Associations of Social Support,Friends Only Known Through the Internet,and Health-Related Quality of Life with Internet Gaming Disorder in Adolescence

Abstract

Internet Gaming Disorder (IGD) has been included in the current edition of the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5). In the present study, the relationship among social support, friends only known through the Internet, health-related quality of life, and IGD in adolescence was explored for the first time. For this purpose, 1,095 adolescents aged from 12 to 14 years were surveyed with a standardized questionnaire concerning IGD, self-perceived social support, proportion of friends only known through the Internet, and health-related quality of life. The authors conducted unpaired t-tests, a chi-square test, as well as correlation and logistic regression analyses. According to the statistical analyses, adolescents with IGD reported lower self-perceived social support, more friends only known through the Internet, and a lower health-related quality of life compared with the group without IGD. Both in bivariate and multivariate logistic regression models, statistically significant associations between IGD and male gender, a higher proportion of friends only known through the Internet, and a lower health-related quality of life (multivariate model: Nagelkerke's R² = 0.37) were revealed. Lower self-perceived social support was related to IGD in the bivariate model only. In summary, quality of life and social aspects seem to be important factors for IGD in adolescence and therefore should be incorporated in further (longitudinal) studies. The findings of the present survey may provide starting points for the development of prevention and intervention programs for adolescents affected by IGD.

Introduction

In 2013, Internet Gaming Disorder (IGD) was included in Section III of the current version of the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) as a new condition warranting more clinical research and experience.¹ IGD refers to a problematic use of video games and is characterized by nine different diagnostic criteria (preoccupation with playing, withdrawal symptoms when not playing, tolerance, unsuccessful attempts to reduce or stop playing, giving up other activities, continuation of playing despite problems, deceiving or covering up playing, playing to escape adverse moods, and risking or losing relationships or career opportunities because of excessive playing).² To confirm a diagnosis of IGD, at least five out of these nine criteria have to be met for the last 12 months.¹ Furthermore, a cutoff point of five criteria was empirically verified in first studies.^3,4 Petry et al.⁵ explored the fit of eight established instruments measuring “problematic gaming” or “Internet addiction” (that were published before the release of the DSM-5)¹ to these new criteria, and found none of them to cover all nine diagnostic criteria of IGD. In the meantime, several new questionnaires covering all aspects of IGD were developed and published. Comprehensive theoretical models for the etiology of the disorder are still lacking, but Király et al.⁶ underlined the interplay of three key factors: Structural characteristics of the video games, psychological characteristics of the gamer, and motivations for playing games.

Prevalence estimates of IGD

Following Petry et al.,² only two prevalence estimates^4,7 based on appropriate instruments have been published for IGD. According to the National Institutes of Health (NIH), “prevalence” is defined as the proportion of a population who has or had a specific characteristic (IGD in the present study) in a given time period (the last 12 months), and it is “estimated” if information on samples of the population of interest is available. Rehbein et al.⁷ surveyed 11,003 adolescents (aged between 13 and 18 years) in Lower Saxony (one of the 16 federal states in Germany) and reported a prevalence estimate of 1.2 percent (confidence interval [95% CI]: 1.0–1.4). Lemmens et al.⁴ investigated a representative sample of Dutch adolescents and adults (age range: 13–40 years) and observed a prevalence rate of 3.8 percent (based on a latent class analysis) or 5.4 percent (based on the cutoff point ≥5). Recently, Pontes et al.⁸ reported a prevalence rate of 2.5 percent (95% CI: 1.7–3.7) in a sample of Slovenian adolescents (N = 1,071, aged 12–16 years). To sum up, prevalence estimates between 1 and 5 percent for IGD were reported in population samples from different European countries.

Associations between social support and quality of life with IGD

Up to now, only very few studies used entirely DSM-5-based instruments² to investigate associations between IGD and different aspects of psychological well-being of the gamer or his or her motivation to play video games. In many published studies, the generally important role of social support in maintaining health and mitigating different effects of stress was shown.⁹ According to Thoits¹⁰^(pS46) social support refers to “…emotional, informational, or practical assistance from significant others, such as family members, friends, or coworkers….” Such “…support actually may be received from others or simply perceived to be available when needed.” To our knowledge, interrelations between social support and IGD have not been examined yet. In one published survey, Longman et al.¹¹ reported higher usage times of video games to be associated with lower levels of offline social support, whereas no differences in self-perceived online social support between adolescents with higher and lower usage times were observed. It is also conceivable, that social support may be relevant for the emergence or maintenance of IGD. As first indications for this assumption, in one study bivariate, associations between IGD and higher levels of loneliness as well as lower levels of prosocial behavior were revealed.⁴ Therefore, a perceived lack of social contacts or social support may promote a behavioral pattern such as IGD. These reflections lead us to the first research question (RQ1) in the present study: Are there statistically significant associations between self-perceived social support and IGD in adolescence?

