The Mediating Role of Impulsivity and the Moderating Role of Gender Between Fear of Missing Out and Gaming Disorder Among a Sample of Chinese University Students
Abstract
The role of fear of missing out (FoMO) in addictive behaviors has recently attracted growing attention. In view of negative effects of gaming disorder (GD) among adolescents and emerging adults, research examining the relationship between FoMO and GD is needed, alongside the roles of impulsivity and gender in the relationship between FoMO and GD. This study examined whether impulsivity as a mediator and gender as a moderator impacted on the relationship between FoMO and GD among a sample of Chinese university students. A sample of 1,288 Chinese university students from three universities completed an online survey through the Wenjuanxing platform. The Chinese Trait-State Fear of Missing Out Scale, the Barratt Impulsiveness Scale-Brief, and the Chinese Gaming Disorder Scale were used in this study. The model results indicated that impulsivity partially mediated the relationship between FoMO and GD, and that there was a larger effect size between impulsivity and GD among males. High levels of FoMO among individuals may impact on executive functions leading to more impulsivity, and are associated with GD. Gender may moderate the relationship between impulsivity and GD. This study deepens the understanding of the relationship between FoMO and GD, and provides new perspectives for practitioners to incorporate into health prevention programs to help regulate emotion, control impulsivity, and decrease GD.
Introduction
With the rapid growth of online gaming, the number of people with gaming disorder (GD) has also increased, especially for vulnerable individuals who may be at greater risk of developing problematic or addictive gaming behavior.1–3 In the gaming studies and behavioral addiction fields, GD is a term that is sometimes used interchangeably with gaming addiction, problematic gaming, and Internet gaming disorder (IGD), and has become a “hot” issue in the field of behavioral addiction.4 The prevalence of problematic online gaming in China has been reported as ranging from 3.5 percent to 17 percent.5 Some scholars have found that problematic gaming is often experienced by adolescents and emerging adults.6–8 Anxiety and impulsivity have been identified to be significantly associated with IGD.9
There have been many studies examining the risk factors for GD and these include gaming features (e.g., realistic graphics, high event frequency, and intermittent reinforcement),10–13 gaming genre (e.g., massively multiplayer online role-playing games [MMORPGs], multiplayer online battle arena [MOBA] games, and real-time strategy [RTS] games),13–15 psychopathological symptoms (e.g., anxiety and depression),15,16 and personality traits (e.g., impulsivity, introversive, and egoistic traits),9,17–19 as well as low level of emotion regulation.20 Moreover, neurobiological factors (e.g., limbic and prefrontal–striatal systems, and neurotransmitters) have also been identified as being associated with GD.21–26
Recently, some studies have focused on “fear of missing out” (FoMO), which is positively associated with excessive social media use.27–29 FoMO has been described as “a pervasive apprehension that others might be having rewarding experiences from which one is absent.”30 Trait-FoMO refers to one of the predispositions in developing state-FoMO, whereas state-FoMO refers to an unstable and situated cognition concerning the FoMO on something online that could impact on Internet-communication disorder through avoidance expectancies.31 Some scholars have also reported that both state-FoMO and problematic Instagram use can mediate the relationship between trait-FoMO and phubbing.32
The Interaction of Person-Affect-Cognition-Execution (I-PACE) model describes the psychological and neurobiological processes of addictive behaviors (GD, gambling disorder, etc.), which are considered as a consequence of the interactions between predispositions, affective and cognitive responses to situational triggers, and executive functions (e.g., impulsive decision making and inhibitory control).33 Based on the I-PACE model, trait-FoMO as one of predispositions and state-FoMO as a specific cognition would both impact on inhibitory control of executive functions and trigger impulsive behavior, and in some cases give rise to addictive behaviors.
FoMO may mediate the impact of social identity in GD among MMORPGs gamers.34 Studies have found that game genre is associated with GD, and that MMORPGs have the strongest positive association with GD.13 In MMORPGs, gamers need to complete tasks or “quests” with others.35,36 Owing to the characteristics of MMORPGs and MOBA games including socializing, relationship, and teamwork,36,37 gamers FoMO on social communication, collaboration, and/or competition, which may lead to impulsive and disordered gaming behavior.
