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Getting Fewer "Likes" Than Others on Social Media Elicits Emotional Distress Among Victimized Adolescents

Abstract

Three studies examined the effects of receiving fewer signs of positive feedback than others on social media. In Study 1, adolescents (N = 613, Mage = 14.3 years) who were randomly assigned to receive few (vs. many) likes during a standardized social media interaction felt more strongly rejected, and reported more negative affect and more negative thoughts about themselves. In Study 2 (N = 145), negative responses to receiving fewer likes were associated with greater depressive symptoms reported day-to-day and at the end of the school year. Study 3 (N = 579) replicated Study 1's main effect of receiving fewer likes and showed that adolescents who already experienced peer victimization at school were the most vulnerable. The findings raise the possibility that technology which makes it easier for adolescents to compare their social status online-even when there is no chance to share explicitly negative comments-could be a risk factor that accelerates the onset of internalizing symptoms among vulnerable youth.
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Abstract
Three studies examined the effects of receiving fewer signs of positive feedback than
others on social media. In Study 1, adolescents (N = 613, M Age = 14.3 years) who were
randomly assigned to receive few (vs. many) likes during a standardized social media interaction
felt more strongly rejected, and reported more negative affect and more negative thoughts about
themselves. In Study 2 (N=145), negative responses to receiving fewer likes were associated with
greater depressive symptoms reported day-to-day and at the end of the school year. Study 3 (N =
579) replicated Study 1’s main effect of receiving fewer likes and showed that adolescents who
already experienced peer victimization at school were the most vulnerable. The findings raise the
possibility that technology which makes it easier for adolescents to compare their social status
online—even when there is no chance to share explicitly negative comments—could be a risk
factor that accelerates the onset of internalizing symptoms among vulnerable youth.
Keywords: adolescence, social media, social validation, evaluative feedback, depression,
stress coping
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Getting Fewer “Likes” Than Others on Social Media Elicits Emotional Distress Among
Victimized Adolescents
In the last few years, there has been a worldwide increase in the use of Internet
applications to publicly share content with others (i.e., social media), and this has created
unprecedented opportunities for social connection, self-expression, and feedback. This trend has
been especially pronounced among adolescents, who are typically the first to adopt new
technologies (Spies Shapiro & Margolin, 2014). In the U.S., over 80 percent of 14- to 22-year-
olds are currently active, daily users of social media (Rideout & Fox, 2018); nearly 70% say that
they check their social media applications multiple times per day. Co-occurring with this increase
in social media use has been a dramatic and alarming increase in youth mental health problems,
leading some to question whether social media might be contributing to this trend (Beyens,
Frison, & Eggermont, 2016; Blomfield-Neira & Barber, 2014; Kross et al., 2013; Nesi &
Prinstein, 2015; Shakya & Christakis, 2017; Vernon, Modecki, & Barber, 2017).
New technological advances like social media, however, are unlikely to be uniformly
good or uniformly bad (Odgers, 2018). Therefore, it is critical for research to understand for
whom, and under what conditions interactions on social media might cause emotional distress.
Odgers (2018) has argued that many interactions on social media are harmless or even positive,
but some could magnify social-emotional vulnerabilities among subgroups of adolescents who
are already struggling. Yet to date only a few small studies have begun to investigate this (e.g.,
Forest & Wood, 2012), and none have focused on the specific mechanisms that could explain it.
Our research examined one common experience on social media that could be a risk
factor for youth: insufficient social validation, defined as not getting enough positive feedback
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from others about the content one has shared. We hypothesized that insufficient social validation
could threaten adolescents’ need for status and acceptance and pose a risk factor for the
development of internalizing symptoms, even in the absence of active, targeted social rejection
or exclusion like cyberbullying or peer harassment. Furthermore, adolescents who are the most
attuned to threats to their status—for instance, those who are suffering ongoing peer
victimization—may be most negatively affected. If this proved to be the case, it would suggest
that a common medium that millions of young people are using might contribute to feelings of
inadequacy and reduced emotional well-being among vulnerable adolescents.
Adolescent Sensitivity to Social Status
Our research is grounded in the adolescent social-affective learning model (Crone &
Dahl, 2012; Blinded for peer review) and we tie this together with the need-threat model
(Williams, 2009) that has been used extensively to understand the effects of ostracism in adult
populations. According to the adolescent social-affective learning model, adolescence is a
developmental period characterized by heightened motivational and affective sensitivity to
experiences that signal differences in social status among peers. Status-relevant experiences can
therefore evoke intense emotional reactions. Many status-relevant experiences engender positive
feelings (e.g. pride, respect) and can help adolescents adapt and thrive. However many status-
relevant experiences are negative (being excluded, ignored, rejected, or humiliated), and are risk
factors for internalizing mental health problems (Crone & Dahl, 2012).
Past experiments with adolescents have shown that peer rejection events—those that
threaten adolescents’ developmentally salient need for status and acceptance—can elicit
psychological pain and emotional distress (Eisenberger, Lieberman, & Williams, 2003; Guyer,
Caouette, Lee, & Ruiz, 2014; Masten et al., 2011; Sebastian, Viding, Williams, & Blakemore,
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2010; Silk et al., 2014; Thomaes et al., 2010). Furthermore, adolescents’ neural and affective
responses to peer rejection events (e.g., being excluded from an online ball toss game; being
disliked by interaction partners) have been associated with elevated risks for internalizing
symptoms, most notably depression (Masten et al., 2011; Prinstein & Aikins, 2004; Silk et al.,
2014). However, all past research on this topic focused on peer rejection events that involved
explicitly negative feedback (e.g., dislike, exclusion). Prior experimental work on adolescents
has not examined a network of people posting self-disclosures and exchanging “likes” as a
means to gain public, quantifiable signs of social status as is done on typical social media
platforms. Thus, there is not yet strong evidence about adolescents’ affective responses to
insufficiently positive feedback that can threaten their needs for status.
Social media is increasingly a place where adolescents’ status is on public display, and
therefore it could pose a risk for emotional distress among those whose social status is
threatened. Users on social media typically contribute content—a link, a picture, a quip, or a
personal disclosure—and expect that others will indicate their approval by giving it a like (i.e.,
clicking a button that says “like”) or something similar. Likes on social media are quantifiable,
public signs of status (see Nesi & Prinstein, 2018 for digital status-seeking on social media), and
so getting another person to like one’s self-expression elicits feelings of validation, conferring
positive status and regard, and thus leads to positive emotions (Davey, Allen, Harrison, Dwyer, &
Yücel, 2009; Gunther Moor, van Leijenhorst, Rombouts, Crone, & Van der Molen, 2010). By the
same token, getting fewer likes than others can be a sign that one has low social status. In fact, a
national survey of youth in the U.S. (Rideout & Fox, 2018) found that 56% of respondents said it
was a negative experience to post content on social media and not receive enough likes.
Similarly, some studies have suggested that positive evaluative feedback (e.g., likes) on social
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media has made unhealthy social comparisons salient (Appel, Gerlach, & Crusius, 2016; Nesi &
Prinstein, 2015), especially among social or emotionally vulnerable individuals (Appel, Crusius,
& Gerlach, 2015; Blease, 2015; Burrow & Rainone, 2017; Forest & Wood, 2012).
One lens for understanding this complex set of issues is the need-threat model of
ostracism (Williams, 2009). In the need-threat model, being excluded or ignored by others
without any explanation or overtly negative behaviors—that is, being ostracized (Williams,
2009)—threatens basic psychological needs, such as the need for social status and acceptance.
Research on the need-threat model has shown that ostracism can elicit negative affect (Sebastian
et al., 2010), and reduce self-esteem (Jamieson, Harkins, & Williams, 2010; Leary, Terdal,
Tambor, & Downs, 1995) even in the absence of active, targeted negative feedback such as
bullying, harassment, or aggression.
Insufficient validation on social media is a modern form of ostracism that may elicit
feelings of rejection, a sign that adolescents’ developmentally salient need for status and
acceptance have been threatened (Crone & Dahl, 2012; Dahl, Allen, Wilbrecht, & Suleiman,
2018; Yeager et al., 2018). Insufficient validation may then trigger consequences of this need
threat, such as negative affect (e.g., feeling distressed, sad, anxious, or embarrassed), and
negative self-relevant cognitions (viewing oneself as less worthy, or less likable), which are
known risk factors for depression (Hankin & Abramson, 2001; Masten et al., 2011; Slavich,
O’Donovan, Epel, & Kemeny, 2010). Evidence supporting our proposal could provide
mechanistic insight into the conditions under which social media use can be associated with poor
mental health, and to whom insufficient validation could pose greater risks (Blomfield-Neira &
Barber, 2014; Feinstein et al., 2013; Lin et al., 2016; Steers, Wickham, & Acitelli, 2014).
The Present Research
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The primary goals of the current research were to: (1) test whether insufficient positive
feedback on social media causes rejection feelings and negative affective-cognitive responses
among adolescents during a socially stressful developmental stage (the first year of high school;
Crosnoe, 2011, Yeager, Lee, & Jamieson, 2016) (Study 1); (2) examine whether feelings of
rejection elicited from insufficient validation on social media predicted elevated risks for
depression (Study 2); and (3) examine whether the effects of insufficient positive social media
feedback were more pronounced among adolescents who more frequently experienced peer
victimization in face-to-face peer contexts (Study 3).
