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Impaired sleep quality mediates the relationship between internet gaming disorder and conduct problems among adolescents: a three-wave longitudinal study

Child and Adolescent Psychiatry and Mental Health volume 19, Article number: 26 (2025) Cite this article

Abstract

Background

Research increasingly demonstrates a positive association between Internet Gaming Disorder (IGD) and conduct problems among adolescents. However, longitudinal data are limited, and the mediating mechanisms remain unclear. This study aimed to examine the predictive effect of IGD on conduct problems and explore the mediating role of impaired sleep quality.

Method

A cohort of 20,137 Chinese seventh- and tenth-grade students was recruited and assessed at three time points: November 2020 (T1), 2021 (T2), and 2022 (T3). IGD, conduct problems, and impaired sleep quality were measured using the Internet Gaming Disorder Scale Short Form, the Strengths and Difficulties Questionnaire, and the Pittsburgh Sleep Quality Index, respectively. Mediation analyses were conducted to evaluate the direct and indirect effect of IGD on conduct problems, with subgroup analyses based on sex and developmental stage.

Results

IGD was found to be an independent risk factor for conduct problems both cross-sectionally and longitudinally. Impaired sleep quality partially mediated the relationship between IGD and conduct problems, accounting for approximately 17.3% of the total effect. Subgroup analyses revealed that the mediation effect of impaired sleep quality was more pronounced in early adolescents and varied by sex, with a stronger total and direct effect in boys.

Conclusions

These findings highlight the need for comprehensive interventions targeting both IGD and impaired sleep quality, tailored to specific sexes and developmental stages, to effectively reduce conduct problems.

Introduction

Conduct problems, encompassing behaviors such as aggression, rule-breaking, and antisocial activities, present a significant public health challenge among adolescents [1]. Affecting approximately 5–10% of adolescents globally, these behaviors can lead to both immediate and long-term consequences [2,3,4]. Beyond behavioral issues, adolescents with conduct problems often experience academic difficulties, strained social relationships, and impaired mental health [5]. Over time, these early behavioral challenges can develop into adverse outcomes in adulthood, including criminal behavior, substance abuse, and chronic mental health disorders [6,7,8]. Additionally, recent studies have highlighted the substantial economic burden of adolescent conduct problems, which includes increased healthcare costs, reduced productivity, and expenses related to the criminal justice system [9, 10]. Hence, it is crucial to identify and address the risk factors contributing to conduct problems.

Association between internet gaming disorder and conduct problems

Internet Gaming Disorder (IGD) has emerged as a growing concern among adolescents [11]. IGD is characterized by excessive and compulsive gaming behaviors that result in significant impairment or distress. It is associated with various negative outcomes, including social isolation, impaired sleep quality, depression, anxiety, academic failure, and suicidality [12,13,14]. Emerging research has identified a positive relationship between IGD and conduct problems [15,16,17]. However, longitudinal studies examining this association are limited and have produced mixed results [18,19,20,21]. While some research suggests that IGD can predict future conduct problems [19], other studies have not found a significant long-term relationship [18]. These inconsistent findings highlight the need for large-scale longitudinal studies to clarify the temporal relationship between IGD and conduct problems.

Impaired sleep quality as potential mediator between IGD and conduct problems

A key gap in the current literature is the limited understanding of the mechanisms linking IGD to conduct problems. Most existing studies have focused on the direct relationship without exploring potential mediating factors. Impaired sleep quality is a promising candidate for mediation, which is a common consequence of behavioral addictions including IGD, social media addiction, and smartphone addiction [22, 23]. Longitudinal research indicates that IGD often leads to sleep problems, such as reduced sleep duration and poorer sleep quality [12]. These sleep issues can, in turn, result in increased irritability, impaired emotional regulation, and heightened aggression, all of which contribute to conduct problems [24, 25]. Preliminary support for this mediation comes from cross-sectional studies. For example, a large-scale American study found that increased screen time was associated with aggressive and rule-breaking behaviors, with shorter sleep duration mediating this relationship [26]. Another study reported that insomnia fully mediated the relationship between IGD and aggression in youths aged 18 to 24 years [27]. However, these studies are limited by their cross-sectional design, which does not allow for establishing temporal order. To date, no longitudinal research has rigorously tested whether impaired sleep quality mediates the relationship between IGD and conduct problems.

Investigating differences across sex and developmental stages in the interrelationship between IGD, conduct problems, and impaired sleep quality

Both IGD and conduct problems are more prevalent among boys, and recent evidence suggests that their relationship may differ by sex. For instance, one study found a reciprocal relationship between IGD and aggression in boys but not in girls [21], highlighting the importance of considering sex differences in future research. Additionally, developmental stage may moderate the association between IGD and mental health outcomes. Research indicates that the impact of IGD on mental health may vary between early and late adolescence [28,29,30]. A recent study showed that the relationship between IGD, depression, and anxiety differed between middle (junior high) and late (senior high) adolescents [28]. Furthermore, a meta-analysis reported that the link between IGD and aggression is stronger in younger adolescents compared to older youths, such as college students [17].These findings emphasize the need to examine how sex and developmental stage influence the relationship between IGD, conduct problems, and impaired sleep quality.

The current study

To bridge these gaps, we conducted the present three-wave longitudinal study among a substantial sample of Chinese adolescents (N = 20137), aiming to test the following hypotheses: (1) Is IGD an independent risk factor for conduct problems among adolescents? (2) Does impaired sleep quality mediate the relationship between IGD and conduct problems? (3) Is there a difference in the association between IGD, conduct problems, and impaired sleep quality across sex and developmental stages? These subgroup analyses were explanatory in nature.