In addition, fear and anxiety often co-occur and commonly overlap. Anxiety disorder and fear-related disorder have been formally classified in the 11th revised edition of the International Classification of Diseases38 (ICD-11). González-Bueso et al.17 reported that there was a large and significant correlation between IGD and anxiety. Trait-anxiety and state-anxiety are predictors of IGD, with state-anxiety being stronger than trait-anxiety.19 The classification of trait-FoMO and state-FoMO is similar to trait-anxiety and state-anxiety. FoMO is regarded as a type of social anxiety.34 Social anxiety has also been found to impact on IGD through motives and metacognitions of online social interactions.39
Moreover, FoMO may also stimulate impulsive consumption in marketing and communication activities because of fearing of missing out on something.40 Kim et al.41 also reported that FoMO was an extrinsic motivation (e.g., “It's a big game not to miss out”) that may promote popular sport event consumption (e.g., Olympics, FIFA World Cup, and the Super Bowl). In China, 15.2 percent of participants in one study reported having an experience of severe FoMO.42 According to the latest report from the China Internet Network Information Centre, the number of individuals (older than 6 years) who play online games increased to 540 million (57.4 percent of all Internet users) in June 2020.43 In some Chinese universities, research has indicated that online games may lead to academic difficulties, compromise interpersonal relationship, and impact negatively on the mental and physical health, and can result in a minority of students dropping out of their studies. Considering the prevalence of online gaming in Chinese university students, this study examined the relationship between FoMO and GD, the mediating role of impulsivity, and the moderating role of gender.
Impulsivity as a mediator
Impulsivity is a tendency including a variety of components, such as a lack of thorough consideration and planning for the future, seeking excitement, taking risks, and rapid decision making.44–46 Impulsivity is considered as a consequence of neuropsychological impairments in executive functions and attention processes.47 Reduced executive control is one of the important mechanism explanations for IGD.48 Therefore, impulsivity is also a core process underpinning both behavioral and substance addictions.49
The pooled findings in a recent systematic review of 33 studies suggested that there was a positive association between impulsivity and IGD.47 Some scholars note that impulsivity appears to be one of the forceful personality factors of GD, especially among adolescents and emerging adults.47,50–54 Impaired self-control (i.e., impulsive thinking or behaviors) may mediate the relationship between daily need frustration and GD,55 which is consistent with self-determination theory (SDT) and recent studies.56,57 Moreover, the I-PACE model describes risk factors of GD including an individual's core characteristics (e.g., trait-FoMO and impulsivity traits), perception of external and internal triggers (e.g., state-FoMO and stimuli-specific reductions in inhibitory control), and gratification/compensation (e.g., diminished control over addictive behaviors [impulsive behavior]) in addictive processes.33
Gender as a moderator
The highest level of FoMO appears to be among young males as opposed to females.30 However, some studies have reported that females as having a higher level of FoMO than males,58–60 as well as some studies reporting no difference.61 Therefore, gender differences concerning FoMO are worthy of further investigation.
The importance of gender differences has been discussed in addictive disorders, including Internet addiction and gambling disorder.62 Gender difference as a moderator was found in the relationship between motor impulsivity and problematic Internet use (PIU), wherein females with higher motor impulsivity had increased PIU levels.44 Some studies have also found that gender may moderate the relationships between impulsivity and risky sex, as well as impulsivity and eating disorder.63–65 Higher impulsivity is associated with increased use of alcohol, nicotine, and caffeine, especially among males.66,67
Many empirical studies have investigated the relationship between GD and gender. These have consistently found that males are significantly more likely to have GD.7,8,68 Males with GD have lower seed connectivity between the posterior cingulate cortex and the orbital part of the left superior frontal gyrus (SFG) than females with GD.69 Clinical evidence has shown that emerging adults and males with GD appear to be more common.70 However, some studies reported that females were more vulnerable to GD than males based on evidence concerning cue-elicited cravings and cortical thickness.71,72 Therefore, gender differences concerning GD from a neurobiological perspective are not as consistent as those from an epidemiological perspective.
The present study
Individuals with high FoMO may positively seek social involvement to avoid social anxiety. Gamers, especially males, may show more impulsive behavior, which subsequently may lead to GD. In this study, the association among FoMO, impulsivity, GD, and gender was examined. It was hypothesized that (a) FoMO would be associated with impulsivity and GD; (b) impulsivity as a mediator would impact on the relationship between FoMO and GD; and (c) gender would moderate the association between FoMO and GD (Fig. 1).

FIG. 1. The proposed moderated mediation model.
Methods
Participants
A cross-sectional study was conducted from October 2019 to April 2020. The survey was performed through Wenjuanxing (an established online survey platform in China). The original sample of 1,447 participants was recruited from three universities in Jiangxi and Liaoning provinces of China by clustering convenience sampling. Participants needed to meet the condition of playing videogames in the past 12 months through computer, smartphone, and/or console. However, 78 participants did not meet the aforementioned condition and 81 participants did not complete all the survey questions. Therefore, data from 159 participants were excluded. A total of 1,288 participants remained (526 males, 762 females) with 89 percent response rate. Participants were aged between 17 and 25 years (mean age = 20.0 ± 1.6 years). The average time spent gaming each day was 3.11 hours.
