research gap about online games addiction

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Systematic literature review online gaming addiction among children and young adults: A framework and research agenda

Affiliations.

1 Colegio Universitario de Estudios Financieros (CUNEF), Madrid, Spain. Electronic address: [email protected].
2 ITM Business School, ITM University, India. Electronic address: [email protected].
3 Southampton Business School, University of Southampton, Southampton, UK. Electronic address: [email protected].
PMID: 35104738
DOI: 10.1016/j.addbeh.2022.107238

Online gaming addiction refers to a persistent and recurrent use of internet to engage in games leading to significant impairment or distress in a person's life. With the current pandemic, media reports suggest that the greater access of online devices among children and young adults has intensified online gaming addiction. However, the domain of online gaming addiction is a relatively new phenomenon with disparate studies examining various facets of it. Hence, the purpose of this research is to analyze the existing literature in order to identify the emerging trends in this area and to provide a systematic review that can be used as guidance for future research in this emerging field. Starting from the gaps that this review highlights, the proposed directions will help scholars find issues and gaps not sufficiently explored that can constitute the bases for further research pathways.

Keywords: Addiction; Children; Games; Internet; Online gaming disorders; Review; Young adults.

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Online game addiction among adolescents: motivation and prevention factors

Online game addiction has become a common phenomenon that affects many individuals and societies. In this study we rely on the functionalist perspective of human behavior and propose and test a balanced model of the antecedents of online game addiction among adolescents, which simultaneously focuses on motivating, and prevention and harm reduction forces. First, a sample of 163 adolescents was used for validating and refining a survey instrument. Second, survey data collected from 623 adolescents were analyzed with Partial Least Squares techniques. The findings point to several functional needs (e.g., need for relationship and need for escapism) that drive online game playing and addiction, as well as to several prevention and harm reduction factors (e.g., education, attention switching activities) that reduce game playing time and alleviate online game addiction. The effects of motivation and prevention factors on online game addiction are often partially mediated by online game playing. Implications for research and practice are discussed.

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More grateful, less addicted! Understanding how gratitude affects online gaming addiction among Chinese college students: a three-wave multiple mediation model

Bin Gao 1 na1 ,
Yi Xu 1 na1 ,
Gui Luo 2 &
Weiyi Li 3

BMC Psychology volume 11 , Article number: 241 ( 2023 ) Cite this article

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Online game addiction has become a prominent public concern, particularly among emerging adults, warranting in-depth investigation. Despite prior cross-sectional research indicating a negative correlation between gratitude and online gaming addiction, a dearth of longitudinal research exists in this area. Furthermore, the underlying mechanisms that explain the link between gratitude and online gaming addiction remain poorly understood, highlighting a critical research gap in the field.

To bridge this gap, our study adopted a three-wave longitudinal design and constructed a multiple mediation model. Over the course of one year, data was collected from a sample of Chinese undergraduates, with 319 students participating at Time 1, 305 at Time 2, and 292 at Time 3. Participants were administered online self-report surveys, enabling the acquisition of valuable data regarding their levels of gratitude, online game addiction, self-control, and loneliness.

The findings revealed a negative correlation between gratitude measured at Time 1 and online game addiction assessed at Time 3. Further analysis demonstrated that both self-control and loneliness played multiple mediating roles at Time 2 in the link between gratitude and online game addiction.

These research findings shed light on the underlying mechanisms between gratitude and online game addiction, which provide implications for developing interventions (e.g., interventions based on gratitude) for reducing young adults’ online game addiction.

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Introduction

Playing online games is a popular leisure activity, and the number of players worldwide is increasing dramatically. For instance, as of June 2022, the number of online game users in China has reached 552 million, representing approximately 52.6% of all Internet users [ 1 ]. However, excessive online gaming may lead to online game addiction. Online game addiction is defined as the persistent and repeated use of the internet to play games that causes significant impairment or distress in a given user’s life [ 2 ]. Currently, it is important to acknowledge that online gaming addiction is a broad term that is commonly used to describe excessive and problematic gaming behavior specifically related to online games and lacks standardized diagnostic criteria, unlike internet gaming disorder, which is generally recognized as a clinical condition [ 3 ]. Thus, this study adopts the term “online gaming addiction” instead of “internet gaming disorder”. Based on a systematic review, the prevalence rates of online game addiction in China were found to range from 3.5 to 17%, indicating a higher prevalence compared to global reports [ 4 ]. Furthermore, online game addiction becomes more prevalent among children and young adults due to the COVID-19 pandemic [ 5 , 6 , 7 ]. More importantly, online game addiction could be linked to various detrimental consequences, such as problems in emotional expression [ 8 ], poor sleep quality [ 9 ], depression [ 10 ], and even suicide [ 11 ]. Therefore, it is theoretically and practically necessary to investigate the protective or risk factors of online game addiction. In recent years, with the flourishing of positive psychology, gratitude has been increasingly highlighted by researchers for its positive effects on coping with online game addiction [ 12 ].

Previous empirical studies have made progress in exploring the correlation between gratitude and online game addiction [ 13 ]. However, these studies have two major limitations. Firstly, the prior researcher primarily used cross-sectional designs, limiting the possibility of making causal inferences regarding the relationship between gratitude and online game addiction [ 12 ]. Additionally, little empirical evidence exists regarding the underlying mechanisms of this relationship [ 13 ]. Secondly, the majority of research in this field has focused on children [ 14 , 15 ] and adolescents [ 16 , 17 , 18 ], neglecting the fact that college students are also at risk for online game addiction [ 19 ]. To address these gaps, the present study aims to investigate the following research questions:

What is the longitudinal association between gratitude and online gaming addiction among college students?

What potential mediating variables exist between college students’ gratitude and their online game addiction?

By examining these research questions, we seek to gain a deeper understanding of the longitudinal relationship between gratitude and online gaming addiction among college students, as well as the potential mediating roles of self-control and loneliness. According to the Interaction of Person-Affect-Cognition-Execution (I-PACE) model [ 20 ], the development of addictive behaviors (e.g., online game addiction) is influenced by various factors, including personal characteristics (e.g., trait gratitude), affective states (e.g., loneliness), and behavioral execution (e.g., impaired self-control). Empirical studies have shown that loneliness has been identified as a risk factor for online game addiction [ 18 ], while gratitude and self-control are recognized as protective factors against online game addiction [ 12 , 14 ]. In response to the need for further expansion of the I-PACE model, we aim to integrate these three factors to provide a more comprehensive framework for understanding their combined influences on online game addiction.

Gratitude and online game addiction

Gratitude refers to an individual’s psychological tendency to recognize and appreciate positive experiences or outcomes resulting from others’ help or kindness, expressed through cognitive, emotional, and behavioral responses [ 21 ]. According to the broaden-and-build theory [ 22 ], positive emotions like gratitude can foster the development of long-lasting personal resources, such as resilience, that may reduce the likelihood of developing addictive behaviors. Empirical study has shown that gratitude can serve as a protective factor against a range of undesirable addictive behaviors, including substance addiction [ 23 , 24 ], internet gaming disorder [ 25 ], and online game addiction [ 3 ]. Furthermore, gratitude has been recognized as a valuable tool for enhancing well-being in 12-step addiction recovery programs, and research suggests that individuals with higher levels of gratitude have positive associations with 12-step practices, post-traumatic growth, and social support, and negative associations with stress and health symptoms [ 26 ]. Gratitude interventions have also proven beneficial for individuals with substance use disorders [ 27 , 28 ]. Therefore, we hypothesize that gratitude would be negatively associated with online game addiction (H1).

Self-control as a mediator

Self-control pertains to the capacity to regulate one’s thoughts, emotions, and actions in order to attain long-term objectives and effectively respond to evolving situational requirements [ 29 ]. Trait gratitude has been found to be positively associated with self-control among university students [ 30 ]. According to the strength model of self-control, self-control is viewed as a finite resource that can be gradually exhausted over time [ 31 ], while gratitude-based interventions, such as gratitude journaling, can enhance self-control resources [ 32 ]. In addition, college students with higher levels of gratitude are more likely to use proactive self-control strategies to avoid temptation [ 33 ], which in turn may help curb addictive behaviors. A cross-sectional study has showed that gratitude positively predicts self-control in college students [ 34 ]. In addition, self-control serves as a safeguard against online game addiction. For example, a study on interventions for online game addiction found a significant association between increased self-control among gamers and reductions in both the severity of addiction and the amount of time spent playing online games [ 35 ]. People with higher levels of self-control showed lower levels of pathological gaming [ 36 ] and internet gaming disorder [ 14 ]. Moreover, previous research has identified self-control as a mediator in the processes of online game addiction [ 37 ]. Thus, we propose that self-control may mediate the link between gratitude and online game addiction (H2).

Loneliness as a mediator

Loneliness is a negative emotional state that arises when an individual’s social connections fail to meet their expectations, resulting in negative psychological experiences such as emptiness, boredom, helplessness, and bitterness [ 38 ]. Young adults have been particularly vulnerable to loneliness and related mental health problems during the COVID-19 pandemic [ 39 , 40 ]. As a negative emotion, loneliness plays a mediating role in the link between gratitude and mental health problems [ 41 ]. In addition, a longitudinal study showed that loneliness could mediate the relationship between parental loneliness and adolescents’ online game addiction [ 18 ]. Intervention studies have shown that gratitude-based interventions, such as gratitude writing exercises, can alleviate loneliness in older adults [ 42 ]. Moreover, dispositional gratitude is negatively associated with loneliness [ 43 ]. Studies have found a positive association between loneliness and online game addiction among adolescents [ 44 ], and that gratitude can predict feelings of loneliness among college students [ 45 ], while loneliness predicts online game addiction in adolescents [ 18 ]. Therefore, it is hypothesized that loneliness may mediate the link between gratitude and online game addiction (H3).

