Relationships between Severity of Internet Gaming Disorder, Severity of Problematic Social Media Use, Sleep Quality and Psychological Distress

Serious health concerns have been linked to specific types and patterns of engagement in internet usage, leading to the concept of “internet addiction” [1,2]. The availability, accessibility and affordability of internet usage worldwide may lead to worsening health problems. According to the International Telecommunication Union (ITU) [3], global internet usage increased from 1990 million in 2010 to 3385 million in 2016. In Hong Kong and Macau, it is estimated that 23.3% of young adults aged 18 to 30 years experience problems with online gaming [4]. Therefore, problematic gaming is a significant concern for young adults in these Asian jurisdictions, and findings suggest similar concerns in other (American, European) countries. In addition to online gaming, internet-based social media platforms (e.g., YouTube, Snapchat, and Instagram) are frequently used, with nearly three fourths (71%) of young adults aged 18–24 years in the US using these media platforms doing so multiple times per day [5]. As such, many young adults may be vulnerable to experiencing Internet gaming and/or social media addictions.

Definitions for addictions have changed over time. Recently, the American Society of Addiction Medicine defined addiction as, “a treatable, chronic medical disease involving complex interactions among brain circuits, genetics, the environment, and an individual’s life experiences. People with addiction use substances or engage in behaviors that become compulsive and often continue despite harmful consequences” [6]. Indeed, behavioral addictions have been included in the latest edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), with gambling disorder and internet gaming disorder (IGD) defined, with the latter as a provisional diagnostic entity [7]. Recently, gaming disorder has been added to the International Classification of Diseases 11th Revision (ICD-11) as a disorder due to addictive behaviors [8]. With poor control over repetitive, persistent, and dysfunctional behaviors, behavioral addictions can result in negative health consequences, including social relationship problems, impairments in functional roles and activities, sleep problems, and mental disorders [9]. Therefore, assisting people, especially young adults, in tackling behavioral addictions is important for healthcare providers.

Debates have focused on whether generalized internet addiction or specific internet addictions are diagnosable entities, and if the latter, which disorders constitute specific internet addictions [10,11]. In the current study, we focused on gaming and social media addictions given their potential impacts. Both social media addiction (SMA) and IGD have been associated with sleep disturbances, including sleep quality deterioration and reductions in sleep duration [12,13]. A potential reason for both SMA and IGD leading to sleep disturbances involves portable smartphones and other portable digital devices that may be brought to bed [13].

With portable smartphones and Wi-Fi access, internet (including of social media) may constitute an unstructured activity, one not limited in time and one that can displace time [14]. As such, SMA may lead to lack of sleep. Delayed bedtimes and late waking times may further lead to the rhythm desynchronization and impact school performance [15]. Other potential mechanisms in disrupting sleep may include psychological stimulation (i.e., excited mood due to use of social media) [16], light-emitting screens (i.e., light may suppress sleep-promoting hormones like melatonin that are typically elevated before bedtime) [17], and shortened sleep duration [18]. Similar considerations exist for online gaming. Gamers from different time zones often participate in multiplayers games [12]. Therefore, some gamers may avoid logging off or may arise in the middle of the night to continue gaming [19], leading to irregular or disorganized sleep-wake patterns. Individuals may become sleep-deprived in order to engage in virtual activities. Consistently, playing online games has been associated with longer sleep latencies and shorter total rapid eye movement (REM) sleep [20].

Apart from negative effects on sleep, SMA and IGD may impact psychological well-being, with associations with depression, anxiety, and stress [2,21]. “Fear of missing out” may keep individuals on social media sites and lead to stress and burnout [4,21]. Internet addiction, as a general concept, may lead to poor sleep quality and psychological problems [2,22,23,24]. Both SMA [25,26,27,28,29] and IGD [30,31,32] have been associated with poor psychological health. However, differential associations of IGD and SMA with health outcomes have been rarely examined and compared in the same studies. To our best knowledge, only one study has examined relationships between IGD/SMA and symptoms of psychiatric disorders (i.e., attention-deficit/hyperactivity disorder, obsessive- compulsive disorder, anxiety, and depression) [33] and another has examined relationships between IGD/SMA and psychological distress (i.e., anxiety, stress, and depression) [32]. Therefore, more research is needed. Specifically, the activity demands and behavioral patterns of the two addictions are different. As internet gaming and use of social media may have different activity demands and behavioral patterns, with gaming typically requiring more rapid reactions and sustained attention over a continuous time period than using social media use, IGD and SMA may differentially impact sleep quality and psychological distress.

The current preliminary study was designed to explore how severities of IGD and SMA relate to sleep quality and emotional distress in a population at risk of internet addiction (i.e., young adults) [34] in order to complement prior studies of primary and secondary school students [1,35]. We hypothesized that both severities of IGD and SMA would relate to poorer sleep quality and more emotional distress.

A cross-sectional study using convenience and snowball sampling was conducted among university students aged 18–24 in Hong Kong in 2019.

