The Unfabulous Four: Maladaptive Personality Functioning, Insecure Attachment, Dissociative Experiences, and Problematic Internet Use Among Young Adults

Abstract

Even though positive associations among problematic Internet use (PIU), maladaptive personality traits, insecure attachment styles, and dissociation have been frequently observed in research, a need exists to examine the interrelationships among these factors in young adults. Two hundred fifty-three young adults (52% females) aged between 18 and 25 years old completed a sociodemographic form and measures on PIU, maladaptive personality traits, dissociative experiences, and adult attachment styles. They also reported how much time they usually spent online. A hierarchical multiple regression analysis showed that male gender, increased time spent online, negative affectivity, an avoidant attachment style, and dissociative symptoms of depersonalization/derealization were strongly associated with PIU scores in the sample. Our findings suggest that an excessive time spent online may combine with maladaptive personality features, insecure attachment dispositions, and difficulties in processing bodily experiences in generating PIU among young adults.
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ORIGINAL ARTICLE
The Unfabulous Four: Maladaptive Personality
Functioning, Insecure Attachment, Dissociative
Experiences, and Problematic Internet Use
Among Young Adults
Adriano Schimmenti
1
&Alessandro Musetti
2
&Antonino Costanzo
1
&Grazia Terrone
3
&
Noemi R. Maganuco
1
&Cosimo Aglieri Rinella
1
&Alessia M. Gervasi
4
#Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract
Even though positive associations among problematic Internet use (PIU), maladaptive person-
ality traits, insecure attachment styles, and dissociation have been frequently observed in
research, a need exists to examine the interrelationships among these factors in young adults.
Two hundred fifty-three young adults (52% females) aged between 18 and 25 years old
completed a sociodemographic form and measures on PIU, maladaptive personality traits,
dissociative experiences, and adult attachment styles. They also reported how much time they
usually spent online. A hierarchical multiple regression analysis showed that male gender,
increased time spent online, negative affectivity, an avoidant attachment style, and dissociative
symptoms of depersonalization/derealization were strongly associated with PIU scores in the
sample. Our findings suggest that an excessive time spent online may combine with maladap-
tive personality features, insecure attachment dispositions, and difficulties in processing bodily
experiences in generating PIU among young adults.
Keywords ProblematicInternetuse.Personality.Attachmentstyles.Dissociation.Yo u n g adu lts
In the last two decades, interest in the use and misuse of the Internet has dramatically increased
along with the development of the technology (Musetti et al. 2016a). Researchers and
https://doi.org/10.1007/s11469-019-00079-0
*Adriano Schimmenti
adriano.schimmenti@gmail.com; adriano.schimmenti@unikore.it
1
Faculty of Human and Social Sciences, UKE - Kore University of Enna, Enna, Italy
2
Department of Humanities, Social Sciences and Cultural Industries, University ofParma, Parma, Italy
3
Department of Humanities, Literature, Cultural Heritage, and Educational Sciences, University of
Foggia, Foggia, Italy
4
Department of Human Sciences, University of Verona, Verona, Italy
International Journal of Mental Health and Addiction (2021) 19:447–461
15Published online: 2019
April

clinicians have paid attention to factors that may contribute to problematic Internet use (PIU).
PIU can be defined as a difficulty with controlling one’s Internet use, which leads to negative
consequences in daily life (Spada 2014). In particular, excessive Internet use has been
frequently reported among adolescents and young adults (Huang 2006; Schimmenti et al.
2014; Shaw and Black 2008).
Different theoretical models exist to explain PIU. Among them, the conceptualization of
PIU as a behavioral addiction (Widyanto and Griffiths 2006;Young1998) is one of the most
recognized in the literature. According to this model, PIU is conceived in terms of an excessive
preoccupation with the Internet and its applications, which may also involve severe addictive
symptoms such as craving, tolerance, and withdrawal that may generate impairments and
distress in the personal, social, and professional lives of individuals. The conceptualization of
PIU as an addictive disorder is currently under debate because it is basically symptom-based
and does not provide information concerning the origins and processes that may foster PIU
(Kardefelt-Winther et al. 2017;MusettiandCorsano2018). However, significant evidence
about problematic Internet behaviors has been collected based on the addiction model of PIU
(Anand et al. 2018; Brand et al. 2014;Kussetal.2013).
