Fear of missing out and self-esteem as mediators of the relationship between maximization and problematic smartphone use

Abstract

Problematic smartphone use (PSU), which involves an excessive and uncontrolled use of smartphones, thereby causing daily-life disturbance, has been associated with a range of negative outcomes including anxiety, depression, and deficits in social relationships. However, the relationship between PSU and maximization, which could be an explanatory factor, has not yet been thoroughly studied. Drawing on the Interaction-Person-Affect-Cognition-Execution (I-PACE) model, the current study aimed to investigate the association between PSU and maximization with the assumption that fear of missing out (FoMO) and self-esteem could mediate this relationship. Empirical data were gathered from 277 Italian university students who completed an online survey. Correlation analysis and structural equation modelling (SEM) were used to investigate the relationships among the variables. The results showed that PSU, maximization, and FoMO were positively correlated; whereas maximization and self-esteem were negatively correlated. Furthermore, FoMO and self-esteem partially mediated that relationship, suggesting that participant maximizers experience more FoMO, especially when the participants have fear of missing out on potentially “better” alternatives to social experiences and exhibit low self-esteem. Thus, higher FoMO and low self-esteem can be a driver of PSU. Finally, this study provides new insights about how maximization may have an impact on the development of addictive behaviour such as PSU.

Full text

Fear of missing out and self-esteem as mediators of the relationship
between maximization and problematic smartphone use
Rocco Servidio
1
Accepted: 30 December 2020
#The Author(s) 2021
Abstract
Problematic smartphone use (PSU), which involves an excessive and uncontrolled use of smartphones, thereby causing daily-life
disturbance, has been associated with a range of negative outcomes including anxiety, depression, and deficits in social relation-
ships. However, the relationship between PSU and maximization, which could be an explanatory factor, has not yet been
thoroughly studied. Drawing on the Interaction-Person-Affect-Cognition-Execution (I-PACE) model, the current study aimed
to investigate the association between PSU and maximization with the assumption that fear of missing out (FoMO) and self-
esteem could mediate this relationship. Empirical data were gathered from 277 Italian university students who completed an
online survey. Correlation analysis and structural equation modelling (SEM) wereused to investigate the relationships among the
variables. The results showed that PSU, maximization, and FoMO were positively correlated; whereas maximization and self-
esteem were negatively correlated. Furthermore, FoMO and self-esteem partially mediated that relationship, suggesting that
participant maximizers experience more FoMO, especially when the participants have fear of missing out on potentially “better”
alternatives to social experiences and exhibit low self-esteem. Thus, higher FoMO and low self-esteem can be a driver of PSU.
Finally, this study provides new insights about how maximization may have an impact on the development of addictive
behaviour such as PSU.
Keywords Problematic smartphone use .Maximization .Self-esteem .FoMO .I-PACE
Introduction
The rapid diffusion and adoption of smartphones, tablets and
smartwatches, have greatly facilitated people’s access to
goods and services found on the web. This ease of access,
however, has translated into increased hours of connectivity
such that the amount of time people spend on their
smartphones has become a growing concern, prompting sev-
eral scholars to explore whether their excessive use could lead
to addictive behaviours (Duke & Montag, 2017; Kim et al.,
2016;LoCocoetal.,2020; Servidio, 2019). The addictive use
of the Internet is often denominated by such terms as: social
media addiction, Facebook addiction, and problematic
smartphone addiction (Choi et al., 2014; Marino, Gini,
Vieno, & Spada, 2018), among others. While Internet addic-
tion and problematic smartphone addiction are two different
terms, they are closely related and refer to the overuse of
online communication technologies characterised by constant
interaction with others (Wegmann & Brand, 2016).
Problematic Smartphone Use (PSU) is a recent construct
which is described as the excessive use of the smartphone,
accompanied by addiction-like behaviour such as withdrawal
(when unable to use one’s phone) and tolerance (increased use
to obtain the same level of satisfaction) (Elhai, Levine, & Hall,
2019; Rozgonjuk & Elhai, 2019). Indeed, PSU can involve
deficits in social relationships, work and/or school perfor-
mance, and can even lead to family disputes caused by exces-
sive smartphone use because of too many hours spent on
social media interaction (Billieux, Maurage, Lopez-
Fernandez, Kuss, & Griffiths, 2015). Additionally, results
from several previous studies found an association between
PSU and poor mental health condition including depression
and anxiety (Coyne, Stockdale, & Summers, 2019; Kara,
*Rocco Servidio
servidio@unical.it
1
Department of Cultures, Education and Society, University of
Calabria, Via Pietro Bucci, Building Cube 20/B, 87036 Arcavacata
di Rende, Cosenza, Italy
https://doi.org/10.1007/s12144-020-01341-8
/ Published online: 2 February 2021
Current Psychology (2023) 42:232–242
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Baytemir, & Inceman-Kara, 2019), sleep deficits (Zhang &
Wu, 2020), low self-esteem (Lannoy et al., 2020), low self-
control (Servidio, 2019), and lower motivation in doing phys-
ical activities (Pereira, Bevilacqua, Coimbra, & Andrade,
2020). We should underline, however, that PSU is not actually
included in the official diagnosis of the International
Classification of Diseases (ICD-11) or the Diagnostic and
Statistical Manual of Mental Disorders (DSM-5) and does
not seem to pose the same risks that drug and alcohol use
disorders do. However, Montag, Wegmann, Sariyska,
Demetrovics, and Brand (2019) indicate that PSU falls into
the realm of mobile Internet use disorders. Thus, based on
preliminary evidence, we believe that studying PSU may be
useful in complementing what we know of the effects of tech-
nological addictive disorders and allows us to better specify
which variables potentially drive PSU.