Method

Study procedure and participants

This longitudinal, school-based study was conducted in Zigong City, located in southwestern China. Detailed information on the sampling process, data collection methods, and quality assurance procedures has been previously published [31,32,33]. In November 2020 (Wave 1, T1), we recruited a total of 13,361 seventh-grade and 6,776 tenth-grade students from 76 schools using a two-step cluster sampling approach. Initially, all eligible middle school principals in the selected area were invited to participate. Subsequently, students from each participating school were enrolled. These participants were followed up in November 2021 (Wave 2, T2) and November 2022 (Wave 3, T3). Data were collected through electronic questionnaires, which students completed in their schools’ computer centers during regular school hours.

The study was conducted in accordance with the Declaration of Helsinki and received ethical approval from the Zigong Mental Health Center (Approval No. 2020-8-01). Written informed consent was obtained from all participants, and for those under 18, consent was also obtained from a parent or legal guardian.

Measurements

Predictor at T1

Internet Gaming Disorder (IGD) was assessed at baseline using the nine-item Internet Gaming Disorder Scale - Short Form (IGDS9-SF) [34]. Participants responded to each item on a five-point Likert scale (1 = never to 5 = always), indicating the frequency of gaming-related behaviors over the past year. Higher scores reflect greater severity of IGD. Based on prior research, participants were categorized into three groups: adolescents without problematic gaming (< 21), risky gamers (21–31), and gamers with IGD (32 or above) [35, 36]. This classification captures varying levels of IGD severity. The IGDS9-SF has demonstrated strong reliability and validity in Chinese populations [37].

Outcome at T1, T2 and T3

Conduct problems were assessed using the conduct problems subscale from the Strengths and Difficulties Questionnaire (SDQ), which is widely used to evaluate internalizing (peer problems, emotional problems) and externalizing (conduct problems, hyperactivity/inattention) issues in children and adolescents [38]. The conduct problems subscale (SDQ-CP) comprises five items that measure symptoms of aggression, rule-breaking, and antisocial tendencies, each scored on a three-point scale (0 = not true, 1 = somewhat true, 2 = certainly true). Higher scores indicate more severe conduct problems. A cutoff score of 5 was used to identify clinically significant conduct problems, in line with previous validation studies in Chinese adolescent populations [39].

Mediators at T1 and T2

Impaired sleep quality was measured at T1 and T2 using the Pittsburgh Sleep Quality Index (PSQI), a widely recognized instrument for assessing sleep-related problems over the past month [40]. The PSQI includes 19 self-reported items that generate seven component scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication, and daytime dysfunction. Each component is scored from 0 to 3, with higher scores indicating poorer sleep quality. A global PSQI score is obtained by summing the component scores, and a score of ≥ 6 signifies impaired sleep quality [41]. The total scores of PSQI were used in all subsequent analysis. The PSQI has demonstrated strong reliability and validity in the Chinese population [41].

Covariates

Baseline demographic variables included gender, age, place of residence, grade level, and family-related factors such as only-child status, left-behind status, and family structure (single-parent or blended family). Participants also reported on smoking and alcohol consumption behaviors. Additional mental health covariates included the peer problems, emotional symptoms, and hyperactivity/inattention subscales of the SDQ [39]. Participants scoring ≥ 6 on peer problems, ≥ 7 on emotional symptoms, and ≥ 7 on hyperactivity/inattention were classified as experiencing clinically significant distress in each respective domain. These covariates were found to be closely associated with conduct problems in prior research [42,43,44,45,46].

Statistical analysis

Descriptive statistics were calculated for all variables, with means and standard deviations presented for continuous variables and frequencies and percentages for categorical variables. Baseline characteristics were compared between adolescents with and without conduct problems using Chi-square tests for categorical variables and Student’s t-tests for continuous variables.

Logistic regression models were then employed to examine both cross-sectional and longitudinal associations between baseline IGD and conduct problems across the three time points. These models controlled for baseline demographic factors and mental health issues. In the longitudinal analysis, we additionally adjusted for baseline conduct problems, which ensured that the observed association between IGD, impaired sleep quality, and later conduct problems reflected their unique contribution, rather than pre-existing behavioral tendencies.

Subsequently, a mediation analysis was conducted with T1 IGDS9-SF scores as the predictor, T2 PSQI total scores as the mediator, and T3 SDQ-CP scores as the outcome for participants with at least one follow-up wave. Missing data were handled using full information maximum likelihood, which estimated parameters using all available data and enhanced statistical efficiency without the need for data imputation [47]. Path coefficients were defined as follows: “a” for the effect of T1 IGD on T2 impaired sleep quality, “b” for the effect of T2 impaired sleep quality on T3 conduct problems, and “c” for the direct effect of T1 IGD on T3 conduct problems. The indirect effect was calculated as the product of paths (a * b). A bootstrap procedure with 5,000 iterations was used to generate 95% confidence intervals for both direct and indirect effects, with effects considered significant if the confidence intervals did not include zero. Both unadjusted and adjusted models were tested. As an additional robustness check, we reran the mediation analysis using only participants with complete data across all waves.

Finally, multiple-group analyses were performed to explore differences by gender (boys vs. girls) and developmental stage (seventh-grade as early adolescents vs. tenth-grade as late adolescents). Chi-square difference tests were used to compare the fit of an unconstrained model against models with paths constrained to be equal across the two groups.

All descriptive analyses, group comparisons, and logistic regressions were conducted using R (version 4.20). Mediation analyses were performed using Mplus (version 8.3). Statistical significance was set at p < 0.05 for all two-tailed tests.

