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. Author manuscript; available in PMC: 2013 Jun 11.
Published in final edited form as: Pediatrics. 2010 Nov 15;126(6):e1414–e1424. doi: 10.1542/peds.2009-2706

Video game playing in high school students: health correlates, gender differences and problematic gaming

Rani A Desai 1, Suchitra Krishnan-Sarin 1, Dana Cavallo 1, Marc N Potenza 1
PMCID: PMC3678538  NIHMSID: NIHMS475521  PMID: 21078729

Abstract

There is concern about the potential for negative impact of video games on youth. However the existing literature on gaming is inconsistent and has often focused on aggression. Health correlates of gaming and the prevalence and correlates of problematic gaming have not been systematically studied. We anonymously surveyed 4,028 adolescents about gaming, reported problems with gaming, and other health behaviors. 51.2% of the sample reported gaming (76.3% of boys and 29.2% of girls). There were no negative health correlates of gaming in boys, and lower odds of smoking regularly; however, girls who reported gaming were less likely to report depression, and more likely to report getting into serious fights and carrying a weapon to school. Among gamers, 4.9% reported problematic gaming, defined as reporting trying to cut back, experiencing an irresistible urge to play, and experiencing a growing tension that could only be relieved by playing. Boys were more likely to report these problems (5.8%) than girls (3.0%). Correlates of problematic gaming included regular cigarette smoking, drug use, depression, and serious fights. Results suggest that gaming is largely normative in boys and not associated with many health factors. In girls, however, gaming appears associated with more externalizing behaviors and fewer internalizing symptoms. The prevalence of problematic gaming is low but not insignificant, and problematic gaming may be contained within a larger spectrum of externalizing behaviors. More research is needed to define safe levels of gaming, refine the definition of problematic gaming, and evaluate effective prevention and intervention strategies.

Keywords: impulse control disorders, adolescents, video gaming, risk behaviors, gender

Introduction

The popularity of video, computer, online, and virtual reality games has raised concern in both the popular media1 and research community regarding the potential for negative health effects of gaming, including the potential for addiction.2-10 Gaming has been associated with both positive and negative clinical correlates; however, the evidence for a negative impact of gaming has been inconsistent. Experienced gamers may exhibit superior visual, spatial and attention skills,11,12, 13 and video game formats have been successfully used to deliver health interventions to children and adolescents.14 Depending upon the specific game, high levels of motor skill and often problem solving are required to advance through levels of play.15 Survey research has indicated that children who play video games often do so in social groups, such as with friends or family members,16, 17 and that frequency of gaming is positively associated with more peer interaction outside of school,16 although there is not enough evidence to conclude that gaming is a positive contributor to social development in children.18 Research on the association between gaming and aggression, in both laboratory19-21 and survey22-25 settings, and several meta-analyses,26, 27 has generally indicated a lack of a strong association between playing games (even violent ones) and aggressive behavior,18 although some studies have found such an association.4, 24, 28-37

While the research to support concern about gaming as a negative health behavior in general remains controversial, there is clear evidence that some individuals develop a pattern of gaming behavior that is problematic.1, 5, 6, 8, 38-42 As video gaming is a non-drug behavior with hedonic components, problematic gaming might be best conceptualized as a non-substance addiction or an impulse control disorder (ICD). The formal ICDs, such as pathological gambling, are characterized by appetitive urges or growing tension prior to participation, relief or pleasure following engagement in the behavior, and repeated behavioral engagement despite negative consequences.43 Importantly, they are not defined by concern or complaints about the behavior from family, which is important when evaluating behaviors in adolescents who may be in conflict with parents around a wide variety of issues. Problematic gaming has typically been defined in the literature based on measures of pathological gambling;5, 6, 40, 44, 45 however, a variety of definitions and criteria have been used, leading to inconsistent estimates of the prevalence of problematic gaming.

Individuals with problematic gaming behavior have been shown to exhibit inattention, hyperactivity and poor self-control,46, 47 experience time distortion while playing,48 and demonstrate increased aggression and diminished empathy if their games of choice contain aggressive content.28-30, 32, 37 Those with gaming problems who are engaged primarily in large online gaming communities often are shy,49 have an external locus of control,49 and use gaming to deal with negative emotions.50

Multiple research gaps exist presently. First, not all adolescents play video games, and the health correlates of gaming (e.g. relationships with drug and alcohol use or depression) are incompletely understood, as much of the published research has focused on school performance, obesity, and aggression. Second, the likelihood of gaming, and the clinical correlates thereof, are likely to differ by gender, and sex differences in gaming and its health correlates are poorly understood. Third, much of the research on gaming has utilized online samples of gamers or small groups of individuals identified as having problematic gaming behaviors, presenting problems for generalizability. This study utilizes survey data from a large sample of adolescents and examines the prevalence and clinical correlates of gaming, reported problems associated with video games, and the prevalence and correlates of problematic gaming.

