Computer Game Addiction in Adolescents and Its Relationship to Chronotype and Personality

This study assessed the relationship between computer game addiction and computer game usage time, age, gender, BIG-5 personality, and chronotype. Seven hundred and forty-one adolescents from Turkey responded to questionnaires on these topics. We found that computer game addiction, computer game usage time, and chronotype were related with each other. Evening-oriented, younger, and male students had higher computer game addiction scores than morning-oriented, older, and female students. Furthermore, extraverted and agreeable students reported lower computer game addiction. No significant relationship was observed between students’ computer game addiction scores and openness to experience, conscientiousness. We conclude that evening types may be more prone to computer game addiction than morning types.


Introduction
Computer games are the second most frequently used application after social media (Wakoopa, 2012). Computer and online game play rates and sales are increasing every day (Entertainment Software Association, 2012). Computer and online games are preferred by a wide range of people ranging from children and adolescents to adults. Entertainment Software Association's (2012) research showed that the average game player is 30 years old and 32% of the players are less than 18 years old. Players choose to play games for several reasons such as fun, recreation (Griffiths & Hunt, 1995;Kuss & Griffiths, 2012), coping with stress (Grusser, Thalemann, Albrecht, & Thalemann, 2005;, sociability, gaining status (Hellström, Nilsson, Leppert, & Åslund, 2012), and escaping real life (Wan & Chiou, 2006;Wood, Griffiths, & Parke, 2007).
Research on video and computer gaming literature reports both positive and negative effects on players. Fifty-two percent of the parents highlighted that computer game playing is positive and an important element of their children's life (Entertainment Software Association, 2012). Thus, playing games promotes problem solving, visual, motor, and spatial skills and fosters interaction with friends outside of school (Boot, Kramer, Simons, Fabiani, & Gratton, 2008;Phillips, Rolls, Rouse, & Griffiths, 1995). Moreover, games may be effective educational tools and games relieve boredom and stress (Bowman & Tamborini, 2012). Despite the positive effects of playing computer games for adolescents, there are also negative effects, especially addictive computer game playing (Witt, Massman, & Jackson, 2011).
Concerning other personality inventories-for example, Festl, Scharkow, and Quandt (2013) used the California Psychological Inventory, Chumbley and Griffiths (2006) used Eysenck's Personality Impulsivity Scale, Fang and Zhao (2010) used Temperament and Character Inventory-it is found that high CGA scores were associated with aggression, low sociability, low self-efficacy, and lower satisfaction with life (Festl et al., 2013). Sensation seeking and boredom inclination was related to playing computer games and CGA (Chiu et al., 2004;Chumbley & Griffiths, 2006;Fang & Zhao, 2010).

Chronotype and CGUT.
Although recent studies revealed important predictors of CGA, the influence of chronotype has not been assessed. Chronotype or circadian typology is an individual difference in personality. Some people prefer morning hours for work and intellectual and physical activity while others prefer evening hours. These circadian preferences are based on a genetic influence that is reflected in hormonal profiles, heart rate, and body temperature (for a general overview see Adan et al., 2012;but also Randler & Schaal, 2010;Randler et al., 2012;Roeser et al., 2012). This genetic basis is also modulated by social and environmental factors (e.g., Leonhard & Randler, 2009). We know from studies on chemical addiction in adolescents (alcohol, drugs, smoking) that evening types have a higher tendency for cigarette craving and alcohol usage (Adan, 1994;Prat & Adan, 2011;Randler, 2008). Furthermore, studies showed that evening type adolescents differ in their time budgets (Kauderer & Randler, 2013): Evening types spend more time in front of screens (Vollmer, Michel, & Randler, 2012), and increased electronic media exposure predict later bedtime (Knutson & Lauderdale, 2009;Shochat, Flint-Bretler, & Tzischinsky, 2010) and a higher amount of television viewing (Gaina et al., 2006).
Evening types spend more time on computer gaming than others (Urbán, Magyaródi, & Rigó, 2011). Moreover, students who played computer games every day have later sleep and wake times and are more evening-oriented (Krejci et al., 2011). Most of the adolescents studied by Lemola et al. (2011) play computer games during the early night. Higuchi, Motohashi, Liu, and Maeda (2005) highlighted that playing games before going to bed delays sleep onset. These studies on time use and time budgets suggest that CGA-as a psychological variable-might be also related to chronotype.

