Relationship Between Personality Traits and Social Avoidance with Internet Gaming Disorder Severity

Relationship Between Personality Traits and Social Avoidance with Internet Gaming Disorder Severity | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 26 September 2025 V1 Latest version Share on Relationship Between Personality Traits and Social Avoidance with Internet Gaming Disorder Severity Authors : Yan Mei Nie 0009-0002-9094-5747 [email protected] and Mark Hilsenroth Authors Info & Affiliations https://doi.org/10.22541/au.175887371.15901106/v1 Published Clinical Psychology & Psychotherapy Version of record Peer review timeline 773 views 433 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract With gaming’s increasing prevalence, particularly during COVID-19, understanding the psychological functioning of individuals with Internet Gaming Disorder (IGD) is crucial. This study replicates and extends Bonnaire and Baptista’s (2019) research on DSM-5 IGD in European young adults, examining alexithymia, anxiety, personality, and interpersonal problems in a U.S. sample. A diverse group of 205 young adults (Mean Age = 20.41, 73% female) completed an anonymous survey assessing IGD using the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF; Pontes & Griffiths, 2015), gaming type, alexithymia, anxiety, personality, and interpersonal issues. IGDS9-SF effectively distinguished Normal Gamers (IGD criteria=0) from Risky Gamers (IGD criteria=1–6), with the latter showing significantly greater pathology across all measures (p<.01). IGD severity correlated with alexithymia (r=0.279, p<0.001), anxiety (r=0.208, p<0.005), disinhibited personality traits (r=0.363, p<0.001), and socially avoidant interpersonal problems (r=0.305, p<0.001). IGD symptoms were associated with difficulties in emotional processing (r=0.267, p<0.001). While gaming type showed no significant differences, Role-Playing gamers trended toward more interpersonal problems (p=0.059). Findings underscore IGD’s connections to emotional, personality, and interpersonal factors, informing clinical assessment and treatment. Abstract With gaming’s increasing prevalence, particularly during COVID-19, understanding the psychological functioning of individuals with Internet Gaming Disorder (IGD) is crucial. This study replicates and extends Bonnaire and Baptista’s (2019) research on DSM-5 IGD in European young adults, examining alexithymia, anxiety, personality, and interpersonal problems in a U.S. sample. A diverse group of 205 young adults (Mean Age = 20.41, 73% female) completed an anonymous survey assessing IGD using the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF; Pontes & Griffiths, 2015), gaming type, alexithymia, anxiety, personality, and interpersonal issues. IGDS9-SF effectively distinguished Normal Gamers (IGD criteria=0) from Risky Gamers (IGD criteria=1–6), with the latter showing significantly greater pathology across all measures (p<.01). IGD severity correlated with alexithymia (r=0.279, p<0.001), anxiety (r=0.208, p<0.005), disinhibited personality traits (r=0.363, p<0.001), and socially avoidant interpersonal problems (r=0.305, p<0.001). IGD symptoms were associated with difficulties in emotional processing (r=0.267, p<0.001). While gaming type showed no significant differences, Role-Playing gamers trended toward more interpersonal problems (p=0.059). Findings underscore IGD’s connections to emotional, personality, and interpersonal factors, informing clinical assessment and treatment. Keywords: Internet Gaming Disorder, personality traits, interpersonal problems, anxiety, alexithymia Relationship Between Personality Traits and Social Avoidance with Internet Gaming Disorder Severity Video games have become one of the most widely consumed forms of entertainment globally, surpassing both film and music industries in revenue and cultural reach (Weinstein & Lejoyeux, 2011). While for most individuals gaming is a normative recreational activity, for some it can escalate into problematic patterns characterized by loss of control, persistence despite negative consequences, and functional impairment, collectively referred to as Internet Gaming Disorder (IGD). In recognition of these clinical concerns, the DSM-5 included IGD in Section III as a condition warranting further study (American Psychiatric Association, 2013), and the World Health Organization formally classified “Gaming Disorder” in the ICD-11 as an addictive behavior disorder (Saunders et al., 2017; Vaccaro & Potenza, 2019). Despite ongoing debates about pathologizing a popular leisure activity, evidence increasingly suggests that IGD shares neurobiological, cognitive, and clinical features with substance use and gambling disorders (Fauth-Bühler & Mann, 2017; Chiappini et al., 2025). Prevalence estimates vary considerably across countries and methodologies, ranging from approximately 1% to over 10%, reflecting differences in measurement and cultural gaming norms (Borges et al., 2020; Müller et al., 2014). While most prevalence studies of IGD have relied on non-clinical or convenience samples of adolescents and young adults, research in clinical settings is more limited. For instance, Rotunda et al. (2025) examined intake records of 2,280 treatment-seeking university students and found that 6.45% endorsed problematic internet or computer use, with preoccupation with surfing, and social messaging as the leading concerns. Although gaming represented a smaller proportion of presenting problems in this clinical sample, nearly 9% of those endorsing internet-related difficulties reported it as a primary reason for seeking help. These findings underscore that problematic technology use, including IGD, is not confined to community or survey-based samples but emerges in real-world clinical contexts with college students, highlighting the importance of systematic assessment in counseling and mental health services. Emerging research has sought to identify the risk factors and individual vulnerabilities associated with IGD. Among these, personality traits stand out as robust predictors. Studies consistently demonstrate that higher neuroticism and lower conscientiousness are associated with greater risk of IGD, while extraversion shows mixed associations (Andreassen et al., 2013; Bonnaire & Baptista, 2019; Müller et al., 2014). These traits overlap with vulnerabilities observed in other behavioral addictions, suggesting a transdiagnostic pathway characterized by impulsivity, emotion dysregulation, and poor self-control (Darvesh et al., 2020; Ghiaccio et al., 2025). Developmental research highlights adolescence as a particularly sensitive period, given heightened sensation seeking combined with still-maturing impulse control (Harden & Tucker-Drob, 2011; Yoneda et al., 2019). Such developmental trajectories may amplify the likelihood that youth turn to gaming as an emotionally gratifying yet potentially maladaptive coping strategy. Social and interpersonal factors also play a critical role in the onset and maintenance of IGD. Individuals with insecure attachment styles, social skill deficits, or difficulties in emotion regulation are more likely to engage in excessive gaming as a means of escaping interpersonal stressors (Estévez et al., 