A relevant theory that helps us understand the addictive use
of Internet applications relating to gambling, gaming, and
pornography use, among others, is the Interaction of Person-
Affect-Cognitive-Execution model (I-PACE) (Brand et al.,
2019; Brand, Young, Laier, Wölfling, & Potenza, 2016).
Since the I-PACE conceptualization has further been extended
to include research on PSU disorders (Oberst, Wegmann,
Stodt, Brand, & Chamarro, 2017;Rozgonjuk&Elhai,2019;
Servidio, 2019), its theoretical framework was deemed appro-
priate for this study. The framework emphasizes the interac-
tion among a person’s core characteristics and the cognitive,
affective, and executive processes as it attempts to explain the
mechanisms underlying the development and maintenance of
a specific Internet-use disorder such as PSU. It also illustrates
the different levels of the addiction process in disorders that
include, but are not limited to Internet-gaming. It poses that
the development of problematic and addictive behaviour oc-
curs when there is an interaction between an individual’spre-
disposing variables (e.g., depression, anxiety, and personal
factors) and certain aspects related to specific situations
(Brand et al., 2016; Brand et al., 2019). The result of the
interaction is an experience of gratification and compensation
associated with specific Internet-related behaviour (e.g., pay-
ing attention to specific stimuli, or feeling the desire to play
online). On the other hand, the affective and cognitive re-
sponse variables are conceptualized as influencing the choice
of Internet technology, which can result in adaptive
or dysfunctional behaviour.
A person, for example, could use his or her own
smartphone to alleviate the burden of real-life problems, to
avoid loneliness, or to experience pleasure and positive emo-
tions from the simple fact that one is online (Brand et al.,
2016). These expectancies can influence not only the individ-
ual’s behaviour, but also the decision to use or not use a
specific Internet and/or smartphone application (Wegmann
&Brand,2016). Thus, certain motives and predisposing fac-
tors are reinforced by the effects of the gratification
experienced and the escape from negative emotions.
Consequently, this may lead to excessive use of the preferred
Internet and/or smartphone application, resulting in reduced
control and stabilization of the person’scorecharacteristics.
Thus, within the conceptualization of I-PACE, this study
focuses on the following variables: first, maximization as a
personality trait that represents the general tendency to strive
for the best possible option, and leads to delayed decisions
(Schwartz et al., 2002); second, a state variable such as fear
of missing out (FoMO), which is the apprehension of missing
out on rewarding experiences, leading to a corresponding
need to stay persistently connected with one’ssocialnetwork
(Przybylski, Murayama, DeHaan, & Gladwell, 2013); and
third, self-esteem, which is another personality variable poten-
tially involved in the risk of PSU (Lannoy et al., 2020). The
proposed relationships are analysed through correlational
analysis and the Structural Equation Modelling (SEM) to test
the mediating effects. Finally, because the role of individual
characteristics (e.g., age and gender) in the risk of PSU is often
inconsistent (Chen et al., 2017), all these variables were in-
cluded as covariates.
Maximization as a Possible Predictor of PSU
Maximization may be one among several characteristics of an
individual that is linked to smartphone overuse. It has been
conceptualized as a personality trait which describes individual
differences in the general tendency of striving to make the best
choice (for reviews see, Misuraca & Fasolo, 2018;Cheek&
Schwartz, 2016). According to Schwartz et al. (2002), maximi-
zation is an inclination to look for the best alternative possible
through systematic and exhaustive searches. The construct of
maximization has been widely applied in exploring decision-
making strategies regarding consumer behaviour experiences.
Findings based on the construct of maximization have re-
vealed that people who display tendencies to maximize have
less life-satisfaction, happiness, optimism, and self-esteem
(Newman, Schug, Yuki, Yamada, & Nezlek, 2018); they are
also depressed, anxious, and impulsive (Purvis, Howell, &
Iyer, 2011; Schwartz et al., 2002). It has also been shown that
maximizers tend to report maladaptive decision-making strat-
egies, avoid making decisions (Schwartz et al., 2002), exhibit
less behavioural coping strategies and show greater tendency
to depend on others for their decisions (Parker, de Bruin, &
Fischhoff, 2007). Another set of studies has revealed that
maximizers are more prone to social comparison (Polman,
2010) and are unhappy when they discover that others select-
ed better choices compared to theirs, even if their own choice
was better than expected (Huang & Zeelenberg, 2012).
