Depression–Anxiety Relationships with Internet Gaming Disorder among Health Sciences Students

Depression–Anxiety Relationships with Internet Gaming Disorder among Health Sciences Students | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Depression–Anxiety Relationships with Internet Gaming Disorder among Health Sciences Students Hend Faye AL-shahrani, Nouf Nawar Alotaibi, Ponnusamy Subramaniam, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9058142/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background This cross-sectional study aimed to assess the prevalence of Internet gaming disorder among health science students in southern Saudi Arabia and to explore its relationship with symptoms of depression and anxiety. Methods Data were collected from 362 Health Sciences Students from Najran University at Southern Saudi Arabia (M age = 21.6 years, SD age = 3.42 years). The sample completed an online survey that included the Internet Gaming Disorder Scale-Short Form, the CES-D Depression Model, and the Generalized Anxiety Disorder Scale. Results The results indicated that 22.6% of health sciences students exhibited signs of Internet gaming disorder. Furthermore, there was a positive correlation between the severity of Internet gaming disorder, levels of depression and anxiety. Both anxiety and depression symptoms explained 48% of the variation in Internet gaming disorder scores. Bivariate redundant analyses indicated that individuals who played online games for six or more hours each day were more likely to exhibit signs of severe depression and anxiety, had a relatively higher severity of Internet gaming disorder and males were more likely to have Internet gaming disorder compared to females. Furthermore, students with Internet gaming disorder had low academic achievement. Conclusion Future studies should validate these findings through more comprehensive research. However, this exploratory study provides valuable insights into potential strategies and programs for preventing Internet gaming disorder among Health Sciences students in Southern Saudi Arabia. Health sciences/Diseases Health sciences/Health care Biological sciences/Psychology Social science/Psychology Internet Gaming Disorder Anxiety Depression Mental Health Saudi Society Health Sciences Students Introduction Since the early 21st century, a surge in research has provided compelling evidence for a problem with online gaming addiction [ 1 ]. This has led to the classification of Internet Gaming Disorder (IGD) as a potential disorder requiring further research before full inclusion in diagnostic manuals [ 2 ]. Paralleling other addictive behaviors like overeating, alcoholism, and drug abuse, IGD has become a major concern within internet addiction research [ 3 ]. However, a core focus remains: identifying individuals who exhibit impaired control over gaming and experience significant negative consequences [ 4 ]. This growing recognition culminated in the official classification of IGD as a behavioral addiction by the American Psychiatric Association in 2013 [ 2 ]. making it the second such designation after gambling addiction. Similarly, In 2018, the World Health Organization recognized Internet gaming addiction as one of the addictive behavioral disorders in the eleventh revision of the International Classification of Diseases (ICD-11) [ 5 ]. Viewed as a chronic mental disorder [ 6 ], IGD manifests through symptoms like a lack of ability to regulate playtime, loss of interest in social activities, and a sense of deprivation when not gaming, regardless of the negative effects [ 7 , 8 ]. This process often results in neglecting studies, sleep, nutrition, hobbies, and social life in favor of excessive gaming [ 9 ]. The cycle can become self-perpetuating, with individuals seeking to escape dissatisfaction through online gaming but ultimately experiencing further isolation and and poor health outcomes [ 10 ]. Variations in survey methods, cultural settings, and diagnostic criteria account for the wide range of IGD prevalence estimates, which extend from under 1% to over 27% across age groups and countries [ 11 – 13 ]. For instance, while Germany reported a documented prevalence of 11%, South Korea had a lower prevalence of 8%, and Iran reported 17% [ 14 – 16 ]. In Saudi Arabia, internet adoption and digital connectivity have grown substantially over the past decade, with penetration reaching nearly 98% by 2023. This rapid growth has fueled the expansion of the gaming sector, making Saudi Arabia one of the largest gaming markets in the Middle East and North Africa[ 17 ]. At the same time, the blurred boundary between healthy gaming and outright addiction has raised concerns among educators, psychologists, parents, and policymakers in Saudi Arabia, especially in specific student groups such as those enrolled in health-related discipline[ 18 ]. Investigating IGD within this student population warrants serious attention, as health sciences students often face demanding academic routines that include coursework, clinical placements, late-night study sessions, and constant pressure to excel [ 19 ]. They frequently transition in a single day from lecture halls to laboratories to hospital wards, each requiring intense focus, strict time management, and significant emotional resilience. Consequently, this demanding lifestyle can deplete psychological energy, creating fertile ground for burnout and recurrent stress. To cope with these pressures, many students turn to digital spaces, with video games serving as one of the most accessible and least stigmatized forms of escapism[ 18 , 19 ]. Moreover, online games—built on electronics and visuals—are immensely popular across diverse groups, offering participants competition, challenge, excitement, and, in some cases, enjoyment of violent play. Examples include PUBG, Fortnite, Call of Duty: Mobile, FIFA, and League of Legends[ 20 , 21 ]. Nevertheless, this enjoyment can become a double-edged sword, as IGD has been linked to a variety of adverse mental health outcomes, including depression, anxiety disorders, anger control problems, emotional distress, neuroticism, low self-esteem, impulsivity, pathological gambling, and poor emotional regulation[ 22 – 25 ]. Theoretical frameworks such as the Interaction of Person-Affect-Cognition-Execution (I-PACE) model [ 26 ], and the Compensatory Internet Use Model [ 27 ], provide comprehensive explanations for the development and maintenance of Internet Gaming Disorder (IGD), emphasizing complex interactions of emotional, cognitive, and behavioral factors especially in vulnerable populations experiencing psychological distress or academic pressure. Given the high prevalence of IGD among young people and its harmful effects, researchers worldwide have conducted numerous studies on the relationship between online gaming, mental health, and quality of life [ 28 , 29 ]. Likewise, Luntungan, Pitoy [ 30 ] found that most respondents in the gaming group had poor mental health. Furthermore, increasing time spent online is strongly associated with higher risks of clinical depression [ 31 ]. A survey of 987 Indian adolescents also showed that those with higher levels of internet addiction reported greater anxiety and depression [ 32 ]. In terms of gender differences, evidence consistently indicates a male predominance in IGD [ 15 , 33 ]. A Canadian study on internet use by Quebec students reported that boys spend significantly more time online gaming, whereas girls more often use the internet for social media [ 34 ]. Neuroimaging research further shows greater brain activity during gaming in males compared to females [ 35 ]. Overall, most studies suggest that males are two to three times more likely to develop IGD than females [ 36 ]. In contrast, some findings indicate that females tend to use the internet primarily for social interaction, while males prefer online gaming [ 13 ]. Additionally, the time an individual spends playing video games is closely tied to IGD risk. Excessive playtime has been associated with psychological problems such as depression [ 37 ], anxiety [ 38 ], and sleep loss [ 39 ]. A study by Wartberg, Kriston [ 40 ]. demonstrated that prolonged play is linked to numerous negative outcomes, including generalized anxiety, depressive symptoms, stress, social fears, and social anxiety. Educational level plays a role as well: first- and second-year students often have more flexible schedules and fewer clinical obligations, allowing longer play sessions, whereas seniors typically restrict gaming due to internships, capstone projects, and job-seeking responsibilities. This literature highlights the increasing challenge concerning excessive online gaming and its dangerous effects, especially among young people. Although studies on IGD have grown, there's still a lack of studies investigating the link between IGD and mental health problems in Saudi Arabia, specifically among health sciences students. To fill this gap, this cross-sectional study examines the relationships between IGD, depression and anxiety in health science students, considering variations based on playtime, gender, and academic performance. More specifically, this study addresses three interrelated research questions: What is the prevalence of IGD among health science students in southern Saudi Arabia? How does IGD correlate with depression and anxiety? Are demographic factors-gender, academic level, and daily gaming hours-associated with variations in IGD severity? Do depression and anxiety significantly predict the level of IGD? Methodology Study Design The predicted associations between depression, anxiety, and IGD among Saudi Arabian health sciences students were investigated in this study using a cross-sectional correlational approach. Standardized psychometric questionnaires that were distributed online were used to gather data. Using regression and correlation analysis, the main objective was to determine if anxiety and depression significantly predict IGD scores. Participants Participants in this exploratory study, which employed a cross-sectional design, were recruited from students at the College of Health Sciences at Najran University in southern Saudi Arabia using convenience sampling. An electronic survey was distributed via Google Forms to students who were available and willing to participate during the study period, from March 24 to May 5, 2024. This distribution was coordinated with the university administration to maximize participant access. The final number of participants was 362 male and female students, exceeding the minimum sample size of 138. This determination was based on a priori statistical power analysis conducted using G*Power 3.1, with an assumed statistical power of 90%, a significance level of 0.05, and a medium effect size of f2 = 0.15. The mean age of participants was 21.6 years (standard deviation = 3.42). The conditions for participation included enrollment in a four-year bachelor's program, being over 18 years of age, proficiency in the Arabic language, and voluntary consent to participate. Data Collection Data for the current study was collected through an online survey from 