2017; Park et al., 2017). Social avoidance in particular has been linked to problematic gaming, as online environments may provide alternative contexts for achievement, affiliation, or identity expression that are perceived as safer or less threatening than face-to-face interactions (Király et al., 2014; Kuss, 2018). However, reliance on gaming as a substitute for real-world social interaction can reinforce withdrawal, exacerbating cycles of avoidance and contributing to poorer psychosocial outcomes over time (Chiang et al., 2022). Longitudinal findings further support that IGD symptoms prospectively predict increases in depression, anxiety, and academic decline, underscoring the functional consequences of this maladaptive trajectory (Lemmens et al., 2015; Chang et al., 2023). At a neurobiological level, individuals with IGD exhibit alterations in reward processing, executive control, and cue reactivity, paralleling findings in substance-related and gambling disorders (Fauth-Bühler & Mann, 2017; Vaccaro & Potenza, 2019). These vulnerabilities may interact with personality traits, such that individuals high in neuroticism or impulsivity are more sensitive to gaming-related cues and less able to regulate urges (Kim, 2022; Ghiaccio et al., 2025). Moreover, social avoidance may function as both a consequence and a maintaining factor of IGD, as avoidance behaviors limit opportunities for corrective social experiences while reinforcing reliance on virtual spaces for gratification. This suggests that personality traits and social avoidance may jointly contribute to the severity of IGD through a combination of affective vulnerability and behavioral reinforcement. Given these converging lines of evidence, examining the interplay between personality traits, social avoidance, and IGD severity is crucial for clarifying mechanisms of risk and informing intervention. By situating IGD within a multidimensional framework, encompassing personality dispositions, interpersonal functioning, and neurobiological vulnerabilities, the present study aims to advance understanding of how individual differences shape susceptibility to problematic gaming. This knowledge may facilitate the development of targeted prevention and treatment approaches, particularly for adolescents and young adults navigating developmental periods of heightened vulnerability. In considering IGD, it is also important to recognize the variability across gaming genres, as different types of games may foster distinct psychological experiences. Role-playing games (RPGs; e.g., Pokémon, World of Warcraft, Maplestory), for example, are often highly immersive, requiring players to adopt alternate identities, engage in long-term quests, and navigate complex social interactions within virtual worlds. These features may heighten the appeal of RPGs for individuals with social avoidance or interpersonal difficulties, who may find structured online relationships less demanding than in-person exchanges. In contrast, Action games (e.g., Call of Duty, Pacman, Counterstrike) emphasize fast-paced reflexes, competition, and short-term rewards, potentially attracting individuals who score high on impulsivity and sensation-seeking traits. Adventure games (e.g., The Legend of Zelda, Elden Ring, Nancy Drew) typically involve narrative-driven exploration and puzzle solving, offering opportunities for escapism and emotional engagement with storylines. Finally, simulation/strategy games (e.g., Starcraft, The Sims, League of Legends) center on planning, resource management, or the replication of real-world activities (e.g., engineering, sports management), which may appeal to individuals who value control and structure. This variability across game types provides theoretical justification for examining whether specific genres are differentially associated with psychological vulnerabilities in IGD, as suggested by prior work noting mixed findings regarding genre-based risk factors (Bonnaire & Baptista, 2019). Purpose of the Present Study Building on previous research, this study aims to provide a unique and distinctive addition to the literature on exploring whether emotional functioning, personality traits, and interpersonal problems predict IGD severity in U.S. young adults. While the present study seeks to replicate the central findings from Bonnaire and Baptista (2019) as well as Lemmens et al. (2015), it meaningfully extends this work by (a) examining a culturally diverse U.S. young adult sample, (b) incorporating maladaptive trait dimensions from the DSM-5 alternative model of personality (PID-5), and (c) assessing interpersonal problems using a circumplex-based measure (IIP-SC). A common limitation in prior IGD research has been the lack of gender diversity, with samples often heavily male (e.g., Pontes et al., 2014, 85% male; Bonnaire & Baptista, 2019, 71% male). The present study, however, recruited 205 U.S. young adults, with 73% identifying as female. This diverse gender distribution broadens the generalizability of findings and addresses an important gap in the literature. By integrating personality, emotional functioning, and interpersonal domains into a single predictive model, the current study advances assessment perspectives on IGD, highlighting which dimensions contribute uniquely to IGD severity. Prior work has focused largely on European populations (e.g., Bonnaire & Baptista, 2019); the generalizability of these findings to more culturally diverse groups remain uncertain. The U.S. represents one of the largest gaming markets worldwide, with a young adult population that is ethnically heterogeneous and embedded in a different educational, social, and healthcare context. Replication and extension of prior findings in this context is therefore not aimed at demonstrating national differences per se, but rather at testing whether previously observed associations between IGD, emotional functioning, and personality features hold across cultural settings. Establishing such cross-cultural consistency is essential for informing both the DSM-5 framework for IGD and for ensuring that commonly used assessment tools (e.g., PID-5, IIP-SC) are valid and clinically informative in diverse U.S. populations. Using tools such as the IGDS9-SF (Pontes & Griffiths, 2015), measures of alexithymia and anxiety, the research provides an approximate replication of earlier findings to extend our understanding of how emotional and interpersonal challenges influence IGD severity. Bonnaire and Baptista (2019) highlighted the importance of psychological factors like alexithymia, depression, and anxiety in predicting IGD, while Lemmens et al. (2015) identified personality traits, particularly disinhibition, as key contributors to compulsive gaming behaviors. Building on these foundational studies, the present research will assess the associations of these emotional and personality factors on IGD within a diverse U.S. population. Additionally, the study examines how gaming preferences (e.g., action, role-playing) may relate with the emotional and interpersonal challenges associated with IGD, addressing an area with noted variability in previous studies. The ultimate aim is to provide insights that can inform clinical interventions and enhance our