{"paper_id":"1a7ec29d-d600-4c20-a4df-0a2e3a03a59b","body_text":"Attitudes or Norms? 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The Filtering Role of Self-Esteem in Gaming Intentions Sun-Jae Doh, Jang-Sun Hwang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8331619/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Apr, 2026 Read the published version in BMC Psychology → Version 1 posted 13 You are reading this latest preprint version Abstract Background Online gaming has become a pervasive leisure activity among young adults, further intensified by the COVID-19 pandemic. While problematic game use (PGU) has been extensively examined in adolescents, it is rarely known about its determinants among college students experiencing greater autonomy and social pressure. Guided by the Theory of Planned Behavior (TPB), this study investigates how attitudes, subjective norms, and perceived behavioral control (PBC) shape gaming intention and how this intention sequentially predicts excessive game use (EGU) and PGU. The study further examines self-esteem as a moderator that may alter the cognitive and social mechanisms underlying intention formation. Methods A sample of 303 Korean undergraduates with online gaming experience participated in the survey with validated measures of TPB constructs, intention, EGU, PGU, and self-esteem. Structural equation modeling (SEM) tested the hypothesized pathways, including sequential mediation from intention → EGU → PGU. Multi-group SEM was used to examine moderation by self-esteem. Results The overall SEM demonstrated good fit. Subjective norm (β = .612), PBC (β = .378), and attitude (β = .124) significantly predicted intention. Intention strongly predicted EGU (β = .709), which subsequently predicted PGU (β = .326). PBC also directly influenced EGU (β = .104). Multi-group analyses revealed distinct mechanisms by self-esteem: attitudes predicted intention only among high self-esteem students, whereas subjective norms had a substantially stronger effect among low self-esteem students. Differences in ATT → INT (Δχ² = 4.97, p < .05) and SUB → INT (Δχ² = 6.88, p < .01) were significant. Conclusions The findings validate TPB in predicting gaming behavior and clarify the progression from intention to excessive and problematic use. Self-esteem shapes the cognitive and social antecedents of intention, highlighting the need for tailored interventions: autonomy- and value-based strategies for high self-esteem individuals, and norm- or peer-based approaches for low self-esteem individuals. Theory of Planned Behavior Online Gaming Excessive Game Use Problematic Game Use Self-Esteem Figures Figure 1 Figure 2 Background The rapid spread of digital media has made online gaming a leading leisure activity among youth worldwide. Mobile adoption and the interactive nature of MMORPGs have raised engagement and play frequency [ 1 ]. COVID-19 further accelerated this shift: school closures affected approximately 1.5 billion students and increased online gaming [ 2 , 3 ]. Yet research has focused mainly on adolescents, leaving college populations underexamined. In Korea, many college students play games regularly—often exceeding five hours weekly—and, given greater autonomy, reduced parental oversight, and diverse social/academic demands, may be especially prone to heavy play. This demographic context suggests that determinants of online gaming may operate differently in emerging adulthood than in adolescence. PGU (Problematic Game Use) refers to a maladaptive pattern of game use that persists despite negative consequences, often accompanied by psychological and social impairment [ 4 , 5 ]. This condition encompasses symptoms such as failure to control time, withdrawal, and deterioration in academic or occupational performance. Recent studies have shown that PGU is positively associated with a variety of negative outcomes including depression, loneliness, and social anxiety [ 6 ], and is accordingly associated with life dissatisfaction and social withdrawal. Moreover, PGU often co-occurs with other problematic online behaviors, such as excessive social media use and online gambling [ 7 ]; therefore, it should be managed as a multifaceted public health concern. Guided by the Theory of Planned Behavior (TPB) [ 8 ], which links attitudes, subjective norms, and perceived behavioral control (PBC) to intention and behavior, this study models a pathway from TPB constructs → intention → excessive use → PGU, employing mediation to test sequential effects. We further examine self-esteem as a moderator—salient for college students navigating high autonomy and social influence but rarely tested in PGU [ 9 , 10 ]. By differentiating usage stages and incorporating self-esteem, the study aims to clarify intention formation and escalation, identify individual differences in pathways, and inform targeted interventions for college students. In doing so, it also extends TPB’s applicability to problematic online gaming and offers practical leverage points for prevention. The rapid penetration of the digital environment has prevailed online gaming to one of the most prominent leisure activities among young people throughout the world. In particular, the widespread adoption of mobile devices and the interactive nature of MMORPGs (Massively Multiplayer Online Role-Playing Games) have increased both the level of engagement and the frequency of play [ 1 ]. The COVID-19 pandemic further intensified this trend; according to the World Health Organization [ 2 ], approximately 1.5 billion children, adolescents, and college students were unable to attend school during the pandemic, leading to a dramatic increase in the use of online media and games. With the shift to remote learning and the enforcement of social distancing measures, young adults dramatically increased their online activity time, with a particularly pronounced surge in gaming behavior being reported [ 3 ]. However, existing research has predominantly focused on adolescents, leaving the area of in-depth studies on problematic online game use (PGU) among college students and young adults relatively underexplored. A recent survey [ 11 ] reported that PGU is often observed among Korean college students who played online games 9.16 hours per a week in average. Compared to adolescents, college students have greater financial and temporal autonomy, experience less parental control, and suffer from diverse social and academic demands, which may make them more vulnerable to excessive gaming. PGU refers to a maladaptive pattern of game use that persists despite negative consequences, often accompanied by psychological and social impairment [ 4 , 5 ]. This condition encompasses symptoms such as failure to control time, withdrawal, and deterioration in academic or occupational performance. Recent studies have shown that PGU is positively associated with a variety of negative outcomes including depression, loneliness, and social anxiety [ 6 ], and is accordingly associated with life dissatisfaction and social withdrawal. Moreover, PGU often co-occurs with other problematic online behaviors, such as excessive social media use and online gambling [ 7 ]; therefore, it should be managed as a multifaceted public health concern. The Theory of Planned Behavior (TPB) posits that attitudes, subjective norms, and perceived behavioral control influence behavioral intention, which in turn predicts actual behavior [ 8 ]. Nonetheless, most prior research adopting TBD examined gaming behavior in a unidimensional framework or analyzed PGU solely as an independent behavioral disorder. To address these limitations, the current study distinguishes between ‘excessive game use’ and ‘problematic game use’ as separate entities, and employs mediation analysis to examine the pathway from TPB constructs to behavioral intention, excessive use, and ultimately problematic use in order. Self-esteem, an individual’s self-evaluation, is an important moderating factor in digital media use research. Given that college students are at the developmental stage characterized by both heightened autonomy and strong social influences, the pathways can be led to PGU varied by self-esteem levels. However, empirical investigations into the moderating role of self-esteem in PGU remain scarce. This study seeks to fill this gap by analyzing how self-esteem influences the TPB-based pathways from behavioral intention through stages of game usage behavior [ 9 , 10 ]. Up to date, it has rarely been investigated the moderating role of self-esteem into the core TPB pathway—attitude, subjective norm, and perceived behavioral control → intention → excessive use → problematic use— with college student samples. By differentiating between excessive and problematic use, this study aims to provide a more precise explanation of the progression of gaming behavior, empirically identify individual differences in behavioral pathways by level of self-esteem, and extend prior research beyond an adolescent focus to capture the unique intersection of autonomy and social influence in college students. With this investigation, the study is expected to reveal distinct mechanisms underlying intention formation, offers empirical grounds for developing tailored intervention strategies for college students, and advances the theoretical applicability of TPB in the context of problematic online game use. Excessive and Problematic Online Game Use Nowadays, excessive and problematic online gaming has been considerably prevalent in many countries, especially since the digital environment was embedded into the game industry. Moreover, COVID-19 pandemic forced many people to excessively use online games. The WHO (World Health Organization) reported that 1.5 billion children were out of school due to the COVID-19, and their game-use time was dramatically increased [ 2 ]. To make the make worse, some significant numbers of children in many countries showed IGD (Internet Gaming Disorder) including US youth (8.5%), Dutch adolescents (5.5%), Australian students (5%), and so forth [ 12 ]. Problematic online game use refers to “a maladaptive pattern of online gaming that results in significant impairment or distress in personal, social, academic, or occupational functioning [ 4 ]”. This behavior is typically characterized by preoccupations with gaming, withdrawal symptoms without gaming, loss of control over gaming time, and continued playing in spite of negative consequences [ 5 ]. Problematic online game use is similar with other addictive behavior such as gambling, for individuals might play gaming as maladaptive coping strategies to soothe stress, negative emotions, or social difficulties [ 13 , 14 ]. Major literatures including ‘The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)’, and ‘the International Classification of Diseases, Eleventh Revision (ICD-11)’ have evaluated problematic online gaming as a potential mental health disorder with legitimizing its clinical significance [ 3 , 5 ]. In the same vein, problematic online gaming is a significant public health concern, since it yields various negative outcomes such as academic decline, social withdrawal, family conflict, and life dissatisfaction [ 15 , 16 ]. There is a strong relationship between problematic gaming and mental health issues such as depression, loneliness, and social anxiety [ 6 , 13 , 14 , 6 ]. To be serious, the problematic online gaming can accompany with other problematic online behaviors, such as excessive social networking or online gambling [ 7 ]. The problematic online gaming is regarded as social harmfulness which should be resolved with societal approach. The problematic online gaming prevails specific demographic groups including children, adolescents, and males. Studies with large samples of adolescents report that prevalence rates range from 1.8% to 3.1% using conservative criteria, with higher rates observed when broader definitions are applied [ 5 ]. Males are consistently evaluated to be at higher risk than females, and problematic gaming is more common among adolescents and young adults [ 5 ]. The rise of massively multiplayer online role-playing games (MMORPGs) with user-to-user interactions has contributed to the increasing visibility of problematic gaming behaviors [ 13 , 17 ]. Theory of Planned Behavior (TPB) and Its Application to Gaming Behavior To resolve this societal symptom, several factors should be managed. The literature identifies several key psychological and social factors underlying online gaming behavior. Among various concepts, the theory of planned behavior (TPB) provides a foundational framework for understanding the human behavior, especially in technology and online environment [ 8 ]. TPB proposes that individual behavior is primarily driven by behavioral intentions, which are influenced by three key factors: attitude toward the behavior, subjective norms, and perceived behavioral control (PBC). Attitude represents individuals’ favorable or unfavorable evaluations of the behavior. Subjective norm means perceived social pressure to perform or refrain from the behavior. Perceived behavioral control reflects the perceived difficulty of exerting the behavior, and may also yield a direct effect on behavior, particularly in contexts where actual control is constrained [ 8 ]. Followings describe the causal relationships between these three factors and Intention to use online games. The prevalence of digital environment has enabled relevant research to take full benefits from TPB. Within digital media research, TPB has been employed extensively to explain behaviors including various Internet usage, smartphone dependence, online consumer activity, and digital gaming adopted and extended TPB to explain digital media consumption [ 18 , 19 ]. By integrating TPB with social cognitive theory, they reported that the importance of attitudes toward media content, perceived social expectations, and perceived behavioral control in shaping media consumption. Regarding online gaming behavior, the TPB provides a wide range of explanations. Attitude can reflect the feeling associated with gaming; subjective norms may