Clinical and Personality Correlates of MMO Gaming: Anxiety and Absorption in Problematic Internet Use
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Article
Social Science Computer Review
31(4) 424-436
ª The Author(s) 2013
Clinical and Personality Reprints and permission:
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Correlates of MMO Gaming: DOI: 10.1177/0894439312475280
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Anxiety and Absorption in
Problematic Internet Use
Sadie H. Cole1 and Jill M. Hooley1
Abstract
Massively-multiplayer online games (MMOs) are increasingly popular worldwide. MMO gaming can result
in problematic Internet use (PIU; or Internet addiction), which is characterized by dysfunction in areas
such as work or relationships. Because PIU in online gaming is increasingly seen in clinical populations, we
explored PIU in the context of MMO gaming. Using a cross-sectional design, we sought to identify clinical
and personality factors, as well as motivations for gaming, that differentiated between people who scored
high or low on a measure of problematic Internet use. Subjects completed all study procedures via an
online survey. Participants were 163 MMO users recruited from the community, from gaming websites,
and from online forums. Subjects completed a series of demographic, mood, anxiety, and personality
questionnaires. The study found that individuals in the high PIU group (n ¼ 79) were more likely to have
higher levels of social phobia (p ¼ .000), state (p ¼ .000) and trait (p ¼ .000) anxiety, introversion
(p ¼ .000), neuroticism (p ¼ .000) and absorption (p ¼ .019) than individuals in the low-PIU group
(n ¼ 84). Different reasons for gaming also characterized the group with more problematic Internet use.
Our findings provide support for the idea that high anxiety and absorption may be risk factors for
problematic Internet use within the MMO gaming environment and suggest that gamers who endorse
problematic Internet use identify different motivations for online gaming than gamers who do not.
Keywords
Internet addiction, anxiety, personality, online gaming
Introduction
Background
One area of Internet use that is growing in popularity involves massively multiplayer online games
(MMOs). Although such games provide entertainment for many people, there is evidence that MMO
gaming can lead to problematic Internet use (PIU; Morrison & Gore, 2010), also referred to as
1
Harvard University, Cambridge, MA, USA
Corresponding Author:
Sadie H. Cole, William James Hall 1254, Harvard University, 33 Kirkland Street, Cambridge, MA 02138, USA.
Email: scole@fas.harvard.edu
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Internet addiction, and cause significant problems in functioning (Hsu, Wen, & Wu, 2009; Lo, Wang,
& Fang, 2005; Mitchell, Becker-Blease, & Finkelhor, 2005; Young, 2009). Addicted online gamers
likely represent a very small proportion of the online gaming community (van Rooij, Schoenmakers,
Vermulst, van den Eijnden, & van de Mheen, 2010). Nonetheless, identifying individuals who are at
risk of addiction in this particular context is clinically important for focusing prevention and treatment
efforts. Smyth (2007) noted that MMO players reported worse health, worse sleep quality, and worse
interference in socializing after 1 month compared to those who played arcade, console, or solo com-
puter games. Messias, Castro, Saini, Usman, and Peeples (2011) reported a link between Internet use/
video games and suicidal ideation and planning in adolescents. These findings raise questions about
the factors that place people at risk of Internet addiction in online gaming.