ability to identify individuals at risk for IGD by integrating a multidisciplinary approach to personality and psychological factors. This study examines several psychological and interpersonal issues associated with Internet Gaming Disorder (IGD) to provide a comprehensive understanding of its severity and association. A primary focus is on emotional regulation and difficulties with identifying and processing emotions, particularly through the lens of alexithymia and anxiety. Alexithymia, often linked to IGD, involves challenges in recognizing and articulating one’s emotions, which can lead to maladaptive coping behaviors, including excessive gaming (Preece et al., 2018). Similarly, anxiety is assessed to determine how heightened anxiety levels may exacerbate compulsive gaming behaviors, contributing to IGD. These emotional factors are critical, as previous studies, including Bonnaire and Baptista (2019), have highlighted the role of emotional dysregulation with IGD severity. In addition to emotional factors, this study explores personality traits that may predispose individuals to IGD, with a particular focus on disinhibition (a tendency towards impulsivity and difficulty in self-control) (Lemmens et al., 2015). Disinhibition is associated with problematic behaviors in various domains and has shown relevance to compulsive gaming (Lemmens et al., 2015). Furthermore, interpersonal problems are considered, as difficulties in social relationships, including social withdrawal or overly dependent behaviors, may serve as both precursors to and consequences of IGD. Addressing a gap identified in previous research, this study directly assesses interpersonal challenges to uncover their unique contribution to IGD severity. Based on prior work (Bonnaire & Baptista, 2019; Lemmens et al., 2015), we advanced several hypotheses. First, we expected that at-risk gamers (meeting one to six IGD criteria) would report higher levels of alexithymia, anxiety, maladaptive personality traits (particularly disinhibition), and interpersonal difficulties than normal gamers (meeting zero IGD criteria). Second, we hypothesized that IGD severity would show positive associations with alexithymia, anxiety, maladaptive personality traits, and interpersonal problems across the full sample. Third, we anticipated that specific traits such as disinhibition, difficulties in emotional processing, and socially avoidant interpersonal patterns would account for unique variance in IGD severity when modeled simultaneously. Finally, although exploratory, we expected that role-playing gamers would report relatively greater interpersonal difficulties than those who primarily played other genres (e.g., action games), reflecting the immersive and socially complex demands of role-playing environments. Sample We report how we determined our sample size, all data exclusions, all manipulations, and all measures in the study. The inclusion criteria required participants to be adults (18 years old and above), as this age range is most susceptible to IGD (Bonnaire & Baptista, 2019; Lemmens et al., 2015; Pontes & Griffiths, 2015c). The study obtained 205 participants, with a representation across genders (73.66% female, 23.41% male, 1.95% non-binary/third gender, 0.98% Other Gender), ethnic backgrounds (41.34% Caucasian, 24.02% Hispanic, 15.64% Asian, 7.82% African American, 7.82% other ethnicities, and 3.35% mixed ethnicities), and educational levels (22% high school graduate, 43% some college, 21% college graduate, 9% postgraduate degree). Participants ranged in age from 18 to 46 years (M = 20.41), with the majority between 18–20 years (76.1%), followed by 26–30 years (11.2%), 21–25 years (10.2%), 31–35 years (2.0%), and 36 years or older (0.5%). All completed surveys and informed consent were kept secure on the Qualtrics website. The Qualtrics platform allowed for the turning off of IP addresses, which was performed to ensure participant anonymity from the study authors. All participants were volunteers and were assured of their anonymity and the confidentiality of their responses in the informed consent form they signed digitally before participating in the study. Participants were recruited from December 2023 to January 2024 through various online listservs such as gaming servers/chatrooms (Discord) and the snowball technique of recruiting through social networking related to internet gaming (e.g. Facebook, LinkedIn). The sample’s demographic data and response rates were carefully monitored to ensure broad representation across demographic groups. Importantly, no interventions or selective recruitment strategies were used during data collection; monitoring was descriptive only, and all participants who met the inclusion criteria and completed the survey were retained. Participants were not compensated for taking the survey. However, they were informed of the study’s aim to understand gaming behavior, and its effects on mental health. This partial masking helped reduce bias in self-reporting on emotional and interpersonal problems. Participants were excluded if they (a) failed to complete the survey in full, (b) failed the embedded attention-check validity item, or (c) provided incomplete responses on key measures (IGDS9-SF, PAQ, GAD-7, PID-5, or IIP-SC). These criteria ensured the final sample (N = 205) reflected complete and valid data for all study variables. Measures Internet Gaming Disorder Scale - Short Form (IGDS9-SF) The IGDS9-SF is a 9-item measure that assesses the severity of Internet Gaming Disorder (IGD) based on the criteria outlined in the DSM-5. This scale utilizes a 5-point Likert scale, where responses range from 1 (”Never”), 2 (”Rarely”), 3 (”Sometimes”), 4 (”Often”), to 5 (”Very often”), resulting in total dimensional scores ranging from 9 to 45, with higher scores indicating greater IGD severity. For categorical classifications, those who answered “Often” or “Very Often” were considered to meet diagnostic criteria for that specific item (i.e. 0-9). The scale has demonstrated high internal consistency (α = .87) and good construct validity, as it has shown significant correlations with other addiction measures and hours of weekly game play (p < 0.0001; Pontes & Griffiths, 2015). In this study, Pontes and Griffiths (2015) reported a mean IGDS9-SF score of 18 (SD = 6.63) in a sample of 528 young adult gamers (mean age = 27 years, 85% male), indicating mild levels of gaming disorder symptoms in their sample. This study will similarly employ the IGDS9-SF to assess IGD in U.S. young adults, drawing on previous psychometric validations. In the current sample, the IGDS9-SF demonstrated a Cronbach’s alpha of 0.833. Generalized Anxiety Disorder-7 (GAD-7) The GAD-7 is a 7-item self-report scale designed to screen for and assess the severity of generalized anxiety disorder (GAD). Each item is rated on a 4-point scale from 0 (”Not at all”) to 3 (”Nearly every day”), yielding a total score that ranges from 0 to 21. Higher scores indicate more severe anxiety symptoms, with cutoffs typically set at 5 (mild anxiety), 10 (moderate anxiety), and 15 (severe anxiety). The GAD-7 has been shown to have excellent internal consistency (α = 0.92) and high test-retest reliability (intraclass correlation = 0.83) in previous