include social approval from peers; and PBC may represent individuals’ beliefs in their ability to regulate gaming time. Collectively, these factors predict the intention to play games, which subsequently influences actual gaming behavior. Studies report that three components including attitudes toward gaming, perceived social norms, and perceived behavioral control significantly influence both the intention to play online games [ 20 ]. Specifically, Attitude, which is an individual's overall evaluation of playing online games, is a critical factor of the playing online games. Lee [ 20 ] applied TPB by incorporating flow experience and perceived enjoyment, found that attitude is a critical predictor of behavioral intention to play online games. Similarly, Alzahrani and his colleagues also reported that attitude, along with perceived enjoyment and flow, significantly influenced actual online game use [ 21 ]. Briefly, positive attitudes toward online gaming environments are associated with higher intentions to play, as users who perceive gaming as enjoyable are more likely to engage in such activities. Subjective norms reflect the perceived social pressure from others including family, friends and social groups to gaming behavior. Subjective norms have been supported for its strong relationship with behavioral intentions as shown in a comprehensive investigation with a meta-analysis [ 22 ]. Accordingly, subjective norms might positively affect the intention to play online games [ 21 , 20 ]. Weiss and Löbbecke combined TPB with social network theory, showing that social interaction design and network exposure—key elements of subjective norms—significantly influence online gaming adoption [ 23 ]. Perceived behavioral control (PBC) is supported to have positive affect on the intention to play online games. Relevant studies [ 20 , 21 ] reported that PBC was a significant predictor of actual online game use, as individuals who feel higher capabilities of playing online games are more likely to play games. Briefly, higher perceived behavioral control—such as ease of access and confidence in gaming skills—leads to stronger intentions to engage in online gaming. These findings provide rigid supports for the TPB-based model that attitude, subjective norms, and PBC positively affect the intention to play online games. Attitude shapes intention through favorable evaluations of gaming, subjective norms perform social influence, and PBC reflects the perceived ease of playing. These factors explain a substantial proportion of the variance in gaming intentions, with some studies reporting that TPB constructs account for 70% or higher of the variance in intention to play [ 20 , 21 , 24 ]. Additionally, TPB explains the transition from intention to actual behavior, particularly in contexts where this transition may be impaired. In gaming, the difference between controlled excessive use and problematic behavior is critical. Previous research [ 25 ] suggests that while behavioral intentions largely predict behavior, the degree of perceived behavioral control (PBC) determines whether such intentions lead to adaptive outcomes. Excessive gaming intentions may be enhanced by enjoyment, stress relief, or social support. However, when PBC is low, individuals may find it difficult to stop playing, even when experiencing negative consequences. This disconnects between intentions and perceived control underlies problematic gaming behavior. Hence, predicting problematic game use should not only incorporate the traditional TPB components and its paths but also consider excessive use as a mediator between intention and problematic game use behavior. The Moderating Role of Self-Esteem Self-esteem can play a critical role in predicting the online game use behavior. In the context of TPB and gaming behavior described above, self-esteem can moderate the relationship between of psychological and social variables and behavior. Individuals with low self-esteem can be more inclined to play games excessively for the purpose of escaping from the reality, seeking affirmation or stress relief through virtual achievements in online games [ 26 ]. As a moderating variable, self-esteem can affect the strength of the relationship between three antecedents of TPB and core dependent variable, the intention to play online game. Briefly, people with lower self-esteem may be more prone to online game use due to reduced self-regulatory capacity or emotional reliance on gaming. Conversely, individuals with higher self-esteem may exhibit greater behavioral control, mitigating the risks associated with high intentions. Specifically, when people hold low self-esteem, behaviors that promise competence or social status become especially self-affirming; as a result, favorable attitudes are more likely to translate into strong intentions [ 27 , 28 ]. Relatedly, self-determination theory highlights the competence and relatedness gratifications delivered by gaming, which can render attitude-consistent intention formation especially potent for those with lower self-esteem [ 29 , 30 ]. Second, sociometer theory conceptualizes self-esteem as an index of perceived relational value; low self-esteem heightens vigilance to approval and rejection cues and thereby strengthens conformity to social expectations [ 31 ]. In socially embedded gaming contexts (teams, guilds, peer chat), this implies a stronger translation of subjective norms into intentions among low-self-esteem individuals, consistent with evidence that lower self-esteem is associated with greater susceptibility to interpersonal influence [ 32 ]. Third, because self-esteem covaries with generalized efficacy beliefs [ 33 ], individuals with high-self-esteem rely less on domain-specific control appraisals when forming intentions, whereas low-self-esteem individuals depend more on perceived controllability to offset anticipated failure. Thus, it is postulated that self-esteem attenuates the three TPB paths to intention—lower self-esteem strengthens the relationships between three antecedents and the intention, whereas higher self-esteem weakens them. Adopting self-esteem into the TPB-based model enhances its explanatory power with explaining the role of individual differences in online game behavior. Methods Research Design and Hypotheses As described, three anteceding components in TPB – attitudes toward the online game, subjective norms, and perceived behavioral control – are predicted to affect the intention to play online games. Though existing literatures [ 20 , 21 ] support the TPB model to predict gaming behavior, the current study focuses on verifying the causal relationship model by dividing gaming behavior into excessive and problematic use of online games. More importantly, the moderating role of self-esteem is posited and examined in the model. As noted earlier, the resolution to manage problematic gaming behavior should be applied differently depending on the user’s characteristics, and the study focuses self-esteem. Accordingly, following hypotheses are investigated and it is depicted as Fig. 1 . H1: Attitude toward the online game is positively associated with the intention to play online games H2: Subjective norm is positively associated with the intention to play online games H3: Perceived behavioral control is positively associated with the intention to play online games and the excessive use of online games. H4: Perceived behavioral control is positively associated with the excessive use of online games. H5: Intention to play online games is positively associated with the excessive use of online games. H6: Excessive use of online games is positively associated with the problematic use of online games. H7 (Moderation): Self-esteem negatively moderates the relationship between attitude and intention, such that the positive association is stronger among individuals with lower self-esteem (and weaker among those with higher self-esteem). H8 (Moderation): Self-esteem negatively moderates the relationship between subjective norm and intention, such that the positive association is stronger among individuals with lower self-esteem. H9 (Moderation): Self-esteem negatively moderates the relationship between perceived behavioral control and intention, such that the positive association is stronger among individuals with lower self-esteem. Participants and Procedure This study was conducted with undergraduate students enrolled at a university located in Seoul, South Korea. The recruitment targeted students who had experience of playing online games at least once. Participants were recruited by posting an invitation notice on the university’s online community and bulletin boards. The notice included information about the study’s purpose, participation procedure, privacy protection policy, and the voluntary nature of participation, as well as the right to withdraw at any time. Students who expressed interest in participating were provided with a URL link to the online survey. Upon completion of the survey, each participant received a coffee coupon for appreciation. Prior to participation, all respondents were provided with detailed information about the study’s purposes, the securement of sensitive information, and the voluntary nature of their responses. Informed consent was obtained electronically. A total of 339 responses were collected, of which 36 were excluded due to careless responding or reporting no experience with online game use. Finally, 303 responses were included for analysis. The demographic characteristics of the sample were as follows: 194 males (64.0%) and 109 females (36.0%), with a mean age of 21.88 years (SD = 2.66). The distribution of academic year was 23.1% freshmen, 33.3% sophomores, 18.5% juniors, and 25.1% seniors, representing a well-balanced sample across year levels and enabling a comprehensive reflection of online game use behaviors among students at different stages of their undergraduate college lives. Measures Key psychological variables related to online game use were measured using validated scales from previous research. Most items were rated on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Internal reliability coefficients (Cronbach’s α) for each measure are reported as followings. ‘Attitude toward Online Game Use’ was measured with three items adapted from [ 21 , 34 ] (e.g., “I think playing online games is good”). Internal consistency was excellent (Cronbach’s α = .958). ‘Subjective Norm’ was assessed using three items adapted from [ 35 , 36 ] to reflect perceived expectations from significant others (e.g., “Most people important to me play online games regularly”). Their internal consistency was acceptable with Cronbach’s α of .839. ‘Perceived Behavioral Control’ was measured with two items adapted from [ 34 , 36 ], focusing on self-efficacy related to online game use (e.g., “I have the knowledge and ability to enjoy online games”). Internal consistency was good (Cronbach’s α = .886). Three latent variables affected by these antecedents were measured with reliable items. Intention to Use Online Games was measured with three items evaluating plans and willingness to play games in the future (e.g., “I will continue to play online games in the future”), with higher level of reliability (Cronbach’s α = .947). Excessive Game Use (EGU) was measured with three self-report items based on [ 37 , 38 ], assessing weekly gaming frequency, average weekly gaming hours, and the proportion of leisure time spent gaming. Problematic Game Use (PGU) was assessed with five core items from the shortened version of [ 1 ]’s Problematic Online Game Use Scale (POGUS), covering obsession, withdrawal, and loss of control. Internal consistency was satisfactory (Cronbach’s α = .863). The moderating variable, Self-Esteem, was measured with four items adapted from [ 36 ] (e.g., “I feel that I have a number of good qualities”). The internal consistency coefficient (Cronbach’s α) for this study was .919. Results Structural Equation Model (SEM) Results for the Overall Sample To examine the proposed model, structural equation modeling (SEM) was conducted using maximum likelihood estimation. The model tested included latent variables for attitude toward online gaming (ATT), subjective norms (SUB), perceived behavioral control (PBC), intention to play online games (INT), excessive game use (EGU), and problematic game use (PGU). The overall model, as shown in Fig. 2 , demonstrated an acceptable fit to the data: χ2(142) = 240.170, p < .001, CFI = .977, TLI = .972, RMSEA = .048, indicating good model fit according to the criteria suggested by [ 39 ]. The results revealed that all hypothesized paths were statistically significant. Specifically, intention to play online games was strongly predicted by subjective norms (β = .612, p < .001), followed by perceived behavioral control (β = .378, p < .001), and to a lesser extent, attitude toward online gaming (β = .124, p < .05), indicating that perceived social pressure and control beliefs play a more substantial role in shaping game-related behavioral intentions than personal evaluations. Intention, in turn, emerged as a strong predictor of excessive game use (β = .709, p < .001), which subsequently led to problematic game use (β = .326, p < .001), supporting the proposed mediational sequence. In addition, perceived behavioral control also had a direct but smaller effect on excessive use (β = .104, p < .05), underscoring its dual role in influencing both intention and behavior. These findings validate the sequential pathway posited by the TPB, while also highlighting the dominant role of social influences and perceived control in driving gaming intentions and behaviors. Moderating Effect of Self-Esteem: Multi-Group SEM To determine whether self-esteem moderated the hypothesized structural relationships, the sample was divided into high (n = 145) and low (n = 158) self-esteem groups based on a median split, and multi-group SEM was conducted separately for each. The model fit indices indicated that the model structure was supported in both groups, though with varying degrees of fit. For the high self-esteem group, the fit indices