24 March to 5 May 2024. A study invitation containing the information package related to the participating study questionnaires (Google Forms) was sent to randomly selected students from the undergraduate health sciences students at Najran University. The information package outlined the study's purpose, procedures, and participants' rights, including voluntary consent, anonymity, confidentiality, and the right to withdraw consent at any time. Prior to the study's commencement, the Ethics Committee of the Deanship of Scientific Research at Najran University, Saudi Arabia, approved the study and its procedures. which comply with the latest version of the Declaration of Helsinki. All participants also signed written informed consent. Tools Socio-demographic survey Participants were asked to provide information about the year of the study, their gender, age, and the average number of hours they spend playing online games each day. Academic achievement was assessed using a self-rated scale that categorizes students into three levels: good, average, and low. These categories are based on students' cumulative GPA ranges, aligned with the university's grading system: good (3.5–4.0), average (2.5–3.49), and low (< 2.5). This categorization aims to reflect academic performance in relation to the study's focus on ADHD risk factors. Future research could enhance the reliability of results by utilizing formal academic records or standardized assessment measures. . Internet Games Disorder Scale - Short Model (IGDS9-SF) The IGDS9-SF, created by Pontes and Griffiths [ 41 ], is a validated 9-item screening instrument designed to identify potential IGD based on the nine core criteria outlined in the DSM-5, For example, “Have you lost interests in previous hobbies and other entertainment activities as a result of your engagement with the game?”. This score assesses the severity of gaming disorder by rating the frequency of gaming over the past 12 months. It uses a five-point Likert scale, ranging from 1 (never) to 5 (very often), with total scores ranging from 9 to 45. Higher scores indicate a greater risk of developing gaming disorder, with a cut-off score of 32 or greater suggesting possible IGD[ 42 ]. The IGDS9-SF has been widely used in international studies and has demonstrated strong psychometric properties across different cultural contexts [ 43 – 45 ]. The IGDS9-SF scale's Arabic version was used in this study. Research was done by El Keshky and Alballa [ 46 ] to confirm the Arabic version's factor structure and psychometric qualities. According to the results, the scale is reliable and valid for use in research and diagnosis in Arabic-speaking nations. With a Cronbach's alpha of 0.92, the current study also showed high reliability for the IGDS9-SF scale. Centre for Epidemiological Studies Depression Scale (CES-D 10) The CES-D 10 [ 47 ] is a self-report scale consisting of 10 items that measures depressive symptoms experienced in the past week. It assesses different aspects of depression, including negative affect, positive affect, and physical symptoms for example, “I was bothered by things that usually don't bother me; I felt hopeful about the future”. Responses are rated on a 4-point scale, ranging from 0 (rarely or none of the time) to 3 (most or all of the time), with items 5 and 8 scored in reverse. Total scores can range from 0 to 30, with scores of 10 or higher indicating significant depressive symptoms [ 47 ]. The CES-D 10 was used because it has good reliability and validity in numerous studies [ 48 – 52 ]. The Arabic version of the CES-D 10 has shown good internal consistency reliability in previous studies conducted in the general population [ 53 ]. The CES-D 10 in this study demonstrated strong internal consistency, reflected by a Cronbach's alpha of .84. Generalized Anxiety Disorder-7 " GAD-7" The GAD-7 is a 7-item self-report tool created by Spitzer, Kroenke [ 54 ] to screen for and assess the severity of generalized anxiety disorder (GAD). It evaluates core diagnostic features of GAD based on DSM-IV criteria, For example “Not being able to stop or control worrying”. The scale uses a 4-point Likert scale, where responses range from 0 (not at all) to 3 (almost every day). Total scores can vary from 0 to 21 points, with scores above 10 indicating a clinical concern [ 54 ]. The GAD-7 has shown good internal consistency and reliability in previous research [ 55 , 56 ]. The GAD-7 scale's Arabic version was used in this study. Several Arabic studies have investigated the factor structure and psychometric qualities of the Arabic version of the GAD-7 [ 57 – 59 ]. According to the results, the scale is reliable and valid for use in research and diagnosis in Arabic-speaking nations. With a Cronbach's alpha of 0.84, the current study also showed high reliability for the GAD-7 scale. Data Analysis All analyses were conducted using SPSS version 21. For every variable being studied, descriptive statistics such as means, standard deviations, and frequencies were computed. Pearson correlation coefficients were calculated in order to evaluate the bivariate relationships among IGD, anxiety, and depression. The predicted associations between anxiety and depression on IGD scores were investigated using multiple linear regression analysis. Using G*Power, the sample size was determined with an effect size of f2 = 0.15 and the statistical test (multiple regression) specified. To evaluate multicollinearity, variance inflation factors (VIF) and tolerance values were computed for each predictor; all values were within acceptable ranges (VIF < 5). The assumptions of homoscedasticity, normality, linearity, and residual independence were evaluated and satisfied before the regression analysis was performed. For every statistical test, a significance limit of p < 0.05 was established. Results Understanding IGD in Saudi University Students Males constituted 55.5% (n = 201) of the sample, while females made up 44.5% (n = 161). The mean age of participants was 21.6 years (± 3.42). Regarding academic achievement, 27.3% of students were classified as good, 45.3% as average, and 27.3% as poor. The distribution of daily gaming hours showed that the majority fell into the below-average category (44.2%). The online gaming revolution, with a prevalence rate reaching 22.6%. (Table 1 ). Table 1 Study participants ( N = 362) Variables Categories f (%) or M ( SD) Age - 21.6 (3.42) years Gender Male 201 (55.5%) Female 161 (44.5%) Academic Achievement Good level 99 (27.3%) middle level 164 (45.3) Low level 99 (27.3) Time spent gaming every day ≤ 1 hour 25 (6.9%) 2–3 hours 120 (33.1%) 4–5 hours 150 (41.4%) ≥ 6 hours 67 (18.5%) IGD No 280 (77.3%) Yes 82 (22.6%) Table 2 illustrates the distribution of Internet Gaming Disorder (IGD) prevalence among participants according to key demographic variables. Chi-square tests revealed statistically significant differences across groups. Notably, males exhibited a substantially higher IGD prevalence rate (28.9%) compared to females (14.9%) (χ²(1) = 8.98, p = 0.003). Regarding academic performance, students with poor achievement levels had markedly greater IGD rates (48.0%) relative to those with moderate (14.0%) and high achievement (12.1%) (χ²(2) = 50.49, p < 0.001). Furthermore, a strong positive association was observed between daily gaming duration and IGD prevalence; only 4% of students gaming less than an hour per day met criteria for IGD, in contrast to 61.8% of those playing six or more hours daily (χ²(3) = 81.16, p < 0.001). These findings underscore that male gender, lower academic achievement, and increased daily gaming hours are significantly associated with elevated IGD risk. Consequently, these factors were controlled for in subsequent regression analyses. Table 2 Comparison of demographic characteristics by IGD among health sciences students (n = 362). Variables Non-IGD group n = 280(77.3%) IGD group N = 82(22.6%) Chi-squared (χ2) P Gender Male 143(71.14%) 58 (28.85) 8.98 0.004 Female 136(84.47%) 25(15.52) Academic Achievement Good 87(87.87) 12(12.12) 50.49 < 0.001 middle 141(85.97%) 23(14.2%) Weak 51(51.51) 48(48.48) Time spent gaming every day ≤ 1 hour 24 (96.00%) 1(4.00%) 81.16 < 0.001 2–3 hours 110 (91.66%) 10 (8.33%) 4–5 hours 120 (80.00%) 30(20.00%) ≥ 6 hours 25 (37.31%) 42 (62.68%) Note : Significant differences were found in IGD prevalence by gender, academic achievement, and daily gaming time. Table 3 One-Way ANOVA Results for IGD Scores by Academic Achievement and Daily Gaming Time (N = 362) Variables Category Mean IGD Score (M) SD M Standard Error p-value Academic Achievement Good 24.01 6.70 -5.14* 0.71 < .001 Middle 29.15 4.70 14.50* 0.72 < .001 Low 33.98 5.70 9.97* 0.80 < .001 Daily Gaming Time ≤ 1 hour 16.36 5.10 20.25* 0.94 < .001 2–3 hours 30.62 4.72 11.04* 0.65 < .001 4–5 hours 25.56 4.73 4.83* 0.72 < .001 ≥ 6 hours 36.61 4.34 - - - Note. Post hoc pairwise comparisons computed using Tukey HSD tests. All mean differences marked with * are statistically significant at p < .001. Table 3 presents the results of one-way ANOVA analyses comparing Internet Gaming Disorder (IGD) scores across categories of academic achievement and daily gaming durations. Statistically significant differences were found among all academic achievement groups (p < 0.001). Students classified with poor academic performance exhibited the highest IGD scores (M = 33.98, SD = 5.70), followed by those with moderate achievement (M = 29.15, SD = 4.74), and students achieving a high academic level (M = 24.01, SD = 6.68). Post hoc Tukey HSD tests confirmed significant pairwise differences among all groups, indicating a gradation in IGD severity associated with academic performance. Similarly, significant differences were observed related to daily gaming duration. Participants who engaged in gaming for six or more hours per day scored significantly higher on the IGD scale (M = 36.61, SD = 4.34) compared to those gaming less than one hour daily (M = 16.36, SD = 5.10), with all intermediate gaming duration groups showing incremental increases in IGD scores (p < 0.001). These differences were also supported by Tukey's post hoc comparisons. It is essential to clarify that these observed differences denote statistical associations without implying causal relationships given the cross-sectional study design. Additionally, the cutoff score used to define IGD categorization was applied consistently, though cultural and environmental considerations may influence the generalizability of this threshold. These results underscore the relevance of academic achievement and gaming duration as key factors associated with IGD severity among health sciences students and justify their inclusion as covariates in subsequent multivariate analyses. Table 4 Comparison of Depression and Anxiety Scores Between IGD and Non-IGD Groups via t-test. ( N = 362) Group f M SD i (df) p Depression IGD 82 14.45 1.84 20.40 (360) < .001 Non-IGD 280 9.98 1.72 Anxiety IGD 82 13.87 2.12 15.102 (360) < .001 Non-IGD 280 9.21 1.86 Table 4 presents a comparison of depression and anxiety scores between participants diagnosed with Internet Gaming Disorder (IGD) and those without the