Although maximization has not been extensively investi-
gated in the field of PSU, there is a recent study that has linked
maximization to problematic social network use. Specifically,
this study found that tendencies to maximize and to
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procrastinate lead to problematic social networks use, espe-
cially in cases when there is a high incidence of specific fears
and intentions to discover, or to avoid missing out on a poten-
tially “better”alternative for social experiences (Müller,
Wegmann, Stolze, & Brand, 2020). Moreover, another study
shows that specific online addictions such as PSU, social me-
dia addiction, and Internet gaming disorder share the same
features with generalized Internet addiction (Chen et al.,
2020). It has also been suggested that PSU is associated with
social media addiction because persons tend to use their
smartphone as easy and portable access to social media appli-
cations (Kuss et al., 2018; Sha, Sariyska, Riedl, Lachmann, &
Montag, 2019).
People with the tendency to maximize and who receive
social media notifications on their smartphone and/or
smartwatch about social events could be more susceptible to
experiencing negative feelings because of the need to maxi-
mize the many choices and decisions theywould have to make
to avoid missing out on new social experiences. According to
the I-PACE model (Brand et al., 2016; Brand et al., 2019), this
subjective stress response to situational factors may influence
the decision to use Internet-related technologies, such as the
smartphone, to cope with the associated cognitions and af-
fects. Therefore, people who think that they can solve specific
problems by going online could be led to an uncontrolled and
impulsive use of online communication applications. Indeed,
similar to those with Internet-addictive behaviour, maximizers
tend to delay decision-making but exhibit impulsivity in mak-
ing such decisions in favour of options that offer immediate
gratification (Müller et al., 2020). The negative impact of this
impulsivity on PSU has been documented since previous stud-
ies have provided evidence of impulsivity as a risk factor for
PSU (Kim et al., 2016;Servidio,2019). In fact, Billieux et al.
(2015) proposed a theoretical framework in which PSU is
driven by impulsivity leading to excessive smartphone use.
No previous studies have examined the link between
maximization and PSU, even if the study by Müller et al.
(2020) has investigated the relationship between maximiza-
tion and problematic social network use. Overall, consider-
ing the existing studies, we can make a reasonable hypoth-
esis that tendencies towards maximization could be related
to PSU (H1). This hypothesis is in line with the assumption
taken by the I-PACE model, which illustrates how person-
alityfactorsandsocialsituationscouldleadtohighexpec-
tancies, and in this case, smartphone-use could represent a
dysfunctional coping strategy of escaping from negative
feelings and of experiencing pleasure by going online to
maximize personal needs.
The Mediating Role of FoMo and Self-Esteem
Given the scarcity of studies examining the potential influence
of maximization on PSU, little is known regarding the
mediating mechanisms underlying this relationship. Thus,
the current study was interested in exploring whether fear of
missing out (FoMO; Przybylski et al., 2013) and self-esteem
could mediate the relationship between maximization and
PSU.
In recent years, FoMO has received great attention since
most of the existing researches focus on the question of
whether FoMO is connected to an increased use of social
media (e.g., Alt & Boniel-Nissim, 2018; Milyavskaya,
Saffran, Hope, & Koestner, 2018). The proliferation of social
media applications and the related rise insmartphoneuse have
heightened people’s awareness of possibly missing out on
potentially exciting social experiences. In this vein, an as-
sumption could be made that the frequent reception of notifi-
cations on smartphones and/or smartwatches, reminding peo-
ple of potentially more rewarding alternatives, could increase
feelings of FoMO (Milyavskaya et al., 2018;Mülleretal.,
2020). Furthermore, it is likewise well known that people
who score high in FoMO are likely to overuse their
smartphones to satisfy the desire of staying connected
(Rozgonjuk, Sindermann, Elhai, & Montag, 2020).
Similar to maximization, a high score in FoMO has been
found to show higher levels of regret indicating that FoMO
plays an important role in the context of PSU and social media
addiction (Oberst et al., 2017; Wegmann, Oberst, Stodt, &
Brand, 2017). Moreover, current studies show that FoMO is
associated to alcohol consumption (Riordan, Flett, Cody,
Conner, & Scarf, 2019), and lower levels of life satisfaction
(Casale, Rugai, & Fioravanti, 2018). Additionally, other re-
searchers have demonstrated that FoMO is associated with
PSU and other online addictive behaviours, such as excessive
social media use (Elhai et al., 2018).