The serial mediating roles of self-control and loneliness

The I-PACE model posits that individuals with behavioral execution deficiency [ 20 ], such as low self-control, and negative affective states like loneliness are more susceptible to developing addictive behaviors, such as online game. Low self-control has also been linked to loneliness, with studies showing that individuals with low self-control may struggle to establish and maintain social relationships, contributing to feelings of loneliness [ 46 ]. Similarly, a recent study found that self-control significantly predicts feelings of loneliness among college students [ 47 ]. Building on these theoretical and empirical findings, we suggest that gratitude could enhance self-control in young adults, which could help alleviate feelings of loneliness and reduce addictive online game playing in the long term. Consequently, we propose the hypothesis that there may exist a sequential mediation effect of self-control and loneliness in the link between gratitude and online game addiction (H4).

The present study

In summary, this research offers several significant contributions to the field of online game addiction and also extends the existing literature. Firstly, it investigates the longitudinal association between gratitude and online game addiction, extending previous studies using a cross-sectional study design. Secondly, it employs a three-wave longitudinal design to explore the mediating mechanisms through which gratitude influences students’ online game addiction. Thirdly, it expands the scope of the I-PACE model by incorporating protective factors, such as gratitude, to better explain addictive behaviors. Specifically, the study examines whether the effects of gratitude on online game addiction are mediated by self-control and loneliness (as illustrated in Fig. 1 ). Notably, this is the first study to directly test this theoretical proposition among college students.

The hypothesized model

Participants

Participants were recruited from a public Chinese university using convenience sampling during the epidemic of COVID-19. This university is a teaching-focused institution with a primary focus on medical disciplines, accommodating a student population exceeding 15,000. The data was collected at three different points in time after the freshmen entered university during the 2021–2022 school year: the beginning (Time1), middle (Time 2), and end (Time 3) of the year. The average interval was 3 months. A total of 381 college freshmen participated in the T1 online survey. Subjects who took less than 5 min to fill out the online questionnaire and had no experience in online games were excluded, resulting in the valid sample of 319 students (M age = 18.24, SD = 0.74, 58.9% females). Among the participants, 177 were from urban areas, while 142 were from rural regions. Notably, a majority of the participants were pursuing academic disciplines primarily concentrated in medical-related fields. Of the 319 participants, 305 students and 292 students completed the T2 survey (subject attrition rate = 0.04%) and T3 survey (attrition rate = 0.08%), respectively. All subjects had online game experience at T3, and their self-reported time spent playing online games was 2.56 ( SD = 1.90) hours per day.

Data for this investigation was collected via the Questionnaire Star Platform, a popular online survey agency in China. Subjects signed an informed consent form before completing the online questionnaire. All participants who were willing to participate in the study signed consent form. They were invited to fill out the surveys in the classroom. This longitudinal study was approved by the ethics committee of the corresponding author’s institution.

Trait gratitude

The measurement of trait gratitude in this study utilized the gratitude questionnaire–6 developed by McCullough et al. [ 21 ]. This unidimensional scale comprises 6 items (e.g., “I am grateful to a wide variety of people”) and has demonstrated good reliability and validity among Chinese college students [ 30 ]. Subjects provided their own responses using a 7-point Likert scale, ranging from 1 ( strongly disagree ) to 7 ( strongly agree ). The scores for all items were summed, and the average score was calculated. A higher average score indicates a higher level of gratitude. The Cronbach’s α coefficient for the scale was calculated to be 0.71 at Time 1 in this study.

Self-control

In this study, self-control was assessed using the brief self-control scale developed by Morean et al. [ 48 ]. This scale comprises 7 items (e.g., “I am good at resisting temptation”) and encompasses two dimensions: self-discipline and impulse control. Previous research has indicated the suitability of this scale for Chinese emerging adults [ 49 ]. Notably, items 2, 4, 6, and 7 required reverse scoring. Subjects provided their own responses using a 5-point Likert scale, ranging from 1 ( strongly disagree ) to 5 ( strongly agree ). The average score was obtained by summing the scores for all items. A higher average score indicates a higher level of self-control. The Cronbach’s α coefficient for the scale was calculated to be 0.70 at Time 2 in this study.

To assess loneliness in this study, the Short-Form Loneliness Scale developed by Hays and Dimatteo [ 50 ] was utilized. This scale consists of eight items that tap into the experience of loneliness, such as “people are around me but not with me”. Previous research conducted among Chinese college students [ 51 ] has demonstrated the satisfactory reliability and validity of this unidimensional scale. Participants were instructed to read each item and indicate their responses on a 4-point Likert scale, ranging from 1 ( never ) to 4 ( always ). The scores for all items were summed, and the average score was computed. A higher average score indicated a greater level of loneliness. The Cronbach’s α coefficient for the scale was 0.81 at Time 2 in this study.

Online game addiction

The measurement of online game addiction in this study utilized the Chinese version of the Online Game Addiction Scale, which is a subscale derived from the Internet Addiction Scale developed by Zhou and Yang [ 52 ]. This scale is a unidimensional measure comprising 8 items (e.g., “I basically spend my time after school playing online games”). Participants responded to these items using a 5-point Likert scale ranging from 1 ( strongly disagree ) to 5 ( strongly agree ). The average score was obtained by summing the scores for all items, with a higher average score indicating a greater level of online game addiction. The Cronbach’s α coefficient for this scale was calculated to be 0.91 at Time 3 in this study.

Statistical analyses

Data screening was conducted to guarantee the quality of the data. Specifically, we noticed that no outliers were present in the data set, and any missing data were addressed through mean imputation, as the proportion of missing data was less than 1% for all variables [ 53 ]. The skewness and kurtosis values (see Table 1 ) for all variables were assessed, and all values fell within the acceptable range of -2 to + 2 for skewness and − 7 to + 7 for kurtosis, indicating a normal distribution of the data [ 54 ]. To test the possible presence of common method biases, we conducted a Harman’s single factor test, which revealed no significant common method variance present in our data. Correlation analyses were performed among the main variables using SPSS 24.0, and we utilized model 6 in the PROCESS macro for the regression analyses. To ensure comparability among variables, all continuous variables were standardized prior to the regression analysis. In addition, gender and age were considered as potential control variables, as prior studies [ 2 , 37 ] have shown their potential influence on individuals’ online game addiction.

Descriptive and correlation analysis

Table 1 displays the descriptive statistics (i.e., mean and standard deviation) and correlation matrix of the variables. Gratitude at Time 1 exhibited a positive correlation with self-control at Time 2, and a negative correlation with loneliness at Time 2 and online game addiction at Time 3. Self-control at Time 2 demonstrated a negative correlation with loneliness at Time 2 and online game addiction at Time 3. Additionally, loneliness at Time 2 exhibited a positive correlation with online game addiction at Time 3. Thus, Hypothesis 1 was supported.

Testing the multiple mediation model

We employed Model 6 of the PROCESS macro [ 55 ] to investigate the multiple mediating effects of gratitude through self-control and loneliness. The results, as presented in Tables 2 and Fig. 2 , demonstrated that all pathways were statistically significant, except for the direct effect of gratitude on online game addiction (β = − 0.04, p > 0.05). Specifically, gratitude exhibited a significant positive prediction of self-control (β = 0.19, p < 0.01) and a significant negative prediction of loneliness (β = − 0.20, p < 0.01). Furthermore, self-control significantly predicted both loneliness (β = − 0.41, p < 0.001) and online game addiction (β = − 0.19, p < 0.01). Additionally, loneliness had a significant positive effect on online game addiction (β = 0.18, p < 0.05). Furthermore, none of the 95% confidence intervals for the path coefficients mentioned above included zero, indicating that all path coefficients were statistically significant.

The multiple mediation effects of self-control and loneliness. Note The presence of a dashed line in the figures indicates that the path coefficient was not found to be significant.

Next, the percentile bootstrap method with bias correction was employed to assess the mediation effect. The results presented in Table 3 indicate that the 95% confidence interval for the direct effect encompasses 0, suggesting non-significance of the direct effect. Conversely, the 95% confidence interval for the indirect path excludes 0, indicating significant mediation effects. These findings suggest that self-control and loneliness serve as complete mediators between gratitude and online game addiction. As a result, Hypotheses 2–4 were supported, indicating significant mediation effects of self-control and loneliness. The multiple mediation model employed in this study accounted for 12% of the variance in online gaming addiction among college students.

This research adopts the I-PACE model as a theoretical framework to examine the influence of predisposing variables (gratitude, self-control, loneliness) on online game addiction among emerging adults, and to provide practical recommendations for addressing the escalating issue of online game addiction. The primary aim of this paper is to contribute to the existing knowledge regarding the longitudinal association between gratitude and online game addiction, as well as to shed light on the underlying mediating mechanisms that link these variables. The present study confirms the presence of a negative relationship between gratitude and online game addiction, and additionally reveals that self-control and loneliness fully mediate this relationship. Further elaboration on the key findings will be provided in the subsequent sections, offering a comprehensive discussion.