studies (Spitzer et al., 2006). The mean GAD-7 score in the study by Byrd-Bredbenner et al. (2021) was 8.4 (SD = 5.1), reflecting moderate anxiety in their university student sample. In the current sample, the Generalized Anxiety Disorder-7 (GAD-7) scale exhibited a Cronbach’s alpha of 0.899. Personality Inventory for DSM-5 - Brief Form (PID-5-BF) The PID-5-BF is a 25-item measure that assesses maladaptive personality traits across five domains: Negative Affectivity, Detachment, Antagonism, Disinhibition, and Psychoticism. Each item is rated on a 4-point scale, ranging from 0 (”Very False or Often False”) to 3 (”Very True or Often True”). The scale has been validated in various populations, showing acceptable internal consistency, with Cronbach’s alpha values ranging from 0.68 to 0.78 across the domains (Anderson et al., 2018). The scale is particularly useful for identifying personality traits that may contribute to or exacerbate IGD severity, with prior studies noting its relevance in clinical settings. In our study, the Personality Inventory for DSM-5 Brief Form (PID-5-BF) total score yielded a Cronbach’s alpha of 0.904. For PID-5-BF subscales (Negative Affect, Detachment, Antagonism, Disinhibition, and Psychoticism), the Cronbach’s alpha was between 0.675-0.819. Perth Alexithymia Questionnaire (PAQ) The PAQ is a 24-item scale designed to measure alexithymia, a condition characterized by difficulty identifying and describing emotions. Each item is rated on a 5-point Likert scale, with responses ranging from 1 (”Strongly disagree”) to 5 (”Strongly agree”). The PAQ has been shown to have high internal consistency, with Cronbach’s alpha values ranging from 0.87 to 0.91 across subscales (Preece et al., 2018). Previous research has linked alexithymia to IGD severity, as individuals with higher alexithymia scores are more likely to use gaming as a maladaptive coping mechanism. In our sample, the Perth Alexithymia Questionnaire (PAQ) total score demonstrated a Cronbach’s alpha of 0.95. For PAQ subscales (General-Difficulty Identifying Feelings (G-DIF), General-Difficulty Describing Feelings (G-DDF), Negative-Difficulty Appraising Feelings (N-DAF), Positive-Difficulty Appraising Feelings (P-DAF), and General-Difficulty Appraising Feelings (G-DAF)), Cronbach’s alpha was between 0.786-0.950. For PAQ subscales (Negative-Difficulty Identifying Feelings (N-DIF), Positive-Difficulty Identifying Feelings (P-DIF), Negative-Difficulty Describing Feelings (N-DDF), Positive-Difficulty Describing Feelings (P-DDF), and General-Externally Oriented Thinking (G-EOT)), Cronbach’s alpha was between 0.743-0.899. Inventory of Interpersonal Problems – Short Circumplex (IIP-SC) The IIP-SC is a 32-item self-report measure designed to assess interpersonal difficulties. Each item is rated on a 5-point scale, ranging from 0 (”Not at all”) to 4 (”Extremely”), and the items cover a range of interpersonal problems, such as being overly controlling or overly nurturant. The IIP-SC has demonstrated reliability, with internal consistency coefficients ranging from 0.68 to 0.84 across various samples (Soldz et al., 1995). The scale has been widely used in clinical research to assess how interpersonal problems may contribute to or result from psychiatric disorders such as IGD. In our current sample, the Inventory of Interpersonal Problems-Short Circumplex (IIP-SC) scale had a Cronbach’s alpha of 0.944. The Cronbach’s alpha values for the IIP-SC subscales ranged from 0.516 to 0.726, reflecting varying levels of internal consistency. The IIP-SC produces eight circumplex subscales, each representing a distinct interpersonal style: Domineering/Controlling, Vindictive/Self-Centered, Cold/Distant, Socially Inhibited, Nonassertive, Overly Accommodating, Self-Sacrificing/Overly Nurturant, and Intrusive/Needy. These dimensions capture maladaptive interpersonal tendencies ranging from excessive control and hostility to dependency and submissiveness (Soldz et al., 1995). For example, the Socially Inhibited and Nonassertive scales assess avoidance of social contact and reluctance to express needs, while the Overly Nurturant scale reflects difficulty setting interpersonal boundaries. Including these subscales provides a nuanced profile of how interpersonal problems relate to IGD severity and allows identification of specific patterns (e.g., social avoidance, excessive dependency) that may drive problematic gaming. Although the overall reliability of the IIP-SC total score was excellent (α = .944), several subscales demonstrated lower internal consistency, with Cronbach’s alpha values ranging from .52 to .73. These values are consistent with prior work noting variability in IIP-SC subscale reliabilities (Soldz et al., 1995). They should be considered when interpreting results that rely on specific subscales. Gaming Type Gaming Type. Participants were asked to indicate their primary game type in a single forced-choice item. They selected from four categories: action (n = 78), simulation/strategy (n = 49), adventure (n = 43), and role-playing (n = 35). Ethics The study protocol, including all instruments, informed consent, and procedures, was reviewed and approved by the Institutional Review Board (IRB) of XXX (masked for anonymous review) to ensure compliance with ethical standards and the safety and well-being of all participants. Results Data Analysis All analyses were conducted using SPSS. Data were screened for completeness, and participants who failed attention checks or did not complete the survey were excluded, resulting in a final sample of 205. Descriptive statistics and reliability estimates were calculated for all measures. Participants were classified as Normal gamers (meeting 0 DSM-5 IGD criteria; n = 142) and At-risk gamers (meeting 1–6 criteria; n = 63) based on IGDS9-SF scores (Lemmens et al 2015). To test whether these groups differed in psychological functioning, we conducted two-group mean comparisons on alexithymia (PAQ), anxiety (GAD-7), maladaptive personality traits (PID-5), and interpersonal problems (IIP-SC). Cohen’s d effect sizes are also provided to aid the interpretation of group differences. Pearson bivariate correlations were used to examine the relationships between continuous IGDS9-SF scores (IGD severity) and psychological variables (alexithymia, anxiety, PID-5 traits, interpersonal problems). These analyses estimate the strength and direction of zero-order associations between IGD severity and emotional, personality, and interpersonal factors. To evaluate the unique contributions of specific psychological variables, a stepwise multiple regression was conducted with IGD severity as the dependent variable. Subscales from the PID-5, PAQ, and IIP-SC were entered as independent predictors. This approach identifies the subset of predictors that account for unique variance in IGD severity, beyond their intercorrelations. Standardized beta coefficients and model R 2 values are reported. Finally, exploratory analyses were conducted to compare psychological and interpersonal scores across major gaming types (e.g., role-playing vs. action games). These analyses were intended to provide preliminary insights into whether the gaming genre is associated with differences in emotional or