Methods

Sampling

Data are derived from a cross-sectional anonymous survey of students in public high schools as described previously.51 Schools were first recruited into the study, and then students at each enrolled school were invited to participate. Invitation letters were sent to all public 4-year and non-vocational or special education high schools in the State of Connecticut. After the initial round of letters were mailed, the response from schools was not yet sufficient to ensure that all geographic regions of the state were sufficiently represented. Therefore, targeted contacts were made to schools that were in areas that would ensure a more representative sample. The final sample was representative of 14- to 18-year-old adolescents in CT according to the most recent Census.51

Survey Procedures

In most cases, the entire student body was targeted for administration of the survey. Students were told that they could voluntarily refuse to complete the survey if they wished and were reminded to keep surveys anonymous. The survey took approximately 50 minutes to complete.

Measures

The measures used in this analysis included self-reported gender, race, ethnicity, grade, and family structure (living with one parent, two parents, or other family structure).

Health and functioning measures were categorized as presented in the tables and included: grade average; extracurricular activities; lifetime smoking history; lifetime marijuana use; lifetime history of a sip of alcohol; current alcohol use among those with a history of any alcohol consumption, categorized as none, light (1-2 days or drinking in the month), moderate (3-9 days of drinking in the month), and heavy (10 or more days of drinking in the month); lifetime use of other drugs; caffeine use; report of being sad or hopeless for two weeks or more in the previous year; getting into fights requiring medical attention in the previous year; carrying a weapon such as a knife, club, or gun to school in the past year; and body mass index (BMI) as calculated from self reported height and weight.

Respondents were asked to report how much time they spent playing video or computer games in a typical week. Respondents who reported “None” were classified as non-game players. For those who played games, the frequency of play was categorized as less than 7 hours per week, 7-14, 15-20, and 21 or more hours per week.

Those who played any video or computer games were asked: if they had ever tried to cut back on playing; whether a family member had expressed concern about the amount of time they spend playing games; whether they missed school, work, or an important social activity because they were playing video or computer games; whether they thought they had a problem with excessive video or computer game use; whether they experienced an irresistible urge or uncontrollable need to play video or computer games; and whether they experienced a growing tension or anxiety that could only be relieved by playing video or computer games. The three items of unsuccessfully trying to cut back, experiencing an irresistible urge to play, and experiencing growing tension only relieved by playing were modeled after the Minnesota Impulse Disorder Inventory52 and are considered the core features of an ICD. Students who endorsed all three items were categorized as ‘problematic video gamers.’ The coefficient alpha for these items was 0.76.

Data Analysis

First, demographic characteristics and health correlates were compared between respondents who played video or computer games and those who did not, stratified by gender, using Chi-square tests for categorical variables and t tests for continuous variables. Second, logistic regression models were fit to assess the association between each health correlate and playing video games, adjusting for demographic differences. Interaction terms between gender and health correlates determined whether the associations were significantly different in girls and boys.

Next, among the sub-sample of respondents who reported any game playing, those with problematic game playing were compared to those with non-problematic gaming, stratified by gender for bivariate analyses. Logistic regression models were fit to examine associations between health correlates and problematic gaming, adjusting for gender and race. There was insufficient statistical power to test gender interactions in multivariable models.

Results

Of the 4,028 respondents with data on video gaming, 2,064 (51.2%) reported playing at least one hour of video games per week. This proportion was higher in boys (76.3%) than in girls (29.2%, p<0.0001) (Table 1). In the total sample, gaming was significantly more prevalent in Asian students and lower grades. Among boys, playing video or computer games was associated with lower grade and with living in a two-parent household. Among girls, significant positive associations were found with Asian race and lower grade.

Table 1.