Measures
Chinese Trait-State Fear of Missing Out Scale
The Trait-State Fear of Missing Out Scale (T-SFoMOS) was used to assess the level of FoMO,31 and was translated into Chinese.73 The 12-item T-SFoMOS includes a trait-FoMO dimension (e.g., “I get worried when I find out my friends are having fun without me”) and a state-FoMO dimension (e.g., “I am continuously online in order not to miss out on anything”). Participants rate items on a 5-point scale (from 1 = “totally disagree” to 5 = “totally agree”). The Cronbach's alpha and McDonald's ω for the total scale were 0.81 and 0.82, respectively in this study.
Barratt Impulsiveness Scale-Brief
The Barratt Impulsiveness Scale-Brief (BIS-Brief)74 was utilized to assess impulsivity.75,76 The BIS-Brief has eight items and was developed by Patton et al.,77 and was translated into Chinese.78 Participants rate the items on a 4-point scale (from 1 = “rarely/never” to 4 = “almost always/always”). The Cronbach's alpha and McDonald's ω were both 0.70 in this study.
Chinese Gaming Disorder Scale
The Chinese Gaming Disorder Scale (CGDS) developed by the present authors was utilized to assess GD. The nine items were adapted from the ICD-1138 (e.g., “I increase priority given to gaming to the extent that gaming takes precedence over my other life interests and daily activities”) and the fifth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5)79 (e.g., “I feel the need to spend increasing amount of time engaged gaming in order to achieve satisfaction or pleasure”). Participants respond with “1 = yes” or “0 = no.” The 9-item CGDS model with two factors was verified by fit indices (χ2 = 64.71, df = 26, p < 0.01; Tucker-Lewis index = 0.927; comparative fit index = 0.947; standardized root mean square residual = 0.036; root mean square error of approximation = 0.036). The Cronbach's alpha and McDonald's ω of the CGDS in this study were 0.73 and 0.74, respectively.
Procedure
From October 2019 to April 2020, participants were recruited from three universities (Gannan Medical University [731 participants], Jiangxi University of Science and Technology [418 participants], and Jinzhou Medical University [298 participants]) in two provinces of China. After the students' approval to gain course credit, the online survey was completed in normally scheduled classes. Participants took ∼5 minutes to complete all the questions. This study was approved by the institutional review board and Ethics Committee of Gannan Medical University and the ethical standards was followed.
Statistical analysis
Descriptive statistics and Pearson's and Spearman's correlation were performed using SPSS 20. Bayesian correlation was performed using JASP (Jeffrey's Amazing Statistics Program). Log(BF10) ≥3 and ≤1/3 are evidence for the null hypothesis (i.e., there is a correlation between variables).80 The Cronbach's alpha and McDonald's ω were also calculated using JASP. The mediating role of impulsivity was examined using PROCESS macro for SPSS (Model 4), whereas the moderating mediation model of impulsivity and gender was conducted using PROCESS macro (Model 59). In addition, the significance of mediating and moderating effects was examined using a bias-corrected bootstrapping method, which is regarded as significant if the confidence intervals (CIs) do not include 0.81
Results
Descriptive statistics and correlation analyses
Table 1 gives the means, standard deviations, skewness, kurtosis, Pearson correlations, Spearman correlations, and Bayesian correlation. The skewness (<2) and kurtosis (<7) level of the study variables indicated a normal data distribution.82 FoMO, trait-FoMO, and state-FoMO were significantly positively associated with impulsivity (r = 0.17, r = 0.18, r = 0.11, all p < 0.001; log(BF10) = 13.34, 17.04, 3.42, all >3) and GD (r = 0.12, r = 0.10, r = 0.10, all p values <0.001; log(BF10) = 4.42, 2.69, 1.76; FoMO >3), respectively. GD was significantly associated with gender (r = 0.30, p < 0.001; log(BF10) = 21.81 > 3). Bayesian correlation verified the effect sizes of the relationship between FoMO, impulsivity, and GD.
| M | SD | Skewness | Kurtosis | 1 | 2 | 3 | 4 | 5 | 6 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | FoMO | 29.04 | 6.88 | −0.168 | 0.084 | 1.00 | |||||
| 2 | Trait-FoMO | 12.12 | 3.57 | 0.006 | −0.197 | 0.80*** | 1.00 | ||||
| log(BF10) | ∞ | ||||||||||
| 3 | State-FoMO | 16.93 | 4.61 | 0.080 | −0.081 | 0.88*** | 0.41*** | 1.00 | |||
| log(BF10) | ∞ | 114.10 | |||||||||
| 4 | Impulsivity | 18.86 | 2.72 | −0.033 | 0.262 | 0.17*** | 0.18*** | 0.11*** | 1.00 | ||
| log(BF10) | 13.34 | 17.04 | 3.42 | ||||||||
| 5 | Gaming disorder(GD) | 0.90 | 1.50 | 1.814 | 2.483 | 0.12*** | 0.10*** | 0.10*** | 0.19*** | 1.00 | |
| log(BF10) | 4.42 | 2.69 | 1.76 | 21.81 | |||||||
| 6 | Gendera | 0.06* | 0.01 | 0.09* | 0.03 | 0.33*** | 1.00 | ||||
| log(BF10) | 1.12 | 3.22 | 0.45 | 2.36 | 58.47 |
Testing for mediation effect
Impulsivity as a mediator impacting on the relationship between FoMO and GD was examined utilizing Hayes' PROCESS (Model 4). FoMO was positively associated with impulsivity (β = 0.17, t = 5.99, p < 0.001) and GD (β = 0.08, t = 3.11, p < 0.01). Impulsivity was positively associated with GD (β = 0.16, t = 6.51, p < 0.001). The total effect (β = 0.102, 95% CI: 0.054–0.150) and indirect effect (β = 0.031, 95% CI: 0.018–0.045) from FoMO to GD through impulsivity were both significant. Therefore, the relationship between FoMO and GD was partially mediated through impulsivity.