disorder (N = 362). Independent samples t-tests revealed statistically significant differences between the two groups. Participants with IGD demonstrated higher mean depression scores (M = 14.45, SD = 1.84) compared to those without IGD (M = 9.98, SD = 1.72). Similarly, anxiety scores were elevated in the IGD group (M = 13.87, SD = 2.12) relative to the non-IGD group (M = 9.21, SD = 1.86). These differences were significant at the p < 0.001 level. It is important to emphasize that these results represent associations rather than causal relationships due to the cross-sectional design of the study. These results underscore the multifactorial nature of IGD and highlight the importance of considering psychological and academic factors in future research and interventions. Table 5 Multiple Regression Predicting IGD Scores Including Psychological and Demographic Predictors Predictor B SE β (Standardized) t P-value VIF Constant 1.19 1.39 - 0.55 < .001 - Anxiety 0.70 0.094 0.42 7.45 < .001 2.8 Depression 1.01 0.85 0.39 11.88 < .001 2.7 Gender 2.34 1.95 0.05 1.20 < .001 1.3 Academic Achievement 3.95 0.74 0.41 5.34 < .001 1.6 Gaming Time 4.77 0.95 0.58 5.02 < .001 2.2 Model summary: F(5, 356) = 68.24, R² = .48, Adj. R² = .47, Durbin–Watson = 1.86 Note: VIF = Variance Inflation Factor indicating multicollinearity. Table 5 presents the results of a multiple regression analysis predicting IGD scores. The overall model was significant, F(5,356) = 68.24, F(5,356) = 68.24, R2 = 0.48R2 = 0.48, Adjusted R2 = 0.47R2 = 0.47, p<.001p<.001, accounting for 48% of the variance in IGD severity. Depression (β = 0.39β = 0.39, p<.001p<.001) and anxiety (β = 0.42β = 0.42, p<.001p<.001) emerged as significant independent psychological predictors. Among demographic and behavioral predictors, academic achievement (β = 0.41β = 0.41, p<.001p<.001) and daily gaming time (β = 0.58β = 0.58, p<.001p<.001) significantly contributed to the model. Gender had a minimal effect (β = 0.05β = 0.05) and was not statistically significant (p=.230p=.230), suggesting limited influence on IGD severity in this sample. Variance inflation factors below 3 indicated no multicollinearity concerns, and the Durbin–Watson statistic of 1.86 suggested no serious autocorrelation. These results demonstrate that IGD severity is strongly associated with anxiety, depression symptoms, academic performance, and gaming duration, while gender plays a negligible role. Discussion Despite Saudi Arabia ranking sixth globally in online video game participation at 92.3%, research on the relationship between depression, anxiety, and IGD remains limited. This exploratory study is among the few that examine this association specifically among health sciences students in southern Saudi Arabia. It found that 22.6% of participants met the criteria for IGD, classifying them as troubled players according to the recommended cut-off of 32 points. This prevalence is consistent with prior studies reporting rates between 19% and 27% among students [60–63] . In contrast, earlier research conducted before the COVID-19 pandemic reported lower rates of 8–10% [64–67] . Moreover, university students in Saudi Arabia [68] , demonstrated a marked increase in gaming behaviors during periods of social isolation. Recent literature suggests that pandemic-related stress and isolation may have contributed to higher IGD rates among university students in several countries, including Saudi Arabia [69] , Collectively, these findings highlight IGD as a growing public health concern warranting further investigation. The present study also revealed that daily gaming time was strongly associated with IGD severity. Participants who reported gaming for more than six hours per day scored significantly higher on the IGD scale, a finding consistent with prior meta-analyses that identified gaming duration as a critical risk factor [70] . Those who played four to five hours daily also exhibited elevated scores, suggesting that preventive interventions targeted at this group could be effective in reducing risk. These results align with previous studies consistently linking gaming duration to greater IGD severity [1, 62, 71] . Gender differences also emerged, with prevalence rates of 10.1% among males compared to 6.3% among females. This pattern aligns with studies conducted within the Saudi population, including previous investigations[ 18 , 72 ]. Comparable trends have been reported in other Arab contexts; for example, an Egyptian study found IGD prevalence at 12.3% among males and 4.4% among females. Additional research [ 40 , 73 , 74 ], further supports the link between IGD and gender. The higher prevalence among males may reflect stronger responsiveness to gaming-related rewards, increased cravings, and reduced inhibitory control [ 74 ]. Furthermore, the gaming industry’s emphasis on male audiences may also contribute to the disproportionate risk [ 75 ]. Academic performance was another area of concern. A one-way analysis of variance revealed significant differences in IGD scores based on academic proficiency. Specifically, students with higher IGD scores reported lower academic achievement. This result is consistent with previous research documenting reduced academic outcomes among individuals with IGD[ 1 , 50 , 76 ]. Lower performance may be explained by the large amount of time devoted to gaming, particularly on school days, which often leads to sleep deprivation and diminished classroom concentration [ 77 ]. Many students become preoccupied with gaming, even waking during the night to continue playing, resulting in constant thoughts about gaming or continuous play. Consequently, assignments and homework are neglected, and sleep-deprived students struggle to focus and learn effectively[ 1 ]. The primary focus of this study was the relationship between IGD and mental health symptoms. Pearson’s correlation coefficients revealed strong positive associations between IGD, anxiety, and depression. When comparing students with IGD to those without, the IGD group reported significantly higher levels of depression and anxiety. Multiple linear regression analyses further demonstrated that both anxiety (β = 0.70, p < .001) and depression (β = 1.01, p < .001) were strong predictors of IGD scores, indicating that a substantial portion of variance in IGD severity can be attributed to mental health symptoms. Moreover, hierarchical regression analysis confirmed that depression and anxiety significantly affected IGD scores even after adjusting for demographic factors. After controlling for gender, academic performance, and daily gaming duration, both variables remained significant predictors. This final model displayed improved explanatory power (adjusted R² = 0.48), underscoring the robust influence of mental health on IGD, independent of behavioral and demographic factors. Also, the significant associations between IGD severity and increased depression and anxiety are consistent with the (interaction of person-affect-cognition-execution) I-PACE model [ 26 ], which highlights affective and cognitive vulnerabilities as central to addictive internet behaviors. The Compensatory Internet Use Model [ 27 ], further supports that students may use gaming as an avoidant coping strategy in response to academic and psychological stressors. These models underscore the complex etiological pathways involved in IGD and provide targets for tailored intervention strategies in this population. Overall, the findings of this study are consistent with international research documenting the negative impact of IGD on psychological well-being. Nevertheless, these results should be interpreted cautiously in light of certain limitations. The use of a convenience sample of health sciences students limits generalizability, while reliance on self-reported questionnaires rather than clinical interviews may have introduced reporting bias. Furthermore, the cross-sectional design prevents firm conclusions regarding causality or directionality. Future research in Saudi Arabia should adopt larger and more diverse samples, utilize longitudinal designs, and incorporate qualitative methods to better understand the mechanisms linking IGD with mental health. Such approaches would help identify risk factors, develop culturally appropriate screening tools, and guide targeted interventions to mitigate the academic, social, and psychological consequences of problematic gaming. Conclusions and Recommendation The current study highlights a concerning prevalence of IGD among health sciences students and identifies a significant correlation between IGD, depression, and anxiety. Despite certain limitations, these findings emphasize the urgent need for preventive measures and interventions to address IGD in young people. The primary objective of this research was to examine the relationship between IGD and mental health issues, specifically depression and anxiety, among health sciences students in southern Saudi Arabia. While the study has limitations, it contributes to a better understanding of IGD within this demographic. The results suggest that IGD, often viewed as a non-substance-related dependency, shares characteristics and mechanisms with substance use disorders, which has important implications for interventions and public health policy. Notably, the findings are consistent with existing literature, indicating that addictive behaviors like IGD are linked to various mental health issues, including anxiety disorders, depression, and stress [ 14 , 22 , 24 ]. Young people, including health sciences students, hold the key to a society's future. However, addiction and mental illness can hinder their potential, leading to significant costs and consequences, including dropouts, job losses, and absenteeism. These challenges can result in long-term disabilities and even premature death from suicide or stress-related lifestyle disorders. Therefore, the current findings underscore the urgent need to develop interventions and strategies to prevent IGD, especially among adolescents and young adults. The first step in this direction is to identify the risk and protective factors that affect IGD and understand the causal mechanisms. For example, users with IGD tend to start playing online games at a relatively young age, so early start playing may be a risk factor for IGD. Accordingly, diverse and exciting early educational curricula are needed to build immunity against online game addiction in adolescents and young adults. Also, integrate educational programs into school curriculums that promote healthy gaming habits, responsible technology use, and strategies for managing screen time. Parents should pay special attention to their children's video game playtime to enhance their psychological and social well-being. Implementing preventative measures and early interventions is essential for limiting the negative effects of IGD. The researchers suggest conducting longitudinal studies with larger and more diverse samples to explore the causal relationships between IGD, mental health symptoms, and other relevant factors. COVID-19 impact: Investigate the specific influence of the COVID-19 pandemic on IGD development