Results

Sample characteristics

Table S1 presents the baseline characteristics of participants across all three waves. Initially, 20,137 seventh and tenth-grade students were enrolled in the study. At the first follow-up (T2), 15,061 students participated (response rate: 75%), and at the second follow-up (T3), 14,706 students completed the survey (response rate: 73%). Approximately 85% of the adolescents participated in at least one follow-up (n = 16,982), and 63% (n = 12,785) participated in all three waves. There were no significant differences in the main study variables—IGD status, conduct problems, and sleep quality—between participants who remained in the study and those who dropped out. However, dropout was slightly more likely among girls, younger students, only children, those with parents of higher education, and seventh-grade students, although these differences were minimal.

At baseline, the prevalence of conduct problems was 9.0% (Table 1). Adolescents with conduct problems were significantly younger (mean age = 13.24 ± 1.36 years) compared to those without (mean age = 13.42 ± 1.46 years). A higher proportion of boys (53.0% vs. 49.1%) and seventh-grade students (73.7% vs. 65.6%) exhibited conduct problems compared to their counterparts without conduct problems (p < 0.05). Additionally, conduct problems were more prevalent among only children (28.0% vs. 22.0%), those from single-parent or remarried families (26.5% vs. 20.1%), and those engaged in substance use (alcohol: 31.6% vs. 15.4%; smoking: 18.5% vs. 5.8%, p < 0.001). Psychologically, adolescents with conduct problems reported more severe impaired sleep quality (PSQI: 6.0 ± 3.8 vs. 3.8 ± 3.0) and higher IGD scores (IGDS9-SF: 19.8 ± 8.7 vs. 14.5 ± 6.0, p < 0.001). Furthermore, the prevalence of emotional problems, peer problems, and hyperactivity/inattention was significantly higher among those with conduct problems.

Table 1 Sample characteristics by baseline conduct problems
Full size table

Cross-sectional and longitudinal association between IGD and conduct problems

The prevalence of conduct problems decreased over time, from 9.0% at T1 to 6.5% at T2 and 6.0% at T3. As illustrated in Fig. 1, both risky gamers and gamers with IGD consistently reported higher prevalence rates of conduct problems compared to healthy gamers across all three time points. Specifically, at baseline, 34.7% of gamers with IGD and 19.3% of risky gamers exhibited conduct problems, compared to 6.3% of healthy gamers. Similar trends were observed at T2 and T3.

Fig. 1
figure 1

The prevalence of conduct problems by baseline IGD status

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Logistic regression analyses revealed that both cross-sectional and longitudinal associations between IGD and conduct problems remained significant after adjusting for baseline covariates (Table 2). Compared to adolescents without problematic gaming, risky gamers had increased odds of conduct problems at T1 (adjusted odds ratio [OR] = 1.41, 95% CI = 1.13–1.77, p = 0.003), T2 (adjusted OR = 1.33, 95% CI = 1.12–1.58, p = 0.001), and T3 (adjusted OR = 1.32, 95% CI = 1.10–1.58, p = 0.003). IGD gamers exhibited even higher odds at T1 (adjusted OR = 3.01, 95% CI = 2.41–3.76, p < 0.001), T2 (adjusted OR = 1.63, 95% CI = 1.20–2.22, p = 0.002), and T3 (adjusted OR = 1.52, 95% CI = 1.09–2.11, p = 0.013).

Table 2 Association of IGD and impaired sleep quality with conduct problems
Full size table

Additionally, baseline impaired sleep quality was significantly associated with increased odds of conduct problems at all three time points: T1 (adjusted OR = 1.40, 95% CI = 1.24–1.58, p < 0.001), T2 (adjusted OR = 1.49, 95% CI = 1.28–1.74, p < 0.001), and T3 (adjusted OR = 1.48, 95% CI = 1.26–1.74, p < 0.001).

The mediating role of impaired sleep quality between IGD and conduct problems

The mediation analysis revealed both direct and indirect effects of IGD on conduct problems (Fig. 2). In the unadjusted model, IGD at T1 was significantly associated with impaired sleep quality at T2 (a = 0.218, 95% CI = 0.201–0.235), which in turn were associated with increased conduct problems at T3 (b = 0.233, 95% CI = 0.214–0.251). The direct effect of IGD on conduct problems (c) was 0.128 (95% CI = 0.110–0.146), and the indirect effect (a × b) was 0.051 (95% CI = 0.045–0.056). This indicates that impaired sleep quality mediated 28.5% of the total effect in the unadjusted model. After adjusting for baseline covariates, all paths remained significant. The direct effect was reduced to 0.043 (95% CI = 0.022–0.063), and the indirect effect decreased to 0.009 (95% CI = 0.005–0.013), accounting for 17.3% of the total effect.

Fig. 2
figure 2

The unadjusted and adjusted mediation model in all samples

Full size image

Sensitivity analysis using data from participants with complete data across all waves produced consistent results. In the fully adjusted model, the direct effect of IGD on conduct problems was 0.041 (95% CI = 0.020–0.062), and the indirect effect via impaired sleep quality was also significant (β = 0.010, 95% CI = 0.006–0.014). These findings further support the reliability of our mediation model.

Subgroup analysis based on sex and developmental stages

Figure 3 displayed the results of subgroup analysis. Multiple-group analyses revealed significant differences in the mediation model between boys and girls (Δχ2 = 101.266, Δdf = 33, p < 0.001). While in both girls and boys, the direct and indirect effect of IGD on conduct problems were significant, both the total effect and direct effect was greater in boys (total effect = 0.061, direct effect = 0.051) compared to girls (total effect = 0.037, direct effect = 0.029). The mediation proportion of impaired sleep quality was slightly higher among girls (21.6%) compared to boys (16.4%).

