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Chapter 7
Factors Related to Phone
Snubbing Behavior in
Emerging Adults:
The Phubbing Phenomenon
Martina Benvenuti Aneta Małgorzata Przepiorka
Italian National Research Council The John Paul II Catholic University of
(CNR), Italy Lublin, Poland

Agata Błachnio Vesela Miroslavova Daskalova

The John Paul II Catholic University of University of Bologna, Italy
Lublin, Poland
Elvis Mazzoni
https://orcid.org/0000-0002-7258-5381
University of Bologna, Italy

ABSTRACT
Smartphones are a fundamental part of emerging adults’ life. The aim of this chapter
is to determine which factors play a role in “phubbing” during emerging adulthood
as well as to propose and test a model of this phenomenon. We tested a model of
relations between phubbing, self-esteem, self-control, well-being, and internet
addiction. The following measures were used: the Rosenberg Self Esteem Scale,
the Brief Self-Control Scale (BSCS), the Flourishing Scale, the Internet Addiction
Scale, and the Phubbing Scale. The participants in the online study were 640 Italian
emerging adults (526 females and 114 males), ranging in age from 18 to 29 (M =
21.7, SD = 2.18). The results showed that the model was well fitted, particularly in
postulating that a decrease in the level of self-control is related to an increase in
Internet addiction, that an increase in Internet addiction increases the probability
of phubbing behavior, and that the level of self-esteem and well-being do not affect
Internet addiction. Gender differences, in favor of males, occurred only in self-esteem.
DOI: 10.4018/978-1-5225-9412-3.ch007

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Factors Related to Phone Snubbing Behavior in Emerging Adults

INTRODUCTION

The Internet is an important part of our daily lives. It is a basic tool for finding
information, social interactions, and the consequent construction of knowledge
(Frozzi & Mazzoni, 2011; Mazzoni & Zanazzi, 2014). The evolution of the Internet
has been accompanied by profound changes in the type of devices used to access it,
including tablets, laptops, and smartphones. Web 2.0 has revolutionized the traditional
ways of communicating, allowing easy access to an unprecedented amount of data
and enabling the spread of news in real time (Kaplan & Haenlein, 2010). Millions
of people have chosen to interact by means of virtual platforms such as blogs,
social networks, chat, and e-mail rather than face to face, which generally requires
more time and effort (Lee, 2014). Particularly the use of smartphones and mobile
phones is an integral part of people’s lives. In Italy, the number of smartphone
users in 2018 was estimated at 33.3 million (Statista, 2018). Moreover, according
to Pew Research Center (2015), 15% of Americans aged 18–29 are dependent on a
smartphone for Internet access. According to Kempt (2015), smartphones account
for more than 50% of active communication handsets worldwide. Thanks to their
portability, smartphones tend to be preferred to computers for surfing the Internet
and have become an integral part of people’s daily lives (Jones, 2014; Oulasvirta,
Rattenbury, Ma, & Raita, 2012; Roberts, Yaya, & Manolis, 2014). The possibility of
being continuously connected increases the amount of the time spent online through
mobile devices. Besides calling, texting, and basic Internet browsing, smartphones
are used for online banking, seeking information about jobs, obtaining class materials
or educational contents, and many other purposes (Blachnio & Przepiorka, 2018).
With the increasing number of smartphones, the benefits and side effects of using
them should be discussed (Blachnio & Przepiorka, 2018). Researchers have become
increasingly interested in the smartphone’s potential for social interactions (Baron
& Campbell, 2012; Campbell & Kwak, 2010; Choliz, 2010; Ha, Chin, Park, Ryu,
& Yu, 2008, Khan, 2008; Lee, Chang, Lin, & Cheng, 2014). Some studies have
suggested that smartphone use can be positive (connections are very important for
receiving and sharing information; Smetaniuk, 2014), while others suggest that the
use of social networking sites (SNSs) may lead to negative outcomes (Holmgren
& Coyne, 2017; Steinfield, Ellison, & Lampe, 2008), which in turn may lead to
Internet addiction. More and more people are developing problematic smartphone
use, which gives rise to concern about the potential consequences of smartphone
overuse (Beranuy, Oberst, Carbonell, & Chamarro, 2009).
This could be particularly relevant during emerging adulthood (Arnett, 2000; 2015),
when the use of the smartphone and online connections is particularly important
due to the residential changes typical of this life stage (Mazzoni & Iannone, 2014).
Emerging adults’ SNS use though smartphones happens when they are all together