According to the conceptualization of PIU as a behavioral addiction, it is possible to
hypothesize that excessive use of the Internet (i.e., an excessive amount of time spent on the
Internet) might represent a risk factor for the development of PIU. In fact, despite there being
no consensus on how much time should be spent on the Internet to display a PIU (Kuss et al.
2014), time spent online has been considered a principal predictor for the development of an
BInternet addiction disorder^(Young 1998) in many studies (e.g., Laconi et al. 2016; Muñoz-
Rivas et al. 2010;NalwaandAnand2003). Specifically, it has been suggested that the more
time one spends online, the higher the arousal when that person is connected. Subsequently,
the interest and arousal toward social stimuli are lowered, leading to altered health habits and
interference in the social, family, academic, or work domains (Muñoz-Rivas et al. 2010).
However, while time spent online may represent an important behavioral indicator of PIU,
for both clinical purposes and the development of preventative actions within the public health
system, it is critical to identify psychological factors that might lead to the onset and
maintenance of PIU. In this respect, understanding the role played by personality features,
mental functions, and relational factors may foster the identification of effective strategies with
which to reduce the impact of PIU on youths’lives. Consistent with the I-PACE (interaction of
person, affect, cognition and execution) model (Brand et al. 2016) of PIU, which postulates
close links between individual features and excessive online behaviors, PIU can represent a
maladaptive coping strategy (Kardefelt-Winther 2014) for young individuals who display
maladaptive personality traits, difficulties in integrating their internal experiences, and prob-
lems in close relationships.
In this respect, maladaptive personality traits have been extensively linked to PIU (for
reviews, see Gervasi et al. 2017a; Mitchell and Potenza 2014). There is evidence that
personality traits such as negative affectivity, impulsivity, and a tendency toward psychoticism
are strongly associated with maladaptive use of the Internet, especially among adolescents and
young adults (Billieux et al. 2011; Guglielmucci et al. 2017; Munno et al. 2017). In a recent
study, Gervasi et al. (2017b) purposed that the tendency to develop PIU symptoms among
young adults could be subtended by a core of internalizing symptoms or externalizing
symptoms. They studied the associations between PIU and the personality domains of negative
affectivity, detachment, antagonism, disinhibition, and psychoticism—that is, the domains
included in the alternative DSM-5 model for personality disorder (American Psychiatric
International Journal of Mental Health and Addiction (2021) 19:447–461
448

Association 2013). These personality domains constitute maladaptive variants of the five-
factor model of personality, which has been widely supported in personality research and
clinical literature (Widiger and Costa Jr 2012). Gervasi et al. (2017b) found that negative
affectivity, disinhibition, and psychoticism positively predicted PIU among young adults. They
discussed their findings by considering PIU as a strategy with which to escape from negative
emotions, satisfy urgency and impulsivity, and avoid disorganized states of mind emerging
into consciousness (Rosegrant 2012; Schimmenti and Caretti 2010).
The presence of maladaptive personality domains has been frequently linked to insecure
attachment styles (for reviews, see Debbané et al. 2016; Nazzaro et al. 2017). This is the case
of infant attachment, intended as the child’s style of relationships with parents (Jia and Jia
2016; Monacis et al. 2017), but this is also the case of adolescent and adult attachment in
relationships with peers and romantic partners (Schimmenti et al. 2014). Attachment is the
motivational system that promotes the search for safety in close and intimate relationships in
all life stages (Bifulco and Thomas 2012), and late adolescence and young adulthood are times
when relationships with peers are extremely important for the development of one’sidentity
(Arnett 2000; Corsano et al. 2017). An anxious attachment style in relationships with peers,
which makes individuals preoccupied about their ability to achieve safety and explore reality,
or an avoidant attachment style, which disengages individuals from searching for close
relationships, may affect one’s identity development and predispose a person to problematic
behaviors such as PIU during late adolescence and young adulthood (Schimmenti et al. 2014).
In fact, insecure attachment styles have been associated with symptoms of Internet addiction
(Eichenberg et al. 2017; Monacis et al. 2017; Schimmenti et al. 2012,2014;Şenormancıet al.
2014) and with addictive behaviors more generally (Musetti et al. 2016b; Schindler and
Bröning 2015). For example, Schimmenti et al. (2014) found that late adolescents with
insecure attachment attitudes were more likely to become problematic Internet users.