It bears mention that the concept of ‘‘Internet addiction’’ is evolving, given the ubiquity of the Inter-
net in modern life. The Diagnostic and Statistical Manuel of Mental Disorders-5 (DSM-5) work group
(American Psychiatric Association, www.dsm5.org, accessed October 21, 2012) has proposed ‘‘Inter-
net Usage Disorder’’ as a nonsubstance-related addiction for Section III (Disorders Requiring Further
Study). Interestingly, the criteria for the proposed disorder specify ‘‘preoccupation with Internet gam-
ing’’ and fail to address other types of Internet use. This highlights the fact that Internet gaming has
been the focus of much Internet addiction research, but the term Internet addiction implies a broader
application than Internet gaming alone. There has been a proliferation of studies examining ‘‘Internet
addiction,’’ ‘‘compulsive Internet use,’’ ‘‘Internet addiction disorder,’’ and so on (e.g., King,
Delfabbro, Griffiths, & Gradisar, 2011; Ko et al., 2009; Lee et al., 2012; Lin et al., 2012; van Rooij,
Schoenmakers, van de Eijnden, & van de Mheen, 2010; van Rooij, Schoenmakers, Vermulst, et al.,
2010), which use a variety of measures (e.g., Young’s Internet Addiction Test [Young, 1998]) to assess
Internet use. Many of these studies focus on online gaming, based on the fact that problems with Inter-
net use are often associated with gaming (e.g., van Rooij, Schoenmakers, van de Eijnden, et al., 2010),
although other types of Internet use may also result in excessive use. The focus of these Internet addic-
tion studies ranges from prevalence (van Rooij, Schoenmakers, Vermulst, et al., 2010) to pathology
(e.g., Ko et al., 2009; Lin et al., 2012; Pawlikowski & Brand, 2011), to pharmacological intervention
(e.g., with a Selective Serotonin Reuptake Inhibitor [SSRI]-antipsychotic combination, Atmaca, 2007;
with escitalopram, Del’Osso et al., 2008; and with bupropion, Han, Hwang, & Renshaw, 2010). Fur-
ther study is needed to determine whether and how different types of excessive Internet use manifest,
which is beyond the scope of this article. However, an important theoretical distinction can be made
between specific and generalized PIU (Davis, 2001), where specific PIU consists of activities that,
absent the Internet, would manifest in other ways (e.g., gambling, which can be conducted offline) and
generalized PIU is characterized by dependence on the unique social context of the Internet. In this
way, it is possible to think of generalized PIU as separate from but related to gaming addiction. Gam-
ing addiction could develop absent the Internet, but online gaming addiction would be one outcome for
generalized PIU. In other words, one might consider gaming addiction as separate from generalized
PIU that manifests in the context of online gaming. This will be discussed in more detail below.
The distinction between specific and generalized PIU relates directly to the study of MMOs.
Unlike some forms of Internet use such as online gambling, which are often conducted in relative
social isolation (Griffiths, 2003; Griffiths, Wardle, Orford, Sproston, & Erens, 2011), MMOs rely
on interpersonal relationships between players (Caplan, Williams, & Yee, 2009). In the popular
game World of Warcraft, users, through their online avatars, can develop cooperative ‘‘guilds’’ and
work together toward common goals. Real-time communication often occurs during game play, and
online and offline relationships develop between players. This is important because one view of PIU
is that the social potential of the Internet contributes to the development of excessive use (e.g.,
Caplan, 2002). The idea that there is a close relationship between socializing and Internet use has
been proposed by several Internet addiction researchers. Davis’s (2001) cognitive behavioral model
of PIU predicts that individuals who have problems with real-life interpersonal skills and
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relationships will be more likely to develop PIU. Caplan (2002, 2005) has also suggested that indi-
viduals who lack self-presentation skills are likely to prefer online interactions to face-to-face com-
munication, which fosters excessive Internet use. In support of this idea, Caplan (2003) has reported
that preference for online social interaction, lack of self-presentational skill, and compulsive Internet
use together accounted for 10% of the variance in negative outcomes resulting from Internet use.
A unique function of Internet communication in gaming is that it allows users to fulfill a need for
belonging (Baumeister & Leary, 1995) without risking face-to-face, real-life ridicule or rejection. It is
therefore likely that certain psychological traits, such as deficient social skills, might predispose
individuals to PIU. Existing psychopathology may also contribute to excessive Internet use. Past
research has found a direct correlation between social anxiety and time spent playing online games
(Lo et al., 2005) as well as an association between impulse-control problems and PIU (Cao, Su, Liu,
& Gao, 2007). Recent work further highlights the importance of deficient psychosocial functioning in
PIU. In a study of Dutch adolescents, low social competence, low self-esteem, and loneliness were all
predictors of pathological gaming (Lemmens, Valkenburg, & Peter, 2011). Use of the Internet for
gaming was also correlated with lower perceived social support in college students (Mitchell, Lebow,
Uribe, Grathouse, & Shoger, 2011). Moreover, after controlling for depression and generalized anxi-
ety, Lee and Stapinski (2011) found that social anxiety was still a significant predictor of PIU.