were χ² (142) = 161.136, p = .130; CFI = .991; TLI = .989; RMSEA = .031, indicating an excellent fit based on conventional cutoff criteria [ 39 ]. Although the chi-square test was non-significant ( p = .130), which traditionally implies that the model does not significantly deviate from the data, it should be interpreted with caution due to its well-known sensitivity to sample size [ 40 ]. In small to moderate samples, a non-significant chi-square is actually desirable and supports model fit. The very high CFI and TLI values, along with a low RMSEA, affirm the robustness of the model in this group. In comparison, the low self-esteem group yielded χ²(142) = 226.695, p < .001; CFI = .959; TLI = .951; RMSEA = .062, suggesting an acceptable but comparatively weaker fit. Together, these findings support the configural invariance of the model and confirm that the overall structure holds across levels of self-esteem, albeit more strongly for individuals with higher self-regard. Table 1 Structural Path Estimates in two groups of Self-Esteem Path Self-Esteem Estimate (β) C.R. p-value ATT → INT High 0.147 2.277 .023 ATT → INT Low 0.053 0.843 .400 SUB → INT High 0.444 5.276 < .001 SUB → INT Low 0.796 7.785 < .001 PBC → INT High 0.545 4.503 < .001 PBC → INT Low 0.261 2.982 .003 PBC → EGU High 0.130 1.717 .086 PBC → EGU Low 0.157 2.206 .027 INT → EGU High 0.811 9.056 < .001 INT → EGU Low 0.621 7.764 < .001 EGU→PGU High 0.291 3.564 < .001 EGU→PGU Low 0.415 5.114 < .001 The comparative results of the structural paths between the high and low self-esteem groups revealed meaningful divergence in the psychosocial mechanisms leading to excessive and problematic gaming as shown in Table 1 . Notably, the effect of attitude on behavioral intention (ATT → INT) was statistically significant only in the high self-esteem group (β = .147, p < .05), while it was nonsignificant in the low self-esteem group (β = .053, p = .400), indicating that individuals with higher self-esteem are more likely to form intentions based on their personal evaluations of gaming. In contrast, subjective norm (SUB → INT) exerted a much stronger influence in the low self-esteem group (β = .796, p < .001) compared to the high self-esteem group (β = .444, p < .001), suggesting that individuals with lower self-worth are more susceptible to social pressures and normative expectations when forming gaming intentions. Although perceived behavioral control (PBC → INT) significantly predicted intention in both groups, the effect was more pronounced in the high self-esteem group (β = .545) than in the low self-esteem group (β = .261), hinting that perceived control may be more internalized among those with higher self-esteem. Importantly, the core mediational pathways—intention predicting excessive use (INT → EGU) and excessive use predicting problematic use (EGU → PGU)—remained robust and statistically significant across both groups, confirming that the motivational sequence outlined by TPB holds consistently, regardless of individual differences in self-esteem. To test the moderation effect more rigorously, a series of nested model comparisons were conducted by constraining each structural path to be equal across groups and examining the changes in chi-square [ 41 ]. A significant change in chi-square (Δχ²) indicates that the effect of a particular path differs significantly between groups, confirming a moderation effect. Table 2 Differences between the path coefficients across the two groups Path Self-Esteem Group Self-Esteem Group Δχ²(df) p-value Path High (β) Low (β) Δχ²(df) p-value ATT → INT .147 .053 4.97 .026 SUB → INT .444 .796 6.88 .009 PBC → INT .545 .261 3.12 .077 PBC → EGU .130 .157 0.55 .458 INT → EGU .811 .621 1.04 .308 EGU→PGU .291 .415 0.88 .348 Δχ²=Chi-square difference between unconstrained and constrained path models (df = 1). The results as shown in Table 2 reveals that the path from attitude to intention (ATT → INT) significantly differed between groups, Δχ²(1) = 4.97 ( p < .05), indicating that individuals with high self-esteem were more likely to act based on their attitudinal evaluations compared to their low self-esteem counterparts. Similarly, the path from subjective norm to intention (SUB → INT) also exhibited a significant difference, Δχ² (1) = 6.88 ( p < .01) suggesting that perceived social pressure plays a disproportionately stronger role for those with lower self-esteem. Although the difference in perceived behavioral control to intention (PBC → INT) did not reach conventional levels of statistical significance (Δχ²(1) = 3.12, p = .077), it was marginally significant and suggests a trend toward stronger internal control dynamics among individuals with higher self-regard. For the remaining paths (PBC → EGU, INT → EGU, and EGU → PGU) none showed statistically significant differences between groups (all p values > .30), indicating that these behavioral progression pathways operate similarly regardless of self-esteem level. This suggests that once gaming intentions are formed, the subsequent translation into excessive use and the escalation from excessive to problematic use are largely invariant across self-esteem profiles. In other words, while self-esteem shapes the formation of gaming intentions through differential reliance on internal attitudes and external norms, it does not substantially alter the behavioral enactment of those intentions into excessive or problematic gaming behaviors. These results underscore the robustness of the TPB’s core mediational sequence across individual differences in self-esteem, aligning with prior evidence that post-intentional behavioral processes tend to be more universal [ 19 , 37 ]. Discussion The current study, grounded in TPB (Theory of Planned Behavior), distinguishes online gaming behavior into excessive game use (EGU) and problematic game use (PGU) and examines the moderating role of self-esteem. Structural equation modeling (SEM) analysis revealed that attitude, subjective norm, and perceived behavioral control (PBC) significantly influenced behavioral intention, which in turn significantly predicted excessive use and problematic use. Among the predictors, subjective norm had the strongest effect on behavioral intention (β = .612, p < .001), suggesting that peer and social environmental influences are key determinants of gaming behavior. Furthermore, PBC showed direct effects not only on behavioral intention but also on excessive use (double paths), underscoring the importance of control beliefs in actual behavior. These findings provide empirical support for the notion that problematic use can be intensified as an extension of intentional use. By distinguishing the behavioral stages into excessive and problematic use, the study offers a refined explanation of the developmental trajectory of gaming behavior. By integrating self-esteem into the TPB framework, this study empirically identifies how the same causal structure varies by levels of individuals’ self-esteem. The moderating effect of self-esteem offers important insights into the personal context of online gaming behavior. As shown in the result, the hypothetical model proposed (Fig. 1 ) was strongly supported in individuals with lower self-esteem; however, the model was less significant to predict the game behavior of individuals with higher self-esteem, in terms of chi-square measure. Nevertheless, the model for each segment showed strong goodness of fit with significant path coefficients in most paths. It is important which path is more critical in each group. For individuals with high self-esteem, attitudes played a central role in shaping intention, consistent with the tendency of autonomous individuals to rely on internal value judgments as behavioral guidelines [ 30 , 42 ]. However, individuals with low self-esteem were more sensitive to social norms, aligning with prior findings that they are more vulnerable to external pressures in digital environments [ 43 ]. The study further demonstrates that the dual pathways of gaming behavior can vary depending on self-esteem level with relating these findings to the dual-process perspective [ 19 , 44 ]. The intentional (cognitive) pathway, through a central route, involves the deliberative planning and execution of behavior based on personal attitudes, beliefs, and social norms, whereas the habitual (automatic) pathway, through a peripheral route, reflects unconscious behaviors shaped by repeated experiences and environmental cues. Individuals with higher self-esteem primarily formed gaming behaviors through the intentional–cognitive path, while lower self-esteem individuals relied more heavily on the habitual–social influence path. This provides a theoretical framework for explaining how psychological traits lead to different behavioral mechanisms under the same environment for playing games. Some academic contributions of this study are yielded as follows. First, by incorporating self-esteem as a moderating variable into an extended TPB model, it enhances the predictive power of gaming behavior research. Second, by differentiating between excessive and problematic use, it offers a useful framework for explaining behavioral progression in future studies. Third, by identifying differences in behavioral pathways between high and low self-esteem groups, it theoretically supports the need for personalized treatment. From a practical perspective, the findings suggest two key implications. First, tailored prevention and intervention strategies are needed. For the low self-esteem group, strategies leveraging peer influence and social norms and providing positive social feedback would be more effective [ 22 ]. For the high self-esteem segment, value- and goal-oriented strategies that stimulate autonomy and intrinsic motivation are more appropriate [ 29 , 30 ]. Second, education on preventing of gaming overuse is essential. Recent studies [ 15 , 45 ] suggest that programs designed to strengthen PBC through self-regulation training and time management can effectively enhance long-term control over gaming behavior. Such approaches can also inform personalized gaming use guidelines based on self-esteem assessments, implemented in university counseling centers or health institutions. Future research should employ longitudinal designs to trace and analyze the causal relationship between gaming behavior and self-esteem over time. Additionally, examining differences in TPB pathways and self-esteem’s moderating effects across cultural contexts (individualism vs. collectivism) would enhance the generalizability of the findings to various groups globally and aid in developing culturally tailored intervention strategies. In sum, this study affirms the validity of TPB in explaining online gaming behavior while increasing the precision of its predictive model through the integration of self-esteem as a key individual difference variable. These findings contribute theoretically to the extension of digital behavior research and practically to the design of customized interventions based on self-esteem levels. Declarations Ethics approval and consent to participate The study protocol was submitted to and approved by The Institutional Review Board of Chung-Ang University (IRB approval no.: 1041078-201804-HRSB-081-01). All procedures performed in this study were conducted in accordance with the ethical standards for research involving human participants. Participation was voluntary, and informed consent was obtained electronically from all respondents prior to data collection. The study involved minimal risk, and confidentiality and anonymity were ensured throughout. Consent for publication Not applicable. All data were collected anonymously, and no identifying information is included in the manuscript and the original data. Availability of data and materials The datasets generated and analyzed during the present study are publicly available in the Figshare repository at the following DOI: https://doi.org/10.6084/m9.figshare.30018790.v1. Competing interests The authors declare that they have no competing interests, financial or otherwise, related to this research. Funding This research received no external funding. Authors’ contributions All authors contributed to the study’s conception, design, analysis, and manuscript preparation. The first author led the study design, data collection, and initial manuscript drafting. The second author contributed to data analysis, interpretation, and manuscript revision. All authors reviewed and approved the final manuscript. Acknowledgements The authors thank the participants for their time and cooperation. The authors also express appreciation to colleagues who provided helpful feedback during the development of the study. References Kim MG, Kim J. Cross-validation of reliability, convergent and discriminant validity for the problematic online game use scale. Comput Hum Behav. 2010;26(3):389–98. World Health Organization. WHO Director-General’s opening remarks at the media briefing on COVID-19. 2020 Mar 11. Available from: https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020 (accessed 10 Dec 2025). Flayelle M, Schimmenti A, Starcevic V, Billieux J. The landscape of problematic gaming: A systematic review. Cyberpsychology Behav Social Netw. 2023;26(1):3–17. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Washington (DC): American Psychiatric Association; 2013. Nogueira-López A, Sánchez-Iglesias I, López-Fernández O, Pontes HM. Problematic video game use: The role of self-esteem and psychological distress. Cyberpsychology Behav Social Netw. 2023;26(5):315–21. Gioia F, Rega V, Boursier V, Cyberpsychology. Behav Social Netw. 2022;25(9):565–72. Rozgonjuk D, Sindermann C, Elhai JD, Montag C. Problematic social media use and gaming disorder: Associations with psychological and social well-being. Cyberpsychology Behav Social Netw. 2021;24(8):531–7. Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179–211. Selfhout MHW, Branje SJT, Delsing M, ter Bogt TFM, Meeus WHJ. Different types of Internet use, depression, and social anxiety: The role of perceived friendship quality in adolescents. J Adolesc. 