interpersonal functioning. Group Comparisons: Normal vs. At-Risk Gamers The study aimed to examine the relationship between Internet Gaming Disorder (IGD) severity and various psychological and interpersonal factors, including anxiety (GAD-7), alexithymia (PAQ), personality traits (PID-5), and interpersonal problems (IIP-SC) (See Table 1). On the PAQ, total scores revealed that at-risk gamers ( n = 63) (M = 89.25, SD = 30.30) exhibited higher IGD scores compared to Normal gamers ( n = 142) (M = 75.54, SD = 27.58). On the GAD-7, total scores revealed that at-risk gamers (M = 9.24, SD = 5.48) exhibited higher IGD scores compared to Normal gamers ( n = 142) (M = 7.14, SD = 5.22). The PID-5 total scores revealed that at-risk gamers (M = 1.04, SD = 0.45) exhibited higher IGD scores compared to Normal gamers (M = 19.28, SD = 12.46). Lastly, PID-5 total scores revealed that at-risk gamers (M = 25.86, SD = 11.35) exhibited higher IGD scores compared to Normal gamers (M = 8.10, SD = 4.76). At-risk gamers scored significantly higher than normal gamers across various psychological measures F (1, 203) = 138.2, p < 0.001. For alexithymia, at-risk gamers had higher mean scores compared to normal gamers F (1, 203) = 10.2, p < .002, with a small effect size ( d = 0.28). Similarly, for anxiety, at-risk gamers had higher mean scores than normal gamers, F (1, 203) = 6.9, p < .009, d = 0.208. Interpersonal problems followed the same trend, with at-risk gamers showing more interpersonal difficulties than normal gamers, F (1, 203) = 13.614, p < .001, d = 0.372. For maladaptive personality traits measured in the PID-5, at-risk gamers showed more negative traits compared to the normal gamers F (1, 203) = 12.8, p < 0.001. These group comparisons highlight the heightened emotional and interpersonal issues faced by at-risk gamers. Correlation analyses revealed that IGD severity was significantly associated with increased anxiety (Table 2) (GAD-7; r = .29, p < .001), alexithymia (PAQ; r = .34, p < .001), personality dysfunctions (PID-5; r = .40, p < .001), and interpersonal difficulties (IIP-SC; r = .33, p < .001). Regression Analyses Given the significant relationships between the total scores of each of these measures with IGD severity, we examined all subscale scores from these measures in relation to predicting IGD severity. A stepwise regression analysis was conducted to identify which subscales of the different psychological measures best predicted IGD severity (Table 3). The first variable to enter into the model was disinhibition (M = .751, SD = 0.650) from the PID-5 (β = .363, p < .001), explaining 13.2% of the variance in IGD severity. This was followed by socially avoidant behaviors (M = 12.14, SD = 4.35) from the IIP-SC (β = .314, p < .001), which explained an additional 5.5% of the variance. Externally oriented thinking (M = 26.50, SD = 10.73) from the PAQ (β = .156, p < .001) and overly nurturant behavior (M = 12.48, SD = 4.41) from the IIP-SC (β = .139, p < .001) were also significant. The negative affect (M = 1.37, SD = 0.80) from the PID-5 was inversely related to IGD severity (β = -.171, p < .001), suggesting that lower levels of emotional dysregulation may reduce the risk of developing severe IGD symptoms. In total, the regression model explained 24.3% of the variance in IGD severity. In examining the role of gaming type, no significant differences were found for most psychological measures. However, a trend towards significance was observed for interpersonal problems ( p = .059), with role-playing gamers ( M = 14.8, SD = 5.3) reporting more interpersonal difficulties than action gamers ( M = 12.1, SD = 4.8; give the t value, p value and d v alue). In the regression analyses, we used a forward stepwise procedure in SPSS with the entry criterion set at p < .05. This meant that predictors were sequentially added to the model if they significantly improved the explained variance in IGD severity. Predictors that did not meet the significance threshold were excluded. Candidate predictors included all subscales from the PID-5-BF, PAQ, and IIP-SC. The first step entered PID-5 Disinhibition (β = .363, p < .001), accounting for 13.2% of the variance in IGD severity. At step two, IIP-SC Socially Avoidant behaviors entered (β = .314, p < .001), explaining an additional 5.5%. Step three added PAQ Externally Oriented Thinking (β = .156, p < .001), and step four added IIP-SC Overly Nurturant behavior (β = .139, p < .001). Finally, PID-5 Negative Affect entered at step five (β = –.171, p < .001), contributing a small but significant inverse association. The full model explained 24.3% of the variance in IGD severity (R² = .243, adjusted R² = .226), indicating that these traits collectively accounted for nearly one-quarter of the variance after controlling for overlap. This procedure highlights that maladaptive personality features (especially disinhibition), socially avoidant interpersonal styles, and externally oriented emotional processing were the most robust predictors of IGD severity in this sample. The inclusion thresholds ensured that only predictors with meaningful, unique contributions were retained, reducing redundancy from correlated measures. Discussion The present study sought to extend the findings of Bonnaire and Baptista (2019) by examining the relationship between Internet Gaming Disorder (IGD) and various emotional and interpersonal factors in a diverse sample of U.S. young adults. A key strength of this study is its gender-diverse sample (73% female, with non-binary and other gender representation), which contrasts with the male-dominated samples of prior IGD research and expands the applicability of the findings. Because this study employed a cross-sectional design, all findings reflect associations rather than causal relationships. Interpretations regarding psychological mechanisms or risk processes should be considered tentative pending replication with longitudinal data. The results support previous research suggesting that emotional functioning, personality traits, and interpersonal difficulties are significantly related to IGD severity (Bonnaire & Baptista, 2019; Lemmens et al., 2015; Pontes & Griffiths, 2015). Specifically, individuals with more severe IGD symptoms exhibited greater levels of alexithymia, anxiety, maladaptive personality traits, and interpersonal problems. These findings align with the vulnerability hypothesis, suggesting that preexisting psychological vulnerabilities (being impulsive and sensation-seeking) may increase the likelihood of developing IGD. Additionally, the largest associations with IGD were personality traits, such as disinhibition and social avoidance, which support the idea that maladaptive personality features are strongly associated with IGD severity (Lemmens et al., 2015). Our results provide additional support for prior research identifying disinhibition as a key factor of IGD severity (Lemmens et al., 2015). The significant association between disinhibition and IGD aligns with the idea that impulsivity and poor self-control are central features of compulsive gaming behaviors. Socially avoidant behaviors also supported the notion that interpersonal difficulties, such as avoidance of real-world interactions, may drive