The results has shown that gratitude is negatively associated with online game addiction, which is consistent with prior cross-sectional study [ 12 ]. Our results are in line with the coping theory [ 56 ], which indicates that individuals with high gratitude are more likely to seek instrumental and affective social support from others [ 57 ] and they tend to adopt more active coping strategies to deal with problems in life [ 58 ], rather than resorting to negative strategies such as online game addiction, thus helping to reduce or counteract online game addiction. Furthermore, this result further supports the broaden-and-build theory proposed by Fredrickson [ 22 ]. In detail, gratitude can help people alleviate negative emotions [ 59 ] and build personal lasting positive resources, such as self-esteem [ 60 ], enhance well-being [ 61 ] and life satisfaction [ 62 ]. These resources are critical to overcoming game addiction for young people. Accordingly, when such positive resources are diminished or unavailable, individuals are more susceptible to engaging in undesirable behaviors, such as online game addiction.

The findings of this study indicate a negative association between gratitude and online game addiction, which is in accordance with previous cross-sectional research [ 12 ]. These results align with the coping theory [ 56 ], which suggests that those with greater gratitude are more inclined to seek instrumental and affective social support from others [ 57 ]. Moreover, they are more likely to employ active coping strategies to effectively deal with life challenges [ 58 ], rather than resorting to negative coping mechanisms like online game addiction. Consequently, gratitude plays a role in reducing or countering online game addiction. Furthermore, these results provide additional support for Fredrickson’s broaden-and-build theory of positive emotions [ 22 ]. Specifically, gratitude can assist individuals in alleviating negative emotions [ 59 ] and cultivating enduring positive resources such as self-esteem [ 60 ], overall well-being [ 61 ], and life satisfaction [ 62 ]. These personal resources are crucial for combating game addiction among young individuals. Consequently, in the absence of such positive resources, individuals are more susceptible to engaging in undesirable behaviors like online game addiction.

Consistent with our hypotheses, the results indicate that self-control functions as a mediator between gratitude and online game addiction. In the first stage of the mediation process (gratitude → self-control), gratitude significantly and positively predicts self-control, which is in accordance with previous research [ 34 ]. There are two plausible explanations for this finding. Firstly, prior studies have demonstrated that people who are grateful are more able to exercise self-control by avoiding temptations [ 33 ], delaying immediate gratification, and opting for larger, delayed rewards [ 63 ]. This suggests that gratitude may play a vital role in promoting self-control. Secondly, positive emotions like gratitude broaden an individual’s range of thoughts and actions and foster the development of enduring personal resources [ 64 ], including resilience and social support. Consequently, individuals are better equipped to manage their emotions and behaviors. In the second stage of the mediation process (self-control → online game addiction), self-control negatively predicts online game addiction, which aligns with previous research [ 37 ]. One potential explanation for the link between self-control and online game addiction is that those with greater self-control are more capable of delaying immediate gratification and resisting the immediate rewards associated with addictive behaviors. Instead, they engage in behaviors that offer long-term benefits [ 65 ]. In line with self-control theory [ 29 ], individuals who possess effective impulse regulation and resistance to temptation are less likely to engage in addictive behaviors, including online game addiction. Hence, it can be inferred that online game addiction may arise from a deficiency in self-control or a failure to exercise self-control.

Consistent with our hypothesis, loneliness is another important explanatory mechanism through which gratitude is linked to college students’ online game addiction. For the first stage of the mediation process (gratitude→loneliness), gratitude could significantly and positively predict loneliness, which is in line with previous studies [ 34 ]. Based on a positive psychology perspective, gratitude is suggested to have the potential to alleviate the negative impact of loneliness by fostering psychological flexibility, engagement in life, and strengthening social relationships [ 66 , 67 ]. By focusing on the positive actions of others and expressing gratitude, individuals may be more likely to form and maintain positive social relationships, which can help to reduce loneliness [ 68 ]. For the second stage of this mediation process (loneliness →online game addiction), loneliness could positively predict online game addiction, which is in line with previous studies [ 37 ]. One theoretical perspective that may help to explain this finding is the self-medication hypothesis [ 69 , 70 ], suggesting that individuals may self-medicate or alleviate negative emotions, including loneliness, by engaging in addictive behaviors such as online gaming.

The aim of this study was to investigate the mechanisms that underlie the link between gratitude and online game addiction in college students, with a specific focus on the serial mediating roles of self-control and loneliness. The findings revealed that both self-control and loneliness played individual and combined mediating roles in the link between gratitude and online game addiction. Specifically, gratitude was positively linked to self-control and negatively linked to loneliness, which subsequently influenced the likelihood of experiencing online game addiction among college students. Moreover, the sequential mediation analysis demonstrated that self-control and loneliness sequentially mediated the influence of gratitude on online game addiction. This suggests that higher levels of gratitude promote self-control, leading to reduced loneliness and ultimately decreasing the risk of online game addiction. Overall, This study helps to understand the relationship between the association between gratitude and online game addiction by proposing an integrated sequential mediation model that incorporates gratitude, self-control, loneliness, and online game addiction. This model offers a comprehensive framework that illuminates the underlying mechanisms involved in the link between gratitude and online game addiction.

Implications

Based on the I-PACE model, we constructed a multiple mediation model to reveal how gratitude affects online game addiction, which has implications for intervening with students addicted to online gaming. First, the current study has expanded existing studies by revealing the longitudinal relationship and the mediation mechanisms between gratitude and online game addiction. Second, to our knowledge, this is the first attempt to reveal that self-control and loneliness are both vital factors linking gratitude to online game addiction, and this result suggests that gratitude intervention programs (i.e., gratitude journaling or letter) can be used to inhibit college students’ online game addiction. Third, previous studies mainly focused on risk factors of online game addiction (e.g., sensation seeking, anxiety and impulsivity), while studying online game addiction from a positive psychology perspective may help identify key character strengths (e.g., gratitude) that could protect college students from developing online game addiction. The I-PACE model currently does not include protective factors (e.g., gratitude) of addictive behavior. Our research results indicate that online compulsive buying are influenced by both risk and protective factors, thus extending the I-PACE model to some extent.

Limitations and future directions

While our research has provided valuable insights, it is important to acknowledge several limitations. Firstly, this longitudinal study focused on examining whether gratitude can predict online game addiction among freshmen, but it did not explore the reverse relationship between the two variables. Future research could employ a cross-lagged design to investigate the reciprocal association between gratitude and online game addiction. Secondly, our study sample consisted of Chinese college students, and therefore, caution should be exercised when generalizing the findings to other population groups. Additionally, the absence of comparative studies examining online game addiction through cross-cultural and cross-national research is a noteworthy gap. It is crucial for future studies to validate our findings in diverse cultural contexts. Furthermore, we did not distinguish the types of online games that participants played. However, future studies have the opportunity to delve deeper into this aspect and explore how specific game characteristics, such as massively multiplayer online games or role-playing games, may influence the relationship between gratitude and online game addiction. Thirdly, this study primarily explored the link between trait gratitude and online game addiction. It is worth noting that gratitude can be differentiated into two types: trait gratitude and state gratitude. These distinct forms of gratitude may exert varying influences on online game addiction, which could be considered in further research. Lastly, it is essential to assess the effectiveness of gratitude-based interventions in mitigating online game addiction. Future research could employ a quasi-experimental design to examine the effectiveness of gratitude intervention on online game addiction.

Online game addiction has become a prominent public concern, particularly among college students. Previous research has established a robust correlation between gratitude and online game addiction. We conducted a longitudinal study involving Chinese college students and identified the mediating roles of self-control and loneliness in the link between gratitude and online game addiction. Our findings contribute to a deeper understanding of the mechanisms that connect gratitude and online game addiction, emphasizing the protective influence of gratitude against the development of online game addiction. These findings have significant implications for developing effective coping strategies to promote rational online game playing among college students, as well as for the prevention and intervention of online gaming addiction, such as implementing gratitude-based interventions.

Data Availability

The corresponding author can provide the datasets used and/or analyzed during the current study upon reasonable request.

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Acknowledgements

We extend our gratitude to the participating schools and research assistants for their assistance in data collection. Lastly, we would like to express our sincere appreciation to all the participants for their valuable contributions, without which this study would not have been possible.

This research did not receive any specific funding from public, commercial, or not-for-profit sectors.

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Bin Gao and Yi Xu contributed equally to this work.

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School of Education, Shanghai Normal University, Shanghai, 200234, China

Bin Gao, Yi Xu & Lu Bai

Mental Health Center, Hefei University of Technology, Hefei, 230009, China

School of Business Administration, Jimei University, Xiamen, 361021, China

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Bin Gao and Yi Xu considered as co-first authors for their contributions to the conception and design of the study. Bin Gao conducted the statistical analysis and wrote the first draft of the manuscript. Lu Bai revised and edited the manuscript and checked the statistical results. Gui Luo and Weiyi Li contributed to questionnaire design and data collection. All authors have approved the manuscript and agree to its submission to this journal.