Study 1 used a random-assignment experimental approach. This was important because
the vast majority of studies in this area have used correlational designs that preclude direct
claims about the causal effect of social media. We adapted a standardized social media
interaction with a group of electronic confederates, previously used with adults (Schneider et al.,
2017; Wolf et al., 2015), to make it age-appropriate for adolescents. Previous studies with college
students and older adults found that this manipulation (e.g., receiving few likes) created short-
term threats to needs to belonging, control, and self-esteem relative to many likes condition
(Schneider et al., 2017; Wolf et al., 2015). However, no prior studies have administered this task
or similar social media-like interaction paradigms with adolescents, who are thought to be more
vulnerable to status-relevant feedback and stress-induced internalizing disorders than adults
(Crone & Dahl, 2012; Hammen, 2005). In school settings, we assigned adolescents to receive
few likes (our operationalization of insufficient social validation) or many likes (our
operationalization of sufficient social validation). Analyses tested whether getting few likes (but
no explicitly negative feedback) would (a) increase feelings of rejection, which would be a sign
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that adolescents were interpreting the experience as a threat to their status and acceptance, and
(b) elicit negative affect and self-relevant cognitions, which are consequences of need threat.
Next, Study 2 examined whether adolescents who felt more strongly rejected by
insufficient validation on the social media task might show heightened prospective risk for
depression. To this end, Study 2 collected additional data from a subset of participants from two
of the schools in Study 1 (N=145), including 10 days of diary reports of stressors and stress
responses, and an 8-month follow-up on depressive symptoms. Study 2 examined whether
adolescents who felt more intensely rejected by receiving few likes also reported greater negative
affect and cognitions in response to daily stressors over 10 days, measured via a daily diary, and
were more likely to show increases in depressive symptoms, measured 8 months later. Study 2 is
unique in that it can contribute to identifying one mechanistic explanation for how positive social
media feedback might worsen adolescents’ mental health outcomes. Moreover, Study 2 provides
the ecological validity of the experimental task, that has long been of interest to
developmentalists (c.f., Bronfenbrenner, 1977).
Finally, Study 3 replicated effects of Study 1 in a well-powered sample, and tested for a
key moderator: adolescents’ reported frequency of prior peer victimization. This is the first direct
test of Odgers’ (2018) hypothesis that social media might serve to magnify existing social-
emotional vulnerabilities in youth. We expected that victimized adolescents might be more
vulnerable to insufficient positive validation on social media for two complementary reasons.
First, insufficient positive validation is attributionally-ambiguous, in that it is rarely obvious to a
person why others did not like one’s post. A teen could ask: was it because they were distracted?
Busy? Not on social media? Or do they truly dislike me or intentionally ignore me? Victimized
youth might be more likely to “go beyond the information given” (Bruner, 1957) and attribute
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the cause of ambiguous social media interactions to negative characteristics of themselves (e.g.,
“maybe I’m not a likable person.”) and therefore exhibit stronger rejection distress and negative
internalizing-type affect (Graham & Juvonen, 1998; Schacter, White, Chang, & Juvonen, 2015).
Second, peer victimization in face-to-face contexts might increase sensitivity to any experience
relevant to social status, and therefore enhance the effects of insufficient validation on social
media.
Study 1
Methods
Participants
Data were collected from N=613 ninth-grade adolescents (Mage= 14.3, SDage= 0.70) who
were enrolled in a summer prep program, a public magnet school, or one of three urban public
high schools. The sample size was determined by our attempt to recruit a maximum number of
active consent students from the schools during the 2015-2017 school years; the decision to stop
data collection was made without knowledge of the results of the studies. All schools were
located in middle- to upper-middle class neighborhoods with varying degrees of racial/ethnic
diversity. The sample included 55% females; 44.9% White/European American, 31.8%
Hispanic/Latinx, 3.5% Black/African American, 12.3% Asian/Asian American/Pacific Islanders,
0.3% Native American Indians, and 6.8% multi-racial or another race/ethnicity. See Table 1 and
Table S1 in the online supplement for demographic characteristics.
Procedure
Participation occurred during the fall semester of 9th-grade (or, for one school, the
summer before 9th-grade) in 2016-17. Data collection occurred in school classrooms or computer
labs. Research assistants blind to condition assignment and to hypotheses verbally informed
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participants that they could skip any questions or withdraw from the study at any phase without
penalty. Participants reported baseline psychosocial characteristics (i.e., depressive symptoms) 2-
3 weeks before the social media task in a separate session. We did not detect any pre-existing
differences in depressive symptoms and other psychological characteristics between randomly
assigned groups (see the online supplement Table S2).
On the day that the social media task was administered, researchers informed students
that they were invited to help the researchers pilot a new program called a “Get-to-Know-People
Task,” purportedly designed to connect people. Participants were told that they would spend the
next 3 minutes virtually interacting with other people on the task and then provide feedback on a
brief questionnaire afterward. In actuality, these other people were pre-programmed computer
scripts generated from pilot studies with hundreds of actual high school adolescents (see online
supplement). Cardboard dividers or screen filters were set up on individual seats to ensure
participants’ privacy as well as to minimize potential disruption from adjacent peers.
Computer scripts randomly assigned adolescents to either the “few likes” (insufficient
social validation) or “many likes” (sufficient social validation) condition. We oversampled the
“few likes” condition (N=454 vs. N=159) to ensure sufficient statistical power to analyze
individual differences in acute rejection feelings within “few likes” condition (see Study 2). After
the 3-minute interaction, students completed a brief questionnaire assessing post-task feelings of
rejection, negative affect, negative self-referent cognitions, and open-ended feedback about their
reactions to other people on the task.
At the end of the task, participants were debriefed to ensure that they felt no distress from
having received few likes; they were thanked for their participation and compensated with a
small gift (e.g., a college keychain worth under $5). Out of an abundance of caution, in a sub-
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sample (N=145) we tested whether random assignment to insufficient social validation (few
likes) condition caused long-term changes in global self-esteem (Rosenberg, 1965) and perceived
global stress (Cohen, Kamarck, & Mermelstein, 1983). As expected, analyses found no long-
term manipulation effects, b= 0.03, p= .765 for 8-month global self-esteem; b= -0.48, p= .424 for
8-month global stress, consistent with the conclusion that receiving few likes was meaningful in
the moment (and therefore useful for testing the hypotheses), but does not cause enduring harm.
Social Media Task. We adapted a paradigm developed by Wolf and colleagues (2015) to
manipulate the level of social validation received by participants: (1) For credibility purposes, we
collected actual high school students’ profiles from pilot studies and used them to create four
parallel versions of the task with varying profile descriptions; (2) Our task included a “ranking
board” that displayed the real-time rank order of the number of likes; and (3) The position of
others’ profiles was randomized to create a variety of visual appearances, in order to minimize
suspicion in the field setting (see online supplement). In a preliminary analysis, task versions did
not significantly moderate adolescents’ acute negative responses, ps > .20, so task version is
ignored in all subsequent analyses.
Participants were instructed that during the 3-minute interaction with a group of other
people, they would read and react to each other’s profiles (that were written by actual high
school students in pilot studies). Participants typed in their initials and then selected an avatar (a
cartoon depiction to represent them during the task). Participants wrote a brief self-descriptive
paragraph (up to 400 English characters) to ostensibly introduce themselves to other people
during the interaction. Written instructions read:
Write something you would like to say about yourself - anything you want to share. For
instance, students usually write about their favorite movies, books, music, sports team, or
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hobbies. Also, you could write about your typical weekend plans, extracurricular
activities, or any clubs you're in. Feel free to add #Hashtags if you can think of words or
phrases that represent who you are!”.
Before connecting, participants learned that they could endorse others’ profiles by clicking a like
button, similar to the like button on real-world social media platforms, such as Facebook,
Instagram, etc. See Figure 1.
Participants were presented with one of four equivalent task versions and were randomly
assigned to either “few likes” condition (insufficient social validation) or “many likes” condition
(sufficient social validation). In reality, other players’ like distributions were determined by pre-
programmed computer scripts. In the few likes condition, participants received only two likes
(approximately 18% of the maximum number of likes; comparable to the number of ball tosses
in the Cyberball (Williams & Jarvis, 2006) exclusion condition from eleven people, which placed
them at the bottom of the ranking board (12th place out of 12 people). In contrast, in the many
likes condition, participants were endorsed with nine likes (approximately 82%), which placed
them in the 2nd place out of 12 people. Meanwhile, the number of likes others received varied
within a range of 3 to 10 likes (mean= 6.4, median= 6), which remained identical across task
versions or likes manipulation conditions. Time schedules of likes distribution were randomly
sampled between 10,000ms and 180,000ms and consistently applied across unique trials to make
them more natural.