Current Study
It is emphasized in the DSM-5 that studies are needed to examine internet gaming disorder with associated biological features (Petry & O'brien, 2013). Here, we investigate this relationship for the first time and we hypothesize a relationship between CGA and evening orientation. In addition, to control for covariates influencing CGA, we sampled additional covariates that have been found to influence CGA in previous studies such as age, gender, personality, chronotype, and CGUT.

Methods
We applied a quantitative cross-sectional survey in which all relevant variables were measured instantly at the same time.

Participants
Participants were 741 adolescents studying at different schools in Istanbul, Turkey. Participants voluntarily completed the questionnaire. A convenient sampling method was used for the selection of participants. In all, 294 of the participants (39.7%) were female and 446 (60.2%) were male. A total of 240 of the participants (32.4%) were in sixth grade, 203 (27.4%) in seventh grade, and 298 (40.2%) in eighth grade. The age ranged from 11 to 16 years and the mean (±SD) was 12.89 (±1.05) years. In all, 195 (26.3%) students preferred sport games, 61 (8.2%) preferred strategy and intelligence games, 146 (19.7%) preferred adventure and action games, 77 (10.4%) preferred war and shooting games, and 36 (4.9%) students preferred card games.

Instruments
Composite Scale of Morningness (CSM). The CSM was adapted to Turkish by Önder, Beşoluk, and Horzum (2013). The CSM is composed of 13 Likert-type scale items (10 items are coded on a 4-point Likert-type scale and 3 items are coded on a 5-point Likert-type scale) and the total score varies from a minimum of 13 (high evening orientation) to a maximum of 55 (high morning orientation). The scale is used in many different countries and shows good psychometric properties and convergent validity (Caci, Deschaux, Adan, & Natale, 2009;Randler, 2009). Cronbach's alpha coefficient of the scale reported by Önder et al. (2013) was .73.
BIG-5 Inventory. The BIG-5 Inventory was used in its short version consisting of 10 items comprising 5 personality dimensions (extraversion, agreeableness, conscientiousness, neuroticism [the opposite of emotional stability], and openness to experience) with 2 items for each dimension on a 5-point Likert-type scale. The inventory was developed by Gosling, Rentfrow, and Swann (2003) and adapted to Turkish by Günel (2010). The internal consistency of the dimensions ranged from .70 to .89.
Computer Game Addiction Scale. The CGA scale was developed by Ayas, Çakir, and Horzum (2011). The CGA scale consists of one factor and 26 items (see scale and item statistics in the appendix) in the form of a 5-point Likert-type scale. The total score varies from a minimum of 26 to a maximum of 130 with high scores reflecting higher CGA. The internal consistency of the scale was .95 in Ayas et al. (2011) and .92 in this study. We rate relative levels of symptoms of CGA on a continuous scale and we do not apply a clinical diagnosis or cut-off scores.