Testing for moderated mediation
The moderated mediation effect of impulsivity as a mediator and gender as a moderator between FoMO to GD were examined using Hayes' PROCESS (Model 59). The results of the moderated mediation analysis are displayed in Table 2. As Model 2 showed, the effect of impulsivity on GD was moderated by gender (β = −0.15, t = −3.36, p < 0.001), but not the effects of FoMO on impulsivity and FoMO on GD. Figure 2 shows the relationship between impulsivity and GD among males and females (M + 1SD and M − 1SD).83 A simple slope test84 showed that the positive relationship between impulsivity and GD was statistically significant among males (β = 0.26, t = 7.41, p < 0.001) and females (β = 0.10, t = 3.47, p < 0.001), but the effect size was much smaller among females.

FIG. 2. Gender as a moderator in the relationship between impulsivity and gaming disorder.
| Predictors | Model 1 (impulsivity) | Model 2 (GD) | ||
|---|---|---|---|---|
| β | t | β | t | |
| FoMO | 0.16 | 5.90*** | 0.09 | 3.80*** |
| Gender (1 = males, 2 = females) | 0.09 | 1.60 | −0.56 | −12.14*** |
| FoMO × gender | 0.04 | 0.62 | −0.05 | −1.10 |
| Impulsivity | 0.17 | 7.34*** | ||
| Impulsivity × gender | −0.15 | −3.36*** | ||
| R2 | 0.03 | 0.15 | ||
| F | 10.25*** | 38.80*** | ||
Discussion
This study examined the moderated mediation effect of impulsivity as a mediator and gender as a moderator between FoMO and GD among a sample of Chinese university students. The findings provide insight into impulsivity mediating the relationship between FoMO and GD as well as gender moderating the relationship between impulsivity and GD. FoMO was positively associated with impulsivity, which was similar to Aydin et al.'s research on impulsive buying.40 In addition, FoMO has also been found to be closely related to impulsive social communication through excessive smartphone use.85 Therefore, higher levels of FoMO may negatively impact executive function and trigger impulsive behavior. Some participants reported habitually or impulsively checking their smartphones even if the phones did not receive any new information,86 because they feared missing out on something important. FoMO was also significantly positively associated with GD in this study, which is similar to Duman and Okzara's research34 (i.e., FoMO was found to be an important predictor of online game addiction among MMORPGs gamers; β = 0.16, p < 0.001, 95% CI: 0.216–0.478). SDT has suggested that daily need frustration undermines individual's self-control,87 whereas FoMO is regarded as an unstable self-regulatory originating from specific deficits in the process of psychological need satisfactions.30
The results identified the partial mediating role of impulsivity from FoMO to GD. Social communication, collaboration, and competition are important motivations in MMORPGs and RTS games.88–90 To satisfy individuals' motivation, gamers with high level of FoMO may lose self-control that gives rise to greater impulsivity, subsequently, and resulting in GD.91 In terms of the I-PACE model, FoMO containing trait and state dimensions, as a specific personality trait or state anxiety, may facilitate impulsivity and impair individual executive function, which may result in GD for a small minority. In addition, SDT posits that problematic gamers fail to control or cease gaming activity, increase impulsivity to achieve instant satisfaction and pleasure, and subsequently lead to GD in some individuals, which may be due to the FoMO on social interactions or the sense of accomplishment and satisfaction from gaming.
This study also found that gender as a moderator in the relationship between impulsivity and GD. Compared with females, the effect size between impulsivity and GD was higher among males. The result is consistent with other findings, which have suggested that a minority of female adolescents and a majority of male adolescents play videogames.92 In addition, the prevalence of IGD/GD is higher among males, especially in some Asian countries (e.g., China and Korea).93,94 It has also been reported that boys with PIU are more influenced by genetic factors than girls.95 Some studies have reported that high levels of testosterone in males may be related to IGD, such as exhibiting more impulsive and aggressive behaviors.96 Moreover, the altered amplitude of low-frequency fluctuation values in the orbital part of the left SFG represented a clinically relevant biomarker for inhibition control of IGD among males.69 This means that IGD may interact with gender-specific patterns of functional connectivity.
