





































74

Graduate Student Journal of Psychology
2023, Vol. 21

Copyright 2023 by the Department of Counseling and Clinical Psychology
Teachers College, Columbia University

Social, Behavioral, and Academic Ramifications of 
Video Game Playing in College 

Alexa Camaganacan
Department of Psychology and Philosophy, Texas Woman's University

 Young adults within the college-aged range (18-
25) spend nearly seven hours a week on average play-
ing video games (Limelight, 2019). Video game usage 
has been linked to positive mental health effects in 
both clinical and non-clinical studies as an alternative 
to psychiatric medication as well as reducing symp-
tomology of psychological issues (Carras et al., 2018; 
Fish et al., 2018). Psychological well-being in college 
students may be a significant facet of school perfor-
mance (Punia & Malaviya, 2015). General technology 
usage may also be a facet in determining psychologi-
cal well-being (Barkely et al., 2014; Bjornsen et al., 
2015; Lepp et al., 2014). To fully understand video 
gaming habits and how they may affect college stu-
dents’ academic performance, the psychological fac-
tors associated with well-being should be considered.
Video Game Usage
 Young adults within the college-aged range (18-
25) spend nearly seven hours a week on average playing 
video games (Limelight, 2019). As of 2019, nearly 46% 
of gamers are women (Gough, 2019). Most gamers 
define themselves as ‘casual’ gamers, and mobile de-
vices such as smartphones or tablets are the most used 
means of playing video games. In the US, casual sin-
gle-player games, such as Angry Birds or Candy Crush, 
are the most popular types of games, followed by casu-
al multi-player games (e.g., Words With Friends) and 
First-Person Shooter (e.g., Call of Duty or Overwatch).
Additionally, 56% of frequent gamers play multiplayer 
games, according to the Entertainment Software As-

sociation ([ESA], 2018). Other popular game genres 
include massive multiplayer online (MMO), simula-
tions, real-time strategy (RTS), puzzles, action, stealth 
shooter, combat, sports, role-playing games (RPG), 
and educational games (Thought Catalog, 2015).
 Because of the rising usage of video games, con-
cerns about related psychological issues have been 
discussed. The Diagnostic and Statistical Manual of 
Mental Disorders, 5th Edition (DSM-5) recognized 
Internet Gaming Disorder, or IGD, as a condition 
warranting further research and included symptoms 
such as preoccupation with gaming, continuing to fo-
cus on gaming despite the presence of problems, and 
jeopardizing jobs or relationships due to continued 
gaming (American Psychiatric Association [APA], 
2013). Continued research on IGD notes men are 
more at risk for developing IGD and IGD is frequent-
ly comorbid with other psychological issues such as de-
pression, anxiety, aggression, and obsessive-compulsive 
symptoms (Zajac et al., 2017). Additionally, IGD may 
place an individual at risk for physical health problems, 
such as being overweight or obese, sleep disorders, or 
a heightened risk for seizures (Li et al., 2017). High-
er levels of gameplay time were also associated with 
issues related to psychosocial adjustment and lower 
levels of life satisfaction (Przybylski & Mishkin, 2016).
 Despite the potential issues that arise with poor 
gaming habits, video game usage has been associated 
with certain positive mental health outcomes. In re-
cent years, video games have been used experimentally 

The purpose of this research project is to determine whether video game usage influences the psychological well-be-
ing of college students. This project seeks to understand technology usage habits among students and whether this 
affects school performance. Previous research suggests video games may be used to treat psychological issues such as 
anxiety. Self-report studies note video games were helpful in certain populations in coping with stress, developing 
positive social behaviors, and improving cognitive abilities (Carras et al., 2018; Nuyens et al., 2019; Schuurmans et 
al., 2018;). Since psychological well-being is a crucial factor in academic performance (Carton & Goodboy, 2015; 
Punia & Malaviya, 2015), the current study will examine potential relationships between gaming and college GPAs. 
Poor habits related to technological usage may lead to negative mental health outcomes. A survey examining these 
factors was completed by college students at Texas Woman’s University. The survey was composed of questions from 
the Internet Gaming Disorder Scale, Psychological Wellbeing Scale, and Boundary Management Subscale. Data was 
tested using ANOVAs, a Tukey HSD test as a post hoc test, and Eta squared. The results of the data found gaming 
tendencies were not significantly associated with GPA but were associated with negative mental health outcomes 
and increased issues with technology boundary management. The study has marked limitations, due to the lack of 
non-gaming survey participants and most respondents identifying as female. These findings may be useful for cli-
nicians in treating addictive gaming tendencies. Future research should examine more diverse student populations.
 Keywords: college students, gaming addiction, GPA, boundary management, psychological well being



75

RAMIFICATIONS OF VIDEO GAME PLAYING IN COLLEGE

to treat mental health issues. In one recent study, ca-
sual video game play (CVG) was assigned to patients 
who were prescribed selective serotonin reuptake 
inhibitor (SSRI) medication (Fish et al., 2018). The 
CVG group continued to take medication while uti-
lizing CVG but was compared to a treatment control 
group that only prescribed two forms of medication. 
The results indicate that CVG was effective in treat-
ing symptoms associated with anxiety disorders and 
could be used as an alternative prescription to exten-
sive medication (Fish et al., 2018). In another recent 
study, a video game-based intervention addressed in-
ternalizing problems for youths with behavioral prob-
lems within residential care facilities (Schuurmans et 
al., 2018). The study also explored the psychological 
effects of treatment on youths’ mentors. Both youth 
groups in the study received ongoing psychotherapy 
or prescribed medication as recommended by clini-
cians; however, only the experimental group received 
the game intervention. At the end of the study, the 
group that participated in the video game interven-
tion self-reported improvements in both anxiety and 
externalizing problems immediately after the study 
and at a 4-month follow-up. The study also indicat-
ed improvements in the mentors’ anxiety levels at 
the immediate follow-up (Schuurmans et al., 2018).
 Another form of clinical research on video games 
used game intervention to treat negative mental health 
outcomes and used in-game behavior to predict treat-
ment outcomes. In a study conducted by Wols et al. 
(2018), a video game intervention was used to teach 
children coping methods for anxious behaviors as 
well as define children’s behaviors as “engaged” or 
“avoidant/safety” based on in-game actions (Wols 
et al., 2018). The researchers noted that game-based 
interventions could be useful in tailoring engaging 
interventions for children, and the game itself could 
be useful in recognizing specific anxiety-related be-
haviors to be targeted in therapy (Wols et al., 2018).
 Non-clinical trial research on video game usage 
and positive mental health outcomes have also shown 
notable results. Carras et al. (2018) interviewed mili-
tary veteran gamers about their experiences and how 
gaming assisted with aspects such as coping or well-
being. Most of the individuals in the sample report-
ed post-traumatic stress disorder (PTSD) symptoms 
or some other form of trauma-related issues. While 
many of the veterans reported they used gaming as a 

