of the students were asked to use the personality feedback to list three ways in which they could express themselves more authentically over the next week on social media. The second group was asked to list with three ways to express themselves in a more self-idealized way.
At the end of the first week, participants received an email with the second survey link. They completed the same subjective well-being measures (t1; Day 0–7), and were shown their personality feedback again as a reminder. The students who were previously assigned to the authentic condition were now asked to list three ways to express themselves in a more self-idealized way (based on their personality profile), and vice versa (reversing the intervention assignments). At the end of the second week, participants received an email with the final survey link. They completed the same subjective well-being measures (t2; Day 7–14).
Subjective well-being
Individuals reported their Life Satisfaction on the same five-item scale as Study 1 39 . In addition, participants responded to positive and negative affect 40 and a single-item general mood measure.
Preregistration note
We had pre-registered the use of the Positive and Negative Affect Scale 61 . However, due to an oversight of the research team, we accidentally collected data using the Brief Mood Inventory Scale 40 . In the SI, we replicate the results using a subset of items, which overlap between the BMIS and the PANAS-X. Given that the two scales are highly correlated, share the same format, and even share some of the same descriptors, we do not expect that the results would have been different when using the PANAS scale.
Reporting summary
Further information on research design is available in the Nature Research Reporting Summary linked to this article.
Data availability
Data for Study 1 are available upon request to the authors. Data for Study 2 relevant to the analyses described are available on our OSF page ( https://osf.io/fxav6/ ). Source data are provided with this paper.
Code availability
Code to reproduce the analyses for Study 1 and Study 2 described herein is available on OSF ( https://osf.io/fxav6/ ).
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We thank Blaine Horton, Jon Jachimowicz, Maya Rossignac-Milon, and Kostadin Kushlev for critical feedback which substantially improved this paper.
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Bailey, E.R., Matz, S.C., Youyou, W. et al. Authentic self-expression on social media is associated with greater subjective well-being. Nat Commun 11 , 4889 (2020). https://doi.org/10.1038/s41467-020-18539-w
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