Fear of missing out (FOMO): overview, theoretical
underpinnings, and literature review on relations
with severity of negative affectivity and problematic
Jon D. Elhai,
Academy of Psychology and Behavior, Tianjin Normal University, Tianjin, China.
Department of Psychology, University of Toledo, Toledo,
Department of Psychiatry, University of Toledo, Toledo, Ohio, USA.
Department of Molecular Psychology, Institute of Psychology
and Education, Ulm University, Ulm, Germany.
This article discusses the fear of missing out (FOMO) on rewarding experiences, an important
psychological construct in contemporary times. We present an overview of the FOMO construct and
its operational deﬁnition and measurement. Then, we review recent empirical research on FOMO’s
relationship with levels of online social engagement, problematic technology and internet commu-
nication use, negative affectivity, and sociodemographic variables. Additionally, we discuss theoretical
conceptualizations regarding possible causes of FOMO and how FOMO may drive problematic
internet technology use. Finally, we discuss future directions for the empirical study of FOMO.
Keywords: Addictive behavior; anxiety; social anxiety; depression; smartphone
The fear of missing out (FOMO) on rewarding experiences
has received increasing empirical study in recent years.
Central to FOMO is the perceived need to persistently stay
connected with one’s social network, resulting in frequent
(and for some people, excessive) use of social networking
sites (SNS) and messaging services.
The enhanced sci-
entiﬁc focus on FOMO coincides with growing societal
debate about whether too much digital ‘‘screen time’’ is
harmful to children and adults.
However, the empirical
literature on FOMO has not yet been synthesized into a
review paper. Our focus in this paper is to deﬁne and dis-
cuss the FOMO construct and its theoretical underpin-
nings, as well as review the recent empirical literature on
relationships between FOMO and levels of online social
engagement, problematic internet use (PIU), negative affec-
tivity, and sociodemographic characteristics.
Background, deﬁnition, and measurement of
FOMO was ﬁrst introduced in media outlets in the early
At that time, SNS use had grown exponentially
around the world.
With the dissemination of means to
check SNS, especially the increasing ubiquity of smart-
phones, it has become easy to learn about potentially
rewarding experiences (online and ofﬂine) that one may
be missing. Incidentally, from early on FOMO was char-
acterized as an anxiety-provoking construct in popular
FOMO has been deﬁned in scientiﬁc literature as
involving two speciﬁc primary components: a) apprehen-
sion that others are having rewarding experiences from
which one is absent, and b) the persistent desire to stay
connected with people in one’s social network.
component maps onto the cognitive aspect of anxiety
(e.g., worry, rumination, etc.). The latter component involves
a behavioral strategy aimed at relieving such anxiety –
analogous to how compulsions aim (though maladapti-
vely) to relieve anxiety in obsessive compulsive disorder.
Currently, this behavioral component of FOMO most often
involves frequent checking of SNS and messaging ser-
vices to maintain social connections and avoid missing
out on rewarding experiences.
The persistent online checking behavior inherent in
FOMO is not only active, i.e. when people have time to
proactively browse their internet-enabled devices such as
smartphones, but is also frequently reactive (or perhaps
passive) through the many social-related notiﬁcations
received over the course of the day – to which there is a
compulsion to respond. On one hand, social-related noti-
ﬁcations are helpful for one’s social life and are rated
because they satisfy and alleviate FOMO.
Correspondence: Haibo Yang, Academy of Psychology and Behavior,
Tianjin Normal University, No. 57-1 Wujiayao Street, Hexi District,
Tianjin, 300074, China.
Submitted Jan 23 2020, accepted Mar 07 2020.
How to cite this article: Elhai JD, Yang H, Montag C. Fear of
missing out (FOMO): overview, theoretical underpinnings, and
literature review on relations with severity of negative affectivity
and problematic technology use. Braz J Psychiatry. 2020;00:000-
Braz J Psychiatry. 2020 xxx-xxx;00(00):000-000
Brazilian Psychiatric Association
Online social interaction can also enhance social capital
for many people.