means of distraction from their mental health issues, 
the interactivity and narrative focus of games can 
help veterans develop insight into their own thoughts 
and feelings, which is useful for clinicians in assessing 
suicidality. Video games offered veterans opportuni-
ties for leadership and social opportunities through 
multiplayer games; these virtual spaces helped vet-
erans develop support systems that are a major ele-
ment in recovery interventions (Carras et al., 2018).
 A Dutch study examined the relationship be-
tween competitive video game usage and children’s 
social development in conduct problems, peer rela-
tions, and prosocial behaviors (Lobel et al., 2019). 
The results did not indicate any significant changes 
in prosocial behaviors but found that children who 
played competitive games reported improvements in 
conduct problems and peer relations. The research-
ers note that competitive gaming in the home en-
vironment should be viewed within the context of 
self-improvement and comradery (Lobel et al., 2019).
 A study conducted by Stiff and Kedra (2018) 
examined the effects of intergroup social video game 
play on reducing prejudice. Participants in the study 
either played the game alone or with an outgroup 
partner and were told their opponent was either 
human or computer-controlled; all participants ro-
tated between the four conditions of the study.
The results of the study indicated that participants 
who played collaboratively with outgroup members 
also reported higher levels of favorability towards 
the outgroup. Stiff and Kedra (2018) concluded the 
findings of their study could be a potential utility of 
video games in reducing prejudice between groups. 
Lastly, specific video games may be useful for im-
proving cognitive functions in specific aspects such 
as top-down control and processing speed (Nuyens 
et al., 2019). Research was compiled from multiple 
studies and focused on specific cognitive aspects such 
as attention, task-switching, and time perception. 
Many studies examined by researchers noted cogni-
tive flexibility relative to task-switching was higher 
in gamers compared to non-gamers and gamers ex-
hibit a higher global attention level and processing 
speed. Lastly, the literature also indicates that gamers 
display higher sub-second time perception, but re-
search in this aspect is still largely limited (Nuyens et 
al., 2019). In general, video games have the potential 
to improve different facets of psychological health.



76

CAMAGANACAN

Psychological Wellbeing and Academics
 Psychological well-being describes multiple fac-
ets of functioning that relate back to overall psycho-
logical health. Psychologist Carolyn Ryff divided 
psychological well-being into six major categories: 
self-acceptance, autonomy, personal growth, positive 
relationships, environmental mastery, and purpose 
in life (Ryff, 2014). Self-acceptance describes a per-
son’s attitudes towards themselves and their ability 
to accept both good and bad qualities. Autonomy is a 
measure of self-determination, independence, and the 
ability to resist societal pressure to think for oneself. 
Personal growth is a person’s feeling of continued de-
velopment and openness to new experiences. Positive 
relationships describe a person’s warm, satisfying, and 
trusting relationship with peers or family as well as the 
capacity to extend empathy to others. Environmental 
mastery measures a person’s sense of mastery and com-
petence in utilizing external activities and opportuni-
ties. Lastly, purpose in life gauges a person’s direction 
in life and long- and short-term goals (Ryff, 2014).
College Students
 Many studies have explored different aspects of 
psychological well-being in college students to identify 
specific internal or external factors that affect students’ 
well-being. A study conducted by Ludban in 2015, 
based on Ryff’s categories, measured the psychological 
well-being of a sample of college students to under-
stand the positive and negative factors that influence 
their psychological health. The results of this study sug-
gest gender, age, support, and financial welfare are the 
primary aspects that predict psychological well-being 
in college students. Receiving support from family or 
friends, especially in specific circumstances for non-tra-
ditional students, is a significant factor in lowering stress 
and maintaining emotional mastery (Ludban, 2015).
 Researchers have also examined the relation-
ship between psychological instability and the pro-
pensity for developing psychological issues such as 
depression in an undergraduate sample (Gable & 
Nezlek, 1998). Students reported on facets of their 
psychological health such as anxiety, self-esteem, 
and causal uncertainty. Results indicated students 
who reported lower levels of psychological well-be-
ing were at a higher risk for depression. Additional-
ly, while the relationship between daily adjustment 
and depression risk is complex, day-to-day insta-
bility should be considered to fully understand the 

trajectory of depression (Gable & Nezlek, 1998).
 Specific lifestyle aspects of psychological well-be-
ing have also been examined (Ozpolat et al., 2012). 
The researchers utilized a lifestyle inventory to mea-
sure and categorize students’ lifestyles into five sub-di-
mensions: control, perfectionism, pleasing, self-es-
teem, and expectations. Findings indicated students 
with low self-esteem and need-to-please lifestyles are 
at a greater risk of negative psychological wellbeing 
outcomes, compared to students who are expecta-
tion-oriented. Students who fit this lifestyle criteria 
may still maintain positive relationships with others 
but may do so at the cost of their own desires and 
well-being (Ozpolat et al., 2012). Additional findings 
indicated that students who engaged in task-orient-
ed coping strategies also self-reported higher levels of 
psychological well-being (Punia & Malaviya, 2015).
Academic Performance
 Studies examining the relationship between psy-
chological well-being and college students’ academic 
performance have been mixed. For example, the con-
nection between the academic performance of first-
year undergraduate students and their psychological 
well-being was examined (Topham & Moller, 2011). 
Results did not indicate an association between psy-
chological well-being and academic performance at 
the end of the first year, but students with clinical 
levels of personal concerns may still be at risk for de-
veloping psychological health problems (Topham & 
Moller, 2011). A similar study conducted in 2015 by 
Punia and Malaviya also examined the relationship 
between college students’ academic performance 
and psychological well-being. The results indicat-
ed that while most of the participants self-reported 
medium levels of well-being and average academic 
performance, those who reported medium or high 
levels of academic performance also reported higher 
levels of psychological well-being. In general, psycho-
logical well-being can affect both broad and specific 
areas of a college student’s academic performance.
 Although IGD symptoms may make it difficult 
for an individual to prioritize school responsibilities 
over gaming, research examining the effects of video 
game usage on academic performance has varied re-
sults. An early study from 2007 attempted to explore 
the correlation between academic performance and 
overall time spent on gaming. Anand’s study utilized 
SAT scores and overall GPA as a gauge of academic 



77

RAMIFICATIONS OF VIDEO GAME PLAYING IN COLLEGE

performance. The results of Anand’s analysis showed 
that extensive gaming habits had a negative impact on 
both GPA and SAT scores. However, Anand empha-
sizes that SAT scores only represent a single instance 
of academic performance and extrapolating conclu-
sions may be difficult (Anand, 2007). A 2014 study 
conducted by Drummond and Sauer examined col-
lected data from adolescents to view the effect size of 
video game usage on academic achievement in science, 
mathematics, and reading. Across the data, differences 
in academic performance were negligible although the 
researcher noted that reading performance did show 
a noticeable decline but did not reach the cutoff level 
(Drummond & Sauer, 2014). A longitudinal German 
study from 2018 also examined the long-term effects 
of extensive gaming time on a sample of adolescents. 
Gnambs et al. (2018) specifically looked at the effects 
of the amount of time students spent playing com-
puter games on their overall grade performance and 
competencies in math and reading. The study results 
indicated that students who played games most fre-
quently would have a decline in grades in the proceed-
ing years, but they did not show marked decreases in 
math and reading competencies (Gnambs et al., 2018).
 A few studies found that moderate video game 
use may be beneficial for skills related to academic de-
velopment. One study from 2013 explored the effects 
of strategic games (i.e., specifically strategy or RPGs) 
on students’ self-reported problem-solving skills over 
time. Adachi and Willoughby (2013) found students 
who played strategy games predicted higher levels of 
problem-solving skills. The researchers also noted that 
higher problem-solving skills were associated with 
higher levels of academic achievement in students 
(Adachi & Willoughby, 2013). Another study by Przy-
bylski and Mishkin (2016) examined the difference in 
effects of overall game time on adolescents’ behavior, 
as well as comparing students who play cooperative 
games versus single-player games. Students in the sam-
ple who played for less than an hour a day had lower 
levels of conduct issues and hyperactivity, but students 
who played for more than three hours a day had higher 
levels of behavioral issues. Additionally, students who 
primarily played single-player games had lower levels 
of behavioral problems and higher levels of academ-
ic achievement; students who played cooperative or 
competitive games were more emotionally stable and 
reported better relationships with their peers (Przy-