Taken together, the literature to date suggests that an MMO environment that requires people to
rely on interaction with others for maximum success in-game but that also allows social exchange to
occur at a distance and with anonymity may be especially appealing for people with specific psy-
chological profiles, such as low self-esteem and depression (Stetina, Kothgassner, Lehenbauer, &
Kryspin-Exner, 2011) or overall higher psychiatric symptomatology (Pawlikowski & Brand,
2011). This is consistent with Davis’ (2001) conceptualization of PIU as developing from the unique
communication functions of the Internet. This social motivation for play may be particularly true for
those who experience heightened anxiety in social situations, such as individuals with social anxiety
disorder. In the current study, we sought to extend prior research by examining the association
between social anxiety, generalized anxiety, and PIU in a sample of gamers. We also sought to iden-
tify personality variables associated with PIU. Accordingly, we explored the extent to which major
personality domains (neuroticism, extraversion, openness to experience, agreeableness, and
conscientiousness; Costa & McCrae, 2009) differentiated between gamers with higher versus lower
levels of PIU. Neuroticism is strongly related to anxiety disorders (Kotov, Gamez, Schmidt, &
Watson, 2010). Mehroof and Griffiths (2010) found a correlation between state and trait anxiety,
neuroticism, and PIU. It is possible that higher neuroticism underlies risk of PIU as well as of anxi-
ety. Therefore, we predicted that online gamers with high PIU scores would exhibit higher levels of
neuroticism. Because low levels of extraversion have been shown to predict a preference for
computer-mediated communication (Orchard & Fullwood, 2010), we further hypothesized that
high-PIU scorers would also exhibit less extraversion.
We also sought to identify factors other than psychopathology variables that might potentially
increase a person’s enjoyment of MMO gaming. MMOs are gaming platforms that are unlike
traditional console video games, or non-MMO games such as Words with Friends that occur within
relatively stable environments. In contrast to console games, MMOs contain a variety of avatars and
environments, limited only by the imagination of their creators and available server space. These
environments are also periodically increased to add new material, including new geographic areas
and combat scenarios, to the existing MMO, increasing their complexity, variety, and visual appeal.
It is reasonable to believe that people who are fantasy-prone and who find it easy to immerse
themselves in imagery, would be particularly likely to find such games attractive. Accordingly,
we examined the hypothesis that people who scored high on a measure of absorption—a construct
that indexes an individual’s capacity for imaginative involvement, fantasy proneness, and imagery
ability (Kremen & Block, 2002; Tellegen & Waller, 2008) would be more likely to report higher levels
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of PIU in the context of MMO games. The motivation for this research was to identify factors that may
place certain people at risk of more PIU than others, given the fact that relatively few people can be
identified as ‘‘Internet addicts.’’ This led us to examine absorption, which was originally identified as a
personality trait by Tellegen and Atkinson (1974) and which was included in the Multidimensional
Personality Questionnaire (Tellegen & Waller, 2008). The authors describe absorption as follows:
Absorption is interpreted as a disposition for having episodes of ‘total’ attention that fully engage one’s
representational (i.e., perceptual, enactive, imaginative, and ideational) resources. This kind of
attentional functioning is believed to result in a heightened sense of the reality of the attentional object,
imperviousness to distracting events, and an altered sense of reality in general.
It is reasonable to test the presence of this type of ‘‘attentional functioning’’ in a sample of people
who become highly engaged in MMO environments. To our knowledge, absorption is a personality
characteristic that has not been examined in previous research.
Finally, using an exploratory approach, we sought to learn more about players’ motivations for
gaming by asking why they liked to play MMOs. Considering the above discussion of personality,
psychopathology, and PIU, we predicted that individuals who played online games and who had
high-PIU scores would be more likely than low-PIU scorers to endorse playing MMOs for reasons
related to social communication.