Demographic characteristics of high school student sample and association with video game playing, by gender

Total Sample Boys (n=1845) Girls (n=2139)
Variable N % % play video games ever X2 p N % % play video games ever X2 p N % % play video games ever X2 p
African-American Yes 399 9.91 51.38 0.0033 0.954 186 10.08 74.19 0.51 0.4731 205 9.58 28.78 0.02 0.8845
No 3629 90.09 51.23 1659 89.92 76.55 1934 90.42 29.27
White Yes 3090 76.71 50.84 0.8493 0.3568 1399 75.83 76.05 0.22 0.6417 1666 77.89 29.47 0.23 0.6298
No 938 23.29 52.56 446 24.17 77.13 473 22.11 28.33
Asian Yes 159 3.95 65.41 13.3 0.0003 83 4.5 81.93 1.52 0.2184 67 3.13 43.28 6.62 0.0101
No 3869 96.05 50.66 1762 95.5 76.05 2072 96.87 28.76
Other race Yes 568 14.1 50.7 0.076 0.7823 250 13.55 79.2 1.33 0.2484 309 14.45 26.86 0.97 0.3243
No 3460 85.9 51.33 1595 86.45 75.86 1830 85.55 29.62
Hispanic Yes 519 13.43 52.41 0.31 0.5806 232 13.15 76.72 0.01 0.9232 273 13.23 30.4 0.14 0.7129
No 3346 86.57 51.11 1532 86.85 76.44 1791 86.77 29.31
Grade 9th 1245 30.99 57.11 29.01 <0.0001 571 30.98 78.63 10.40 0.0155 654 30.65 37.92 35.23 <0.0001
10th 1108 27.58 50.9 505 27.4 79.01 592 27.74 26.35
11th 1055 26.26 47.39 477 25.88 74.42 571 26.76 24.69
12th 609 15.16 46.47 290 15.74 70.34 317 14.85 24.61
Family structure One parent 910 22.9 48.02 5.29 0.0711 386 21.15 70.98 10.33 0.0057 515 24.45 30.49 1.77 0.4133
Two parents 2865 72.09 52.32 1353 74.14 78.27 1484 70.47 28.17
Other 199 5.01 49.75 86 4.71 70.93 107 5.08 32.71
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Among boys, gaming was associated with higher grade average, never smoking, never having used marijuana, and high caffeine consumption (Table 2) In girls, gaming was associated with occasional smoking, never having used marijuana, never having a sip of alcohol, high caffeine use, no history of depression, getting into serious fights, and carrying a weapon. Gaming was associated with slightly higher BMI in girls (mean(SD) BMI for gamers=22.35(4.44), for non-gamers=21.94(3.61); p=0.03), but not in boys.

Table 2.

Health and functioning measures and association with lifetime video game playing, by gender

Total Sample Boys Girls
Variable N % % play video games ever X2 p N % % play video games ever X2 p N % % play video games ever X2 p
Grade average A's and B's 2319 59.11 48.68 15.48 0.0004 941 52.05 78.21 6.7393 0.0344 1361 65.5 28.14 2.5883 0.2741
C's 1157 29.49 54.8 594 32.85 75.76 549 26.42 31.51
D's and F's 447 11.39 55.7 273 15.1 70.7 168 8.08 31.55
Extra-curricular activities Yes 3056 75.87 50.95 0.43 0.5104 1382 74.91 76.48 0.087 0.768 1642 76.76 29.05 0.098 0.7543
No 972 24.13 52.16 463 25.09 75.81 497 23.24 29.78
Smoking, lifetime
Never 2441 62.41 54.4 34.34 <0.0001 1146 64.53 79.58 29.91 <0.0001 1268 60.53 31.39 12.42 0.002
Occasionally 949 24.26 43.73 397 22.35 71.54 546 26.06 23.26
Regularly 521 13.32 47.22 233 13.12 66.52 281 13.41 30.25
Marijuana, lifetime Yes 1476 39.07 47.29 11.72 0.0006 689 40.39 70.68 16.85 <0.0001 772 25.78 25.78 7.11 0.0077
No 2302 60.93 53 1017 59.61 79.35 1259 61.97 31.32
Sip of alcohol, lifetime Yes 3312 86.72 49.34 21.36 <0.0001 1444 84 75.48 1.49 0.2228 1833 89.07 28.31 7.87 0.005
No 507 13.28 60.36 275 16 78.91 225 37.33 37.33
Current alcohol frequency Never regular 756 31.01 48.81 2.81 0.4233 338 32.1 75.74 4.19 0.2419 412 30.18 26.46 5.74 0.1249
Light 704 28.88 48.15 295 28.02 72.54 402 29.45 30.35
Moderate 697 28.59 44.76 286 27.16 75.17 406 29.74 22.91
Heavy 281 11.53 46.26 134 12.73 67.16 145 10.62 26.9
Other drug use, lifetime Yes 305 9.17 54.43 1.33 0.2483 156 10.3 71.79 1.66 0.1971 144 8.09 34.03 1.28 0.2576
No 3022 90.83 50.96 1359 89.7 76.45 1636 91.91 29.52
Caffeine use None 785 20.03 46.11 13.58 0.0011 390 21.87 66.41 26.74 <0.0001 381 18.2 24.67 8.83 0.0121
1-2 drinks per day 2134 54.45 50.98 922 51.71 79.61 1195 57.1 28.79
2+ drinks per day 1000 25.52 54.9 471 26.42 77.28 517 24.7 33.66
Sad or hopeless 2+weeks Yes 835 21.78 47.19 6.27 0.0123 269 15.57 76.97 1.13 0.2874 556 26.9 27.66 7.85 0.0051
No 2999 78.22 52.08 1459 84.43 73.98 1511 73.1 33.99
Serious fights Yes 265 6.75 61.13 11.95 0.0005 166 9.33 71.69 2.02 0.1548 91 4.32 39.56 4.97 0.0258
No 3660 93.25 50.14 1613 90.67 76.63 2014 95.68 28.7
Carry a weapon Yes 742 18.81 67.65 101.58 <0.0001 552 30.79 74.46 1.49 0.2217 176 8.35 44.32 21.51 <0.0001
No 3202 81.19 47.13 1241 69.21 77.12 1933 91.65 27.73
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Table 3 presents adjusted logistic regression analyses with interaction terms to identify significant differences across gender groups. Boys reporting gaming were less likely to be regular smokers, while there was no association between smoking and gaming in girls. Boys were also more likely to drink 1-2 servings of caffeinated drinks per day, while girls reporting gaming were more likely to drink 3 or more caffeine drinks per day. Girls reporting gaming were less likely to report depression, while there was no such association among boys. Similarly, girls were more likely to get into serious fights and carry a weapon, but no such association was seen among boys. Finally, girls reporting gaming had slightly higher average BMI measures (OR=1.03, p=0.01), while there was no association in boys (OR=1.0001, p=0.98).