bylski & Mishkin, 2016). Ventura et al.’s online study 
from 2013 compared the levels of persistence with 
tasks exhibited by gamers compared to non-gamers. 
During the study, persistence was measured using 
anagram or riddle tasks, which were correlated with 
a self-reported measure of persistence and examined 
alongside self-reported levels of gaming time. Individ-
uals who reported higher levels of gaming time spent 
longer time persisting on tasks (Ventura et al., 2013).
 Further research has examined the link between 
psychological well-being and aspects of school perfor-
mance. For example, the exploration of the concept of 
belongingness at a university, and how it is affected by 
students’ values, university norms, health, and academic 
outcomes have been examined (Suhlmann et al., 2018). 
Findings indicate that a sense of belongingness at a 
university contributes to overall psychological well-be-
ing and reduces dropout intention. Furthermore, a 
dignity self-construct is a major aspect of the relation-
ship between student belongingness and the norms 
and values of the university (Suhlmann et al., 2018).
 In addition to university retention, psycholog-
ical well-being also affects the way students are in-
volved in classroom participation (Carton & Good-
boy, 2015). Carton and Goodboy’s (2015) study 
examine how psychological issues such as depression, 
stress, and anxiety affect interaction involvement, 
and how these results could extrapolate to a class-
room setting. The results indicated stress and depres-
sion were both negatively related to responsiveness 
and attentiveness, while anxiety was only related to 
attentiveness. It was concluded that these results 
could interfere with student class performance with 
symptomatology such as rumination, exhaustion, 
and poor sleep quality (Carton & Goodboy, 2015).
Problematic Technology Usage
 Psychological health can be greatly affected by dif-
ferent forms of technology usage. Emerging literature 
has coined the phenomenon of technostress, which 
describes the struggles associated with adapting or cop-
ing with technologies in a healthy manner (La Torre et 
al., 2019). While emerging studies primarily focus on 
technostress because of workplace stress, technostress 
can be considered in other aspects of life. Specific forms 
of non-work-related technostress primarily stem from 
excessive usage of social networking services (SNS) and 
include issues such as communication or social inter-
action overload, internet multitasking, and compulsive 



78

CAMAGANACAN

usage of smartphones. In a professional environment, 
technostress can lead to issues with psychological 
well-being such as worry, self-criticism, and a negative 
self-view (La Torre et al., 2019). Non-work-related 
technostress can result in conflicts between family and 
technology or work and technology. Furthermore, per-
ceived stress stemming from technostress can lead to 
burnout, depression, or anxiety (La Torre et al., 2019). 
While current research on technostress is largely fo-
cused on work-related contingencies, non-work-relat-
ed technostress is also important to consider given the 
major psychological effects of technostress symptoms.
Personality and Developmental Trends
 While not explicitly labeled under the techno-
stress definition, many studies have examined the 
psychological effects of technology dependency and 
personal factors that may be related to problematic 
technology usage. A study conducted by Montag et 
al. (2014) explored how personality factors may affect 
smartphone usage in college students. The researchers 
measured phone usage within their sample as well as 
participants’ personality factors based on the big five 
personality traits (i.e., openness, conscientiousness, 
extraversion, agreeableness, and neuroticism). The re-
sults of the study indicated extraversion was highly as-
sociated with higher levels of phone usage (Montag et 
al., 2014). A similar study conducted by Hsiao (2017) 
also explored the correlates of technology usage with 
the big five personality traits. However, this study also 
included traits such as materialism and external locus 
of control, and technology usage was specified as com-
pulsive usage of SNS and mobile game applications. 
Findings indicated that neuroticism, materialism, ex-
traversion, and locus of control increase compulsive 
usage of SNS apps, while agreeableness, materialism, 
and locus of control influence the usage of game apps 
(Hsiao, 2017). Similarly, researchers have also exam-
ined phone usage in a young adult sample to under-
stand individual differences in personality traits as it 
pertains to smartphone usage (Harari et al., 2019). 
Once again, extraversion was associated with higher 
levels of social behaviors, and thus more technology 
usage. Results showed openness to be associated with 
higher levels of social behaviors (Harari et al., 2019).
 Tams et al. (2018) explored issues of locus of con-
trol in the context of technology dependency. In partic-
ular, the study describes the issue of Nomophobia, or 
the fear of not being able to access one’s smartphone, 

and correlations with technostress. In a work setting, 
technostress can lead to phone dependency, which in 
turn may result in Nomophobia and additional stress. 
However, when situational certainty is established, the 
effects of Nomophobia may decrease (Tams et al., 2018).
 The effects of technology usage on adolescent psy-
chological well-being has garnered much attention in 
recent years. For example, Twenge et al. (2018) mea-
sured self-reported levels of technology usage in mul-
tiple domains such as television viewing habits and 
new media screen activities and compared these usage 
levels to measures such as psychological well-being 
and levels of in-person interaction. Results indicat-
ed psychological well-being decreased as adolescent 
technology usage increased during the four-year pe-
riod. Additionally, non-technology-based activities, 
such as using print media or sports and exercise that 
were associated with higher levels of psychological 
well-being declined over time (Twenge et al., 2018).
 Several studies have noted the issues of problem-
atic technology use in college students. De Leo and 
Wulfert (2013) explored the tenants of problematic 
Internet use (PIU) and how PIU relates to other ex-
ternalizing negative behaviors such as illicit drug use or 
risky sex in a college student sample. The researchers 
found that PIU was not highly correlated with other 
forms of externalizing behaviors, and furthermore did 
not increase antisocial behaviors or affect academic per-
formance. However, PIU behaviors were suggested to 
be risky for students who are experiencing socially anx-
ious or withdrawn behaviors and may lead to interfer-
ences in daily functioning (De Leo & Wulfert, 2013). 
Beranuy et al. (2009) explored correlates between 
problematic Internet and phone use with perceived 
emotional intelligence and psychological distress. 
Findings indicated students who display higher levels 
of psychological distress also engage in higher levels of 
problematic technology use. Additionally, higher lev-
els of attention to emotion, a component of emotional 
intelligence, were also associated with higher levels of 
maladaptive technology usage (Beranuy et al., 2009).
 Specific fields of study may put students at risk 
for experiencing more symptoms of technostress. 
For instance, students in more technology-heavy 
fields of study, such as journalism and broadcasting, 
report higher levels of maladaptive technology us-
age, and female students show more consequences 
of maladaptive technology use than male students 



79

RAMIFICATIONS OF VIDEO GAME PLAYING IN COLLEGE

(Beranuy et al., 2009). Bjornsen and Archer (2015) 
further explored the relationship between academic 
performance and problematic technology usage. Their
study examined the in-class phone usage of a sample 
of college students and how the usage correlated with 
students’ test scores. Results indicated phone usage 
was significantly negatively correlated with test scores 
and using a phone during class for social networking 
purposes was the activity most associated with lower 
test scores (Bjornsen & Archer, 2015). Similarly, Leep 
et al. (2014) examined the relationship between college 
students’ cell phone usage and their quality of life, and 
how GPA and anxiety mediate the relationship. The 
study found students with higher levels of cell phone 
usage had lower GPAs, higher levels of anxiety, and 
overall lower levels of perceived quality of life. The 
researchers noted at the end of their study that recog-
nizing the relationship between quality of life and cell 
phone usage is important for high-usage students to 
reflect on their habits (Lepp et al., 2014). In general, 
college students with poor mental health are more like-
ly to engage in maladaptive technology-use behaviors, 
which may also affect their academic performance.

