Internet Overuse and Personality 1
Running head: INTERNET OVERUSE AND PERSONALITY
Internet Overuse and Personality: A Look at the Big Five, BIS/BAS, Loneliness, &
Boredom
Jared Salisbury
Adviser: William Revelle
Second Reader: Benjamin Gorvine
Internet Overuse and Personality 2
Abstract
Psychologists have been concerned with Internet overuse for many years. Much of the
research relating this phenomenon to personality has emphasized social uses of the
Internet and has concluded that people with social deficits (low Extraversion, high
Neuroticism, high Loneliness) use the Internet for socializing and overuse it as a result.
The present research finds this line of thinking is outdated and limited in scope, and
posits that Internet overuse can be thought of in terms of information seeking and lack of
impulse control. A new subjective Internet overuse scale was developed and analyzed
along with reports of amount and type of Internet use, the Big Five dimensions of
personality, Behavioral Inhibition and Behavioral Approach scales from Gray’s
Reinforcement Sensitivity Theory of personality, and scales assessing Loneliness and
Boredom. A survey was administered online and analyzed using the Synthetic Aperture
Personality Assessment technique. Results show that low Conscientiousness is the best
predictor of Internet overuse, supporting the impulse control hypothesis, but do not rule
out social deficits. Emphasis is placed on the wide variety of motivations for and types of
Internet use, and the benefit of taking a fresh, unbiased look at human interaction with
the medium.
Internet Overuse and Personality 3
Internet Overuse and Personality: A Look at the Big Five,
BIS/BAS, Loneliness, & Boredom
Consider the following anecdote: Two college friends are up late one night, deep in
rambling conversation. Mention of an avocado sparks the inevitable question, bound to
arise once and only once in such a setting, when the mysterious green lump rears its
bumpy head: Is an avocado a fruit or a vegetable? Being that these two friends are living
in the United States in the early 21st Century, their course of action is obvious: consult
Wikipedia. They open a browser on the conveniently placed, already booted, wi-fi capable
laptop sitting before them and commence their search. Within minutes, the original
question seems trivial; of course an avocado is a fruit. The challenge becomes classifying it
as a true fruit (as opposed to a false fruit, which is composed of other parts of the plant in
addition to the ovum) and as a simple fruit (as opposed to an aggregate fruit, which is
composed of more than one ovum). In 15 minutes time, the friends have become veritable
fruit experts, capable of categorizing even the most enigmatic of ripened plant ovaries.
Never before in human history has information been so accessible, immediate, and
densely distributed. The words Internet and World Wide Web are lobbed about so
frequently we often overlook their connotations; the Internet is quite literally a vast web of
interconnected information. For an illustration of this, consider another phenomenon that
Wikipedia makes possible, which was also most likely borne of the minds of bored
American college students. I refer to the ”Wikipedia Game,” in which two or more players
race to navigate from one entry to another, completely unrelated one using only the
hyperlinks on each page. More surprising than the fact that this is actually entertaining is
that a skilled player usually only takes a few minutes to get from Michael Jackson to
Pharmacogenomics.
Wikipedia provides some of the most concrete examples, but all applications of the
Internet boil down to the consumption of information. As such, the Internet provides a
Internet Overuse and Personality 4
potent means for the expression of the ”seeking” mechanism identified in neuroscience
literature. Closely associated with the dopaminergic system, the seeking mechanism is
what drives us to seek out new information related to goals. Rather than experiencing
pleasure (the function of the opiate system), the dopaminergic system reinforces behaviors
which lead to pleasure. Without satiety built in, it can easily become problematic, and is
associated with substance abuse and addictive behaviors (Panksepp, 1998). As anyone
who has ever felt compelled to check e-mail incessantly, follow irrelevant links on websites,
or look up useless information can attest, information seeking can easily get out of hand,
and the Internet provides the perfect environment for such behavior.
Since its conception, the Internet has rapidly become a bigger and bigger part of
more and more people’s lives. One would be hard pressed to find an American college
student who does not use the Internet on a daily basis. The notion of a paperless
workplace is gradually becoming a reality for many. Smart phones, such as Blackberries
and iPhones, have lifted the constraints of time and place. As the Internet becomes more
ubiquitous, the need for a more complete understanding of the human animal’s interaction
with it becomes all the more pressing. With the vast majority of the industrialized world
getting persistent exposure to the Internet, the question is not who uses the Internet
often, but for whom is its use likely to be problematic? The present research attempts to
answer this question by applying theories and measures from personality psychology.
The application of psychology to the study of the Internet is by no means a new
field. Wisely, researchers have recognized the ever-growing importance of the new medium
since its early days. A large portion of the literature has been devoted to the discussion of
”Internet addiction” or ”pathological Internet use,” a compulsion to use the Internet
which interferes with everyday functioning. And with good reason: a recent metasynthesis
of Internet addiction studies estimated that nearly 9 million Americans may be labeled
Internet addicts (Byun et al., 2009). However, it remains problematic that no common
Internet Overuse and Personality 5
definition for Internet addiction has been decided upon; a good working definition comes
from Beard (2005): ”An individual is addicted when an individual’s psychological state,
which includes both mental and emotional states, as well as their scholastic, occupational
and social interactions, is impaired by the overuse of the medium.” The most common
scales used to diagnose Internet addiction are derived from those found in compulsive
gambling literature, and the common brain chemistry involved in each suggests a
theoretical link. A large study conducted in Taiwan reported comorbidity of Internet
addiction with substance abuse, lending further credence to the notion that Internet
addiction shares many of the characteristics of other addictions (Ko et al., 2006).