and explore whether the observed high prevalence is temporary or a long-term trend. Intervention efficacy: Evaluate the effectiveness of different preventive and treatment interventions for IGD among young people. Qualitative studies: Conduct qualitative studies to gain a deeper understanding of the experiences, motivations, and challenges faced by individuals with IGD. Declarations Authors contributions All authors: conceived of the presented idea. MH, N. A, H.A., P.S, E.M, M.W., and H.F.A: Conceptualization. N.A, M.H. E.M. M.W., and H. A: Data Collection. M.H, P.S and N.A. Data Analysis. N.A, H.A., H.A, P.S, E.M., and M.H: Resources. M.H., N.A., H.H. P.S, E.M. M.W., and H.A: Writing—Original Draft Preparation, Writing—Review & Editing. H. A: Funding Acquisition. All authors conceptualized the study, collected, analyzed, interpreted the data and writing the manuscript. Funding This work was supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2026R707), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Declaration of Interest Statement: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethics approval and consent to participation Ethical approval was obtained from the Institutional Review Board (IRB) of the Deanship of Scientific Research at Najran University, Najran, Saudi Arabia, No (NU/IFC/2/SEHRC/-/19). Informed consent was obtained electronically at the beginning of the online questionnaire. All participants were required to read the consent statement and indicate their agreement before proceeding. Participation was voluntary, all information was kept strictly confidential, and the data were used solely for scientific research purposes. Only participants who agreed to the study conditions and provided informed consent proceeded to complete the study instruments. Furthermore, all procedures performed in this study were conducted in accordance with the ethical standards of the Declaration of Helsinki. Consent to participate. Informed consent was obtained from all individual participants included in the study. Consent to publish: Not applicable Availability of data and material The data is available on request by the corresponding author. References Hawi, N. S., Samaha, M. & Griffiths, M. D. Internet gaming disorder in Lebanon: Relationships with age, sleep habits, and academic achievement. J. Behav. addictions . 7 (1), 70–78 (2018). American Psychiatric Association, D. and, American Psychiatric, D. & Association Diagnostic and statistical manual of mental disorders: DSM-5 Vol. 5 (American psychiatric association Washington, DC, 2013). Lam, L. T. et al. The association between internet addiction and self-injurious behaviour among adolescents. Inj. Prev. 15 (6), 403–408 (2009). Gentile, A. J. et al. 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Clarification of the cut-off score for nine-item Internet Gaming Disorder Scale–Short Form (IGDS9-SF) in a Chinese context. Front. Psychiatry . 11 , 470 (2020). Beranuy, M. et al. Spanish validation of the internet gaming disorder scale–short form (IGDS9-SF): Prevalence and relationship with online gambling and quality of life. Int. J. Environ. Res. Public Health . 17 (5), 1562 (2020). Poon, L. Y. et al. Psychometric properties of the internet gaming disorder scale–short-form (IGDS9-SF): Systematic review. J. Med. Internet. Res. 23 (10), e26821 (2021). Sánchez-Iglesias, I. et al. Spanish validation and scoring of the internet gaming disorder scale-short-form (IGDS9-SF). Span. J. Psychol. 23 , e22 (2020). El Keshky, M. E. S., T.J.F.i.P, H. & Alballa Factor structure and psychometric properties of an Arabic version of the Internet Gaming Disorder Scale, short form (IGDS-SF9) . 11 : p. 1231550. (2023). Andresen, E. M. et al. Screening for depression in well older adults: evaluation of. Prev. Med. 10 , 77–84 (1994). Jiang, L. et al. The reliability and validity of the center for epidemiologic studies depression scale (CES-D) for Chinese university students. Front. Psychiatry . 10 , 315 (2019). Hammad, M. A. & Awed, H. S. Investigating the relationship between social media addiction and mental health. Nurture 17 (3), 149–156 (2023). Hammad, M. A. & Awed, H. S. The use of social media and its relationship to psychological alienation and academic procrastination. Int. J. Membrane Sci. Technol. 10 (2), 332–340 (2023). Al Harthy, S. S., Hammad, M. A. & Awed, H. S. Association between social inclusion and mental health among people with disabilities engaged in sports clubs: a cross-sectional survey. Front. Psychol. 16 , 1504352 (2025). Al-Shahrani, H. F. & Hammad, M. A. Mental health disorders and quality of life among Saudi women who have experienced domestic violence. Front. Public. Health . 13 , 1568733 (2025). RAMI, Y. et al. Psychometric properties of the Moroccan dialect versions of the Perceived Stress Scale and the Center for Epidemiologic Studies Depression Scale among Moroccan university students . 9 (4): pp. 583–594. (2024). Spitzer, R. L. et al. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch. Intern. Med. 166 (10), 1092–1097 (2006). DeMartini, J., Patel, G. & Fancher, T. L. Generalized anxiety disorder. Ann. Intern. Med. 170 (7), ITC49–ITC64 (2019). Tong, X. et al. Validation of the Generalized Anxiety Disorder-7 (GAD-7) among Chinese people with epilepsy. Epilepsy Res. 120 , 31–36 (2016). Sawaya, H. et al. Adaptation and initial validation of the Patient Health Questionnaire–9 (PHQ-9) and the Generalized Anxiety Disorder–7 Questionnaire (GAD-7) in an Arabic speaking Lebanese psychiatric outpatient sample . 239 : pp. 245–252. (2016). Khoury-Malhame, M. E. et al. Psychometric validation of the Arabic version of the GAD-7 among Lebanese Adolescents . 20 (8): p. e0329627. (2025). Yousuf, M. et al. Patient health questionnaire-9 and generalized anxiety discorders-7: Arabic version reliability in Jordan. 56(3). (2022). Swain, R. & Ojha, J. Prevalence of Rate of Internet Gaming Disorder and its Association with Substance Abuse and Psychosocial Behavior among Undergraduate Students . Int. J. Innovative Sci. Res. Technol. , : pp. 2145–2151. (2025). Hammad, M. A. & Al-shahrani, H. F. Impulsivity and aggression as risk factors for internet gaming disorder among university students. Sci. Rep. 14 (1), 3712 (2024). Al Sunni, A. & Latif, R. Determining the effectiveness of a cell phone-based student response system. J. Taibah Univ. Med. Sci. 15 (1), 59–65 (2020). Bumozah, H. S., Al-Quwaidhi, A. J. & Rahmah, A. G. J. C. Prevalence and risk factors of internet gaming disorder among female secondary school students in Al-Ahsa, Kingdom of Saudi Arabia . 15 (6). (2023). Fam, J. Y. J.S.j.o.p., Prevalence of internet gaming disorder in adolescents: A meta-analysis across three decades . 59 (5): pp. 524–531. (2018). Al Asqah, M. I. et al. The prevalence of internet gaming disorder among medical students at King Saud University, Riyadh, Saudi Arabia. A cross-sectional study. Saudi Med. J. 41 (12), 1359–1363 (2020). Poli, R. and E.J.N.j.o.p. Agrimi, Internet addiction disorder: prevalence in an Italian student population . 66 (1): pp. 55–59. (2012). Canan, F. et al. The association between Internet addiction and dissociation among Turkish college students . 53 (5): pp. 422–426. (2012). Alsaad, A. J. et al. Impact of the COVID-19 pandemic quarantine on gaming behavior among children and adolescents in the Eastern Province of Saudi Arabia. Int. J. Med. Developing Ctries. 5 (4), 1007–1007 (2021). Volpe, U. et al. COVID-19-related social isolation predispose to problematic internet and online video gaming use in Italy. 19(3): p. 1539. (2022). Gao, Y. X., Wang, J. Y. & Dong, G. H. The prevalence and possible risk factors of internet gaming disorder among adolescents and young adults: Systematic reviews and meta-analyses. J. Psychiatr. Res. 154 , 35–43 (2022). Alenezi, S. et al. Prevalence and Associated Factors of Internet Gaming Disorder among Residents in Saudi Arabia: A Cross-Sectional Study. (2023). Rajab, A. M. et al. Gaming addiction and perceived stress among Saudi adolescents. Addict. Behav. Rep. 11 , 100261 (2020). Aggarwal, A. & Pandian, J. D. Internet gaming disorder in undergraduate medical and dentistry students. CHRISMED J. Health Res. 6 (4), 237–241 (2019). Dong, G. H. & Potenza, M. N. Considering gender differences in the study and treatment of internet gaming disorder. J. Psychiatr. Res. 153 , 25–29 (2022). Cheng, C., Cheung, M. W. L. & Wang, H. Multinational comparison of internet gaming disorder and psychosocial problems versus well-being: Meta-analysis of 20 countries. Comput. Hum. Behav. 88 , 153–167 (2018). Brunborg, G. S., Mentzoni, R. A. & Frøyland, L. R. Is video gaming, or video game addiction, associated with depression, academic achievement, heavy episodic drinking, or conduct problems? J. Behav. addictions . 3 (1), 27–32 (2014). Ko, C. Internet gaming disorder Curr. Addict. Rep. , 1 , 177–185. (2014). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 03 May, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers invited by journal 07 Apr, 2026 Editor invited by journal 16 Mar, 2026 Editor assigned by journal 11 Mar, 2026 Submission checks completed at journal 11 Mar, 2026 First submitted to journal 07 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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This has led to the classification of Internet Gaming Disorder (IGD) as a potential disorder requiring further research before full inclusion in diagnostic manuals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Paralleling other addictive behaviors like overeating, alcoholism, and drug abuse, IGD has become a major concern within internet addiction research [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, a core focus remains: identifying individuals who exhibit impaired control over gaming and experience significant negative consequences [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This growing recognition culminated in the official classification of IGD as a behavioral addiction by the American Psychiatric Association in 2013 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. making it the second such designation after gambling addiction. Similarly, In 2018, the World Health Organization recognized Internet gaming addiction as one of the addictive behavioral disorders in the eleventh revision of the International Classification of Diseases (ICD-11) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Viewed as a chronic mental disorder [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], IGD manifests through symptoms like a lack of ability to regulate playtime, loss of interest in social activities, and a sense of deprivation when not gaming, regardless of the negative effects [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This process often results in neglecting studies, sleep, nutrition, hobbies, and social life in favor of excessive gaming [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The cycle can become self-perpetuating, with individuals seeking to escape dissatisfaction through online gaming but ultimately experiencing further isolation and and poor health outcomes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVariations in survey methods, cultural settings, and diagnostic criteria account for the wide range of IGD prevalence estimates, which extend from under 1% to over 27% across age groups and countries [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. For instance, while Germany reported a documented prevalence of 11%, South Korea had a lower prevalence of 8%, and Iran reported 17% [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In Saudi Arabia, internet adoption and digital connectivity have grown substantially over the past decade, with penetration reaching nearly 98% by 2023. This rapid growth has fueled the expansion of the gaming sector, making Saudi Arabia one of the largest gaming markets in the Middle East and North Africa[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt the same time, the blurred boundary between healthy gaming and outright addiction has raised concerns among educators, psychologists, parents, and policymakers in Saudi Arabia, especially in specific student groups such as those enrolled in health-related discipline[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Investigating IGD within this student population warrants serious attention, as health sciences students often face demanding academic routines that include coursework, clinical placements, late-night study sessions, and constant pressure to excel [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. They frequently transition in a single day from lecture halls to laboratories to hospital wards, each requiring intense focus, strict time management, and significant emotional resilience. Consequently, this demanding lifestyle can deplete psychological energy, creating fertile ground for burnout and recurrent stress. To cope with these pressures, many students turn to digital spaces, with video games serving as one of the most accessible and least stigmatized forms of escapism[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, online games\u0026mdash;built on electronics and visuals\u0026mdash;are immensely popular across diverse groups, offering participants competition, challenge, excitement, and, in some cases, enjoyment of violent play. Examples include PUBG, Fortnite, Call of Duty: Mobile, FIFA, and League of Legends[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Nevertheless, this enjoyment can become a double-edged sword, as IGD has been linked to a variety of adverse mental health outcomes, including depression, anxiety disorders, anger control problems, emotional distress, neuroticism, low self-esteem, impulsivity, pathological gambling, and poor emotional regulation[\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Theoretical frameworks such as the Interaction of Person-Affect-Cognition-Execution (I-PACE) model [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], and the Compensatory Internet Use Model [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], provide comprehensive explanations for the development and maintenance of Internet Gaming Disorder (IGD), emphasizing complex interactions of emotional, cognitive, and behavioral factors especially in vulnerable populations experiencing psychological distress or academic pressure.\u003c/p\u003e \u003cp\u003eGiven the high prevalence of IGD among young people and its harmful effects, researchers worldwide have conducted numerous studies on the relationship between online gaming, mental health, and quality of life [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Likewise, Luntungan, Pitoy [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] found that most respondents in the gaming group had poor mental health. Furthermore, increasing time spent online is strongly associated with higher risks of clinical depression [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. A survey of 987 Indian adolescents also showed that those with higher levels of internet addiction reported greater anxiety and depression [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn terms of gender differences, evidence consistently indicates a male predominance in IGD [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. A Canadian study on internet use by Quebec students reported that boys spend significantly more time online gaming, whereas girls more often use the internet for social media [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Neuroimaging research further shows greater brain activity during gaming in males compared to females [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Overall, most studies suggest that males are two to three times more likely to develop IGD than females [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In contrast, some findings indicate that females tend to use the internet primarily for social interaction, while males prefer online gaming [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Additionally, the time an individual spends playing video games is closely tied to IGD risk. Excessive playtime has been associated with psychological problems such as depression [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], anxiety [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and sleep loss [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. A study by Wartberg, Kriston [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. demonstrated that prolonged play is linked to numerous negative outcomes, including generalized anxiety, depressive symptoms, stress, social fears, and social anxiety. Educational level plays a role as well: first- and second-year students often have more flexible schedules and fewer clinical obligations, allowing longer play sessions, whereas seniors typically restrict gaming due to internships, capstone projects, and job-seeking responsibilities.\u003c/p\u003e \u003cp\u003eThis literature highlights the increasing challenge concerning excessive online gaming and its dangerous effects, especially among young people. Although studies on IGD have grown, there's still a lack of studies investigating the link between IGD and mental health problems in Saudi Arabia, specifically among health sciences students. To fill this gap, this cross-sectional study examines the relationships between IGD, depression and anxiety in health science students, considering variations based on playtime, gender, and academic performance. More specifically, this study addresses three interrelated research questions:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWhat is the prevalence of IGD among health science students in southern Saudi Arabia?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHow does IGD correlate with depression and anxiety?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAre demographic factors-gender, academic level, and daily gaming hours-associated with variations in IGD severity?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDo depression and anxiety significantly predict the level of IGD?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eStudy Design\u003c/p\u003e \u003cp\u003eThe predicted associations between depression, anxiety, and IGD among Saudi Arabian health sciences students were investigated in this study using a cross-sectional correlational approach. Standardized psychometric questionnaires that were distributed online were used to gather data. Using regression and correlation analysis, the main objective was to determine if anxiety and depression significantly predict IGD scores.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e Participants in this exploratory study, which employed a cross-sectional design, were recruited from students at the College of Health Sciences at Najran University in southern Saudi Arabia using convenience sampling. An electronic survey was distributed via Google Forms to students who were available and willing to participate during the study period, from March 24 to May 5, 2024. This distribution was coordinated with the university administration to maximize participant access.\u003c/p\u003e\u003cp\u003eThe final number of participants was 362 male and female students, exceeding the minimum sample size of 138. This determination was based on a priori statistical power analysis conducted using G*Power 3.1, with an assumed statistical power of 90%, a significance level of 0.05, and a medium effect size of f2\u0026thinsp;=\u0026thinsp;0.15. The mean age of participants was 21.6 years (standard deviation\u0026thinsp;=\u0026thinsp;3.42). The conditions for participation included enrollment in a four-year bachelor's program, being over 18 years of age, proficiency in the Arabic language, and voluntary consent to participate.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eData for the current study was collected through an online survey from 24 March to 5 May 2024. A study invitation containing the information package related to the participating study questionnaires (Google Forms) was sent to randomly selected students from the undergraduate health sciences students at Najran University. The information package outlined the study's purpose, procedures, and participants' rights, including voluntary consent, anonymity, confidentiality, and the right to withdraw consent at any time. Prior to the study's commencement, the Ethics Committee of the Deanship of Scientific Research at Najran University, Saudi Arabia, approved the study and its procedures. which comply with the latest version of the Declaration of Helsinki. All participants also signed written informed consent.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eTools\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic survey\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eParticipants were asked to provide information about the year of the study, their gender, age, and the average number of hours they spend playing online games each day. Academic achievement was assessed using a self-rated scale that categorizes students into three levels: good, average, and low. These categories are based on students' cumulative GPA ranges, aligned with the university's grading system: good (3.5\u0026ndash;4.0), average (2.5\u0026ndash;3.49), and low (\u0026lt;\u0026thinsp;2.5). This categorization aims to reflect academic performance in relation to the study's focus on ADHD risk factors. Future research could enhance the reliability of results by utilizing formal academic records or standardized assessment measures.\u003c/p\u003e \u003cp\u003e.\u003cb\u003eInternet Games Disorder Scale - Short Model (IGDS9-SF)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe IGDS9-SF, created by Pontes and Griffiths [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], is a validated 9-item screening instrument designed to identify potential IGD based on the nine core criteria outlined in the DSM-5, For example, \u0026ldquo;Have you lost interests in previous hobbies and other entertainment activities as a result of your engagement with the game?