Fig. 3
figure 3

The mediation model across sex (boys and girls) and developmental stages

Full size image

There were also significant differences in the mediation model between early and late adolescents (Δχ2 = 137.718, Δdf = 33, p < 0.001). Both early (seventh-grade) and late (tenth-grade) adolescents showed significant direct and indirect effects of IGD on conduct problems, with comparable total effects. However, the proportion of the mediation effect via impaired sleep quality was higher among early adolescents (23.5%) compared to late adolescents (10%). This indicates that impaired sleep quality played a more substantial mediating role in the IGD-conduct problems relationship during early adolescence.

Discussion

This three-wave cohort study examined the prospective association between IGD and conduct problems and explored the mediating effect of impaired sleep quality among Chinese adolescents. The key findings of our study are threefold: (1) IGD is an independent risk factor for conduct problems; (2) Impaired sleep quality partially mediate the relationship between IGD and conduct problems, accounting for approximately one-fifth of the total effect; and (3) The IGD-sleep-conduct problems relationship varies significantly across sex and developmental stages.

Cross-sectional and longitudinal association between IGD and conduct problems

At baseline, the prevalence of conduct problems and IGD was 9.0% and 2.6%, respectively, consistent with recent large-scale epidemiological data on Chinese adolescents [3, 48, 49]. While most prior research on the association between IGD and conduct problems has been conducted in Western populations [15, 16], our findings replicate these associations within a substantial Chinese sample. We observed a strong cross-sectional and longitudinal relationship between IGD and conduct problems. Notably, even adolescents classified as risky gamers, who did not meet the criteria for IGD, exhibited a higher risk of concurrent and future conduct problems. These results suggest that even subclinical levels of problematic gaming are linked to increased behavioral issues. This cross-cultural consistency underscores the universal nature of the IGD-conduct problems relationship and highlights the importance of screening for conduct problems among adolescents engaged in problematic gaming behaviors, including both risky gamers and those with IGD.

Several explanations may account for the substantial association between IGD and conduct problems. First, excessive gaming may displace time spent on social activities [50, 51], leading to reduced social skills and increased interpersonal conflicts, such as family disputes and peer bullying [52], which can contribute to conduct problems. Second, adolescents with IGD often struggle with difficulties in emotional regulation and expression and possess inadequate coping strategies [53,54,55]. Reliance on gaming for emotional regulation may hinder the development of healthier coping mechanisms, exacerbating behavioral issues [56]. Finally, from a neurobiological perspective, IGD is associated with alterations in brain regions involved in executive functioning [57,58,59], such as the prefrontal cortex, which is critical for impulse control and decision-making. Structural and functional changes in these areas may impair adolescents’ ability to regulate behaviors and adhere to social norms, thereby fostering conduct problems.

The indirect effect of impaired sleep quality

Our study found that impaired sleep quality is an independent predictor of conduct problems, consistent with prior research [60]. Poor sleep disrupts emotional regulation, resulting in heightened irritability, impulsivity, and aggression [24, 25].It also impairs executive functions, such as impulse control and decision-making [61], which increases the likelihood of risk-taking and rule-breaking behaviors. These effects may be underpinned by biological mechanisms, including dysregulation of the hypothalamic-pituitary-adrenal axis, alterations in the brain’s cholinergic system, and structural changes in key brain regions [62,63,64]. Together, these pathways highlight the critical role of sleep disturbances in the development and exacerbation of conduct problems.

Consistent with our hypothesis, impaired sleep quality significantly mediated the relationship between IGD and conduct problems, accounting for about one-fifth of the total effect after adjusting for covariates. This finding contributes to the growing body of literature recognizing impaired sleep quality as a crucial pathway linking IGD to a series of adverse mental health outcomes, including depression, suicidality, psychotic-like experiences, and impaired well-being [65,66,67,68,69]. Collectively, these results highlight the importance of incorporating sleep assessments and interventions into strategies aimed at mitigating the behavioral and psychological impacts of IGD. Comprehensive intervention programs that target both gaming behaviors and sleep health could more effectively support the well-being of affected adolescents.

The difference across sex and developmental stages

Our study revealed significant sex differences in the IGD-sleep-conduct problems relationship. Specifically, both the direct and total effects of IGD on conduct problems were more pronounced among boys, indicating that IGD may be a stronger predictor of conduct problems in this group. These findings partially align with those of Kim et al. [21], who observed a longitudinal association between IGD and aggression in Korean adolescent boys but not in girls. One possible explanation for these sex differences is the type of games played; boys may engage more frequently in aggressive and violent gaming, which could potentially lead to higher conduct problems [70]. Additionally, previous research on IGD and depression has produced similar results, finding a stronger effect of IGD on later depression among boy [71, 72], though the results were not entirely consistent [29, 73]. Collectively, these findings might suggest that boys may be more vulnerable to IGD-related mental distress. Future studies should explore the underlying biological and psychosocial mechanisms contributing to these sex differences.

Regarding developmental stages, the mediation effect of impaired sleep quality was more pronounced among early adolescents (seventh-grade students) compared to late adolescents (tenth-grade students). While the total effects of IGD on conduct problems were comparable across both groups, impaired sleep quality accounted for a larger proportion of this relationship in early adolescents. This suggests that younger adolescents may be more vulnerable to the negative impacts of IGD on sleep, which in turn affects their behavioral outcomes. Early adolescence is a critical period for developing sleep patterns and behavioral regulation; thus, interventions targeting sleep hygiene may be particularly beneficial for this age group.