Despite some methodological inconsistencies and disagreement over a formal
definition, the evidence indicates that Internet addiction is a very real, relatively
widespread disorder (Byun et al., 2009). Significant attempts have been made to apply
personality psychology–to see who Internet addicts are–particularly within the framework
of the Big Five dimensions of personality. The Big Five are Openness to Experience,
Conscientiousness, Extraversion, Agreeableness, and Stability, five personality traits which
have consistently emerged as essential and universal facets of personality (Goldberg, 1990).
Studies on the Big Five and Internet addiction have generally concluded that Internet
addicts score high on Neuroticism (the opposite of Stability) and low on Extraversion
(Hamburger & Ben-Artzi, 2000). Of the relatively few studies that have ventured outside
the Big Five, Internet addiction has been positively associated with sensation seeking (Lin
& Tsai, 2002), and, within Cloninger’s tridimensional theory of personality, it is associated
with high Novelty Seeking, high Harm Avoidance, and low Reward Dependence (Ko et al.,
2006). Further research has implicated Loneliness as an important situational factor which
is firmly entrenched in aspects of personality (Hamburger & Ben-Artzi, 2003).
The present body of research on Internet overuse is insufficient for several reasons.
The first is not so much a criticism of the research as it is a difficulty of the field in
Internet Overuse and Personality 6
general: Internet research cannot help but be constantly outdated. The landscape is
vastly different now than it was two years ago, let alone ten. Any research attempting to
build upon the existing literature must take into account the fact that more, different
people use the Internet for more, different purposes now than in the past. The portrait
that previous research has painted of the typical Internet over-user as a socially inept,
adolescent male grows less and less convincing (though there is still probably some truth
to it). That is not to say that previous research was not thorough, or was flawed in some
way, but new research that draws too heavily on old conclusions is bound to miss
important features of the Internet’s constant evolution.
The second deficit is in some sense a product of the first difficulty: research has
typically only taken a top-down approach to the pathology of Internet addiction, which
was necessary during the early days of the field but may no longer be appropriate.
Specifically, these studies focused on a clinical population, either screened through an
Internet addiction scale or self-selected, then analyzed how these people use the Internet
and what their common personality traits are. They have concluded that Internet addicts
are most often a part of an online community, which is attractive to them due to their
social deficits offline. Research on personality and Loneliness (Hamburger & Ben-Artzi,
2003) has corroborated this story, and subsequent research on more general populations
has by and large only attempted to confirm these results. For these reasons I suggest that
the importance of the online community in problematic Internet use research has been
exaggerated, at least in the current environment. For one thing, it differs greatly from the
experience of the average Internet user, especially now that the term ”Internet user”
encompasses such a large and rapidly growing portion of the general population. Further,
the above anecdote is meant to convey that the social aspects of the Internet are not the
only way its use can become problematic. Other explanations may be equally valid; for
example, just as Loneliness is an important situational factor for problematic social uses
Internet Overuse and Personality 7
of the Internet, perhaps Boredom and amount of free time can help explain some of its
other problematic uses.
I use the word problematic above to underscore the third deficit in current research:
the focus on ”addiction” has been extremely confining, particularly when dealing with an
issue that could theoretically affect a large portion of the population in varying degrees.
Since any attempt to classify Internet addiction amounts to an arbitrary cutoff, and
researchers have yet to reach a consensus of where that cutoff should be placed, or even
what scale to use (Byun et al., 2009), it seems wiser to consider a continuum of Internet
overuse. This will allow us to study behavior that doesn’t meet the requirements of
full-fledged Internet addiction, but can still be problematic for a large number of people.
Related to the narrow focus of Internet addiction research is the limited number of
ways personality psychology has been applied to it. Whereas most research has focused on
high-order personality traits such as the Big Five, given the elegant neuropsychological
explanation for seeking outlined above, low-order trait theories seem promising. Despite
the wide gap in knowledge between neuroscience and personality psychology, fruitful
attempts have been made to link the two. Gray’s Reinforcement Sensitivity Theory
(RST), for example, postulates that personality stems from the biologically based
Behavioral Approach System (BAS), Behavioral Inhibition System (BIS), and
Fight-Flight-Freeze System (FFFS) (Corr, 2008). Sensitivities within these systems result
in the reinforcement of certain behaviors, which over time become the stable high-order
personality traits described by, for example, the Big Five. RST shares many similarities
with Cloninger’s tridimensional model, which maintains that Novelty Seeking, Harm
Avoidance, and Reward Dependence constitute the most basic dimensions of personality
(Cloninger, 1987); however, RST, which is based on animal studies, has a firmer biological
foundation and is supported by a wealth of empirical evidence (Corr, 2008). Though we
lack the sophistication to link the seeking mechanism to RST, RST is a promising avenue
Internet Overuse and Personality 8
for exploring Internet overuse, especially given the success that was had with Cloninger’s
tridimensional model.
The present research will attempt to improve upon these deficits. Given the
ever-changing nature of the Internet, this study will be relatively independent of past
conclusions to the point of being exploratory. It will accomplish this by surveying amount
and type of Internet use, how problematic it is (on a continuous scale), important
situational factors such as Loneliness and Boredom, and competing theories of personality
concurrently. I hypothesize that low-order traits will have more explanatory power than
high-order ones, and that Loneliness and Boredom will arise as important predictors of
behavior. I also predict that previous conclusions, such as the fact that people low in
Extraversion and low in Stability use the Internet more, will still be valid, but will only
account for a limited amount of people experiencing problematic Internet use.