2009;32(5):813–29. McKay MT, Percy A, Cole JC. Self-esteem and self-efficacy: The influence of social media use on adolescents. Comput Hum Behav. 2018;81:83–90. Kim B, Kang HS, Park J. A latent profile approach for classifying internet gamers based on motives for online gaming. J Behav Addictions. 2023;12(1):148–58. Yousafzai SY, Sherin A. COVID-19 and internet gaming disorder in children and adolescents. J Pak Med Assoc. 2020;70(Suppl 3):S128–30. Maroney N, Williams BJ, Thomas A, Skues J, Moulding R. A stress-coping model of problem online video game use. Int J Mental Health Addict. 2019;17(4):845–58. Di Blasi M, Giardina A, Giordano C, Coco GL, Tosto C, Billieux J, Schimmenti A. Problematic video game use as an emotional coping strategy: Evidence from a sample of MMORPG gamers. J Behav Addictions. 2019;8(1):25–34. Haagsma MC, Caplan SE, Peters O, Pieterse ME. A cognitive-behavioral model of problematic online gaming: The role of cognitive coping and self-regulation. Comput Hum Behav. 2013;28(1):13–20. Festl R, Scharkow M, Quandt T. Problematic computer game use among adolescents, younger and older adults. Addiction. 2013;108(3):592–9. Billieux J, Deleuze J, Griffiths MD, Kuss DJ. Internet gaming addiction: The case of massively multiplayer online role-playing games. J Behav Addictions. 2015;4(3):205–12. Yue H, Li C, Liu M, Jin R, Bao H. Validity test of the theory of planned behavior in college students’ withdrawal from smartphone dependence. Curr Psychol. 2022;41(8):5524–31. LaRose R, Lin CA, Eastin MS. Unregulated internet usage: Addiction, habit, or deficient self-regulation? Media Psychol. 2003;5(3):225–53. Lee MC. Understanding the behavioral intention to play online games: An extension of the theory of planned behavior. Online Inf Rev. 2009;33(5):849–72. Alzahrani AI, Mahmud I, Ramayah T, Alfarraj O, Alalwan N. Extending the theory of planned behavior (TPB) to explain online game playing among Malaysian undergraduate students. Telematics Inform. 2017;34(4):239–51. Rivis A, Sheeran P. Descriptive norms as an additional predictor in the theory of planned behavior. Curr Psychol. 2003;22(3):218–33. Weiss T, Löbbecke C. Online gaming adoption at the stage of maturity: A study of social and technical influences. Int J Inf Manag. 2008;28(3):217–32. Lee MC, Tsai TR. What drives people to continue to play online games? An extension of technology model and theory of planned behavior. Int J Human–Computer Interact. 2010;26(6):601–20. Ajzen I. Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. J Appl Soc Psychol. 2002;32(4):665–83. Kavanagh M, Brett C, Brignell C. What is the reported relationship between self-esteem and gaming disorder? A systematic review and meta-analysis. Comput Hum Behav. 2023;145:10776. 10.1016/j.chb.2023.10776 . Sivanathan N, Pettit NC. Protecting the self through consumption: Status goods as affirmational commodities. J Exp Soc Psychol. 2010;46(3):564–70. Steele CM. The psychology of self-affirmation: Sustaining the integrity of the self. Adv Exp Soc Psychol. 1988;21:261–302. Deci EL, Ryan RM. The what and why of goal pursuits: Human needs and the self-determination of behavior. Psychol Inq. 2000;11(4):227–68. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55(1):68–78. Leary MR, Baumeister RF. The nature and function of self-esteem: Sociometer theory. Adv Exp Soc Psychol. 2000;32:1–62. Bearden WO, Netemeyer RG, Teel JE. Measurement of consumer susceptibility to interpersonal influence. J Consum Res. 1989;15(4):473–81. Judge TA, Erez A, Bono JE, Thoresen CJ. Are measures of self-esteem, neuroticism, locus of control, and generalized self-efficacy indicators of a common core construct? J Personal Soc Psychol. 2002;83(3):693–710. Ajzen I. Constructing a TPB questionnaire: Conceptual and methodological considerations. 2002. Available from: https://people.umass.edu/aizen/tpb.html (accessed 10 Dec 2025). Cooke R, Sniehotta F, Schüz B. Predicting binge-drinking behavior using an extended TPB: Examining the impact of anticipated regret and descriptive norms. Alcohol Alcohol. 2007;42(2):84–91. Ho SS, Lwin MO, Lee EW. Till logout do us part? Comparison of factors predicting excessive social network sites use and addiction between Singaporean adolescents and adults. Comput Hum Behav. 2017;75:632–42. Lukavská K, Hrabec O, Chrz V. The role of habits in massive multiplayer online role-playing game usage: Predicting excessive and problematic gaming through players' sensitivity to situational cues. Cyberpsychology, Behavior, and Social Networking. 2016;19(4):277–282. Lu Y, Zhou T, Wang B. Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Comput Hum Behav. 2009;25(1):29–39. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equation Modeling: Multidisciplinary J. 1999;6(1):1–55. Kline RB. Principles and practice of structural equation modeling. 4th ed. New York (NY): Guilford; 2023. Byrne BM. Structural equation modeling with Mplus: Basic concepts, applications, and programming. New York (NY): Routledge; 2012. Kernis MH. Toward a conceptualization of optimal self-esteem. Psychol Inq. 2003;14(1):1–26. Kang S. Social influence on internet game addiction in adolescents. Korean J Youth Stud. 2010;17(7):45–68. Petty RE, Cacioppo JT, Schumann D. Central and peripheral routes to advertising effectiveness: The moderating role of involvement. J Consum Res. 1983;10(2):135–46. Kim HK, Davis KE. Toward a comprehensive theory of problematic Internet use: Evaluating the role of self-esteem, anxiety, flow, and the self-rated importance of Internet activities. Comput Hum Behav. 2009;25(2):490–500. Additional Declarations No competing interests reported. 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The Filtering Role of Self-Esteem in Gaming Intentions\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eThe rapid spread of digital media has made online gaming a leading leisure activity among youth worldwide. Mobile adoption and the interactive nature of MMORPGs have raised engagement and play frequency [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. COVID-19 further accelerated this shift: school closures affected approximately 1.5\\u0026nbsp;billion students and increased online gaming [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Yet research has focused mainly on adolescents, leaving college populations underexamined. In Korea, many college students play games regularly\\u0026mdash;often exceeding five hours weekly\\u0026mdash;and, given greater autonomy, reduced parental oversight, and diverse social/academic demands, may be especially prone to heavy play. This demographic context suggests that determinants of online gaming may operate differently in emerging adulthood than in adolescence.\\u003c/p\\u003e \\u003cp\\u003ePGU (Problematic Game Use) refers to a maladaptive pattern of game use that persists despite negative consequences, often accompanied by psychological and social impairment [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. This condition encompasses symptoms such as failure to control time, withdrawal, and deterioration in academic or occupational performance. Recent studies have shown that PGU is positively associated with a variety of negative outcomes including depression, loneliness, and social anxiety [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e], and is accordingly associated with life dissatisfaction and social withdrawal. Moreover, PGU often co-occurs with other problematic online behaviors, such as excessive social media use and online gambling [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]; therefore, it should be managed as a multifaceted public health concern.\\u003c/p\\u003e \\u003cp\\u003eGuided by the Theory of Planned Behavior (TPB) [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e], which links attitudes, subjective norms, and perceived behavioral control (PBC) to intention and behavior, this study models a pathway from TPB constructs \\u0026rarr; intention \\u0026rarr; excessive use \\u0026rarr; PGU, employing mediation to test sequential effects. We further examine self-esteem as a moderator\\u0026mdash;salient for college students navigating high autonomy and social influence but rarely tested in PGU [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. By differentiating usage stages and incorporating self-esteem, the study aims to clarify intention formation and escalation, identify individual differences in pathways, and inform targeted interventions for college students. In doing so, it also extends TPB\\u0026rsquo;s applicability to problematic online gaming and offers practical leverage points for prevention.\\u003c/p\\u003e \\u003cp\\u003eThe rapid penetration of the digital environment has prevailed online gaming to one of the most prominent leisure activities among young people throughout the world. In particular, the widespread adoption of mobile devices and the interactive nature of MMORPGs (Massively Multiplayer Online Role-Playing Games) have increased both the level of engagement and the frequency of play [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. The COVID-19 pandemic further intensified this trend; according to the World Health Organization [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e], approximately 1.5\\u0026nbsp;billion children, adolescents, and college students were unable to attend school during the pandemic, leading to a dramatic increase in the use of online media and games. With the shift to remote learning and the enforcement of social distancing measures, young adults dramatically increased their online activity time, with a particularly pronounced surge in gaming behavior being reported [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. However, existing research has predominantly focused on adolescents, leaving the area of in-depth studies on problematic online game use (PGU) among college students and young adults relatively underexplored. A recent survey [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e] reported that PGU is often observed among Korean college students who played online games 9.16 hours per a week in average. Compared to adolescents, college students have greater financial and temporal autonomy, experience less parental control, and suffer from diverse social and academic demands, which may make them more vulnerable to excessive gaming.\\u003c/p\\u003e \\u003cp\\u003ePGU refers to a maladaptive pattern of game use that persists despite negative consequences, often accompanied by psychological and social impairment [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. This condition encompasses symptoms such as failure to control time, withdrawal, and deterioration in academic or occupational performance. Recent studies have shown that PGU is positively associated with a variety of negative outcomes including depression, loneliness, and social anxiety [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e], and is accordingly associated with life dissatisfaction and social withdrawal. Moreover, PGU often co-occurs with other problematic online behaviors, such as excessive social media use and online gambling [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]; therefore, it should be managed as a multifaceted public health concern.\\u003c/p\\u003e \\u003cp\\u003eThe Theory of Planned Behavior (TPB) posits that attitudes, subjective norms, and perceived behavioral control influence behavioral intention, which in turn predicts actual behavior [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. Nonetheless, most prior research adopting TBD examined gaming behavior in a unidimensional framework or analyzed PGU solely as an independent behavioral disorder. To address these limitations, the current study distinguishes between \\u0026lsquo;excessive game use\\u0026rsquo; and \\u0026lsquo;problematic game use\\u0026rsquo; as separate entities, and employs mediation analysis to examine the pathway from TPB constructs to behavioral intention, excessive use, and ultimately problematic use in order.\\u003c/p\\u003e \\u003cp\\u003eSelf-esteem, an individual\\u0026rsquo;s self-evaluation, is an important moderating factor in digital media use research. Given that college students are at the developmental stage characterized by both heightened autonomy and strong social influences, the pathways can be led to PGU varied by self-esteem levels. However, empirical investigations into the moderating role of self-esteem in PGU remain scarce. This study seeks to fill this gap by analyzing how self-esteem influences the TPB-based pathways from behavioral intention through stages of game usage behavior [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eUp to date, it has rarely been investigated the moderating role of self-esteem into the core TPB pathway\\u0026mdash;attitude, subjective norm, and perceived behavioral control \\u0026rarr; intention \\u0026rarr; excessive use \\u0026rarr; problematic use\\u0026mdash; with college student samples. By differentiating between excessive and problematic use, this study aims to provide a more precise explanation of the progression of gaming behavior, empirically identify individual differences in behavioral pathways by level of self-esteem, and extend prior research beyond an adolescent focus to capture the unique intersection of autonomy and social influence in college students. With this investigation, the study is expected to reveal distinct mechanisms underlying intention formation, offers empirical grounds for developing tailored intervention strategies for college students, and advances the theoretical applicability of TPB in the context of problematic online game use.