Recently, Milyavskaya et al. (2018) drew further similari-
ties between FoMO and maximization. Specifically, starting
from the assumption that having too many choices can lead to
choice paralysis, “FoMO can be thought to arise from an
abundance of choices among activities or experiences, partic-
ularly those of a social nature, coupled with an uncertainty
over the ‘best’choice and anticipatory regret over the options
not selected”(Milyavskaya et al., 2018, p. 725). Thus, people
who score higher in maximization might have increased feel-
ings of FoMO. Accordingly, this study hypothesizes that ten-
dencies towards maximization predict the severity of the ex-
perience of FoMO (H2).
Additionally, empirical studies have examined the mediat-
ing role of FoMO in the relationship between psychological
variables and PSU. For example, Wang et al. (2019a)found
that procrastination and FoMO partially mediated the relation-
ship between sensation seeking and smartphone addiction.
Another study indicated that envy was positively related to
PSU, with FoMO mediating this relationship (Wang et al.,
2019b). Moreover, another study shows that people who score
high in FoMO are more prone to check the notifications on
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their smartphone, as well as to update their social media pro-
file and status because they want to be part of the online
community, which behaviour may result in developing the
risk of PSU (Long, Wang, Liu, & Lei, 2019). Consequently,
they may develop an addictive PSU behaviour due to an al-
most compulsive use of such communication tools.
Following these lines of research, the present study hypoth-
esizes that FoMO could mediate the relationship between
maximization and PSU (H3). The reception of frequent re-
minders of alternatives, and the thought of possibly missing
out on social experiences which are perhaps more gratifying,
could be positively associated with PSU (Milyavskaya et al.,
2018;Mülleretal.,2020). In the I-PACE model, FoMO is a
cognitive or affective response driven by predisposing vari-
ables such as personality traits, and which in turn contribute to
PSU (Brand et al., 2016).
With regard to self-esteem, although prior scholars have
investigated the relationships between personality traits and
PSU, few studies have explored its role in PSU (Lannoy
et al., 2020).AccordingtoRosenberg(1965), self-esteem
is one’s positive or negative attitude toward oneself and
one’s evaluation of one’s own thoughts and feelings overall
in relation to oneself. People with high self-esteem tend to
use technologies in a balanced manner, tend to positively
cope with stressful situations, and develop a positive atti-
tude towards life (Servidio, Gentile, & Boca, 2018). On the
other hand, people with low self-esteem try to find shelter in
the Internet network, which allows them to control the self-
aspects they want to make public. Similar to what is com-
monly observed with other forms of addictive behaviour,
low self-esteem is associated with Internet addiction and
with the compulsive use of social media applications
(Andreassen, Pallesen, & Griffiths, 2017).
A cross-sectional study showed that dysfunctional attitudes
and self-esteem were found to be mediators between anxious
attachment styles and smartphone addiction (Yuchang,
Cuicui, Junxiu, & Junyi, 2017). Another study found that
self-esteem mediated the link between adolescent student-
student relationship and PSU (Wang et al., 2017). Moreover,
the results ofa recent meta-analysis identified that self-esteem,
among other psychopathological variables, was inconsistently
related to PSU, with small to medium effects (Elhai, Dvorak,
Levine, & Hall, 2017). Overall, these results suggest explor-
ing the role of self-esteem by including new constructs.
As regards the relationship between maximization and self-
esteem, one study shows that people with high maximization
tendencies, compared to satisfiers, are more sensitive to
experiencing low self-esteem (Misuraca & Fasolo, 2018). The
behaviour of maximizers is characterized by a high need for
scrupulousness and order that reduces self-esteem and optimism
and increases high levels of regret, because they sacrifice limited
resources in an attempt to discover the best options (Newman
et al., 2018). In relation to smartphone use, people tend to use
their own smartphone to search for the best alternative, and in
turn reinforce the decision to remain connected online, thus in-
creasing the risk of developing addictive behaviours.
To date, however, few studies have examined the mediat-
ing role of self-esteem in the relation between personality
traits and PSU. Based on the literature reviewed above, this
study hypothesizes that maximization is negatively associated
with self-esteem, which in turn is negatively associated with
PSU (H4). In other words, self-esteem mediates the relation-
ship between maximization and PSU (H5).
The Present Study
Taking all the previous discussions together, it is assumed that
an individual with the tendency to maximize would most likely
have the propensity for PSU. This association between maxi-
mization and PSU could be mediated by specific variables re-
lated to opinions and feelings of potentially missing out on
significant events that occur online (e.g., FoMO), and by a
miximizer’s low levels of self-esteem, which in turn could in-
crease PSU. Thus, the tendency to avoid missing out on poten-
tially better social experiences may reinforce a dysfunctional
and uncontrolled use of the smartphone, resulting in higher
symptoms of PSU. These cyclic relationships are consistent
with the assumption taken by the I-PACE model, given that
previous gratification experiences in the use of Internet-based
applications tend to change the subjective reward expectations
that are associated with the specific behaviour.