Method
Participants
Subjects participating in the online survey followed a link on the Personality Project
website (http://personality-project.org), a resource for scientific literature on personality.
The only incentive for completing the survey was a chance to see one’s Big Five
personality score. As such, participants are in no way a representative sample, though
they are demographically diverse. Data from a total of 14,146 subjects are reported. Due
to an error in data collection, gender and age were not recorded for roughly 11,000
subjects. Of the 3,155 subjects for which gender and age were recorded, 64% were female,
with a median age of 24. This corresponds roughly to the demographics of previous
Personality Project research (70% female, median age 23), so we can safely assume the
sample is similar to what has been reported in the past (Revelle, Wilt, & Rosenthal, 2010).
Internet Overuse and Personality 9
Measures
Subjects were asked to report the average number of hours they spend online per
day. In light of research on motivations to use the Internet (Landers & Lounsbury, 2006;
Hamburger & Ben-Artzi, 2000), they were also asked to report how many hours they
spend doing the following: using the Internet for work or school; communicating with
others online (through chatting, e-mailing, sending messages through social networking
sites, etc.) (excluding for work or school); browsing social networking sites (e.g.,
Facebook, Myspace) or other online communities; browsing websites other than social
networking sites or other online communities (excluding for work or school); and playing
games online (including gambling). In order to further characterize social uses of the
Internet (communication and browsing social networking sites) subjects were asked what
proportion of the people they interact with online were first met online. They were also
asked how many times they check e-mail per day, how may websites they regularly check
for updates, and whether or not they own a smart phone. (See Appendix Table A1 for the
ranges and corresponding numerical values.)
To measure how problematic Internet use was for individuals, the Internet overuse
scale was developed based on existing Internet addiction and overuse scales (Caplan, 2002;
Morahan-Martin & Schumacher, 2000; Song, Larose, Eastin, & Lin, 2004). A total of 10
items were used. Items were chosen, reworded, or created in order to be as general as
possible (”My use of the Internet interferes with other activities”) in contrast to the
tendency of some existing scales to focus on social uses of the Internet. (See Table 1 for
the full list of questions comprising the scale.)
100 Big Five personality items, 20 for each factor, were selected from the
International Personality Item Pool (IPIP) developed by Goldberg (Goldberg et al., 2006).
The IPIP is a public domain equivalent to many commonly used, proprietary personality
scales. The items chosen were developed as markers of the Big Five personality
Internet Overuse and Personality 10
dimensions of Openness to Experience, Conscientiousness, Extraversion, Agreeableness,
and Stability (Goldberg, 1990, 1999).
An additional 36 items from the IPIP inventory were based on Carver and White’s
BIS and BAS scales (1994). BIS is measured by a single scale (”I am always worried
about something”), while BAS is divided into Fun-seeking (”I am willing to try anything
once”), Drive (”I take charge”), and Reward-responsiveness subscales (”I feel excited or
happy for no apparent reason”), which load onto a single BAS factor.
Four of twenty items from the Revised UCLA Loneliness Scale (Russell, Peplau, &
Cutrona, 1980) were presented to assess feelings of loneliness (”I feel isolated from
others”). To assess feelings of boredom and excessive free time, two items were taken from
the IPIP and two new items were created (”I often find myself with nothing to do”).
All Internet overuse and personality items were formatted as Likert-type
self-statements ranging from 1 (very inaccurate) to 6 (very accurate).
Procedure
The online survey made use of the Synthetic Aperture Personality Assessment
(SAPA) methodology (Revelle et al., 2010). SAPA takes its name from the Synthetic
Aperture Measurement technique used in astronomy, in which a large, high-resolution
radio telescope is created by synthesizing the input of many smaller ones. Similarly, using
SAPA, a survey with many items can be synthesized from many surveys with relatively
few items.
The method relies on a large sample size achieved via the Internet to essentially
spread out the burden placed on any one subject. Each participant answered roughly 85
questions from a pool of several hundred, for the purposes of this study and others being
run simultaneously through the Personality Project. The items were systematically
sampled so that every pair of items was presented an equal number of times, with the
Internet Overuse and Personality 11
exception that Big Five items were sampled considerably more in order to provide
accurate feedback to the subject. This allowed for statistics to be performed at the
correlation level.
The survey consisted of: 50 Big Five items (10 for each factor) sampled from 100
Big Five items (20 for each factor); 10 items sampled from the BIS/BAS, Internet overuse,
Loneliness, and Boredom scales (among others unrelated to this research); and all the
Internet usage items described above.
Subjects entering the online survey were greeted by a welcome screen and asked to
agree to a consent form. They then filled out basic demographic information (age, sex,
education, and country of residence). Subjects from the United States were asked their
ethnic identity, SAT Verbal and Quantitative scores, and ACT total score. They then
completed the survey. Upon completion, subjects were given feedback on their Big Five
personality scores, presented numerically, graphically, and in paragraph form.
Results
Descriptive statistics for demographic and Internet use and overuse items are
reported in Table 1. Internet overuse items had means ranging from 2.38 to 3.74 and
standard deviations ranging from 1.47 to 1.77, indicating a fairly large range of perception
of Internet use centered around neutral. With the median subject reporting using the
Internet 2 to 4 hours per day, the online sample does not appear to be grossly skewed
towards high Internet use, but presumably it is slightly higher than a representative
sample. The median subject uses the Internet for work or school 1-2 hours, and spends 1
hour or less on other uses. Subjects tended to interact more with people first met offline
than online. The median subject checks 3 websites for updates regularly, and checks his or
her e-mail 3 times per day. Slightly over half the sample (51%) owns a smart phone.
