Online games have evolved into a ubiquitous feature of entertainment and leisure, fostering connectivity and interaction among players across the globe. This progression has been fueled by the increasing accessibility of high-speed internet, widespread adoption of smartphones, and inherent social aspects of online gaming. As of June 2023, approximately 40% of the world’s population engaged in online gaming (Techreport, 2023). Despite the entertainment and social connectivity that online gaming facilitates, the phenomenon of excessive engagement, typified by internet gaming addiction (IGA), can give rise to consequential physical and mental health issues, encompassing diminished productivity and academic achievement (Chu, 2023), sleep disturbances (Alimoradi et al., 2019), and elevated rates of depression (Ostinelli et al., 2021). Results of a survey involving 2,628 Chinese participants revealed a 13.4% prevalence of IGA (Yang & Zhang, 2023). Thus, it is both theoretically and practically imperative to explore preventers and risk-related determinants of IGA, facilitating the formulation of effective interventions to address this emerging issue.

The interaction of person–affect–cognition–execution (I-PACE) model, as posited by Brand et al. (2019), underscores the significance of personal traits, including sensation seeking, as crucial predictors of an individual’s engagement in addictive behaviors. Empirical evidence supports sensation seeking as a salient predictor across diverse addictive behaviors, exemplified in studies examining smartphone addiction (P. Wang et al., 2018) and internet addiction (Kara, 2019). Moreover, cross-sectional investigations have demonstrated that individuals with heightened levels of sensation seeking exhibit an elevated susceptibility to developing IGA (Batmaz & Celik, 2021; Hu et al., 2017). However, within the existing literature landscape, a notable dearth exists of direct inquiries into the longitudinal association between sensation seeking and IGA.

 

Sensation seekers, characterized by elevated levels of impulsivity, exhibit poor self-control, a characteristic that is particularly evident among university students (Mehroof & Griffiths, 2010). Moreover, the inclination of sensation seekers toward immediate rewards and thrills, as opposed to considering long-term goals or consequences, underscores a predisposition that diverges from self-control principles (Del Giudice et al., 2014). Within the framework of the cognitive–behavioral model of addiction, it is posited that sensation seeking may propel individuals to actively seek novel and stimulating experiences, such as those offered by online games, as a coping mechanism for negative emotions or in pursuit of excitement (Charlton & Danforth, 2007; King et al., 2011).

 

According to the dual systems model (Strack & Deutsch, 2004), sensation seeking is primarily associated with the impulsive system, motivating individuals to actively seek novel and stimulating experiences without giving due consideration to the long-term consequences. In contrast, self-control is linked with the reflective system, empowering individuals to regulate impulses and make decisions aligned with long-term goals (Hofmann et al., 2009). Low self-control emerges as a catalyst for IGA, as diminished capacity for self-regulation leads individuals to prioritize immediate desires over adhering to long-term plans (Hofmann & Kotabe, 2012). Cross-sectional investigations have consistently underscored the susceptibility of individuals with poor self-control to developing gaming addiction, even after controlling for demographics such as age and gender (Bhagat et al., 2020; Li et al., 2023).

 

Furthermore, the I-PACE model posits that addictive behaviors, including IGA, manifest as a consequence of the intricate interplay of personality traits, affective states, and behavioral execution (Brand et al., 2019). Fear of missing out (FOMO) encapsulates individuals’ pervasive apprehension about potentially missing rewarding experiences that others enjoy, marked by an incessant desire to stay apprised of others’ activities (Przybylski et al., 2013). Numerous empirical inquiries have underscored the role of FOMO as a predisposing factor contributing to addictive behaviors (e.g., Brailovskaia & Margraf, 2024; Duman & Ozkara, 2021).

 

Additionally, Niu et al. (2022) identified FOMO as a significant moderator between individual predictors and adaptive outcomes. However, empirical evidence specifically supporting the moderating role of FOMO in the relationship between antecedent variables  (e.g., sensation seeking and self-control) and addictive behaviors remains limited (Mehroof & Griffiths, 2010). Drawing on previous empirical findings and the I-PACE model, in this study we explored the potential moderating effect of FOMO on the relationships of sensation seeking and self-control with IGA.

 

In sum, we proposed the following hypotheses:

Hypothesis 1: Sensation seeking will have a positive correlation with internet gaming addiction.

Hypothesis 2: Self-control will mediate the link between sensation seeking and internet gaming addiction.

Hypothesis 3a: Fear of missing out will moderate the link between sensation seeking and internet gaming addiction.

Hypothesis 3b: Fear of missing out will moderate the link between self-control and internet gaming addiction.

 

The research model is shown in Figure 1.