On the other hand, interruptive smart-
phone and computer notiﬁcations (and associated check-
ing behavior) are known to have adverse effects. Such
notiﬁcations can result in a distracted and less focused
daily experience, impairing attention
and other daily life activities
‘‘switching costs,’’ which make it difﬁcult to return to and
complete the task at hand.
Thus, FOMO can drive exces-
sive checking for and responding to SNS notiﬁcations,
making it difﬁcult to remain productive in daily life.
context, we also mention growing discussion on the need
to regulate the number of elements built in to social media
apps that elicit FOMO
in an attempt to prolong usage
time to harvest more personal data in the age of sur-
Several self-report scales have been developed to meas-
ure FOMO, of which the most widely used is the 10-item
Likert-type FOMO Scale developed by Przybylski et al.
This scale includes items such as ‘‘I fear others have more
rewarding experiences than me,’’ and ‘‘When I miss out
on a planned get-together it bothers me.’’ Another similar
scale is Alt’s FOMO Scale, with 17-item
versions. A third scale added items to the Przybylski
FOMO Scale by incorporating state-based FOMO content
to distinguish it from trait-based FOMO.
used the two FOMO Scale items described above as
examples of trait-based FOMO, and added state-based
FOMO items such as ‘‘I am continuously online in order to
not miss out on anything’’ and ‘‘I fear not to be up-to-date
in my social networking sites.’’ Additionally, some research
has used behavioral measures to examine FOMO by
assessing the physiological distress (e.g., heart rate and
blood pressure) of being separated from a smartphone and
Several studies have explored the latent dimensions
of FOMO by using exploratory and/or conﬁrmatory factor
analysis to better understand this construct. Some work
has tested and found support for a single latent dimen-
Wegmann et al.
added the previously des-
cribed state-based content to the Przybylski et al.
FOMO Scale and reﬁned it through exploratory factor
analysis with a sample of German participants. They then
validated the expanded scale with conﬁrmatory factor
analysis in a separate German sample, revealing a two-
dimensional model involving trait- and state-based FOMO
Another study revealed two FOMO factors
involving missing out on the experiences of others, and
the use of rumination strategies for controlling one’s social
Finally, other research has discovered
three FOMO factors in social, news, and commercial
FOMO appears to be a universal phenomenon, having
been investigated and supported as a valid construct in
numerous countries and languages. For example, FOMO
has been studied in samples from Israel,
the United Kingdom,
and various regions within the United
One paper compared the FOMO scores
of German and Spanish samples, ﬁnding that Germans
scored signiﬁcantly higher on trait-based FOMO, with a
small effect (Z
FOMO’s relationships with relevant variables
We now review recent empirical research on bivariate rela-
tionships between FOMO and relevant variables, including
PIU, psychopathology and sociodemographic character-
istics. Ours is not a comprehensive systematic review,
since we focused on ﬁndings from the past couple of years.
Speciﬁcally, when reviewing FOMO’s relations with rele-
vant constructs, we only included studies published since
2018. Nevertheless, we also reviewed earlier studies when
discussing FOMO’s relations with sociodemographic vari-
ables, since few papers have reported such ﬁndings.
We organized the discussed references in an Endnote
Frequency and problematic use of internet
First, we will discuss research investigating FOMO in
relation to greater frequency of, but not necessarily mala-
daptive, SNS use. The majority of these studies investi-
gated only Facebook use or overall SNS use, employing
self-report methodology with a correlational, cross-
sectional survey design. Moderate to large relationships
have been discovered in several such studies involving
samples of children and youth, college students, and
For example, Dempsey et al.
data from 289 American college students using a cross-
sectional web survey design with standardized, self-report
scales. The authors reported a bivariate Pearson correla-
tion of -0.19 between the Przybylski et al.
Scale and a ﬁve-item Facebook use frequency scale
(computed such that lower scores indicate greater Face-
We should provide a caveat at this juncture about healthy
vs. maladaptive internet technology (including SNS) use.
A higher level of social networking is not necessarily
maladaptive, but it can be if it becomes excessive or
‘‘problematic.’’ In fact, PIU is deﬁned as when overuse
results in adverse effects.