Suspicion Check. At the end of the study, participants were given an opportunity to leave
open-ended feedback about their task experience. A pair of trained research assistants coded
participants’ open-ended feedback to detect any suspicion about the manipulation (inter-coder
agreement ranged between 88% and 99%); 27 out of total 613 participants (4.4%) were coded as
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expressing suspicion about the task—e.g., asking whether other people were real—which is a
low rate. To produce a conservative intent-to-treat effect, we kept these participants in the final
sample for the primary analyses, but removing these participants' data produced the same
substantive conclusions (see Table S4 in the online supplement).
The social media task program, task stimuli, examples of adolescents’ profiles, and
syntax for data analyses are posted online (osf.io/skzx6/).
Measures
Post-Task Survey Questions. Feelings of rejection were measured with a single item: “I
felt rejected by others during the task” (1=Strongly disagree ~ 7=Strongly agree). Higher values
indicate more intense feelings of rejection following the social media interaction.
Negative affect was assessed with an average composite of three items: perceived stress,
sadness, and anxiety. A single item measured perceived stress: “The Get-To-Know-People task
was stressful” (1= Strongly disagree ~ 7= Strongly agree; linearly converted to a 5-point scale).
Supplementing this, participants also reported feelings of sadness and anxiety (1=Not at all ~ 5=
A great deal; inter-item correlation rs= .35 ~ .51, ps < .001).
Negative self-referent cognitions were measured with negative self-attributions, negative
state self-esteem, and coping appraisals: (1) negative self-attributions were assessed with a single
item, “Maybe I’m just not a likable person”; (2) negative state self-esteem was measured with
two items: e.g., “How good or bad about yourself did the Get-To-Know-People task make you
feel?”, “During the Get-To-Know-People task, I felt like a person of worth, at least on an equal
basis with others (reversed),” r = .48, p < .001. Responses were rated on a 5-point scale (1= Not
at all ~ 5= A great deal) and higher values correspond to more negative state self-concept; (3)
coping appraisal was assessed with three items: e.g., “I felt like I could not handle the stress that
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I experienced during the Get-To-Know-People task”. Responses were rated on a 7-point scale
(1= Strongly disagree ~ 7= Strongly agree; linearly converted to a 5-point scale) and higher
values indicated more negative coping appraisal (inter-item correlation rs= .30 ~ .36, ps < .001).
These three sub-concepts were aggregated by computing an unweighted average composite score
of negative self-referent cognitions. See the online supplement Table S3 for item-level
correlations.
Results
Main Effects of Number of Social Media Likes
Adolescents reported significantly greater feelings of rejection when they were randomly
assigned to receive few likes, relative to when they received many likes, Mfew likes= 3.51, SDfew likes=
1.86; Mmany likes= 2.05, SDmany likes= 1.34, t(596) = 8.97, p < .001, Cohen’s d = .84. See Figure 2.
Thus, insufficient social validation caused an increase in feelings of rejection relative to
sufficient social validation, even though no participants in our study received negative feedback
(i.e., no bullying or harassment).
Analyses next examined whether these feelings of rejection might translate into risk
factors for the development of depression: negative affect and negative self-referent cognitions.
Preliminary analyses indicated that, as expected by the cognitive model of depression (Hankin &
Abramson, 2001), feelings of rejection were correlated with negative affect, r= .52, p < .001, and
negative self-referent cognitions, r= .62, p < .001.
Receiving few likes, relative to many likes, led to significantly more intense negative
affect (feeling stressed, sad, and anxious, α = .66), Mfew likes= 1.94, SDfew likes= 0.97; Mmany likes= 1.61,
SDmany likes= 0.69, t(604)= 3.94, p < .001, d= .37, and negative self-referent cognitions (wondering
whether they were not likable, reporting lower state self-esteem, and thinking they could not
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handle the demands, α = .66), Mfew likes= 2.13, SDfew likes= 0.81; Mmany likes= 1.69, SDmany likes= 0.65,
t(599) = 6.08, p < .001, d = .57, both of which are risk factors for depression (Figure 2 and Table
S4 in the online supplement report the results for individual items).
Gender and Race/Ethnicity Moderation
Analyses did not find moderation by gender. As in past research (Hankin & Abramson,
2001; Nesi & Prinstein, 2015), girls exhibited more negative internalizing responses overall:
Feelings of rejection (Mboys= 2.83, SDboys= 1.78; Mgirls= 3.37, SDgirls= 1.89, t(589)= 3.47, p < .
001), negative affect (Mboys= 1.70, SDboys= 0.91; Mgirls= 1.97, SDgirls= 0.91, t(596)= 3.51, p < .
001), and negative self-referent cognitions (Mboys= 1.92, SDboys= 0.83; Mgirls= 2.09, SDgirls= 0.76,
t(592)= 2.34, p = .02). However, girls and boys were not differentially impacted by the
manipulation (that is, few likes), interaction ps > .20. See online supplement Table S5.
In addition, we explored whether racial/ethnic minority status moderated how adolescents
responded to insufficient positive feedback on the social media task. We did not expect it would
because our experimental task randomly displayed a diverse group of adolescent profiles with
varying skin tones and physical appearances to rule out racial ingroup vs. outgroup exclusion
effects. Consistent with our expectation, we did not find significant moderation effects by
adolescents’ racial/ethnic minority status (such as, being identified as non-White/other racial or
ethnic groups), interaction ps > .15. See online supplement Table S6.
These absent moderation effects by gender and race/ethnicity suggest that insufficient
positive validation on social media can be impactful, almost regardless of adolescents’
demographic backgrounds.
Study 2
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Study 2 tested whether adolescents who experienced more intense feelings of rejection
when receiving insufficient social validation on social media (i.e., in the few likes condition) also
coped poorly with real-world, day-to-day social stressors and showed a greater increase in
depressive symptoms over time. To answer these questions, a sub-sample of participants from
Study 1 was tracked during a 10-day daily diary and at an 8-month longitudinal assessment.
Methods
Participants
A total of N=174 (98.3%) students from two schools in Study 1 consented to participate
in a more intensive longitudinal study involving up to 10-days of daily diaries. The subsample of
Study 2 participants did not differ from Study 1 participants in terms of demographics and
baseline depressive symptoms. Of those who participated in daily diary surveys and completed
the social media task, N=145 had been randomly assigned to few likes condition (insufficient
social validation) during the social media task, and thus constituted the primary Study 2 analytic
sample. See Table 1 and Table S7 for demographic characteristics. None of the other schools
who provided data for Study 1 participated in this longitudinal study; thus, Study 2 reports all
data available to test the present hypotheses.
Procedure and Measures
Daily Diary Surveys. Before the social media task administration, participants
completed a daily survey over ten days during afternoon classes (between 1 p.m. to 4:30 p.m.).
Students used computers or smartphones to respond. Students reported on events that occurred
within the last 24 hours, and on their reactions to the events. Participants took approximately 5-
10 minutes each day to complete the questionnaire. The completion rate for the daily surveys
was satisfactory (80% ~ 100% across days, see Table S8).
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Participants were asked to report up to two daily negative events in open-ended prompts
that read: e.g., “Please write about one negative thing that happened today or that you thought a
lot about today. Just write enough so we can understand what it was (5-10 words).” Participants
then rated the perceived intensity of negativity using a 5-point scale (1= Not at all negative ~ 5=
Extremely negative). In parallel with Study 1, participants’ daily negative affect and cognitions in
response to daily stressors were assessed. Daily negative affect was assessed with a composite of
daily stress, sadness, and anxiety. Level-1 inter-item correlations were rs= .30 ~ .40, ps < .001.
Daily negative cognitions were measured with a composite of two sub-concepts: (1) daily
maladaptive coping appraisal, saying they can’t handle the demand from the negative events; and
(2) daily ruminative thinking, saying they can’t stop thinking about the negative events happened
today (1= Strongly disagree ~ 7= Strongly agree). Level-1 inter-item correlations were rs= .54 ~ .
73, ps < .001. See Table S9 in the online supplement.
Depressive Symptoms at 8-Month Follow-up. We administered the Children’s
Depression Inventory (CDI), full version (Kovacs, 1992) to track longitudinal changes in
depressive symptoms over 8 months. The CDI scale was administered at the beginning of ninth-
grade school year (approximately two to three weeks before social media task administration);
and once again at the end of ninth-grade school year. One item related to suicidal ideation was
removed from the questionnaire resulting in a total of 26 items for the full inventory. Each item
asked participants to report which of three levels of a symptom described their feelings best in
the past two weeks (e.g., 2= “I am sad all the time,” 1= “I am sad many times,” 0= “I am sad
once in a while”). Average scores (ranging between 0 and 2) were computed and then weighted
with a total number of items to create a sum composite score (ranging between 0 and 52) at
baseline (α = .88) and 8-month follow-up (α = .89) respectively. To measure 8-month increases
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in depressive symptoms, baseline CDI sum score was subtracted from the 8-month CDI sum
score, so that a higher positive number indicates greater prospective increases in depressive
symptoms over an 8-month period (M = -1.02, SD = 5.53, range = -28.2 ~ 16).