Participants were recruited via convenience sampling from Hubei University of Medicine in China. We collected data at three distinct time points during the 2022–2023 academic year. Initially, 466 college students completed the online survey during Wave 1 (baseline, October 2022). Because 67 of these students had no experience with online gaming, they were eliminated from the study; thus, 399 participants remained, who engaged in a self-reported mean daily gameplay time of 1.65 hours (SD = 1.27). Among them, 217 (54.4%) were women, 182 (45.6%) were men, and the mean age of the group was 19.78 years (SD = 1.11, range = 17–21). At Wave 2 (April 2023) we received 361 responses to the survey. Between Wave 2 and Wave 3 we enhanced participant follow-up efforts—such as implementing more frequent reminders, utilizing multiple contact channels (e.g., email, text messages, or phone calls), and offering reinforced incentives—which likely re-engaged some participants who had initially missed Wave 2. Thus, during Wave 3 (October 2023), 375 students responded to the survey and all reported active online gaming experience, disclosing a mean daily gameplay time of 2.19 hours (SD = 1.76, range = 1–10).

 

Data for this research were collected through the Survey Star platform, a widely recognized online survey company in China. Prior to completing the survey, students provided informed consent and affirmed their voluntary participation. This process was adherent to ethical standards and regulations governing human research participation.

The original English measures were independently translated into Chinese by two bilingual researchers with expertise in psychology and fluency in both languages. Both translators were native Chinese speakers with advanced proficiency in English. The sensation-seeking items were assessed on a 7-point Likert scale ranging from 1 (not at all true of me) to 7 (extremely true of me). All other items were rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).

At Wave 1 we assessed sensation seeking with six items extracted from the Sensation-Seeking Scale (Steinberg et al., 2008). A sample item is “I enjoy new and exciting experiences and sensations, even if they are somewhat frightening.” High scores denote a heightened inclination toward sensation seeking. Cronbach’s alpha in our study was .81.

During Wave 2 we assessed self-control with the Brief Self-Control Scale (Morean et al., 2014). This seven-item scale incorporates two distinct dimensions: self-discipline (three items, e.g., “I am good at resisting temptation”) and impulse control (four items, e.g., “I often act without thinking”; reverse scored). Prior studies have validated the psychometric soundness of this scale for use with Chinese college students (Luo et al., 2021). High scores indicate heightened levels of self-control. Cronbach’s alpha in our study was .71.

During Wave 2 we evaluated FOMO with the Chinese version (Li et al., 2019) of the of the Fear of Missing Out Scale (Przybylski et al., 2013), which comprises eight items (e.g., “I get worried when I find out my friends are having fun without me”). Higher scores signify greater FOMO. Cronbach’s alpha in our study was .78.

In Wave 3 we assessed IGA with the Internet Game Addiction Scale, which is derived from the broader Internet Addiction Scale developed by Zhou and Yang (2006). Comprising eight items, the scoring of this scale reflects a continuum of addictive tendencies, with a higher score signifying greater tendencies. Sample items are “I often neglect many things around me because I’m focused on playing online games,” “When I try to reduce or stop playing online games, I become irritable and moody,” and “My gaming habits have negatively impacted my relationships and academic performance.” Cronbach’s alpha in our study was .90.

We used SPSS 24.0 for data analysis, supplemented by Model 15 of the PROCESS macro 3.0 (Hayes, 2018) for moderated mediation analysis. We included gender and age as control variables because of previous evidence indicating their effects on IGA (Rosendo-Rios et al., 2022). Utilizing the PROCESS macro, we generated bias-corrected bootstrapped 95% confidence intervals (CIs) through 5,000 iterations to ascertain the robustness of the data analysis outcomes. 

Table 1 shows the descriptive and correlation analysis results. Sensation seeking was negatively related to self-control and positively linked to FOMO and IGA. In addition, self-control showed a negative link with FOMO and IGA. Furthermore, FOMO showed a positive connection with IGA. Thus, Hypothesis 1 was supported.

Subsequently, we employed the PROCESS macro to examine the proposed model through a moderated mediation analysis. Table 2 shows the summary statistical results. Sensation seeking at Wave 1 exhibited a significant predictive effect on both self-control at Wave 2 and IGA at Wave 3. Moreover, self-control at Wave 2 demonstrated a significant predictive effect on IGA at Wave 3. The interaction term of sensation seeking at Wave 1 and FOMO at Wave 2 manifested a significant predictive effect on IGA at Wave 3 (see Table 2). Additionally, the interaction term of self-control at Wave 2 and FOMO at Wave 2 exhibited a marginally significant predictive effect on IGA at Wave 3 (see Table 2). Thus, self-control operated as a partial mediator of the longitudinal relationship between sensation seeking and IGA (indirect effect = .05), accounting for 23.81% of the total effect (effect value = .21). Thus, Hypothesis 2 was supported.

 

Moreover, the bootstrapped 95% CI for the moderation effect did not include zero. This implies that FOMO at Wave 2 served as a moderator, influencing both the direct relationship between sensation seeking at Wave 1 and IGA at Wave 3, and the link between self-control at Wave 2 and IGA at Wave 3.