Such adverse effects are
typically categorized as those observed in addictive dis-
orders involving drug and alcohol use, including with-
drawal when denied access, tolerance (requiring increas-
ing periods of use to feel the same level of emotional
relief), and functional impairment such as work or social
problems, hazardous use, etc.
For recent discussion
on this topic and a taxonomy of internet-related use
disorders, including SNS use disorder or problematic SNS
use, see work by Montag et al.
We should also point out
that only problematic use of internet gaming is currently
an ofﬁcial medical/mental health diagnosis
; for pre-
liminary empirical ﬁndings, see recent work.
Nonetheless, problematic use of other forms of internet
technology, such as smartphones and SNS, are important
because of the adverse health and functional conse-
quences that can result from overuse.
smartphone itself is only a vehicle for accessing social
Braz J Psychiatry. 2020;00(00)
2JD Elhai et al.
media apps etc., the construct of problematic smartphone
use (PSU) (alternatively, smartphone addiction or smart-
phone use disorder) is frequently debated.
reviews of PIU have included smartphone
including relations between problematic use and
psychological (including psychopathological) constructs.
The relationships between unspeciﬁed PIU and PSU have
also been investigated, showing overlap (correlations) of
around 0.50 in recent research.
scales in the aforementioned reviews have frequently
used diagnostic criteria for drug and alcohol use that have
been modiﬁed to assess use of a speciﬁc technology
FOMO has been empirically studied in relation to
problematic SNS use in numerous studies. These studies
have almost exclusively used self-report methodology
with a correlational, cross-sectional survey design. Mode-
rate to large positive associations between FOMO and
levels of problematic SNS use have been found in several
studies of school-aged adolescents, college students,
Dempsey et al.
a bivariate Pearson correlation of 0.32 between the
Przybylski et al.
FOMO Scale and the six-item Bergen
Facebook Addiction Scale.
Thus, FOMO has been
linked not only to greater frequency of SNS use, but also
to higher levels of problematic SNS use.
Many studies have also examined FOMO in relation to
levels of problematic smartphone use. These investiga-
tions have exclusively used self-report methods and a
correlational, cross-sectional research design. Numerous
studies with samples from all age groups have found
moderate to large positive associations between FOMO
and problematic smartphone use.
For example, Elhai, Yang, Fang et al.
from 1,034 Chinese university students, using a cross-
sectional, online self-report survey design with standard-
ized psychological scales. They reported a bivariate
Pearson correlation of 0.29 between the Chinese versions
of the Przybylski et al.
FOMO Scale and the 10-item
Smartphone Addiction Scale.
FOMO and other adverse effects from smartphones have
also been investigated. FOMO has been positively
correlated with disrupted daily life activities due to smart-
as well as to distracted pedestrian
behavior due to smartphone use.
Negative affectivity and demographics
FOMO has been conceptualized as a construct that
primarily involves anxiety-related psychopathology,
anxiety disorders are conceptualized as an important
aspect of underlying negative affectivity.
FOMO has been examined in relation to anxiety symptom
severity, including social anxiety, in studies with adoles-
cent and adult samples that used correlational, cross-
sectional designs. Across studies, FOMO has revealed
moderate to large positive relationships with anxiety
For instance, in the
previously mentioned study by Elhai, Yang, Fang et al.,
a bivariate Pearson correlation of 0.33 was reported
between the Przybylski et al.
FOMO Scale and the
seven-item anxiety subscale of the Depression Anxiety
Anxiety highly correlates (and is comorbid) with dep-
which is also a fundamental aspect of
underlying negative affectivity.
FOMO has also been
examined in relation to depression severity from adoles-
cence through adulthood using correlational, cross-sec-
tional methodology. Speciﬁcally, mild to moderate positive
associations have been found between FOMO and dep-
ression symptom severity.
Yang, Fang et al.
reported a bivariate Pearson correla-
tion of 0.29 between the Przybylski et al.
and seven-item depression subscale of the Depression
Anxiety Stress Scale-21.
Other indices of negative affectivity have been sup-
ported in connection with FOMO through correlational,
cross-sectional methodology. Moderate to large positive
associations have been found for FOMO with rumina-
as well as for FOMO with negative affect and
Additionally, a moderate positive correlation
has been found between FOMO and proneness to expe-
; in fact, boredom proneness is
conceptualized as a negative affectivity construct that
additionally involves impaired attention.