Table 3.

Association between lifetime video game playing and other health factors, adjusting for grade and stratified by gender

Total Sample Boys Girls Gender interaction
Variable Category OR p OR p OR p p value
Grade average (Ref: A's and B's) C's 0.66 0.8586 0.868 0.6483 1.14 0.458 0.0623
D's and F's 0.84 0.1422 0.673 0.0278 1.08 0.9568
Extra-curricular activities Yes 0.97 0.6836 0.99 0.9351 0.961 0.7263
Smoking, lifetime (Ref: Never) Occasionally 0.76 0.0144 0.656 0.4695 0.71 0.003 0.1408
Regularly 0.69 <0.0001 0.524 0.0046 1.07 0.1004 0.0028
Marijuana, lifetime Yes 0.75 0.0002 0.653 0.0002 0.834 0.0854 0.1984
Sip of alcohol, lifetime Yes 0.78 0.0239 0.856 0.3362 0.715 0.0245 0.3239
Current alcohol frequency (Ref: Never regular) Light 1.05 0.7099 0.846 0.8659 1.243 0.1
Moderate 0.9 0.4022 0.978 0.3059 0.863 0.0716
Heavy 0.87 0.3964 0.671 0.0965 1.127 0.6305
Other drug use, lifetime Yes 1.04 0.7675 0.832 0.3376 1.292 0.1758
Caffeine use (Ref: None) 1-2 drinks per day 1.51 <0.0001 1.929 0.0004 1.19 0.7481 0.0049
2+ drinks per day 1.65 <0.0001 1.684 0.1366 1.51 0.0052 0.5075
Sad or hopeless 2+weeks Yes 1.19 0.0549 1.154 0.3499 0.721 0.0024 0.0149
Serious fights Yes 1.05 0.7501 0.778 0.1725 1.668 0.0218 0.008
Carry a weapon Yes 1.17 0.1109 0.86 0.2056 2.095 <0.0001 <0.0001
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1 Interaction term tests whether the Odds Ratios for boys and girls are significantly different from each other

Table 4 presents the frequency of gaming, along with reported problems associated with gaming, among the sample of 2,196 gamers. In the total sample, the majority of respondents reported playing less than 7 hours per week (61.1%); however, 10.9% reported playing 20 hours or more in a typical week. The most commonly endorsed items related to problems with gaming were family members expressing concern about gaming, trying to cut back on gaming, and experiencing an irresistible urge to play. While the majority of respondents endorsed none of the problematic symptoms, 4.9% endorsed all three of the items indicative of an ICD.

Table 4.