An interesting aspect concerning social support is the role of friends only known through the Internet. These friends only known through the Internet (in addition to traditional social contacts like schoolmates), could either be a source of social support on the one hand or promote more intense media activities (such as IGD) on the other hand or even both. In the present study, it was not determined how the adolescents and their friends only known through the Internet got to know each other the first time or how they interact online. Therefore, these social contacts could be made while playing video games together, on social media sites, and so on. To the best of our knowledge, empirical data on relationships between friends only known through the Internet and IGD are currently not available. Thus, the second research question (RQ2) is: Are there statistically significant associations between the proportion of friends only known through the Internet and IGD in adolescence?

In two surveys, the associations between satisfaction of life (a construct closely related to health-related quality of life) and IGD were investigated: Lemmens et al.⁴ examined 2,444 adolescents and adults (aged 13–40 years) and observed a statistically significant bivariate correlation between IGD and lower satisfaction with life. Subramaniam et al.¹² surveyed 1,251 participants (age range: 13–40 years) and also reported a lower satisfaction with life to be associated with IGD.

Thus, first findings indicate interrelations between IGD and satisfaction with life. But it is still unexplained if the relations are similar for health-related quality of life and IGD. These thoughts lead us to the third research question (RQ3): Are there statistically significant associations between health-related quality of life and IGD in adolescence?

An increasing body of empirical evidence shows the importance of social support (offline or online) and quality of life for psychological well-being.^9,13 It can be assumed that these aspects are also of high importance for IGD. Therefore, the objective of the present study was to investigate how IGD in adolescence is related to self-perceived social support, (proportion of) friends only known through the Internet, and health-related quality of life.

Materials and Methods

Procedure

According to published findings, the prevalence estimates for IGD in Europe are in a single-digit percentage range.^4,7,8 Therefore, in general population samples, only a small number of persons are expected to be affected by IGD. A small number of cases lead to restrictions concerning suitable statistical analysis methods. To counteract these problems, adolescents with subjectively perceived problems in digital media use were oversampled in the present survey. Based on parental and adolescent responses to two screening items (assessing the self-perceived frequency of adolescent excessive media use and the severity of problematic media use), the adolescents were assigned to a group with more subjectively perceived problems in digital media use (higher risk group) or to another group with less subjectively perceived problems (lower risk group). The possible answers to the self-perceived frequency of adolescent excessive media use were 1 = “never,” 2 = “rarely,” 3 = “sometimes,” 4 = “often,” 5 = “very often.” The response format for the severity of adolescent problematic media use was 1 = “unproblematic,” 2 = “somewhat difficult,” 3 = “moderately difficult,” 4 = “seriously difficult.” The adolescent (more specifically the family dyad) was assigned to the higher risk group, if the adolescent or the parent (or both) had rated the frequency of adolescent media use at least sometimes to be excessive and the severity of adolescent problematic media use at least somewhat difficult (in all other cases the dyad was allocated to the lower risk group).

The data collection was carried out by an experienced market research firm (GfK Media and Communication Research) in 1,095 families. The predefined target values for the market research firm were 700 higher risk group families (70 percent of the whole sample) and 300 lower risk group families (30 percent). All in all, the market research firm investigated 1,095 instead of the predefined 1,000 families (to ensure they will achieve the final target values in the planned longitudinal course of the study). The target achievement was as follows: 757 higher risk group families (or 69.1 percent) and 338 lower risk group families (30.9 percent). All families were first contacted by phone by the 253 involved interviewers, and the screening items were asked during this phone call. For the first contact, there were only very few selection criteria: one child in the family had to be aged between 12 and 14 and the German (of the parent and child) had to be fluent. After the quota for the lower risk group families (∼30 percent of the entire sample) was fulfilled, all families reporting a “lower risk group-profile” were only screened but not surveyed by the interviewers. There were also predefined quotas for the entire sample regarding age (33.3 percent for every age group), gender (50.0 percent each), and the regions (analogous to the population distribution in Germany). All data were collected at the family's home (face-to-face interviews, separately with the adolescent and his or her parent) in all 16 German federal states (every family received 10€ for participation).