Procedure
Permission for conduct was obtained from the National Education Directorships. Participation was anonymous and voluntary. One of the researchers applied the scale and if any question from students arose about the questionnaire, he gave information and assisted the participants. For the statistical analyses, we applied hierarchical linear regressions to evaluate how well variables predicted CGA, and to assess if chronotype adds significantly to the well-known predictors of CCGA. These analyses were performed via SPSS 20.
CGA and CGUT were significantly correlated, r = .576, p < .001. Pearson's correlations were used to assess bivariate relationships with CGA scores as dependent variables and age, BIG-5 factors, CGUT, and chronotype as independent factors (see Table 1). We found a significant positive relationship between CGA scores and neuroticism. Negative correlations existed between extraversion, agreeableness, conscientiousness, openness and morningness on the one side and CGA on the other. This suggests that extraverted, agreeable, conscientious, open and morning-oriented students are less addicted to computer games. Due to the high sample size, low correlations also became significant. The hierarchical regression model contained age and gender as predictors of CGA in the first block (Table 2). In the first block, F change was not significant: F change (2, 659) = 1.202, p > .05, R 2 change = .004. In the second block, BIG-5 factors were added to the predictors. The second block's F change was significant and R 2 change increased compared with the previous block: F change (5, 654) = 9.820, p < .001, R 2 change = .070. Third, we added CSM scores as a predictor of CGA scores. The third block's F change was significant and R 2 changed: F change (1, 653) = 50.721, p < .001, R 2 change = .066. Finally, we added CGUT as a predictor of CGA scores to the fourth block ( Table 2). The fourth block's F change was significant and R 2 change increased compared with the previous block: F change (1, 652) = 294.098, p < .001, R 2 change = .268.
There was a significant and strong influence of M/E on CGA with evening type students scoring higher on the CGA. This indicates that CSM scores add to the model of CGA in addition to previously identified factors, such as age, gender, and personality. Students with a higher CGUT scored higher on CGA.

Discussion
As the most important result, we found a strong influence of chronotype on CGA. In the discussion, we follow each aspect separately keeping the structure of the hierarchical regression analyses.
Gender revealed a significant influence on CGA. A higher scoring of males in this trait has been found in many studies (Hartmann & Klimmt, 2006;Horzum, 2011;Walther et al., 2012;Xu et al., 2012) and was confirmed by our findings. Some researchers suggest that males have a stronger motivation to play (Chou & Tsai, 2007) and pick up more positive thoughts from playing computer games, and thus, computers are regarded as a "male toy" (Horzum, 2011). In addition, when playing games, males' brain satisfaction region seems to be more active than females' (Hoeft, Watson, Kesler, Bettinger, & Reiss, 2008). Furthermore, males have an inherent advantage in visual memory. Moreover, males perform better in visual memory on male exemplars while females perform better on female exemplars . Most of the games have male exemplars and gender differences may be affected by exemplars or their visual memory affect. Another reason is parental style. In some countries, parents exert more control over internet, computer, and game use of their daughters than of their sons, and parents are more permissive toward their sons (Horzum & Bektas, in press). Families' permissive parental style causes males to play more often and longer that may lead to higher addiction.
There was a negative effect of age on CGA. These findings are consistent with the literature. In our study, participants' age ranged from 11 to 16. This age group is most addicted (Festl et al., 2013;Walther et al., 2012;Xu et al., 2012) and adolescents from this age group spent more time with computer games than adults (Lemola et al., 2011).
We found a significant influence of all five personality domains on CGA in bivariate correlations but in the regression model, only the influence of extraversion, agreeableness, and emotional stability on CGA remained significant. This may have several reasons, but one reason might be that BIG-5 personality factors are correlated with morningness−eveningness, especially conscientiousness is strongly related to CSM scores (Randler, 2008), which suggests that the nonsignificant influence of conscientiousness on CGA might be owed to the higher statistical influence of morningness−eveningness. Extraversion and agreeableness were inversely related to CGA. Introverted people are described as solitary, shy, moody, quiet, relying on the decisions of others. Introverted people usually have a poorer social network and experience more rejection by peers (John & Srivastava, 2008). On one side, introverted people may rather express themselves and their feelings by playing computer games, or on the other side, may compensate for or eliminate loneliness while playing computer games. Concerning agreeableness, typical features of disagreeable people are independence, skepticism, irritability, and moodiness. Disagreeable people don't trust others and prefer competition over cooperation (John & Srivastava, 2008). Therefore, computer games may be suitable for disagreeable people's feelings of independence and competition.
In the regression analysis, conscientiousness and openness to experience were unrelated to CGA. This finding is consistent with Collins et al. (2012). However, conscientious students have a more organized and planned personality. Therefore, these students' CGA was expected to be lower than the CGA of less conscientious people-see the results in Table 1-because they keep an eye on their daily duties. Openness to Experience does not seem to be associated with CGA.
The relationship between CGA and eveningness is new and has not been shown previously, although research suggests that this relationship should be highly likely, as, e.g. Kauderer and Randler (2013) found that evening type adolescents spend more time on the computer (based on a time budget study), and Vollmer et al. (2012) reported a longer screen time of evening types (assessed by self-report Likerttype scales). As eveningness is related to higher substance use and misuse (Adan et al., 2012), we here add behavioral computer games addiction as another risk factor for eveningoriented adolescents.
Evening type students have more emotional problems than morning types (Barclay, Eley, Maughan, Rowe, & Gregory, 2010;Gau et al., 2007;Lange & Randler, 2011), show more problems concerning the timing of sleep (Gau & Soong, 1995), and, finally, achievement problems in school and university are higher in evening-oriented students (Beşoluk, Önder, & Deveci, 2011;Preckel, Lipnevich, Schneider, & Roberts, 2011). Game-addicted players are motivated for games because, apart from school, games are an alternative source for achievement and interplayer competition (Klimmt et al., 2009;Kneer & Glock, 2013;Yee, 2006) with more immediate reward. When games are used Note. Predictors were entered in four steps. First, age and gender were input, in Step 2 personality based on the Big Five was entered, in Step 3 chronotype was entered, and finally in Step 4 CGUT was entered. Gender: 0 = female, 1 = male. CSM = Composite Scale of Morningness from 13 = extreme eveningness to 55 = extreme morningness; CGUT = Computer Game Usage (in minutes); CGA = Computer Game Addiction Scale (with higher values indicating higher addiction). Durbin−Watson* = 1.696, Tolerance values** range from .378 to .957 and VIF values** range from 1.045 to 2.648. *Durbin−Watson value was near 2, and nonautocorrelation between variables is indicated. **All tolerance values are greater than .20 and VIF values smaller than 5, no multicollinearity problem is indicated. Significant effects are printed in bold.
for escaping everyday stress and for gaining achievement, they were associated with a high risk for addiction (Hellström et al., 2012). Especially evening-type adolescents may choose to play computer games to escape behavioral problems as some kind of coping mechanism. Students with high scores CGA had a higher daily CGUT. This might be due to the fact that people with high scores CGA have problems with their control over their time and seek to increase the dose similarly to chemical addictions. Moreover, several researcher used CGUT as a criterion to classify internet addiction or CGA (see Festl et al., 2013;Hellström et al., 2012;Kneer & Glock, 2013;Lee et al., 2007;Rehbein et al., 2010;. Their main findings were that students with high scores CGA spend more time with game playing.