Finally, even though much is known about the association
between personality traits and PSU, no previous studies have
investigated the effects of other personality traits, like maxi-
mization, onthis relationship, and how FoMO and self-esteem
may affect the link between maximization and PSU.
Investigating these relationships may give new insights by
providing additional knowledge to PSU studies, as maximiza-
tion could be a predisposing variable that leads to PSU.
Additionally, including FoMO and self-esteem into this rela-
tionship may explain their mechanisms in the association.
Method
Participants
A sample of 277 undergraduate students was recruited from
an Italian public university during the 2019–2020 academic
year. The sample consisted of 68 males (24.5%) and 207 fe-
males (74.7%). Two students did not report their gender
(0.7%). The participants’ages ranged from 19 to 38 (M=
23.46, SD = 3.56). Most participants attended psychological
and educational courses (64.6%); the rest were enrolled in
various courses such as economics (4%), healthcare (5.8%)
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and a scientific one (13.7%). The remaining students (11.9%)
did not indicate their degree courses.
Measures
Maximization Scale
The Maximization scale (Schwartz et al., 2002) was used to
measure the individual maximizing tendency. The scale was
translated from English to Italian according to the recommen-
dations of the International Test Commission (2017). It con-
tains 13 items (e.g., I often find it difficult to shop for a gift for
a friend) and the participants reported the extent to which each
statement described them, using a seven-point Likert scale
ranging (from 1 = “strongly disagree”to 7 = “strongly agree”)
with higher scores indicating higher maximization tendencies.
The scale revealed a satisfactory internal reliability, α=.75
(M= 3.78, SD = .97). Finally, confirmatory factor analysis
showed that all the items loaded on the scale, indicating that
the construct validity of the instrument was good, χ
2S-B
(60, N=270)=85.82,p= .018, CFI = .941, TLI = .923,
RMSEA = .040, 90% CI [.02, .06], SRMR =.050.
Fear of Missing out Scale
The Italian version of the Fear of Missing Out (FoMO) scale
was used to measure the adolescents’disposition towards fear
of missing out (Casale & Fioravanti, 2020;Przybylskietal.,
2013). The scale comprises 10 items (e.g., I fear others have
more rewarding experiences than me), measured on a five-
point Likert type (from 1 = “not at all true of me”to 5 =
“extremely true of me”). For the present study, the reliability
of the scale was, α=.70.
Rosenberg Self-Esteem Scale
The Italian version of the Rosenberg Self-Esteem scale (Prezza,
Trombaccia, & Armento, 1997) was used to measure the sub-
jective feelings of self-value and self-acceptance. Participants
rated their agreement with 10 statements (e.g., “IfeelthatIhave
a number of good qualities”) on a four-point Likert type (from
1=“strongly agree”to 4 = “strongly disagree”). Higher scores
indicate higher self-esteem. The internal consistency in the sam-
ple of this present study, α= .86, was good.
Problematic Smartphone Use Scale
The short Italian version of the 10 items-Problematic
Smartphone Use scale for adolescents and young adults was used
(PSU; De Pasquale, Sciacca, & Hichy, 2017; Kwon, Kim, Cho,
& Yang, 2013). Participants gave their answer on a six-point
Likert scale (from 1 = “strongly disagree”to 6 = “strongly
agree”) with higher scores indicating higher PSU. A sample item
is “I have used my Smartphone longer than I had intended”.The
PSU scale showed good reliability and validity for the assess-
ment of PSU and the Italian version has shown good psychomet-
ric properties as well (see also, Servidio, 2019). The scale reli-
ability in the current sample was, α= .82.
Procedure
A cross-section web-based survey was conducted, which pro-
vided a battery of assessment aimed at investigating individual
behaviour towards digital technologies. Additionally, the par-
ticipants were asked to provide demographic information about
their gender, age, and degree course. A snowball procedure was
applied in recruiting the participants. Specifically, it consisted
of having a participant ask colleagues or fellow university stu-
dents to complete the survey, and those new participants, in
turn, recruited other university students they knew and so on.
The information about the study was emailed with the link of
the survey to undergraduate students. Furthermore, the link of
the survey was posted on a Facebook wall. Only measures
relevant to the current research are reported.
All participants were informed of the study’s objectives
and were guaranteed strict confidentiality in their answers to
the questionnaire. Those who agreed to participate in this
study signed an online informed consent form, and were in-
vited to complete an anonymous questionnaire. All partici-
pants volunteered for the study and none of them received
any kind of remuneration. Moreover, they were also given
the opportunity to withdraw the data from the study at any
stage. Completing the online survey took approximately
25 min.