Identifying Differences Between Low- and High-PIU Gamers
We sought to replicate and extend earlier research by examining the clinical and personality char-
acteristics of people who regularly engaged in MMO games, such as World of Warcraft, using a
cross-sectional survey approach. At a general level, we sought to identify psychosocial and beha-
vioral factors that distinguished people with high scores on a measure of PIU from those with low
scores on the same measure. The goal of this study was to confirm earlier findings relating anxiety to
PIU in gamers, and also to expand such work by examining other factors, such as personality traits
and motivations for gaming, that might be relevant in predicting PIU in MMO users.
Hypotheses
We tested several hypotheses about the role of clinical and personality factors in problematic MMO
gaming. Specifically, we predicted that (1) higher scores on measures of PIU would be correlated
with higher scores on measures of state, trait, and social anxiety. This is because anxious people
in general and socially anxious people in particular might be expected to experience MMO
game-based social interactions as less threatening and more rewarding than less anxious people.
We further predicted that (2) high absorption, which reflects fantasy proneness, would predispose
individuals to experience online games as more enjoyable. For these reasons, we therefore expected
that people in the high-PIU group would have higher absorption scores than people in the low-PIU
group. We also expected that (3) high-PIU gamers would exhibit low extraversion and high neuroti-
cism. Finally, we predicted that (4) high-PIU gamers would identify reasons for gaming related to
social communication more often than low-PIU gamers.
Method
Participants
Participants were recruited by posting an invitation to complete a study survey, and a link to the
survey, on Craigslist.org and on online gaming forums. The study was anonymous, and no
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identifiable data were collected from subjects. The website PsychData.com was used to survey
participants. Internet protocol (IP) addresses ensured that no subject completed the survey twice.
The study advertisement sought out adult current or past players of MMO games who played
more days than not or played for more than 2 hr at a time on days they did play. We collected data
on a total of 163 participants (65 female, 92 male, 6 unreported), with a mean age of 27.3 years
(SD ¼ 9.1).
Procedure
Participants provided informed consent via the web survey, then completed the measures described
below and were asked about their reasons for gaming. Finally, participants provided estimates of the
amount of time they had been playing (total number of months) as well as the number of hours they
spent playing in a typical session. Mean daily gaming time in the sample was 3.5 hr (SD ¼ 1.33);
mean time since starting gaming was 31.56 months (SD ¼ 17.78).
Measures
We first administered a demographic questionnaire that asked participants to report their age, sex,
number of months playing MMOs, daily time spent gaming, and other relevant characteristics. To
test our hypotheses about personality and clinical traits that would distinguish low- and high-PIU
gamers, we used a series of well-validated measures of these traits. To divide the sample of MMO
gamers into low- and high-PIU groups for comparison, we used a median split based on the scores
from the Generalized Pathological Internet Use scale (GPIUS; see below).
GPIUS
The GPIUS (Caplan, 2002) is a 29-item scale that was developed to operationalize Davis’s (2001)
model of generalized PIU as a person’s experience of particular combinations of cognitions, beha-
viors, and outcomes associated with PIU. The scale contains items rated on a 5-point Likert-type
scale, from 1 ¼ strongly disagree to 5 ¼ strongly agree, where the strength of agreement indicates
the degree to which the subject feels the item reflects his or her Internet-related experiences. The
items are designed to address cognitions (e.g., ‘‘I am worthless offline, but online I am someone’’),
behaviors, (e.g., ‘‘I spend more time online than I expect to’’), and outcomes (e.g., ‘‘I have missed
school or work because of online activities’’), which together characterize PIU as a consequence,
rather than a cause, of related pathology (Caplan, 2002). The GPIUS contains seven factors. These
are correlated with each other and with psychosocial well-being variables in a way that is consistent
with Davis’s original theory and that provides support for the construct validity of the scale.
Analyses of internal consistency show high a coefficients (.92 in the present study), demonstrating
that the scale has good reliability. The GPIUS has been used by several authors to assess PIU.