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Gao, B., Xu, Y., Bai, L. et al. More grateful, less addicted! Understanding how gratitude affects online gaming addiction among Chinese college students: a three-wave multiple mediation model. BMC Psychol 11 , 241 (2023). https://doi.org/10.1186/s40359-023-01271-7

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Online Gaming Addiction and Basic Psychological Needs Among Adolescents: The Mediating Roles of Meaning in Life and Responsibility

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Alican Kaya ORCID: orcid.org/0000-0003-2933-0161 1 ,
Nuri Türk ORCID: orcid.org/0000-0002-7059-9528 2 ,
Hasan Batmaz ORCID: orcid.org/0000-0002-5979-1586 3 &
Mark D. Griffiths ORCID: orcid.org/0000-0001-8880-6524 4

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Individuals whose basic needs are naturally satisfied are much less dependent on their environment and more autonomous. Basic psychological needs (i.e., the general motivators of human actions) are significant predictors of online gaming addiction. Moreover, it has been posited that meaning and responsibility in life are at the center of life from an existential point of view. Therefore, a hypothetical model was tested to examine the relationships between basic psychological needs (autonomy, competence, relatedness), online gaming addiction, responsibility, and meaning in life. Data were collected from a sample of 546 participants. Mediation analysis was conducted, and the results indicated that basic psychological needs, online gaming addiction, responsibility, and meaning in life had significant negative and positive relationships. The findings indicated that responsibility and meaning in life had a serial mediating effect in the relationship between basic psychological needs and online gaming addiction. The findings also showed that the inverse relationship between online gaming addiction and basic psychological needs was at least partially explained by meaning in life and responsibility. The results of the present study are of great importance and suggest that interventions to satisfy the basic psychological needs of adolescents may help prevent online gaming addiction.

How the Dark Triad associated with internet gaming disorder? The serial mediation of basic psychological needs satisfaction and negative coping styles

The Mechanism Underlying the Effect of Actual-Ideal Self-Discrepancy on Internet Gaming Addiction: a Moderated Mediation Model

Cognitive, Metacognitive, Motivational, and Emotional Predictors of the Intensity of Internet Gaming Disorder among Adolescents

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Introduction

Technological addictions have become an area of increasing research interest and are conceptualized as non-chemical (i.e., behavioral) addictions (Kuss & Billieux, 2017 ). Moreover, they can be engaged in actively or passively (Widyanto & Griffiths, 2006 ). For example, television addiction is a passive technological addiction, whereas smartphone addiction and Internet addiction are active technological addictions (Griffiths, 2017 ). Online addictions have increased rapidly due to the increased use of smartphones, tablets, and laptops. Furthermore, overuse of the Internet has been conceptualized in a number of different ways, including problematic Internet use (Aboujaoude et al., 2006 ; Young, 2009 ), excessive Internet use (Choi et al., 2009 ; Lee et al., 2008 ), and Internet addiction (Griffiths, 2017 ) with some considering it to be an impulsive disorder (Young & Rodgers, 2009 ). In addition, online gaming addiction, which is another addiction associated with the Internet, is defined by the American Psychiatric Association (APA, 2013 ) as the consistent and prolonged use of the Internet to play videogames, frequently with other gamers, that causes disruption and clinically impairs several aspects of a person’s life (e.g., personal relationships, occupation and/or education). Key characteristics of online gaming addiction are individuals obsessively playing online videogames to the point of neglecting everything else in their lives, which leads to social and/or psychological disorders in such individuals (Ates et al., 2018 ; Batmaz & Çelik, 2021 ).

Previous studies have indicated various variables that predict and/or are associated with gaming addiction, including attention-deficit/hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety and depression (Andreassen et al., 2016 ), social anxiety (Karaca et al., 2020 ), low self-esteem (Kim et al., 2022 ), inter-personal competence (Lee et al., 2019 ), relationship problems and relationship problems, and hostile family environment (Sela et al., 2020 ). In addition, social skill deficits (Mun & Lee, 2022 ), social and psychological isolation (Young, 2009 ), perceived stress (Rajab et al., 2020 ), suicidality (Erevik et al., 2022 ), and aggressive behaviors (McInroy & Mishna, 2017 ) have been reported among individuals who develop gaming addiction.

Although online gaming meets the various needs of individuals, when the behavior turns into an addiction, it leads to adverse effects on individuals, especially adolescents, where it can impair their mental health (Batmaz et al., 2020 ; Purwaningsih & Nurmala, 2021 ). Among adolescents, online gaming addiction has been reported to disrupt mental health, increase depression, anxiety, and psychoticism, disrupt family relationships (De Pasquale et al., 2020 ), lower quality of life (Beranuy et al., 2020 ), increase social phobia (Wei et al., 2012 ), lower school performance, and improve sleep deprivation (Chamarro et al., 2020 ; Király et al., 2015 ). In short, online gaming addiction negatively affects adolescents’ lives in different areas (Griffiths, 2022 ; Haberlin & Atkin, 2022 ). Therefore, research is needed to delineate the causes of online gaming addiction, eliminate its adverse effects, and implement necessary treatment.

Although many studies have been conducted examining online game addiction among adolescents (see Rosendo-Rios et al., 2022 ) for a recent review of studies), there are few studies examining the relationship between basic psychological needs and online game addiction (Bekir & Celik, 2019 ). In the present study, it is posited that basic psychological needs could be predictors due to the relationship with gaming disorders and problematic gaming (Allen & Anderson, 2018 ; Liu et al., 2021 ; Yu et al., 2015 ). When basic psychological needs are not met, it pushes individuals to exhibit maladaptive behavioral reactions (i.e., online gaming addiction) (Bekir & Çelik, 2019 ). In addition, few studies have addressed the relationship between responsibility and meaning in life and online game addiction (Arslan, 2021 ; Kaya, 2021 ). Moreover, no study has ever examined the mediating role of responsibility and meaning in life in the relationship between basic psychological needs and online game addiction. For these reasons, the present study examined the mediating roles of responsibility and meaning in life in explaining the relationship between basic psychological needs and online game addiction.

Online Gaming Addiction and Basic Psychological Needs

Self-determination theory is a well-established motivational theory comprising six mini-theories (Ryan & Deci, 2017 ). One of these mini-theories is the Basic Psychological Needs Theory (BPNT), which claims that the satisfaction of basic psychological needs is associated with better health and greater psychological well-being (Ryan & Deci, 2000 ). Basic psychological needs are requirements for psychological development, integrity, and well-being (Deci & Ryan, 2000 ). In contrast to the often-frustrating real world, videogames are designed to satisfy all three psychological needs (i.e., autonomy, competence, and relatedness) (Rigby & Ryan, 2011 ). Satisfaction of the needs for competence, autonomy, and relatedness can explain large amounts of the variance in game enjoyment (Rigby & Ryan, 2011 ; Tamborini et al., 2011 ). Online gaming can fulfill the (i) need for relatedness by directing players to social relationships with real or fictional characters, (ii) need for autonomy by giving them management and control within the game, and (iii) need for competence by making them feel successful in playing challenging videogames (Allen & Anderson, 2018 ).

Individuals addicted to videogames need novelty seeking, socialization, competition, and/or entertainment (Hussain et al., 2012 ; Larrieu et al., 2022 ). Studies have shown that gaming addiction is related to basic needs (Billieux et al., 2015 ) and psychological needs such as success, independence, fun, and respect (Herodotou et al., 2012 ). The increasing demand for playing videogames shows that adolescents try to satisfy some of their psychological needs via the Internet (Shen et al., 2013 ; Turan, 2021 ). One longitudinal study found that problematic online gaming and satisfaction of basic psychological needs were positively associated (Yu et al., 2015 ). It has also been reported that adolescents whose basic psychological needs were not met and whose perceived social support was low had high levels of gaming addiction (Yıldırım & Zeren, 2021 ). In this context, some studies claim that online games are tools for satisfying basic psychological needs (Oliver et al., 2016 ). However, studies have shown that the low level of basic psychological need satisfaction in real life can be met with high need satisfaction in online gaming, which leads to addiction for a small minority (Kardefelt-Winther, 2014 ; Rigby & Ryan, 2017 ; Wu et al., 2013 ). Based on the aforementioned literature, it was expected that there would be a significant negative relationship between basic psychological needs derived from real-life and online gaming addiction.

Online Gaming Addiction and Meaning in Life

The debate about the meaning in life has been ongoing for years (Yalom, 2020 ). Because there are many definitions of meaning in life, making a standard definition of meaning in life has been difficult (King & Hicks, 2021 ; Park, 2010 ). Meaning in life is a multifaceted construct conceptualized in various ways that address the value and purpose of life, meaningful life goals, and sometimes spirituality (Jim et al., 2006 ). According to Ryff ( 1989 ), meaning in life is a sign of a sense of direction, goals, and well-being. Frankl ( 2009 ) states that meaning in life differs from individual to individual, day to day, and hour to hour. Many studies have been conducted regarding meaning in life and concepts in the literature. For instance, some of these studies assert that meaning in life increases happiness (Debats et al., 1993 ) and life satisfaction (Yıkılmaz & Demir Güdül, 2015 ) and that the presence of meaning in life positively affects psychological health (Bailey & Phillips, 2016 ) and has a high level of meaning that can lower the incidence of depression (Mascaro & Rosen, 2005 ).

Similar to the aforementioned studies, adolescents’ having meaning in life can protect them from problematic behaviors such as substance abuse and eating disorders (Brassai et al., 2011 ; Shek et al., 2019 ). Adolescence is a period of seeking identity (Erikson, 1968 ) and decision-making (Marcia, 1980 ). Steger et al., ( 2006 ) pointed out that adolescents’ experience of seeking meaning in life or having a meaning in life may be determinative for successful identity development. However, considering that questioning the meaning in life results from the search for identity, it could be speculated that adolescents who constantly play online videogames will be far from such a search. Although studies have shown that adolescents search for identity in while online gaming (Monacis et al., 2017 ; Subrahmanyam & Šmahel, 2011 ; Tanhan & Özlem, 2015 ), it has been reported that excessive online gaming can also make this exploration more maladaptive, and this may lead to online gaming addiction (King & Delfabbro, 2014 ; Kokkini et al., 2022 ). One study reported that as gaming addiction decreases among adolescents, the level of meaning in life increases (Kaya, 2021 ). In general, it is expected in the present study that the existence of meaning in life in among adolescents will reduce online gaming addiction.