Results
Daily Diary Analytic Approach
Daily diary analyses were conducted in R using lme4 (Bates, Mächler, Bolker, & Walker,
2015) and lmerTest packages (Kuznetsova, Brockhoff, & Christensen, 2015). Daily survey
responses (level 1) were nested within students (level 2). Multilevel analyses examined whether
adolescents who felt more rejected by insufficient social validation (on the Study 1 social media
task) also exhibited a stronger association between daily social stressors and negative affect or
cognition. We assumed that adolescents who felt worse and thought more poorly of themselves
when socially stressful events happened could be characterized as coping poorly.
To classify the intensity of the daily social stressors (the Level-1 predictor), two
independent coders coded open-ended negative events (% agreement between coders mean
97.3%, min 90.2% ~ max 99.9% across event categories) and gave it a “1” if the event described
any social evaluative domain (see Yeager, Lee, & Jamieson, 2016 for the coding scheme). To
minimize measurement errors, we computed the average intensity of up to two daily negative
social events to index how intensely negative social stressors occurred each day. Those who did
not report any negative social events were re-coded with the lowest intensity (=1 out of 5-point
scale) to avoid listwise deletion. The intensity of daily social stressors (Level 1-predictor) was
person-mean centered to examine the within-person slopes. Random slope models were specified
as below. Daily negative affect and cognitions for day i of student j were predicted by the cross-
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level interaction of intensity of daily social stressors (Level-1) and feelings of rejection after
insufficient social validation (few likes) on the social media task (Level-2):
Level 1 (day level):
Intensity of Daily Social Stressors
(¿¿ ij)+eij
Yij (Daily Negative AffectCognitions )=β0j+β1j¿
Level 2 (person level):
β1j=γ10 +γ11(Social Media Feelings of Rejection j)+u1j
Where
eij N
(
0, σ2
)
and
u1jN
(
0, τ11
2
)
. Here, the focal test is the significance of
γ11
parameter. We predicted that adolescents who expressed greater rejection feelings after
insufficient social validation (few likes) on social media might exhibit more intense negative
affect and cognitions on days with intense social stressors.
Increased Negative Affective and Cognitive Reactivity in Response to Daily Stressors
As a preliminary matter, daily negative affect and negative cognitions repeatedly assessed
over ten days in naturalistic social settings were associated with concurrent depressive
symptoms, rs = .35 ~ .37, ps < .001, as expected.
Next, there was a Daily Stressor (Level-1) × Social Media Feelings of Rejection (Level-
2) cross-level interaction predicting daily negative affect, b= 0.08, SE=0.03, t(95)= 2.48, p= .015,
and daily negative cognitions, b= 0.12, SE=0.05, t(109)= 2.53, p= .013. See Figure 3 and Table
S10 in the online supplement. As predicted, adolescents with higher feelings of rejection in
response to insufficient social validation (few likes) exhibited a stronger association between the
intensity of daily social stressors and both daily negative affect and daily negative cognitions,
relative to those who reported lower feelings of rejection after insufficient validation.
We probed these cross-level interactions by estimating the within-person slopes for daily
stress among adolescents who reported high (+1 SD) and low (-1 SD) feelings of rejection after
19
insufficient social validation. Among adolescents with higher rejection feelings (+1 SD) after the
social media task, days with more negative social stressors were accompanied by greater
negative affect, b= 0.25, SE= 0.04, t(106)= 5.90, p < .001, and negative cognitions, b= 0.51, SE=
0.06, t(119)= 8.06, p < .001. Among adolescents with lower feelings of rejection (-1 SD) after the
social media task—those who seemed to cope better with insufficient social validation on social
media—the intensity of daily negative social stressors was associated with daily negative
affective and cognitive reactivity about half as much as those with higher rejection feelings after
the social media task: negative affect, b= 0.10, SE= 0.04, t(84)= 2.34, p= .021; negative
cognitions, b= 0.28, SE= 0.06, t(95)= 4.37, p < .001. See Figure 3 and Table S10. Supplementary
analyses with sub-constructs of daily negative affect (see Figure S1) and daily negative
cognitions (see Figure S2 in the online supplement) supported the same conclusions.
Increases in Depressive Symptoms at 8-Month Follow-Up
Two methods tested whether adolescents who experienced more acute feelings of
rejection after few likes on social media would also exhibit an increase in depressive symptoms
over time. First, ordinary linear regression models found that acute rejection feelings after
insufficient likes predicted 8-month increases in depressive symptoms, while controlling for
baseline depressive symptoms, b= 1.12, SE= 0.49, t(122)= 2.28, p= .025,
= 0.20 (see Table 2
Model I). Results did not change when controlling for gender (a known correlate of depression;
Hankin & Abramson, 2001), b= 1.00, SE= 0.47, t(121)= 2.33, p= .022,
= 0.20 (Table 2 Model
II). Second, a logistic regression found that acute rejection feelings after insufficient likes
significantly predicted a binary outcome of clinically significant depression at 8-month follow-
up (coded 1 if the 8-month CDI sum scores were above a standard cutoff score of 19 out of 52,
which is suitable for non-clinical samples; Timbremont, Braet, & Dreessen, 2004), b= 1.00, SE=
20
0.45, z= 2.21, p= .027, OR=2.72, 95% CI[1.19, 7.22] (see Table 2 Model III). When controlling
for gender, the effect of rejection feelings remained significant, b= 1.11, SE= 0.49, z= 2.29, p= .
022, OR=3.06, 95% CI[1.26, 8.85] (Table 2 Model IV).
Finally, feelings of rejection after receiving sufficient likes did not significantly predict
increases in depressive symptoms 8 months later, b= -1.57, SE= 1.85, t(21)= -0.85, p= .406,
=
-0.26; neither did it predict the likelihood of developing clinical depression, b= -0.96, SE= 0.87,
z= -1.11, p= .267, OR= 0.38, 95% CI[0.05, 1.74]. However, this exploratory analysis within
sufficient likes condition is limited due to small sample size (N=24).
Study 3
Is social media use only harmful for those who are already struggling with face-to-face
peer interactions, as some have suggested (Odgers, 2018)? To answer this, Study 3 randomly
assigned likes to adolescents and tested for differential effects among adolescents who had been
victimized in prior face-to-face peer interactions.
Our predictions were rooted in longstanding social-psychological models of attributional
ambiguity. Namely, we expected that in the causally ambiguous context of insufficiently positive
social media feedback, face-to-face peer experiences may provide a contextual framework
through which adolescents “go beyond the information given” (Bruner, 1957) to interpret
causally-ambiguous information as negative (for a related argument, see Crocker, Voelkl, Testa,
& Major, 1991; Mendes, Major, McCoy, & Blascovich, 2008; Thomaes, Sedikides, Reijntjes,
Brummelman, & Bushman, 2015). A secondary, though no less important, contribution of Study
3 was to replicate main effects of the manipulation observed in Study 1 in another large sample.
Methods
Participants
21
During the 2017-18 school year, a total N=735 ninth-grade students from four urban
public high schools were recruited to participate. Of this sample, N=127 students did not
complete the social media task and N=29 students did not answer post-task survey questionnaire
due to various circumstances (e.g., conflicts with class schedules, absences, or voluntary
withdrawal). The final sample included N=579 ninth-grade adolescents (Mage = 15.3, SDage =
0.40) who returned an active parental and student consent forms during recruitment visits,
completed a social media task with a random assignment of likes feedback condition, and
answered a questionnaire following the task. This sample size yielded >99% power to detect the
effect size for feelings of rejection in Study 1 (d= .84) at p < .05. The Study 3 sample included
49.7% females; 53.5% White/European American, 32.5% Hispanic/Latinx, 3.8% Black/African
American, 6.0% Asian/Asian American, 0.5% Pacific Islander, 0.2% Native American
Indians/Alaskan, and 3.5% were multi-racial or another race/ethnicity. See Table 1 and Table
S11.
Procedure
Data collection occurred during the spring semester of the 2017-18 school year.
Participants were invited to two study sessions (~ 30 minutes) in school computer labs. On the
first day, participants completed a comprehensive self-report survey that assessed face-to-face
peer victimization experience along with other demographic and psychosocial characteristics.
On the following day, participants were invited to a 2nd session in which they were
instructed to complete a “Get-To-Know-People” task. The task materials, visual and text stimuli,
and written instructions were identical to the materials used in Study 1. Again, participants were
randomly assigned to receive few likes (N=279) vs. many likes (N=300) feedback from other
players. Supplementary analyses indicated that the random assignment was successful, no pre-
22
existing group differences were detected (see Table S12). Prior to the task, participants were
verbally informed that they could skip any questions or withdraw from the study at any point
without penalty. Upon completion, students were compensated with a small gift (e.g., a college
wristband under $2 value). Students were verbally de-briefed about the purpose and nature of the
computerized task. They were told that it did not involve actual likes given by real people, but
instead the feedback was simulated by computer scripts for scientific research purposes.