\u0026rdquo;. This score assesses the severity of gaming disorder by rating the frequency of gaming over the past 12 months. It uses a five-point Likert scale, ranging from 1 (never) to 5 (very often), with total scores ranging from 9 to 45. Higher scores indicate a greater risk of developing gaming disorder, with a cut-off score of 32 or greater suggesting possible IGD[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The IGDS9-SF has been widely used in international studies and has demonstrated strong psychometric properties across different cultural contexts [\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe IGDS9-SF scale's Arabic version was used in this study. Research was done by El Keshky and Alballa [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] to confirm the Arabic version's factor structure and psychometric qualities. According to the results, the scale is reliable and valid for use in research and diagnosis in Arabic-speaking nations. With a Cronbach's alpha of 0.92, the current study also showed high reliability for the IGDS9-SF scale.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCentre for Epidemiological Studies Depression Scale (CES-D 10)\u003c/h3\u003e\n\u003cp\u003eThe CES-D 10 [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] is a self-report scale consisting of 10 items that measures depressive symptoms experienced in the past week. It assesses different aspects of depression, including negative affect, positive affect, and physical symptoms for example, \u0026ldquo;I was bothered by things that usually don't bother me; I felt hopeful about the future\u0026rdquo;. Responses are rated on a 4-point scale, ranging from 0 (rarely or none of the time) to 3 (most or all of the time), with items 5 and 8 scored in reverse. Total scores can range from 0 to 30, with scores of 10 or higher indicating significant depressive symptoms [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The CES-D 10 was used because it has good reliability and validity in numerous studies [\u003cspan additionalcitationids=\"CR49 CR50 CR51\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. The Arabic version of the CES-D 10 has shown good internal consistency reliability in previous studies conducted in the general population [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The CES-D 10 in this study demonstrated strong internal consistency, reflected by a Cronbach's alpha of .84.\u003c/p\u003e \u003cp\u003e \u003cb\u003eGeneralized\u003c/b\u003e \u003cb\u003eAnxiety Disorder-7 \" GAD-7\"\u003c/b\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe GAD-7 is a 7-item self-report tool created by Spitzer, Kroenke [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] to screen for and assess the severity of generalized anxiety disorder (GAD). It evaluates core diagnostic features of GAD based on DSM-IV criteria, For example \u0026ldquo;Not being able to stop or control worrying\u0026rdquo;. The scale uses a 4-point Likert scale, where responses range from 0 (not at all) to 3 (almost every day). Total scores can vary from 0 to 21 points, with scores above 10 indicating a clinical concern [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The GAD-7 has shown good internal consistency and reliability in previous research [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe GAD-7 scale's Arabic version was used in this study. Several Arabic studies have investigated the factor structure and psychometric qualities of the Arabic version of the GAD-7 [\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. According to the results, the scale is reliable and valid for use in research and diagnosis in Arabic-speaking nations. With a Cronbach's alpha of 0.84, the current study also showed high reliability for the GAD-7 scale.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eAll analyses were conducted using SPSS version 21. For every variable being studied, descriptive statistics such as means, standard deviations, and frequencies were computed. Pearson correlation coefficients were calculated in order to evaluate the bivariate relationships among IGD, anxiety, and depression. The predicted associations between anxiety and depression on IGD scores were investigated using multiple linear regression analysis. Using G*Power, the sample size was determined with an effect size of f2\u0026thinsp;=\u0026thinsp;0.15 and the statistical test (multiple regression) specified. To evaluate multicollinearity, variance inflation factors (VIF) and tolerance values were computed for each predictor; all values were within acceptable ranges (VIF\u0026thinsp;\u0026lt;\u0026thinsp;5). The assumptions of homoscedasticity, normality, linearity, and residual independence were evaluated and satisfied before the regression analysis was performed. For every statistical test, a significance limit of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was established.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":" \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eUnderstanding \u003cem\u003eIGD in Saudi University Students\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eMales constituted 55.5% (n\u0026thinsp;=\u0026thinsp;201) of the sample, while females made up 44.5% (n\u0026thinsp;=\u0026thinsp;161). The mean age of participants was 21.6 years (\u0026plusmn;\u0026thinsp;3.42). Regarding academic achievement, 27.3% of students were classified as good, 45.3% as average, and 27.3% as poor. The distribution of daily gaming hours showed that the majority fell into the below-average category (44.2%). The online gaming revolution, with a prevalence rate reaching 22.6%. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eStudy participants (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;362)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ef\u003c/em\u003e (%) or \u003cem\u003eM\u003c/em\u003e (\u003cem\u003eSD)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.6 (3.42) years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e201 (55.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e161 (44.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAcademic Achievement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emiddle level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164 (45.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (27.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTime spent gaming every day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1 hour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026ndash;3 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (33.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026ndash;5 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150 (41.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;6 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (18.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e280 (77.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82 (22.6%)\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\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the distribution of Internet Gaming Disorder (IGD) prevalence among participants according to key demographic variables. Chi-square tests revealed statistically significant differences across groups. Notably, males exhibited a substantially higher IGD prevalence rate (28.9%) compared to females (14.9%) (χ\u0026sup2;(1)\u0026thinsp;=\u0026thinsp;8.98, p\u0026thinsp;=\u0026thinsp;0.003). Regarding academic performance, students with poor achievement levels had markedly greater IGD rates (48.0%) relative to those with moderate (14.0%) and high achievement (12.1%) (χ\u0026sup2;(2)\u0026thinsp;=\u0026thinsp;50.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, a strong positive association was observed between daily gaming duration and IGD prevalence; only 4% of students gaming less than an hour per day met criteria for IGD, in contrast to 61.8% of those playing six or more hours daily (χ\u0026sup2;(3)\u0026thinsp;=\u0026thinsp;81.16, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings underscore that male gender, lower academic achievement, and increased daily gaming hours are significantly associated with elevated IGD risk. Consequently, these factors were controlled for in subsequent regression analyses.\u003c/p\u003e \u003c/div\u003e \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\u003eComparison of demographic characteristics by IGD among health sciences students (n\u0026thinsp;=\u0026thinsp;362).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-IGD group\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;280(77.3%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIGD group\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;82(22.6%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eChi-squared (χ2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e143(71.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58 (28.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e8.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e136(84.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25(15.52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAcademic Achievement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87(87.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12(12.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e50.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e141(85.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23(14.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51(51.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48(48.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTime spent gaming every day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1 hour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (96.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1(4.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e81.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026ndash;3 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110 (91.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026ndash;5 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120 (80.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30(20.00%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;6 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (37.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42 (62.68%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote\u003c/em\u003e: Significant differences were found in IGD prevalence by gender, academic achievement, and daily gaming time.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOne-Way ANOVA Results for IGD Scores by Academic Achievement and Daily Gaming Time (N\u0026thinsp;=\u0026thinsp;362)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean IGD Score (M)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\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\u003eAcademic Achievement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-5.14*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.50*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\u003e33.