individuals toward immersive gaming environments (Pontes & Griffiths, 2015). Furthermore, externally oriented thinking and overly nurturant behaviors in IGD may serve as a maladaptive coping mechanism for individuals who struggle with self-awareness and boundary-setting in relationships. Notably, negative affect was inversely related to IGD severity, suggesting that individuals reporting lower levels of emotional dysregulation also tended to report less severe IGD symptoms. Given the cross-sectional design, this association should be interpreted cautiously and does not establish directionality. The study’s findings regarding alexithymia and anxiety further highlight the emotional challenges associated with IGD. Significant correlations between IGD severity and both alexithymia and anxiety are consistent with previous literature (Bonnaire & Baptista, 2019; Estévez et al., 2017). Individuals with alexithymia, who experience difficulties in identifying and expressing emotions, may turn to gaming as a means of emotional escape or to help regulate feeling states. Similarly, heightened anxiety levels may exacerbate gaming behaviors, as individuals seek refuge in virtual environments to alleviate or avoid emotional distress. These results underscore the critical role of emotional regulation in IGD and suggest that interventions targeting these emotional vulnerabilities may be particularly effective. Interpersonal problems, as assessed by the Inventory of Interpersonal Problems – Short Circumplex (IIP-SC), were also significantly related to IGD severity. At-risk gamers reported more interpersonal difficulties compared to normal gamers, aligning with prior research linking IGD to social avoidance and dependency (Pontes & Griffiths, 2015). Although gaming type did not significantly affect most psychological measures, a trend in significance with a moderate ( d = 0.322) effect indicated that players who preferred role-playing games (RPGs; e.g., Pokémon, World of Warcraft, Maplestory) reported more interpersonal difficulties than those who preferred action games (e.g., Call of Duty, Pacman, Counterstrike). This aligns with the immersive and socially complex nature of RPGs, which may appeal to individuals seeking escape or structured social interactions that are less demanding than real-life exchanges. While the trend was not statistically significant, it suggests that specific gaming genres may have distinct associations with psychological and interpersonal factors, warranting further investigation. While exploratory, this observation aligns with prior work suggesting that specific game genres may differentially relate to psychological vulnerabilities in IGD (Bonnaire & Baptista, 2019). The study’s regression analysis accounted for 24.3% of the variance in IGD severity, underscoring the predictive power of emotional, personality, and interpersonal factors. Disinhibition, socially avoidant behaviors, and externally oriented thinking were particularly salient traits that may occur in individuals with IGD, consistent with prior findings (Lemmens et al., 2015; Pontes & Griffiths, 2015). These results emphasize the multifaceted nature of IGD and highlight the need for comprehensive assessments that address a wide range of psychological and interpersonal factors. Limitations The cross-sectional design precludes causal inferences, and reliance on self-report measures may introduce biases, such as social desirability or recall inaccuracies. Additionally, the sample primarily consisted of young adults, limiting generalizability to other age groups. Future research should employ longitudinal designs to better understand the temporal relationships between emotional, personality, and interpersonal factors and IGD in larger and more diagnostically diverse samples. Measurement-related limitations should also be acknowledged. As with many behavioral addiction measures, the IGDS9-SF may identify a larger proportion of individuals as “at risk” than appear to be clinically impaired, raising concerns about potential inflation of prevalence estimates. Moreover, the IGDS9-SF has not been validated against clinical judgment, which constrains conclusions about its diagnostic utility. Some of the subscales employed in the present study, particularly from the IIP-SC, demonstrated relatively weak internal consistency, and this limits confidence in subscale-specific findings. Finally, although the stepwise regression approach was chosen to identify the most parsimonious set of predictors, replication using theoretically driven hierarchical models or penalized regression methods (e.g., LASSO) would strengthen confidence in the observed predictors of IGD severity. ¿p#1 Clinical Implications and Future Directions The present findings carry important implications for treatment development and refinement in Internet Gaming Disorder (IGD). Current clinical approaches most often employ cognitive-behavioral therapy (CBT), which has demonstrated moderate efficacy in reducing IGD severity and improving functioning across randomized trials (Zajac et al., 2017; Zajac et al., 2019). However, these interventions primarily target gaming-related cognitions and behavioral regulation, and less often address the emotional processing deficits and interpersonal vulnerabilities identified in this study. The associations we observed between IGD severity, alexithymia, and social avoidance suggest that treatments incorporating emotion regulation strategies and interpersonal skill-building may be especially valuable. Mindfulness-based approaches and emotion-focused interventions, for instance, have shown promise in reducing cravings and improving emotional awareness in related behavioral addictions (Sharma, 2022; Stevens et al., 2018). Integrating such modules into CBT for IGD may help address the affect related and relational issues highlighted by our data. In addition, our findings suggest that disinhibition and socially avoidant interpersonal styles may predict unique variance in IGD severity, aligning with clinical research suggesting the utility of targeting impulsivity and interpersonal functioning in treatment. Pharmacological interventions such as bupropion or methylphenidate have been shown to reduce impulsive gaming behaviors in some trials, though effects are mixed and often modest (Zajac et al., 2019; Wang et al., 2024, Lin et al., 2025). Family-based and systemic therapies may also be particularly well suited to IGD cases marked by social withdrawal, as they directly address relational dynamics and communication patterns (Chrétien, 2025; Ock, 2025). Incorporating modules focused on boundary setting, assertiveness, and building offline relationships may therefore enhance generalization of treatment gains beyond gaming contexts. Despite these advances, there remain notable gaps in the treatment literature. Few existing interventions explicitly measure or target alexithymia or interpersonal avoidance, constructs that emerged as central in our study. Likewise, while role-playing gamers showed a trend toward greater interpersonal difficulties, treatment studies have rarely examined whether game genre moderated treatment response or requires tailored intervention strategies. Future research should evaluate whether