Clinical implication of the present study

Our study has several public health and clinical implications. The robust cross-sectional and longitudinal associations between IGD and conduct problems underscore the necessity for early identification and targeted interventions for adolescents engaged in problematic gaming. Recognizing IGD as a substantial risk factor for conduct problems emphasizes the importance of screening for both conditions in educational and clinical settings. Comprehensive screening programs that include assessments for IGD, conduct problems, and sleep quality can facilitate timely and effective interventions. The mediating effect of impaired sleep quality between IGD and conduct problems suggests that targeting sleep problems simultaneously with gaming behaviors may be an effective strategy for reducing gaming-related conduct problems. For example, interventions could integrate cognitive-behavioral therapy for insomnia (CBT-I) to improve sleep quality alongside CBT for IGD to address compulsive gaming. Additionally, psychoeducational programs could teach adolescents and parents about the importance of sleep hygiene and healthy screen time habits. School-based initiatives, such as sleep awareness campaigns and structured gaming schedules, could further reinforce these efforts. Future research is needed to validate the efficacy of such integrated approaches. Tailored intervention strategies are warranted based on subgroup analyses: girls and early adolescents may benefit more from interventions targeting impaired sleep quality, whereas boys and late adolescents might require more direct interventions addressing IGD itself.

Strength and limitations

The present study boasts several strengths, including a large sample size and a robust three-wave longitudinal design, which enhance the reliability and generalizability of the findings. However, several limitations must be acknowledged. First, the reliance on self-reported measures may introduce response biases, such as social desirability or recall bias, potentially affecting data accuracy. Second, the study’s focus on Chinese adolescents may limit the generalizability of the findings to other cultural or geographical populations. Third, although impaired sleep quality was examined as a mediator, other potential mediators, such as emotional regulation, family dysfunction, and cyberbullying, were not explored and may also play critical roles in the IGD-conduct problems relationship. Additionally, while our three-wave longitudinal design supports temporal inferences, the observational nature of the study limits causal conclusions, and reverse causation remains a possibility. Future research should address these limitations by incorporating objective measures, diverse populations, and additional mediating factors to further clarify the mechanisms linking IGD to conduct problems.

Conclusion

Internet gaming disorder is an independent risk factor for conduct problems among adolescents, with impaired sleep quality serving as a partial mediator in this relationship. Significant differences emerged across sex and developmental stages in the IGD-sleep-conduct problems association. Addressing both IGD and associated impaired sleep quality holds promise for reducing conduct problems. Additionally, interventions tailored to specific sexes and developmental stages may be warranted to enhance their effectiveness.

Data availability

The data was available on request from the corresponding author.

Abbreviations

IGD:

Internet gaming disorder

SDQ:

Strengths and Difficulties Questionnaire

SDQ-CP:

the conduct problem subscale of Strengths and Difficulties Questionnaire

PSQI:

Pittsburgh Sleep Quality Index

References

  1. Bevilacqua L, Hale D, Barker ED, Viner R. Conduct problems trajectories and psychosocial outcomes: a systematic review and meta-analysis. Eur Child Adolesc Psychiatry. 2018;27:1239–60.

    Article  PubMed  Google Scholar 

  2. Ghandour RM, Sherman LJ, Vladutiu CJ, Ali MM, Lynch SE, Bitsko RH, et al. Prevalence and treatment of depression, anxiety, and conduct problems in US children. J Pediatr. 2019;206:256–e2673.

    Article  PubMed  Google Scholar 

  3. Liu Q, Zhou Y, Xie X, Xue Q, Zhu K, Wan Z, et al. The prevalence of behavioral problems among school-aged children in home quarantine during the COVID-19 pandemic in China. J Affect Disord. 2021;279:412–6.

    Article  CAS  PubMed  Google Scholar 

  4. Riehm KE, Mojtabai R. Trends in parent-rated emotional symptoms, conduct problems, and hyperactivity/inattention among U.S. Children and adolescents, 2004–2019. J Affect Disord. 2022;299:294–7.

    Article  PubMed  Google Scholar 

  5. Ayano G, Abraha M, Tsegay L, Gizachew Y. Umbrella review of the global prevalence of conduct disorder in children and adolescents. Psychiatr Q. 2024;95:173–83.

    Article  PubMed  Google Scholar 

  6. Fergusson DM, Horwood LJ, Ridder EM. Conduct and attentional problems in childhood and adolescence and later substance use, abuse and dependence: results of a 25-year longitudinal study. Drug Alcohol Depend. 2007;88(Suppl 1):S14–26.

    Article  PubMed  Google Scholar 

  7. Wertz J, Agnew-Blais J, Caspi A, Danese A, Fisher HL, Goldman-Mellor S, et al. From childhood conduct problems to poor functioning at age 18 years: examining explanations in a longitudinal cohort study. J Am Acad Child Adolesc Psychiatry. 2018;57:54–e604.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Manninen M, Koivukangas J, Holm M, Lindgren M. Lifetime psychiatric diagnoses among adolescents with severe conduct problems - A register-based follow-up study. Child Abuse Negl. 2022;131:105765.

    Article  PubMed  Google Scholar 

  9. Rissanen E, Kuvaja-Köllner V, Elonheimo H, Sillanmäki L, Sourander A, Kankaanpää E. The long-term cost of childhood conduct problems: Finnish nationwide 1981 birth cohort study. J Child Psychol Psychiatry. 2022;63:683–92.

    Article  PubMed  Google Scholar 

  10. Goulter N, Hur YS, Jones DE, Godwin J, McMahon RJ, Dodge KA, et al. Kindergarten conduct problems are associated with monetized outcomes in adolescence and adulthood. J Child Psychol Psychiatry. 2024;65:328–39.

    Article  PubMed  Google Scholar 

  11. 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. 2022;154:35–43.

    Article  PubMed  Google Scholar 

  12. Byeon G, Jo S-J, Park J-I, Jeong H, Lee HK, Yim HW. Risk factors and outcomes of internet gaming disorder identified in Korean prospective adolescent cohort study. J Behav Addict. 2022;11:1035–43.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Coutelle R, Balzer J, Rolling J, Lalanne L. Problematic gaming, psychiatric comorbidities, and adolescence: a systematic review of the literature. Addict Behav. 2024;157:108091.