Limitations
One limitation is the correlative nature of the study, and prospective work could help to identify causes and effects. Furthermore, we did not assess the sleep−wake cycle (bed times, rise times) that could add further evidence to this relationship. Probably bed times may become a stronger predictor if assessed together with the CSM scores. Another limitation of the study is that it was conducted before the latest edition of the DSM-5 was published. The new edition of the DSM includes criteria related to game addiction, but in this study, these criteria have not been taken into account. The third limitation of this study is that game motives and gaming motivation was not assessed. As there might be relationships between motivation and chronotype, these correlations might explain the results. In school achievement, for example, motivation and chronotype is related with each other. Fourth, CGA was measured by a self-report scale in this study. Thus, this addiction measurement did not include external validity evidence such as brain waves, heart rate, eating, drinking and hygiene habits and parental monitoring.

Conclusion and Recommendation
In conclusion, our study contributes to the relation between CGA and gender, age, chronotype, CGUT as well as BIG-5 personality. Evening types, younger adolescents, and males spend more time with computer games and report higher CGA. Chronotype was a significant predictor in this study, with a higher amount of variance explained compared with other personality factors. We therefore strongly recommend that future studies should assess chronotype preferences when investigating CGA.

Appendix
CGA scale items. Please note: the original items are in Turkish language; please see in Ayas, Çakir, and Horzum (2011) and note that the translation into English is to aid the reader.

Items
Factor loading Item total correlation α if item deleted