\\u003c/p\\u003e\\n\\u003ch3\\u003eExcessive and Problematic Online Game Use\\u003c/h3\\u003e\\n\\u003cp\\u003eNowadays, excessive and problematic online gaming has been considerably prevalent in many countries, especially since the digital environment was embedded into the game industry. Moreover, COVID-19 pandemic forced many people to excessively use online games. The WHO (World Health Organization) reported that 1.5\\u0026nbsp;billion children were out of school due to the COVID-19, and their game-use time was dramatically increased [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. To make the make worse, some significant numbers of children in many countries showed IGD (Internet Gaming Disorder) including US youth (8.5%), Dutch adolescents (5.5%), Australian students (5%), and so forth [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eProblematic online game use refers to \\u0026ldquo;a maladaptive pattern of online gaming that results in significant impairment or distress in personal, social, academic, or occupational functioning [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]\\u0026rdquo;. This behavior is typically characterized by preoccupations with gaming, withdrawal symptoms without gaming, loss of control over gaming time, and continued playing in spite of negative consequences [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Problematic online game use is similar with other addictive behavior such as gambling, for individuals might play gaming as maladaptive coping strategies to soothe stress, negative emotions, or social difficulties [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. Major literatures including \\u0026lsquo;The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)\\u0026rsquo;, and \\u0026lsquo;the International Classification of Diseases, Eleventh Revision (ICD-11)\\u0026rsquo; have evaluated problematic online gaming as a potential mental health disorder with legitimizing its clinical significance [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eIn the same vein, problematic online gaming is a significant public health concern, since it yields various negative outcomes such as academic decline, social withdrawal, family conflict, and life dissatisfaction [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. There is a strong relationship between problematic gaming and mental health issues such as depression, loneliness, and social anxiety [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. To be serious, the problematic online gaming can accompany with other problematic online behaviors, such as excessive social networking or online gambling [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. The problematic online gaming is regarded as social harmfulness which should be resolved with societal approach.\\u003c/p\\u003e \\u003cp\\u003eThe problematic online gaming prevails specific demographic groups including children, adolescents, and males. Studies with large samples of adolescents report that prevalence rates range from 1.8% to 3.1% using conservative criteria, with higher rates observed when broader definitions are applied [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Males are consistently evaluated to be at higher risk than females, and problematic gaming is more common among adolescents and young adults [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. The rise of massively multiplayer online role-playing games (MMORPGs) with user-to-user interactions has contributed to the increasing visibility of problematic gaming behaviors [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eTheory of Planned Behavior (TPB) and Its Application to Gaming Behavior\\u003c/h2\\u003e \\u003cp\\u003eTo resolve this societal symptom, several factors should be managed. The literature identifies several key psychological and social factors underlying online gaming behavior. Among various concepts, the theory of planned behavior (TPB) provides a foundational framework for understanding the human behavior, especially in technology and online environment [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. TPB proposes that individual behavior is primarily driven by behavioral intentions, which are influenced by three key factors: attitude toward the behavior, subjective norms, and perceived behavioral control (PBC). Attitude represents individuals\\u0026rsquo; favorable or unfavorable evaluations of the behavior. Subjective norm means perceived social pressure to perform or refrain from the behavior. Perceived behavioral control reflects the perceived difficulty of exerting the behavior, and may also yield a direct effect on behavior, particularly in contexts where actual control is constrained [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. Followings describe the causal relationships between these three factors and Intention to use online games.\\u003c/p\\u003e \\u003cp\\u003eThe prevalence of digital environment has enabled relevant research to take full benefits from TPB. Within digital media research, TPB has been employed extensively to explain behaviors including various Internet usage, smartphone dependence, online consumer activity, and digital gaming adopted and extended TPB to explain digital media consumption [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. By integrating TPB with social cognitive theory, they reported that the importance of attitudes toward media content, perceived social expectations, and perceived behavioral control in shaping media consumption.\\u003c/p\\u003e \\u003cp\\u003eRegarding online gaming behavior, the TPB provides a wide range of explanations. Attitude can reflect the feeling associated with gaming; subjective norms may include social approval from peers; and PBC may represent individuals\\u0026rsquo; beliefs in their ability to regulate gaming time. Collectively, these factors predict the intention to play games, which subsequently influences actual gaming behavior. Studies report that three components including attitudes toward gaming, perceived social norms, and perceived behavioral control significantly influence both the intention to play online games [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eSpecifically, Attitude, which is an individual's overall evaluation of playing online games, is a critical factor of the playing online games. Lee [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e] applied TPB by incorporating flow experience and perceived enjoyment, found that attitude is a critical predictor of behavioral intention to play online games. Similarly, Alzahrani and his colleagues also reported that attitude, along with perceived enjoyment and flow, significantly influenced actual online game use [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. Briefly, positive attitudes toward online gaming environments are associated with higher intentions to play, as users who perceive gaming as enjoyable are more likely to engage in such activities. Subjective norms reflect the perceived social pressure from others including family, friends and social groups to gaming behavior. Subjective norms have been supported for its strong relationship with behavioral intentions as shown in a comprehensive investigation with a meta-analysis [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]. Accordingly, subjective norms might positively affect the intention to play online games [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Weiss and L\\u0026ouml;bbecke combined TPB with social network theory, showing that social interaction design and network exposure\\u0026mdash;key elements of subjective norms\\u0026mdash;significantly influence online gaming adoption [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. Perceived behavioral control (PBC) is supported to have positive affect on the intention to play online games. Relevant studies [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] reported that PBC was a significant predictor of actual online game use, as individuals who feel higher capabilities of playing online games are more likely to play games. Briefly, higher perceived behavioral control\\u0026mdash;such as ease of access and confidence in gaming skills\\u0026mdash;leads to stronger intentions to engage in online gaming.\\u003c/p\\u003e \\u003cp\\u003eThese findings provide rigid supports for the TPB-based model that attitude, subjective norms, and PBC positively affect the intention to play online games. Attitude shapes intention through favorable evaluations of gaming, subjective norms perform social influence, and PBC reflects the perceived ease of playing. These factors explain a substantial proportion of the variance in gaming intentions, with some studies reporting that TPB constructs account for 70% or higher of the variance in intention to play [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAdditionally, TPB explains the transition from intention to actual behavior, particularly in contexts where this transition may be impaired. In gaming, the difference between controlled excessive use and problematic behavior is critical. Previous research [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e] suggests that while behavioral intentions largely predict behavior, the degree of perceived behavioral control (PBC) determines whether such intentions lead to adaptive outcomes. Excessive gaming intentions may be enhanced by enjoyment, stress relief, or social support. However, when PBC is low, individuals may find it difficult to stop playing, even when experiencing negative consequences. This disconnects between intentions and perceived control underlies problematic gaming behavior. Hence, predicting problematic game use should not only incorporate the traditional TPB components and its paths but also consider excessive use as a mediator between intention and problematic game use behavior.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eThe Moderating Role of Self-Esteem\\u003c/h3\\u003e\\n\\u003cp\\u003eSelf-esteem can play a critical role in predicting the online game use behavior. In the context of TPB and gaming behavior described above, self-esteem can moderate the relationship between of psychological and social variables and behavior. Individuals with low self-esteem can be more inclined to play games excessively for the purpose of escaping from the reality, seeking affirmation or stress relief through virtual achievements in online games [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. As a moderating variable, self-esteem can affect the strength of the relationship between three antecedents of TPB and core dependent variable, the intention to play online game. Briefly, people with lower self-esteem may be more prone to online game use due to reduced self-regulatory capacity or emotional reliance on gaming. Conversely, individuals with higher self-esteem may exhibit greater behavioral control, mitigating the risks associated with high intentions.\\u003c/p\\u003e \\u003cp\\u003eSpecifically, when people hold low self-esteem, behaviors that promise competence or social status become especially self-affirming; as a result, favorable attitudes are more likely to translate into strong intentions [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. Relatedly, self-determination theory highlights the competence and relatedness gratifications delivered by gaming, which can render attitude-consistent intention formation especially potent for those with lower self-esteem [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e]. Second, sociometer theory conceptualizes self-esteem as an index of perceived relational value; low self-esteem heightens vigilance to approval and rejection cues and thereby strengthens conformity to social expectations [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. In socially embedded gaming contexts (teams, guilds, peer chat), this implies a stronger translation of subjective norms into intentions among low-self-esteem individuals, consistent with evidence that lower self-esteem is associated with greater susceptibility to interpersonal influence [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. Third, because self-esteem covaries with generalized efficacy beliefs [\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e], individuals with high-self-esteem rely less on domain-specific control appraisals when forming intentions, whereas low-self-esteem individuals depend more on perceived controllability to offset anticipated failure. Thus, it is postulated that self-esteem attenuates the three TPB paths to intention\\u0026mdash;lower self-esteem strengthens the relationships between three antecedents and the intention, whereas higher self-esteem weakens them. Adopting self-esteem into the TPB-based model enhances its explanatory power with explaining the role of individual differences in online game behavior.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eResearch Design and Hypotheses\\u003c/h2\\u003e \\u003cp\\u003eAs described, three anteceding components in TPB \\u0026ndash; attitudes toward the online game, subjective norms, and perceived behavioral control \\u0026ndash; are predicted to affect the intention to play online games. Though existing literatures [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] support the TPB model to predict gaming behavior, the current study focuses on verifying the causal relationship model by dividing gaming behavior into excessive and problematic use of online games. More importantly, the moderating role of self-esteem is posited and examined in the model. As noted earlier, the resolution to manage problematic gaming behavior should be applied differently depending on the user\\u0026rsquo;s characteristics, and the study focuses self-esteem. Accordingly, following hypotheses are investigated and it is depicted as Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003eH1: Attitude toward the online game is positively associated with the intention to play online games\\u003c/p\\u003e \\u003cp\\u003eH2: Subjective norm is positively associated with the intention to play online games\\u003c/p\\u003e \\u003cp\\u003eH3: Perceived behavioral control is positively associated with the intention to play online games and the excessive use of online games.\\u003c/p\\u003e \\u003cp\\u003eH4: Perceived behavioral control is positively associated with the excessive use of online games.\\u003c/p\\u003e \\u003cp\\u003eH5: Intention to play online games is positively associated with the excessive use of online games.\\u003c/p\\u003e \\u003cp\\u003eH6: Excessive use of online games is positively associated with the problematic use of online games.