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(Holmgren & Coyne, 2017). In this regard, a new phenomenon related to smartphone
use is emerging, called phubbing. The term “phubbing” has been derived from two
words: “phone” and “snubbing,” and means looking at one’s mobile device during
real conversations with another person (Karadağ et al., 2015). Because emerging
adulthood is the age of exploration, change, and instability (Arnett, 2015), emerging
adults are most at risk for phubbing behavior. Therefore, the aim of this chapter is
to determine which factors play a role in phubbing during emerging adulthood (this
includes testing for gender differences) as well as to propose and test a prospective
model that will help explain this phenomenon.

BACKGROUND

Jeffrey Arnett (2004, 2006, 2012) first proposed a theory of emerging adulthood that
covered the age range from 18 to 29, with a focus on ages 18 to 25. Arnett’s theory
centers around five characteristic features, which define emerging adulthood as:

1. The Age of Identity Exploration: Young people decide who they are and
what they want from work, school, and love;
2. The Age of Instability: The post-high school years are marked by repeated
residence changes, as young people go to university and live either with friends
or with a romantic partner. For most, frequent moves end as families and careers
are established around the age of 30 (in Italy, around the age of 34);
3. The Self-Focused Age: Free from parent(s) and the society-directed routine
of school, young people try to decide what they want to do, where they want
to go, and who they want to be with before these choices become limited by
the constraints of marriage, children, and career;
4. The Age of Feeling In-Between: Many emerging adults say they take
responsibility for themselves but still do not completely feel like an adult;
5. The Age of Possibilities: most emerging adults believe they have good chances
of living “better than their parents did,” and even if their parents are divorced
they believe they will find a lifelong soul mate.

All these features begin to develop before emerging adulthood and continue to
develop afterwards, but it is during emerging adulthood that they reach their peak
(Reifman, Arnett, & Colwell, 2007).
Considering the characteristics listed above, emerging adults are at risk of feeling
more insecure, having less self-control, and – as a result – feeling lower personal
well-being (Galambos, Barker, & Krahn, 2006).

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An important aspect of emerging adults’ life is related to their use of the Internet,
particularly to build and maintain their social capital during their transitions (Ellison,
Steinfield, & Lampe, 2007; 2011; Mazzoni & Iannone, 2014). However, the use of
the Internet (especially the use of smartphones to be always connected), can lead
to dysfunctional behaviors due to inverse instrumentality effects (Ekbia & Nardi,
2012), such as going to concerts or museums not in order to directly pursue one’s
interests but to share online photos of the events and receive positive feedback on
their SNS profiles.
A further stage in the dysfunctional dynamics is phubbing behavior, as persons
“snub” in-presence interactions to pay attention to online ones. One possible
explanation for these results is that if individuals do not receive adequate social-
support in daily life, they tend to create a parallel life to activate contacts and build
relationships online in order to compensate for this shortage (Mazzoni, Baiocco,
Cannata, & Dimas, 2016). Furthermore, low self-control leads to Internet addiction
behaviors (Karadağ et al., 2015, 2016; Kim, Namkoong, Ku & Kim, 2008; Malouf
et al., 2014; Mehroof & Griffiths, 2010; Tangney, Baumeister & Boone, 2004;
Young, 1998) and manifests itself as mobile phone overuse (Kwon et al., 2013;
Lopez-Fernandez, Honrubia-Serrano, Freixa-Blanxart, & Gibson, 2014; Salehan &
Negahban, 2013; Smetaniuk, 2014). Phubbing also has an impact on interpersonal
relationships and personal well-being (Roberts & David, 2017).
These patterns lead to many situations involving compulsive or impulsive online
behavior (Baumeister & Heatherton, 1996; e.g., checking for, replying to, and sending
updates, feedback, or text messages in SNS profiles for many hours per day), which
in turn may predict phubbing. This concept has been defined as snubbing others in
social interactions (Haigh, 2015; Karadağ et al., 2016), manifesting itself in individual
behavior that consists in people looking at and using their mobile phone during a
conversation with other individuals, thus escaping from interpersonal communication.
Based on previous research concerning this behavior (Haigh, 2015; Karadağ et al.,
2016; Blachnio & Przepiorka, 2018), it can be assumed that the factors that should
be considered as potentially significant to phubbing include self-esteem, self-control,
well-being, and Internet addiction.