Participants (N = 300) had a mean (SD) age of 20.89 (1.48) years. Less than half of the participants were male (40.67%), with small proportion of current smokers (0.36%). On average, participants spent 5.29 h (2.34) on smartphones, 3.09 h (1.80) on social networks and 1.19 h (1.53) gaming per day.

Participants had a mean (SD) score of 16.98 (6.48) on the IGDS9-SF, 15.37 (4.11) on the BSMAS, 5.16 (4.47) for Depression; 4.18 (3.83) for Anxiety; 6.72 (4.25) for Stress; and 6.63 (2.14) on the PSQI (Table 1). Additionally, all scores on the IGDS9-SF, BSMAS, DASS-21, and PSQI distributed normally or nearly normally as their skewness values were between 0.34 and 1.15 and kurtosis values were between −0.32 and 2.24. According to the cutoffs on the IGDS9-SF (score of 21 or above) and BSMAS (score of 19 or above), 77 (25.7%) of participants had IGD and 67 (22.3%) had SMA.

Table 2 shows that all the studied variables were significantly correlated (p < 0.001). More specifically, IGDS9-SF, BSMAS, depression, anxiety, stress, and PSQI scores were all positively correlated (r = 0.221 to 0.363). The magnitudes of correlations between DASS-21 subscales and IGDS9-SF (r = 0.331 to 0.363) were similar to those between DASS-21 subscales and BSMAS (r = 0.336 to 0.384). Indeed, the Fisher’s r-to-z transformation on dependent samples showed non-significant findings (z = 0.227 to 0.807; p = 0.42 to 0.82). Although the correlation between BSMAS and PSQI scores (r = 0.351) showed a numerically larger magnitude than that between IGDS9-SF and PSQI (r = 0.249), the Fisher’s r-to-z transformation on dependent samples showed no significant difference in the correlation comparison (z = 1.509; p = 0.13).

Multiple linear regressions in Table 3 (F-values ranged between 6.916 and 10.323; all p < 0.001) showed that both IGDS9-SF and BSMAS were associated with all outcome variables (i.e., depression, anxiety, stress, and sleep quality) after controlling for age, gender, time spent on smartphones, time spent on social media, and time spent gaming. As shown by the standardized coefficient (β), IGDS9-SF had a higher association with depression (β = 0.295), anxiety (β = 0.325), and stress (β = 0.339) as compared to BSMAS (β = 0.235 for depression; 0.219 for anxiety; 0.262 for stress) without significance (t = 0.116 to 0.577; p = 0.56 to 0.91). In contrast, BSMAS scores had a significantly higher association with poor sleep quality (β = 0.292) as compared to IGDS9-SF scores (β = 0.157; t = 2.436; p = 0.01).

This study found that participants with greater IGD and/or SMA severities had more depression, anxiety, and stress. Moreover, participants’ sleep quality was poorer with greater severities of IGD or SMA. According to our Pearson’s correlation and multiple regression results, sleep quality demonstrated a numerically more robust association with SMA severity as compared to IGD severity. On the other hand, similar to findings from Pontes [32], our findings showed that psychological distress demonstrated a numerically more robust association with IGD severity, as compared SMA severity. Although no significant differences were found in the comparisons of Pearson’s correlation coefficients, regression analyses revealed that some relationships were significantly different in the association magnitudes and some were not. Specifically, the sleep quality had a significantly stronger association with SMA severity (β = 0.292) than with IGD severity (β = 0.157); psychological distress had similar magnitudes of association with both SMA severity (β = 0.219 to 0.262) and IGD severity (β = 0.295 to 0.339). We believe that the results of comparing regression coefficients are more robust than those of comparing Pearson’s correlation coefficients, because Pearson’s correlation did not control confounders’ effects, whereas regression analysis did. Therefore, we tentatively conclude that severities of IGD and SMA share similar associations with psychological distress; SMA severity had stronger association with sleep quality than did IGD severity.

Our sample had comparable or higher IGDS9-SF scores (Mean score = 16.98) than those from the general population in Italy (Mean score = 15.93; n = 687) [43]. Our sample also had comparable or higher BSMAS scores (Mean score = 15.37) than those from the general population in Italy (Mean score = 14.20; n = 734) [48]. When comparing scores to similar ethnic populations, our sample had similar IGDS9-SF scores relative to a sample comprised of young adults from Hong Kong and Taiwan (Mean score = 16.92; n = 640) [46] and comparable or slightly higher BSMAS scores (Mean score = 14.46; n = 640) [46].

Associations between IGD severity and psychological distress found in the present study are in line with previous studies [2,4,22]. Adolescents with anxiety, depression, or stress may spend excessive time on gaming on the internet as a coping mechanism, to escape from worries and difficulties in reality [22,59]. Unfortunately, gaming may not help people cope with psychological distress in a positive way. Spending more time gaming may provoke more emotional difficulties, and subsequently lead to IGD and related problems [59]. This cycle could further exacerbate symptoms of IGD and psychological distress [59]. Additionally, people with IGD have exhibited relatively less cognitive reappraisal and more expressive suppression, and these tendencies may prevent emotional difficulties from being resolved and the potential for depression to develop or worsen [59].