    Article  PubMed  Google Scholar 

  14. Hawi NS, Samaha M, Griffiths MD. Internet gaming disorder in Lebanon: relationships with age, sleep habits, and academic achievement. J Behav Addict. 2018;7:70–8.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Richard J, Fletcher É, Boutin S, Derevensky J, Temcheff C. Conduct problems and depressive symptoms in association with problem gambling and gaming: A systematic review. J Behav Addict. 2020;9:497–533.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Suchá J, Dolejš M, Dostál D, Pipová H, Pontes HM. Internet gaming disorder and risky behaviours among Czech adolescents: A nationally representative study. J Behav Addict. 2024;13:742–50.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Li S, Wu Z, Zhang Y, Xu M, Wang X, Ma X. Internet gaming disorder and aggression: a meta-analysis of teenagers and young adults. Front Public Health. 2023;11:1111889.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Wartberg L, Kriston L, Zieglmeier M, Lincoln T, Kammerl R. A longitudinal study on psychosocial causes and consequences of internet gaming disorder in adolescence. Psychol Med. 2019;49:287–94.

    Article  PubMed  Google Scholar 

  19. Brunborg GS, Mentzoni RA, Frøyland LR. Is video gaming, or video game addiction, associated with depression, academic achievement, heavy episodic drinking, or conduct problems? J Behav Addict. 2014;3:27–32.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Hygen BW, Skalická V, Stenseng F, Belsky J, Steinsbekk S, Wichstrøm L. The co-occurrence between symptoms of internet gaming disorder and psychiatric disorders in childhood and adolescence: prospective relations or common causes? J Child Psychol Psychiatry. 2020;61:890–8.

    Article  PubMed  Google Scholar 

  21. Kim J, Lee D, Lee S, Kim E, Oh S. Reinforcing relationships between gaming disorder and aggression and intrusive parenting across 4 years. Cyberpsychol Behav Soc Netw. 2023;26:106–13.

    Article  PubMed  Google Scholar 

  22. Wang J, Wang N, Liu P, Liu Y. Social network site addiction, sleep quality, depression and adolescent difficulty describing feelings: a moderated mediation model. BMC Psychol. 2025;13:57.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Xiao T, Pan M, Xiao X, Liu Y. The relationship between physical activity and sleep disorders in adolescents: a chain-mediated model of anxiety and mobile phone dependence. BMC Psychol. 2024;12:751.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Demichelis OP, Grainger SA, Burr L, Henry JD. Emotion regulation mediates the effects of sleep on stress and aggression. J Sleep Res. 2023;32:e13787.

    Article  PubMed  Google Scholar 

  25. Palmer CA, Alfano CA. Sleep and emotion regulation: an organizing, integrative review. Sleep Med Rev. 2017;31:6–16.

    Article  PubMed  Google Scholar 

  26. Guerrero MD, Barnes JD, Chaput J-P, Tremblay MS. Screen time and problem behaviors in children: exploring the mediating role of sleep duration. Int J Behav Nutr Phys Act. 2019;16:105.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Bersani FS, Barchielli B, Ferracuti S, Panno A, Carbone GA, Massullo C, et al. The association of problematic use of social media and online videogames with aggression is mediated by insomnia severity: a cross-sectional study in a sample of 18- to 24-year-old individuals. Aggress Behav. 2022;48:348–55.

    Article  PubMed  Google Scholar 

  28. Gao T, Chen Y, Gai Q, D’Arcy C, Su Y. The co-occurrence between symptoms of internet gaming disorder, depression, and anxiety in middle and late adolescence: A cross-lagged panel network analysis. Addict Behav. 2025;161:108215.

    Article  PubMed  Google Scholar 

  29. Zhang M, Nie Q, Ye W, Wang Y, Yang Z, Teng Z. Longitudinal dynamic relationships between videogame use and symptoms of gaming disorder and depression among Chinese children and adolescents. J Youth Adolesc. 2025;54(2):426–438.

  30. Junus A, Hsu Y-C, Wong C, Yip PSF. Is internet gaming disorder associated with suicidal behaviors among the younger generation? Multiple logistic regressions on a large-scale purposive sampling survey. J Psychiatr Res. 2023;161:2–9.

    Article  PubMed  Google Scholar 

  31. Peng P, Chen Z, Ren S, Liu Y, He R, Liang Y, et al. Determination of the cutoff point for smartphone Application-Based addiction scale for adolescents: a latent profile analysis. BMC Psychiatry. 2023;23:675.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Chen Z, Ren S, He R, Liang Y, Tan Y, Liu Y, et al. Prevalence and associated factors of depressive and anxiety symptoms among Chinese secondary school students. BMC Psychiatry. 2023;23:580.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Peng P, Chen Z, Ren S, Liu Y, Li J, Liao A, et al. Association between school bullying victimization and e-cigarette use and its sex difference: evidence from Chinese adolescents. Journal of Smoking Cessation. 2025; 20: e001.

  34. Pontes HM, Griffiths MD. Measuring DSM-5 internet gaming disorder: development and validation of a short psychometric scale. Comput Hum Behav. 2015;45:137–43.

    Article  Google Scholar 

  35. Monacis L, de Palo V, Griffiths MD, Sinatra M. Validation of the internet gaming disorder Scale– Short-Form (IGDS9-SF) in an Italian-speaking sample. J Behav Addict. 2016;5:683–90.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Qin L, Cheng L, Hu M, Liu Q, Tong J, Hao W, et al. Clarification of the Cut-off score for Nine-Item internet gaming disorder Scale–Short form (IGDS9-SF) in a Chinese context. Front Psychiatry. 2020;11:470.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Chen I-H, Ahorsu DK, Pakpour AH, Griffiths MD, Lin C-Y, Chen C-Y. Psychometric properties of three simplified Chinese Online-Related addictive behavior instruments among Mainland Chinese primary school students. Front Psychiatry. 2020;11:875.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Goodman R. The strengths and difficulties questionnaire: a research note. J Child Psychol Psychiatry. 1997;38:581–6.