Statistical Analyses
Before performing the data analyses, all the variables were
screened for linearity, homoscedasticity, and homogeneity of
variance. Additionally, univariate normality (skewness and
kurtosis), multivariate outliers, and cases with missing values
were checked. The scatterplot of standardised predicted values
versus standardised residuals, showed that the data met the
assumptions of linearity and the residuals were approximately
normally distributed. This suggests that the data does not vi-
olate the assumption of homoscedasticity. The Levene’sFtest
revealed that the homogeneity of variance assumption was
met with, p= .166. Following the general recommendations
for skewness and kurtosis, our variables were normally dis-
tributed (Tabachnick & Fidell, 2014); the highest skewness
value was, .73 (FoMO), and for kurtosis was, −.41
(Maximization). By computing the Mahalanobis distance
with, p< .001 for the chi-square (χ
2
) distribution value
(Tabachnick & Fidell, 2014), no multivariate outliers among
the cases were identified. No cases had missing data.
Descriptive statistics and Pearson’s correlation analyses were
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computed. The internal reliability was obtained by computing
the alpha of Cronbach (α). SPSS 25 package was used to run
the preliminary statistical procedures.
A partial and a full mediating model were separately tested to
verify whether the proposed mediators, self-esteem, and FoMO
fully explained the relationships between maximization and
PSU. Age and gender were also controlled. Confirmatory factor
analysis (CFA) and structural equation modelling (SEM) were
performed using Mplus 7.04 (Muthén & Muthén, 2014). As Hu
and Bentler (1999) recommended, multiple indices were used to
evaluate the model fit (adopted cut-offs in brackets): the chi-
square (χ
2
) test value with the associated pvalue (p>.05),com-
parative fit index (CFI ≥.95), Tucker–Lewis Index (TLI ≥.95),
root-mean-squared error of approximation (RMSEA ≤.06), and
its 90% confidence interval, and standardized root mean square
residual (SRMR < .08). Both confirmatory and SEM were esti-
mated with the maximum-likelihood parameter with standard
errors and a mean-adjusted chi-square test statistic that were
robust to non-normality (MLM) as Maydeu-Olivares (2017)
suggested. The MLM chi-square test statistic is also referred to
as the Satorra-Bentler (S-B) chi-square.
With regard to the SEM, item parcelling was applied
(Little, Cunningham, Shahar, & Widaman, 2002) to define
each construct of the model on a latent level. The item parcel-
ling was built by applying a balanced method, which aims to
combine high and low inter-correlations values (Little,
Rhemtulla, Gibson, & Schoemann, 2013). Finally, the partial
mediating model and the fullmediating model were compared
to determine the mediating role of self-esteem and FoMO in
the relationship between maximization and PSU. The models
were evaluated by using a chi-square (χ
2
) difference test,
which provides a statistical test of whether the constraints
are justified (Kline, 2016). To establish significant differences
between models, at least two out of three criteria had to be
satisfied: Δχ
2
significant at, p<.05, ΔCFI ≤.005, and
ΔRMSEA ≤.010 (Chen, 2007).
Ethics
All the research materials and procedures were designed and
conducted according to the ethical standards laid out by the
Italian Psychological Association (AIP) and the Declaration of
Helsinki.
Results
Descriptive and Correlations
Means, standard deviations, and bivariate correlations of the
measurements of maximization, self-esteem, FoMO, PSU,
age, and gender are shown in Table 1. The mean of
maximization score indicates tendencies towards maximizers
rather than satisfiers (who are inclined to attempt to find a tree
that works for them rather than the best one) in the current
sample. Finally, all the correlations between the constructs are
significant and satisfy the conditions for performing the SEM
analysis.
Structural Equation Modelling and Mediation Analysis
Figure 1illustrates the findings from the SEM used to analyse
the hypotheses of the present study and includes the standard-
ized estimates. The hypothesized model provided a good fit to
the data, χ
2S-B
(59, N= 275) = 90.22, p= .005, CFI = .966,
TLI = .955, RMSEA = .044, 90% CI [.02, .06],
SRMR = .061. Age and gender were predictors of PSU.
Finally, PSU accounted for 35% of the variance.
Table 2shows the results of the mediation analysis and the
indirect effects for PSU and its predictor and mediators’variables.
The results of the analysis indicated that the relationship
between maximization and PSU was partially mediated by
self-esteem and FoMO. As for the indirect effects, both self-
esteem and FoMO indirectly affected the association between
maximization and PSU.
Next, a full mediated model and a partially mediated one
were tested. Although the full mediated model provided suf-
ficient fit to the data, χ
2S-B
(60, N= 275) = 113.96, p=.000,
CFI = .941, TLI = .924, RMSEA = .060, 90% CI [.04, .07],
SRMR = .072, after comparing the two models, the results
showed that the full mediated model fits the data worse,
Δχ
2
(1) = 26.27, p< .001, ΔCFI = −.025, ΔRMSEA = .013.