Characteristics of video game playing, among those who have played video games

Total Sample Boys Girls
Characteristic Level N % N % N % X2 p
Frequency of game playing in a typical week <7 hours 1262 61.14 739 52.49 511 81.76 160.22 <0.0001
7-14 hrs 385 18.65 314 22.3 65 10.4
15-20 hrs 192 9.3 160 11.36 28 4.48
20+ hrs 225 10.9 195 13.85 21 3.4
Ever tried to cut back? 408 20.2 302 22.0 96 15.6 10.87 0.001
Family expressed concern? 560 27.79 466 33.92 84 13.73 86.19 <0.0001
Missed activities to play? 289 14.37 238 17.33 41 6.73 39.21 <0.0001
Do you think you have a problem? 175 8.76 134 9.84 33 5.44 10.48 0.0012
Experienced irresistable urge to play? 395 19.72 318 23.28 68 11.18 39.13 <0.0001
Experienced growing tension only relieved by playing? 319 15.91 253 18.51 56 9.2 27.69 <0.0001
Three key symptoms endorsed1 106 4.9 84 5.85 22 3.02 8.34 0.0039
Total number of items endorsed 0 1094 53.92 650 47.03 429 69.53 97.3 <0.0001
1 366 18.04 269 19.46 95 15.4
2 243 11.98 197 14.25 42 6.81
3 131 6.46 106 7.67 24 3.89
4 109 5.37 94 6.8 13 2.11
5 51 2.51 42 3.04 9 1.46
6 35 1.72 24 1.74 5 0.81
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1

Unsuccessfully tried to cut back, experience irresistable urge, experience growing tension only relieved by playing

There were significant gender differences in patterns of gaming and problems with gaming as well. Girls as compared with boys more frequently reported playing fewer than 7 hours in a week, and 14% of boys reported playing 20 or more hours per week. Girls also reported problematic gaming less often than did boys. There were 84 boys (5.9%) who endorsed the three problem measures, while only 22 girls (3.0%) did so.

Table 5 compares demographic characteristics of those in the problematic gaming group, compared to all others who reported gaming, stratified by gender. Among boys, problematic gaming was associated with non-white and Asian race. There were no significant associations among girls.

Table 5.

Demographic characteristics of those who report video game playing and association with problematic gaming

Total Sample Boys Girls
Variable Number of gamers % % problematic gamers X2 p Number of gamers % % problematic gamers X2 p Number of gamers % % problematic gamers X2 p
African-American Yes 219 9.97 7.76 3.56 0.0591 141 9.83 7.8 1.08 0.2995 71 9.74 2.82 0.0109 0.917
No 1977 90.03 4.81 1294 90.17 5.64 658 90.26 3.04
White Yes 1656 75.41 4.47 5.55 0.0185 1079 75.19 4.91 6.99 0.0082 561 76.95 3.21 0.302 0.5823
No 540 24.59 7.04 356 24.81 8.71 168 23.05 2.38
Asian Yes 109 4.96 7.34 1.19 0.2757 70 4.88 11.43 4.15 0.0416 31 4.25 0 1.01 0.3155
No 2087 95.04 4.98 1365 95.12 5.57 698 95.75 3.15
Other race Yes 314 14.3 5.1 0.0001 0.9968 200 13.94 6.5 0.18 0.6747 107 14.68 2.8 0.02 0.8885
No 1882 85.7 5.1 1235 86.06 5.75 622 85.32 3.05
Hispanic Yes 296 14.02 7.43 4.63 0.0315 184 13.37 8.7 3.64 0.0564 102 14.35 3.92 0.27 0.6021
No 1816 85.98 4.52 1192 86.63 5.2 609 85.65 2.96
Grade 9th 743 33.97 4.31 3.18 0.3651 452 31.54 4.42 4.07 0.2538 277 38.15 2.89 0.47 0.9256
10th 601 27.48 5.16 400 27.91 6 192 26.45 3.13
11th 525 24.01 4.95 364 25.4 5.77 157 21.63 2.55
12th 318 14.54 6.92 217 15.14 8.29 100 13.77 4
Family structure One parent 478 22.12 5.02 0.84 0.6573 290 20.45 5.52 0.408 0.8154 183 25.74 3.83 0.502 0.7781
Two parents 1566 72.47 4.92 1061 74.82 5.66 483 67.93 2.9
Other 117 5.41 6.84 67 4.72 7.46 45 6.33 2.22
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Among health correlates (Table 6), problematic gaming was associated in boys with smoking regularly, depression, and getting into serious fights or carrying a weapon. Among girls, problematic gaming was associated with other drug use, depression and serious fights. There was no association with BMI in either boys (p=0.20) or in girls (p=0.33).

Table 6.