Spielberger State-Trait Anxiety Inventory (STAI)
The Spielberger STAI (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1970) is a measure of both
state and trait anxiety. It is based on a model in which state anxiety, or the fluctuating experience of
arousal to threatening stimuli, is distinguished from trait anxiety, a more stable dispositional trait.
The STAI is a brief self-report measure that consists of 40 items on two separate 20-item forms
(STAI-Y1 and STAI-Y2). State items assess how the person feels in the moment (e.g., ‘‘I am tense,’’
or the reverse-scored ‘‘I feel calm’’). Trait items assess how the person generally feels (e.g., ‘‘I lack
self-confidence’’). The STAI is a well-validated and frequently used measure. The scale has good
construct validity, correlating with other known measures of anxiety (Spielberger et al., 1970).
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Test–retest reliability over a period of 3 weeks has been reported at .97 for Trait anxiety and .45 for
State anxiety (Metzger, 1976). Internal consistency of the measure is high, with Cronbach’s a coef-
ficients of .92 for both forms (Ramanaiah, Franzen, & Schill, 1983).
Tellegen Absorption Scale (TAS)
The TAS (Tellegen & Atkinson, 1974) was constructed as part of a larger personality scale and
measures the construct of absorption. The TAS is a 34-item self-report scale that is widely used
in personality research and has been demonstrated to be reliable and valid. Responses are given
in a 4-point Likert-type scale from 0 to 3 (0 ¼ never; 3 ¼ always). Questions address aspects of
an individual’s experience of the world and contain items such as ‘‘While watching a movie, a
TV show, or a play, I may become so involved that I may forget about myself and my surroundings
and experience the story as if it were real and as if I were taking part in it.’’
NEO-Five Factor Inventory (NEO-FFI)
This is a shortened version of the NEO Personality Inventory–Revised (Costa & McCrae, 1992) and
is based on the five-factor model of personality classification. The NEO-FFI consists of 60
statements rated on a 5-point scale from strongly agree to strongly disagree. It taps the five major
dimensions of personality (Neuroticism, Extraversion, Openness, Agreeableness, and Conscien-
tiousness) and has good reliability and validity (Costa & McCrae, 1992).
Social Phobia Scale (SPS)
The SPS (Mattick & Clarke, 1998) is a self-report measure that assesses fears of being scrutinized by
others. It contains 20 items, rated on a 0–4 Likert-type scale. Respondents indicate the degree to
which they feel each statement is characteristic of them (0 ¼ not at all and 4 ¼ extremely). In the
original development of the measure, the SPS item-total correlations were high. The scale showed
good internal consistency and test–retest reliability, as well as showing good discriminant and con-
struct validity. That is, the scale discriminated social phobia from agoraphobia and scores on the
measure correlated with scores from the Spielberger STAI and the Fear of Negative Evaluation scale
(Mattick & Clarke, 1998; Watson & Friend, 1969).
Results
Low- Versus High-PIU Groups
Independent sample t-tests were used to compare people with low versus high PIU on the variables
of interest. No cutoff score has been published for the GPIUS, given the author’s goal of exploring
relationships among variables rather than assigning users to diagnostic categories (Caplan, 2003).
Therefore, to create groups for the purpose of comparison, we assigned participants to the low
(n ¼ 84) and high (n ¼ 79) PIU groups using a median split based on the GPIUS score. The mean
GPIUS score of the low-PIU group was 54.5 (SD ¼ 10.0) and the mean GPIUS score of the high-PIU
group was 87.2 (SD ¼ 13.4), t(161) ¼ 17.803, p < .001, r ¼ .81.The high-PIU (57.9% male) and low-
PIU (59.3% male) groups did not differ in gender composition, w2(1) ¼ .0.03, p ¼ .86, or in age,
t(161) ¼ .851, p ¼ .396, r ¼ .07.
Note that this method of comparing groups does not imply that the high-PIU group represents an
‘‘addicted’’ group of gamers; rather, that they have higher scores on what is in fact a continuous mea-
sure. Furthermore, because the mean of the high-PIU group is 87.2 (on a scale ranging from 29 to
145), the reader may question whether the high-PIU group actually has objectively high scores.