PHONE SNUBBING BEHAVIOR DURING EMERGING

ADULTHOOD: A THEORETICAL PERSPECTIVE

Phubbing is a multidimensional phenomenon, and it may occur during over the

lifespan (Karadağ et al., 2015, 2016; Chotpitayasunondh & Douglas, 2016; Roberts
& David, 2017; Blachnio & Przepiorka, 2018). In previous studies, researchers
have highlighted different determinants of this behavior. Karadağ and colleagues

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(2015; 2016) hypothesized that phubbing is a combination of five addictions: (1)

mobile phone addiction, (2) SMS addiction, (3) Internet addiction, (4) social media
addiction, and (5) game addiction. Moreover, Chotpitayasunondh and Douglas
(2016) believed that phubbing could be a result of different addiction behaviors.
In their research, they found that Internet addiction, fear of missing out, and self-
control predicted smartphone addiction, which in turn predicted phubbing behavior
and the extent to which people were phubbed. They also investigated whether the
experience of being phubbed predicted the extent to which phubbing was perceived
to be normative – i.e., whether it was normal for other people in a face-to-face
situation to look at their smartphones and whether you could do it yourself without
feeling judged or uncomfortable (Chotpitayasunondh & Douglas, 2016). Conversely,
David, and Roberts (2017) explained this phenomenon as a result of three different
factors: social exclusion, need for attention, and social media intensity. Their point
of draws on the uses and gratifications theory (Katz, Blumler, & Gurevitch 1973;
Chen 2011; Han et al., 2015) and on the optimal flow theory (Salehan & Negahban
2013). The uses and gratifications theory argues that people who use media satisfy
particular needs (e.g., the need for attention from others). For example, in social
situations after being phubbed, people feel excluded and desire consideration to feel
included, so they look for attention on SNSs. The optimal flow theory argues that
people’s experience with SNSs (e.g., Facebook, Instagram, and YouTube) could
be so enjoyable that users develop a very intense relationship. According to Soat
(2015), receiving positive feedback (e.g., “likes” on Facebook) results in dopamine
release similar to the rush we might get from an in-person hug or smile (Soat, 2015).
These feelings could lead people to use SNSs more intensively in order to satisfy
the need for attention so as not to feel socially excluded, even in the presence of
others and when engaging in phubbing behavior. David and Roberts state “phubbing
leads to individuals feeling excluded in person, and these feelings of being excluded
in person lead to individuals intensely engaging with social media in hopes of
receiving attention and gaining a sense of belonging.” (David & Roberts 2017, p.
158). Finally, Blachnio and Przepiorka (2018) consider phubbing as resulting from
communication disturbances and phone obsession. In their model, they explain that
individuals with low self-esteem, high loneliness, and low life-satisfaction could be
most at risk for overuse of SNSs (particularly Facebook) and to be obsessed with
the use of their smartphones, which may result in phubbing behavior during face-
to-face situations with other people.
Taking these perspectives into account, the researchers aim to add a different,
integrative model and perspective, specifically designed for emerging adulthood
and highlighting those factors, as antecedents of phubbing, that play a fundamental