Health and functioning measures and association with problematic gaming, by gender

Total Sample Boys Girls
Variable Number of gamers % % problematic gamers X2 p Number of gamers % % problematic gamers X2 p Number of gamers % % problematic gamers X2 p
Grade average A's and B's 1189 55.64 4.63 1.07 0.5847 748 53.24 5.61 0.2313 0.8908 431 61.05 2.78 0.569 0.7521
C's 674 31.54 5.49 457 32.53 5.91 206 29.18 3.88
D's and F's 274 12.82 5.84 200 14.23 6.5 69 9.77 2.9
Extra-curricular activities Yes 1646 74.95 4.68 2.42 0.1198 1072 74.7 5.41 1.51 0.2191 552 75.72 2.54 1.81 0.1795
No 550 25.05 6.36 363 25.3 7.16 177 24.28 4.52
Smoking, lifetime
Never 1363 64.35 3.96 10.28 0.0058 911 66.06 4.39 9.91 0.0071 434 61.13 2.76 2.08 0.353
Occasionally 467 22.05 5.57 302 21.9 6.62 161 22.68 2.48
Regularly 288 13.6 8.33 166 12.04 10.24 115 16.2 5.22
Marijuana, lifetime Yes 776 37.91 6.19 2.86 0.0906 507 38.32 6.31 0.36 0.5472 256 36.99 4.69 3 0.0831
No 1271 62.09 4.48 816 61.68 5.51 436 63.01 2.29
Sip of alcohol, lifetime Yes 1758 85.05 4.95 0.78 0.3778 1118 83.75 5.64 0.99 0.3207 614 87.59 3.26 0.23 0.6313
No 309 14.95 6.15 217 16.25 7.37 87 12.41 2.3
Current alcohol frequency Never regular 396 31.5 5.3 2.44 0.4867 255 31.99 5.49 1.01 0.7984 138 30.8 5.07 6.91 0.0751
Light 366 29.12 3.28 221 27.73 4.52 142 31.7 1.41
Moderate 344 27.37 3.49 222 27.85 4.5 118 26.34 0.85
Heavy 151 12.01 3.97 99 12.42 3.03 50 11.16 6.01
Other drug use, lifetime Yes 183 10.13 10.38 12.53 0.0004 120 10.17 9.17 3.03 0.0814 58 9.63 10.34 10.85 0.001
No 1623 89.87 1.37 1060 89.83 5.28 544 90.37 2.39
Caffeine use None 403 18.88 7.69 9.44 0.0089 279 20.04 7.89 4.18 0.1236 112 15.75 6.25 5.42 0.0666
1-2 drinks per day 1142 53.49 3.85 738 53.02 4.61 394 55.41 2.03
2+ drinks per day 590 27.63 5.08 375 26.94 5.87 205 28.83 2.93
Sad or hopeless 2+weeks Yes 431 20.66 10.21 36.85 <0.0001 211 15.62 11.37 17.44 <0.0001 214 30.27 7.48 21.62 <0.0001
No 1655 79.34 3.26 1140 84.38 4.3 493 69.73 1.01
Serious fights Yes 177 8.3 14.12 35.56 <0.0001 129 9.31 13.95 19.12 <0.0001 41 5.73 9.76 6.52 0.0106
No 1955 91.7 4.04 1257 90.69 4.69 675 94.27 2.67
Carry a weapon Yes 530 24.75 7.74 12.63 0.0004 431 30.85 7.66 5.51 0.019 86 12.04 4.65 0.81 0.369
No 1611 75.25 3.91 966 69.15 4.55 628 87.96 2.87
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Logistic regression models presented in Table 7 indicated that, adjusted for race and gender, problematic gaming was associated with higher odds of smoking regularly, other drug use, lower caffeine consumption, depression, serious fights and carrying a weapon to school. However, given effect sizes and the number of models, the most robust of these findings are for an increase in regular smoking (OR=2.12, p=0.007), depression (OR=3.62, p<0.0001) and serious fights (OR=2.97, p<0.0001).

Table 7.