Impulsivity as a mediator and gender as a moderator spear to impact the relationship between FoMO and GD among Chinese students. Nevertheless, several limitations should be noted in this study. First, the data were collected through self-report and a convenience sample was used, which may result in some response biases, such as memory recall, individual motivation, and social desirability. The sample may also be unrepresentative of Chinese university students. Future studies should utilize representative random samples and utilize longitudinal and other more objective methodologies to further explore the relationship among FoMO, impulsivity, and GD (e.g., clinical assessment, functional magnetic resonance imaging techniques, and cohort-sequential longitudinal design). Second, there were possible confounding variables. For instance, social networking site addiction and smartphone addiction were not controlled for in this study. Furthermore, the impact of different videogame genres should also be identified in future study, particularly because undefined gaming genres (casual games, puzzle games, etc.) may have contributed to low correlations and regression coefficients in this study. Third, further research is required to give more insight into the features of trait and state dimension of FoMO. For example, studies could evaluate the difference between trait and state dimension of FoMO, which are considered as predictor variables that impact on GD. Moreover, further research may be necessary to delineate the differences between the different gaming genres (e.g., MMORPGs, RTS games, First Person Shooter games, and MOBA games) and the impact of different gaming genres in the relationship between FoMO, impulsivity, and GD. Despite these limitations, the results of this study demonstrate the moderating mediation effects of impulsivity as a mediator and gender as a moderator from FoMO to GD. Based on the findings, the impact of FoMO on GD among Chinese university students may be moderated by gender and mediated through impulsivity.
Author Disclosure Statement
There are no financial or non-financial competing interests. None of the research staff received incentives for recruiting participants or for any other purpose directly associated with the study.
Funding Information
The Science Education Program Project “Thirteenth Five-Year Plan” of Jiangxi Province 2020GX184, Doctor start-up fund of Gannan Medical University QD201819, Key project of Gannan Medical University ZD201838, Humanities and Social Science Research Project of Jiangxi Province XL20104, The International Innovation Team of Jilin University 2019GJTD06.
References
- 1. Screening and assessment tools for gaming disorder: a comprehensive systematic review. Clinical Psychology Review 2020; 74:101831. Crossref, Google Scholar
- 2. Symptoms of Internet gaming disorder in youth: predictors and comorbidity. Journal of Abnormal Child Psychology 2019; 47:71–83. Crossref, Medline, Google Scholar
- 3. Need fulfilment and internet gaming disorder: a preliminary integrative model. Addictive Behaviors Reports 2019; 9:100144. Crossref, Medline, Google Scholar
- 4. . Video game addiction: past, present and future. Current Psychiatry Reviews 2012; 8:308–318. Crossref, Google Scholar
- 5. Prevalence and correlates of problematic online gaming: a systematic review of the evidence published in Chinese. Current Addiction Reports 2018; 5:359–371. Crossref, Google Scholar
- 6. . Challenges of gaming disorder: suggestions from a public health perspective. General Psychiatry 2019; 32:e100086. Crossref, Medline, Google Scholar
- 7. . Online gaming addiction in children and adolescents: a review of empirical research. Journal of Behavioral Addictions 2012; 1:3–22. Crossref, Medline, Google Scholar
- 8. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychology of Addictive Behaviors 2016; 30:252–262. Crossref, Medline, Google Scholar
- 9. Risk factors for internet gaming disorder: psychological factors and internet gaming characteristics. International Journal of Environmental Research and Public Health 2018; 15:40. Crossref, Google Scholar
- 10. . An overview of structural characteristics in problematic video game playing. Current Addiction Reports 2017; 4:272–283. Crossref, Medline, Google Scholar
- 11. . Video game structural characteristics: a new psychological taxonomy. International Journal of Mental Health and Addiction 2010; 8:90–106. Crossref, Google Scholar
- 12. . The role of structural characteristics in problematic video game play: an empirical study. International Journal of Mental Health and Addiction 2011; 9:320–333. Crossref, Google Scholar
- 13. Maladaptive player-game relationships in problematic gaming and gaming disorder: a systematic review. Clinical Psychology Review 2019; 73:101777. Crossref, Medline, Google Scholar
- 14. . Study what makes games addictive. Nature 2019; 573:346. Crossref, Medline, Google Scholar
- 15. . Internet gaming disorder in male and female young adults: the role of alexithymia, depression, anxiety and gaming type. Psychiatry Research 2019; 272:521–530. Crossref, Medline, Google Scholar
- 16. Problematic involvement in online games: a cluster analytic approach. Computers in Human Behavior 2015; 43:242–250. Crossref, Google Scholar