Beside the anxious and avoidant attachment styles, disorganized attachment (a condition in
which the individual displays highly inconsistent and conflictual mental states with respect to
attachment behavior, as he or she did not develop coherent strategies, whether secure or
insecure, to relate with significant others) has been established as one of the strongest
predictors for the onset of psychiatric symptoms and addictive behaviors in later life
(Schindler and Bröning 2015). This consideration fits well with the positive associations
found in the literature between psychoticism and PIU (Gervasi et al. 2017b) and, more
generally, with empirical data and clinical observations supporting the association between
disorganized mental states and PIU (Schimmenti et al. 2012,2017b). Also, the positive
relationship between PIU and a lack of integration in mental states is consistent with the
widely demonstrated relationship between PIU and dissociative symptoms, such as amnesia,
depersonalization/derealization, and extreme absorption (Bernardi and Pallanti 2009;
Dalbudak et al. 2014; Musetti et al. 2018; Schimmenti and Caretti 2017;Schimmentietal.
2012). Dissociation represents a mechanism by which individuals temporarily protect the mind
from experiences that overwhelm their capacity for cognitive processing, through a passive
disengagement from reality and a compartmentalization of behaviors, thoughts, memories, and
feelings. However, when dissociation is overly activated and relied upon as an individual’s
primary response to distressful experiences, it may hinder one’s capacity for mental integration
of experiences and may foster psychopathology (Schimmenti 2018). Accordingly, Bernardi
and Pallanti (2009) found a positive and strong association between PIU and dissociative
symptoms in a group of psychiatric outpatients.Furthermore, Schimmenti et al. (2012)showed
that dissociation mediated the relationship between disorganized attachment and PIU in a
International Journal of Mental Health and Addiction (2021) 19:447–461 449

sample of online gamers with high levels of Internet addiction symptoms. Moreover,
Schimmenti and Caretti (2017) proposed that an extreme syndrome defined as video-
terminal dissociative trance (VDT) may result from overtly excessive Internet use. The VDT
contemplates an alteration of the states of consciousness, identity, memory, self-awareness, and
self-integrity, in which the personal sense of identity flows into a virtual identity to escape from
traumatic memories. The authors also provided anecdotal evidence for this extreme condition
of PIU among young adults, thus suggesting that dissociative symptoms may be relevant for
understanding PIU.
Therefore, both theoretical considerations and empirical findings support the view that
maladaptive personality features, insecure attachment styles, and dissociative features may add
to the excessive time spent online and may foster PIU. Accordingly, in the current study, we
sought to investigate the role of these psychological factors in influencing PIU scores among
young adults. To the best of our knowledge, this is the first time that all these factors have been
studied together in relation to PIU. This is surprising, as this kind of study may help to
disentangle the specific contributions of each of these variables in the development of PIU. In
detail, we studied whether hours per day spent online, maladaptive personality traits, attach-
ment styles, and dissociative symptoms influenced PIU scores in young adults. On the basis of
previous findings, we hypothesized that the maladaptive personality domains of negative
affectivity, disinhibition and psychoticism, the insecure attachment styles, and the dissociative
symptoms would have influenced PIU scores in our sample.
Method
Participants
The study involved 253 Italian young adults (121 males, 47.7%; 132 females, 52.3%) aged
from 18 to 25 years (M= 21.38 years, SD = 2.56) recruited through public and electronic
advertisements (flyers in public places and posts in social network pages) directed to young
adults living in the city of Enna, Italy.
Procedures
Ethical clearance was obtained by the Internal Review Board for Psychological Research
of the UKE-Kore University of Enna. The inclusion criteria were being in the emerging-
adulthood life stage (i.e., between 18 and 25 years old) and not reporting the use of
psychotropic medications. Participants who contacted the research office were asked for
their availability to complete (online or in person) a series of measures on Internet use and
personality. All of the participants gave their informed consent and completed an anony-
mous module with sociodemographic information (age, gender, and years of education),
the amount of hours per day they were connected to the Internet, and self-reported
questionnaires on PIU, maladaptive personality domains, attachment styles, and dissocia-
tive symptoms. Of the 270 persons who contacted the research office, 10 (3.70%) did not
meet the inclusion criteria, and seven (2.59%) did not entirely and correctly complete the
measures used in the present study. The study was carried out according to the Ethical
Code of the Italian Association of Psychology (AIP) and the American Psychological
Association (APA).