Measures
Prior Peer Victimization. We administered six items from the overt and relational
victimization scale (Prinstein, Boergers, & Vernberg, 2001). Participants were asked: In your
school, in the past two weeks, how often did the following things happen to you? Using a 5-point
scale (1=Never, 2=Once or twice, 3=A few times, 4=About once a week; 5=A few times a week),
participants rated how frequently they were (1) hit/ kicked/ pushed by another student in a mean
way; (2) threatened to be hurt/ beaten up; (3) left out from an activity or a conversation; (4) not
invited to a party or a social event; (5) not sit near at lunch or in class; and (6) got rumors or lies
spread out to hurt my reputation. For moderation analyses, we used a composite score averaging
all six items (α= .74; M= 1.30, SD= 0.45, Min 1 ~ Max 3.83, 53% adolescents with non-zero
experience of face-to-face peer victimization in the past two weeks), in which a higher score
indicates more frequent exposures to peer victimization.
Social Media Pre-Task Expectation. Prior to task administration, students reported their
pre-existing expectation of receiving positive feedback: “I expect that everyone will like me after
reading my profile” (1= Strongly disagree ~ 7= Strongly agree; M= 3.69; SD= 1.44).
Social Media Post-Task Responses. We administered a post-task questionnaire that was
similar to Study 1 at the completion of the social media task interaction. A single item (“I felt
23
rejected by others during the Get-To-Know-People task”) measured feelings of rejection (1=
Strongly disagree ~ 7= Strongly agree). Negative affect was assessed with a composite score of
four items: feeling stressful, sad, anxious, and embarrassed (1=Not at all ~ 5= A great deal), α = .
74; rs = .37 ~ .54, ps < .001. Negative self-referent cognitions were measured with two sub-
constructs: (1) negative state self-esteem (Thomaes et al., 2010), with three items (e.g., I feel
satisfied with/ I feel good about/ I am proud of myself right now; 1=Not at all ~ 5= A great deal;
reverse-coded), α = .97; rs = .85 ~ .95, ps < .001; and (2) characterological trait attributions
(adapted from Schacter, White, Chang, & Juvonen, 2015), two items (e.g., Maybe I’m not a
likable person; Kids like me are just not meant to be popular; 1= Strongly disagree ~ 7=
Strongly agree), α = .80; r = .66, p < .001. See Table S13 for item-level correlations.
Results
Replication of Main Effects of Social Media Likes
Consistent with Study 1, adolescents who were randomly assigned to receive few likes
during the social media task reported significantly greater feelings of rejection, Mfew likes= 3.79,
SDfew likes= 1.95; Mmany likes= 2.30, SDmany likes= 1.42; t(575)= 10.50, p < .001, d= .87; and higher
levels of negative affect (stressed, sad, anxious, and embarrassed), relative to those assigned to
receive many likes, Mfew likes= 1.84, SDfew likes= 0.85; Mmany likes= 1.51, SDmany likes= 0.63; t(575)= 5.23,
p < .001, d= .44. Those assigned to the few likes condition also reported significantly lower state
self-esteem (feeling less positively about the self after the interaction), Mfew likes= 3.15, SDfew likes=
1.30; Mmany likes= 3.50, SDmany likes= 1.15; t(575)= -3.44, p < .001, d= -.29; and more intense
characterological trait attributions, viewing themselves as not likable or not meant to be popular,
Mfew likes= 2.85, SDfew likes= 1.47; Mmany likes= 2.41, SDmany likes= 1.35; t(573)= 3.81, p < .001, d= .32.
See Figure 2, and also Table S14 in the online supplement for the results broken out by the
24
individual items. Taken together, Study 3 replicated the main effects from Study 1 with similar
effect sizes.
Moderation Analyses by Prior Peer Victimization
We observed a significant moderation effect on feelings of rejection. In a linear
regression, the Prior Peer Victimization Social Media Likes Condition interaction was
significant, b= 0.99, t= 3.07, p= .002,
= 0.45, with region of significance (ROS) [0.40 ~ 5.00] at
p < .05 level. Simple effects were estimated at 1 (no face-to-face peer victimization in the past
two weeks) vs. 3 (moderate-high levels of face-to-face peer victimization) of the victimization
composite scale value because -1SD from the sample mean (= 0.83) was a non-existent scale
value. Simple effects analyses revealed that adolescents with moderate to high levels of prior
peer victimization (centered at 3) reported significantly more intense rejection feelings when
receiving few likes, relative to many likes (simple effect of likes condition b= 3.22, p < .001).
Adolescents with no prior peer victimization experience in the past two weeks (centered at 1)
reported significant yet weaker differences in rejection feelings between few vs. many likes
condition (simple effect of likes condition b= 1.24, t= 7.12, p < .001). See Figure 4, first panel,
and Table S15 in the online supplement.
Next, a significant Face-to-Face Peer Victimization Social Media Likes Condition
interaction emerged for negative affect, b= 0.42, t= 2.89, p= .004,
= 0.19, ROS [0.92 ~ 5.00] at
p < .05 level. Simple effects tests showed that adolescents with moderate to high levels of face-
to-face peer victimization (at 3) reported significantly more intense negative affect when
receiving few likes, relative to many likes (simple effect of few likes condition at 3, b= 1.04, t=
4.07, p < .001; simple effect at 1, b= 0.20, t= 2.59, p= .01). See Figure 4, second panel, and Table
S15. And there was a significant Face-to-Face Peer Victimization Social Media Likes
25
Condition interaction on negative self-referent cognitions, b= 0.55, t= 2.92, p= .004,
= 0.25,
ROS [1.03 ~ 5.00] at p < .05 level. A simple effect analysis found a significant condition effect
among those with moderate to high levels of face-to-face peer victimization (b= 1.29, t= 3.85, p
< .001), but not among those with no face-to-face victimization (b= 0.18, t= 1.76, p= .08) (see
Figure 4, third panel, and Table S15).
We did not detect any significant moderation effects on any outcomes by adolescents’
pre-task expectation of getting positive feedback, ps > .20. This is important for clarifying the
moderating effect of victimization. It was not that victimized youth were expecting not to be
liked; it was that, when insufficiently liked, they were differentially harmed by the experience.
Discussion
As social media has penetrated adolescents’ social lives, researchers have called for more
theory-driven, ecologically valid, scientific studies of how social media affects adolescent
emotional well-being and social development (Crone & Konijn, 2018; George & Odgers, 2015;
Odgers, 2018; Spies Shapiro & Margolin, 2014). Here we tried to meet these calls in new ways.
First, we drew on the adolescent social-affective learning model (Yeager, Lee, & Dahl, 2017)
and the need-threat model (Williams, 2009) to generate predictions about the specific social
media interactions which could relate to internalizing disorders and why. Further, we tested
hypotheses about the subgroups of adolescents who might be most vulnerable.
Our studies found that insufficient validation on social media was a brief yet powerful
emotional event that threatened adolescents’ social status and elicited emotional distress. And
rejection feelings arising from insufficiently positive validation during a brief social media
interaction were correlated with ecologically-valid risk factors for depression in adolescence
(maladaptive day-to-day stress appraisals) and greater increases in depressive symptoms over 8
26
months. These findings are consistent with the adolescent social-affective learning model (Crone
& Dahl, 2012; Yeager et al., 2018, 2017) and the need-threat literature (Jamieson et al., 2010;
Sebastian et al., 2010; Wolf et al., 2015) in the sense that social media evaluative feedback that
publicly signals undesirable social status triggered negative internalizing-type affective responses
that are known risk factors for depression. And these findings are in line with previous research
showing that adolescents’ affective sensitivity to peer rejection events is associated with
prospective risk for depression (Masten et al., 2011; Nolan, Flynn, & Garber, 2003; Silk et al.,
2014; Slavich et al., 2010).
Importantly, the rejection feelings adolescents reported were elicited from insufficient
positive feedback, not explicit targeted rejecting feedback (e.g., dislike, exclusion,
cyberbullying). This distinction is important to consider in future work on the adolescent social-
affective learning model. It suggests that adolescents are highly attuned to symbolic social status
cues communicated through differing amounts of positive evaluative feedback on social media
and experience emotional distress when their momentary social status does not measure up to
others. Study 2 uncovered a potential mechanism through which positive social media evaluative
feedback could contribute to worse mental health outcomes during adolescence, which as
mentioned is a developmental period when affective sensitivity to social status rises (see Crone
& Dahl, 2012; Yeager et al., 2018).
Another contribution of our research was to confirm recent claims that some youth are
more vulnerable to the negative effects of social media than others (Odgers, 2018). Study 3
found that previously victimized adolescents reported stronger rejection feelings, more negative
internalizing-type affect, and greater characterological self-trait attributions (e.g., “maybe I am
not a likable person”) in response to receiving few likes from unacquainted others (Study 3).
27
These findings add to the prior literature on peer victimization by highlighting victimized youths’
cognitive vulnerabilities in using self-blaming attributions in response to causally ambiguous
social interaction contexts (Graham & Juvonen, 1998; Schacter et al., 2015). Moreover, we
extend prior research that victimized youths are more likely to be targeted for cyberbullying and
peer harassment in online contexts (Kowalski, Giumetti, Schroeder, & Lattanner, 2014), to also
examine emotional distress in responses to a simple lack of enthusiastic social validation in
online contexts.