The Current Study
 The purpose of this study is to examine the rela-
tionship between gaming, psychological well-being, 
and GPA in a college student sample. Previous re-
search indicates that video games have the potential 
to improve psychological well-being, but a poor rela-
tionship with technology may have negative psycho-
logical and academic consequences. The researcher is 
interested in seeing if students who play video games 
casually (CVGs) report higher levels of psychologi-
cal well-being compared to non-gamers (NGs) and 
gamers meeting the criteria for internet gaming dis-
order (AGs). Additionally, the researcher seeks to 
compare academic performance via GPAs between 
the three groups. Lastly, the researcher wishes to see 
if AGs also  have more issues with technology bound-
ary management compared to casual gamers and non-
gamers. This research adds to the existing literature 
about the relationship between psychological health, 
academic performance, and video game use as well as 
video games as a factor contributing to technostress.
Hypotheses
1. Is there a relationship between gaming and 

subjective well-being in college students? H1: 

CVGs will report higher personal well-being 
compared with AGs and NGs. H2: NGs will 
report higher subjective well-being than AGs.

2. Is there a relationship between GPA and game 
usage among college students? H1: NGs will 
have a higher GPA compared with AGs and 
CVGs. H2: CVGs will have a higher GPA 
compared with AGs.

3. Is there a relationship between technology 
boundary management and gaming? H1: 
NGs will have lower levels of boundary man-
agement problems compared with AGs and 
CVGs. H2: CVGs will have lower levels of 
boundary management problems compared 
with AGs.

Methods
 Data was collected from a sample of undergrad-
uate students attending Texas Woman’s University. 
The survey was published online using the PsychDa-
ta Survey program after obtaining approval by the 
Institutional Review Board. The survey was used to 
collect self-reported data from students. The survey 
protocol included psychometric instruments as well 
as demographic measures. Participants electronical-
ly provided informed consent before participating in 
the survey and received SONA credits as an incentive 
to participate. The inclusion criteria required partici-
pants to be 18 years or older and currently enrolled in 
classes for the semester. Participants who did not meet 
the minimal age range were excluded. The data were 
examined using IBM’s Statistical Package for Social 
Sciences (SPSS). Demographics of interest included 
age, gender, ethnicity, current number of credit hours, 
current GPA, types of video games played, specif-
ic genres of games played, whether the student plays 
games online or not, and number of hours played in a 
week. Groups were defined as NGs, AGs, and CVGs. 
NGs (non-gamers) are students who did not report 
playing video games at all. AGs (addicted gamers) are 
students who reported playing video games and met 
the minimum criteria for Internet Gaming Disorder 
based on their responses. Lastly, CVGs (casual gamers) 
are students who reported playing video games but did 
not meet the criteria for Internet Gaming Disorder.
 The sample consisted mostly of Hispanic and 
Latino students (33.5%) followed by White (25.7%), 
Black and African American (20.4%), and other 



8080

CAMAGANACAN

ethnicities (20.4%). The mean age of students in 
the sample was 19.4 years (SD = 1.7). The gender 
ratio of the sample was 93.2% female, 6.5% male, 
and 0.3% non-binary or other. On average, stu-
dents reported taking 13.8 credit hours (SD = 2.3) 
and had 3.3 GPAs (SD = 0.7). Students played 2.4 
hours of video games a week on average (SD = 1.0).
Measures
 The degree of gaming addiction in the sample was 
measured with the Internet Gaming Disorder Scale 
(IGD Scale). The IGD Scale (Lemmens et al., 2015) is a 
27-item measure with a yes/no dichotomous scale. The 
IGD Scale is used to measure behaviors consistent with 
internet gaming disorder, such as overt preoccupation 
or persistence with gaming. The dichotomous version 
of the scale is internally consistent and possesses good 
criterion-related validity, with a Cronbach’s alpha of 
.93 (Lemmens et al., 2015). More yes answers indicate 
more symptoms of IGD. An example of an item on the 
IGD Scale is “During the last year, have you been feeling 
tense or restless when you were unable to play games?” 
The DSM-5 notes that, while the IGD diagnosis 
usually involves behaviors related to specific Internet 
games, it can involve non-Internet games (APA, 2013).
Additionally, the DSM-5 recognizes nine crite-
ria for IGD: preoccupation, tolerance, withdrawal, 
persistence, escape, problems, deception, displace-
ment, and conflict, as defined in Table 1 below. The 
DSM-5 recommends a minimal threshold of ex-
periencing five or more criteria for diagnostic pur-
poses. As a result, addicted gamers, or AGs, are de-
fined as gamers who meet this minimal threshold.
 Perceived well-being will be measured with the 
Psychological Wellbeing Scale (PWB Scale; Ryff & 
Keyes, 1995). The shortened version of the PWB Scale 
was utilized and consists of 18 items on a seven-point 
Likert-type scale with anchors ranging from one 
(strongly agree) to seven(strongly disagree). This ver-
sion of the PWB Scale has lower internal consistency 
but higher factorial validity; the scale has a Cronbach’s 
Reliability over .88 (Lee et al., 2019). The PWB Scale 
is used to gauge psychological well-being in adults 
across multiple subscales including relationships with 
others and personal growth. We used all scales of the 
measure to determine how students perceive their psy-
chological well-being. Higher scores indicate lower lev-
els of perceived psychological well-being. An example 
of an item is “When I look at the story of my life, I 

am pleased with how things have turned out so far.”
 The Boundary Management Subscale (Asbury 
et al., 2018) is a nine-item measure with a three-point 
Likert-type scale with anchors ranging from one (nev-
er) to three (always). The Boundary Management 
Subscale has convergent reliability and internal con-
sistency with a Cronbach’s Alpha over .70 (Asbury et 
al., 2018). The Boundary Management Scale is used 
to measure boundary management behaviors relat-
ed to technology use. Higher scores indicate more 
issues with boundary management. An example of 
an item is “When I go online, I lose track of time.”

Results
Data Cleaning
 Before conducting our analysis, the data was 
screened for outliers and missing data. Eight stu-
dents were removed who were under the minimum 
age range or missing demographic information, 
32 for missing significant portions of the PWB or 
BM surveys, and an additional 129 duplicate re-
sponses. A total of 169 responses were removed 
from the data set, and the final total sample was 
382. Data met all assumptions regarding normality.
 Overall, app games made up 34.4% of usage, 
gaming consoles represented 35%, and PC gaming at 
30.7%. Most students who participated preferred one 
gaming platform type (42.6%), with 38.3% using two 
types, and 18.9% stated they played all three. The re-
ported favored game genre within the sample was casu-
al multi-player (46.4%) followed by causal single-play-
er (30.1%), sports (4.9%), and RPG (4.6%). The full 
spread of demographics can be seen in Table 2 below.
Data Analysis
 An ANOVA was conducted to test each of the 
hypotheses. The three gaming groups served as the 
independent variables, while psychological well-be-
ing, GPA, and boundary management served as the 
dependent variables. This analysis was used to exam-
ine potential differences between gaming usage and 
the dependent variables of psychological well-being, 
GPA, and boundary management respectively. After 
running the ANOVAs, group means were compared 
by running post-hoc tests. A Tukey HSD test was uti-
lized as a conservative post hoc test for identifying sig-
nificant main effects and interactions. Eta squared was 
also used to calculate the effect sizes between our means 
and measure the relationship between our variables.