To visually represent the moderating effect of FOMO, we utilized the pick-a-point approach and performed a simple slope analysis by grouping FOMO into high and low levels (M ± 1 SD). The results (see Figure 2) revealed that the positive predictive effect of sensation seeking on IGA was stronger for students with high FOMO (β = .27, p < .001) than for those with low FOMO (β = .04, p > .05).

Similarly, as shown in Figure 3, the results of the simple slope analysis indicated that the negative predictive effect of self-control on IGA was stronger for students with low FOMO (β = –.32, p < .001) than for those who with high FOMO (β = –.14, p = .07). These results supported Hypotheses 3a and 3b.

In summary, this research has made several substantial contributions in the area of IGA and extended the existing literature. First, we used a longitudinal design to investigate the association between sensation seeking and IGA. Second, we explored the mediating and moderating mechanisms through which sensation seeking influences IGA by incorporating self-control and FOMO. Third, we have expanded the scope of the I-PACE model (Brand et al., 2019) to better explain the antecedents of IGA.

 

Analyses demonstrated a positive link between sensation seeking and IGA, aligning with earlier research findings (Hu et al., 2017; Mehroof & Griffiths, 2010) and further supporting the cognitive–behavioral model of addiction (King et al., 2011). Over time, repetitive engagement in novel and stimulating gaming experiences may reinforce patterns of addictive behavior, thereby contributing to the onset or escalation of IGA. Evidence across various domains has consistently indicated that sensation seeking is a high-risk predictor for diverse forms of addiction.

 

The results of this study substantiated the role of self-control as a mediator of the link between sensation seeking and IGA. Furthermore, within the context of self-regulation theory (Mamayek et al., 2017), self-control is posited as a critical mechanism for managing impulses and resisting temptations, thereby serving as a deterrent against the development or exacerbation of addictive behaviors.

 

We also found that FOMO positively moderated the associations between sensation seeking and IGA, and between and self-control and IGA. Specifically, there was a more pronounced predictive effect of sensation seeking/self-control on IGA in our study among individuals with high (vs. low) FOMO. The dual systems model of behavior (Steinberg et al., 2018) indicates that problematic behaviors in adolescents stem from the asynchronous development of the arousal-prone reward system, which fosters sensation seeking, and the self-regulatory regions that constrain individuals’ resistance to these propensities. Empirical evidence suggests that sensation seeking may have a detrimental impact on self-regulation (Z. Wang et al., 2020), predominantly activating the impulsive system and diminishing self-control (Steinberg et al., 2008). Compared to their peers, individuals characterized by high sensation seeking or low self-control may already be more susceptible to the allure of online gaming, and FOMO could exacerbate this susceptibility by heightening the desire to participate in social interactions and experiences (Przybylski et al., 2013). Moreover, researchers have demonstrated that FOMO interacts with individual differences in sensation seeking to predict problematic technology use (Elhai et al., 2021). Individuals with elevated sensation-seeking tendencies are particularly prone to experiencing FOMO, driven by their inclination to seek out novel and stimulating experiences to satiate their need for excitement and arousal.

To mitigate the rising concern about IGA among college students, educational programs aimed at enhancing self-control skills could prove instrumental in equipping students with the ability to regulate their impulses and make decisions aligned with long-term goals. Implementing strategies that emphasize the importance of balancing online and offline activities, promoting healthy social interactions, and fostering a supportive campus environment could contribute to a holistic approach in reducing IGA. Beyond individual-level interventions, program planners at institutions should consider integrating digital literacy and responsible gaming education into curricula to raise awareness of potential risks associated with excessive gaming. Additionally, staff at universities could collaborate with mental health professionals to provide targeted counseling services and peer-support programs, ensuring that students struggling with IGA have access to timely and effective assistance. From a societal perspective, policymakers and stakeholders should advocate for responsible gaming practices by working with game developers to incorporate features that promote healthy gaming behaviors, such as time-management reminders and in-game parental controls that could be useful for college students when they are home during vacations.

Although we have provided valuable evidence in this study, several limitations must be acknowledged and taken into account when evaluating the results. We examined gaming behaviors in a general college student population, with respondents who spent a mean of 1.65 to 2.19 hours of gaming each day. This was not a group of clinically diagnosed cases of gaming disorder, which typically involves more extreme usage of 8 or more hours per day. Our results captured gaming-related problems on a continuum and we acknowledge that clinical diagnosis requires more stringent criteria. Researchers could validate these results in future studies with diagnosed populations or with samples with longer playtimes. In addition, as the sample included only Chinese college students, generalizing these results requires caution. Cultural and contextual factors may influence IGA, so that further studies are needed to test cross-cultural validity. Additionally, the focus in our study was on whether sensation seeking predicts IGA, but we did not examine their reciprocal link; future research could use a cross-lagged design. Last, relying solely on self-reported data limits insights into the mechanisms of IGA. In future studies, researchers could incorporate objective measures and physiological indicators.

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