Online Gaming Addiction and Responsibility

One of the characteristic features of online gaming addiction is that individuals spend their time playing online games by procrastinating and/or not doing their daily work (Thatcheret al., 2008 ). According to the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria, one criterion for Internet gaming disorder is that individuals continue to play online games despite being aware of psychosocial problems (American Psychiatric Association, 2013 ). Here, individuals fail to engage in important day-to-day responsibilities and play online games instead. Similarly, it has been shown that online gaming addicts jeopardize or lose their job, education, and/or career opportunities to play online games (Kardefelt-Winther, 2014 ). Time spent playing games instead of engaging in life’s more important tasks can be viewed as a lack of responsibility by individuals themselves, their families, and/or friends (Wartberg et al., 2017 ; Zhang et al., 2019 ).

Responsibility consists of three elements: accountability, liability, and imputability (Robinson, 2009 ). Imputability refers to individuals being responsible for their actions and decisions, accountability refers to fulfilling contractual expectations, and liability refers to assuming a moral responsibility without a contract (Holdorf & Greenwald, 2018 ). The concept of responsibility therapy is defined as the ability of individuals to meet their own needs while allowing others around them to meet their needs (Corey, 2015 ). Being conscious of responsibility means that individuals are aware of themselves and their feelings, thoughts, and pain (Yalom, 2020 ). Dökmen ( 2019 ) defines it as a responsibility to accept the consequences on others of what an individual does or does not do based on his thoughts.

In addition, it is discussed in the literature under two dimensions: emotion (Berkowitz & Daniels, 1963 ; Özen, 2013 ) and behavior (Glasser, 2005 ; Taylı, 2006 ). Individuals with a sense of responsibility have characteristics such as acting with awareness of their own and others’ rights, respecting others, and attempting to fulfill their responsibilities (Özen, 2011 ; Yough et al., 2022 ). On the other hand, individuals who do not have a sense of responsibility make themselves and others feel worthless while living without a plan or program (Cüceloğlu, 2015 ). Studies have shown that a low sense of responsibility can lead to aggression, lying, and avoidance of responsibility, while a high level of responsibility can trigger perfectionism, leading to anxiety, depression, and obsessive-compulsive disorders (Taylı, 2013 ; Wang et al., 2022 ).

The behavior of responsibility, the second sub-dimension of responsibility (Yalom, 2020 ), means that individuals can take responsibility by bearing the consequences of their behavior without attributing it to someone else (Douglass, 2001 ; Shahzadi et al., 2022 ). It has a function that improves positive activities and prevents harmful activities (Kesici, 2018 ). For example, individuals who act responsibly are respected by society and avoid punishment (Douglass, 2001 ). On the other hand, during adolescence, when serious responsibilities begin to be undertaken, a minority of individuals may move away from social life due to gaming addiction. Because of this situation, other people in the individual’s social life (e.g., family and friends) become unimportant to adolescents with low awareness of responsibility. Recent studies have observed that adolescents who excessively play videogames have difficulty fulfilling their responsibilities (Dinçer & Kolan, 2020 ; Doğan & Pamuk, 2022 ). In the present study, it was expected that adolescents with higher levels of responsibility would be less addicted to online gaming (i.e., an inverse relationship).

Basic Psychological Needs, Meaning in Life, Responsibility, and Online Game Addiction

Basic Psychological Needs Theory (BPNT) focuses on the satisfaction and frustration of psychological needs and argues that these needs significantly impact individuals’ psychological health and well-being (Ryan & Deci, 2000 ). Lack of fulfillment of basic psychological needs leads to negative consequences (e.g., depression, stress, and addiction) (Cantarero et al., 2021 ; Levine et al., 2022 ; Orkibi & Ronen, 2017 ; Xiao & Zheng, 2022 ). However, satisfying these needs is associated with positive outcomes such as general self-efficacy (İhsan et al., 2011 ), mental resilience (Kilinç & Gürer, 2019 ), subjective well-being (Akbağ & Ümmet, 2018 ), and obtaining meaning in life (Çelik & Gazioğlu, 2017 ). Furthermore, Weinstein et al. ( 2012 ) suggested that the search for meaning increased significantly when these needs were satisfied. Individuals whose needs are fulfilled are more prone to seek meaning in their life and, therefore, to experience meaning in their life, whereas individuals whose needs are not fulfilled experience a sense of meaninglessness (Eakman, 2013 ). According to Steger ( 2006 ), although individuals continue to search for meaning in one area of their lives, they may have meaning in a different area of their life. Meaning in life is defined as the purpose and importance of the life that individuals derive from their experiences (Baumeister & Vohs, 2002 ; Steger et al., 2006 ). Frankl ( 1969 ) posited that to achieve the meaning of life, an individual must take responsibility for realizing their potential, even at a young age. Therefore, a meaningful life requires individuals taking responsibility for themselves and others.

Responsibility refers to the individual’s sense of duty toward family, friends, and society (Geçtan, 2006 ), and can be examined in personal and social dimensions (Arslan & Wong, 2022 ). Personal responsibility means that an individual is accountable to themselves and to the needs or well-being of others (Ruyter, 2002 ). It also emphasizes self-responsibility by representing the individual’s behaviors and choices that can affect themselves and others (Mergler & Shield, 2016 ). Social responsibility relates to values that support individuals’ moral and prosocial behavior (Wray-Lake & Syvertsen, 2011 ). It includes decisions and actions that benefit others and society (Martins et al., 2015 ). Moreover, it is an important source of support in strengthening individuals’ mental health and improving their life skills (Martins et al., 2017 ) as well as coping with addictions (Amini et al., 2020 ). Therefore, individuals’ personal and social responsibility can protect them against negative situations such as developing addictions (e.g., online gaming addiction) (Chiou & Wan, 2007 ).

Online games allow individuals to meet other players, have fun, achieve status, and obtain financial benefits (Ballabio et al., 2017 ; Columb et al., 2022 ). In addition, escaping from the problems of real life, even temporarily, and achieving relaxation are among the benefits that individuals gain through gaming (Yee, 2006 ). Consequently, online gaming can lead individuals to play online games frequently and for long periods of time, which in turn can lead to the risk of addiction (Luciana, 2010 ; Sachdeva & Verma, 2015 ). The 11th revision of the International Classification of Diseases (ICD-11) characterized gaming disorder as a repetitive or persistent pattern of gaming behavior (World Health Organization, 2019 ). Individuals that are affected by online gaming addiction have also been reported to experience problems with interpersonal relationships (Wongpakaran et al., 2021 ), occupation (Lelonek-Kuleta et al., 2021 ), and health (Chan et al., 2022 ). As such, online gaming addiction can lead to situations that threaten the lives and functionality of individuals through the process and its consequences.

The Present Study

The present study was framed according to self-determination and existentialist positive psychology theories. Self-determination theory (SDT) suggests that the non-satisfaction or inhibition of basic psychological needs can lead to negative consequences (i.e., online gaming addiction). In addition, it emphasizes that behaviors emerge from the individual’s beliefs, meaning, and value judgments rather than external factors (i.e., social norms and group pressure). According to the SDT, need (autonomy, competence, and relatedness) predicts meaning in life (Eakman, 2013 ). Moreover, in a longitudinal study based on SDT, individuals whose basic psychological needs were fulfilled had increased meaning in life (Zhang et al., 2022 ). In addition, the existentialist theory of positive psychology suggests that the meaning in life, which individuals create themselves, can be sustained through responsibility. Individuals having responsibility can also enable them to lead a meaningful life (Arslan & Yıldırım, 2021 ; Wong, 2019 ). According to Wong ( 2010 ), meaning consists of the components of purpose, understanding, responsibility, and enjoyment (PURE). In addition to responsibility being one of the basic concepts that constitute meaning, the search for meaning in life continues intensely during adolescence (Steger, 2012 ). This is especially the case for adolescents who begin to question people and the world deeply, having a meaningful life can protect them from behavioral addictions (Qiu et al., 2022 ; Zhao et al., 2020 ). Considering the role of responsibility and meaning in the life of adolescents, it is important to examine online game addiction, which may be affected by basic psychological needs. Therefore, a serial mediation model was determined based on the assumptions of self-determination and existential positive psychotherapy theory.

In addition to the aforementioned theoretical framework, studies have shown that unfulfilled basic psychological needs are predictors of online gaming addiction (Allen & Anderson, 2018 ; Liang et al., 2021 ; Mills & Allen, 2020 ; Yu et al., 2015 ). However, studies conducted with adolescents have found a relationship between online gaming addiction and responsibility and meaning in life (Doğan & Pamuk, 2022 ; Kaya, 2021 ). In the present study, which also considers the different dynamics in online gaming addiction, a new model is proposed to examine the relationship between basic psychological needs and online gaming addiction through responsibility and meaning in life. In this context, the present study assessed whether basic psychological needs (i.e., autonomy, relatedness, competence) affect the relationship between online gaming addiction, meaning in life, and responsibility among adolescents. Four research questions were investigated: Do basic psychological needs predict online gaming addiction? (RQ1); Does the level of responsibility have a mediating effect on the relationship between basic psychological needs and online game addiction? (RQ2); Does meaning in life have a mediating effect on the relationship between basic psychological needs and online game addiction? (RQ3); Do responsibility and meaning in life have a serial mediating effect on the relationship between basic psychological needs and online game addiction? (RQ4).