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role in this life stage: self-esteem, self-control, well-being, and Internet addiction.
Drawing on the literature review, the model was developed to explicate factors and
their links to phubbing behavior. The model is represented conceptually in Figure 1.
Emerging adults face numerous transitions and changes, which may affect
different personal characteristics such as self-esteem, self-control, and well-being.
As mentioned before, these affections could lead to an overuse of the Internet
(Internet addiction). Valkenburg, Peter, and Schouten (2006) highlighted how the
frequency of Internet use, particularly SNS use, indirectly affected self-esteem
and psychological well-being. We agree with David and Roberts (2017) that the
frequency of use is affected by the frequency of positive feedback (e.g., “likes” on
Facebook or “re-tweets” on Twitter) which they received on their SNS profiles.
Additionally, in another study, analyzing the relationship between social capital
(i.e., the potential benefits of creating and maintaining interpersonal relationships),
self-esteem, and the use of SNSs, it turned out that those who had low self-esteem
were more driven to use Facebook to maintain social capital than those who had
high self-esteem (Steinfield, Ellison, & Lampe, 2008; Mazzoni & Iannone, 2014).
For instance, people preferred chatting, vocal messaging, to face-to-face interactions,
because these relations are characterized by less harsh and more focused responses,
less negative judgment, anonymity, as well as more expressive and uninterrupted
communication (Walther & Boyd, 2002). According to LaRose, Linn, and Eastin
(2003), compulsive or impulsive behavior (Baumeister & Heatherton, 1996), including
online behavior (e.g., checking for, replying to, and sending updates, feedback, or
text messages in online SNS profiles many hours per day), are marked by low self-
control and play an important role in Internet overuse. As the capacity of employing
self-control varies across individuals, those who find it more difficult are more
likely to suffer negative consequences regarding emotional, social, and behavioral
adjustment (Malouf et al., 2014). Thus, individuals start accessing the Internet to
relieve boredom, reduce loneliness, or pass the time. These can be considered self-
reactive incentives leading to a conditioned response that follows using the Internet
to relieve negative mood states. Over time, this behavior evolves into a habit, and

Figure 1. Theoretical model of phubbing

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the impulse to be online becomes automatic. The more automatic the behavior, the
less attention the individual pays to the self-regulatory mechanism (Bandura, 1991)
and to the initial motivations that led them to be online. Derived from the above
concepts and theoretical background, this study has two goals:

1. To test the following hypotheses using correlation analyses:

a. H1. Self-esteem, self-control, and well-being are negatively associated
with phubbing.
b. H2. Self-esteem, self-control, and well-being are negatively associated
with Internet addiction.
c. H3. Internet addiction is positively associated with phubbing.
2. To test the fit of the model using structural equation modeling of the relationships
between phubbing, self-esteem, self-control, well-being, and Internet addiction.

THE PHUBBING PHENOMENON: A STUDY

ON ITALIAN EMERGING ADULTS

Method

Participants

The sample consist of 640 Italian emerging adults (526 females and 114 males),
ranging in age from 18 to 29 (M = 21.7, SD = 2.18).

Materials and Procedure

The study uses a cross-sectional design (Shaughnessy, Zechmeister, & Zeichmeister,

2014). The participants completed the informed consent procedure and an online
self-report questionnaire designed via Qualtrics software. The instrument was
distributed online mostly through social media (mainly Facebook) and via email
(voluntarily provided by the participants). The researcher has received approval
from the Ethics Committee of Alma Mater Studiorum – University of Bologna. The
questionnaire was prepared after careful evaluation of the existing instruments and
was conceived to take account of a broad range of variables.
The questionnaire includes items related to demographic characteristics such as
nationality, gender, age, type of occupation, and relationship status.

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Measures

The main criteria for the choice of the scales were their validity, brevity, and theoretical
background. All scales used were translated from English into Italian by the research
team, since the study was targeted at Italian university students. Back translations
were also performed to ensure the accuracy of the translation. A brief description
of the research project, its purposes, and the reasons for students to participate in
the study were presented at the beginning of the questionnaire. The questionnaire
also included questions about the number of hours per day they used the Internet (on
weekends and on weekdays), marital status, and the type of occupation. We decided
to distinguish weekdays (Monday to Friday) from weekends (Saturday and Sunday)
to verify whether there were differences between the days when people usually work
and/or study and leisure time, which is usually Saturdays and Sundays. Despite the
fact that the sample consisted of university students, the researchers decided to ask
the participants about their type of occupation, because many student work. Finally,
as affective relationships are very important during emerging adulthood (Arnett,
2015), we asked them about their marital status.
All the instruments used in this study were taken from the recent literature and
had already been validated in other contexts. To assess face validity and eliminate
the possible translation mistakes, the researchers had the survey examined by a small
convenience sample. The indications given were used in redacting the final version
of the survey. We tested the Cronbach’s α reliability of the scales used in this study
and found that they all had good reliability coefficients (α > .70).