International Journal of Mental Health and Addiction (2021) 19:447–461
450

Measures
Problematic Internet Use The Italian version of the Internet Addiction Test (IAT; Young
1998; Italian adaptation by Ferraro et al. 2006) is a 20-item self-reported questionnaire that
quantifies excessive Internet use. Items are rated on a 5-point Likert scale ranging from 1
(never)to5(always). Total scores can range from 20 to 100. A cutoff value of 50 or above is
often used to identify people with PIU in international and Italian research (Young 1998;
Schimmenti et al. 2014,2018). The IAT includes questions such as BHow often do you fear
that life without the Internet would be boring, empty, and joyless?^Cronbach’s alpha of the
IAT was .93 in this study.
Personality Domains The Italian version of the Personality Inventory for DSM-5—Brief
Form—Adult (PID-5-BF; Krueger et al. 2012; Italian adaptation by Fossati et al. 2013)was
administered to the participants to assess their personality. The PID-5-BF is a 25-item self-
reported questionnaire assessing five maladaptive personality domains (negative affectivity,
detachment, antagonism, disinhibition, and psychoticism) according to the alternative DSM-5
model for personality disorders (American Psychiatric Association 2013). An example item is
BI worry about almost everything^(related to the domain of negative affectivity). Items are
rated on a 4-point Likert scale ranging from 0 (very false or often false)to3(very true or often
true). The maximum score for each domain is 15, while the maximum overall reachable score
is 75 points, and the higher the score, the more dysfunctional the individual’s personality is.
The Cronbach’s alpha for the PID-5-BF total score in this study was .89, while the Cronbach’s
alpha for the singular traits ranged from .67 (negative affectivity) to .77 (psychoticism).
Attachment Styles The Italian translation of the Relationship Questionnaire (RQ;
Bartholomew and Horowitz 1991; Italian adaptation by Carli 1995) was used to assess
attachment styles. The RQ is a four-sentence self-report measure that describes four prototyp-
ical attachment attitudes: secure (which entails a positive view of self and a positive view of
others), dismissing (which entails a positive view of self but a negative view of others),
preoccupied (which entails a positive view of others but a negative view of self), and fearful
(which entails a negative view of both self and others). An example of the RQ statements is the
following: BI am comfortable without close emotional relationships. It is very important to me
to feel independent and self-sufficient, and I prefer not to depend on others or have others
depend on me^(which refers to dismissive attitudes in close relationships). The participants
were required to indicate how much they agreed or disagreed with each of the sentences using
a 7-point Likert scale. Following the predetermined criteria for calculating scores on the two
principal domains (anxiety and avoidance) of insecure attachment styles (Bartholomew and
Horowitz 1991), we used the scores on the four attitudes to calculate the final scores for
attachment anxiety ((fearful + preoccupied) −(secure + dismissing)) and attachment avoidance
((fearful + dismissing) −(secure + preoccupied)).
Dissociation The Italian translation of the Dissociative Experiences Scale-II (DES-II; Carlson
and Putnam 1993; Italian adaptation by Schimmenti 2016) was used to assess dissociation.
The DES-II is a 28-item self-reported questionnaire that measures dissociative experiences.
Each item rates the percentages of time that individuals experience symptoms. An example
item is BSome people have the experience of feeling that their body does not seem to belong to
them. Circle the number to show what percentage of the time this happens to you.^The total
International Journal of Mental Health and Addiction (2021) 19:447–461 451

score is obtained by summing the percentages of the 28 item scores and dividing that total by
28. The Cronbach’s alpha of the scale was .95.
Considering the original three-factor model of dissociative symptoms identified by Carlson
and colleagues (Carlson et al. 1991), we calculated and considered the three symptoms
subscales: amnesia (alpha = .83), depersonalization/derealization (alpha = .87), and absorption
(alpha = .86).
Statistical Analyses
Descriptive statistics were calculated for all of the variables examined in the current study.
Partial correlations were examined to look at the associations between the investigated vari-
ables, controlling for sociodemographic factors (gender, age, andyears of education). Finally, a
hierarchical regression analysis with IAT scores as the dependent variable was performed,
including sociodemographic variables (step 1), time spent online (step 2), PID-5-BF domain
scores (step 3), attachment anxiety and avoidance scores (step 4), and dissociative symptom
scores (step 5) as predictors. A level of p< .05 was set as the level for statistical significance.