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Table 1. Differences Between Low- and High-PIU Groups on Measures of Anxiety, Creativity, and Absorption.
Low-PIU Group Mean High-PIU Group Mean
(SD), n ¼ 84 (SD), n ¼ 79 t df p r
STAI-state 32.52 (9.09) 35.15 (11.19) 4.162 161 .000 .31
STAI-trait 35.27 (10.16) 46.66 (11.18) 6.812 161 .000 .47
SPS 32.05 (12.24) 44.11 (7.84) 5.005 137.07a .000 .37
TAS 67.12 (18.11) 73.89 (18.19) 2.379 161 .019 .18
Note. SPS ¼ Social Phobia scale; STAI ¼ state-trait anxiety inventory; TAS ¼ Tellegen Absorption scale.
a
Levene’s test for equality of variances was significant at p ¼ .000; therefore, the value presented represents equal variances
not assumed.
Table 2. Personality Characteristics of Low- Versus High-PIU Scorers.
Low-PIU Group High-PIU Group
Mean (SD) Mean (SD) t df p r
Neuroticism 18.48 (9.39) 27.35 (9.79) 5.901 161 .000* .42
Extraversion 26.38 (7.10) 21.87 (7.18) 4.031 161 .000* .30
Openness to experience 33.00 (5.73) 32.18 (7.03) .821 161 .413 .06
Agreeableness 30.09 (6.80) 28.32 (6.76) 1.661 161 .099 .13
Conscientiousness 30.03 (8.08) 26.39 (7.69) 2.946 161 .004** .23
*
Significant at p < .001. **Significant at p < .01.
Taking into account the fact that the GPIUS measures outcomes of Internet use in addition to cogni-
tions and behaviors associated with use, higher scores by definition indicate more problematic use.
Anxiety, Absorption, and PIU
Consistent with prediction, gamers reporting more PIU also endorsed significantly higher levels of
state anxiety, trait anxiety, and social phobia than people in the low-PIU group (see Table 1 for
means and statistics). Also as expected, those in the high-PIU group scored higher on the TAS than
did those in the low-PIU group. This represents the first finding that the personality trait of absorp-
tion is related to PIU in online gaming, and supports the idea that fantasy proneness may predispose
individuals to find online games rewarding. Together, these findings suggest that high-PIU scorers
were more anxious in a variety of ways and were more inclined to be drawn into fantasy and ima-
ginative involvement.
NEO-FFI Personality Traits
In a series of additional analyses, we also examined the personality traits of high- and low-PIU
scorers using the NEO-FFI (see Table 2). The two groups did not differ significantly on Openness
to Experience or Agreeableness. However, consistent with prediction and with prior research, high-
PIU participants were more neurotic and less extraverted than their low-PIU counterparts. They also
scored lower on the trait of conscientiousness.
Motivations for Gaming
As predicted, there were significant differences between the two groups of gamers with respect to
their reasons for playing MMOs. Gamers in the high-PIU group were significantly more likely to
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Table 3. Reasons for Gaming Endorsed by Participants in Low- Versus High-PIU Groups.
Item Low-PIU Group High-PIU Group w2 Sig
To socialize n 43 57 7.544 .006*
% 26.4 35.0
Just for fun n 73 65 .671 .413
% 44.8 39.9
To meet new people n 10 13 .696 .404
% 6.1 8.0
To get away from real life n 31 52 13.62 .000**
% 19 31.9
Decrease stress n 42 52 4.175 .041*
% 25.8 31.9
Decrease anxiety n 16 22 1.764 .184
% 9.8 13.5
To feel happier n 19 43 17.480 .000**
% 11.7 26.4
Prefer to other games/entertainment n 43 42 .064 .801
% 26.4 25.8
Other n 17 16 .000 .998
% 10.4 9.8
*
Significant at p < .01. **Significant at p < .001.
endorse the items ‘‘to socialize,’’ ‘‘to get away from real life,’’ ‘‘to decrease stress,’’ and ‘‘to feel
happier.’’ These results are consistent with the idea that individuals who play MMOs to excess desire
social interaction and may also have some degree of psychosocial impairment. These data are pre-
sented in Table 3.