Rosenberg Self Esteem Scale

Self-esteem was assessed by means of the Rosenberg Self-Esteem Scale (Rosenberg,
1965), adapted into Italian by Prezza, Trombaccia, and Armento (1997). Well-known
in literature, this instrument consists of 10 items rated on a 4-point Likert scale from
1 (strongly agree) to 4 (strongly disagree).

Brief Self-Control Scale (BSCS)

The Brief Self-Control Scale, developed by Tangey, Baumeister, and Boone (2004)
and re-validated by Maloney, Grawitch, and Barber (2012), is composed of 13 items
rated on a 5-point Likert scale from 1 (not at all like me) to 5 (very much like me).
The participants were asked to rate how well each item (e.g., “I am good at resisting
temptation”; “I have a hard time breaking bad habits”; and “I never allow myself
to lose control”) related to them.

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Flourishing Scale
The Flourishing Scale (Diener et al., 2009) consists of eight items rated on a 7-point
Likert scale from 1 (strongly disagree) to 7 (strongly agree). The items describe
important aspects of human functioning, ranging from positive relationships to
feelings of competence and having a sense of meaning and purpose in life. All
items are phrased positively (e.g. “I lead a purposeful and meaningful life”; “My
social relationships are supportive and rewarding”). The total score can range from
8 (strong disagreement with all items) to 56 (strong agreement with all items).

Internet Addiction Scale

The Internet Addiction Scale, developed by Karadağ et al. (2015), was used to
measure Internet addiction. It consists of six items (e.g., “The people around me
say that I spend too much time dealing with the Internet”; “I spend time using the
Internet more than I plan to”; “I can’t wait to use the Internet if I don’t have access
to the Internet for a long time”) rated on a 5-point Likert scale from 1 (never) to 5
(always).

Phubbing Scale
The Phubbing Scale was developed by Karadağ et al. (2015) and consists of 10 items
(e.g., “My eyes start wandering on my phone when I’m together with others”; “I am
always busy with my mobile phone when I’m with my friends”; “I feel incomplete
without my mobile phone”). The items were rated on a 5-point Likert scale from 1
(never) to 5 (always).

Results

Descriptive Analyses

Results show that most emerging adults report being in a relationship (n = 344,
53.8%), while 46.3% (n = 296) report being single. Regarding types of occupation
in the sample the vast majority of the participants were university students (n =
563, 88%); the second largest group were students who also worked during their
university years (n = 60, 9.4%). The smallest group were those who worked but
did not study (n = 5, 0.8%).
Turning on the time spent online on weekdays, the majority of emerging adults
reported spending up to ten hours online per day (71.5%), while the others admitted
to spending more than eleven hours online per day (28.5%). Finally, considering the
time spent online on weekdays, most of the participants (more than on weekdays)

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spent up to ten hours online (78%), while others admitted to spending more than
eleven hours online per day (22%).

The Relations Between the Variables

Analyzed, Gender, and Marital Status

The first purpose of the present study that was to investigate the correlations between
self-esteem, self-control, well-being, Internet addiction, and phubbing. Table 1 shows
the correlations among these variables.
It should be noted that there was a negative correlation between self-esteem, self-
control, well-being, and phubbing, as well as between these variables and Internet
addiction, which was positively associated with phubbing. Moreover, an interesting
result derives from a comparative analysis between females and males in terms of
all the variables discussed in the previous section (Table 2).