Results
Descriptive statistics are reported in Table 1for all the observed variables in the current study.
As expected for a youth sample from the normal population, the mean scores of the investi-
gated measures were in the normal range, and most of the participants did not report prominent
symptoms of PIU.
Partial correlations between the investigated constructs were examined, controlling for
sociodemographic variables (see Table 2). As it is seen in Table 2, PIU scores were positively
and significantly associated with time spent online and with all of the investigated psycholog-
ical variables.
Table 1 Descriptive statistics
MSD Observed range Skewness Kurtosis
Age 21.43 2.55 18–25 −0.02 −1.46
Years of education 12.36 2.77 5–18 −0.51 −0.59
Internet Addiction Test 39.68 13.71 20–81 1.01 0.32
Hours per day spent online 2.41 1.80 0–13 2.08 6.62
PID-5-BF
Negative affectivity 6.30 2.99 0–13 0.45 −0.73
Detachment 3.91 2.85 0–13 0.94 0.50
Antagonism 3.63 3.04 0–14 0.90 0.39
Disinhibition 5.46 3.25 0–14 0.37 −0.42
Psychoticism 4.39 3.44 0–15 0.69 −0.37
Relationship questionnaire
Anxious style −3.40 4.20 −12–9 0.65 −0.33
Avoidant style −0.33 3.91 −9–10 0.15 −0.72
DES-II scales
Amnesia 11.42 12.28 0–57.14 1.51 1.82
Depersonalization/derealization 11.30 15.29 0–63.33 1.72 2.27
Absorption 29.74 19.94 0–100 1.13 1.25
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452

Table 2 Partial correlations between the study variables (controlling for gender, age, and years of education)
Hours per day
spent online
Negative
affectivity
Detachment Antagonism Disinhibition Psychoticism Anxious
attachment
Avoidant
attachment
Amnesia Depersonalization Absorption
IAT .414*** .411*** .367*** .302*** .351*** .428*** .320*** .212** .369*** .398*** .261***
Hours per day
spent online
–.257*** .288*** .317*** .294*** .297*** .257*** −.013 .235*** .181** .066
Negative
affectivity
–.423*** .431*** .403*** .463*** .293*** .105 .334*** .346*** .295***
Detachment –.430*** .473*** .558*** .298*** .337*** .337*** .304*** .206**
Antagonism –.496*** .492*** .117 −.016 .361*** .345*** .242***
Disinhibition –.484*** .169** .084 .407*** .374*** .302***
Psy –.275*** .255*** .509*** .533*** .432***
Anxious
attachment
–.119 .289*** .251*** .247***
Avoidant
attachment
–.125* .117 .095
Amnesia –.797*** .716***
Depersonalization –.685***
Absorption –
*p<.05;**p<.01; ***p<.001
International Journal of Mental Health and Addiction (2021) 19:447–461 453

A hierarchical linear regression analysis was performed to examine the predictive associ-
ations of hours per day spent online, maladaptive personality domains, attachment styles, and
dissociative symptoms on the dependent variable PIU (IAT scores). Five steps were entered in
the following order. Step 1 was entered with sociodemographic variables (gender, age, and
years of education). Step 2 was entered with number of hours spent on the Internet by
participants. Step 3 was entered with PID-5-BF scores on personality domains (negative
affectivity, detachment, antagonism, disinhibition, and psychoticism). Step 4 was entered with
RQ anxious style and avoidant style scores. Finally, step 5 was entered with the scores on the
three subscales of the DES-II (amnesia, depersonalization/derealization, and absorption). The
results of the hierarchical regression analysis are reported in Table 3.
