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). 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RAMIFICATIONS OF VIDEO GAME PLAYING IN COLLEGE 88 Table 2 Demographics of Sample CAMAGANACAN 89 Table 3 One-Way ANOVA Results for DVs by Gaming Group (N = 382) RAMIFICATIONS OF VIDEO GAME PLAYING IN COLLEGE 90 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? CAMAGANACAN 91 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.” RAMIFICATIONS OF VIDEO GAME PLAYING IN COLLEGE 92 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 CAMAGANACAN