Table 1. Time spent online on weekdays

Variables M SD 1 2 3 4
1. Self-Esteem 29.3 6.73 (.90)
2. Self-Control 41.8 8.77 .34** (.82)
3. Well-Being 42.0 7.82 .66** .43** (.86)
4. Internet Addiction 2.22 0.68 -.22** -.36** -.27** (.71)
5. Phubbing 2.60 0.58 -.12** -.26** -.13** .59** (.74)
Note. ** p < .01 * p <.05 Cronbach’s alpha values are showed in brackets.

Table 2. ANOVA between variables and gender

Variables Females Males F p

28.9 31.2
Self-esteem 11.7 .00*
(6.82) (5.94)
41.9 41.3
Self-control .42 .52
(8.95) (7.93)
41.9 42.7
Well-being .95 .33
(8.03) (6.81)
2.23 2.13
Internet addiction 2.40 .12
(.69) (0.62)
2.59 2.48
Phubbing 3.54 .06
(.58) (.61)
Note. ** p < .01; * p < .05. Standard deviations are showed in brackets below the means.

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 Factors Related to Phone Snubbing Behavior in Emerging Adults

The results do not show differences between females and males, except for self-
esteem, on which males scored higher than females did. This result is not a novelty,
since it probably argues that the same difference normally found in adolescence
could continue into the early period of emerging adulthood (Quatman & Watson,
2001; Robins, Trzesniewski, Tracy, Gosling, & Potter, 2002; Orth, Trzesniewski,
& Robins, 2010).
Finally, Table 3 shows a comparative analysis performed to verify if there are
differences in the relations between the variables considered (self-esteem, self-
control, well-being, Internet addiction, and phubbing) depending on marital status.
The results show that the people who are in a relationship have significantly
higher self-esteem and well-being compared to those who are single. Self-control
is higher in those who are in a relationship, while Internet addiction is higher in
those who are single. Finally, phubbing is higher in those who are in a relationship
than in singles.

Model Test

The second purpose of this chapter was to test the model using structural equations
for interrelations between the variables. Using structural equation modeling, the
authors tested the theoretical model (Figure 2) of relations between self-esteem,
self-control, well-being, Internet addiction, and phubbing.
To test the structural equation model, we used IBM SPSS Amos 25. The values
of RMSEA should be lower than .08 to indicate that the model is well fitted, and
optimally they should be lower than .05 (Hooper, Coughlan, & Mullen, 2008). The

Table 3. ANOVA between variables and marital status

Marital Status
Variables In a Relationship / F p
Single
Engaged
28.2 30.2
Self-esteem 14 .00**
(6.76) (6.58)
41 42.5
Self-control 4.27 .04*
(8.51) (8.95)
40.4 43.4
Well-being 23.9 .00**
(7.95) (7.45)
2.28 2.16
Internet addiction 4.34 .04*
(0.71) (0.65)
2.52 2.62
Phubbing 5.13 .02*
(0.61) (0.56)
Note. ** p < .01; * p < .05. Standard deviations are showed in brackets below the means.

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Factors Related to Phone Snubbing Behavior in Emerging Adults

Figure 2. The model of relations between the variables: test results

Table 4. Regression weights of the tested model

Dependent Predictor Estimate SE p

Internet addiction Self-esteem -.004 .005 .384
Self-control -.023 .003 < .001
Well-being -.010 .004 .022
Phubbing Internet addiction .505 .027 < .001

comparative fit index (CFI) should be higher than .90 for an acceptable model and
equal to 1.0 for a perfect model (Hu & Bentler, 1998). The Tucker–Lewis Index
(TLI) should range from 0 to 1: the higher the value, the better the fit (Schermelleh-
Engel, Moosbrugger, & Muller, 2003). The goodness-of-fit indices demonstrated
that the model was very well fitted to our data: maximum likelihood χ2 = 6.44, df
= 3, χ2/df = 0.93, CFI = .97, TLI = .99, RMSEA = .04 [.01, .07].
As reported in Table 5, decreasing the level of self-control led to an increase
in Internet addiction, and an increase in Internet addiction led to an increase in
phubbing behavior, while the levels of self-esteem and well-being did not affect
Internet addiction.
Table 5 shows the covariances between the predictors, with an increase in self-
control, well-being, and self-esteem increasing the levels of both well-being and
self-control.