Descriptive statistics cannot be reported at the scale level because no one individual
Internet Overuse and Personality 12
answers all questions of a scale in the SAPA methodology.
Standardized Cronbach’s α scores for each scale are easily calculated directly from
the correlation matrix (Table 2). The Big Five scales all had excellent reliability, with α’s
ranging from 0.86 to 0.93. BIS and BAS both had good reliability (α = 0.87, 0.86),
although the BAS subscales were slightly less reliable. The Loneliness and Boredom scales
had mediocre reliability (α = 0.66, 0.74), which is to be expected with only 4 items each.
Signifance statistics are not reported for correlations or regressions because, with
such a large sample size, they would grow redundant. Instead, these results focus on effect
sizes.
The correlations among scales and the demographic and Internet usage items were
calculated from the raw, pairwise item correlations synthetically, taking into account that
scale by scale intercorrelations are just composites of correlation (Revelle et al., 2010) (see
Appendix Table A2). Of particular relevance to this study are the correlations of the
various personality scales to the Internet overuse scale and the Internet use items.
Internet overuse was correlated negatively with Conscientiousness (−0.45), Stability
(−0.28), Agreeableness (−0.21), and Extraversion (−0.20) and positively with BIS (0.33),
Boredom (0.32), BAS Fun-seeking (0.17), and Loneliness (0.13). Results are similar but to
a lesser degree for the Internet usage items; for example, total non-work or school Internet
use correlated negatively with Conscientousness (−0.27), Agreeableness (−0.19),
Extraversion (−0.17), and BAS Drive (−0.13), and positively with Boredom (0.30),
Loneliness (0.13), and BIS (0.11). Subjective Internet overuse was correlated with total
Internet use (0.42) but not with Internet use for work or school (0.01). As expected,
Loneliness correllated with Boredom (0.23).
The BIS/BAS scales were intimately related to the Big Five Scales. BIS was
extremely negatively correlated with Stability (−0.82). The BAS subscales, Fun-seeking,
Drive, and Reward-sensitivity, were all positively correlated with Extraversion (0.38, 0.59,
Internet Overuse and Personality 13
0.49) and Openness (0.20, 0.35, 0.13), while Fun-seeking was negatively correlated with
Conscientiousness (−0.24), Drive was positively correlated with Conscientiousness (0.25),
and Rewad-sensitivity was positively correlated with Agreeableness (0.52). Unsurprisingly,
BAS itself was positively correlated to Extraversion (0.63), Openness (0.31), and
Agreeableness (0.23).
Multiple regressions were performed from the correlation matrix (Revelle et al.,
2010). Table 3 reports the results of various models regressing Big Five or BIS/BAS scales
(with or without subscales), demographic variables, and Loneliness and Boredom scales on
Internet overuse in a hierarchical fashion, in order to show the differences in variance
explained by competing theories of personality and the contributions of demographics,
Loneliness, and Boredom. The models that included all three sets of variables had the
best fit, with the Big Five model (R
2
= 0.286) beating out BIS/BAS with and without
subscales (R
2
= 0.242, 0.221). In the BIS/BAS model with subscales, the best predictors
(those with the highest β weights) were BIS (β = 0.32), BAS Fun-seeking (0.22), Boredom
(0.21), and Age (−0.12). In the Big Five model, the best predictors were
Conscientiousness (β = −0.35), Stability (−0.17), Age (−0.15), and Openness (0.12).
Table 4 reports the results of similar regressions, this time on total hours spent online, not
for work or school. R
2
values were lower for these models, but again the Big Five model
with demographics, Loneliness, and Boredom (R
2
= 0.134) had better fit than either
BIS/BAS model (R
2
= 0.118, 0.109). Boredom played a large role in this model
(β = 0.19), as did Conscientiousness (−0.16).
Since the Big Five model with demographics, Loneliness, and Boredom was
consistently the best model, it is the only one reported for the remaining Internet use
outcomes (Table 5). Gender (being female) played a role in predicting Internet use for
work or school (β = 0.15), using social networking sites (0.11), and interacting with people
met offline (0.11). Somewhat surprisingly, Extraversion positively predicted using the
Internet Overuse and Personality 14
Internet to communicate (0.09) and use social networking sites (0.10) and (less
surprisingly) predicted owning a smart phone (0.13). Lonely people were more likely to
interact with people met online (−0.18) (note the direction of the scale: lower values
indicate more people met online, higher values, more people met offline) but spent less
time using the Internet for communication (−0.07), social networking (−0.12), and gaming
(−0.13). Rather, Bored people spent more time using the Internet to communicate (0.14),
use social networking sites (0.17) and other websites (0.16), and play games (0.19).
To take a closer look at social uses of the Internet, models were extended to include
who one interacts with online and possession of a smart phone (Table 6). People who
interact more with people first met online tend to use the Internet more for
communication (β = −0.29), social networking (−0.21), and gaming (−0.25). People who
own a smart phone tend to check their e-mail more often (0.11).
Discussion
Use and overuse of the Internet cannot be explained in terms of social deficits alone.
The results of this study contrast the existing literature in many ways. While
Extraversion and Stability remain inversely related to Internet overuse, Conscientiousness
emerges as its strongest predictor. The positive association with Openness may imply that
the vast amount of information on the Internet appeals to people for intellectual reasons.
