• How does playing more video games during lockdown affect health? - The  Johns Hopkins News-Letter

    Video gaming is an extremely popular leisure-time activity with more than two billion users worldwide (Newzoo, 2017). However, the media as well as professionals have underscored the potential dangers of excessive video gaming. With the present research, we aimed to shed light on the relation between video gaming and gamers’ psychological functioning. Questionnaires on personality and psychological health as well as video gaming habits were administered to 2,734 individuals (2,377 male, 357 female, Mage = 23.06, SDage = 5.91). Results revealed a medium-sized negative correlation between problematic video gaming and psychological functioning with regard to psychological symptoms, affectivity, coping, and self-esteem. Moreover, gamers’ reasons for playing and their preferred game genres were differentially related to psychological functioning with the most notable findings for distraction-motivated players as well as action game players. Future studies are needed to examine whether these psychological health risks reflect the causes or consequences of video gaming.

    Introduction

    Video gaming is a very popular leisure activity among adults (Pew Research Center, 2018). The amount of time spent playing video games has increased steadily, from 5.1 h/week in 2011 to 6.5 h/week in 2017 (The Nielsen Company, 2017). Video gaming is known to have some benefits such as improving focus, multitasking, and working memory, but it may also come with costs when it is used heavily. By spending a predominant part of the day gaming, excessive video gamers are at risk of showing lower educational and career attainment, problems with peers, and lower social skills (Mihara and Higuchi, 2017). On the one hand, video game use is widespread, and it may come with certain precursors as well as consequences. On the other hand, little is known about the relations between various video gaming habits and psychological functioning. This study aims to shed light on these important relations using a large sample.

    A video game is defined as “a game which we play thanks to an audiovisual apparatus and which can be based on a story” (Esposito, 2005). In the last few years, the amount of scientific research devoted to video game playing has increased (e.g., Ferguson, 2015; Calvert et al., 2017; Hamari and Keronen, 2017). Most scientific studies in this area of research have focused on the extent of video game play and its diverse correlates. While some researchers have emphasized the benefits of game playing and even suggested a therapeutic use of video games (Primack et al., 2012; Granic et al., 2014; Colder Carras et al., 2018), others have been intrigued by its potential dangers (Anderson et al., 2010; Müller and Wölfling, 2017).

    Parents and professionals may be worried about their excessively playing children being “addicted.” However, problematic and potentially addictive video game use goes beyond the extent of playing (in hours per week; Skoric et al., 2009). It also includes such issues as craving, loss of control, and negative consequences of excessive gaming. While it is still a matter of debate whether problematic video game play should be considered a behavioral addiction, its status as a mental disorder has been clarified since the release of the DSM-5 in 2013. In the DSM-5, the American Psychiatric Association (2013) defined Internet Gaming Disorder with diagnostic criteria closely related to Gambling Disorder. Generally, this decision has been supported by many researchers (e.g., Petry et al., 2014) but has also caused controversies. Researchers have criticized the selection of diagnostic criteria and the vague definition of the Internet Gaming Disorder construct, which excludes offline games from being related to addictive use (e.g., Griffiths et al., 2016; Bean et al., 2017).

    Several studies, literature reviews, and meta-analyses have focused on the correlates of problematic video gaming, usually assessed as a continuum with addiction marking the upper end of the scale (e.g., Ferguson et al., 2011; Kuss and Griffiths, 2012). The degree of addictive video game use has been found to be related to personality traits such as low self-esteem (Ko et al., 2005) and low self-efficacy (Jeong and Kim, 2011), anxiety, and aggression (Mehroof and Griffiths, 2010), and even to clinical symptoms of depression and anxiety disorders (Wang et al., 2018). Potential consequences of video game use have been identified as well, such as a lack of real-life friends (Kowert et al., 2014a), stress and maladaptive coping (Milani et al., 2018), lower psychosocial well-being and loneliness (Lemmens et al., 2011), psychosomatic problems (Müller et al., 2015; Milani et al., 2018), and decreased academic achievement (Chiu et al., 2004; Gentile, 2009). Effect sizes have varied widely across studies (Ferguson et al., 2011). There seem to be sex and age differences with regard to video gaming behavior: potentially problematic video gaming was found to be more likely among males than females (e.g., Greenberg et al., 2010; Estévez et al., 2017), and among younger gamers (Rehbein et al., 2016).