Measures

IGD was measured for the last 12 months using the Internet Gaming Disorder Scale (IGDS).⁴ The IGDS consists of nine self-report items (binary response format: 0 = “no,” 1 = “yes”) on the presence of IGD symptoms. According to the Kuder–Richardson-20 formula for binary items, reliability of the IGDS was 0.82 in the sample of the present study. By summing up the responses, a sum score was calculated with a higher sum indicating a higher risk of IGD. According to Lemmens et al.,⁴ adolescents who answered “yes” to five or more out of the nine criteria (positive screening result) were classified as having IGD.

Self-perceived social support was measured using the Oslo Social Support Scale (OSSS).¹⁴ The OSSS consists of three questions with a different response format for each item. Cronbach's alpha was 0.57 for the OSSS. A higher sum indicates a better social support.

Furthermore, we applied a single question (5-level response format: 1 = “none,” 2 = “few,” 3 = “half and half,” 4 = “most,” 5 = “all”) to measure the proportion of Internet-only friends of the adolescent in all of his or her friends. A higher rating indicates more friends who are only known through the Internet.

To assess self-reported health-related quality of life within the last week, we used the Kidscreen-10.¹³ The Kidscreen-10 consists of 10 items with two different 5-level response formats (1 = “never,” 2 = “seldom,” 3 = “quite often,” 4 = “very often,” 5 = “always” and 1 = “not at all,” 2 = “slightly,” 3 = “moderately,” 4 = “very,” 5 = “extremely”). Following Ravens-Sieberer et al.,¹⁵^(p156) the instrument evaluates “…aspects of the children's physical well-being, moods and emotions, autonomy, the satisfaction with relationship with parents and the atmosphere at home, perceived nature of the respondents' relationships with other children/adolescents and the child's/adolescent's perceptions of his/her cognitive capacity, learning and concentration, and his/her feelings about school.” Cronbach's alpha was 0.83 for the Kidscreen-10 in the sample of the present survey. Higher Kidscreen-10 scores indicate a better health-related quality of life. Additional information on sociodemographic characteristics such as age and gender were assessed from both adolescents and parents.

Participants

The sample consisted of 1,095 family dyads (an adolescent and one related parent each). We investigated 539 girls (49.2 percent) and 556 boys (50.8 percent). The mean age of adolescents was 12.99 (SD = 0.82, range: 12–14) years. Based on the current school performance of the adolescent, the related parent was requested to predict the prospective level of graduation of his or her child (forecast). Altogether, the parents predicted for 40.8 percent of the adolescents a graduation on a high educational level, for 48.2 percent on a medium educational level, and for 11.0 percent of the sample on a low level.

Data analysis

Statistical analyses were performed on all 1,095 cases (regardless of whether an adolescent was assigned to the higher or lower risk group). Overall, 76 adolescents (6.9 percent of the sample) stated that they had never played video games (we asked for all types of online or offline games played on computer, tablet computer, games console, and smartphone) and thus, did not have to answer the nine IGDS questions. For these 76 cases, we determined the IGDS sum value on 0 and assigned them to the group without IGD. We used SPSS version 22.0 (IBM, 2013, New York) to calculate unpaired t-tests, a chi-square test, as well as correlation and logistic regression analyses. We compared the two groups without (sum score <5 in the IGDS) and with IGD (sum score ≥5). The response variable for the logistic regression analysis was a diagnosis of IGD (“no” or “yes,” based on the cutoff point ≥5).⁴ As explanatory variables, we used gender of the adolescent, age of the adolescent, social support, proportion of friends only known through the Internet, and health-related quality of life. We conducted five binary logistic regression analyses (separately for each independent variable) and one multivariable analysis (including all explanatory variables). The goodness of fit for the multivariate analysis was verified by the Hosmer–Lemeshow test.