Adjusted odds of reporting problematic gaming, adjusted for race and gender, among video game players

Variable Category OR 95% CI p
Grade average (Ref: A's and B's) C's 1.08 (0.69, 1.71) 0.7383
D's and F's 1.14 (0.62, 2.08) 0.6821
Extra-curricular activities Yes 0.68 (0.44, 1.05) 0.0795
Smoking, lifetime (Ref: Never) Occasionally 1.36 (0.82, 2.26) 0.2369
Regularly 2.12 (1.23, 3.64) 0.0066
Marijuana, lifetime Yes 1.26 (0.82, 1.92) 0.2905
Sip of alcohol, lifetime Yes 0.93 (0.53, 1.63) 0.7945
Current alcohol frequency (Ref: Never regular) Light 0.76 (0.36, 1.61) 0.4701
Moderate 0.76 (0.35, 1.63) 0.4745
Heavy 0.97 (0.37, 2.51) 0.9449
Other drug use, lifetime Yes 2.25 (1.26, 4.02) 0.0064
Caffeine use (Ref: None) 1-2 drinks per day 0.51 (0.31, 0.85) 0.0094
2+ drinks per day 0.7 (0.40, 1.21) 0.198
Sad or hopeless 2+weeks Yes 3.62 (2.31, 5.65) <0.0001
Serious fights Yes 2.97 (1.74, 5.07) <0.0001
Carry a weapon Yes 1.65 (1.06, 2.58) 0.0262
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Discussion

This study is among the first and largest to examine clinical correlates of video gaming and problematic gaming in a community sample of adolescents. We found that about half of the students reported gaming, concentrated among younger students and more common in boys.

There were no significant negative health correlates of gaming in boys, likely reflecting the popularity and normative nature of such games for this group. Additionally, boys who reported gaming were significantly less likely to report being a regular smoker. However, among girls gaming was associated with modestly lower risk of depression and moderate increases in serious fights (OR=1.7) and carrying a weapon (OR=2.1).

We also found that among boys reporting gaming, 5.9% endorsed problematic gaming, compared to 3.0% of girls reporting gaming, suggesting that male gamers may be at higher risk for developing a gaming problem, but that overall the risk of developing a problem is relatively low. Problematic gaming was associated with some important risk behaviors, with moderate effects sizes found for depression (OR=3.6) and fighting (OR=3.0), but was not associated with grade averages, extra-curricular activities, marijuana use, or alcohol use.

Gender differences in correlates of gaming

The gender differences observed between gamers and non-gamers, coupled with the contrast in frequencies of gaming across gender, is suggestive of a gender-specific self-selection process. That is, while gaming may be more appealing to boys in general, it may be particularly attractive to girls with particular characteristics. Although causality cannot be examined in these cross sectional data and competing hypotheses not eliminated, this finding may suggest not that gaming leads to aggression but that more aggressive girls are attracted to gaming as a recreational activity. The finding may also reflect cultural differences in socioeconomic conditions at home and in their communities: it is possible that girls who live in more violent neighborhoods, where they are more likely to experience fights and to carry a weapon for protection, are also more likely to be attracted to gaming, may be more likely to spend time with male peers who are themselves gaming, or may prefer to stay home and play games rather than be outside in dangerous communities.

The finding may also be reflective of personality characteristics that are more externalizing; girls reporting gaming are not only more likely to get into fights and carry weapons, behaviors generally considered to be externalizing, but also are somewhat less likely to report feelings of depression, which would reflect more internalizing patterns. An additional possibility is that gaming may exert a positive effect on mood in girls; however, this hypothesis and the precise nature of the relationship warrant additional study in longitudinal investigations.

Among boys, the finding that gaming is associated with more pro-social or beneficial behaviors, such as less cigarette use, may reflect a different peer group among gamers. As noted above, the general lack of associations between health behaviors and gaming in boys may also reflect the normative nature of gaming for boys in the current US culture.

Problematic Gaming

Although there are no uniformly agreed-upon thresholds for ‘excessive’ game playing, we found higher frequencies of playing among boys than girls, with about 14% of boys reporting playing on average 3 hours a day or more. This, coupled with the possibility that frequencies may be under-reported due to the known phenomenon of time lapse,48 where gamers appear unaware of how much time has elapsed while playing, may reflect a strong appeal of these games, particularly to boys. However, it also suggests a need to further characterize the potential risks and benefits associated with high frequency play, and to balance such risks and benefits against those of other activities favored by adolescents, including watching TV or experimenting with substances.53

Boys were significantly more likely than girls to report problems with gaming. When examining the three measures of an ICD, a relatively low but important proportion of both boys and girls have gaming problems. Further research is needed to examine the accuracy of self-reports of such problems, and whether these or other questions are the best way to assess impairment related to gaming. It is possible, for example, that some of the items may be endorsed as a “badge of honor” (e.g., claiming to have a problem or an irresistible urge to play as a sign of a ‘serious’ or very experienced player).