    In addition to looking at problematic video game use and its relation to psychological functioning, it is relevant to also focus on why individuals play video games. Players use video games for very different reasons (Ryan et al., 2006; Yee, 2006) such as to distract themselves from daily hassles or because they enjoy the social relationships they have developed in the virtual world. Potentially problematic video gaming has been found to be related to various reasons for playing such as coping and escape (Hussain and Griffiths, 2009; Schneider et al., 2018), socialization (Laconi et al., 2017), and personal satisfaction (Ng and Wiemer-Hastings, 2005). Coping (Laconi et al., 2017), social interaction, and competition were among the main reasons for gaming among males but not among females (Lucas and Sherry, 2004). Mixed results emerged concerning age differences (Greenberg et al., 2010), but especially younger gamers seemed to be motivated for video gaming by social interactions (Hilgard et al., 2013). However, so far it remains unclear to what extent people’s various reasons for playing video games are differentially related to their psychological functioning.

    Besides investigating the links between potentially problematic video game use and psychological functioning as well as between reasons for playing video games and psychological functioning, it is relevant to also look at which game genres individuals prefer. Correlates of preferences for certain game genres (e.g., simulation, strategy, action, role-playing) are cognitive enhancement (Dobrowolski et al., 2015; Bediou et al., 2018), but also the amount of time spent playing (Lemmens and Hendriks, 2016; Rehbein et al., 2016) and psychopathological symptoms (Laconi et al., 2017). Males were shown to prefer action and strategy games, whereas females showed a preference for games of skill (Scharkow et al., 2015; Rehbein et al., 2016). Younger gamers seemed to prefer action games, older players more so games of skill (Scharkow et al., 2015). However, it is not yet understood to what extent preferences for certain video game genres are differentially related to psychological functioning.

    Typically, research has focused merely on violent video games (e.g., Anderson and Bushman, 2001; Elson and Ferguson, 2014) or one specific game within one specific game genre (frequently World of Warcraft; Graham and Gosling, 2013; Visser et al., 2013; Herodotou et al., 2014), thereby neglecting the variety of possible gaming habits across various game genres.

    In the present study, our objective was to examine the relation between video gaming and psychological functioning in a fine-grained manner. For this purpose, we examined psychological functioning by employing various variables such as psychological symptoms, coping strategies, and social support. Likewise, we assessed video gaming in a similarly detailed way, ranging from (a) problematic video game use, (b) the reasons for playing, to (c) the preferred game genres. This strategy prevented us from making potentially invalid generalizations about video gaming in general and allowed us to examine the spectrum of gaming habits and the respective relations between such habits and a diverse set of variables representing psychological functioning.

    Playing video games excessively should be appealing to individuals with poor psychological functioning because games allow people to avoid their everyday problems and instead immerse themselves in another environment (Taquet et al., 2017). Moreover, video games offer people a chance to connect with other people socially despite any more or less evident psychological problems they may have (Kowert et al., 2014b; Mazurek et al., 2015). On the other hand, potentially problematic video game use may also lead to psychological problems because it reduces the amount of time and the number of opportunities gamers have to practice real-life behavior (Gentile, 2009). Thus, we expected to find a negative correlation between problematic video gaming and variables representing psychological functioning such that we expected more potentially problematic video game use to be related to dysfunctional coping strategies (Wood and Griffith, 2007), negative affectivity (Mathiak et al., 2011), and poor school performance (Mihara and Higuchi, 2017). Moreover, we expected to find differential correlates of people’s reasons for playing video games and their psychological functioning: Playing for escape-oriented reasons such as distraction should go along with diverse indices of poor psychological functioning (Király et al., 2015), whereas playing for gain-oriented reasons such as the storyline or the social connections in the game should be related to adequate psychological functioning (Longman et al., 2009). Also, we expected to find people’s preferred game genres (e.g., strategy, action) to be differentially related to their psychological functioning (Park et al., 2016). Finally, we aimed to shed light on the unique contribution of each measure of psychological functioning to the prediction of problematic video game use.

    Materials and Methods

    Participants1

    A total of N = 2,891 individuals (2,421 male, 470 female) with a mean age of 23.17 years (SD = 5.99, Range: 13–65) participated in our study. Of these participants, N = 2,734 (95%) confirmed their use of video games and were thus included in further analyses (2,377 male, 357 female, with a mean age of 23.06 years; SD = 5.91, Range: 13–65). The distribution of participants with regard to sex and age mirrors the findings of past research with males and younger individuals being more likely to play video games (e.g., Griffiths et al., 2004). Participants’ place of residence was Germany.

    Procedure and Instruments2

    We posted links to our online questionnaire on various online forums as well as on popular online game sites. To achieve heterogeneity of the sample, no exclusion criteria other than having access to the Internet and understanding German were specified. As an incentive to participate in the study, four vouchers of 50€ were raffled.