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.97*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily Gaming Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1 hour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.25*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026ndash;3 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.04*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026ndash;5 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.83*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;6 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote.\u003c/em\u003e Post hoc pairwise comparisons computed using Tukey HSD tests. All mean differences marked with * are statistically significant at p \u0026lt; .001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results of one-way ANOVA analyses comparing Internet Gaming Disorder (IGD) scores across categories of academic achievement and daily gaming durations. Statistically significant differences were found among all academic achievement groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Students classified with poor academic performance exhibited the highest IGD scores (M\u0026thinsp;=\u0026thinsp;33.98, SD\u0026thinsp;=\u0026thinsp;5.70), followed by those with moderate achievement (M\u0026thinsp;=\u0026thinsp;29.15, SD\u0026thinsp;=\u0026thinsp;4.74), and students achieving a high academic level (M\u0026thinsp;=\u0026thinsp;24.01, SD\u0026thinsp;=\u0026thinsp;6.68). Post hoc Tukey HSD tests confirmed significant pairwise differences among all groups, indicating a gradation in IGD severity associated with academic performance. Similarly, significant differences were observed related to daily gaming duration. Participants who engaged in gaming for six or more hours per day scored significantly higher on the IGD scale (M\u0026thinsp;=\u0026thinsp;36.61, SD\u0026thinsp;=\u0026thinsp;4.34) compared to those gaming less than one hour daily (M\u0026thinsp;=\u0026thinsp;16.36, SD\u0026thinsp;=\u0026thinsp;5.10), with all intermediate gaming duration groups showing incremental increases in IGD scores (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These differences were also supported by Tukey's post hoc comparisons.\u003c/p\u003e \u003cp\u003eIt is essential to clarify that these observed differences denote statistical associations without implying causal relationships given the cross-sectional study design. Additionally, the cutoff score used to define IGD categorization was applied consistently, though cultural and environmental considerations may influence the generalizability of this threshold. These results underscore the relevance of academic achievement and gaming duration as key factors associated with IGD severity among health sciences students and justify their inclusion as covariates in subsequent multivariate analyses.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Depression and Anxiety Scores Between IGD and Non-IGD Groups via t-test. (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;362)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ef\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ei\u003c/em\u003e (df)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e20.40 (360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-IGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e15.102 (360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-IGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.86\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents a comparison of depression and anxiety scores between participants diagnosed with Internet Gaming Disorder (IGD) and those without the disorder (N\u0026thinsp;=\u0026thinsp;362). Independent samples t-tests revealed statistically significant differences between the two groups. Participants with IGD demonstrated higher mean depression scores (M\u0026thinsp;=\u0026thinsp;14.45, SD\u0026thinsp;=\u0026thinsp;1.84) compared to those without IGD (M\u0026thinsp;=\u0026thinsp;9.98, SD\u0026thinsp;=\u0026thinsp;1.72). Similarly, anxiety scores were elevated in the IGD group (M\u0026thinsp;=\u0026thinsp;13.87, SD\u0026thinsp;=\u0026thinsp;2.12) relative to the non-IGD group (M\u0026thinsp;=\u0026thinsp;9.21, SD\u0026thinsp;=\u0026thinsp;1.86). These differences were significant at the p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 level. It is important to emphasize that these results represent associations rather than causal relationships due to the cross-sectional design of the study. These results underscore the multifactorial nature of IGD and highlight the importance of considering psychological and academic factors in future research and interventions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Regression Predicting IGD Scores Including Psychological and Demographic Predictors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ (Standardized)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic Achievement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGaming Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eModel summary: F(5, 356)\u0026thinsp;=\u0026thinsp;68.24, R\u0026sup2; = .48, Adj. R\u0026sup2; = .47, Durbin\u0026ndash;Watson\u0026thinsp;=\u0026thinsp;1.86\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote: VIF\u0026thinsp;=\u003c/em\u003e\u0026thinsp;Variance Inflation Factor indicating multicollinearity.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the results of a multiple regression analysis predicting IGD scores. The overall model was significant, F(5,356)\u0026thinsp;=\u0026thinsp;68.24, F(5,356)\u0026thinsp;=\u0026thinsp;68.24, R2\u0026thinsp;=\u0026thinsp;0.48R2\u0026thinsp;=\u0026thinsp;0.48, Adjusted R2\u0026thinsp;=\u0026thinsp;0.47R2\u0026thinsp;=\u0026thinsp;0.47, p\u0026lt;.001p\u0026lt;.001, accounting for 48% of the variance in IGD severity. Depression (β\u0026thinsp;=\u0026thinsp;0.39β\u0026thinsp;=\u0026thinsp;0.39, p\u0026lt;.001p\u0026lt;.001) and anxiety (β\u0026thinsp;=\u0026thinsp;0.42β\u0026thinsp;=\u0026thinsp;0.42, p\u0026lt;.001p\u0026lt;.001) emerged as significant independent psychological predictors. Among demographic and behavioral predictors, academic achievement (β\u0026thinsp;=\u0026thinsp;0.41β\u0026thinsp;=\u0026thinsp;0.41, p\u0026lt;.001p\u0026lt;.001) and daily gaming time (β\u0026thinsp;=\u0026thinsp;0.58β\u0026thinsp;=\u0026thinsp;0.58, p\u0026lt;.001p\u0026lt;.001) significantly contributed to the model. Gender had a minimal effect (β\u0026thinsp;=\u0026thinsp;0.05β\u0026thinsp;=\u0026thinsp;0.05) and was not statistically significant (p=.230p=.230), suggesting limited influence on IGD severity in this sample. Variance inflation factors below 3 indicated no multicollinearity concerns, and the Durbin\u0026ndash;Watson statistic of 1.86 suggested no serious autocorrelation. These results demonstrate that IGD severity is strongly associated with anxiety, depression symptoms, academic performance, and gaming duration, while gender plays a negligible role.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDespite Saudi Arabia ranking sixth globally in online video game participation at 92.3%, research on the relationship between depression, anxiety, and IGD remains limited. This exploratory study is among the few that examine this association specifically among health sciences students in southern Saudi Arabia. It found that 22.6% of participants met the criteria for IGD, classifying them as troubled players according to the recommended cut-off of 32 points. This prevalence is consistent with prior studies reporting rates between 19% and 27% among students\u003csup\u003e[60\u0026ndash;63]\u003c/sup\u003e. In contrast, earlier research conducted before the COVID-19 pandemic reported lower rates of 8\u0026ndash;10%\u003csup\u003e[64\u0026ndash;67]\u003c/sup\u003e. Moreover, university students in Saudi Arabia \u003csup\u003e[68]\u003c/sup\u003e, demonstrated a marked increase in gaming behaviors during periods of social isolation. Recent literature suggests that pandemic-related stress and isolation may have contributed to higher IGD rates among university students in several countries, including Saudi Arabia\u003csup\u003e[69]\u003c/sup\u003e, Collectively, these findings highlight IGD as a growing public health concern warranting further investigation.\u003c/p\u003e \u003cp\u003eThe present study also revealed that daily gaming time was strongly associated with IGD severity. Participants who reported gaming for more than six hours per day scored significantly higher on the IGD scale, a finding consistent with prior meta-analyses that identified gaming duration as a critical risk factor\u003csup\u003e[70]\u003c/sup\u003e. Those who played four to five hours daily also exhibited elevated scores, suggesting that preventive interventions targeted at this group could be effective in reducing risk. These results align with previous studies consistently linking gaming duration to greater IGD severity\u003csup\u003e[1, 62, 71]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGender differences also emerged, with prevalence rates of 10.1% among males compared to 6.3% among females. This pattern aligns with studies conducted within the Saudi population, including previous investigations[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Comparable trends have been reported in other Arab contexts; for example, an Egyptian study found IGD prevalence at 12.3% among males and 4.4% among females. Additional research [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e], further supports the link between IGD and gender. The higher prevalence among males may reflect stronger responsiveness to gaming-related rewards, increased cravings, and reduced inhibitory control [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Furthermore, the gaming industry\u0026rsquo;s emphasis on male audiences may also contribute to the disproportionate risk [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAcademic performance was another area of concern. A one-way analysis of variance revealed significant differences in IGD scores based on academic proficiency. Specifically, students with higher IGD scores reported lower academic achievement. This result is consistent with previous research documenting reduced academic outcomes among individuals with IGD[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. Lower performance may be explained by the large amount of time devoted to gaming, particularly on school days, which often leads to sleep deprivation and diminished classroom concentration [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Many students become preoccupied with gaming, even waking during the night to continue playing, resulting in constant thoughts about gaming or continuous play. Consequently, assignments and homework are neglected, and sleep-deprived students struggle to focus and learn effectively[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe primary focus of this study was the relationship between IGD and mental health symptoms. Pearson\u0026rsquo;s correlation coefficients revealed strong positive associations between IGD, anxiety, and depression. When comparing students with IGD to those without, the IGD group reported significantly higher levels of depression and anxiety. Multiple linear regression analyses further demonstrated that both anxiety (β\u0026thinsp;=\u0026thinsp;0.70, p \u0026lt; .001) and depression (β\u0026thinsp;=\u0026thinsp;1.01, p \u0026lt; .001) were strong predictors of IGD scores, indicating that a substantial portion of variance in IGD severity can be attributed to mental health symptoms. Moreover, hierarchical regression analysis confirmed that depression and anxiety significantly affected IGD scores even after adjusting for demographic factors. After controlling for gender, academic performance, and daily gaming duration, both variables remained significant predictors. This final model displayed improved explanatory power (adjusted R\u0026sup2; = 0.48), underscoring the robust influence of mental health on IGD, independent of behavioral and demographic factors. Also, the significant associations between IGD severity and increased depression and anxiety are consistent with the (interaction of person-affect-cognition-execution) I-PACE model [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], which highlights affective and cognitive vulnerabilities as central to addictive internet behaviors. The Compensatory Internet Use Model [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], further supports that students may use gaming as an avoidant coping strategy in response to academic and psychological stressors. These models underscore the complex etiological pathways involved in IGD and provide targets for tailored intervention strategies in this population.