integrating interpersonal and emotional regulation modules into CBT protocols enhances efficacy, particularly for individuals endorsing high levels of alexithymia or social avoidance. Longitudinal and dismantling trials that assess not only symptom reduction but also changes in interpersonal functioning and emotional processing will be critical to advance a more nuanced, multidimensional approach to IGD treatment (Day et al., 2017; Shumaker, 2022). ¿p#1 Conclusion This study advances our understanding of IGD by identifying critical emotional, personality, and interpersonal factors that predict its severity. The findings highlight the importance of targeting disinhibition, social avoidance, alexithymia, and anxiety in clinical interventions for IGD. Moreover, the results underscore the need to consider gaming type in assessments and interventions, as certain genres may exacerbate interpersonal challenges. By integrating psychological, social, and behavioral dimensions, this research contributes to the development of comprehensive models for understanding and addressing IGD, ultimately informing more effective prevention and treatment strategies. References American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing. Anderson, J. L., Sellbom, M., & Salekin, R. T. (2018). Utility of the Personality Inventory for DSM-5–brief form (PID-5-BF) in the measurement of maladaptive personality and psychopathology. Assessment, 25 (5), 596–607. https://doi.org/10.1177/1073191116676889 Andreassen, C. S., Griffiths, M. D., Gjertsen, S. R., Krossbakken, E., Kvam, S., & Pallesen, S. (2013). The relationships between behavioral addictions and the five-factor model of personality. Journal of Behavioral Addictions, 2 (2), 90-99. https://doi.org/10.1556/JBA.2.2013.003 Bonnaire, C., & Baptista, D. (2019). Internet gaming disorder in male and female young adults: The role of alexithymia, depression, anxiety and gaming type. Psychiatry Research , 272 , 521–530. https://doi.org/10.1016/j.psychres.2018.12.158 Borges, G., Benjet, C., Robles-García, R., & Medina-Mora, M. E. (2020). The epidemiology of gaming disorder: A global overview. Journal of Psychiatric Research, 129, 68–73. Chang, S., Hsiao, R. C., & Yen, C. F. (2023). Validation of the Internet Gaming Disorder Scale–Short Form among adolescents with attention-deficit/hyperactivity disorder. International Journal of Environmental Research and Public Health, 20 (3), Chrétien, M., Savard, J., & Bouchard, S. (2025). Internet gaming disorder: Treatment approaches and clinical challenges. Frontiers in Psychiatry, Chiang, Y. T., Lin, Y. H., & Chen, I. H. (2022). Longitudinal associations between Internet gaming disorder symptoms and psychosocial problems in adolescents. Addictive Behaviors, 129, 107259. Chiappini, S., Schifano, F., & Potenza, M. N. (2025). Internet gaming disorder: Neurocognitive and neurobiological features. Frontiers in Psychiatry, 16, 1441237. Clorado de Sá, L. S., de Oliveira, M. P., & Monteiro, J. C. (2025). Clinical interventions for gaming disorder: A systematic review of psychological treatments. Addictive Behaviors Reports, 22, 101708. Day, M., & Wade, T. D. (2017). Treatment of internet gaming disorder: A systematic review. Clinical Psychology Review, 54, 56–68. Darvesh, N., Radhakrishnan, A., Lachance, C. C., Nincic, V., Sharpe, J. P., Ghassemi, M., Straus, S. E., & Tricco, A. C. (2020). Exploring the prevalence of gaming disorder and Internet gaming disorder: a rapid scoping review. Systematic reviews , 9 (1), 68. https://doi.org/10.1186/s13643-020-01329-2 Estévez, A., Jàuregui, P., Sànchez-Marcos, I., Lopez-Gonzàlez, H., & Griffiths, M. D. (2017). Attachment and emotion regulation in substance addictions and behavioral addictions. Journal of Behavioral Addictions , 6 (4), 534–544. https://doi.org/10.1556/2006.6.2017.086 Fauth-Bühler, M., & Mann, K. (2017). Neurobiological correlates of Internet gaming disorder: Similarities to pathological gambling. Addiction Biology, 22 (1), 372–383. Fusar-Poli, P., Hijazi, Z., Stahl, D., & Steyerberg, E. W. (2018). The science of prognosis in psychiatry: A review. JAMA Psychiatry , 75 (12), 1289-1297. https://doi.org/10.1001/jamapsychiatry.2018.2530 Gentile, D. A., Choo, H., Liau, A., Sim, T., Li, D., Fung, D., & Khoo, A. (2011). Pathological video game use among youths: A two-year longitudinal study. Pediatrics , 127 (2), e319–e329. https://doi.org/10.1542/peds.2010-1353 Ghiaccio, R., Passaro, A., Stasolla, F., Martini, E., De Fortuna, A. M., & De Luca Picione, R. (2025). Exploring the Association Between Problematic Internet Use, Internet Gaming Disorder in Adolescents with ADHD: A Scoping Review. International Journal of Environmental Research and Public Health , 22 (4), 496. https://doi.org/10.3390/ijerph22040496 Harden, K. P., & Tucker-Drob, E. M. (2011). Individual differences in the development of sensation seeking and impulsivity during adolescence: Further evidence for a dual systems model. Developmental Psychology, 47 (3), 739–746. https://doi.org/10.1037/a0023279 Huys, Q. J., Maia, T. V., & Frank, M. J. (2016). Computational psychiatry as a bridge from neuroscience to clinical applications. Nature Neuroscience , 19 (3), 404–413. https://doi.org/10.1038/nn.4238 Király, O., Griffiths, M. D., Urbán, R., Farkas, J., Kökönyei, G., Elekes, Z., Tamás, D., & Demetrovics, Z. (2014). Problematic internet use and problematic online gaming are not the same: Findings from a large nationally representative adolescent sample. Cyberpsychology, Behavior and Social Networking , 17 (12), 749–754. https://doi.org/10.1089/cyber.2014.0475 Kim, H. S. (2022). Impulsivity and emotion dysregulation in Internet gaming disorder: A systematic review. Current Addiction Reports, 9, 45–55. Kuss, D. J., Pontes, H. M., & Griffiths, M. D. (2018). Neurobiological correlates in internet gaming disorder: A systematic literature review. Frontiers in psychiatry , 9 , 166. Leising, D., Grande, T., & Faber, R. (2009). The Toronto Alexithymia Scale (TAS-20): A measure of general psychological distress. Journal of Research in Personality , 43 (4), 707–710. https://doi.org/10.1016/j.jrp.2009.03.009 Lemmens, J. S., Valkenburg, P. M., & Gentile, D. A. (2015). The Internet Gaming Disorder Scale. Psychological Assessment , 27 (2), 567–582. https://doi.org/10.1037/pas0000062 Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2009). Development and validation of a game addiction scale for adolescents. Media Psychology , 12 (1), 77–95. https://doi.org/10.1080/15213260802669458 Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2011). Psychosocial causes and consequences of pathological gaming. Computers in Human Behavior , 27 (1), 144–152. https://doi.org/10.1016/j.chb.2010.07.015 Li, C. Y., & Wang, C. (2019). The influence of personality traits on online compulsive behavior: The moderating role of gender. Current Psychology , 38 (2), 380–392. https://doi.org/10.1007/s12144-017-9615-1 Lin, C. Y., Broström, A., Griffiths, M. D., & Pakpour, A. H. (2020). Psychological interventions for internet gaming disorder: A systematic review. Current Addiction Reports, 7, 123–135. https://doi.org/10.1016/j.psychres.2020.113060 Lin, C. Y., Chang, C. C., & Lee, T. H. (2025). Personalized digital interventions for internet gaming disorder: New directions for treatment. Journal of Behavioral Addictions, 14(1), 45–58. https://doi.org/10.1007/s40429-025-00644-9 Loreto, G. (2023). Integrating psychological and physiological perspectives in the study of behavioral addictions. Journal of Behavioral Addictions , 12 (1), 59-72. https://doi.org/10.1556/JBA.2023.12.1.009 Mak, K. K., Lai, C. M., Watanabe, H., Kim, D. I., Bahar, N., Ramos, M., & Cheng, C. (2019). Epidemiology of internet behaviors and addiction among adolescents in six Asian countries. Cyberpsychology, Behavior, and Social Networking , 17 (11), 720-728. https://doi.org/10.1089/cyber.2014.0139 Müller, K. W., Beutel, M. E., Egloff, B., & Wölfling, K. (2014). Investigating risk factors for Internet gaming disorder: a comparison of patients with addictive gaming, pathological gamblers and healthy controls regarding the big five personality traits. European addiction research , 20 (3), 129-136. Ock, C.