\\u003c/p\\u003e \\u003cp\\u003eH7 (Moderation): Self-esteem negatively moderates the relationship between attitude and intention, such that the positive association is stronger among individuals with lower self-esteem (and weaker among those with higher self-esteem).\\u003c/p\\u003e \\u003cp\\u003eH8 (Moderation): Self-esteem negatively moderates the relationship between subjective norm and intention, such that the positive association is stronger among individuals with lower self-esteem.\\u003c/p\\u003e \\u003cp\\u003eH9 (Moderation): Self-esteem negatively moderates the relationship between perceived behavioral control and intention, such that the positive association is stronger among individuals with lower self-esteem.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eParticipants and Procedure\\u003c/h3\\u003e\\n\\u003cp\\u003eThis study was conducted with undergraduate students enrolled at a university located in Seoul, South Korea. The recruitment targeted students who had experience of playing online games at least once. Participants were recruited by posting an invitation notice on the university\\u0026rsquo;s online community and bulletin boards. The notice included information about the study\\u0026rsquo;s purpose, participation procedure, privacy protection policy, and the voluntary nature of participation, as well as the right to withdraw at any time. Students who expressed interest in participating were provided with a URL link to the online survey. Upon completion of the survey, each participant received a coffee coupon for appreciation.\\u003c/p\\u003e \\u003cp\\u003ePrior to participation, all respondents were provided with detailed information about the study\\u0026rsquo;s purposes, the securement of sensitive information, and the voluntary nature of their responses. Informed consent was obtained electronically. A total of 339 responses were collected, of which 36 were excluded due to careless responding or reporting no experience with online game use. Finally, 303 responses were included for analysis.\\u003c/p\\u003e \\u003cp\\u003eThe demographic characteristics of the sample were as follows: 194 males (64.0%) and 109 females (36.0%), with a mean age of 21.88 years (SD\\u0026thinsp;=\\u0026thinsp;2.66). The distribution of academic year was 23.1% freshmen, 33.3% sophomores, 18.5% juniors, and 25.1% seniors, representing a well-balanced sample across year levels and enabling a comprehensive reflection of online game use behaviors among students at different stages of their undergraduate college lives.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eMeasures\\u003c/h2\\u003e \\u003cp\\u003eKey psychological variables related to online game use were measured using validated scales from previous research. Most items were rated on a 7-point Likert scale (1\\u0026thinsp;=\\u0026thinsp;strongly disagree, 7\\u0026thinsp;=\\u0026thinsp;strongly agree). Internal reliability coefficients (Cronbach\\u0026rsquo;s α) for each measure are reported as followings. \\u0026lsquo;Attitude toward Online Game Use\\u0026rsquo; was measured with three items adapted from [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e] (e.g., \\u0026ldquo;I think playing online games is good\\u0026rdquo;). Internal consistency was excellent (Cronbach\\u0026rsquo;s α\\u0026thinsp;=\\u0026thinsp;.958). \\u0026lsquo;Subjective Norm\\u0026rsquo; was assessed using three items adapted from [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e] to reflect perceived expectations from significant others (e.g., \\u0026ldquo;Most people important to me play online games regularly\\u0026rdquo;). Their internal consistency was acceptable with Cronbach\\u0026rsquo;s α of .839. \\u0026lsquo;Perceived Behavioral Control\\u0026rsquo; was measured with two items adapted from [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e], focusing on self-efficacy related to online game use (e.g., \\u0026ldquo;I have the knowledge and ability to enjoy online games\\u0026rdquo;). Internal consistency was good (Cronbach\\u0026rsquo;s α\\u0026thinsp;=\\u0026thinsp;.886).\\u003c/p\\u003e \\u003cp\\u003eThree latent variables affected by these antecedents were measured with reliable items. Intention to Use Online Games was measured with three items evaluating plans and willingness to play games in the future (e.g., \\u0026ldquo;I will continue to play online games in the future\\u0026rdquo;), with higher level of reliability (Cronbach\\u0026rsquo;s α\\u0026thinsp;=\\u0026thinsp;.947). Excessive Game Use (EGU) was measured with three self-report items based on [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e], assessing weekly gaming frequency, average weekly gaming hours, and the proportion of leisure time spent gaming. Problematic Game Use (PGU) was assessed with five core items from the shortened version of [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]\\u0026rsquo;s Problematic Online Game Use Scale (POGUS), covering obsession, withdrawal, and loss of control. Internal consistency was satisfactory (Cronbach\\u0026rsquo;s α\\u0026thinsp;=\\u0026thinsp;.863). The moderating variable, Self-Esteem, was measured with four items adapted from [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e] (e.g., \\u0026ldquo;I feel that I have a number of good qualities\\u0026rdquo;). The internal consistency coefficient (Cronbach\\u0026rsquo;s α) for this study was .919.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStructural Equation Model (SEM) Results for the Overall Sample\\u003c/h2\\u003e \\u003cp\\u003eTo examine the proposed model, structural equation modeling (SEM) was conducted using maximum likelihood estimation. The model tested included latent variables for attitude toward online gaming (ATT), subjective norms (SUB), perceived behavioral control (PBC), intention to play online games (INT), excessive game use (EGU), and problematic game use (PGU). The overall model, as shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, demonstrated an acceptable fit to the data: χ2(142)\\u0026thinsp;=\\u0026thinsp;240.170, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001, CFI\\u0026thinsp;=\\u0026thinsp;.977, TLI\\u0026thinsp;=\\u0026thinsp;.972, RMSEA\\u0026thinsp;=\\u0026thinsp;.048, indicating good model fit according to the criteria suggested by [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe results revealed that all hypothesized paths were statistically significant. Specifically, intention to play online games was strongly predicted by subjective norms (β\\u0026thinsp;=\\u0026thinsp;.612, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001), followed by perceived behavioral control (β\\u0026thinsp;=\\u0026thinsp;.378, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001), and to a lesser extent, attitude toward online gaming (β\\u0026thinsp;=\\u0026thinsp;.124, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.05), indicating that perceived social pressure and control beliefs play a more substantial role in shaping game-related behavioral intentions than personal evaluations. Intention, in turn, emerged as a strong predictor of excessive game use (β\\u0026thinsp;=\\u0026thinsp;.709, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001), which subsequently led to problematic game use (β\\u0026thinsp;=\\u0026thinsp;.326, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001), supporting the proposed mediational sequence. In addition, perceived behavioral control also had a direct but smaller effect on excessive use (β\\u0026thinsp;=\\u0026thinsp;.104, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.05), underscoring its dual role in influencing both intention and behavior. These findings validate the sequential pathway posited by the TPB, while also highlighting the dominant role of social influences and perceived control in driving gaming intentions and behaviors.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eModerating Effect of Self-Esteem: Multi-Group SEM\\u003c/h2\\u003e \\u003cp\\u003eTo determine whether self-esteem moderated the hypothesized structural relationships, the sample was divided into high (n\\u0026thinsp;=\\u0026thinsp;145) and low (n\\u0026thinsp;=\\u0026thinsp;158) self-esteem groups based on a median split, and multi-group SEM was conducted separately for each. The model fit indices indicated that the model structure was supported in both groups, though with varying degrees of fit. For the high self-esteem group, the fit indices were χ\\u0026sup2; (142)\\u0026thinsp;=\\u0026thinsp;161.136, p\\u0026thinsp;=\\u0026thinsp;.130; CFI\\u0026thinsp;=\\u0026thinsp;.991; TLI\\u0026thinsp;=\\u0026thinsp;.989; RMSEA\\u0026thinsp;=\\u0026thinsp;.031, indicating an excellent fit based on conventional cutoff criteria [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. Although the chi-square test was non-significant (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.130), which traditionally implies that the model does not significantly deviate from the data, it should be interpreted with caution due to its well-known sensitivity to sample size [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. In small to moderate samples, a non-significant chi-square is actually desirable and supports model fit. The very high CFI and TLI values, along with a low RMSEA, affirm the robustness of the model in this group. In comparison, the low self-esteem group yielded χ\\u0026sup2;(142)\\u0026thinsp;=\\u0026thinsp;226.695, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001; CFI\\u0026thinsp;=\\u0026thinsp;.959; TLI\\u0026thinsp;=\\u0026thinsp;.951; RMSEA\\u0026thinsp;=\\u0026thinsp;.062, suggesting an acceptable but comparatively weaker fit. Together, these findings support the configural invariance of the model and confirm that the overall structure holds across levels of self-esteem, albeit more strongly for individuals with higher self-regard.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eStructural Path Estimates in two groups of Self-Esteem\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePath\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSelf-Esteem\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eEstimate (β)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eC.R.\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep-value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eATT \\u0026rarr; INT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHigh\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.147\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.277\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.023\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eATT \\u0026rarr; INT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLow\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.053\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.843\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.400\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSUB \\u0026rarr; INT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHigh\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.444\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.276\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSUB \\u0026rarr; INT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLow\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.796\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e7.785\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePBC \\u0026rarr; INT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHigh\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.545\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.503\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePBC \\u0026rarr; INT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLow\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.261\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.982\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.003\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePBC \\u0026rarr; EGU\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHigh\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.130\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.717\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.086\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePBC \\u0026rarr; EGU\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLow\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.157\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.206\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.027\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eINT \\u0026rarr; EGU\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHigh\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.811\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9.056\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eINT \\u0026rarr; EGU\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLow\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.621\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e7.764\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEGU\\u0026rarr;PGU\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHigh\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.291\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.564\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEGU\\u0026rarr;PGU\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLow\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.415\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.114\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe comparative results of the structural paths between the high and low self-esteem groups revealed meaningful divergence in the psychosocial mechanisms leading to excessive and problematic gaming as shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. Notably, the effect of attitude on behavioral intention (ATT \\u0026rarr; INT) was statistically significant only in the high self-esteem group (β\\u0026thinsp;=\\u0026thinsp;.147, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.05), while it was nonsignificant in the low self-esteem group (β\\u0026thinsp;=\\u0026thinsp;.053, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.400), indicating that individuals with higher self-esteem are more likely to form intentions based on their personal evaluations of gaming. In contrast, subjective norm (SUB \\u0026rarr; INT) exerted a much stronger influence in the low self-esteem group (β\\u0026thinsp;=\\u0026thinsp;.796, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001) compared to the high self-esteem group (β\\u0026thinsp;=\\u0026thinsp;.444, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001), suggesting that individuals with lower self-worth are more susceptible to social pressures and normative expectations when forming gaming intentions. Although perceived behavioral control (PBC \\u0026rarr; INT) significantly predicted intention in both groups, the effect was more pronounced in the high self-esteem group (β\\u0026thinsp;=\\u0026thinsp;.545) than in the low self-esteem group (β\\u0026thinsp;=\\u0026thinsp;.261), hinting that perceived control may be more internalized among those with higher self-esteem. Importantly, the core mediational pathways\\u0026mdash;intention predicting excessive use (INT \\u0026rarr; EGU) and excessive use predicting problematic use (EGU \\u0026rarr; PGU)\\u0026mdash;remained robust and statistically significant across both groups, confirming that the motivational sequence outlined by TPB holds consistently, regardless of individual differences in self-esteem.