Therefore, the less restricted model fits the data better than
the smaller model in which some parameters are fixed. Thus,
the partial mediating model was selected as the final one.
Discussion
The aim of the current study was to investigate the predictive
role of maximization on PSU, and the mediating effects of
FoMO and self-esteem in this relationship.
Table 1 Descriptive statistics and correlations between the measures of
maximization, self-esteem, FoMO, PSU, age, and gender
MSD123456
1. Maximization 49.17 12.58 –
2. Self-Esteem 29.68 4.84 −.19
***
–
3. FoMO 19.60 5.23 .31
***
−.13
*
–
4. PSU 27.00 9.33 .47
***
−.21
***
.31
***
–
5. Age 23.46 3.56 −.09 .08 −.11
*
.07 –
6. Gender
a
––.03 −.12
*
−.00 .12
*
−.10 –
Note. FoMO = Fear of Missing Out. PSU = Problematic Smartphone Use
a
Male = 1, female = 2
*
p<.05.
***
p<.001
237Curr Psychol (2023) 42:232–242
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A direct, positive, and significant association between
maximization and PSU was found, supporting H1. The em-
pirical results of this study confirm that maximization inclina-
tions are associated with PSU. These results fit with the theo-
retical conceptualization of the I-PACE model (Brand et al.,
2019), whose focus is to explain how specific Internet-use
disorders, such as PSU, are developed and maintained.
Individuals with the tendency to maximize in finding the “bet-
ter”option increase their risk of developing PSU. Given that
impulsiveness is a personality characteristic of maximizers,
we can interpret this result in the context of studies demon-
strating that impulsivity increases the risk of PSU (Kim et al.,
2016; Servidio, 2019), as well as in the framework of the I-
PACE model, which associates impulsivity with unspecified
Internet-use disorder (Brand et al., 2019). The results of the
SEM indicate that the association between maximization and
PSU was partially mediated by FoMO and self-esteem, reveal-
ing the predictive role of maximization in the development of
PSU. Thus, this study provides new insights for future inves-
tigations aimed at identifying and reducing the risk of prob-
lematic smartphone use.
Consistent with a previous study (Müller et al., 2020), the
assumption that an association could exist between maximi-
zation and FoMO (H2) was supported by the present results.
This association might indicate that the tendency to maximize
decisions increases the likelihood of FoMO, which then inten-
sifies dysfunctional online interaction and specifically the risk
of PSU. This positive association underlines the idea that by
having several options on hand, people could change deci-
sions and use their smartphone to search for better alternatives,
and in turn increase the risk of developing PSU. People who
experience FoMO tend to frequently check their social media
smartphone applications, which could result in PSU (Casale
et al., 2018). Similarly, because a smartphone allows access to
different kind of applications, FoMO could be accentuated
when the person considers multiple socially relevant events
(Milyavskaya et al., 2018). According to the I-PACE model,
Fig. 1 Results of the structural equation model, including factor loadings and direct effects and significance levels. Note.
*
p<.05.
**
p< .01.
***
p< .001
Table 2 Mediation and indirect effects with standardized estimate of
fear of missing out, and self-esteem for the relationship between maximi-
zation and problematic smartphone use
Pathway Estimate SE z p
MAX --> PSU
Total .512 .059 8.681 .000
Direct effect .404 .070 5.745 .000
MAX -->RSE -->PSU
Specific indirect effect .030 .014 1.856 .053
MAX --> FoMO -->PSU
Specific indirect effect .082 .032 2.575 .010
Note. SE = standard error. MAX = Maximization; PSU = Problematic
Smartphone Use; RSE = Rosenberg Self-Esteem. FoMO = Fear of
Missing Out
238 Curr Psychol (2023) 42:232–242
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people could also use their smartphone applications to cope
with negative emotions arising from the feeling caused by
FoMO and this mechanism characterises the development of
addictive behaviour (Brand et al., 2019). In this view, PSU
could be interpreted as a cognitive-emotional regulation strat-
egy aimed at handling the stress associated with failing to
fulfil personal needs. Taken together, the study’sfindingspro-
vide a new perspective in exploring the cause of FoMO and
how it is related to PSU.
The hypothesized mediating role of FoMO (H3) in the
prediction of PSU was partially supported by the results of
the SEM. While this study offered empirical support for the
hypothesized mediating link, the result of the partial mediation
provides a clue that other mediators may have been
overlooked in the proposed model. Further studies should
consider examining the effect of social comparison
(Festinger, 1954), which often leads people to think that they
are worse off than others in certain aspects, thus increasing the
experience of negative feelings. Indeed, maximizers tend to
adopt strategies of seeking out and comparing alternatives
because they experience a tendency towards perfectionism
and this could lead to increased use of the Internet and its
related technologies such as the smartphone in searching for
better alternatives.