    Video Gaming

    Potentially problematic video game use

    The AICA-S, the Scale for the Assessment of Internet and Computer game Addiction (Wölfling et al., 2016), was used to assess participants’ gaming behavior with regard to potential problematic use. Based on the DSM criteria for Internet Gaming Disorder (tolerance, craving, loss of control, emotion regulation, withdrawal, and unsuccessful attempts to cut back), this standardized self-report scale consists of 15 items usually with a five-point scale ranging from 1 (never) to 5 (very often). The final score (Min = 0, Max = 27 points) is computed using weighted scoring (items with an item-total correlation > 0.55 in the norm sample are weighted double; Wölfling et al., 2011). The AICA-S score can be used to differentiate between regular (0–6.5 points) and problematic use of video games (7–13 points: abuse; 13.5–27 points: addiction). In our sample, N = 2,265 (83%) were identified as regular gamers, and N = 469 (17%) as problematic gamers. We used the AICA-S as a continuous variable for all further analyses (M = 3.98, SD = 3.22, Range: 0–24). The instrument has been validated for different age groups in the general population and in clinical samples (Müller et al., 2014a, 2019, but note small sample size; Müller et al., 2014b). Cronbach’s alpha was α = 0.70. As expected, the AICA-S score was correlated with male sex (r = 0.17∗∗∗) and age (r = –0.15∗∗∗). On average, participants played video games for M = 4.09 hours per weekday (SD = 4.44, Range: 0–24), and M = 4.21 h per day at the weekend (SD = 2.99, Range: 0–24).

    Reasons for playing

    Gamers indicated how often they played video games for certain reasons. They rated each of 10 reasons separately on Likert scales ranging from 1 (never) to 4 (very often). The most prevalent reasons were relaxation (M = 2.96, SD = 0.91), amusement (M = 2.94, SD = 0.85), and because of the storyline (M = 2.67, SD = 1.10).

    Game genres

    Gamers were asked how often they usually played various video game subgenres such as first-person shooter, round-based strategy, massively multiplayer online role-playing games (MMORPGs), life simulations, and others. Ratings were made on Likert scales ranging from 1 (never) to 4 (very often). Using Apperley’s (2006) classification of game genres, we categorized the subgenres into the main genres action (M = 2.54, SD = 0.84), strategy (M = 2.13, SD = 0.80), role-playing (M = 2.01, SD = 0.73), and simulation (M = 1.58, SD = 0.44). A cluster for unclassified subgenres (M = 1.54, SD = 0.39) was added to additionally account for such subgenres as jump’n’runs and games of skill. Descriptive statistics and intercorrelations for all measures (including sex and age) are presented in Supplementary Tables S1–S4.

    Psychological Functioning

    Participants provided ratings of their psychological functioning on the following constructs:

    General psychopathology

    The SCL-K-9 (Klaghofer and Brähler, 2001), a short version of the SCL-90-R (Derogatis, 1975), was administered to assess participants’ subjective impairment regarding psychological symptoms (somatization, obsessive-compulsive, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism). The SCL-K-9 score is strongly correlated with the original score of the SCL-90-R (r = 0.93). The 9 items were answered on 5-point Likert-type scales ranging from 1 (do not agree at all) to 5 (agree completely). Cronbach’s alpha was satisfactory (α = 0.77).

    Coping

    We assessed 10 coping strategies with the Brief COPE (Carver, 1997; German version by Knoll et al., 2005), which is the shorter version of the COPE (Carver et al., 1989): self-distraction, denial, substance use, venting, self-blame, behavioral disengagement, acceptance, active coping, planning, and positive reframing. The two items per subscale were administered on 5-point Likert-type scales ranging from 1 (never) to 5 (very often). Intercorrelations of the two items per subscale ranged from r = 0.32, p < 0.001 for positive reframing to r = 0.78, p < 0.001 for substance use (with one exception: r = -0.05, p = 0.01 for self-distraction).

    Affect

    We measured general affect as a trait and affect during video gaming as a state using the German version (Krohne et al., 1996) of the Positive and Negative Affect Schedule (PANAS; Watson et al., 1988). On a 5-point Likert-type scale ranging from 1 (not at all) to 5 (completely), participants rated the intensity of 20 adjectives. Cronbach’s alpha was α = 0.78 for general positive affect, α = 0.83 for general negative affect, α = 0.85 for positive affect while playing, and α = 0.83 for negative affect while playing.

    Shyness

    The measure for the assessment of shyness in adults (Asendorpf, 1997) consists of 5 items that were answered on a 5-point Likert-type scale ranging from 1 (not at all) to 5 (completely). Cronbach’s alpha was excellent (α = 0.86).