81

RAMIFICATIONS OF VIDEO GAME PLAYING IN COLLEGE

 A one-way between-subjects ANOVA was con-
ducted to compare subjective well-being between 
non-gamers, addicted gamers, and casual gamers. 
There was a significant main effect of gaming time 
on personal well-being [F(2, 370) = 3.69, p = 0.03)]. 
Post-hoc comparisons using the Tukey HSD test in-
dicated that the mean well-being score for AGs (M = 
92.45, SD = 13.57, n = 202) was significantly different 
than the scores for CVGs (M = 96.14, SD = 13.32, 
n = 141). However, NGs’ scores did not significant-
ly differ from either AGs or CVGs (M = 91.13, SD 
= 14.34, n = 30). Taken together, these results indi-
cate that gamers who met the criteria for addiction 
were more likely to report overall lower levels of sub-
jective well-being compared to casual gamers. Non-
gamers do not appear to report significantly better 
well-being than addicted gamers or casual gamers.
 A second one-way ANOVA was conduct-
ed to compare GPA between NGs (M = 3.31, 
SD = 0.55, n = 28), AGs (M = 3.25, SD = 
0.68, n = 203), and CVGs (M = 3.38, SD
= 0.62,  n = 138). There was no significant main effect of 
gaming on GPA [F(2, 366) = 1.54, p = 0.22]. As a result, 
gaming habits were not found to affect a student’s GPA.
 The final one-way ANOVA was conducted to 
compare boundary management levels between gam-
er types. There was a significant main effect of gam-
ing on boundary management [F(2, 379) = 8.97, p = 
0.00]. Post-hoc comparisons using the Tukey HSD 
test indicated that the mean boundary management 
score for AGs (M = 1.99, SD = 0.32, n = 208), was 
significantly different than boundary management 
scores for CVGs (M = 1.84, SD = 0.31, n = 142). 
NGs’ scores (M = 1.95, SD = 0.33, n = 32) did not
significantly differ from either AGs or CVGs. 
These results indicate that gamers who met
the criteria for addiction are more likely to self-re-
port more problems with technology bound-
ary management than casual gamers. The results 
of my ANOVAs can be seen below in Table 3.

Discussion
 The current study examined the relationship be-
tween gaming, psychological well-being, GPA, and 
technology boundary management. The researcher 
hypothesized addicted gamers would report lower 
levels of well-being, lower GPAs, and more strug-
gles with technology boundary management com-

pared to non-gamers and casual gamers. The re-
searcher also hypothesized non- gamers would 
report higher levels of well-being, higher GPAs, 
and fewer struggles with boundary management 
compared to casual gamers and addicted gamers.
 The analyses supported two of the three hy-
potheses. Definite conclusions could not be drawn 
about the NGs in the sample because of the few 
responses from NGs. However, the results suggest 
differences in psychological well-being and bound-
ary management between the AGs and CVGs. The 
researcher expected GPA to also be significantly dif-
ferent between AGs and CVGs, but gaming did not 
appear to be a factor related to grades in college. The 
non-significant findings between GPA and gaming 
tendencies may be due to the sample. Texas Wom-
an’s University has a primarily female student pop-
ulation, and previous research on gender and GPA 
performance notes that women in general tend to 
have higher GPAs than men (Keiser et al., 2016). In 
turn, perhaps there is a ceiling effect in the sample 
where women’s higher GPA may be due to increased 
abilities to self-discipline for academia (Duckworth 
& Seligman, 2006). The predominantly female sam-
ple may be useful to emerging research, as current 
studies on IGD seem to focus on male samples, 
and being male is often concluded to be a signifi-
cant predictor of the disorder (Carlisle et al., 2019; 
Männikkö et al., 2019). A 2020 study compared a 
sample of male and female gamers and problemat-
ic technology usage towards video games or social 
media usage. The study found that female gamers 
tended to engage in problematic social media usage, 
while males were more likely to have problematic 
gaming tendencies (Cudo et al., 2020). An attempt 
at re-running the ANOVAs sans male participants 
(n = 26) resulted in no significant changes in out-
comes. As IGD is still an emerging disorder, with 
little research focused on female-exclusive samples 
thus far, the researcher would caution against the 
generalization of the findings related to academic 
performance and IGD. However, future research on 
IGD in female samples may want to continue focus-
ing on the overlap between IGD and problematic 
technology usage, particularly with social media.
 Current findings do support the literature 
suggesting IGD is often comorbid with other psy-
chological issues and problematic technology use 



82

is associated with worse psychological outcomes. A 
longitudinal study on adolescents’ pathological game 
usage noted that students with initially moderate 
symptoms were at a higher risk of developing increas-
ing symptoms over time, including specific issues such 
as anxiety, depression, and problematic phone usage 
(Coyne et al., 2020). Another study noted additional 
correlations between addicted technology usage and 
psychological disorders, with men being more vul-
nerable to video game addiction and women to prob-
lematic social media usage (Andreassen et al., 2016). 
Recognizing the overlap between IGD and technol-
ogy boundary management is also an important step 
in research, as recognizing symptoms and related ef-
fects for both areas is still limited (Zajac et al., 2017).
 The preference towards game consoles within the 
sample is curious, as current research on gaming addic-
tion is primarily centered around online gaming. On-
line games are in constant development, which encour-
ages players to play often and play for long periods of 
time. Furthermore, online games offer prolonged op-
portunities to interact with other people online. Both 
factors may contribute to addictive gaming tendencies 
(Yildiz, 2019). Additionally, greater concerns are being 
levied about mobile game addiction. One study theo-
rizes that mobile gaming addiction may be the result 
of phubbing, a phenomenon that results from indi-
viduals using phones at the behest of in-person social
interaction (Yam & İlhan, 2020). This study also 
notes phubbing refers to the overlapping ef-
fects of mobile gaming, social media, internet, 
and phone addiction, which ties back to some 
of the previously discussed issues with technost-
ress. Considering the preferred console of choice 
may be a point of interest in future IGD research.
 Also, of interest within the sample is the high 
number of respondents who identified as Hispanic 
or Latino. Texas Woman’s University has a high pop-
ulation of Latino and Hispanic students, estimated 
to be around 28.3% of the total student population 
([TWU], 2020). Again, while current IGD research 
is limited, the few ethnocentric studies have primari-
ly focused on Asian countries such as China or Korea 
due to extreme cases of game addiction leading to the 
death of an individual (Chen et al., 2018). According 
to the National Alliance on Mental Illness (NAMI), 
Hispanics and Latinos seek out mental health services 
less than the rest of the adult population. Delays in 

seeking treatment often lead to worse psychological 
health outcomes. Additionally, common psycholog-
ical issues within these communities include gener-
alized anxiety disorder, depression, post-traumatic 
stress disorder, and substance abuse (NAMI, 2020). 
Understanding the inherent mental illness risks within 
the Hispanic and Latino communities may be useful 
for clinicians in treating IGD within the population.
 Another area of focus to consider is the reason why 
students may be motivated to play video games. Broad-
er research points to a variety of factors that contribute 
to player enjoyment such as the pleasure and satisfac-
tion from executing a behavior, entertainment, and 
the ability to socialize with others (Hsu & Lu, 2004). 
Video games can also empower individuals, particular-
ly if an individual lives in an uncertain environment 
(King & Delfabbro, 2009). Additionally, personality 
and motivational factors can account for individual en-
gagement in gaming (King & Delfabbro, 2009). Lastly, 
gaming may be used as a coping strategy for stress or 
other forms of psychological issues, though inherent 
disorders may put an individual at risk for gaming ad-
diction (Chang et al., 2019; Kircaburun et al., 2019). 
Gaming motivation often differs between individu-
als but may account for the likelihood of addiction.
Limitations
 This study is subject to several limitations. Data 
collected for the study was self-reported and sub-
jected to response bias. Additionally, the study was 
quasi-experimental and causality cannot be inferred. 
Social desirability bias may have affected partici-
pant responses to the survey. This study also has 
limited generalizability because the sample primar-
ily consists of Hispanic and Latino female college 
students. Due to the nature of the study, few NGs 
participated, which made it difficult to draw con-
clusions about NGs compared to AGs and CVGs.
Future Research
 Future research should address the design limita-
tions by expanding to college populations from other 
geographic regions to see how the model generalizes to 
other college students outside of the southern Unit-
ed States area. Additionally, further research should 
include more comparison data taken from non-
gamers, as well as more male and non-binary gamers 
and gamers of other ethnicities. A longitudinal study 
should be considered to understand the long-term ef-
fects of gaming on GPA and well-being to better permit 