Interestingly, Loneliness predicts Internet overuse in the direction opposite of what was
expected when the effects of Boredom, a stronger but related predictor, are taken into
account through regression. The emerging picture is not of someone with social deficits
relying on the Internet for companionship, but of someone lacking impulse control and
drive, with a lot of free time on his or her hands.
The BIS/BAS scales were generally not as predictive as Big Five, but still bear
mentioning. The high predictive strength of BIS and BAS Fun Seeking on Internet overuse
Internet Overuse and Personality 15
paints an interesting picture: people who have a high desire for fun but are too inhibited
to express it in other areas of life resort to using the Internet excessively. However, the
extremely high negative correlation between BIS and Stability raises doubt as to whether
the two scales are indeed measuring different constructs. Once again, the data point to a
lack of impulse control, though itis difficult to interpret what exactly the BIS scale tells us.
The demographic variables reveal striking differences in how different people use the
Internet. Females tend to use the Internet more overall, for work or school, and for
browsing social networking sites, while males tend to use it more for online gaming.
Despite these differences, subjective Internet overuse does not vary with gender.
Unsurprisingly, older, more educated people tend to use the Internet more for work or
school and check their e-mail more often, while younger people tend to use social
networking sites more. These point to different motivations for using the Internet that
vary with age, gender, and educational attainment.
The fact that Boredom is better than Loneliness at predicting of Internet use across
the board, including social uses, is quite telling. It detracts from the hypothesis that
lonely people resort to the Internet for friends; rather, the Internet is something that
draws people with a lot of free time on their hands. Of course, the two concepts are
closely related, but in general the broader notion that Boredom leads to Internet use is
favored over the alternative of Loneliness, which is relegated to social uses of the Internet.
It is also true that people high in Extraversion tend to use the Internet more for chatting
and social networking; unsurprisingly, they carry their need for social interaction with
them online.
Not all of the data disconfirms the social deficit hypothesis; the fact that Loneliness
predicts more interaction with people met online lends credence to the idea that lonely
people socialize online. Further, people who interact with people met online tend to use
the Internet more overall and for social purposes; however, they are nto more likely to
Internet Overuse and Personality 16
beleive they are overusing the Internet. This raises the possibility that perhaps socializing
online can be healthy for some people who lack social skills, or at least preferable to the
alternative of isolation.
There are some important limitations to bear in mind when interpreting the results
of this study. First, the Loneliness and Boredom scales, which turned out to be associated
with Internet use and overuse in interesting ways, are only comprised of 4 items each, and
hence have relatively low reliabilty. Future studies should use longer, more reliable scales
to explore these relationships, given their theoretical importance. Second, the instrument
for measuring amount and type of Internet use could be improved upon. Although easy to
implement in survey form, it may have been difficult for subjects to give an accurate self
report of Internet use, especially if, for example, someone spends a few minutes chatting
here and there while using the Internet for work. Future studies could address this
problem by monitoring actual Internet use, and could look at other interesting outcomes,
like frequency of switching tasks while using the Internet.
Although our measures lack the specificity to say how ”compulsively” someone uses
the Internet, as we would like to have to address the role of the seeking mechanism in
Internet overuse, the results we do have, particularly the strong relationship between
overuse and low Conscientiousness, support the theoretical connection. People low in
Conscientiousness tend to let their Internet use get away from them. The association with
high Openness may indicate that this is especially true for people attuned to new
information. From a BIS/BAS approach, one would not have expected inhibition to be so
strongly associated with overuse (though the theoretical grounds of the BIS scale are
suspect), but the predictive power of BAS Fun-seeking fits in nicely with the concept of
seeking. It seems reasonable to conclude that the seeking mechanism plays a role in
Internet use and overuse, but it does so amidst many other motivations, like socializing,
from which it is difficult to disentangle at the personality level.
Internet Overuse and Personality 17
These results are not intended to disprove the previous hypothesis that socially
inept people turn to the Internet; with countless people using the Internet for myriad
reasons, there is undoubtedly some truth to this. Rather, it should be emphasized that
this explanation no longer generalizes to the Internet using population at large, which has
expanded considerably since much of the previous research was conducted. It is helpful to
take a fresh, unbiased look at human interactions with the Internet, a medium that for
good or ill plays an ever increasing role in our lives.
Internet Overuse and Personality 18
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personality traits in relation to Internet usage. Computers in Human Behavior , 22 ,
283–293.
Lin, S. J., & Tsai, C. (2002). Sensation seeking and Internet dependence of Taiwanese
high school adolescents. Computers in Human Behavior , 18 , 411–426.
Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological
Internet use among college students. Computers in Human Behavior , 16 , 13–29.
Panksepp, J. (1998). Affective neuroscience: The foundations of human and animal
emotions. Oxford University Press.
Revelle, W., Wilt, J., & Rosenthal, A. (2010). Handbook of Individual Differences in
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G. Matthews, & B. Szymura (Eds.), (chap. Individual differences in cognition: New
methods for examining the personality-cognition link).