Table 5. Covariances between variables

Covariance Estimate SE p
Self-control Well-being 29.3 2.95 < .001
Well-being 34.4 2.49 < .001
Self-esteem
Self-control 19.8 2.46 < .001

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DISCUSSION

The main goal of this study was to identify the factors (and their relations) that
play a role in phubbing behavior during emerging adulthood. All the hypotheses
formulated were confirmed. The correlation analysis and the model test allowed the
researchers to gain a deeper understanding of the results obtained.
As regards the first hypothesis (H1. Self-esteem, self-control, and well-being
are negatively associated with phubbing), the results show that if an emerging adult
has low self-esteem, low self-control, and low well-being, he or she is more at risk
of manifesting phubbing behavior in a face-to-face situation. As regards the second
hypothesis (H2. Self-esteem, self-control, and well-being are negatively associated
with Internet addiction), the results show that if an emerging adult has low self-
esteem, low self-control, and low well-being, he or she is likely to exhibit Internet
addiction behaviors. These results are strictly linked to those concerning the third
hypothesis (H3. Internet addiction is positively associated with phubbing). The
results show that Internet addiction could lead to phubbing behavior. These patterns
are partially confirmed by the model test. Self-esteem and well-being were not good
predictors of Internet addiction. The only significant predictor was self-control: it
was related to Internet addiction, which in turn predicted phubbing behavior. This
means that emerging adults are more at risk of manifesting phubbing behavior if
they have a low level of self-control. One possible explanation of this can be found
in the uses and gratifications theory (Katz, Blumler, & Gurevitch 1973; Chen, 2011;
Han et al., 2015), and another explanation is provided by the optimal flow theory
(Salehan & Negahban, 2013). In the light of the former theory, emerging adults
feel excluded and they desire to feel included, which is why they look for attention
on the Internet and SNSs. In the light of the latter, their enjoyment derives from
SNS activity (or Internet use in general). This attitude leads to dopamine release
similar to the rush one might get from an in-person hug or smile (Soat, 2015). Thus,
emerging adults are pushed to use SNSs more intensively on order to satisfy the
need for attention and in order not to feel socially excluded, even when they are in
the presence of others – and this could be phubbing behavior. The most interesting
results of the comparative analysis is the higher score on phubbing in those who are
in a relationship compared to singles. A possible explanation lies in the fact that when
a couple spend time together both partners look at the smartphone, which represent
a barrier to meaningful communication, causing conflict, lowering relationship
satisfaction, and undermining individual well-being (Krasnova, Abramova, Notter,
& Baumann, 2016).
To the best of our knowledge, this study is the first to examine the determinants
of phubbing in the emerging adult population, but it has certain limitations. Firstly,
the design was cross-sectional and does not make it possible to draw conclusions

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about causality. A longitudinal study would afford a better insight into problematic
Facebook use and the development of phubbing. Secondly, the sample was not
homogeneous: it represented mostly university students. This could make the
findings difficult to generalize, but given that the researchers are referring to
emerging adults, this could also be a positive aspect, since university students
represent the group that Arnett and Schwab (2012) call younger emerging adults.
Finally, the data were collected online by means of a snowball procedure, which is
not free from bias (Tyrer & Heyman, 2016). Although we collected the data with
these disadvantages in mind, other research has shown that this procedure is valid
(Meyerson & Tryon, 2003) and yields reliable results (e.g., Blachnio, Przepiorka,
& Rudnicka, 2016). Despite these limitations, the present findings may have some
important implications for emerging adult research. Further research is required to
establish how mobile phone use and phubbing behavior may differ between women
and men in their emerging adulthood.
A significant proportion of emerging adults use SNSs via the mobile phone
in their everyday lives (Poushter, 2017). It is therefore increasingly important to
consider the impact that SNSs have on the quality of social life – especially on
phubbing behavior, of which still little is known. Moreover, based on the results
of the present study, further research could address other aspects of the phubbing
phenomenon, such as the difference between younger and older emerging adults
(Arnett & Schwab, 2012). Additionally, this study provides the groundwork for
researchers to investigate the effects of phubbing behavior on the quality of emerging
adults’ offline social interactions, especially the consequences that this behavior
has on romantic relationships.