FOMO has also been investigated for relations with
variables involving the opposite of negative affectivity –
namely, perceived quality of life. These studies have used
cross-sectional methods similar to those of most of the
previously mentioned studies. Speciﬁcally, FOMO has
shown mild to moderate inverse correlations with life
Furthermore, mild to moderate inverse
associations have been found between FOMO and
Finally, FOMO has been associated with particular
demographic characteristics in a small number of studies
with correlational, cross-sectional designs. FOMO has
been correlated with younger age in some studies,
and others have found it to be more related to females
One study of North Americans found
that FOMO was more related to Caucasians than racial
Theoretical underpinnings of FOMO
FOMO was ﬁrst conceptualized using self-determination
theory (SDT), which was developed by Ryan & Deci
applied by Przybylski et al. to understanding what drives
SDT attempts to explain how personality is
formed and the psychological needs that drive persona-
lity formation. SDT proposes that intrinsic (rather than
extrinsic) motivation for reward is essential in promoting
mental health, and that intrinsic motivation is best
promoted when one feels socially connected to others.
Therefore, in SDT, social relatedness can drive intrinsic
motivation, which in turn can encourage positive mental
Przybylski et al. applied SDT to FOMO, pro-
posing that FOMO is a negative emotional state resulting
from unmet social relatedness needs.
zation that FOMO involves negative affect from unmet
social needs is similar to theories about the negative
emotional effects of social ostracism.
Braz J Psychiatry. 2020;00(00)
FOMO review 3
In this context, research involving personality psychol-
ogy should also be mentioned. FOMO has been linked to
the personality trait of neuroticism,
one of the most
well-known risk factors for developing a mood disorder.
Furthermore, narcissism likely plays a role in FOMO.
Vulnerable narcissists in particular have unmet social
relatedness needs (similar to those with severe FOMO)
and more often engage in problematic SNS use.
fore, FOMO may have a mediational role between narcis-
sism and problematic SNS use.
Subsequent investigations have assessed whether
FOMO inﬂuences negative affectivity, such as depression
and anxiety, or whether negative affectivity inﬂuences
FOMO. For instance, several papers have conceptualized
FOMO as a driving factor for negative affectivity.
However, other papers have conceptualized negative
affectivity as an antecedent of FOMO.
It is not yet
clear whether FOMO causes negative affectivity, whether
negative affectivity causes FOMO, or whether there is
a bidirectional effect. Repeated measures, longitudi-
nal designs, and experiments may eventually provide
answers to this question. Studies with repeated measures
designs have found some initial support that FOMO
drives negative affect over short (1-week) periods of
FOMO is also widely considered a driving mechanism
for PIU, as discussed above. As such, FOMO has been
theorized for its role in PIU. The Interaction of Person-
Affect-Cognition-Execution (I-PACE) model of PIU con-
ceptualizes risk factors for PIU, both in early
stages of excessive technology use.
that background personal variables, such as psycho-
pathology, personality, and biology (including genetics),
can inﬂuence problematic use. I-PACE additionally sug-
gests that responses to background variables also play a
role in PIU as mediating mechanisms between back-
ground variables and problematic use. Such response
variables include coping strategies, cognitive bias, ability
to inhibit impulsive behavior, craving and expectations
about internet use.
FOMO has been conceptualized as an internet-related
maladaptive cognitive bias within the I-PACE model’s
Elhai et al. suggested that
because depression and anxiety involve social isolation,
FOMO can be a natural consequence, in turn driving
In fact, consistent with I-PACE, several papers
have found FOMO to mediate relations between psycho-
pathological symptoms (i.e., depression and anxiety)
and PIU levels.
Thus, FOMO may be a
mechanism that explains how some depressed/anxious
people develop PIU.
Conclusions and future directions
FOMO is an important psychological construct in the
digital age. FOMO has been examined and validated
globally with several self-report psychological scales, as
well as with physiological monitoring. Support has been
established for FOMO in relation to greater frequency of
SNS use, higher levels of problematic SNS and smart-
phone use, more severe anxiety, depression and negative
affectivity, and lower levels of perceived quality of life.