    Article  CAS  PubMed  Google Scholar 

  39. Du Y, Kou J, Coghill D. The validity, reliability and normative scores of the parent, teacher and self report versions of the strengths and difficulties questionnaire in China. Child Adolesc Psychiatry Ment Health. 2008;2:8.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28:193–213.

    Article  CAS  PubMed  Google Scholar 

  41. Tsai P-S, Wang S-Y, Wang M-Y, Su C-T, Yang T-T, Huang C-J, et al. Psychometric evaluation of the Chinese version of the Pittsburgh sleep quality index (CPSQI) in primary insomnia and control subjects. Qual Life Res. 2005;14:1943–52.

    Article  CAS  PubMed  Google Scholar 

  42. Wang F, Zhou X, Hesketh T. Psychological adjustment and behaviours in children of migrant workers in China. Child Care Health Dev. 2017;43:884–90.

    Article  CAS  PubMed  Google Scholar 

  43. Yu Y, Wang T, Liang J, Yang C, Wang H, Zhao X, et al. Behavioural problems amongst Pre-School children in Chongqing, China: current situation and influencing factors. Risk Manag Healthc Policy. 2020;13:1149–60.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Lansford JE, Godwin J, Rothenberg WA, Alampay LP, Al-Hassan SM, Bacchini D et al. Parenting risk and protective factors in the development of conduct problems in seven countries. Prev Sci. 2024.

  45. Colins OF, Fanti KA, Hellfeldt K, Frogner L, Andershed H. Developmental trajectories of conduct problems from childhood to adolescence: early childhood antecedents and outcomes in adolescence. Dev Psychopathol. 2025;1–16.

  46. Aoki A, Togoobaatar G, Tseveenjav A, Nyam N, Zuunnast K, Lkhagvasuren G, et al. Socioeconomic and lifestyle factors associated with mental health problems among Mongolian elementary school children. Soc Psychiatry Psychiatr Epidemiol. 2022;57:791–803.

    Article  PubMed  Google Scholar 

  47. Niu C. Impact of missing data and ICC on full information maximum-likelihood Estimation in multilevel SEMs. Model Assist Stat Appl. 2024;19:49–59.

    Google Scholar 

  48. Deng X, Hu Y-B, Liu C-Y, Li Q, Yang N, Zhang Q-Y, et al. Psychological distress and aggression among adolescents with internet gaming disorder symptoms. Psychiatry Res. 2024;331:115624.

    Article  PubMed  Google Scholar 

  49. Zhang L, Han J, Liu M, Yang C, Liao Y. The prevalence and possible risk factors of gaming disorder among adolescents in China. BMC Psychiatry. 2024;24:381.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Lobel A, Engels RCME, Stone LL, Burk WJ, Granic I. Video gaming and children’s psychosocial wellbeing: A longitudinal study. J Youth Adolesc. 2017;46:884–97.

    Article  PubMed  PubMed Central  Google Scholar 

  51. van den Eijnden R, Koning I, Doornwaard S, van Gurp F, Ter Bogt T. The impact of heavy and disordered use of games and social media on adolescents’ psychological, social, and school functioning. J Behav Addict. 2018;7:697–706.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Bonnaire C, Phan O. Relationships between parental attitudes, family functioning and internet gaming disorder in adolescents attending school. Psychiatry Res. 2017;255:104–10.

    Article  PubMed  Google Scholar 

  53. González-Roz A, Castaño Y, Krotter A, Salazar-Cedillo A, Gervilla E. Emotional dysregulation in relation to substance use and behavioral addictions: findings from five separate meta-analyses. Int J Clin Health Psychol. 2024;24:100502.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Ahmed GK, Abdalla AA, Mohamed AM, Mohamed LA, Shamaa HA. Relationship between time spent playing internet gaming apps and behavioral problems, sleep problems, alexithymia, and emotion dysregulations in children: a multicentre study. Child Adolesc Psychiatry Ment Health. 2022;16:67.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Li L, Niu Z, Song Y, Griffiths MD, Wen H, Yu Z et al. Relationships between gaming disorder, risk factors, and protective factors among a sample of Chinese university students utilizing a network perspective. Int J Ment Health Addict. 2023;1–19.

  56. King DL, Delfabbro PH. The concept of harm in internet gaming disorder. J Behav Addict. 2018;7:562–4.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Shin Y-B, Kim H, Kim S-J, Kim J-J. A neural mechanism of the relationship between impulsivity and emotion dysregulation in patients with internet gaming disorder. Addict Biol. 2021;26:e12916.

    Article  CAS  PubMed  Google Scholar 

  58. Lee J, Lee S, Chun JW, Cho H, Kim D, Jung Y-C. Compromised prefrontal cognitive control over emotional interference in adolescents with internet gaming disorder. Cyberpsychol Behav Soc Netw. 2015;18:661–8.

    Article  PubMed  Google Scholar 

  59. Yu J, Abdullah MFIL, Mansor NS. EEG components of inhibitory control ability in internet gaming disorder: A systematic review and meta-analysis of randomized controlled trials. Brain Behav. 2024;14:e3388.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Lin W-H, Yi C-C. Unhealthy sleep practices, conduct problems, and daytime functioning during adolescence. J Youth Adolesc. 2015;44:431–46.

    Article  PubMed  Google Scholar 

  61. Wei X, Ma J, Liu S, Li S, Shi S, Guo X, et al. The effects of sleep deprivation on risky decision making. Psychon Bull Rev. 2025;32:80–96.