\\u003c/p\\u003e \\u003cp\\u003eTo test the moderation effect more rigorously, a series of nested model comparisons were conducted by constraining each structural path to be equal across groups and examining the changes in chi-square [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. A significant change in chi-square (Δχ\\u0026sup2;) indicates that the effect of a particular path differs significantly between groups, confirming a moderation effect.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eDifferences between the path coefficients across the two groups\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePath\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSelf-Esteem Group\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eSelf-Esteem Group\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eΔχ\\u0026sup2;(df)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep-value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePath\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHigh (β)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eLow (β)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eΔχ\\u0026sup2;(df)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep-value\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eATT \\u0026rarr; INT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e.147\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e.053\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.026\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSUB \\u0026rarr; INT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e.444\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e.796\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.88\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.009\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePBC \\u0026rarr; INT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e.545\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e.261\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.077\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePBC \\u0026rarr; EGU\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e.130\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e.157\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.55\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.458\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eINT \\u0026rarr; EGU\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e.811\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e.621\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.308\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEGU\\u0026rarr;PGU\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e.291\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e.415\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.88\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e.348\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eΔχ\\u0026sup2;=Chi-square difference between unconstrained and constrained path models (df\\u0026thinsp;=\\u0026thinsp;1).\\u003c/p\\u003e \\u003cp\\u003eThe results as shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e reveals that the path from attitude to intention (ATT \\u0026rarr; INT) significantly differed between groups, Δχ\\u0026sup2;(1)\\u0026thinsp;=\\u0026thinsp;4.97 (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.05), indicating that individuals with high self-esteem were more likely to act based on their attitudinal evaluations compared to their low self-esteem counterparts. Similarly, the path from subjective norm to intention (SUB \\u0026rarr; INT) also exhibited a significant difference, Δχ\\u0026sup2; (1)\\u0026thinsp;=\\u0026thinsp;6.88 (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.01) suggesting that perceived social pressure plays a disproportionately stronger role for those with lower self-esteem. Although the difference in perceived behavioral control to intention (PBC \\u0026rarr; INT) did not reach conventional levels of statistical significance (Δχ\\u0026sup2;(1)\\u0026thinsp;=\\u0026thinsp;3.12, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.077), it was marginally significant and suggests a trend toward stronger internal control dynamics among individuals with higher self-regard. For the remaining paths (PBC \\u0026rarr; EGU, INT \\u0026rarr; EGU, and EGU \\u0026rarr; PGU) none showed statistically significant differences between groups (all \\u003cem\\u003ep\\u003c/em\\u003e values\\u0026thinsp;\\u0026gt;\\u0026thinsp;.30), indicating that these behavioral progression pathways operate similarly regardless of self-esteem level. This suggests that once gaming intentions are formed, the subsequent translation into excessive use and the escalation from excessive to problematic use are largely invariant across self-esteem profiles. In other words, while self-esteem shapes the formation of gaming intentions through differential reliance on internal attitudes and external norms, it does not substantially alter the behavioral enactment of those intentions into excessive or problematic gaming behaviors. These results underscore the robustness of the TPB\\u0026rsquo;s core mediational sequence across individual differences in self-esteem, aligning with prior evidence that post-intentional behavioral processes tend to be more universal [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThe current study, grounded in TPB (Theory of Planned Behavior), distinguishes online gaming behavior into excessive game use (EGU) and problematic game use (PGU) and examines the moderating role of self-esteem. Structural equation modeling (SEM) analysis revealed that attitude, subjective norm, and perceived behavioral control (PBC) significantly influenced behavioral intention, which in turn significantly predicted excessive use and problematic use. Among the predictors, subjective norm had the strongest effect on behavioral intention (β\\u0026thinsp;=\\u0026thinsp;.612, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001), suggesting that peer and social environmental influences are key determinants of gaming behavior. Furthermore, PBC showed direct effects not only on behavioral intention but also on excessive use (double paths), underscoring the importance of control beliefs in actual behavior. These findings provide empirical support for the notion that problematic use can be intensified as an extension of intentional use. By distinguishing the behavioral stages into excessive and problematic use, the study offers a refined explanation of the developmental trajectory of gaming behavior.\\u003c/p\\u003e \\u003cp\\u003eBy integrating self-esteem into the TPB framework, this study empirically identifies how the same causal structure varies by levels of individuals\\u0026rsquo; self-esteem. The moderating effect of self-esteem offers important insights into the personal context of online gaming behavior. As shown in the result, the hypothetical model proposed (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e) was strongly supported in individuals with lower self-esteem; however, the model was less significant to predict the game behavior of individuals with higher self-esteem, in terms of chi-square measure. Nevertheless, the model for each segment showed strong goodness of fit with significant path coefficients in most paths. It is important which path is more critical in each group. For individuals with high self-esteem, attitudes played a central role in shaping intention, consistent with the tendency of autonomous individuals to rely on internal value judgments as behavioral guidelines [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. However, individuals with low self-esteem were more sensitive to social norms, aligning with prior findings that they are more vulnerable to external pressures in digital environments [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe study further demonstrates that the dual pathways of gaming behavior can vary depending on self-esteem level with relating these findings to the dual-process perspective [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e]. The intentional (cognitive) pathway, through a central route, involves the deliberative planning and execution of behavior based on personal attitudes, beliefs, and social norms, whereas the habitual (automatic) pathway, through a peripheral route, reflects unconscious behaviors shaped by repeated experiences and environmental cues. Individuals with higher self-esteem primarily formed gaming behaviors through the intentional\\u0026ndash;cognitive path, while lower self-esteem individuals relied more heavily on the habitual\\u0026ndash;social influence path. This provides a theoretical framework for explaining how psychological traits lead to different behavioral mechanisms under the same environment for playing games.\\u003c/p\\u003e \\u003cp\\u003eSome academic contributions of this study are yielded as follows. First, by incorporating self-esteem as a moderating variable into an extended TPB model, it enhances the predictive power of gaming behavior research. Second, by differentiating between excessive and problematic use, it offers a useful framework for explaining behavioral progression in future studies. Third, by identifying differences in behavioral pathways between high and low self-esteem groups, it theoretically supports the need for personalized treatment.\\u003c/p\\u003e \\u003cp\\u003eFrom a practical perspective, the findings suggest two key implications. First, tailored prevention and intervention strategies are needed. For the low self-esteem group, strategies leveraging peer influence and social norms and providing positive social feedback would be more effective [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]. For the high self-esteem segment, value- and goal-oriented strategies that stimulate autonomy and intrinsic motivation are more appropriate [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e]. Second, education on preventing of gaming overuse is essential. Recent studies [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e] suggest that programs designed to strengthen PBC through self-regulation training and time management can effectively enhance long-term control over gaming behavior. Such approaches can also inform personalized gaming use guidelines based on self-esteem assessments, implemented in university counseling centers or health institutions.\\u003c/p\\u003e \\u003cp\\u003eFuture research should employ longitudinal designs to trace and analyze the causal relationship between gaming behavior and self-esteem over time. Additionally, examining differences in TPB pathways and self-esteem\\u0026rsquo;s moderating effects across cultural contexts (individualism vs. collectivism) would enhance the generalizability of the findings to various groups globally and aid in developing culturally tailored intervention strategies.\\u003c/p\\u003e \\u003cp\\u003eIn sum, this study affirms the validity of TPB in explaining online gaming behavior while increasing the precision of its predictive model through the integration of self-esteem as a key individual difference variable. These findings contribute theoretically to the extension of digital behavior research and practically to the design of customized interventions based on self-esteem levels.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study protocol was submitted to and approved \\u003cstrong\\u003e\\u003cu\\u003eby The Institutional Review Board of Chung-Ang University \\u003c/u\\u003e\\u003c/strong\\u003e(IRB approval no.: 1041078-201804-HRSB-081-01). All procedures performed in this study were conducted in accordance with the ethical standards for research involving human participants. Participation was voluntary, and informed consent was obtained electronically from all respondents prior to data collection. The study involved minimal risk, and confidentiality and anonymity were ensured throughout.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable. All data were collected anonymously, and no identifying information is included in the manuscript and the original data.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe datasets generated and analyzed during the present study are publicly available in the \\u003cem\\u003eFigshare\\u003c/em\\u003e repository at the following DOI: https://doi.org/10.6084/m9.figshare.30018790.v1.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that they have no competing interests, financial or otherwise, related to this research.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research received no external funding.