Preliminary evidence indicates that FOMO is more related
to younger age and female sex.
Future research could explore unanswered questions
regarding the FOMO construct. Nearly all work assessing
the relations between FOMO and high or problematic
levels of technology use has involved self-reported beha-
vior as the dependent variable. However, self-reported
rates of internet use differ from objective measures of use
(e.g. device logs).
In particular, digital phenotyping
could help the psychological sciences overcome some of
the problems arising from self-report methods, such as
problems self-assessing a construct such as FOMO and
the tendency to answer questions in socially desirable
We are aware of only one FOMO study that
has objectively measured internet technology use (smart-
phone), ﬁnding that FOMO was related to higher level of
More work in this area is needed. Furthermore,
the vast majority of research on FOMO has used cross-
sectional research methodology. We encourage resear-
chers to use repeated measures, longitudinal, daily diary
and/or experience sampling designs to further assess
FOMO. Such designs can attempt to answer whether
FOMO drives negative affectivity or vice-versa, which has
been done thus far in only two papers,
FOMO drives problematic smartphone/SNS use or vice-
versa, which is as yet unexplored.
Additionally, the research on FOMO has been exclu-
sively variable-centered. No studies have used person-
centered analyses to examine possible heterogeneity
in the experiences/symptoms of FOMO across indivi-
duals with mixture modeling such as cluster, latent
class, or latent proﬁle analysis. Furthermore, FOMO and
other negative affectivity variables are all correlated with
PIU and with each other. Therefore, statistical methods,
such as machine learning algorithms that can address
collinearity and relative variable importance and can
shrink regression coefﬁcients among collinear predic-
tors to realistic levels, are advisable for further FOMO
When writing the present paper, we were also surprised
that FOMO has not yet been investigated with neuros-
cientiﬁc tools to better understand which neural processes
underlie the relevant construct. This is a glaring omission,
since studies have increasingly used such tools to
investigate the effects of excessive social network use/
or the power of likes on platforms
such as Instagram.
This less-traveled path will be of
tremendous importance for gaining deeper insights into
the actual nature of FOMO. It will also be important to
disentangle more state/trait effects of FOMO, given that
Balta et al.
found that associations with neuroticism
are stronger for trait FOMO (r = 0.29) than state FOMO
(r = 0.15). See also Wegmann et al.
on the distinction
between state vs. trait FOMO.
Finally, other psychological constructs that have pre-
liminary associations with FOMO should be further
examined in subsequent studies, including behavioral
activation, which is important for treating major depres-
as well as the need for physical touch.
Another important area to study is app design that
Braz J Psychiatry. 2020;00(00)
4JD Elhai et al.
reduces FOMO by batching interruptive smartphone
We hope that advances in methodologi-
cal design will further our understanding of FOMO and its
relationship with relevant psychological variables.
JDE is a paid, full-time faculty member at University of
Toledo and a paid, visiting scientist at Tianjin Normal
University; he receives grant research funding from the
U.S. National Institutes of Health and the Department of
Defense. CM has received (from Ulm University and the
University of Bonn) grants from the German Research
Foundation (DFG) and the German Federal Ministry for
Research and Education.
JDE receives royalties for several books published on post-
traumatic stress disorder (PTSD); occasionally serves as a
paid, expert witness on PTSD legal cases. CM has perfor-
med grant reviews for several agencies; has edited journal
sections and articles; has given academic lectures in clini-
cal or scientiﬁc venues or companies; has generated books
or book chapters for publishers of mental health texts (for
some of these activities he received royalties, but never
from the gaming or social media industry); is part of a dis-
cussion circle (Digitalita
¨t und Verantwortung: https://about.
wortung/) debating ethical questions linked to social media,
digitalization and society/democracy at Facebook (no
salary); and is currently on the scientiﬁc advisory board
of the Nymphenburg Group (nymphenburg.de; for this
activity he is ﬁnancially compensated). The other author
reports no conﬂicts of interest.
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