Results

Group comparison

Overall, 835 adolescents had a negative and 260 adolescents a positive screening result (sum score ≥5 in the IGDS) for IGD. We found no difference in age between the two groups (12.97 years vs. 13.02 years, t = −0.83, df = 1,093, and p = 0.407). The gender ratios were different for both groups (χ ² = 110.45, df = 1, and p < 0.001). A higher percentage of males were affected by IGD. We observed statistically significant differences in the mean values of self-perceived social support (10.55 vs. 9.32, t = 8.62, df = 1,093, and p < 0.001), proportion of friends only known through the Internet (1.57 vs. 2.10, t = −9.21, df = 1,093, and p < 0.001) and health-related quality of life (41.74 vs. 37.07, t = 11.71, df = 381.56, and p < 0.001) between the two groups. Adolescents with IGD reported lower self-perceived social support, a higher proportion of friends only known through the Internet, and a lower health-related quality of life compared with the group without IGD.

Bivariate analyses

The bivariate correlations of all included variables are presented in Table 1. In answer to RQ1, RQ2, and RQ3, we found in the bivariate logistic regression analyses statistically significant associations between the affiliation to the group with IGD and male gender, a lower self-perceived social support, a higher proportion of friends only known through the Internet, and a lower health-related quality of life (Nagelkerke's R² values between 0.09 and 0.18, see Table 2). Age of the adolescent was not related to IGD.

Table 1.

Correlation Matrix for All Included Variables

Variable	Internet Gaming Disorder Scale	Gender of adolescent	Age of adolescent	Social support	Proportion of friends only known through the Internet	Health-related quality of life
Internet Gaming Disorder Scale	1
Gender of adolescent^a	−0.40^**	1
Age of adolescent	0.03	−0.01	1
Social support	−0.28^**	0.05	−0.13^**	1
Proportion of friends only known through the Internet	0.31^**	−0.10^**	0.17^**	−0.24^**	1
Health-related quality of life	−0.42^**	0.03	−0.10^**	0.50^**	−0.20^**	1

Male gender = 0, female gender = 1..

p < 0.01.

Table 2.

Associations of Social Support, Proportion of Friends Only Known Through the Internet, and Health-Related Quality of Life with Internet Gaming Disorder in Adolescents

	Bivariate regression models					Full regression model
Variable (questionnaire)	Internet Gaming Disorder (N = 1,095), unadjusted odds ratio (95% CI)					Internet Gaming Disorder (N = 1,095), adjusted odds ratios (95% CI)
Gender of adolescent^a	0.19^*** (0.14–0.26)	—	—	—	—	0.15^*** (0.10–0.22)
Age of adolescent	—	1.08 (0.91–1.27)	—	—	—	0.85 (0.69–1.05)
Social support (Oslo Social Support Scale)	—	—	0.75^*** (0.70–0.80)	—	—	0.92 (0.84–1.01)
Proportion of friends only known through the Internet	—	—	—	2.01^*** (1.71–2.36)	—	1.78^*** (1.47–2.16)
Health-related quality of life (Kidscreen-10)	—	—	—	—	0.85^*** (0.83–0.88)	0.85^*** (0.82–0.89)
Nagelkerke's R²	0.15	0.00	0.09	0.10	0.18	0.37

Male gender = 0, female gender = 1.

***

p < 0.001.

Multivariable analysis

As a subsequent answer to RQ2 and RQ3, we observed in the multivariate logistic regression analysis that male gender, a higher proportion of friends only known through the Internet, and a lower health-related quality of life were associated with higher odds of IGD (see right column of Table 2 for adjusted odds ratios). In contrast, age of the adolescent and self-perceived social support were not related to IGD (further answer to RQ1) in the multivariable analysis. The Hosmer–Lemeshow test was not statistically significant for the computed multivariate model (p = 0.572), thus indicating a good model fit. Nagelkerke's R² showed a value of 0.37, indicating that more than a third of the variation between the two groups (adolescents without and with IGD) was explained by these factors.

Discussion

In the present study, associations among self-perceived social support, friends only known through the Internet, health-related quality of life, and IGD in adolescence were explored for the first time. In a sample of 1,095 adolescents, we found bivariate relationships between all these three aspects and the disorder, whereas in a multivariate model, only male gender, friends only known through the Internet, and health-related quality of life were associated with IGD.