Identifying Predictor Variables for PIU in Gamers
Finally, we used stepwise regression to identify the factors that were most strongly associated with
PIU in our sample. Past research, in addition to the results of the t-tests reported above, indicates that
anxiety may be a risk factor for PIU. However, no study to date has examined the potential contri-
bution played by the construct of absorption, or the contribution made by anxiety when absorption is
also considered. Therefore, the TAS and all three anxiety measures (STAI-State, STAI-Trait, and
SPS) were added into the model using backward entry to test their contribution to the variance in
PIU scores (measured by the GPIUS). In Step 1, TAS, STAI-State, STAI-Trait, and SPS together
accounted for 35.5% of the variance in GPIUS score. In Step 2, removal of STAI-State did not result
in a significant change in the predictive value of the model. In Step 3, the removal of TAS also did
not significantly change the predictive value of the model. There was no evidence of multicollinear-
ity or heteroscedasticity in the results. These data suggest that trait anxiety and social phobia are
most predictive of PIU, even when absorption is taken into account. The results of this regression
analysis are reported in Table 4.
Because neuroticism is highly correlated with anxiety, it is also informative to know whether
anxiety still predicts PIU score after controlling for neuroticism. To examine this, we used hierarch-
ical regression, entering neuroticism in the first step and then entering trait anxiety and social anxiety
in the second step (see Table 5). Even with neuroticism already in the model, entry of the anxiety
variables led to a significant change in the F value and explained additional variance. These findings
indicate that although anxiety and neuroticism are highly correlated, it is anxiety, rather than neu-
roticism that is most important in understanding PIU.
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Table 4. Anxiety and Absorption Measures as Predictors of GPIUS Score.
B SE B b
Step 1
Constant 29.08 6.13
TAS .02 .08 .02
STAI-State .03 .17 .01
STAI-Trait .68 .17 .41*
SPS .29 .10 .24**
Step 2
Constant 28.38 5.81
TAS .02 .08 .02
STAI-Trait .69 .14 .42*
SPS .29 .10 .24**
Step 3
Constant 30.43 4.54
STAI-Trait .70 .13 .42*
SPS .30 .10 .24**
Note. SPS ¼ Social Phobia scale; STAI ¼ state-trait anxiety inventory; TAS ¼ Tellegen Absorption scale.
R2 ¼ .36 for Step 1 (p ¼ .000); DR2 ¼ .00 for Step 2 (p ¼ .87); DR2 ¼ .00 for Step 3 (p ¼ .77).
*
Significant at p < .001. **Significant at p < .01.
Table 5. Neuroticism and Anxiety Variables as Predictors of GPIUS Score.
B SE B b
Step 1
Constant 47.41 4.54
Neuroticism 1.01 .13 .51*
Step 2
Constant 30.69 5.34
Neuroticism .03 .29 .01
STAI-Trait .68 .25 .41**
SPS .30 .10 .10**
Note. SPS ¼ Social Phobia scale; STAI ¼ state-trait anxiety inventory.
R2 ¼ .28 for Step 1 (p ¼ .000); DR2 ¼ .08 for Step 2 (p ¼ .000).
*
Significant at p < .001. **Significant at p < .01
Discussion
Anxiety and PIU in Gaming
The purpose of this study was to provide data on the clinical and personality characteristics of online
gamers who report PIU. Based on earlier research, we predicted that state anxiety, trait anxiety, and
social phobia would be associated with more PIU in this sample. Consistent with prediction, high-
PIU scorers experienced more difficulties in all of these areas. Regression analysis further indicated
that the best predictors of higher scores on a measure of PIU were trait anxiety and social phobia.