The present study also found a positive correlation between IGD severity and poor sleep quality, consistent with prior studies. Achab et al. suggested that people with IGD tend to have sleep deprivation or diurnal sleepiness [12], in line with findings that people who engage frequently in gaming are likely to delay their bedtimes and shorten their total time spent in bed [14]. Internet gaming may also arouse central and autonomic nervous systems, which may subsequently lead to increases in sleep latency [20]. Prolonged gaming may lead to physical discomfort, such as muscular pain and headache, which may impact sleep quality [13]. As a result, engaging more frequently in internet gaming may lead to poorer sleep.

The present study found a significantly positive association between SMA severity and psychological distress, in line with previous studies that people with SMA are prone to depressive and anxiety symptoms [4,21]. A sense of loss of control may underlie this phenomenon [9]. Individuals with more problematic smartphone use may experience more functional impairment, and this may interfere with their school/work and family life and eventually lead to increased stress [9]. Individuals with SMA may also be less physically active and have poorer sleep, which may predispose to psychological distress. Social networking provides a platform for persons to escape from negative emotions. However, excessive escapism may disrupt sleep and eventually induce more stress and depressive symptoms [21]. Negative social comparison may also contribute. Feelings of inferiority may be elicited if individuals engage in self-comparison with idealized representations often communicated on social media [4].

The present study found that SMA severity was positively correlated with sleep disturbance. This observation supports prior findings that suggest that time spent on social media is positively associated to sleep problems, such as insomnia, daytime sleepiness, and evening chronotype [13]. A phase delay in the circadian clock could be a reason for the association between SMA severity and sleep quality [13]. Using social media, especially before bed, may lead to difficulties falling asleep and bedtime delay [13]. The relationship between SMA severity and sleep quality may reflect cognitive and emotional arousal when using social media before sleep, with increased arousal preventing sleep [60]. Additionally, blue light from the screen may activate circadian clocks and generate delays in sleep latency [15].

Although both severities of both IGD and SMA were associated with poor sleep, SMA severity was more strongly related. Different strengths of associations could involve multiple possible mechanisms. First, the use of social media may constitute a more on-going process than internet gaming, which may have more well-defined beginnings and endings for each gaming task or component. The sleep patterns of users may be disrupted when they are preoccupied and waiting for replies from others on social media, which may not be well limited in time [14]. Being offline from interactions on social media may generate greater preoccupation and withdrawal when compared to gaming, potentially leading to greater disturbance in sleep quality [35]. Second, different levels and natures of interactions between social media and internet gaming may also explain differences in strengths of associations. Internet gaming may contain similar stimuli within games with main goals involving winning. In contrast, interactions on social media may be more complex, although this may be debatable given the complexities and varieties of games. Individuals may have a variety of goals and aims when using social media, involving multiple interpersonal relations which may require more mental or emotional effort that could lead to poorer sleep. However, as these factors were not assessed in the present study, further investigation is needed to test these presently speculative possibilities.

IGD severity showed associations with psychological distress that were comparable to those between SMA severity and psychological distress. Aspects of gaming and social media warrant consideration in relationships to psychological distress. Internet gaming often involves activities in multi-player chat rooms. Online gamers may thus form a team with individuals they have never physically contacted before when they engage in online games [61]. The teammates may share a goal in the game, and they may discuss their teamwork strategy to win the game. With the mindset of winning and within a virtual competitive environment, these individuals may become aggressive as they focus on winning [61]. Therefore, online gaming may not be an ideal platform for disclosing inner feelings, while social media may be used as a platform to express emotions [62]. Indeed, people with psychological distress can upload a new post on social media to share their current feelings or have an online discussion regarding their work or academic issues in WhatsApp. Therefore, the reasons may be different for the associations between IGD/SMA severity and psychological distress; however, both may share similar magnitudes of association with psychological distress. Additional research is needed to examine possible mechanisms linking IGD and SMA severities with psychological distress.

The present findings suggest that teaching faculty and healthcare providers in universities should attend to students’ online gaming behaviors and social media use, especially as IGD and SMA may interact in mutually reinforcing ways [63]. Future research should investigate overlapping and unique factors relating to IGD and SMA. For example, interventions related to SMA may wish to focus on sleeping habits, although given the associations between SMA and IGD with sleep disturbances, the specificity may not be robust.

In conclusion, the present study assessed associations between severities of IGD and SMA and two health outcomes (i.e., psychological health and sleep quality) among Hong Kong university students. The results showed that both severities of IGD and SMA were positively associated with psychological distress and sleep disruption. In addition, although severities of IGD and SMA show similar associations with psychological distress, SMA severity was more strongly associated with poor sleep relative to IGD severity (Table 4). Thus, healthcare providers should consider both domains (psychological distress and sleep) when encountering IGD or SMA, with consideration of the potentially greater impact of SMA on sleep. More research is needed into specific interventions to improve health and sleep in individuals with features of IGD or SMA.