The finding concerning male gender, is in line with the result of Rehbein et al.,⁷ who also reported that boys are more frequently affected by IGD than girls in adolescence (Pontes et al.⁸ reported only a prevalence estimate for the whole sample, but no comparison between male and female adolescents). According to Feierabend et al.,¹⁶ 83 percent of the male adolescents used video games daily or several times a week, whereas only 43 percent of the female adolescents used these games daily or several times a week (values based on a population sample of 1,200 German adolescents aged 12–19 years). This finding indicates a much higher number of boys than girls playing video games with a high intensity (a behavior pattern that could promote the development of IGD).

Furthermore, in the present survey, we observed a statistically significant relationship between lower health-related quality of life and IGD. This finding goes well with the results of Lemmens et al.⁴ and Subramaniam et al.,¹² both reporting a lower satisfaction with life (a construct closely related to health-related quality of life) to be associated with IGD in combined samples of adolescents and adults. Thus, an intense and problematic use of video games could be interpreted as an attempt of the adolescent to compensate his or her lower quality of life. But based on the available cross-sectional data, it remains unclear if a lower health-related quality of life promotes adolescent IGD or, vice versa, if IGD leads to a lower level of quality of life or if both aspects interact.

The high importance of social aspects for video game usage in general (especially for multiplayer games) was revealed in some previous studies. For example, there is empirical evidence that social interactions are an important motive for playing multiplayer games.^17,18 In the present study, for the first time, the proportion of friends only known through the Internet was taken into account and associations with a higher risk for IGD were observed. A higher proportion of friends only known through the Internet are likely to be positively correlated with a higher amount of social interactions on the Internet or in the video game. A possible consequence could be a neglect of offline social contacts and correspondingly a lower self-perceived social support [as measured by the OSSS¹³ and in line with the results of Longman et al.¹¹ for offline support].

The present study has several limitations. We have used an approach to oversample adolescents with different degrees of severity of problematic media use. We did not investigate a representative population sample and surveyed only young adolescents (aged 12–14 years). Therefore, it remains unclear, if the results are valid for all German adolescents. Furthermore, to measure health-related quality of life, we applied the Kidscreen-10.¹³ Other instruments would have provided the opportunity for a better differentiation between different aspects of quality of life (e.g., the Kidscreen-27 assesses five domains: “physical,” “psychological well-being,” “parents,” “peers,” and “school”).¹³ Possibly, IGD in adolescence is associated with some but not all dimensions of health-related quality of life.

Further on, for a deeper understanding, it would have been valuable to assess offline and online aspects of social support (analogous to the concept realized by Longman et al.¹¹) and to differentiate between them. But the applied instrument (OSSS) measures self-perceived offline social support only. Furthermore, the OSSS rather evaluates the quantity (e.g., number of persons) than the quality of social support (how satisfied an adolescent is with his or her social support). But of course, a higher number of social contacts must not necessarily be more supportive than few very intensive friendships. Besides, the OSSS was the sole instrument with a poor reliability in the present study.

It is also conceivable, that the affected adolescents experience a lower offline social support on the one hand, but perceive a stronger social support in the video game context on the other hand (maybe as an appropriate compensation). Based on the available data, we cannot answer this question. Besides, we have not collected further information on the types of games that were played by the adolescents. It is imaginable, that distinct types of video games affect the investigated aspects (e.g., health-related quality of life) in different ways.

In further studies, more extensive assessments of social contacts limited to the Internet or video games could be useful (e.g., frequency of contacts, number of persons, and importance of in-game contacts), for a deeper understanding of these relationships. Currently, comprehensive theoretical models regarding IGD and incorporating the different social aspects are still lacking. As important next steps for future research activities on IGD, we would suggest the development of a theoretical framework and its empirical examination.

Despite these limitations, the present study makes an important contribution to the existing research on IGD. According to our findings, especially health-related quality of life and social contacts (in the context of video game use) seem to be important aspects for IGD in adolescence. These aspects (e.g., health-related quality of life) should be incorporated in further longitudinal studies, to clarify if they are only correlates of or also predictors for IGD. If the results were confirmed in further studies, the reported findings should be considered in the development of interventions or prevention measures for adolescents affected by IGD.

Footnotes

Acknowledgments

The data for the present article have been gathered in the VEIF project. The VEIF study was supported by the German Research Foundation (DFG, grant to the project leader Prof. R.K., grant number KA 1611/6-1).

Author Disclosure Statement

No competing financial interests exist.

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