These findings have some relevance for practice. In particular, they raise the intriguing
possibility that social media use may contribute to a negative evaluative feedback loop,
differentially for teens who had been victimized in the past, and future research can test this
directly. For example, victimized teens may turn to social media, posting self-disclosing content,
with the hope of receiving validation from peers to satisfy their unmet needs for status and
acceptance from peers. But their likes may not measure up to those garnered by others
(especially their well-accepted, popular peers), leading some to feel rejected and inadequate, and
also to develop more negative self theories (e.g., “I’m not a likable person”; “I’m not meant to be
a high status person”). Indeed, a U.S. national survey (Rideout & Fox, 2018) found that
adolescents with elevated depressive symptoms were nearly 30 percentage points more likely to
say they posted content on social media that hardly received any comments or likes, relative to
non-depressed counterparts (71% vs. 43%), suggesting vulnerable individuals’ impoverished
positive feedback in virtual social contexts. Ironically, this might cause these social-emotionally
vulnerable adolescents to turn to social media even more to avidly seek supportive social
feedback, causing the initial cycle to repeat and intensify (c.f., Rideout & Fox, 2018).
28
From a translational research perspective, our research underscores the need to develop
and test theoretically driven intervention programs that can better guide vulnerable youths to
positively appraise the meaning of online social feedback. To our knowledge, no evidence-based
interventions are currently available to address adolescents’ social and emotional struggles with
social media feedback. Nor are most programs tailored to educate adolescents in terms of how to
make sense of immense amounts of social status comparison cues on social media. Interventions
might bolster vulnerable adolescents’ psychological resilience to repeated, quantifiable
evaluative feedback online, or they might seek to reduce the pressure to demonstrate an
unattainable social status. The next stage of research, therefore, might look into factors that
buffer adolescents from the effects of social media use, and see how they can be embedded into
rigorously evaluated programs.
Last but not least, methodologically the social media task adapted here with diverse
adolescent profiles may prove useful as an experimental tool to investigate the developmental
impact of social media across diverse groups of youth. To facilitate future research, we publicly
post our experimental task stimuli and adolescent profiles database online (osf.io/skzx6/).
Limitations
There are several limitations to the current research. First, the effects of insufficient social
validation reported here could actually be conservative. The range of the number of few vs.
many likes feedback in our study was limited to 11 people. In real-world social media, quantified
feedback may go well beyond this number, given the average size of friends network on social
media (e.g., a median of 126 friends on Facebook, and 180 followers on Instagram; Rideout &
Fox, 2018). Future studies should continue to alter the sizes of the groups.
29
Next, our study induced a single occasion of insufficient social validation in order to
isolate its immediate causal effects and avoid potential ethical problems that could emerge from
a stronger manipulation. In the real-world, however, repeated exposures to insufficient social
validation could contribute to cycles of rejection distress and escalated internalizing symptoms.
Or, alternatively, those who felt insufficiently validated might rather withdraw from the social
media platforms over time or passively browse instead (though see Verduyn et al., 2015 for
detrimental effects of passive social media use). Future studies should further explore the
cumulative effects of insufficient social media validation and examine the alternative ways that
adolescents cope with it.
Conclusion
Social media provides unique challenges and new opportunities to adolescents, parents,
educators, clinicians, and engineers. By shining a light on how quantified social feedback can
pose a risk for vulnerable adolescents, we hope that our results inform stakeholders and inspire
improvements to platforms. For instance, it is encouraging that some social media applications
have begun to acknowledge the possible negative psychological consequences of quantified
evaluative feedback, and have modified (or considered doing so) platforms to not displaying
real-time, quantified social validation to mitigate users’ psychological pressures (Newcomb,
2019, May 1). We also hope that our results help inform contemporary efforts to reduce
adolescents' reliance on social media (e.g., screen time features on digital devices that allow
users to monitor their usage).
30
References
Appel, H., Crusius, J., & Gerlach, A. L. (2015). Social comparison, envy, and depression on
Facebook: A study looking at the effects of high comparison standards on depressed
individuals. Journal of Social and Clinical Psychology, 34, 277–289. doi:
10.1521/jscp.2015.34.4.277
Appel, H., Gerlach, A. L., & Crusius, J. (2016). The interplay between Facebook use, social
comparison, envy, and depression. Current Opinion in Psychology, 9, 44–49. doi:
10.1016/j.copsyc.2015.10.006
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models
using lme4. Journal of Statistical Software, 67, 1–48. doi: 10.18637/jss.v067.i01
Beyens, I., Frison, E., & Eggermont, S. (2016). “I don’t want to miss a thing”: Adolescents’ fear
of missing out and its relationship to adolescents’ social needs, Facebook use, and
Facebook related stress. Computers in Human Behavior, 64, 1–8. doi:
10.1016/j.chb.2016.05.083
Blease, C. R. (2015). Too many ‘friends,’ too few ‘likes’? Evolutionary psychology and
‘Facebook depression’. Review of General Psychology, 19, 1–13. doi:
10.1037/gpr0000030
Blomfield-Neira, C. J., & Barber, B. L. (2014). Social networking site use: Linked to
adolescents’ social self-concept, self-esteem, and depressed mood: SNS use and
adolescent indicators of adjustment. Australian Journal of Psychology, 66, 56–64. doi:
10.1111/ajpy.12034
Bronfenbrenner, U. (1977). Toward an experimental ecology of human development. American
Psychologist, 32, 513–531. doi: 10.1037/0003-066X.32.7.513
31
Bruner, J. S. (1957). On perceptual readiness. Psychological Review, 64, 123–152. doi:
http://dx.doi.org/10.1037/h0043805
Burrow, A. L., & Rainone, N. (2017). How many likes did I get?: Purpose moderates links
between positive social media feedback and self-esteem. Journal of Experimental Social
Psychology, 69, 232–236. doi: 10.1016/j.jesp.2016.09.005
Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress.
Journal of Health and Social Behavior, 24, 385–396. doi: 10.2307/2136404
Crocker, J., Voelkl, K., Testa, M., & Major, B. (1991). Social stigma: The affective consequences
of attributional ambiguity. Journal of Personality and Social Psychology, 60, 218–228.
doi: 10.1016/b978-0-08-088579-7.50019-3
Crone, E. A., & Dahl, R. E. (2012). Understanding adolescence as a period of social-affective
engagement and goal flexibility. Nature Reviews Neuroscience, 13, 636–650. doi:
10.1038/nrn3313
Crone, E. A., & Konijn, E. A. (2018). Media use and brain development during adolescence.
Nature Communications, 9, 1–10. doi: 10.1038/s41467-018-03126-x
Crosnoe, R. (2011). Fitting in, standing out: Navigating the social challenges of high school to
get an education. New York, NY: Cambridge University Press.
Dahl, R. E., Allen, N. B., Wilbrecht, L., & Suleiman, A. B. (2018). Importance of investing in
adolescence from a developmental science perspective. Nature, 554, 441–450. doi:
10.1038/nature25770
Davey, C. G., Allen, N. B., Harrison, B. J., Dwyer, D. B., & Yücel, M. (2009). Being liked
activates primary reward and midline self-related brain regions. Human Brain Mapping,
660–668. doi: 10.1002/hbm.20895
32
Eisenberger, N. I., Lieberman, M. D., & Williams, K. D. (2003). Does rejection hurt? An fMRI
study of social exclusion. Science, 302, 290–292. doi: 10.1126/science.1089134
Feinstein, B. A., Hershenberg, R., Bhatia, V., Latack, J. A., Meuwly, N., & Davila, J. (2013).
Negative social comparison on Facebook and depressive symptoms: Rumination as a
mechanism. Psychology of Popular Media Culture, 2, 161–170. doi: 10.1037/a0033111
Forest, A. L., & Wood, J. V. (2012). When social networking is not working: Individuals with
low self-esteem recognize but do not reap the benefits of self-disclosure on Facebook.
Psychological Science, 23, 295–302. doi: 10.1177/0956797611429709
George, M. J., & Odgers, C. L. (2015). Seven fears and the science of how mobile technologies
may be influencing adolescents in the digital age. Perspectives on Psychological Science,
10, 832–851. doi: 10.1177/1745691615596788
Graham, S., & Juvonen, J. (1998). Self-blame and peer victimization in middle school: An
attributional analysis. Developmental Psychology, 34, 587–599. doi:
https://doi.org/10.1037//0012-1649.34.3.587
Gunther Moor, B., van Leijenhorst, L., Rombouts, S. A. R. B., Crone, E. A., & Van der Molen,
M. W. (2010). Do you like me? Neural correlates of social evaluation and developmental
trajectories. Social Neuroscience, 5, 461–482.
Guyer, A. E., Caouette, J. D., Lee, C. C., & Ruiz, S. K. (2014). Will they like me? Adolescents’
emotional responses to peer evaluation. International Journal of Behavioral
Development, 38, 155–163. doi: 10.1177/0165025413515627
Hammen, C. (2005). Stress and depression. Annual Review of Clinical Psychology, 1, 293–319.
doi: 10.1146/annurev.clinpsy.1.102803.143938
33
Hankin, B. L., & Abramson, L. Y. (2001). Development of gender differences in depression: An
elaborated cognitive vulnerability–transactional stress theory. Psychological Bulletin,
127, 773–796. doi: 10.1037/0033-2909.127.6.773
Jamieson, J. P., Harkins, S. G., & Williams, K. D. (2010). Need threat can motivate performance
after ostracism. Personality and Social Psychology Bulletin, 36, 690–702. doi:
10.1177/0146167209358882
Kovacs, M. (1992). Children’s Depression Inventory: Manual. North Tonawanda, NY: Multi-
Health Systems.
Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., & Lattanner, M. R. (2014). Bullying in the
digital age: A critical review and meta-analysis of cyberbullying research among youth.
Psychological Bulletin, 140, 1073–1137. doi: 10.1037/a0035618
Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D. S., Lin, N., … Ybarra, O. (2013).
Facebook use predicts declines in subjective well-being in young adults. PLoS ONE, 8,
e69841. doi: 10.1371/journal.pone.0069841
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2015). lmerTest: Tests in linear mixed
effects models (Version 2.0-29). Retrieved from https://cran.r-
project.org/web/packages/lmerTest/index.html
Leary, M. R., Terdal, S. K., Tambor, E. S., & Downs, D. L. (1995). Self-esteem as an
interpersonal monitor: The sociometer hypothesis. Journal of Personality and Social
Psychology, 68, 518–530. doi: 10.1037//0022-3514.68.3.518
Lee, H. Y., & Yeager, D. S. (2019). Adolescents with an entity theory of personality are more
vigilant to social status and use relational aggression to maintain social status. Social
Development.
34
Lin, L. yi, Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J. B., … Primack, B. A.
(2016). Association between social media use and depression among U.S. young adults.
Depression and Anxiety, 33, 323–331. doi: 10.1002/da.22466
Masten, C. L., Eisenberger, N. I., Borofsky, L. A., McNealy, K., Pfeifer, J. H., & Dapretto, M.
(2011). Subgenual anterior cingulate responses to peer rejection: A marker of adolescents’
risk for depression. Development and Psychopathology, 23, 283–292. doi:
10.1017/S0954579410000799
Mendes, W. B., Major, B., McCoy, S., & Blascovich, J. (2008). How attributional ambiguity
shapes physiological and emotional responses to social rejection and acceptance. Journal
of Personality and Social Psychology, 94, 278–291. doi: 10.1037/0022-3514.94.2.278
Nesi, J., & Prinstein, M. J. (2015). Using social media for social comparison and feedback-
seeking: Gender and popularity moderate associations with depressive symptoms.
Journal of Abnormal Child Psychology, 43, 1427–1438. doi: 10.1007/s10802-015-0020-0
Nesi, J., & Prinstein, M. J. (2018). In search of likes: Longitudinal associations between
adolescents’ digital status seeking and health-risk behaviors. Journal of Clinical Child &
Adolescent Psychology, 1–9. doi: 10.1080/15374416.2018.1437733
Newcomb, A. (2019, May 1). Twitter and Instagram are starting to imagine a world without
‘likes’. Fortune. Retrieved from https://fortune.com/2019/05/01/twitter-instagram-
facebook-like-button
Nolan, S. A., Flynn, C., & Garber, J. (2003). Prospective relations between rejection and
depression in young adolescents. Journal of Personality and Social Psychology, 85, 745–
755. doi: 10.1037/0022-3514.85.4.745
35
Odgers, C. (2018). Smartphones are bad for some teens, not all. Nature, 554, 432–434. doi:
10.1038/d41586-018-02109-8
Prinstein, M. J., & Aikins, J. W. (2004). Cognitive moderators of the longitudinal association
between peer rejection and adolescent depressive symptoms. Journal of Abnormal Child
Psychology, 32, 147–158. doi: 10.1023/b:jacp.0000019767.55592.63
Prinstein, M. J., Boergers, J., & Vernberg, E. M. (2001). Overt and relational aggression in
adolescents: Social-psychological adjustment of aggressors and victims. Journal of
Clinical Child Psychology, 30, 479–491. doi: 10.1207/S15374424JCCP3004_05
Rideout, V., & Fox, S. (2018). Digital health practices, social media use, and mental well-being
among teens and young adults in the U.S. Hopelab, 1–95. Retrieved from:
http://learning.wellbeingtrust.org/be-well/digital-health-practices-social-media-use-and-
mental-well-being-among-teens-and-young-adults-in-the-u-s
Rosenberg, M. (1965). Society and the adolescent self-image. Princeton, NJ: Princeton
University Press.
Schacter, H. L., White, S. J., Chang, V. Y., & Juvonen, J. (2015). “Why me?”: Characterological
self-blame and continued victimization in the first year of middle school. Journal of
Clinical Child & Adolescent Psychology, 44, 446–455. doi:
10.1080/15374416.2013.865194
Schneider, F. M., Zwillich, B., Bindl, M. J., Hopp, F. R., Reich, S., & Vorderer, P. (2017). Social
media ostracism: The effects of being excluded online. Computers in Human Behavior,
73, 385–393. doi: 10.1016/j.chb.2017.03.052
36
Sebastian, C., Viding, E., Williams, K. D., & Blakemore, S.-J. (2010). Social brain development
and the affective consequences of ostracism in adolescence. Brain and Cognition, 72,
134–145. doi: 10.1016/j.bandc.2009.06.008
Shakya, H. B., & Christakis, N. A. (2017). Association of Facebook use with compromised well-
being: A longitudinal study. American Journal of Epidemiology, 185, 203–211. doi:
10.1093/aje/kww189
Silk, J. S., Siegle, G. J., Lee, K. H., Nelson, E. E., Stroud, L. R., & Dahl, R. E. (2014). Increased
neural response to peer rejection associated with adolescent depression and pubertal
development. Social Cognitive and Affective Neuroscience, 9, 1798–1807. doi:
10.1093/scan/nst175
Slavich, G. M., O’Donovan, A., Epel, E. S., & Kemeny, M. E. (2010). Black sheep get the blues:
A psychobiological model of social rejection and depression. Neuroscience &
Biobehavioral Reviews, 35, 39–45. doi: 10.1016/j.neubiorev.2010.01.003
Spies Shapiro, L. A., & Margolin, G. (2014). Growing up wired: Social networking sites and
adolescent psychosocial development. Clinical Child and Family Psychology Review, 17,
1–18. doi: 10.1007/s10567-013-0135-1
Steers, M.-L. N., Wickham, R. E., & Acitelli, L. K. (2014). Seeing everyone else’s highlight
reels: How Facebook usage is linked to depressive symptoms. Journal of Social and
Clinical Psychology, 33, 701–731. doi: 10.1521/jscp.2014.33.8.701
Thomaes, S., Reijntjes, A., Orobio de Castro, B., Bushman, B. J., Poorthuis, A., & Telch, M. J.
(2010). I like me if you like me: On the interpersonal modulation and regulation of
preadolescents’ state self-esteem. Child Development, 81, 811–825. doi: 10.1111/j.1467-
8624.2010.01435.x
37
Thomaes, S., Sedikides, C., Reijntjes, A., Brummelman, E., & Bushman, B. J. (2015). Emotional
contrast or compensation? How support reminders influence the pain of acute peer
disapproval in preadolescents. Developmental Psychology, 51, 1438–1449. doi:
10.1037/dev0000041
Timbremont, B., Braet, C., & Dreessen, L. (2004). Assessing depression in youth: Relation
between the Children’s Depression Inventory and a structured interview. Journal of
Clinical Child & Adolescent Psychology, 33, 149–157. doi:
10.1207/S15374424JCCP3301_14
Verduyn, P., Lee, D. S., Park, J., Shablack, H., Orvell, A., Bayer, J., … Kross, E. (2015). Passive
Facebook usage undermines affective well-being: Experimental and longitudinal
evidence. Journal of Experimental Psychology: General, 144, 480–488. doi:
10.1037/xge0000057
Vernon, L., Modecki, K. L., & Barber, B. L. (2017). Tracking effects of problematic social
networking on adolescent psychopathology: The mediating role of sleep disruptions.
Journal of Clinical Child & Adolescent Psychology, 46, 269–283. doi:
10.1080/15374416.2016.1188702
Williams, K. D. (2009). Ostracism: A temporal need‐threat model. In Advances in Experimental
Social Psychology (Vol. 41, pp. 275–314). Academic Press.
Williams, K. D., & Jarvis, B. (2006). Cyberball: A program for use in research on interpersonal
ostracism and acceptance. Behavior Research Methods, Instruments, and Computers, 38,
174–180. doi: 10.3758/BF03192765
38
Wolf, W., Levordashka, A., Ruff, J. R., Kraaijeveld, S., Lueckmann, J.-M., & Williams, K. D.
(2015). Ostracism Online: A social media ostracism paradigm. Behavior Research
Methods, 47, 361–373. doi: 10.3758/s13428-014-0475-x
Yeager, D. S., Dahl, R. E., & Dweck, C. S. (2018). Why interventions to influence adolescent
behavior often fail but could succeed. Perspectives on Psychological Science, 13, 101–
122. doi: 10.1177/1745691617722620
Yeager, D. S., Lee, H. Y., & Dahl, R. E. (2017). Competence and motivation during adolescence.