CAMAGANACAN



83

causal inferences to be made. It may also be of inter-
est to expand the research population beyond college 
students and examine working adults’ usage of video 
games, and how usage relates to technology bound-
ary management and affects perceived wellbeing.
Conclusion
 The study underscores the effects of IGD in the 
lives of students and provides insight into how IGD 
correlates with perceived psychological well-being and 
technology boundary management. Both psychologi-
cal well-being and boundary management significant-
ly correlate with gaming. Although the study does not 
fully address IGD psychological issues, the study offers 
valuable insight into understanding IGD and its related 
effects on mental health. Despite limitations, the study 
shows that issues with technology boundary manage-
ment and lowered subjective well-being are associated 
with addicted gaming. Both factors should be evalu-
ated during the treatment of IGD. Clinicians should 
consider the overlap between technology boundary 
management and addicted gaming tendencies, as well 
as incorporate interventions to improve well-being.

References
Adachi, P. J., & Willoughby, T. (2013). More than just 

fun and games: The longitudinal relationships 
between strategic video games, self-reported prob-
lem-solving skills, and academic grades. Journal of 
Youth and Adolescence, 42(7), 1041-1052. https://
doi.org/10.1007/s10964-013-9913-9

American Psychiatric Association. (2013). Diagnostic 
and Statistical Manual of Mental Disorders (5th 
ed.). Arlington, VA: American Psychiatric Pub-
lishing.

Anand, V. (2007). A study of time management: 
The correlation between video game usage and 
academic performance markers. CyberPsychol-
ogy & Behavior, 10(4), 552-559. https://doi.
org/10.1089/cpb.2007.9991

Andreassen, C. S., Billieux, J., Griffiths, M. D., Kuss, 
D. J., Demetrovics, Z., Mazzoni, E., & Pallesen, 
S. (2016). The relationship between addictive use 
of social media and video games and symptoms of 
psychiatric disorders: A large-scale cross- section-
al study. Psychology of Addictive Behaviors, 30(2), 
252. https://doi.org/10.1037/adb0000160.

Asbury, E. T., Casey, J., & Desai, K. (2018). Family 
eJournal: benefits of online guided group journal-

ing for women. Journal of Public Mental Health, 
17(3), 135-141. https://doi.org/10.1108/JPMH-
01-2018-0008

Beranuy, M., Oberst, U., Carbonell, X., & Chamar-
ro, A. (2009). Problematic Internet and mobile 
phone use and clinical symptoms in college stu-
dents: The role of emotional intelligence. Com-
puters in Human Behavior, 25(5), 1182-1187. 
https://doi.org/10.1016/j.chb.2009.03.001

Bjornsen, C. A., & Archer, K. J. (2015). Relations be-
tween college students’ cell phone use during class 
and grades. Scholarship of Teaching and Learning 
in Psychology, 1(4), 326. https://doi.org/10.1037/
stl0000045

Carlisle, K. L., Neukrug, E., Pribesh, S., & Krah-
winkel, J. (2019). Personality, motivation, and 
internet gaming disorder: Conceptualizing the 
gamer. Journal of Addictions & Offender Coun-
seling, 40(2), 107–122. https://doi- org.ezp.twu.
edu/10.1002/jaoc.12069

Carras, M. C., Kalbarczyk, A., Wells, K., Banks, J., 
Kowert, R., Gillespie, C., & Latkin,C. (2018). 
Connection, meaning, and distraction: A qualita-
tive study of video game play and mental health 
recovery in veterans treated for mental and/or be-
havioral health problems. Social Science & Med-
icine, 216, 124-132. https://doi.org/10.1016/j.
socscimed.2018.08.044

Carton, S. T., & Goodboy, A. K. (2015). College stu-
dents’ psychological wellbeing and interaction 
involvement in class. Communication Research 
Reports, 32(2), 180-184. https://doi.org/10.1080
/08824096.2015.1016145

Chen, K. H., Oliffe, J. L., & Kelly, M. T. (2018). 
Internet gaming disorder: An emergent 
health issue for men. American Journal of 
men's Health, 12(4), 1151-1159. https://doi.
org/10.1177/1557988318766950

Coyne, S. M., Stockdale, L. A., Warburton, W., Gen-
tile, D. A., Yang, C., & Merrill, B.M. (2020). Patho-
logical video game symptoms from adolescence to 
emerging adulthood: A 6-year longitudinal study 
of trajectories, predictors, and outcomes. Develop-
mental Psychology, 56(7), 1385–1396. https://doi.
org/10.1037/dev0000939

Cudo, A., Torój, M., Misiuro, T., & Griffiths, M. D. 
(2020). Problematic Facebook use and problem-
atic video gaming among female and male gamers. 

RAMIFICATIONS OF VIDEO GAME PLAYING IN COLLEGE



84

Cyberpsychology, Behavior, and Social Network-
ing, 23(2), 126-133. https://doi.org/10.1089/cy-
ber.2019.0252

De Leo, J. A., & Wulfert, E. (2013). Problematic In-
ternet use and other risky behaviors in college stu-
dents: An application of problem-behavior theo-
ry. Psychology of Addictive Behaviors, 27(1), 133. 
https://doi.org/10.1037/a0030823

Drummond, A., & Sauer, J. D. (2014). Video-games 
do not negatively impact adolescent academic 
performance in science, mathematics, or reading. 
PloS One, 9(4), e87943. https://doi.org/10.1371/
journal.pone.0087943

Duckworth, A. L., & Seligman, M. E. (2006). Self-dis-
cipline gives girls the edge: Gender in self-disci-
pline, grades, and achievement test scores. Journal 
of Educational Psychology, 98(1), 198. https://doi.
org/10.1037/0022-0663.98.1.198

Electronic Software Association (2018). 2018 Essen-
tial Facts about the Computer and Video Game In-
dustry. Retrieved from http://www.theesa.com/
esa-research/2018- essential-facts-about-the-com-
puter-and-video-game-industry/

Fish, M. T., Russoniello, C. V., & O’Brien, K. (2018). 
Zombies vs. anxiety: An augmentation study of 
prescribed video game play compared to med-
ication in reducing anxiety symptoms. Simu-
lation & Gaming, 49(5), 553-566. https://doi.
org/10.1177/1046878118773126

Gable, S. L., & Nezlek, J. B. (1998). Level and in-
stability of day-to-day psychological well-being 
and risk for depression. Journal of Personality 
and Social Psychology, 74(1), 129. https://doi.
org/10.1037/0022-3514.74.1.129

Gnambs, T., Stasielowicz, L., Wolter, I., & Appel, M. 
(2018). Do computer games jeopardize education-
al outcomes? A prospective study on gaming times 
and academic achievement. Psychology of Popular 
Media Culture, 9(1), 69–82. https://10.31234/
osf.io/2s8rv