This study also confirmed that maximization was negative-
ly related to self-esteem, which in turn was negatively related
to PSU, supporting H4, that is, self-esteem partially mediates
the association between maximization and PSU (H5).
Moreover, the indirect effects were marginally significant.
By contrast, an increase in maximization is associated with
lower levels of self-esteem and life-satisfaction (Schwartz
et al., 2002) and reduced self-esteem increases the risk of
PSU. Maximizing is linked to social comparison which leads
to more counterfactual thinking and regret and subsequently
leads to greater dissatisfaction and lower personal well-being
(Newman et al., 2018). As suggested by Billieux et al. (2015),
individuals with low self-esteem have distorted cognitions and
difficulty in emotion regulation. Thus, these people feel the
need to use a smartphone to obtain comfort in affective rela-
tionships. Self-esteem is a key component of any self-
improvement program that could help people to resist addic-
tive behaviours such as PSU. The results of the current study
are consistent with previous findings which suggest that indi-
viduals with low self-esteem have the propensity of becoming
Internet addicts (Andreassen et al., 2017; Servidio et al.,
2018). In addition, this result is consistent with another study
showing that individuals with low self-esteem have difficulty
undertaking social interactions and receive less social support,
and consequently feel unpleasant emotions such as loneliness
(Yuchang et al., 2017). According to the I-PACE model, lone-
liness and self-esteem are two important factors in addictive
behaviour (Brand et al., 2019), thus self-esteem could work as
a protective factor against PSU. Therefore, removing
irrational beliefs and improving self-esteem could reduce
PSU tendencies.
Limitations and Future Research
This study has some limitations. First, due to the cross-
sectional nature of the study design, we cannot make any
causal inferences about the observed findings. For example,
the causality between maximization and PSU remains unclear.
It could be plausible that smartphone use may increase the
desire to search for the best alternative. According to
Milyavskaya et al. (2018), for instance, we can assume circu-
lar or bi-directional association in a manner that maximiza-
tion, as well as FoMO and self-esteem, affect PSU but that
smartphone overuse, in turn, can influence these variables,
increasing the problematic or addictive behaviour in terms of
stabilizing and intensifying mechanisms (cf., Brand et al.,
2019;Mülleretal.,2020). Because of the cross-sectional na-
ture of this study, future research could perhaps explore these
findings using a longitudinal design.
Second, the scale for measuring maximization has not yet
been validated. Based on the results of the present study, fu-
ture investigations could use the proposed instrument to vali-
date and test its psychometric properties. A third limitation
was related to the sample, which was skewed towards women,
who usually use the smartphone and social media applications
more than men (Chen et al., 2017). Finally, the present study
used only self-report questionnaires that have well-known
limitations such as desirability biases.
Conclusions and Practical Implications
The results of the current study suggest that maximization
tendency is a significant predictor of PSU, especially if rein-
forced by a belief of missing out on an opportunity for a
rewarding social experience, as indicated by the partially me-
diating role of FoMO and self-esteem. The present study con-
tributes to prior literature on the relationship between person-
ality traits constructs, in this case, maximization, and PSU by
considering the mediating role of FoMO and self-esteem.
Furthermore, this is the first study that, to our knowledge,
explores the link between maximization and PSU, indicating
that maximization can be a potential PSU-driving variable.
These findings have specific social and behavioural implica-
tions on the relevance that FoMO and maximization have in
relation to the dysfunctional use of smartphones.
From a practical point of view, the current outcomes sug-
gest that health professionals who are trying to reduce the
prevalence of PSU should focus on increasing self-esteem
and decreasing FoMO to prevent the problematic behaviour
connected with the overuse of smartphone applications and
related Internet technologies. Finally, the study provided
239Curr Psychol (2023) 42:232–242
1 3
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empirical support for the I-PACE model that the interaction of
several risk factors may lead to different kinds of problematic
online behaviour.
Data Availability Statement The dataset generated and analysed during
the current study is available from the corresponding author on reasonable
request.
Funding Open Access funding provided by Università della Calabria.
This research received no specific grant from any funding agency in the
public, commercial, or not-for-profit sectors.
Declarations
Conflict of Interest The Author declares that they have no conflicts of
interest.
Ethical Approval All procedures performed in studies involving human
participants were in accordance with the ethical standards of the institu-
tional and/or national research committee and with the 1964 Helsinki
declaration and its later amendments or comparable ethical standards.
Informed Consent Informed consent was obtained from all individual
participants included in the study.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing, adap-
tation, distribution and reproduction in any medium or format, as long as
you give appropriate credit to the original author(s) and the source, pro-
vide a link to the Creative Commons licence, and indicate if changes were
made. The images or other third party material in this article are included
in the article's Creative Commons licence, unless indicated otherwise in a
credit line to the material. If material is not included in the article's
Creative Commons licence and your intended use is not permitted by
statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this
licence, visit http://creativecommons.org/licenses/by/4.0/.
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