SOLUTIONS AND RECOMMENDATIONS

The Internet has revolutionized our lifestyles. New generation devices such as
smartphones, mobile phones, and tablets allow users to be always connected; the
Web represents a significant part of their daily life. These epochal changes bring
with them questions about the potentialities and risks of the Web. As revealed by
the results of the present study, online environments such as SNSs bring together
known and unknown individuals in a networked web of communication that is
propelled by individual and group-based motivations. Research on SNSs suggests
that they can negatively influence human development (see Caplan, 2005; Davis,
2001; Young & Case, 2004), as illustrated by increased compulsive Internet use
tendency (i.e., Internet addiction). On the contrary, the study by Barker (2009) has

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found positive outcomes of SNS use, such as identification with like-minded others
and enhanced well-being in individuals with low self-esteem offline (Stern & Taylor,
2007; Valkenburg & Peter, 2007).
The consequences of Internet use (particularly SNS use) remains a popular
research topic. The motivations and predictors of specific types of SNS use require
further research that will clarify which types of behaviors users engage in on the
Internet. Specifically, emerging adults’ use of SNSs (and the reasons behind it) could
better explain phubbing behavior. By identifying the behaviors that predict Internet
(both problematic and functional) and SNS use, researchers could move the field
of psychology forward and test more coherent causal chains between predictors,
behaviors, and consequences of emerging adults’ computer engagement.

FUTURE RESEARCH DIRECTIONS

In future studies, researchers must clarify some of the concepts that have merely
been touched on in this study. They should further explore the issues suggested by
the theoretical perspectives and by the empirical results of the present study. To
better understand the phubbing phenomenon, future research could be conducted in
different cultural, social, and economic contexts to show how the variables considered
in this study (self-esteem, self-control, well-being, Internet addiction) influence
phubbing behavior in emerging adulthood. Moreover, gender, marital status, and
type of occupation have not been taken into consideration as moderating variables.
Further research could also explore how, and in what way(s), these variables could
influence phubbing. Finally, considering that most of the literature on Internet
addiction (including this study) is based on student samples, it would be important
to analyze the situation in different segments of the population, as the results could
differ significantly.

CONCLUSION

In summary, the aim of this study was to obtain a wide-ranging picture of how
phubbing is determined by a combination of different psychological variables during
emerging adulthood. The contribution of the presented research is twofold. Firstly,
it has identified the determinants of phubbing (self-esteem, self-control, and well-
being) through emerging adults’ Internet addiction behaviors. Secondly, the study
has more deeply explained the antecedents Internet use in a phubbing situation. More
precisely, we tested a model of relations between self-esteem, self-control, well-being,
Internet addiction, and phubbing. This model added a different point of view that

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has not been explained by the existing literature. The relations found while testing
the model might shed light on the new social phenomenon referred to as phubbing
and could inspire researchers conducting studies on emerging adults to consider
testing the differences in phubbing between younger and older emerging adults.

ACKNOWLEDGMENT

This research was supported by a grant no. 2017/26/M/HS6/00779 from the Polish
National Science Centre (NCN).

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ADDITIONAL READING

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KEY TERMS AND DEFINITIONS

Emerging Adulthood: A life stage (which depends on culture, social environment,

and the financial situation) characterized by exploration, instability, self-focus,
feeling in-between, and possibilities.
Internet Addiction: Behavior characterized by excessive use of the Internet that
leads to impairment or distress.
Offline Life: The set of actions a person performs and the set of relationships
he/she has when he/she is disconnected from the Internet.
Online Life: The set of actions a person performs and the set of relationships
he/she has when he/she is connected to the internet.
Phubbing: Behavior that consists in an individual looking at his or her smartphone
during a real-life conversation with other individuals, avoiding interpersonal
communication.
Self-Control: A measure of how effectively a person controls himself or herself
and his/her actions.
Self-Esteem: A measure of how popular and successful a person perceives
himself or herself to be in his/her social interactions.
Well-Being: A state characterized by health, happiness, and prosperity.

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