Gough, C. (2019). U.S. computer and video gamers 
from 2006-2019, by gender. Retrieved from 
https://www.statista.com/statistics/232383/gen-
der-split-of-us- computer-and-video-gamers/

Harari, G. M., Müller, S. R., Stachl, C., Wang, R., 
Wang, W., Bühner, M., … Gosling, S.D. (2019). 
Sensing sociability: Individual differences in young 
adults’ conversation, calling, texting, and app use 

behaviors in daily life. Journal of Personality and 
Social Psychology, 119(1), 204–228. https://doi- 
org.ezp.twu.edu/10.1037/pspp0000245.supp

Hsiao, K. L. (2017). Compulsive mobile application 
usage and technostress: The role of personality 
traits. Online Information Review, 41(2), 272-295. 
https://doi.org/10.1108/OIR-03-2016-0091

Hsu, C. L., & Lu, H. P. (2004). Why do people play 
online games? An extended TAM with social influ-
ences and flow experience. Information & Manage-
ment, 41(7), 853-868. https://doi.org/10.1016/j.
im.2003.08.014

Keiser, H. N., Sackett, P. R., Kuncel, N. R., & Brothen, 
T. (2016). Why women perform better in college 
than admission scores would predict: Exploring 
the roles of conscientiousness and course-taking 
patterns. Journal of Applied Psychology, 101(4), 
569. https://doi.org/10.1037/apl0000069

King, D. L., & Delfabbro, P. (2009). Understanding 
and assisting excessive players of video games: A 
community psychology perspective. Australian 
Community Psychologist, 21(1), 62-74. https://
doi.org/10.1.1.574.8438

Kircaburun, K., Griffiths, M. D., & Billieux, J. (2019). 
Psychosocial factors mediating the relationship 
between childhood emotional trauma and inter-
net gaming disorder: A pilot study. European Jour-
nal of Psychotraumatology, 10(1), 1–11. https://
doi-org.ezp.twu.edu/10.1080/20008198.2018.15
65031.

La Torre, G., Esposito, A., Sciarra, I., & Chiappetta, 
M. (2019). Definition, symptoms and risk of tech-
no-stress: A systematic review. International Ar-
chives of Occupational and Environmental Health, 
92(1), 13-35. https://doi.org/ 10.1007/s00420-
018-1352-1

Lee, T. S. H., Sun, H. F., & Chiang, H. H. (2019). De-
velopment and validation of the short-form Ryff's 
psychological wellbeing scale for clinical nurses 
in Taiwan. Journal of Medical Sciences, 39(4), 
157.https://doi.org/10.4103/jmedsci.jmeds-
ci_191_18

Lemmens, J. S., Valkenburg, P. M., & Gentile, D. A. 
(2015). The Internet gaming disorder scale. Psy-
chological Assessment, 27(2), 567. https://doi.
org/10.1037/pas0000062

Lepp, A., Barkley, J. E., & Karpinski, A. C. (2014). 
The relationship between cell phone use, academ-

CAMAGANACAN



85

ic performance, anxiety, and satisfaction with life 
in college students. Computers in Human Behav-
ior, 31(1), 343-350. https://doi.org/10.1016/j.
chb.2013.10.049

Li, W., Garland, E. L., McGovern, P., O'Brien, J. E., 
Tronnier, C., & Howard, M. O. (2017). Mind-
fulness-oriented recovery enhancement for inter-
net gaming disorder in US adults: A stage I ran-
domized controlled trial. Psychology of Addictive 
Behaviors, 31(4), 393. https://doi.org/10.1037/
adb0000269

Limelight Networks. (2019). Market research: The 
state of online gaming – 2019. Retrieved from 
https://www.limelight.com/resources/white-pa-
per/state-of-online- gaming-2019/

Lobel, A., Engels, R. C., Stone, L. L., & Granic, I. 
(2019). Gaining a competitive edge: Longitudinal 
associations between children’s competitive video 
game playing, conduct problems, peer relations, 
and prosocial behavior. Psychology of Popular Me-
dia Culture, 8(1), 76. https://doi.org/10.1037/
ppm0000159

Ludban, M. (2015). Psychological wellbeing of college 
students. Undergraduate Research Journal for the 
Human Sciences, 14(1). https://publications.kon.
org/urc/v14/ludban.html

Männikkö, N., Ruotsalainen, H., Tolvanen, A., & 
Kääriäinen, M. (2019). Psychometric properties 
of the Internet Gaming Disorder Test (IGDT‐10) 
and problematic gaming behavior among Finnish 
vocational school students. Scandinavian Journal 
of Psychology, 60(3), 252–260. https://doi- org.
ezp.twu.edu/10.1111/sjop.12533

Montag, C., Błaszkiewicz, K., Lachmann, B., Andone, 
I., Sariyska, R., Trendafilov, B.,… Markowetz, A. 
(2014). Correlating personality and actual phone 
usage: Evidence from psychoinformatics. Jour-
nal of Individual Differences, 35(3), 158–165. 
https://doi-org.ezp.twu.edu/10.1027/1614-
0001/a000139

National Alliance on Mental Illness. (2020). Latino 
Mental Health. Retrieved from https://www.
nami.org/Support-Education/Diverse-Commu-
nities/Latino-Mental- Health.

Nuyens, F. M., Kuss, D. J., Lopez-Fernandez, O., & 
Griffiths, M. D. (2019). The empirical analysis 
of non-problematic video gaming and cognitive 
skills: A systematic review. International Journal 

of Mental Health and Addiction, 17(2), 389-414. 
https://doi.org/ 10.1007/s11469-018-9946-0

Ozpolat, A. R., Isgor, I. Y., & Sezer, F. (2012). Investi-
gating psychological well-being of university stu-
dents according to lifestyles. Procedia-Social and 
Behavioral Sciences, 47(1), 256-262. https://doi.
org/10.1016/j.sbspro.2012.06.648

Przybylski, A. K., & Mishkin, A. F. (2016). How the 
quantity and quality of electronic gaming relates 
to adolescents’ academic engagement and psy-
chosocial adjustment. Psychology of Popular Me-
dia Culture, 5(2), 145. https://doi.org/10.1037/
ppm0000070

Punia, N., & Malaviya, R. (2015). Psychological 
well-being of first year college students. Indian 
Journal of Educational Studies: An Interdisciplin-
ary Journal, 2(1),60-68.https://http://ccemohali.
org/img/Ch%208%20Punia%20and%20Malviya.
pdf

Ryff, C. D., & Keyes, C. L. M. (1995). The structure 
of psychological well-being revisited. Journal of 
Personality and Social Psychology, 69(4), 719–727. 
https://doi.org/10.1037//0022-3514.69.4.719

Ryff, C. D. (2014). Psychological wellbeing revisit-
ed: Advances in the science and practice of eu-
daimonia. Psychotherapy and Psychosomatics, 
83(1), 10-28. https://doi.org/10.1159/000353263

Schuurmans, A. A., Nijhof, K. S., Engels, R. C., & 
Granic, I. (2018). Using a videogame interven-
tion to reduce anxiety and externalizing problems 
among youths in residential care: An initial ran-
domized controlled trial. Journal of Psychopathol-
ogy and Behavioral Assessment, 40(2), 344-354. 
https://doi.org/10.1007/s10862-017-9638-2

Stiff, C., & Kedra, P. (2018). Playing well with others: 
The role of opponent and intergroup anxiety in 
the reduction of prejudice through collaborative 
video game play. Psychology of Popular Media 
Culture, 9(1), 105–115. https://doi.org/10.1037/
ppm0000210