\u003c/p\u003e \u003cp\u003eOverall, the findings of this study are consistent with international research documenting the negative impact of IGD on psychological well-being. Nevertheless, these results should be interpreted cautiously in light of certain limitations. The use of a convenience sample of health sciences students limits generalizability, while reliance on self-reported questionnaires rather than clinical interviews may have introduced reporting bias. Furthermore, the cross-sectional design prevents firm conclusions regarding causality or directionality.\u003c/p\u003e \u003cp\u003eFuture research in Saudi Arabia should adopt larger and more diverse samples, utilize longitudinal designs, and incorporate qualitative methods to better understand the mechanisms linking IGD with mental health. Such approaches would help identify risk factors, develop culturally appropriate screening tools, and guide targeted interventions to mitigate the academic, social, and psychological consequences of problematic gaming.\u003c/p\u003e "},{"header":"Conclusions and Recommendation","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003cp\u003eThe current study highlights a concerning prevalence of IGD among health sciences students and identifies a significant correlation between IGD, depression, and anxiety. Despite certain limitations, these findings emphasize the urgent need for preventive measures and interventions to address IGD in young people. The primary objective of this research was to examine the relationship between IGD and mental health issues, specifically depression and anxiety, among health sciences students in southern Saudi Arabia. While the study has limitations, it contributes to a better understanding of IGD within this demographic. The results suggest that IGD, often viewed as a non-substance-related dependency, shares characteristics and mechanisms with substance use disorders, which has important implications for interventions and public health policy. Notably, the findings are consistent with existing literature, indicating that addictive behaviors like IGD are linked to various mental health issues, including anxiety disorders, depression, and stress [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eYoung people, including health sciences students, hold the key to a society's future. However, addiction and mental illness can hinder their potential, leading to significant costs and consequences, including dropouts, job losses, and absenteeism. These challenges can result in long-term disabilities and even premature death from suicide or stress-related lifestyle disorders. Therefore, the current findings underscore the urgent need to develop interventions and strategies to prevent IGD, especially among adolescents and young adults.\u003c/p\u003e \u003cp\u003eThe first step in this direction is to identify the risk and protective factors that affect IGD and understand the causal mechanisms. For example, users with IGD tend to start playing online games at a relatively young age, so early start playing may be a risk factor for IGD. Accordingly, diverse and exciting early educational curricula are needed to build immunity against online game addiction in adolescents and young adults. Also, integrate educational programs into school curriculums that promote healthy gaming habits, responsible technology use, and strategies for managing screen time. Parents should pay special attention to their children's video game playtime to enhance their psychological and social well-being. Implementing preventative measures and early interventions is essential for limiting the negative effects of IGD.\u003c/p\u003e \u003cp\u003eThe researchers suggest conducting longitudinal studies with larger and more diverse samples to explore the causal relationships between IGD, mental health symptoms, and other relevant factors. COVID-19 impact: Investigate the specific influence of the COVID-19 pandemic on IGD development and explore whether the observed high prevalence is temporary or a long-term trend. Intervention efficacy: Evaluate the effectiveness of different preventive and treatment interventions for IGD among young people. Qualitative studies: Conduct qualitative studies to gain a deeper understanding of the experiences, motivations, and challenges faced by individuals with IGD.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors: conceived of the presented idea. MH, N. A, H.A., P.S, E.M, M.W., and H.F.A: Conceptualization. \u0026nbsp;N.A, M.H. E.M. M.W., and H. A: Data Collection. \u0026nbsp;M.H, P.S and N.A. Data Analysis. N.A, H.A., H.A, P.S, E.M., and M.H: Resources. M.H., N.A., H.H. P.S, E.M. M.W., and H.A: Writing\u0026mdash;Original Draft Preparation, Writing\u0026mdash;Review \u0026amp; Editing. H. A: Funding Acquisition. All authors conceptualized the study, collected, analyzed, interpreted the data and writing the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2026R707), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Interest Statement:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Institutional Review Board (IRB) of the Deanship of Scientific Research at Najran University, Najran, Saudi Arabia, No (NU/IFC/2/SEHRC/-/19).\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eInformed consent was obtained electronically at the beginning of the online questionnaire. All participants were required to read the consent statement and indicate their agreement before proceeding. Participation was voluntary, all information was kept strictly confidential, and the data were used solely for scientific research purposes. Only participants who agreed to the study conditions and provided informed consent proceeded to complete the study instruments.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eFurthermore, all procedures performed in this study were conducted in accordance with the ethical standards of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data is available on request by the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHawi, N. S., Samaha, M. \u0026amp; Griffiths, M. D. 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(2014).\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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Internet Gaming Disorder, Anxiety, Depression, Mental Health, Saudi Society, Health Sciences Students","lastPublishedDoi":"10.21203/rs.3.rs-9058142/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9058142/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis cross-sectional study aimed to assess the prevalence of Internet gaming disorder among health science students in southern Saudi Arabia and to explore its relationship with symptoms of depression and anxiety.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eData were collected from 362 Health Sciences Students from Najran University at Southern Saudi Arabia (M age\u0026thinsp;=\u0026thinsp;21.6 years, SD age\u0026thinsp;=\u0026thinsp;3.42 years). The sample completed an online survey that included the Internet Gaming Disorder Scale-Short Form, the CES-D Depression Model, and the Generalized Anxiety Disorder Scale.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results indicated that 22.6% of health sciences students exhibited signs of Internet gaming disorder. Furthermore, there was a positive correlation between the severity of Internet gaming disorder, levels of depression and anxiety. Both anxiety and depression symptoms explained 48% of the variation in Internet gaming disorder scores. Bivariate redundant analyses indicated that individuals who played online games for six or more hours each day were more likely to exhibit signs of severe depression and anxiety, had a relatively higher severity of Internet gaming disorder and males were more likely to have Internet gaming disorder compared to females. Furthermore, students with Internet gaming disorder had low academic achievement.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eFuture studies should validate these findings through more comprehensive research. However, this exploratory study provides valuable insights into potential strategies and programs for preventing Internet gaming disorder among Health Sciences students in Southern Saudi Arabia.\u003c/p\u003e","manuscriptTitle":"Depression–Anxiety Relationships with Internet Gaming Disorder among Health Sciences Students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-13 17:07:39","doi":"10.21203/rs.3.rs-9058142/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-03T22:48:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"271164230176316684431223004760090084727","date":"2026-04-28T13:29:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-07T09:44:25+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-16T09:06:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-11T11:52:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-11T11:52:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-07T11:37:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"87821133-7539-4f1e-90ae-a86e2a738090","owner":[],"postedDate":"April 13th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-03T22:48:25+00:00","index":93,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":65844933,"name":"Health sciences/Diseases"},{"id":65844934,"name":"Health sciences/Health care"},{"id":65844935,"name":"Biological sciences/Psychology"},{"id":65844936,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-04-13T17:07:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-13 17:07:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9058142","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9058142","identity":"rs-9058142","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}