Participants

Power analysis was performed via the G* Power 3.1.9.7 program to determine the sample size required for the present study. For this purpose, at the conventional significance level of 0.05 and power at 0.80, a small effect size is determined as r = 0.20 (Cohen, 2013 ). As a result of the analysis, it was determined that the required sample size was 395. The sample in the present study comprised 546 individuals (393 females and 153 males). The participants ranged from 15 to 18 years old, with a mean age of 16.25 years (SD ± 0.82). Just below half the sample of the participants were in the 9th grade ( n =252; 46.2%), 156 were in the 10th grade (28.6%), 74 were in the 11th grade (13.6%), and 64 were in the 12th grade (11.7%). Over one-third of the sample self-reported their socioeconomic status (SES) as being low ( n =210; 38.5%), 224 reported it as being medium (41.0%), and 112 reported it as being high (20.5%). Participants stated that they played videogames 3.56 h daily on average (SD ± 3.12). The number of devices they used to play online videogames was 2.09 (SD ± 0.96).

Basic Psychological Needs Scale (BPNS)

The 21-item BPNS (Deci & Ryan, 2000 ; Turkish version: Kesici et al., 2003 ) was used to assess basic psychological needs. The scale consists of three subscales: (i) autonomy (AU), (ii) competence (CMP), and (iii) relatedness (RLT). The scale has 21 items that tap into the satisfaction of autonomy (e.g., “I feel free to decide how to live my life”), relatedness (e.g., “There aren’t many people in my life that I feel close to”), and competence (e.g., “The people I know say that I am successful in what I do”) which are rated on five-point Likert scale from 1 ( strongly disagree ) to 5 ( strongly agree ). The higher the score, the greater fulfillment of autonomy, competence, and relatedness. In the present study, the scale’s internal reliabilities for the need for autonomy were α=.76, McDonald’s ω= 76; the need for competence were α =.67, McDonald’s ω= 68; and the need for relatedness were α =.82, McDonald’s ω= 83.

Meaning in Life Questionnaire Scale (MILQS)

The 10-item MILQS (Steger et al., 2006 ; Turkish version: Demirbaş-Çelik and İşmen-Gazioğlu, 2015 ) was used to assess meaning in life. Items (e.g., “I’m always looking for my life’s purpose”) are rated on seven-point Likert scale from 1 ( definitely disagree ) to 7 ( definitely agree ). The total score ranges between 10 and 70. The higher the score, the higher the individual’s level of search for meaning in life. In the present study, the internal reliability for the existence of meaning in life was α=.85 and for seeking meaning in life was α=.82. For the overall scale, Cronbach’s α was .67, and McDonald’s ω was .72.

Sense of Responsibility and Behavior Scale (SRBS)

The 18-item SRBS (Özen, 2013 ) was used to assess responsibility. Items (e.g., “I feel responsible for being a member of charitable organizations”) are rated on four-point scale ranging from 1 ( never ) to 4 ( always ). The total score ranges between 18 and 72. The higher the score, the greater the level of responsibility. The SRBS consists of two subscales and each can be used separately. The sense of responsibility sub-dimension was used in the present study. For this sub-dimension, Cronbach’s α was .86, and McDonald’s ω was .87.

Online Game Addiction Scale (OGAS)

The 21-item OGAS (Başol & Kaya, 2018 ) was used to assess online gaming addiction. Items (e.g., “My friendships were damaged/broken due to online games”) are rated on a five-point Likert scale ranging from 1 ( absolutely disagree ) to 5 ( absolutely agree ). The total score ranges between 21 and 105 points. The higher the score, the greater the risk of online gaming addiction. In the present study, Cronbach’s α was .88, and McDonald’s ω was .89.

Procedure and Ethics

Participants were selected from three different high schools in Turkey in the cities of Ağrı, Karabük, and Siirt. The schools were informed about the purpose and duration of the study. The researchers visited the schools, and informed consent forms were distributed. Written informed consent forms were obtained from the legal guardians or parents of the adolescents who volunteered to participate in the study. The purpose of the study was explained to the participants. The eligibility criteria for participation in the study were being an adolescent and being an individual who played (or used to play) one or more online videogames. An online link to the survey was sent to the participants, and each participant was allowed to complete the survey only once. All data were collected using Google Forms in the classroom. Participants were reminded that they might stop answering at any stage of the survey process if they wanted to. Participants were asked not to provide personal information to ensure anonymity and confidentiality. Ethics committee approval of this research was obtained from Ağrı İbrahim Çeçen University (reference number: 110), and every research stage was carried out in accordance with the Declaration of Helsinki.

Data Analysis

All analyses were carried out using SPSS version 26, Hayes’ ( 2018 ) PROCESS Macro (version 3), and G* Power 3.1.9.7 programs. Before starting the analysis, the necessary assumptions to perform the analysis were tested. The kurtosis and skewness values were examined to understand whether the assumptions required for the prerequisites of parametric tests were met. The skewness and kurtosis values for a normal distribution have acceptable threshold values if they are ±2 (George, 2010 ). There were no assumption violations in the research data. In addition, it was found that the correlation between the study variables was not high. The correlations ranged between .17 and .63 ( p <.001). The research variables were also examined to ensure there were no multicollinearity issues. When the tolerance, variance inflation factor (VIF), and confidence interval (CI) values were examined, these values were all within acceptable limits. It was determined that VIF was between 1.12 and 1.48, the tolerance value was between .67 and .89, and CI was between 7.21 and 17.88. The limit values required to avoid multicollinearity problems are more than 0.20 for the tolerance value, less than 10 for the VIF value, and less than 30 for the CI value (Albayrak, 2005 ; Büyüköztürk, 2016 ; Şata, 2020 ). Consequently, no multicollinearity problems were detected. Mahalanobis distance values were examined to determine whether there were outliers in the sample. A total of 21 outliers were identified in the dataset. These outliers were excluded from the analysis, meaning the final sample size was 546. SPSS PROCESS macro was utilized to conduct mediation analyses (Hayes, 2018 ). The bootstrapping method was employed with 5000 resampling and 95% confidence intervals (CIs) to test the significance of the mediating pathways. An effect is deemed significant if the confidence interval does not contain zero (Preacher & Hayes, 2008 ).

Table 1 shows the correlations between all the main variables in the study (basic psychological needs (autonomy, competence, relatedness), online gaming addiction, responsibility, and meaning in life). Pearson correlations indicated that all variables were significantly (albeit moderately and weakly) related.

Serial Multiple Mediational Analyses—Modeling Data

Table 2 , Table 3 , and Table 4 show the results of the serial mediation analysis. First, there was a direct effect of autonomy on online gaming addiction ( β =−.67, p <.001). Moreover, the relationship between competence and online gaming addiction was examined. There was a direct effect of competence on online gaming addiction ( β =−.63, p < . 001). When the relationship between relatedness, the last of the basic psychological needs, and online gaming addiction was examined, there was a direct effect of relatedness on online gaming addiction ( β =−.48, p < . 001). There was also a significant indirect effect of autonomy on online gaming addiction via responsibility (indirect effect=−.12, SE=.02, 95% CI= [−.20, −.06]). Also, the indirect effect of competence on online gaming addiction via responsibility was significant (indirect effect=−.19, SE=.02, 95% CI= [−.31, −.10]). Lastly, the indirect effect of relatedness on online gaming addiction via responsibility was significant (indirect effect=−.17, SE=.01, 95% CI= [−.26, −.10]).

When indirect effects were examined, there was a significant indirect effect of autonomy on online gaming addiction via meaning in life (indirect effect=−.07, SE=.02, 95% CI= [−.14, −.00]). Also, the indirect effect of competence on online gaming addiction via meaning in life was significant (indirect effect=−.11, SE=.02, 95% CI= [−.22, −.00]). Lastly, the indirect effect of relatedness on online gaming addiction via meaning in life was significant (indirect effect=−.05, SE=.01, 95% CI= [−.10, −.01]).

Moreover, the indirect effects of autonomy on online gaming addiction via meaning in life and responsibility were tested. The effect was significant (testing serial multiple mediation; effect=−.04 SE=.01, 95% CI= [−.07, −.01]). Also, the indirect effects of competence on online gaming addiction via meaning in life and responsibility were tested. The effect was significant (testing serial multiple mediation; effect=−.02 SE=.01, 95% CI= [−.04, −.00]). Moreover, the indirect effects of relatedness on online gaming addiction via meaning in life and responsibility were tested. The effect was significant (testing serial multiple mediation; effect=−.02 SE=.01, 95% CI= [−.06, −.01]). In the relationship between basic psychological needs (autonomy, competence, relatedness) and online gaming addiction, meaning in life and responsibility had serial mediating effects.