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Internet Overuse and Personality 20
Appendix
Additional Tables
Table A1
Table A2
Internet Overuse and Personality 21
Table 1
Descriptive statistics of demographic (for Gender, 1=Male, 2=Female), Internet overuse
(reverse coded items denoted (R)), and Internet use items (for Phone, 1=Does not own a
smart phone, 2=Does own a smart phone, see Appendix Table A1 for other values
n
Mean
SD
Median
Gender
3155
1.64
0.48
2
Educ
11944
3.12
1.05
3
Age
3155
27.76
11.49
24
”I use the Internet so much that it interferes with other activities”
832
2.71
1.65
2
”I use the Internet without really thinking why”
849
3.47
1.72
4
”I never stay online longer than originally intended” (R)
853
2.46
1.47
2
”I have never lost sleep to spend more time online” (R)
821
3.02
1.77
3
”I lose track of time online”
831
3.74
1.66
4
”I rarely miss being online if I cant go on” (R)
870
3.65
1.66
4
”I have trouble completing other tasks when the Internet is accessible”
885
3.07
1.67
3
”Sometimes I would be better off not having access to the Internet”
887
2.99
1.71
3
”My performance at work or school has suffered due to my Internet use”
892
2.38
1.59
2
”I sometimes use the Internet when I should be spending time with
friends or family”
875
3.43
1.69
4
Total
11356
3.35
1.57
3
Work
11329
2.59
1.43
2
Chat
11286
1.82
1.37
1
Social
11300
1.72
1.36
1
Web
11317
1.56
1.25
1
Game
11236
0.72
1.24
0
SocialWho
8009
4.83
1.41
5
Updates
11119
2.9
1.87
3
11374
3.33
2.63
3
Phone
11437
1.51
0.5
2
TotalNonwork
9923
1.06
1.19
1
Internet Overuse and Personality 22
Table 2
Standardized α’s, average item correlation, and number of items for each scale
Standardized α
Average item correlation
Number of items
Extra
0.93
0.40
20
Stab
0.92
0.38
20
Cons
0.92
0.35
20
Agree
0.90
0.31
20
Open
0.86
0.23
20
InternetOveruse
0.86
0.37
10
BIS
0.87
0.39
10
BASFun
0.81
0.30
10
BASDrive
0.79
0.27
10
BASReward
0.74
0.32
6
BAS
0.86
0.19
26
Lonely
0.66
0.39
4
Bored
0.74
0.41
4
Internet Overuse and Personality 23
T
able
3
β
weights
and
R
2
values
of
var
ious
line
ar
re
gr
ession
mo
dels
for
su
bje
ctive
Internet
overuse.
Big
Five
mo
dels
ar
e
comp
ar
ed
to
BIS/BAS
(with
and
without
subsc
ales),
and
demo
gr
aphic,
L
oneliness,
and
Bor
edom
variables
ar
e
adde
d
to
show
their
imp
act
on
p
er
cent
varianc
e
explaine
d
(R
2
.
In
ternetOv
eruse
Mo
del
1
Mo
del
2
Mo
del
3
Mo
del
4
Mo
del
5
Mo
d
e
l
6
Mo
del
7
Mo
del
8
Mo
del
9
Gender
-
0.01
0.01
-
-0.06
-0.04
-
-0.10
-0.06
Age
-
-0.17
-0.15
-
-0.16
-0.12
-
-0.19
-0.15
Educ
-
0.04
0.
04
-
0.03
0.04
-
0.04
0.05
Extra
-0.07
-0.08
-0.09
-
-
-
-
-
-
Stab
-0.18
-0.17
-0.17
-
-
-
-
-
-
Cons
-0.40
-0.37
-0.35
-
-
-
-
-
-
Agree
-0.04
-0.03
-0.04
-
-
-
-
-
-
Op
en
0.08
0.10
0.12
-
-
-
-
-
-
BIS
-
-
-
0.38
0.36
0.32
0.35
0.34
0.29
BASF
un
-
-
-
0.31
0.26
0.22
-
-
-
BASDriv
e
-
-
-
-0.05
-0.06
-0.01
-
-
-
BASRew
ard
-
-
-
-0.14
-0.12
-0.
09
-
-
-
BAS
-
-
-
-
-
-
0.11
0.08
0.12
Lonely
-
-
-0.07
-
-
0.02
-
-
0.07
Bored
-
-
0.10
-
-
0.21
-
-
0.23
R
2
0.250
0.276
0.286
0.1785
0.202
0.242
0.121
0.162
0.221
Internet Overuse and Personality 24
T
able
4
β
weights
and
R
2
values
of
various
line
ar
re
gr
ession
mo
dels
for
hours
p
er
day
sp
ent
using
the
Internet,
not
for
work
or
scho
ol.
Big
Five
mo
dels
ar
e
comp
ar
ed
to
BIS/BAS
(with
and
without
subsc
ales),
and
demo
gr
aphic,
L
oneliness,
and
Bor
edom
variables
ar
e
adde
d
to
show
their
imp
act
on
p
er
cent
vari
anc
e
explaine
d
(R
2
.
T
otalNon
w
ork
Mo
del
1
Mo
del
2
Mo
del
3
Mo
del
4
Mo
d
e
l
5
Mo
del
6
Mo
del
7
Mo
del
8
Mo
del
9
Gender
-
-0.01
0.00
-
-0.06
-0.03
-
-0.09
-0.05
Age
-
-0.07
-0.06
-
-0.10
-0.
07
-
-0.12
-0.08
Educ
-
-0.06
-0.06
-
-0.06
-0.05
-
-0.06
-0.05
Extra
-0.10
-0.11
-0.07
-
-
-
-
-
-
Stab
0.00
0.00
0.02
-
-
-
-
-
-
Cons
-0.23
-0.22
-0.16
-
-
-
-
-
-
Agree
-0.09
-0.