- 17. Association between internet gaming disorder or pathological video-game use and comorbid psychopathology: a comprehensive review. International Journal of Environmental Research and Public Health 2018; 15:668. Crossref, Medline, Google Scholar
- 18. . Internet gaming disorder and its associated personality traits: a systematic review using PRISMA guidelines. International Journal of Mental Health and Addiction1 2019 [Epub ahead of print]; DOI:
10.1007/s11469-019-00081-6 Crossref, Google Scholar - 19. . Online gaming addiction: the role of sensation seeking, self-control, neuroticism, aggression, state anxiety, and trait anxiety. Cyberpsychology, Behavior, and Social Networking 2010; 13:313–316. Link, Google Scholar
- 20. Attachment and emotion regulation in substance addictions and behavioral addictions. Journal of Behavioral Addiction 2017; 6:534–544. Crossref, Medline, Google Scholar
- 21. Brain activities associated with gaming urge of online gaming addiction. Journal of Psychiatric Research 2009; 43:739–747. Crossref, Medline, Google Scholar
- 22. The adaptive decision-making, risky decision, and decision-making style of Internet gaming disorder. European Psychiatry 2017; 44:189–197. Crossref, Medline, Google Scholar
- 23. . Neurobiological correlates in Internet Gaming Disorder: a systematic review. Frontiers in Psychiatry 2018; 9:166. Crossref, Medline, Google Scholar
- 24. . Decision-making and related processes in Internet Gaming Disorder and other types of Internet-use disorders. Current Addiction Reports 2017; 4:262–271. Crossref, Google Scholar
- 25. A tripartite neurocognitive model of internet gaming disorder. Frontiers in Psychiatry 2017; 8:285. Crossref, Medline, Google Scholar
- 26. . New developments in brain research of internet and gaming disorder. Neuroscience and Biobehavioral Reviews 2017; 75:314–330. Crossref, Medline, Google Scholar
- 27. . College students' academic motivation, media engagement and fear of missing out. Computers in Human Behavior 2015; 49:111–119. Crossref, Google Scholar
- 28. . Students' social media engagement and fear of missing out (FoMO) in a diverse classroom. Journal of Computing in Higher Education 2017; 29:388–410. Crossref, Google Scholar
- 29. . Using multidimensional scaling and PLS-SEM to assess the relationships between personality traits, problematic internet use, and fear of missing out. Behavior & Information Technology 2018; 37:1264–1276. Crossref, Google Scholar
- 30. Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior 2013; 29:1841–1848. Crossref, Google Scholar
- 31. Online-specific fear of missing out and Internet-use expectancies contribute to symptoms of internet communication disorder. Addictive Behaviors Reports 2017; 5:33–42. Crossref, Medline, Google Scholar
- 32. Neuroticism, trait fear of missing out, and phubbing: the mediating role of state fear of missing out and problematic Instagram use. International Journal of Mental Health Addiction 2020; 18:628–639. Crossref, Google Scholar
- 33. The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: update, generalization to addictive behaviors beyond Internet-use disorders, and specification of the process character of addictive behaviors. Neuroscience & Biobehavioral Reviews 2019; 104:1–10. Crossref, Medline, Google Scholar
- 34. . The impact of social identity on online game addiction: the mediating role of the fear of missing out (FoMO) and the moderating role of the need to belong. Current Psychology 2019; 38:1–10. Google Scholar
- 35. Typology and socio-demographic characteristics of massively multiplayer online game players. International Journal of Human Computer Interaction 2013; 29:192–200. Crossref, Google Scholar
- 36. . The demographics, motivations, and derived experiences of users of massively multi-user online graphical environments. Presence Teleoperators and Virtual Environments 2006; 15:309–329. Crossref, Google Scholar
- 37. . The impacts of social interactions in MMORPGs on older adults' social capital. Computers in Human Behavior 2015; 51:495–503. Crossref, Google Scholar
- 38.
World Health Organization (WHO) . (2019). 6C51 Gaming disorder. https://icd.who.int/browse11/l-m/en#/http://id.who.int/icd/entity/1448597234 (accessedMar. 15, 2020 ). Google Scholar - 39. Social anxiety and Internet gaming disorder: the role of motives and metacognitions. Journal of Behavioral Addictions 2020 [Epub ahead of print]; DOI:
10.1556/2006.2020.00044 Crossref, Google Scholar - 40. The relationship of consumers' compulsive buying behavior with biological rhythm, impulsivity, and fear of missing out. Biological Rhythm Research 2019; 26:1–9. Crossref, Google Scholar
- 41. . Investigating ‘Fear of Missing Out’ (FOMO) as an extrinsic motive affecting sport event consumer's behavioral intention and FOMO-driven consumption's influence on intrinsic rewards, extrinsic rewards, and consumer satisfaction. PLoS One 2020; 15:e0243744. Crossref, Medline, Google Scholar
- 42.
Xinli001 (2016) . How to say goodbye to the fear of missing out. China: Guangzhou Renxin Network Technology Co. LTD. www.xinli001.com/info/100001714 (accessedJan. 27, 2020 ). Google Scholar - 43.