The results indicated that autonomy predicted online gaming addiction. When autonomy was entered as the predictor, it significantly predicted online gaming addiction ( β = −0.67, t = −5.58, p < .001), and accounted for 5.4% of the variance in the model. Figure 1 shows the regression coefficients of the mediation model. The indirect path mediated by responsibility ( β =−.12, 95% CI= [−.20, −.06]) produced a higher change in variance than the indirect path mediated by meaning in life ( β =−.07, 95% CI= [−.14, −.00]) in the relationship between relatedness and online gaming addiction (see Table 2 ). Therefore, responsibility appeared to have a higher effect than meaning in life. Autonomy predicted a higher level of meaning in life. It also predicted a higher level of responsibility. Higher meaning in life was associated with a higher level of responsibility. Higher level of responsibility was associated with lower online gaming addiction. Consequently, the results indicated that the relationship between autonomy and online gaming addiction was partially mediated by meaning in life and responsibility (see Fig. 1 ).

The results of the serial multiple mediational models

It was also found that competence predicted online gaming addiction. There was also an indirect relationship between competence and online gaming addiction ( β = −0.64, t = −4.13, p < .001), accounting for 4.7% of the variance in the model. Competence predicted meaning and responsibility in life. The indirect path mediated by responsibility ( β =−.19, 95% CI= [−.31, −.10]) produced a higher change in variance than the indirect path mediated by meaning in life ( β =−.11, 95% CI= [−.22, −.00]) in the relationship between competence and online gaming addiction Furthermore, the relationship between competence and online gaming addiction was mediated by meaning in life and responsibility separately (see Table 3 ). The results also showed that meaning in life and responsibility had serial mediation effects in the relationship between competence and online gaming addiction (see Fig. 2 ).

Lastly, the results indicated that relatedness predicted online gaming addiction ( β = −0.48, t = −4.63, p < .001). When relatedness was included in the model, it was found that it accounted for 3.8% of the variance. Moreover, there was also an indirect relationship between relatedness and online gaming addiction. When the indirect effects are examined, the indirect path mediated by responsibility ( β =−.17, 95% CI= [−.26, −.10]) produced a higher change in variance than the indirect path mediated by meaning in life ( β =−.05, 95% CI= [−.10, −.01]) in the relationship between relatedness and online gaming addiction (see Table 4 ). The results suggested that the relationship between relatedness and online gaming addiction was partially mediated by meaning in life and responsibility (see Fig. 3 ).

In self-determination theory (SDT), basic psychological needs comprise autonomy, competence, and relatedness. In SDT (Deci & Ryan, 2000 ), basic psychological needs are expressed as essential psychological nutrients for psychological development, integrity, and well-being. Negative psychological consequences occur when requirements are not met, neglected, or prevented (Deci & Ryan, 2000 ). If individuals cannot satisfy a basic need, they engage in activities that give pleasure to individuals momentarily, even if they do not satisfy them (Antunes et al., 2020 ; Deci & Ryan, 2011 ). One of these activities is online gaming, which has an incredibly interactive structure. At the same time, online videogames are appreciated because they create an environment where both the need for relatedness and autonomy are met in the virtual world. Individuals naturally seek new challenges to experience a sense of efficacy even when no external rewards (e.g., money) are earned (Dindar, 2018 ; Matsumoto, 2009 ). The fact that online games have a reward mechanism is suitable for activating feelings of competence among individuals. It is thought that adolescents tend to meet their basic psychological needs (need for autonomy, competence, and relatedness) that they cannot fully meet from their parents or close friends through online gaming.

The present study examined the mediating role of meaning in life and the level of responsibility in the relationship between online gaming addiction and basic psychological needs (i.e., autonomy, competence, and relatedness) among adolescents. Findings showed that autonomy predicted online game addiction. In other words, autonomy had significant negative effect on online game addiction. Considering that addiction is related to reduced autonomy (Amatem, 2008 ), it can be said that the finding is compatible with the literature. However, there is a study in which there was a negative relationship between the need for autonomy and digital game addiction among adolescents (Dursun and Çapan, 2018 ), which supports the research finding. On the contrary, there is a study in which autonomy and online game addiction had significant positive relationships (Bekir and Çelik, 2019 ). Similarly, it is known that the need for autonomy has a positive relationship with social media addiction (Young-Ju et al., 2018 ) and a negative relationship with Internet addiction (Piri et al., 2018 ; Zeren & Can, 2019 ). These studies, which have obtained different results, make the relationship between the need for autonomy and digital addictions open to discussion but also show that further research is needed.

According to the present study’s findings, it was found that relatedness and competence, as well as autonomy, predicted online gaming addiction. Studies have shown that competence and relatedness have significant relationships with online gaming addiction (Bekir and Çelik, 2019 ; Dursun and Çapan, 2018 ). In addition, research has shown that relatedness has a negative relationship with short-form video addiction (Yang et al., 2022 ), and relatedness dissatisfaction positively correlates with Internet gaming disorder (Hui et al., 2019 ). Moreover, significant negative relationships have been found between competence and smartphone addiction (Gao et al., 2022 ; Sun et al., 2020 ) and Internet addiction (Zeren & Can, 2019 ; Canoğulları, 2014 ). Based on these results concerning technological addictions, it can be said that the literature findings and the results of the present study are compatible.

The tendency of individuals to play online videogames may be to meet their autonomy, competence, and relatedness needs (Ryan et al., 2006 ). In addition, when basic psychological needs are prevented, technological addictions (gaming addiction, smartphone addiction, social network addiction, and Internet addiction) increase (Gugliandolo et al., 2020 ). This may be the compensation for unmet basic psychological needs through addiction (Kuss et al., 2017 ; Mills et al., 2018 ). Therefore, fulfilling basic psychological needs in real life and eliminating the problems that prevent this satisfaction can be a protective factor against online gaming addiction.

Another finding of the present study was that the level of responsibility hads a mediating effect on the relationship between basic psychological needs and online gaming addiction. However, there was a positive and significant relationship between basic psychological needs and responsibility. In contrast, a significant negative relationship was found between responsibility and online gaming addiction. Considering that the components of responsibility (accountability, liability, and imputability) in Robinson’s ( 2009 ) definition appear less important in online environments, it is assumed that adolescents who are addicted to online gaming experience less sense of responsibility. A recent study found that a higher level of responsibility significantly predicted online gaming addiction, whereas a lower level of responsibility negatively affected online gaming addiction (Kesici, 2020 ).

Research conducted by Arslan ( 2021 ) found that secondary school students’ sense of responsibility and behavior had a crucial predictive role in online gaming addiction. Another study reported a significant negative relationship between the students’ videogame addiction and their personal and social responsibility behavior (Dinçer & Kolan, 2020 ). Based on previous studies and the results of the present study, it is thought that increasing the level of responsibility of secondary and high school students would reduce gaming addiction. Adolescents whose level of responsibility increases are also more likely to engage in responsible behavior. This is supported by studies in the literature that physical education and sports play an essential role in helping adolescents acquire responsible behavior (Bayraktar et al., 2016 ; Bugdayci, 2019 ; Tazegül, 2014 ). These studies’ results are considered necessary regarding online gaming addiction because such behavior leads to a sedentary lifestyle (Cómez-Mármol et al., 2017 ).

Findings indicated that meaning in life had a mediating effect on the relationship between basic psychological needs and online gaming addiction. However, there was a positive and significant relationship between basic psychological needs and meaning in life. In contrast, a significant negative relationship between meaning in life and online gaming addiction was found. These findings demonstrate the importance of meaning in life in preventing online gaming addiction among adolescents. A study by Kaya ( 2021 ) on adolescent online gaming addiction found that as the level of online gaming addiction decreased, the level of meaning in life increased. These results suggest that meaning in life affects online gaming addiction as a cause and consequence. Considering that having a meaningful life increases resilience (Batmaz et al., 2021 ; Doğrusever et al., 2022 ), low resilience increases gaming addiction (Canale et al., 2019 ), and gaming addiction reduces happiness (Kaya, 2021 ; Turan, 2021 ), meaning in life seems to be an essential variable that can affect gaming addiction.

What makes the present study unique to the online gaming addiction literature is that responsibility and meaning in life had a serial mediating effect on the relationship between basic psychological needs and online gaming addiction. In other words, the results indicated that the relationship between relatedness, competence, and autonomy with online gaming addiction was partially mediated by meaning in life and responsibility. This finding suggests that the need for autonomy, competence, and relatedness increases the level of meaning in life, which in turn reduces online game addiction. Similarly, online game addiction can decrease as the need for autonomy, competence, and relatedness increases the level of responsibility. In addition, based on the serial mediation effect, it suggests that meeting the need for autonomy, competence, and relatedness can reduce adolescents’ online game addiction by increasing their meaning in life and their level of responsibility.

To the best of the authors’ knowledge, the present study is the first to examine the mediating role of responsibility and meaning in life between basic psychological needs and online gaming addiction. The associations between these variables provide greater understanding and knowledge concerning online gaming addiction and provide additional insight into the significant causes that underlie playing games online (which may be potential factors in the acquisition, development, and maintenance of online gaming addiction among adolescents). Moreover, fulfilling basic psychological needs appears to increase responsibility and meaning in life and reduce susceptibility to online gaming addiction. The findings enrich the literature because it suggests new protective factors that might prevent adolescents from developing online gaming addiction.

The findings offer relevant practical implications for adolescents, educators, families, private and public health institutions, and mental health professionals to assist them in designing addiction prevention strategies and policies. Results also suggest that basic psychological need satisfaction fulfilment in real life plays an important role in the development and maintenance of online gaming addiction among adolescents. Educators, parents, and adolescents could utilize awareness of the factors contributing to online gaming addiction to help them take preventive measures against it. In addition, if adolescents have high levels of responsibility and meaning in life, it may help reduce online game addiction. Considering the findings, it is recommended that mental health professionals provide training and services that increase the level of responsibility among adolescents and enable them to have meaning in their lives to prevent the onset of online gaming addiction. In addition, private and public health institutions should implement training programs to improve the skills of parents, such as digital parenting, to cope with online gaming addiction. This training should also ensure that parents behave with awareness of the basic psychological needs of adolescents in the family and that they gain thoughts and approaches that can add responsibility and meaning in life.