    Loneliness

    We administered the German version (Elbing, 1991) of the NYU Loneliness Scale (Rubenstein and Shaver, 1982). The 4 items were answered on 5- to 6-point Likert-type scales. Cronbach’s alpha was satisfactory (α = 0.79).

    Preference for solitude

    A 10-item measure of preference for solitude (Nestler et al., 2011) was answered on a 6-point Likert-type scale ranging from 1 (not at all) to 6 (completely). Cronbach’s alpha was excellent (α = 0.86).

    Life satisfaction

    Participants answered a one-item life satisfaction measure on a 4-point Likert-type scale ranging from 1 (not at all) to 4 (completely).

    Self-esteem

    We administered the German version (von Collani and Herzberg, 2003) of the Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1979). The 10 items were answered on a 4-point Likert-type scale ranging from 1 (not at all) to 4 (completely). Cronbach’s alpha was excellent (α = 0.88).

    Self-efficacy

    We administered a 10-item generalized self-efficacy scale (Schwarzer and Jerusalem, 1995), which was answered on a 4-point Likert-type scale ranging from 1 (not at all) to 4 (completely). Cronbach’s alpha was excellent (α = 0.86).

    Social support and friends

    We administered the perceived available social support subscale from the Berlin Social Support Scales (BSSS; Schwarzer and Schulz, 2003). The 8 items were answered on a 5-point Likert-type scale ranging from 1 (not at all) to 5 (completely). Cronbach’s alpha was excellent (α = 0.94). Participants indicated how many offline friends and offline acquaintances they had (r = 0.44, p < 0.001) as well as how many online friends and online acquaintances they had (r = 0.33, p < 0.001). Due to left-skewed distributions, we logarithmized the data before aggregation.

    Grades

    Participants reported their grade point average. German grades are assessed on a scale that ranges from 1 (excellent) to 6 (insufficient). Thus, higher scores indicate worse grades.

    Participants further reported their sex and age. Both were used as control variables in further analyses.

    Analyses

    In a first step, we computed zero-order correlations between the video gaming variables and the measures of psychological functioning. In a second step, we computed partial correlations in which we controlled for sex and age because past research has repeatedly shown that sex and age are correlated with both video gaming (Homer et al., 2012; Mihara and Higuchi, 2017) and psychological functioning (Kessler et al., 2007; Nolen-Hoeksema, 2012). Finally, we explored the unique contribution of each measure of psychological functioning to the prediction of potentially problematic video gaming. Therefore, we computed regressions with potentially problematic video gaming as the dependent variable and sex, age, and the measures of psychological functioning as predictors (entered simultaneously into the regression equation). By employing this procedure, we were able to determine the effect that each variable had over and above the other ones. For instance, we could identify whether general psychopathology was predictive of potentially problematic video game use when the influence of all other variables (e.g., shyness, loneliness, and others) was held constant.

    Additionally, we included analyses regarding sex and age differences in the link between video gaming and psychological functioning. Since we collected a self-selected sample where different sexes and age groups were not represented equally, our findings are only preliminary, but may stimulate future research.

    Results

    Potentially Problematic Video Game Use and Psychological Functioning

    First, we examined whether potentially problematic video game use was related to various psychological functioning variables. As can be seen in Table 1, the results for the zero-order correlations were similar to those for the partial correlations in which we controlled for sex and age. A medium-sized positive relation to the potentially problematic use of video games emerged for the presence of psychological symptoms including depression, anxiety, and hostility. Furthermore, several coping strategies were differentially associated with the potentially problematic use of video games: Self-blame and behavioral disengagement showed the strongest positive relations to potentially problematic video game use, followed by denial, acceptance, substance use, self-distraction, and venting. Planning, active coping, and, to a lesser extent, positive reframing were negatively associated with the potentially problematic use of video games. Moreover, the association with potentially problematic video game use was negative for general positive affect and positive and larger in size for general negative affect. However, potentially problematic video game use was clearly positively associated with the experience of both positive and negative affect while playing. Further, a preference for solitude, shyness, and loneliness were positively correlated with the potentially problematic use of video games. Lower self-esteem, lower life satisfaction, and, to a lesser extent, poorer perceived social support and lower self-efficacy went along with potentially problematic video game use. There was an association between fewer offline friends and acquaintances but more online connections with potentially problematic video gaming. Finally, poorer performance in school (i.e., higher grades) was related to the potentially problematic use of video games. These results suggest that potentially problematic video gaming goes along with poor psychological functioning and vice versa.

    [“source=frontiersin”]

    Categories: Gaming

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