In A. J. Elliot, C. S. Dweck, & D. S. Yeager (Eds.), Handbook of competence and
motivation: Theory and application (Second, pp. 431–448).
Yeager, D. S., Lee, H. Y., & Jamieson, J. P. (2016). How to improve adolescent stress responses:
Insights from integrating implicit theories of personality and biopsychosocial models.
Psychological Science, 27, 1078–1091. doi: 10.1177/0956797616649604
39
Table 1. Characteristics of Adolescents Who Participated in Study 1, 2, and 3.
Study 1
(N=613)
Study 2
(N=145)
Study 3
(N=579)
School Site
a summer prep program,
a public magnet school,
three urban public high
school
a public magnet school,
an urban public
high school
four urban public
high school
Mean age (SD) 14.3 (0.70) 14.8 (0.55) 15.3 (0.40)
Sex
% Boys 45.0% 48.6% 50.3%
% Girls 55.0% 51.4% 49.7%
Race/Ethnicity
% White/European American 44.9% 57.6% 53.5%
% Hispanic/Latinx 31.8% 19.4% 32.5%
% Black/African American 3.5% 1.4% 3.8%
% Asian/Pacific Islander 12.3% 14.6% 6.5%
% Native American Indian 0.3% 0.0% 0.2%
% Multi-racial/Other 6.8% 6.9% 3.5%
Maternal Education
% No high school degree 15.4% 2.0% 5.6%
% High school degree 23.1% 14.3% 19.3%
% 2-year associate
degree 5.5% 5.1% 5.1%
% 4-year college
degree 25.5% 36.7% 32.7%
% Master’s degree or
above 20.9% 35.7% 23.4%
% Participant did not
know 9.5% 6.1% 14.0%
Internalizing Symptoms
CDI score (SD) 0.42 (0.32) 0.46 (0.30) 0.45 (0.32)
40
41
Table 2. Social media feelings of rejection predicted 8-month prospective increases in depressive symptoms and the likelihoods
of developing clinically significant depression, in Study 2.
Linear regression
(DV= 8-month increases in
depressive symptoms)
Logistic regression
(DV= 8-month clinical depression
binary outcome)
Model I Model II Model III Model IV
(Intercept) −1.190*
(0.461)
−2.851***
(0.668)
−3.793***
(0.736)
−4.807*
(1.170)
Social media feelings of rejection (z-scored) 1.123*
(0.494)
1.105*
(0.474)
1.001*
(0.453)
1.110*
(0.486)
Covariates:
Baseline CDI scores (z-scored) −2.331***
(0.482)
−2.511***
(0.467)
2.448***
(0.574)
2.594***
(0.635)
Female 2.977**
(0.896)
1.205**
(0.880)
R20.165 0.235
P< .001 < .001 < .001 < .001
N125 125 125 125
Note: Analysis included adolescents who completed baseline and 8-month CDI inventory. In Model I and II, 8-month increases in CDI scores were
computed by 8-month CDI sum scores minus baseline CDI sum scores. In Model III and IV, logistic regression models used a binary outcome of
clinically significant depression (8-month CDI sum scores above 19 out of 52). *** p < .001, ** p < .01, * p < .05.
Figure 1. An example of social media task stimuli, few likes condition.
Note: During the three-minute online interaction, participants were instructed to interact with eleven other people seemingly same-age peers, who were in
fact controlled by pre-programmed computer scripts. Participant’s profile was always displayed on the top left corner, whereas others’ profiles were
randomly displayed. When people received a like from another person, it updated the total number of likes below each profile, popped up a green
notification window at the bottom left corner of the screen, and changed the rank order on the ranking board at the right corner, all of which made the
experience of receiving likes highly salient.
42
Figure 2. Main effects of social media task social validation on adolescents’ feelings of rejection, negative affect, and negative self-
referent cognitions, in Study 1 and 3.
Note: In Study 1 (N=613), Few Likes condition (N=454) vs. Many Likes condition (N=159); In Study 3 (N=579), Few Likes condition (N=279) vs. Many
Likes condition (N=300); Black dots denote group means, black lines indicate standard errors of group means, and white lines indicate group median
levels. Differences in degrees of freedom across outcomes within a study are due to small differences in participant non-response for a given item.
43
Figure 3. Adolescents’ feelings of rejection after insufficient social validation on a social
media task predicted daily negative affective and cognitive reactivity, in Study 2.
Simple slope of intensity of daily social stressors b= 0.10, P= .021
Crosslevel interaction b= 0.08, P= .015
!"#$%&'()
321 0 1 2 3
1
2
3
4
5
6
7
$'!'
*)
!'
Simple slope of intensity of daily social stressors b= 0.25, P < .001
Crosslevel interaction b= 0.08, P= .015
+#,!"#$%& '()
3210123
1
2
3
4
5
6
7
$'!'
*)
!'
Simple slope of intensity of daily social stressors b= 0.28, P < .001
Crosslevel interaction b= 0.12, P= .013
!"#$%&'()
321 0 1 2 3
1
2
3
4
5
6
7
$'!'
*)
!'
Simple slope of intensity of daily social stressors b= 0.51, P < .001
Crosslevel interaction b= 0.12, P= .013
+#,!"#$%& '()
3210123
1
2
3
4
5
6
7
$'!'
*)
!'
Note: Level 1 (day level) N= 1,266, Level 2 (person level) N= 145, Gray lines represent person-specific
fitted random slopes from multilevel models in which daily negative affect (top row) and daily negative
cognitions (bottom row) are predicted by the intensity of daily social stressors (person-mean centered).
Red lines indicate the group average fixed-effect slopes, estimated at low (-1SD, left panel) vs. high
(+1SD, right panel) feelings of rejection after insufficient social validation (few likes) on the social media
task. b= unstandardized betas.
44
Figure 4. Adolescents’ prior peer victimization moderated feelings of rejection, negative affect, and negative self-referent cognitive
responses to insufficient social validation on a social media task, in Study 3.
***
b= 1.24
***
b= 3.22
**
b= 0.20
***
b= 1.04
+
b= 0.18
***
b= 1.29
Note: N= 503, moderation analyses excluded participants who did not complete the peer victimization scale prior to the social media task administration.
Interaction effects were tested in ordinary linear regression models with a full continuous moderator. We plotted simple slopes of prior face-to-face peer
victimization at Few Likes (solid light gray lines) vs. Many Likes (dashed dark gray lines) condition. Simple effects of likes condition were tested at “no
prior peer victimization” (at composite score= 1 of x-axis) vs. “moderate-high levels of prior peer victimization” (at composite score= 3 of x-axis). b=
unstandardized betas; *** p < .001, ** p < .01, * p < .05, + p < .10.
45
... Social media users perceive ostracism associated with the absence of PDAs from relationally close or socially superior network members (Hayes et al., 2018). Lee et al. (2020) found that receiving fewer likes than peers elicits negative affect and negative thoughts in adolescents. Therefore, extant research literature suggests that social media users experience positive sentiments after receiving PDAs, and negative sentiments when they do not receive PDAs. ...
... Our findings suggest that the value of PDAs is potent enough for some people to motivate them to engage in risky behaviors. This is not surprising in light of experimental research manipulating the number of likes adolescents received on social media (Lee et al., 2020). Those who were given few likes exhibited significantly greater depression than those receiving many likes (Lee et al., 2020). ...
... This is not surprising in light of experimental research manipulating the number of likes adolescents received on social media (Lee et al., 2020). Those who were given few likes exhibited significantly greater depression than those receiving many likes (Lee et al., 2020). The negative psychological consequences of not receiving likes appears to be associated with a motivation to obtain PDAs. ...
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Paralinguistic digital affordances (PDAs; e.g., likes) are sought out by social media users and serve an important function of enhancing social reputation in online contexts. Nonetheless, there has been no standardized measure for evaluating gratification from receiving PDAs. This study provides a brief, validated self-report questionnaire on PDA gratification. The results of factor analysis verified the three-factor structure (i.e., emotional, status, and social gratifications) of the questionnaire. Internal consistency was established using inter-item correlation, corrected item-total correlation, and Cronbach’s alpha. Gratification from receiving PDAs was positively associated with risky behaviors used to enhance fame, tendency to use social media’s black market, and problematic Internet use. The findings provide preliminary evidence that gratification from receiving PDAs may increase the likelihood of maladaptive fame-seeking behaviors in social media users. The Gratification From Receiving PDAs Questionnaire appears to be a promising measure that may offer new insights into the motivations involved in social media use.
... Recent literature [57,61] has also shown gender differences in online self-presentation: female adolescents were likely to modify their online selfpresentation by editing their photos, which led to lower selfacceptance, including reduced body and life satisfaction [10,62]. Indeed, SNSs make online social status comparisons easier, with negative emotional consequences [63], regardless of explicit negative comments [64]. For example, adolescent girls undergoing treatment for obesity «undertook self-presentation strategies to conceal weight-related content such as avoiding showing close-up photos of their bodies and not posting images of unhealthy 'fattening' foods» [61]. ...
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