Suhlmann, M., Sassenberg, K., Nagengast, B., & Traut-
wein, U. (2018). Belonging mediates effects of stu-
dent-university fit on wellbeing, motivation, and 
dropout intention. Social Psychology, 49(1), 16-28. 
https://doi.org/10.1027/1864- 9335/a000325

Tams, S., Legoux, R., & Leger, P. M. (2018). Smart-
phone withdrawal creates stress: A moderated me-
diation model of nomophobia, social threat, and 

RAMIFICATIONS OF VIDEO GAME PLAYING IN COLLEGE



86

phone withdrawal context. Computers in Human 
Behavior, 81(1), 1-9. https://doi.org/10.1016/j.
chb.2017.11.026

Texas Woman’s University (2020).  Reports, Data, & 
References: Texas Woman’s University Boldly go. 
Retrieved from https://twu.edu/institutional-re-
search/reports-data--references/ 

Thought Catalog (2015). 12 types of computer games 
every gamer should know about. Retrieved from 
https://thoughtcatalog.com/jane-hurst/2015/02/12-
types-of-computer-games-every-gamer-should-know-
about/

Topham, P., & Moller, N. (2011). New students' psy-
chological well-being and its relation to first-year 
academic performance in a UK university. Coun-
seling and Psychotherapy Research, 11(3), 196-203. 
https://doi.org/10.1080/14733145.2010.519043

Twenge, J. M., Martin, G. N., & Campbell, W. K. 
(2018). Decreases in psychological well-being 
among American adolescents after 2012 and 
links to screen time during the rise of smart-
phone technology. Emotion, 18(6), 765. https://doi.
org/10.1037/emo0000403

Ventura, M., Shute, V., & Zhao, W. (2013). The relation-
ship between video game use and a performance-based 
measure of persistence. Computers & Education, 60(1), 
52-58. https://doi.org/10.1016/j.compedu.2012.07.003

Wei, C., Yu, C., & Zhang, W. (2019). Children's stressful 
life experience, school connectedness, and online gam-
ing addiction moderated by gratitude. Social Behavior 
and Personality: an International Journal, 47(12), 
1-11. https://doi.org/10.2224/sbp.7942

Wols, A., Lichtwarck-Aschoff, A., Schoneveld, E. A., & 
Granic, I. (2018). In-game play behaviors during an 
applied video game for anxiety prevention predict 
successful intervention outcomes. Journal of Psycho-
pathology and Behavioral Assessment, 40(4), 655-668. 
https://doi.org/10.1007/s10862-018-9684-4

Yam, F. C., & İlhan, T. (2020). Holistic technological ad-
diction of modern age: Phubbing. Current Approaches 
in Psychiatry/Psikiyatride Guncel Yaklasimlar, 12(1), 
1-15. https://10.18863/pgy.551299

Yildiz Durak, H. (2019). Human factors and cybersecurity 
in online game addiction: An analysis of the relation-
ship between high school students’ online game addic-
tion and the state of providing personal cybersecurity 
and representing cyber human values in online games. 
Social Science Quarterly, 100(6), 1984–1998. https://

doi- org.ezp.twu.edu/10.1111/ssqu.12693
Zajac, K., Ginley, M. K., Chang, R., & Petry, N. M. (2017). 

Treatments for Internet gaming disorder and Internet 
addiction: A systematic review. Psychology of Addic-
tive Behaviors, 31(8), 979. https://doi.org/10.1037/
adb0000315

 

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Table 1

Nine Criteria for Internet Gaming Disorder From the DSM-5

Note. DSM-5 = Diagnostic and Statistical Manual of Mental Disorders (5th ed.; American Psychiatric Associa-

tion, 2013). Adapted from “The Internet Gaming Disorder Scale by Lemmens, J. S., Valkenburg, P. M., & Gen-

tile, D. A., 2015, Psychological Assessment, 27, p. 567.

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Table 2

Demographics of Sample

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Table 3

One-Way ANOVA Results for DVs by Gaming Group (N = 382)

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Appendix A

Twenty-Seven Items for the Internet Gaming Disorder Scale Preoccupation
During the last year...
. . . have there been periods when you were constantly thinking about a game while at school or work?
. . . have there been periods when all you could think of was the moment that you could play a game?
. . . have there been periods when you were constantly fretting about a game?
Tolerance
During the last year...
. . . have you felt the need to continue playing for longer periods of time?
. . . have you felt the need to play more often?
. . . have you felt unsatisfied because you wanted to play more?
Withdrawal
During the last year...
. . . have you been feeling tense or restless when you were unable to play games?
. . . have you been feeling angry or frustrated when you were unable to play games?
. . . have you been feeling miserable when you were unable to play a game?
Persistence
During the last year...
. . . did you want to play less, but couldn’t?
. . . did you try to play less, but couldn’t?
. . . were you unable to reduce your time playing games, after others had repeatedly told you to play less?
Escape
During the last year...
. . . have you played games to forget about your problems?
. . . have you played games so that you would not have to think about annoying things?
. . . have you played games to escape negative feelings?

Problems
During the last year...
. . . have you skipped work or school so that you could play games?
. . . have you played throughout the night, or almost the whole night?
. . . have you had arguments with others about the consequences of your gaming behavior?
Deception
During the last year...
. . . have you lied to your parents or partner about the time you spent playing games?
. . . have you hidden the time you spend on games from others?
. . . have you played games secretively?
Displacement
During the last year...
. . . have you been spending less time with friends, partner or family to play games?
. . . have you lost interest in hobbies or other activities because gaming is all you wanted to do?
. . . have you neglected other activities (e.g., hanging out with friends, hobbies or sports) so that you could play 
games?
Conflict
During the last year...
. . . have you experienced serious problems at work or school because of gaming?
. . . have you experienced serious conflicts with family, friends or partner because of gaming?
. . . have you lost or jeopardized an important friendship or relationship because of gaming?

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Appendix B

Psychological Wellbeing Scale
1. “I like most parts of my personality.”
2. “When I look at the story of my life, I am pleased with how things have turned out so far.”
3. “Some people wander aimlessly through life, but I am not one of them.”
4. “The demands of everyday life often get me down.”
5. “In many ways I feel disappointed about my achievements in life.”
6. “Maintaining close relationships has been difficult and frustrating for me.”
7. “I live life one day at a time and don't really think about the future.”
8. “In general, I feel I am in charge of the situation in which I live.”
9. “I am good at managing the responsibilities of daily life.”
10. “I sometimes feel as if I've done all there is to do in life.”
11. “For me, life has been a continuous process of learning, changing, and growth.”
12. “I think it is important to have new experiences that challenge how I think about myself and the world.”
13. “People would describe me as a giving person, willing to share my time with others.”
14. “I gave up trying to make big improvements or changes in my life a long time ago”
15. “I tend to be influenced by people with strong opinions”
16. “I have not experienced many warm and trusting relationships with others.”
17. “I have confidence in my own opinions, even if they are different from the way most other people think.”
18. “I judge myself by what I think is important, not by the values of what others think is important.”

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Appendix C

Boundary Management Subscale
• I am on my cell phone while watching TV I am on my cell phone while driving
• Others get mad at me because I am on my cell phone frequently
• I leave my cell phone on and place it close to my bed when I go to sleep I am on my cell phone during din-

ner, even when dining with others When I go online, I lose track of time
• The time I spend online interferes with my personal relationships
• I neglect things that need to get done due to the time I spend online I get extremely anxious when I cannot 

use my cell phone

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