    Article  PubMed  Google Scholar 

  62. Van Someren EJW. Brain mechanisms of insomnia: new perspectives on causes and consequences. Physiol Rev. 2021;101:995–1046.

    Article  PubMed  Google Scholar 

  63. van Dalfsen JH, Markus CR. The influence of sleep on human hypothalamic-pituitary-adrenal (HPA) axis reactivity: A systematic review. Sleep Med Rev. 2018;39:187–94.

    Article  PubMed  Google Scholar 

  64. Galván A. The need for sleep in the adolescent brain. Trends Cogn Sci. 2020;24:79–89.

    Article  PubMed  Google Scholar 

  65. Liao A, Peng P, Tan Y, Li J, Chen Z, Zhao L et al. Sleep Disturbance Mediates the Relationship between Problematic Technology Use and Psychotic-Like Experiences: A Large Cross-Sectional Study in 87,302 Chinese Adolescents. Journal of Psychiatry and Brain Science [Internet]. 2024 [cited 2024 Jul 15];9. Available from: https://jpbs.hapres.com/htmls/JPBS_1613_Detail.html

  66. Alshammari T, Alseraye S, Rogowska A, Alrasheed N, Alshammari M. Examining the indirect effect of online gaming on depression via sleep inequality and Anxiety-A serial and parallel mediation analysis. J Clin Med. 2022;11:7293.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Fekih-Romdhane F, Lamloum E, Loch AA, Cherif W, Cheour M, Hallit S. The relationship between internet gaming disorder and psychotic experiences: cyberbullying and insomnia severity as mediators. BMC Psychiatry. 2023;23:857.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Peng P, Chen Z, Ren S, Liu Y, Li J, Liao A et al. Internet gaming disorder and suicidal behaviors mediated by sleep disturbance: a large-scale school-based study in 135,174 Chinese middle school students. Eur Child Adolesc Psychiatry. 2025. Published online March 3, 2025

  69. Peng P, Chen ZM, Ren SL, He Y, Li JG, Liao AJ, et al. Internet gaming disorder and depression mediated by impaired resilience and sleep distress: a three-wave longitudinal study among Chinese adolescents. Epidemiol Psychiatr Sci. 2025;34:e11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. López-Fernández FJ, Mezquita L, Griffiths MD, Ortet G, Ibáñez MI. The role of personality on disordered gaming and game genre preferences in adolescence: gender differences and person-environment transactions. Adicciones. 2021;33:263–72.

    Article  PubMed  Google Scholar 

  71. Teng Z, Pontes HM, Nie Q, Xiang G, Griffiths MD, Guo C. Internet gaming disorder and psychosocial well-being: A longitudinal study of older-aged adolescents and emerging adults. Addict Behav. 2020;110:106530.

    Article  PubMed  Google Scholar 

  72. Xu X, Li H, Bai R, Liu Q. Do boys and girls display different levels of depression in response to mobile phone addiction?? Examining the longitudinal effects of four types of mobile phone addiction?. Psychol Res Behav Manag. 2024;17:4315–29.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Mikuška J, Vazsonyi AT. Developmental links between gaming and depressive symptoms. J Res Adolesc. 2018;28:680–97.

    Article  PubMed  Google Scholar 

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Acknowledgements

We would like to acknowledge all the participants, their parents and staffs who help proceed the study procedure.

Funding

This research was supported by the STI 2030-Major Projects of China under Grant 2022ZD0211200, the National Natural Science Foundation of China under Grant U22A20302, and the Municipal Key R&D Program of Ningbo (2023Z175) to YH Liao. It was supported by the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China under Grant No.LBD23H090001 to JS Tang. The funding had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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Authors and Affiliations

  1. Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China

    Pu Peng, Jieyin Jin, Xu Shao, Shanshan Chen, Jinsong Tang & Yanhui Liao

  2. Department of Psychiatry, Zigong Mental Health Center, Zigong, Sichuan, China

    Zhangming Chen, Ruini He, Yudiao Liang & Youguo Tan

  3. Department of Nursing, Sichuan Vocational College of Health and Rehabilitation, Zigong, Sichuan, China

    Silan Ren

  4. Department of Psychiatry, National Center for Mental Disorders, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China

    Ying He, Jinguang Li, Aijun Liao, Linlin Zhao & Xiaogang Chen

  5. East Qingchun Road, Hangzhou, Zhejiang, P.R. China

    Yanhui Liao

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  1. Pu Peng
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Contributions

Yanhui Liao contributed to all aspects of the study. Pu Peng contributed to the analysis and interpretation of data, statistical analysis, and the drafting of the manuscript. Zhangming Chen, Jinsong Tang, and Xiaogang Chen contributed to the study design. Jieyin Jin, Jiguang Li, Aijun Liao, Linlin Zhao, Silan Ren, Shanshan Chen, Shao Xu, Ruini He, Yudiao Liang, and Youguo Tan contributed to the data acquisition. All authors have reviewed, revised and approved the final manuscript.

Corresponding author

Correspondence to Yanhui Liao.

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Ethics approval and consent to participate

This study was performed in line with the principles of the Declaration of Helsinki. The study was approved by the Ethics Committee of the Zigong Mental Health Center (Approval No. 2020-8-01). Informed consent was obtained from all participants and their parents for those under 18 years old.

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The authors declare no competing interests.

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Peng, P., Jin, J., Chen, Z. et al. Impaired sleep quality mediates the relationship between internet gaming disorder and conduct problems among adolescents: a three-wave longitudinal study. Child Adolesc Psychiatry Ment Health 19, 26 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13034-025-00889-2

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Keywords

Child and Adolescent Psychiatry and Mental Health

ISSN: 1753-2000