08
-0.05
-
-
-
-
-
-
Op
en
0.05
0.06
0.07
-
-
-
-
-
-
BIS
-
-
-
0.12
0.11
0.06
0.10
0.11
0.
05
BASF
un
-
-
-
0.17
0.13
0.09
-
-
-
BASDriv
e
-
-
-
-0.13
-0.14
-0.
08
-
-
-
BASRew
ard
-
-
-
-0.12
-0.11
-0.07
-
-
-
BAS
-
-
-
-
-
-
-0.04
-0.08
-0.03
Lonely
-
-
0.00
-
-
0.04
-
-
0.06
Bored
-
-
0.19
-
-
0.23
-
-
0.25
R
2
0.095
0.107
0.134
0.048
0.068
0.118
0.014
0.044
0.109
Internet Overuse and Personality 25
T
able
5
β
weights
and
R
2
values
of
demo
gr
aphics,
Big
Five,
L
oneliness,
and
Bor
edom
re
gr
esse
d
on
each
outc
ome
variable.
In
ternetOv
eruse
T
otal
T
otalNon
w
ork
W
ork
Chat
So
cial
So
cialWho
W
eb
Game
W
ebsites
Ph
one
Gender
0.01
0.13
0.00
0.15
0.07
0.10
0.11
0.00
-0.09
-0.08
0.00
0.01
Age
-0.15
0.04
-0.06
0.11
-0.03
-0.18
-0.02
-0.03
0.01
-0.08
0.11
0.02
Educ
0.04
0.04
-0.06
0.07
0.00
-0.02
0.04
0.01
-0.08
0.12
0.20
0.00
Extra
-0.09
-0.10
-0.07
-0.02
0.09
0.10
-0.03
-0.06
-0.08
-0.06
-0.04
0.13
Stab
-0.17
-0.02
0.02
-0.02
-0.05
-0.09
0.01
0.01
0.01
-0.01
-0.04
-0.02
Cons
-0.35
-0.06
-0.16
0.07
-0.04
-0.03
0.01
-0.04
-0.05
-0.03
0.01
0.05
Agree
-0.04
-0.09
-0.05
-0.03
-0.03
-0.02
0.01
-0.
04
-0.07
-0.03
-0.09
-0.05
Op
en
0.12
0.15
0.07
0.06
0.01
-0.04
0.08
0.08
0.03
0.12
0.10
-0.04
Lonely
-0.07
-0.05
0.00
-0.01
-0.07
-0.11
-0.18
0.05
-0.13
0.06
-0.07
-0.02
Bored
0.10
0.08
0.19
-0.09
0.14
0.17
-0.02
0.16
0.19
0.08
-0.05
-0.03
R
2
0.286
0.057
0.134
0.077
0.042
0.125
0.057
0.062
0.085
0.067
0.087
0.021
Internet Overuse and Personality 26
Table 6
β weights and R
2
values of demographics, Big Five, Loneliness, Boredom, interacting with
people first met online, and smart phone ownership regressed on each Internet overuse and
social uses of the Internet.
InternetOveruse
Chat
Social
Game
Gender
0.01
0.10
0.13
-0.07
0.00
Age
-0.15
-0.04
-0.19
0.00
0.11
Educ
0.04
0.01
-0.01
-0.07
0.20
Extra
-0.09
0.07
0.09
-0.09
-0.05
Stab
-0.17
-0.04
-0.08
0.02
-0.04
Cons
-0.35
-0.04
-0.03
-0.05
0.01
Agree
-0.04
-0.03
-0.01
-0.06
-0.08
Open
0.12
0.03
-0.02
0.05
0.10
Lonely
-0.07
-0.13
-0.15
-0.18
-0.06
Bored
0.10
0.14
0.16
0.18
-0.05
SocialWho
0.00
-0.29
-0.21
-0.25
0.01
Phone
-0.01
0.04
0.05
0.02
0.11
R
2
0.29
0.12
0.17
0.15
0.10
Internet Overuse and Personality 27
T
able
A1
Or
dinal
ranges
for
Educ
ation
and
Internet
usage
items.
V
alue
Educ
So
cialWho
T
otal,
W
ork,
Chat,
So
cial,
W
eb,
Games
W
ebsites
(Lev
el
of
education)
(Av
erage
hours
p
er
da
y)
(With
whom
do
y
ou
in
teract
online?)
(Num
b
er
of
w
ebsites
y
ou
regularly
c
hec
k
for
up
dates)
(Av
erage
times
c
hec
k
ed
p
er
da
y)
NA
Not
applicable
0
Less
than
12
y
ears
0
0
0
0
1
High
sc
ho
ol
graduate
O
n
ly
p
eople
first
met
online
less
than
1
1
1
2
Some
college,
did
not
graduate
Mostly
p
eople
first
met
online
at
least
1
but
less
than
2
2
2
3
Curren
tly
attending
college
Sligh
tly
more
p
eople
first
met
online
than
offline
at
least
2
but
less
than
4
3
3
4
College
graduate
Sligh
tly
more
p
eople
first
met
offline
than
online
at
leas
t
4
but
less
than
6
4
4
5
Graduate
or
professional
degree
Mostly
p
eople
first
met
offline
at
least
6
but
less
than
8
5
5
6
Only
p
eople
first
met
offline
at
least
8
but
less
than
10
6-8
6-10
7
at
least
10
but
less
than
12
9-11
11-15
8
at
least
12
but
less
than
14
12-14
16-20
9
more
than
14
14+
21-25
10
26-30
11
31+
Internet Overuse and Personality 28
T
able
A2
R
aw
corr
elations
of
demo
gr
aphics,
sc
ales,
and
Internet
use
items
Gender
Educ
Age
Extra
Stab
Cons
Agree
Open
InternetOv
eruse
BIS
BASF un
BASDrive
BASReward
BAS
Lonely
Bored
T otal
W ork
Chat
Social
W eb
Game
Social
Who
W ebsites
Emai
l
Phone
T otalNon
work
Gender
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Educ
-0.01
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Age
0.01
0.33
1.