Additional analyses confirmed the importance of anxiety as a predictor of higher PIU score, even
after accounting for neuroticism. This means that individuals who are more generally anxious and
who have difficulties in social situations are the people most likely to have problems using online
games in moderation. These results replicate and extend recent findings (e.g., Mehroof &
Griffiths, 2010).
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Of course, these data do not mean that anxiety causes PIU. Not only are higher scores on the mea-
sure not diagnostic, it may be the case that using the Internet to excess leads to more anxiety over
time. Longitudinal investigations are needed to clarify this issue. Nonetheless, high trait anxiety may
constitute a risk factor for PIU in gaming.
Absorption and PIU in Gaming
We also expected that levels of absorption would be higher in gamers with higher PIU scores, a rela-
tionship that has not previously been explored. Absorption was correlated with higher PIU, suggest-
ing that people who are fantasy-prone find online games more engaging than people who are not;
this may represent a particular vulnerability to PIU in online gaming.
Taken together, our findings suggest that the highly immersive online environment offered by
MMO games may be especially appealing to anxious and imaginative individuals. The opportunity
to interact with others in a safe yet stimulating environment may contribute to excessive gaming. Of
course, because of their cross-sectional nature, no inferences about causal directions can be made.
However, our data do provide a possible explanation for why a small minority of people might
develop highly problematic or excessive use when exposed to MMOs.
Reasons for Gaming
We also found that high-PIU subjects were more likely than low-PIU subjects to endorse socializing
and escaping real life as reasons for gaming. Within the high-PIU group, trait anxiety was associated
with greater likelihood of using gaming to decrease stress and to escape real life. When combined
with the personality data from the NEO-FFI, which indicated that high-PIU participants were less
conscientious, more introverted and more neurotic (Chen, Tu, & Wang, 2008; Mehroof & Griffiths,
2010; Peters & Malesky, 2008), the emerging picture is therefore one of a socially anxious, fantasy-
prone individual who desires social interaction yet finds such interaction challenging. Together,
these findings replicate earlier research associating PIU and anxiety and provide new information
about the role of absorption and other personality traits, as well as motivations for play in online
gaming.
Limitations and Future Directions
Although the predicted differences between low- and high-PIU individuals were supported by the data,
the study is limited by the fact that it is cross-sectional. As a result, we know nothing about factors that
may have preceded PIU or that may have developed or been exacerbated over the course of game play.
It is possible that highly anxious people are drawn to online gaming, or find it more appealing than
low-anxious people. However, it is also possible that gaming results in increased anxiety or changes
in personality over time (e.g., perhaps due to neglect of work or other obligations). Furthermore, the
median split for creating groups based on a continuous variable should be cautiously interpreted by the
reader. The author of the GPIUS (Caplan, personal communication with S. Cole, December 03, 2012)
has stated that the GPIUS is not intended as a diagnostic tool. Therefore, when interpreting these data,
which compare low and high scorers on the GPIUS, it should be understood that this does not imply
that everyone in the high-PIU group is a game ‘‘addict.’’ Understanding whether clinical and person-
ality factors change over time with increased gaming is an important next step for research. Longitu-
dinal studies will further our understanding of who is at increased risk of PIU and help us learn
moreabout the consequences of excessive online gaming.
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Authors’ Notes
The authors wish to thank Luka Babic for his assistance with data collection.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or
publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication
of this article: This research was supported by a grant from the Harvard University Department of Psychology and
by a fellowship from the Sackler Scholar Programme in Psychobiology to Sadie Cole. No competing financial
interests exist.
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Author Biographies
Sadie H. Cole, AM, is a doctoral candidate in the clinical science program in the Department of Psychology at
Harvard University. She is currently conducting her predoctoral internship in clinical psychology at McLean
Hospital in Belmont, MA. She can be reached at scole@fas.harvard.edu.
Jill M. Hooley, DPhil, is a professor of psychology at Harvard University and is the head of the experimental
psychopathology and clinical psychology program at Harvard. She has a long-standing interest in psychosocial
predictors of relapse in severe psychopathology such as schizophrenia and depression. She can be reached at
jmh@wjh.harvard.edu.
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