China Internet Network Information Center (2020) . The 46th Statistical report on internet development in China. www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202009/t20200929_71257.pdf (accessedDec. 16, 2020 ). Google Scholar - 44. . Impulsivity as a precedent factor for problematic Internet use: how can we be sure? International Journal of Psychology 2017; 52:389–397. Crossref, Medline, Google Scholar
- 45. . Relationship between impulsivity, social media usage and loneliness. Educational Process: International Journal 2015; 5:106–115. Crossref, Google Scholar
- 46. . The neuropsychiatry of impulsivity. Current Opinion in Psychiatry 2007; 20:255–261. Crossref, Medline, Google Scholar
- 47. . The association between internet gaming disorder and impulsivity: a systematic review of literature. International Journal of Mental Health and Addiction 2019 [Epub ahead of print]; DOI:
10.1007/s11469-019-00126-w Crossref, Google Scholar - 48. Abnormal gray matter volume and impulsivity in young adults with Internet gaming disorder. Addiction Biology 2018; 23:1160–1167. Crossref, Medline, Google Scholar
- 49. . A systematic meta-review of impulsivity and compulsivity in addictive behaviors. Neuropsychology Review 2019; 29:14–26. Crossref, Medline, Google Scholar
- 50. . Response inhibition and Internet Gaming Disorder: a meta-analysis. Addictive Behaviors 2017; 71:54–60. Crossref, Medline, Google Scholar
- 51. . Psychosocial correlates of internet gaming disorder: psychopathology, life satisfaction, and impulsivity. Computers in Human Behavior 2017; 68:388–394. Crossref, Google Scholar
- 52. Sensation seeking and online gaming addiction in adolescents: a moderated mediation model of positive affective associations and impulsivity. Frontiers in Psychology 2017; 8:699. Crossref, Medline, Google Scholar
- 53. Impulsivity and compulsivity in Internet gaming disorder: a comparison with obsessive-compulsive disorder and alcohol use disorder. Journal of Behavioral Addictions 2017; 6:545–553. Crossref, Medline, Google Scholar
- 54. Internet gaming disorder in children and adolescents: a systematic review. Developmental Medicine & Child Neurology 2018; 60:645–659. Crossref, Medline, Google Scholar
- 55. . Self-determination theory, internet gaming disorder, and the mediating role of self-control. Computers in Human Behavior 2020; 105:106209. Crossref, Google Scholar
- 56. . Satisfaction and frustration of basic psychological needs in the real world and in video games predict internet gaming disorder scores and well-being. Computers in Human Behavior 2018; 84:220–229. Crossref, Google Scholar
- 57. Exploring the pull and push underlying problem video game use: a self-determination theory approach. Personality and Individual Differences 2018; 135:176–181. Crossref, Google Scholar
- 58. . Personality, fear of missing out and problematic internet use and their relationship to subjective well-being. Computers in Human Behavior 2017; 76:534–540. Crossref, Google Scholar
- 59. Fear of missing out as a predictor of problematic social media use and phubbing behavior among Flemish adolescents. International Journal of Environmental Research and Public Health 2018; 15:2319. Crossref, Google Scholar
- 60. . “I don't want to miss a thing”: adolescents' fear of missing out and its relationship to adolescents' social needs, Facebook use, and Facebook related stress. Computers in Human Behavior 2016; 64:1–8. Crossref, Google Scholar
- 61. . Fear of missing uut (FOMO) among youth in Bosnia and Herzegovina-Scale and selected mechanisms. Children and Youth Services Review 2018; 88:541–549. Crossref, Google Scholar
- 62. Sex differences in addictive disorders. Frontiers in Neuroendocrinology 2014; 35:272–284. Crossref, Medline, Google Scholar
- 63. . A meta-analytic review of the relationship between adolescent risky sexual behavior and impulsivity across gender, age, and race. Clinical Psychology Review 2014; 34:551–562. Crossref, Medline, Google Scholar
- 64. Gender moderates the relationship between impulsivity and sexual risk-taking in a cocaine-using psychiatric outpatient population. Personality and Individual Differences 2015; 75:190–194. Crossref, Medline, Google Scholar
- 65. Gender differences in the relationship between impulsivity and disordered eating behaviors and attitudes. Eating Behaviors 2015; 18:120–124. Crossref, Medline, Google Scholar
- 66. . Gender and impulsivity differences in licit substance use. Journal of Substance Abuse 1997; 9:269–275. Crossref, Medline, Google Scholar
- 67. . Does gender moderate associations among impulsivity and health-risk behaviors? Addictive Behaviors 2008; 33:252–265. Crossref, Medline, Google Scholar
- 68. Gender differences and related factors affecting online gaming addiction among Taiwanese adolescents. Journal of Nervous and Mental Disease 2005; 193:273–277. Crossref, Medline, Google Scholar