00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Extra
0.01
0.00
0.03
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Stab
-0.22
0.04
0.
09
0.31
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Cons
0.
09
0.05
0.20
0.19
0.21
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Agree
0.25
0.02
0.13
0.42
0.20
0.30
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Op
en
-0.09
0.15
0.16
0.24
0.18
0.14
0.22
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
In
t
ernetOv
eruse
-0.01
-0.03
-0.24
-0.20
-0.28
-0.45
-0.21
-0.03
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
BIS
0.28
-0.01
-0.15
-0.37
-0.82
-0.21
-0.01
-0.23
0.33
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
BASF
un
-0.11
-0.10
-0.24
0.38
0.05
-0.24
0.02
0.20
0.17
-0.15
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
BASDriv
e
-0.02
-0.03
-0.
12
0.59
0.11
0.25
0.11
0.35
-0.06
-0.22
0.39
1.
00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
BASRew
ard
0.18
-0.12
-0.12
0.49
-0.01
0.03
0.52
0.13
0.01
0.10
0.42
0.32
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
-
BAS
-0.01
-0.10
-0.21
0.63
0.08
0.01
0.23
0.31
0.06
-0.15
0.82
0.77
0.68
1.00
-
-
-
-
-
-
-
-
-
-
-
-
-
Lonely
-0.05
0.04
0.09
-0.50
-0.29
-0.21
-0.47
0.00
0.13
0.18
-0.12
-0.
18
-0.39
-0.27
1.00
-
-
-
-
-
-
-
-
-
-
-
-
Bored
-0.09
-0.
07
-0.19
-0.32
-0.25
-0.41
-0.34
-0.16
0.32
0.19
0.04
-0.24
-0.08
-0.12
0.23
1.00
-
-
-
-
-
-
-
-
-
-
-
T
otal
0.09
0.06
0.03
-0.11
-0.08
-0.09
-0.08
0.08
0.42
0.10
-0.04
-0.06
-0.08
-0.08
0.07
0.11
1.00
-
-
-
-
-
-
-
-
-
-
W
ork
0.16
0.
12
0.17
0.03
-0.00
0.14
0.08
0.08
0.01
-0.00
-0.12
0.02
-0.05
-0.06
-0.01
-0.15
0.56
1.00
-
-
-
-
-
-
-
-
-
Chat
0.06
-0.
03
-0.08
0.04
-0.07
-0.09
-0.02
-0.03
0.34
0.11
0.07
0.03
0.07
0.08
-0.05
0.14
0.48
0.29
1.00
-
-
-
-
-
-
-
-
So
cial
0.11
-0.11
-0.25
0.05
-0.12
-0.11
-0.01
-0.11
0.38
0.18
0.09
0.03
0.10
0.09
-0.11
0.18
0.41
0.19
0.62
1.00
-
-
-
-
-
-
-
W
eb
-0.04
0.00
-0.05
-0.14
-0.07
-0.13
-0.14
0.
02
0.29
0.11
-0.03
-0.09
-0.11
-0.09
0.14
0.21
0.45
0.26
0.44
0.38
1.00
-
-
-
-
-
-
Game
-0.13
-0.09
-0.08
-0.10
-0.02
-0.14
-0.13
-0.04
0.20
0.01
0.
09
-0.07
-0.03
-0.00
-0.01
0.23
0.30
0.08
0.
31
0.26
0.32
1.00
-
-
-
-
-
So
cial
W
ho
0.11
0.04
0.00
0.10
0.06
0.08
0.14
0.08
-0.04
-0.04
0.04
0.05
0.13
0.09
-0.19
-0.09
-0.16
-0.10
-0.27
-0.19
-0.26
-0.26
1.00
-
-
-
-
W
ebsites
-0.11
0.11
-0.04
-0.11
-0.04
-0.10
-0.12
0.09
0.32
0.08
-0.01
-0.01
-0.07
-0.03
0.13
0.13
0.30
0.12
0.24
0.21
0.35
0.16
-0.15
1.00
-
-
-
-0.01
0.25
0.18
-0.01
0.00
0.05
-0.02
0.12
0.18
0.02
-0.09
0.06
-0.06
-0.03
0.01
-0.07
0.36
0.30
0.23
0.12
0.18
0.00
0.02
0.28
1.00
-
-
Phone
0.01
0.
00
0.02
0.12
0.03
0.07
0.03
-0.01
-0.06
-0.04
-0.02
0.
09
-0.04
0.02
-0.07
-0.07
0.03
0.09
0.05
0.06
0.01
0.01
-0.02
0.00
0.11
1.00
-
T
otalNon
w
ork
-0.06
-0.09
-0.14
-0.17
-0.09
-0.27
-0.19
-0.03
0.43
0.11
0.05
-0.13
-0.08
-0.06
0.13
0.30
0.53
-0.27
0.32
0.34
0.33
0.35
-0.17
0.
22
0.07
-0.04
1.00