-M., Lee, H.-S., Chae, J., & Kim, H. (2025). Effectiveness of non-pharmacological interventions on gaming disorder: A systematic review and meta-analysis. Psychiatry Investigation, 22 (5), 490–503. Pontes, H. M., & Griffiths, M. D. (2015). Measuring DSM-5 internet gaming disorder: Development and validation of a short psychometric scale. Computers in Human Behavior , 45 , 137–143. https://doi.org/10.1016/j.chb.2014.12.006 Preece, D., Becerra, R., Robinson, K., Dandy, J., & Allan, A. (2018). The psychometric assessment of alexithymia: Development and validation of the Perth Alexithymia Questionnaire. Personality and Individual Differences , 132 , 32–44. https://doi.org/10.1016/j.paid.2018.05.011 Rotunda, R. J., Knapp, E., Wolfe, E., & Kennedy, R. (2025). Prevalence of problematic internet use in a clinical sample of university students. Professional Psychology: Research and Practice. Saunders, J. B., Hao, W., Long, J., King, D. L., Mann, K., Fauth-Bühler, M., … & Poznyak, V. (2017). Gaming disorder: Its delineation as an important condition for diagnosis, management, and prevention. Journal of behavioral addictions , 6 (3), 271-279. Sharma, M. K. (2022). Mindfulness interventions for technology and gaming addictions: A review. Journal of Mental Health, 31 (4), 456–464. Sharma, M. K., Aggarwal, A., & Singh, R. (2023). Internet Gaming Disorder: Advances in treatment research. Frontiers in Psychiatry, 14 , 100223. Shumaker, D., & Manning, C. (2022). Existential implications of internet gaming disorder: An existential–humanistic therapy perspective. The Humanistic Psychologist, 50(4), 544–558. Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine , 166 (10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092 Stevens, M. W. R., King, D. L., Dorstyn, D., & Delfabbro, P. H. (2019). Cognitive‑behavioral therapy for Internet gaming disorder: A systematic review and meta‑analysis. Clinical Psychology & Psychotherapy , 26 (2), 191–203. Tarter, R. E. (2002). Etiology of substance use disorder: An overview. Handbook of Substance Abuse , 147–158. Vaccaro, A. G., & Potenza, M. N. (2019). Diagnostic and classification considerations regarding gaming disorder: Neurocognitive and neurobiological features. Frontiers in psychiatry , 10 , 405. Wang, H.-Y., & Cheng, C. (2022). The associations between gaming motivation and internet gaming disorder: Systematic review and meta-analysis. JMIR Mental Health , 9 (2), e23700. https://doi.org/10.2196/23700 Wang, W., Li, C., & Zhao, Y. (2024). Pharmacological interventions for Internet Gaming Disorder: A systematic review. Addictive Behaviors, 152 , 107996. Weinstein, A., & Lejoyeux, M. (2010). Internet addiction or excessive internet use. The American journal of drug and alcohol abuse , 36 (5), 277-283. Yoneda, T., Ames, M. E., & Leadbeater, B. J. (2019). Is there a positive side to sensation seeking? Trajectories of sensation seeking and impulsivity may have unique outcomes in young adulthood. Journal of Adolescence , 73 , 42-52. Zajac, K., Ginley, M. K., Chang, R., & Petry, N. M. (2017). Treatments for Internet gaming disorder and Internet addiction: A systematic review. Psychology of Addictive Behaviors , 31 (8), 979–994. Zajac, K., Ginley, M. K., & Petry, N. M. (2019). Cognitive-behavioral therapy for Internet Gaming Disorder: A randomized clinical trial. Journal of Consulting and Clinical Psychology, 87 (10), 965–977. Zigmond, A. S., & Snaith, R. P. (1983). The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica , 67 (6), 361–370. https://doi.org/10.1111/j.1600-0447.1983.tb09716.x xxx and xxx contributed equally to all aspects of this project, including study conceptualization, data collection, data preparation, data analysis, and report writing. Both authors approved the final version of the manuscript for submission. Data Transparency Statement: Data will be provided upon request by the first author. Tables ¿p#1 Measure Normal Gamers (n = 142) M (SD) At-Risk Gamers (n = 63) M (SD) F(1, 203) p Cohen’s d Alexithymia (PAQ) 75.54 (27.58) 89.25 (30.30) 10.2 0.002 0.28 Anxiety (GAD-7) 7.14 (5.22) 9.24 (5.48) 6.9 0.009 0.21 Interpersonal Problems (IIP-SC) 10.20 (4.76) 15.30 (5.20) 13.61 <.001 0.37 Maladaptive Personality Traits (PID-5) 19.28 (12.46) 25.86 (11.35) 12.8 <.001 0.35 Note. F-tests reported from one-way ANOVAs. Cohen’s d is calculated as a standardized mean difference. ¿p#1 Variable 1. PAQ 2. GAD-7 3. PID-5 4. IIP-SC 1. IGD Severity .34*** .29*** .40*** .33*** 2. Alexithymia (PAQ) — .45*** .38*** .41*** 3. Anxiety (GAD-7) — — .36*** .39*** 4. Personality Traits (PID-5) — — — .44*** 5. Interpersonal Problems (IIP-SC) — — — — p < .05; **p < .01; ***p < .001. Table 3 - Stepwise Regression: Alexithymia, Anxiety, Interpersonal, and Personality Variables predicting IGDS-9SF Total Score Step and independent variable (subscale) R r 2 b F p 1. Disinhibition (PID-5) .363 0.132 0.363 30.883 <.001 2. Octant FG (Socially Avoidant) (IIP-SC) .433 0.187 0.314 23.288 <.001 3. Generally-Externally oriented thinking (G-EOT) (PAQ) .458 0.21 0.156 17.801 <.001 4. Octant LM (Overly Nurturant) (IIP-SC) .477 0.227 0.139 14.718 <.001 5. Negative Affect (PID-5) .493 0.243 -0.171 12.767 <.001 Note. PID-5 = Personality Inventory for DSM–5, IIP-SC = Inventory of Interpersonal Problems–Short Circumplex, PAQ = Perth Alexithymia Questionnaire Information & Authors Information Version history V1 Version 1 26 September 2025 Peer review timeline Published Clinical Psychology & Psychotherapy Version of Record 28 Jan 2026 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords adult mental health anxiety interpersonal relationships personality Authors Affiliations Yan Mei Nie 0009-0002-9094-5747 [email protected] Adelphi University Gordon F Derner School of Psychology View all articles by this author Mark Hilsenroth Adelphi University Gordon F Derner School of Psychology View all articles by this author Metrics & Citations Metrics Article Usage 773 views 433 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Yan Mei Nie, Mark Hilsenroth. Relationship Between Personality Traits and Social Avoidance with Internet Gaming Disorder Severity. Authorea . 26 September 2025. DOI: https://doi.org/10.22541/au.175887371.15901106/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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