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026rsquo; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll authors contributed to the study\\u0026rsquo;s conception, design, analysis, and manuscript preparation. The first author led the study design, data collection, and initial manuscript drafting. The second author contributed to data analysis, interpretation, and manuscript revision. All authors reviewed and approved the final manuscript.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors thank the participants for their time and cooperation. The authors also express appreciation to colleagues who provided helpful feedback during the development of the study.\\u003c/p\\u003e\\n\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eKim MG, Kim J. Cross-validation of reliability, convergent and discriminant validity for the problematic online game use scale. Comput Hum Behav. 2010;26(3):389\\u0026ndash;98.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWorld Health Organization. WHO Director-General\\u0026rsquo;s opening remarks at the media briefing on COVID-19. 2020 Mar 11. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020\\u003c/span\\u003e\\u003cspan address=\\\"https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (accessed 10 Dec 2025).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFlayelle M, Schimmenti A, Starcevic V, Billieux J. The landscape of problematic gaming: A systematic review. Cyberpsychology Behav Social Netw. 2023;26(1):3\\u0026ndash;17.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAmerican Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Washington (DC): American Psychiatric Association; 2013.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNogueira-L\\u0026oacute;pez A, S\\u0026aacute;nchez-Iglesias I, L\\u0026oacute;pez-Fern\\u0026aacute;ndez O, Pontes HM. Problematic video game use: The role of self-esteem and psychological distress. Cyberpsychology Behav Social Netw. 2023;26(5):315\\u0026ndash;21.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGioia F, Rega V, Boursier V, Cyberpsychology. Behav Social Netw. 2022;25(9):565\\u0026ndash;72.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRozgonjuk D, Sindermann C, Elhai JD, Montag C. Problematic social media use and gaming disorder: Associations with psychological and social well-being. Cyberpsychology Behav Social Netw. 2021;24(8):531\\u0026ndash;7.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAjzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179\\u0026ndash;211.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSelfhout MHW, Branje SJT, Delsing M, ter Bogt TFM, Meeus WHJ. Different types of Internet use, depression, and social anxiety: The role of perceived friendship quality in adolescents. J Adolesc. 2009;32(5):813\\u0026ndash;29.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMcKay MT, Percy A, Cole JC. Self-esteem and self-efficacy: The influence of social media use on adolescents. Comput Hum Behav. 2018;81:83\\u0026ndash;90.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKim B, Kang HS, Park J. A latent profile approach for classifying internet gamers based on motives for online gaming. J Behav Addictions. 2023;12(1):148\\u0026ndash;58.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYousafzai SY, Sherin A. COVID-19 and internet gaming disorder in children and adolescents. J Pak Med Assoc. 2020;70(Suppl 3):S128\\u0026ndash;30.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMaroney N, Williams BJ, Thomas A, Skues J, Moulding R. A stress-coping model of problem online video game use. Int J Mental Health Addict. 2019;17(4):845\\u0026ndash;58.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDi Blasi M, Giardina A, Giordano C, Coco GL, Tosto C, Billieux J, Schimmenti A. Problematic video game use as an emotional coping strategy: Evidence from a sample of MMORPG gamers. J Behav Addictions. 2019;8(1):25\\u0026ndash;34.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHaagsma MC, Caplan SE, Peters O, Pieterse ME. A cognitive-behavioral model of problematic online gaming: The role of cognitive coping and self-regulation. Comput Hum Behav. 2013;28(1):13\\u0026ndash;20.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFestl R, Scharkow M, Quandt T. Problematic computer game use among adolescents, younger and older adults. Addiction. 2013;108(3):592\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBillieux J, Deleuze J, Griffiths MD, Kuss DJ. Internet gaming addiction: The case of massively multiplayer online role-playing games. J Behav Addictions. 2015;4(3):205\\u0026ndash;12.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYue H, Li C, Liu M, Jin R, Bao H. Validity test of the theory of planned behavior in college students\\u0026rsquo; withdrawal from smartphone dependence. Curr Psychol. 2022;41(8):5524\\u0026ndash;31.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLaRose R, Lin CA, Eastin MS. Unregulated internet usage: Addiction, habit, or deficient self-regulation? Media Psychol. 2003;5(3):225\\u0026ndash;53.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee MC. Understanding the behavioral intention to play online games: An extension of the theory of planned behavior. Online Inf Rev. 2009;33(5):849\\u0026ndash;72.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAlzahrani AI, Mahmud I, Ramayah T, Alfarraj O, Alalwan N. Extending the theory of planned behavior (TPB) to explain online game playing among Malaysian undergraduate students. Telematics Inform. 2017;34(4):239\\u0026ndash;51.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRivis A, Sheeran P. Descriptive norms as an additional predictor in the theory of planned behavior. Curr Psychol. 2003;22(3):218\\u0026ndash;33.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWeiss T, L\\u0026ouml;bbecke C. Online gaming adoption at the stage of maturity: A study of social and technical influences. Int J Inf Manag. 2008;28(3):217\\u0026ndash;32.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee MC, Tsai TR. What drives people to continue to play online games? An extension of technology model and theory of planned behavior. Int J Human\\u0026ndash;Computer Interact. 2010;26(6):601\\u0026ndash;20.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAjzen I. Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. J Appl Soc Psychol. 2002;32(4):665\\u0026ndash;83.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKavanagh M, Brett C, Brignell C. What is the reported relationship between self-esteem and gaming disorder? A systematic review and meta-analysis. Comput Hum Behav. 2023;145:10776. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.chb.2023.10776\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.chb.2023.10776\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSivanathan N, Pettit NC. Protecting the self through consumption: Status goods as affirmational commodities. J Exp Soc Psychol. 2010;46(3):564\\u0026ndash;70.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSteele CM. The psychology of self-affirmation: Sustaining the integrity of the self. Adv Exp Soc Psychol. 1988;21:261\\u0026ndash;302.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDeci EL, Ryan RM. The what and why of goal pursuits: Human needs and the self-determination of behavior. Psychol Inq. 2000;11(4):227\\u0026ndash;68.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRyan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55(1):68\\u0026ndash;78.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLeary MR, Baumeister RF. The nature and function of self-esteem: Sociometer theory. Adv Exp Soc Psychol. 2000;32:1\\u0026ndash;62.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBearden WO, Netemeyer RG, Teel JE. Measurement of consumer susceptibility to interpersonal influence. J Consum Res. 1989;15(4):473\\u0026ndash;81.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJudge TA, Erez A, Bono JE, Thoresen CJ. Are measures of self-esteem, neuroticism, locus of control, and generalized self-efficacy indicators of a common core construct? J Personal Soc Psychol. 2002;83(3):693\\u0026ndash;710.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAjzen I. Constructing a TPB questionnaire: Conceptual and methodological considerations. 2002. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://people.umass.edu/aizen/tpb.html\\u003c/span\\u003e\\u003cspan address=\\\"https://people.umass.edu/aizen/tpb.html\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e (accessed 10 Dec 2025).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCooke R, Sniehotta F, Sch\\u0026uuml;z B. Predicting binge-drinking behavior using an extended TPB: Examining the impact of anticipated regret and descriptive norms. Alcohol Alcohol. 2007;42(2):84\\u0026ndash;91.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHo SS, Lwin MO, Lee EW. Till logout do us part? Comparison of factors predicting excessive social network sites use and addiction between Singaporean adolescents and adults. Comput Hum Behav. 2017;75:632\\u0026ndash;42.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLukavsk\\u0026aacute; K, Hrabec O, Chrz V. The role of habits in massive multiplayer online role-playing game usage: Predicting excessive and problematic gaming through players' sensitivity to situational cues. Cyberpsychology, Behavior, and Social Networking. 2016;19(4):277\\u0026ndash;282.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLu Y, Zhou T, Wang B. Exploring Chinese users\\u0026rsquo; acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Comput Hum Behav. 2009;25(1):29\\u0026ndash;39.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equation Modeling: Multidisciplinary J. 1999;6(1):1\\u0026ndash;55.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKline RB. Principles and practice of structural equation modeling. 4th ed. New York (NY): Guilford; 2023.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eByrne BM. Structural equation modeling with Mplus: Basic concepts, applications, and programming. New York (NY): Routledge; 2012.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKernis MH. Toward a conceptualization of optimal self-esteem. Psychol Inq. 2003;14(1):1\\u0026ndash;26.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKang S. Social influence on internet game addiction in adolescents. Korean J Youth Stud. 2010;17(7):45\\u0026ndash;68.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePetty RE, Cacioppo JT, Schumann D. Central and peripheral routes to advertising effectiveness: The moderating role of involvement. J Consum Res. 1983;10(2):135\\u0026ndash;46.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKim HK, Davis KE. Toward a comprehensive theory of problematic Internet use: Evaluating the role of self-esteem, anxiety, flow, and the self-rated importance of Internet activities. Comput Hum Behav. 2009;25(2):490\\u0026ndash;500.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-psychology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"psyo\",\"sideBox\":\"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"BMC Psychology\",\"twitterHandle\":\"BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Theory of Planned Behavior, Online Gaming, Excessive Game Use, Problematic Game Use, Self-Esteem\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-8331619/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-8331619/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eOnline gaming has become a pervasive leisure activity among young adults, further intensified by the COVID-19 pandemic. While problematic game use (PGU) has been extensively examined in adolescents, it is rarely known about its determinants among college students experiencing greater autonomy and social pressure. Guided by the Theory of Planned Behavior (TPB), this study investigates how attitudes, subjective norms, and perceived behavioral control (PBC) shape gaming intention and how this intention sequentially predicts excessive game use (EGU) and PGU. The study further examines self-esteem as a moderator that may alter the cognitive and social mechanisms underlying intention formation.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eA sample of 303 Korean undergraduates with online gaming experience participated in the survey with validated measures of TPB constructs, intention, EGU, PGU, and self-esteem. Structural equation modeling (SEM) tested the hypothesized pathways, including sequential mediation from intention \\u0026rarr; EGU \\u0026rarr; PGU. Multi-group SEM was used to examine moderation by self-esteem.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eThe overall SEM demonstrated good fit. Subjective norm (β\\u0026thinsp;=\\u0026thinsp;.612), PBC (β\\u0026thinsp;=\\u0026thinsp;.378), and attitude (β\\u0026thinsp;=\\u0026thinsp;.124) significantly predicted intention. Intention strongly predicted EGU (β\\u0026thinsp;=\\u0026thinsp;.709), which subsequently predicted PGU (β\\u0026thinsp;=\\u0026thinsp;.326). PBC also directly influenced EGU (β\\u0026thinsp;=\\u0026thinsp;.104). Multi-group analyses revealed distinct mechanisms by self-esteem: attitudes predicted intention only among high self-esteem students, whereas subjective norms had a substantially stronger effect among low self-esteem students. Differences in ATT \\u0026rarr; INT (Δχ\\u0026sup2; = 4.97, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.05) and SUB \\u0026rarr; INT (Δχ\\u0026sup2; = 6.88, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.01) were significant.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eThe findings validate TPB in predicting gaming behavior and clarify the progression from intention to excessive and problematic use. Self-esteem shapes the cognitive and social antecedents of intention, highlighting the need for tailored interventions: autonomy- and value-based strategies for high self-esteem individuals, and norm- or peer-based approaches for low self-esteem individuals.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Attitudes or Norms? 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