The hierarchical regression analysis revealed that male gender (male coded as 1; female
coded as 2) was a strong predictor for PIU in all steps, while age and years ofeducation did not
predict PIU. However, the model including only the sociodemographic factors as statistical
predictors explained only 5% of variance in the PIU scores. As expected, the hours per day a
person remained connected to the Internet was also a strong predictor of PIU scores, and the
inclusion of time spent online among the predictors in step 2 increased the explained variance
of PIU scores from 5% to 21%. Regarding the psychological factors, the only maladaptive
domains that predicted PIU in step 3 were negative affectivity and psychoticism. However,
negative affectivity continued to predict PIU in each step; psychoticism predicted PIU until
step 4 but did not predict PIU in step 5, when dissociative experiences were entered as
predictors. This might suggest an overlapping of psychoticism and dissociative symptoms, a
hypothesis already suggested in the literature on PIU predictors. Interestingly, both attachment
anxiety and attachment avoidance predicted PIU when entered in step 4, but only the avoidant
style continued to predict PIU when dissociative symptoms were entered in step 5. In fact, in
step 5, which included all of the investigated variables, the depersonalization/derealization
symptoms of dissociation positively and significantly predicted PIU, together with male
gender, hours per day spent online, negative affectivity, and avoidant attachment. This final
model explained 41% of variance in the PIU scores.
Discussion
We investigated the relationship among PIU scores, hours per day spent on the Internet,
maladaptive personality traits, insecure attachment, and dissociation in young adults, control-
ling for gender, age, and education. As we expected, partial correlation analyses showed that
PIU scores were significantly and positively associated with the other investigated variables.
Furthermore, the results of the study showed a significant association between male gender
and PIU scores. The fact that being male seemed to predispose individuals to PIU in our
sample is consistent with the existing literature (Bakken et al. 2009;Hoetal.2014;Kormas
et al. 2011). Notably, it has been previously reported that males may use the Internet more than
females, especially for leisure activities (e.g., gaming but also pornography and gambling; see
Beutel et al. 2011;Weiser2000). In turn, Internet use for leisure activities has been more
consistently associated with PIU than its use for other activities, such as work (Yee 2006).
Another variable that positively influenced PIU scores in our sample was increased time
spent online. This finding seems to be in line with the model conceptualizing PIU as a
behavioral addiction (Young 1998). In our study, the more time spent online, the more
problematic the relationship with the Internet was for our participants, similarly to what
International Journal of Mental Health and Addiction (2021) 19:447–461
454

happens with higher amounts of substance use in substance abusers. Indeed, in the current
study, the variable of hours per day spent online was positively and significantly associated
with PIU scores, independently from other variables. This may suggest that an excessive
Internet use may predispose an individual to PIU beyond the personality profile, attachment
Table 3 Hierarchical regression model for problematic Internet use (IAT) scores
R2R2BLower bound Upper bound β
Step 1 .05** .05
Gender −5.26 −8.63 −1.90 −0.19**
Age −0.41 −1.24 0.42 −0.08
Years of education −0.14 −0.90 0.62 −0.03
Step 2 .16*** .21
Gender −4.80 −7.87 −1.73 −0.17**
Age −0.14 −0.90 0.62 −0.03
Years of education −0.09 −0.78 0.60 −0.02
Hours per day spent online 3.12 2.26 3.97 0.41***
Step 3 .14*** .36
Gender −6.05 −9.01 −3.09 −0.22***
Age −0.28 −0.98 0.41 −0.05
Years of education 0.15 −0.49 0.79 0.03
Hours per day spent online 2.05 1.20 2.89 0.27***
Negative affectivity 0.93 0.36 1.50 0.20**
Detachment 0.35 −0.28 0.98 0.07
Antagonism −0.17 −0.75 0.41 −0.04
Disinhibition 0.33 −0.21 0.88 0.08
Psychoticism 0.75 0.21 1.29 0.19**
Step 4 .03** .38
Gender −5.67 −8.59 −2.75 −0.21***
Age −0.39 −1.07 0.30 −0.07
Years of education 0.19 −0.44 0.82 0.04
Hours per day spent online 1.98 1.13 2.83 0.26***
Negative affectivity 0.83 0.26 1.40 0.18**
Detachment 0.01 −0.64 0.67 0.00
Antagonism 0.04 −0.55 0.62 0.01
Disinhibition 0.38 −0.16 0.92 0.09
Psychoticism 0.58 0.03 1.12 0.14*
Anxious attachment 0.40 0.04 0.75 0.12*
Avoidant attachment 0.46 0.08 0.85 0.13*
Step 5 .02* .41
Gender −5.55 −8.47 −2.64 −0.20***
Age −0.41 −1.09 0.27 −0.08
Years of education 0.27 −0.36 0.90 0.05
Hours per day spent online 1.99 1.14 2.85 0.26***
Negative affectivity 0.77 0.21 1.34 0.17**
Detachment 0.07 −0.58 0.72 0.01
Antagonism −0.02 −0.60 0.56 −0.00
Disinhibition 0.29 −0.25 0.83 0.07
Psychoticism 0.29 −0.28 0.87 0.07
Anxious attachment 0.35 −0.01 0.70 0.11
Avoidant attachment 0.46 0.08 0.84 0.13*
Amnesia −0.01 −0.22 0.19 −0.01
Depersonalization/derealization 0.19 0.03 0.35 0.21*
Absorption −0.03 −0.13 0.08 −0.04
Lower bound and upper bound identify the 95% confidence interval for Bcoefficients
*p<.05;**p< .01; ***p<.001
International Journal of Mental Health and Addiction (2021) 19:447–461 455

styles, and dissociative symptoms. However, it is also possible that increased time spent online
is a consequence, rather than a cause, of the development of PIU, or that excessive time spent
online is actually just an epiphenomenon of the psychological problems related to maladaptive
personality domains, insecure attachment, and dissociation. Future research is needed to
examine the direction of this relationship.