The results of this study suggest that adolescents with problematic gaming are more likely to also be engaging in other risk behaviors such as smoking, drug use and violence, and are more likely to report depression. It is not possible in these data to determine whether problematic gaming leads to experimentation, aggression, or depression, vice versa, or the factors develop in conjunction, perhaps related to common etiological factors such as the violence content in games, or other common underlying traits such as introversion/extraversion, impulsivity or sensation seeking. Future longitudinal research is needed to examine the onset of risk behaviors in temporal relation to gaming and their potential roles in the development of health problems.

Those reporting problems with gaming were also significantly more likely to report depression. Further research is needed to understand the role that video games play in brain function,54-56 including those pathways also associated with depression. However, some research has suggested that adolescents who play excessive amounts of video games in part do so to deal with negative affect.50, 57 Conversely, excessive playing may alter brain function in such a way as to increase depressed affect and the risk of depression.

Strengths and Limitations

This study is among the largest to examine gaming in high school students, and this sample size allowed for the examination of gender differences in health correlates. Data were examined using regression models in a manner consistent with prior work investigating youth impulse control behaviors, allowing for comparability across studies.58 However, the data are cross-sectional, so that temporal associations cannot be elucidated, and this limits our ability to suggest causal pathways or theoretical models for problematic gaming. Also, the data were self-reported and the psychometric properties of the questions have not been directly evaluated, although they were based upon validated questions used to assess other impulsive behaviors in the Minnesota Impulse Disorder Inventory.52 Further research is needed to determine whether these questions are accurate, reliable, and appropriate for assessing problem gaming. We selected a relatively stringent threshold for defining problematic gaming, and further research is needed to determine the optimal threshold for this definition. Despite a substantial sample size, the low prevalence of problematic gaming did not allow us to fully investigate gender interactions in multivariable models. Given the suggestion of differences in bivariate analyses, future research should examine potential gender differences in the correlates of problematic gaming. Additionally, other factors, such as depression, that are found in association with other impulse control behaviors may represent important variables of consequence (perhaps particularly for girls59, 60) in the development of problematic video gaming, and future studies should investigate directly and systematically the relationships between gender, mood and problematic video gaming. Additional factors such as temperament warrant similar consideration as potential vulnerability factors.61 Such analyses could help identify how additional factors might be mediating the relationship between problem video game playing and negative measures of health and functioning. Finally, we were unable to distinguish between computer games, handheld video games, physically active games such as Wii, and online gaming. It is possible that each of these types of games may attract different types of players and correlate differentially with specific health measures, particularly since the types of games played may be directly associated with socio-economic status (SES), which we were unable to assess reliably.

In conclusion, we found no significant negative health correlates of video game use in boys; modest correlations with higher aggression and reduced depression in girls; a relatively low but important percentage of reported problems with gaming; and important associations between problematic gaming and smoking, drug use, aggressive behavior and depression, though no associations with grade averages, extra-curricular activities, marijuana use, or alcohol use. Additional research is needed to examine recreational and problematic levels of video gaming, to determine safe levels of gaming, and to identify risk factors and potential points of intervention and prevention. Additionally, more research is needed into beneficial uses of video games given their popularity amongst youth.62

Acknowledgments

Financial disclosures:

This study was supported by the NIH grants PSOAA15632, RLl AA017539, ULl DE19586, the NIH Roadmap for Medical Research/Common Fund, the National Center for Responsible Gaming and its affiliated Institute for Research on Gambling Disorders and the State of Connecticut, Department of Mental Health and Addiction Services. This work was also supported by the Yale University Transdisciplinary Tobacco Use Research Center (TTURC) and the Yale University Psychotherapy Development Research Center. The contents of the manuscript are solely the responsibility of the authors and do not necessarily represent the official views of any of the funding agencies.

Over the past three years, Dr. Potenza has received financial support or compensation for the following: Dr. Potenza has consulted for and advised Boehringer Ingelheim; has had financial interests in Somaxon; has received research support from the National Institutes of Health, Veteran's Administration, Mohegan Sun Casino, the National Center for Responsible Gaming and its affiliated Institute for Research on Gambling Disorders, and Forest Laboratories pharmaceuticals; has participated in surveys, mailings or telephone consultations related to drug addiction, impulse control disorders or other health topics; has consulted for law offices on issues related to addictions or impulse control disorders; has provided clinical care in the Connecticut Department of Mental Health and Addiction Services Problem Gambling Services Program; has performed grant reviews for the National Institutes of Health and other agencies; has guest-edited sections of journals; has given academic lectures in grand rounds, CME events and other clinical or scientific venues; and has generated books or book chapters for publishers of mental health texts.

Abbreviations

BMI

body mass index

ICD

impulse control disorder

OR

odds ratio

SD

standard deviation

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