- 69. Sex differences in resting-state cerebral activity alterations in internet gaming disorder. Brain Imaging and Behavior 2019; 13:1406–1417. Crossref, Medline, Google Scholar
- 70. . Gaming addiction as a disorder: the mysterious patients in No.29 ward. Law & Life 2020; 37:6–8. Google Scholar
- 71. Gender-related differences in cue-elicited cravings in Internet gaming disorder: the effects of deprivation. Journal of Behavioral Addictions 2018; 7:953–964. Crossref, Medline, Google Scholar
- 72. Females are more vulnerable to Internet gaming disorder than males: evidence from cortical thickness abnormalities. Psychiatry Res Neuroimaging 2019; 283:145–153. Crossref, Medline, Google Scholar
- 73. . Revision of the Chinese version of Trait-State Fear of Missing Out. Chinese Journal of Clinical Psychology 2018; 27:268–272. Google Scholar
- 74. New tricks for an old measure: the development of the Barratt Impulsiveness Scale-Brief (BIS-Brief). Psychological Assessment 2013; 25:216–226. Crossref, Medline, Google Scholar
- 75. Examining the psychometric properties of the Barratt Impulsiveness Scale-Brief Form in justice-involved samples. Psychological Assessment 2015; 27:1211–1218. Crossref, Medline, Google Scholar
- 76. A test of the psychometric characteristics of the BIS-Brief among three groups of youth. Psychological Assessment 2018; 30:847–856. Crossref, Medline, Google Scholar
- 77. . Factor structure of the Barratt impulsiveness scale. Journal of Clinical Psychology 1995; 51:768–774. Crossref, Medline, Google Scholar
- 78. Reliability and validity of Chinese version of Barratt impulsiveness scale-11. Chinese Journal of Clinical Psychology 2006; 14:343–345. Google Scholar
- 79. . Measuring DSM-5 Internet gaming disorder: development and validation of a short psychometric scale. Computers in Human Behavior 2015; 45:137–143. Crossref, Google Scholar
- 80. Lack of privileged access to awareness for rewarding social scenes in autism spectrum disorder. Journal of Autism Autism and Developmental Disorders 2018; 48:3311–3318. Crossref, Medline, Google Scholar
- 81. . (2013) Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. New York: Guilford Press. Google Scholar
- 82. . The robustness of test statistics to non-normality and specification error in confirmatory factor analysis. Psychological Methods 1996; 1:16–29. Crossref, Google Scholar
- 83. (2003) Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah, NJ: Lawrence Erlbaum Associates. Google Scholar
- 84. . Contemporary approaches and classic advice for analyzing mediating and moderating variables. Monographs of the Society for Research in Child Development 2006; 71:88–104. Google Scholar
- 85. . “I wanna be in the loop!” -The role of Fear of Missing Out (FoMO) for the quantity and quality of young adolescents' mobile phone use. Reihe Rezeptionsforschung 2018; 38:39–53. Google Scholar
- 86. . Are you awake? Mobile phone use after lights out. Computers in Human Behavior 2016; 64:932–937. Crossref, Google Scholar
- 87. . (2017) Self-determination theory: basic psychological needs in motivation, development, and wellness. New York: Guilford Press. Crossref, Google Scholar
- 88. . Breaking the stereotype: the case of online gaming. CyberPsychology and Behavior 2003; 6:81–91. Link, Google Scholar
- 89. . Demographic factors and playing variables in online computer gaming. CyberPsychology and Behavior 2004; 7:479–487. Link, Google Scholar
- 90. . Learner interaction in a massively multiplayer online role playing game (MMORPG): a sociocultural discourse analysis. ReCALL 2012; 24:361–380. Crossref, Google Scholar
- 91. . Chaos and confusion in DSM-5 diagnosis of internet gaming disorder: issues, concerns, and recommendations for clarity in the field. Journal of Behavioral Addictions 2017; 6:103–109. Crossref, Medline, Google Scholar
- 92. Video-gaming among high school students: health correlates, gender differences, and problematic gaming. Pediatrics 2010; 126:E1414–E1424. Crossref, Medline, Google Scholar
- 93. The gender difference on Internet addictive among adolescent: the mediation effect of the differentiation of social and psychological situation in school. Chinese Journal of Clinical Psychology 2015; 23:1044–1048. Google Scholar
- 94. . Gender differences in Internet addiction associated with psychological health indicators among adolescents using a National Web-based Survey. International Journal of Mental Health and Addiction 2014; 12:660–669. Crossref, Google Scholar
- 95. A twin study of problematic internet use: its heritability and genetic association with effortful control. Twin Research and Human Genetics 2014; 17:279–287. Crossref, Medline, Google Scholar
- 96. . Neural mechanisms of the testosterone aggression relation: the role of orbitofrontal cortex. Journal of Cognitive Neuroscience 2010; 22:2357–2368. Crossref, Medline, Google Scholar