Regarding personality features, negative affectivity was positively associated with PIU, as
expected. Internalizing personality patterns have been frequently associated with maladaptive
Internet use (see Carli et al. 2013, for a review). Moreover, the interpretation that negative
affectivity could lead young adults to search for a way to escape from negative emotions
through salient Internet stimulation has received some support in the relevant literature (Kim
et al. 2017), with experimental studies supporting positive associations between exposure to
negative stimuli and PIU (Schimmenti et al. 2018). As for time spent online, negative
affectivity influenced PIU scores independently from attachment styles and dissociative
symptoms, suggesting that internalizing tendencies may predispose one to PIU beyond
insecure attachment, even in the absence of dissociation. One possible interpretation of our
results is that low self-esteem and negative emotions, indicators of negative affectivity, could
increase the amount of time spent online. Moreover, despite the specific mechanisms behind
the strong relationship between negative affectivity and PIU being clear (Boonvisudhi and
Kuladee 2017), some studies underline that a dysfunction of the serotoninergic system may
subtend both conditions (Lee et al. 2008; Wrase et al. 2006). Indeed, our results suggest that
internalizing tendencies and PIU could be interrelated independently of other variables,
supporting the hypothesis of a common neurobiological basis for PIU. We did not find
evidence that detachment, disinhibition, or antagonism influenced PIU scores, suggesting that
these maladaptive personality domains may be linked to some profiles of problematic Internet
users, but they may be not globally involved in PIU (Gervasi et al. 2017a; Guglielmucci et al.
2017). In this context, a result that particularly contrasted our expectations was that the
disinhibition domain of personality did not influence PIU scores. This result is in contrast
with literature showing positive links among PIU, low self-control, and high impulsivity
(Billieux et al. 2015; Gentile 2011; Gervasi et al. 2017b). A possible explanation of this
finding is that excessive Internet use in our sample of normal youth could be linked to
problems concerning tolerance of negative affect, typical of the adolescent and young adult
life stages, rather than to excessively inhibited or disinhibited arousal (Armstrong et al. 2000).
Regarding psychoticism, we found that it was positively associated with PIU in step 3
of the regression analysis. However, when the dissociative symptoms were included in the
final model, the dissociative domain of depersonalization/derealization influenced PIU
scores, and psychoticism was excluded from the significant predictors of the model. This
is in agreement with literature suggesting similarities between psychotic symptoms and
dissociative symptoms in PIU (Schimmenti et al. 2012,2017a)aswellasastrong
relationship between dissociation and PIU (Bernardi and Pallanti 2009;Dalbudaketal.
2014; Schimmenti and Caretti 2017). This finding is also in line with psychodynamic
models, suggesting that the Internet may be used as a psychic retreat to prevent over-
whelming affect from emerging into consciousness (Schimmenti and Caretti 2010;
Schimmenti et al. 2017b). However, our results add that psychoticism alone, without
dissociative manifestations, might not be sufficient for the development of PIU. Indeed,
the literature has identified psychoticism as a possible risk factor for PIU (Dong et al.
2011;Schimmentietal.2017a; Xiuqin et al. 2010)butnotasakeyfactorasdissociation
(Bernardi and Pallanti 2009).
International Journal of Mental Health and Addiction (2021) 19:447–461
456

Among the dissociative domains, only depersonalization/derealization was found to be
strongly and positively associated with PIU (Beutel et al. 2011; Recupero 2010) and not
amnesia or absorption. This may suggest that PIU is linked with a specific difficulty in
processing and integrating bodily experiences, as previously proposed in clinical literature
(Schimmenti and Caretti 2017) and recently supported by neurobiological evidence from
patients seeking psychological treatment for PIU. In this respect, Lai et al. (2017)reported
in a recent study that a group of people undergoing psychological treatment for Internet
addiction showed higher activation of primary somatosensory cortex and lower activation of
paralimbic system, temporal, and orbito-frontal cortex in response to Internet images compared
to a control group, which suggests that people with PIU may process bodily experiences
differently when they perceive Internet-related stimuli.
The association between depersonalization/derealization and PIU also fits well with the
influence of avoidant attachment style on PIU scores that was evidenced in step 4 of the
hierarchical regression analysis. An avoidant attachment style is characterized by a negative
view of other people and predisposes one to sensation-seeking behaviors and to the tendency
to formulate choices independently from other people (Monacis et al. 2017). Moreover, it
could be underpinned by a fragmented and loosely integrated identity structure. In support, in a
recent study, Schimmenti et al. (2017a) found that schizotypal personality traits decreased
when participants thought about themselves in the virtual world, suggesting that a tendency to
detach from attachment relationships may be compensated for in the Internet.
As with all research, this study comes with many limitations. First, our sample was not overly
large and included only young adult volunteers from the normal population, so the results of this
study are not immediately generalizable to other people in this life stage. Studies with clinical
samples are greatly needed to extend our findings and provide more definitive significance for public
health. Second, the data were entirely collected by self-reported measures, so the accuracy of
individual reports cannot be guaranteed, although the measures used in the present study are widely
applied in research and have consistently demonstrated adequate psychometric properties. However,
a multimethod assessment is warranted for future research. Third, the cross-sectional nature of the
study makes it difficult to definitively establish causal links and does not allow us to exclude the
possibility that our findings were affected by other variables not explored here (e.g., problems with
affect regulation, psychiatric symptoms, or current social support). Thus, longitudinal studies with
clinical and nonclinical samples of young adults are greatly needed to clarify our findings on the
relationships among personality domains, adult attachment styles, dissociative symptoms, and PIU
during young adulthood.
Conclusions
In conclusion, we found that male gender, time spent online, negative affectivity, an avoidant
attachment style, and dissociative symptoms of depersonalization/derealization were associated with
increased PIU scores in young adults. This suggests that problematic Internet use cannot be defined
exclusively in terms of an addictive behavior and that, at least in young adult males, addictive
tendencies (excessive time spent online) may combine with personality features (negative affectiv-
ity), relational factors (avoidance in close relationships), and difficulties in processing bodily feelings
(depersonalization/derealization symptoms) in generating dysfunctional Internet use. This might
have relevant implications for informing the prevention of PIU and treatment of young adults who
are overinvolved with the Internet. Prevention and tailored intervention actions should help these
International Journal of Mental Health and Addiction (2021) 19:447–461 457

individuals to face preexisting maladjustment or psychopathology, rather than limiting treatments to
the problematic use of the Internet per se. In fact, the present findings suggest that it could be useful
to assess the influences of negative affectivity, depersonalization features, and avoidance in close
relationships in young adults who display significant symptoms of PIU and to eventually treat these
problems. This could help these individuals to better understand the origin of their symptoms and to
learn how to cope with their psychological difficulties, which might reduce their risk of compul-
sively using the Internet as a dysfunctional strategy with which to escape from their internal and
relational problems.
Compliance with Ethical Standards
Ethical clearance was obtained by the Internal Review Board for Psychological Research of the UKE-Kore
University of Enna. The study was carried out according to the Ethical Code of the Italian Association of
Psychology (AIP) and the American Psychological Association (APA).
Conflict of Interest The authors declare that they have no conflict of interest.
Informed Consent All procedures followed in this study were in accordance with the ethical standards of the
responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration
of 1975, as revised in 2000. Informed consent was obtained from all participants for being included in the study.
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