Limitations

As in all studies, the present study also has some limitations. The first is that the study was cross-sectional. Conducting a cross-sectional study means that causality between the study variables cannot be determined. Second, completing the survey online may have influenced respondents’ responses (with those without home Internet access unable to participate). The online data were also collected during the COVID-19 pandemic. Therefore, adolescents living in isolated environments may have increased their gaming during this period. This unusual situation may have resulted in a lower sense of responsibility and a less meaningful life. This is consistent with the present study’s findings. Another limitation is that the participants were high school students studying in different schools in Turkish provinces, so the findings are not necessarily generalizable to all Turkish schoolchildren. The sample was also limited because it did not include other education levels, such as primary and secondary schools and children from different geographical and cultural regions in Turkey and/or other countries. Future studies are needed with different age groups, such as primary school, secondary school, university students, adults, and various geographical regions in the sample groups (both in and outside Turkey). Such studies are needed to confirm the findings reported here and should include other research designs (e.g., longitudinal studies to determine causality between variables) and other types of data (e.g., qualitative interview data to attain richer data). Another limitation of the present study was that the participant’s responses were self-report and therefore subject to well-established method biases (e.g., social desirability, memory recall).

The study’s findings indicated that adolescents whose basic psychological needs were met exhibited lower levels of online gaming addiction than adolescents whose basic psychological needs were not met. Consequently, the adverse effects of online gaming addiction may be reduced by interventions that meet adolescents’ basic psychological needs. Similarly, a significant negative relationship was found between responsibility and online gaming addiction. Consequently, it appears that adolescents who fulfill the requirements of individual and social responsibilities (studying, spending time with family, going out with friends, etc.) have greater protection from the more negative effects of online gaming. However, when meaning in life and responsibility are included in the relationship between basic psychological needs and online gaming addiction, the effect of basic psychological needs on online game addiction decreases. This suggests that meaning in life and responsibility have a serial mediating role between basic psychological needs and online gaming addiction.

Data Availability

The data that support the findings of this study are available from the first author upon reasonable request.

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Alican Kaya

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Hasan Batmaz

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Study conception/design: AK, HB, NT, and MDG. Data collection: AK, HB, and NT. analysis: AK and HB. Drafting of manuscript: AK, HB, NT, and MDG. Editing: MDG. Statistical expertise: AK and HB. Administrative/technical/material support: HB and HYK.

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Kaya, A., Türk, N., Batmaz, H. et al. Online Gaming Addiction and Basic Psychological Needs Among Adolescents: The Mediating Roles of Meaning in Life and Responsibility. Int J Ment Health Addiction 22 , 2413–2437 (2024). https://doi.org/10.1007/s11469-022-00994-9

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ORIGINAL RESEARCH article

The effects of online game addiction on reduced academic achievement motivation among chinese college students: the mediating role of learning engagement.

1 BinZhou College of Science and Technology, Binzhou, China
2 Binzhou Polytechnic, Binzhou, China
3 Faculty of Education, Beijing Normal University, Beijing, China
4 National Institute of Vocational Education, Beijing Normal University, Beijing, China

Introduction: The present study aimed to examine the effects of online game addiction on reduced academic achievement motivation, and the mediating role of learning engagement among Chinese college students to investigate the relationships between the three variables.

Methods: The study used convenience sampling to recruit Chinese university students to participate voluntarily. A total of 443 valid questionnaires were collected through the Questionnaire Star application. The average age of the participants was 18.77 years old, with 157 males and 286 females. Statistical analysis was conducted using SPSS and AMOS.

Results: (1) Chinese college students’ online game addiction negatively affected their behavioral, emotional, and cognitive engagement (the three dimensions of learning engagement); (2) behavioral, emotional, and cognitive engagement negatively affected their reduced academic achievement motivation; (3) learning engagement mediated the relationship between online game addiction and reduced academic achievement motivation.

1. Introduction

Online games, along with improvements in technology, have entered the daily life of college students through the popularity of computers, smartphones, PSPs (PlayStation Portable), and other gaming devices. Online game addiction has recently become a critical problem affecting college students’ studies and lives. As early as 2018, online game addiction was officially included in the category of “addictive mental disorders” by the World Health Organization (WHO), and the International Classification of Diseases (ICD) was updated specifically to include the category of “Internet Gaming Disorder” (IGD). Prior research investigating Chinese college students’ online game addiction status mostly comprised regional small-scale studies. For example, a study on 394 college students in Chengde City, Hebei province, China showed that the rate of online game addiction was about 9% ( Cui et al., 2021 ). According to the results of an online game survey conducted by China Youth Network (2019) on 682 Chinese college students who played online games, nearly 60% of participants played games for more than 1 h a day, over 30% stayed up late because of playing games, over 40% thought that playing games had affected their physical health, over 70% claimed that games did not affect their studies, and over 60% had spent money on online games. This phenomenon has been exacerbated by the fact that smartphones and various portable gaming devices have become new vehicles for gaming with the development of technology. The increase in the frequency or time spent on daily gaming among adolescents implies a growth in the probability of gaming addiction, while an increase in the level of education decreases the probability of gaming addiction ( Esposito et al., 2020 ; Kesici, 2020 ). Moreover, during the COVID-19 pandemic, adolescents’ video game use and the severity of online gaming disorders increased significantly ( Teng et al., 2021 ).

A large body of literature on the relationship between problematic smartphone use and academic performance has illustrated the varying adverse effects of excessive smartphone obsession ( Durak, 2018 ; Mendoza et al., 2018 ; Rozgonjuk et al., 2018 ). These effects are manifested in three critical ways: first, the more frequently cell phones are used during study, the greater the negative impact on academic performance and achievement; second, students are required to master the basic skills and cognitive abilities to succeed academically, which are negatively affected by excessive cell phone use and addiction ( Sunday et al., 2021 ); third, online game addiction negatively affects students’ learning motivation ( Demir and Kutlu, 2018 ; Eliyani and Sari, 2021 ). However, there is currently a lack of scientifically objective means of effective data collection regarding online game addiction among college students in China, such as big data. Hong R. Z. et al. (2021) and Nong et al. (2023) suggested that the impact of addiction on students’ learning should be explored more deeply.

Since the 1990s, learning engagement has been regarded as a positive behavioral practice in learning in Europe and the United States, and plays an important role in the field of higher education research ( Axelson and Flick, 2010 ). Recently, studies on learning engagement among college students have also been a hot topic in various countries ( Guo et al., 2021 ). According to Fredricks et al. (2004) , learning engagement includes three dimensions: behavioral, emotional, and cognitive.

The concept of behavioral engagement encompasses three aspects: first, positive behavior in the classroom, such as following school rules and regulations and classroom norms; second, engagement in learning; and third, active participation in school activities ( Finn et al., 1995 ). Emotional engagement refers to students’ responses to their academic content and learning environment. The emotional responses to academic content include students’ emotional responses such as interest or disinterest in learning during academic activities ( Kahu and Nelson, 2018 ), while the emotional responses to the learning environment refer to students’ identification with their peers, teachers, and the school environment ( Stipek, 2002 ). Cognitive engagement is often associated with internal processes such as deep processing, using cognitive strategies, self-regulation, investment in learning, the ability to think reflectively, and making connections in daily life ( Khan et al., 2017 ). Cognitive engagement emphasizes the student’s investment in learning and self-regulation or strategies.

According to Yang X. et al. (2021) , learning engagement refers to students’ socialization, behavioral intensity, affective qualities, and use of cognitive strategies in performing learning activities. Besides, Kuh et al. (2007) argued that learning engagement was “the amount of time and effort students devote to instructional goals and meaningful educational practices.” Learning engagement is not only an important indicator of students’ learning process, but also a significant predictor of students’ academic achievement ( Zhang, 2012 ). It is also an essential factor in promoting college students’ academic success and improving education quality.

As one of the crucial components of students’ learning motivation ( Han and Lu, 2018 ), achievement motivation is the driving force behind an individual’s efforts to put energy into what he or she perceives to be valuable and meaningful to achieve a desired outcome ( Story et al., 2009 ). It can be considered as achievement motivation when an individual’s behavior involves “competing at a standard of excellence” ( Brunstein and Heckhausen, 2018 ). Students’ achievement motivation ensures the continuity of learning activities, achieving academic excellence and desired goals ( Sopiah, 2021 ). Based on the concept of achievement motivation, academic achievement motivation refers to the mental perceptions or intentions that students carry out regarding their academic achievement, a cognitive structure by which students perceive success or failure and determine their behavior ( Elliot and Church, 1997 ). Related research also suggests that motivation is one variable that significantly predicts learning engagement ( Xiong et al., 2015 ).

Therefore, it is worthwhile to investigate the internal influence mechanism of college students’ online game addiction on their reduced academic achievement motivation and the role of learning engagement, which is also an issue that cannot be ignored in higher education research. The present study explored the relationship between online game addiction, learning engagement, and reduced academic achievement motivation among college students by establishing a structural equation model (SEM) to shed light on the problem of online game addiction among college students.

2. Research model and hypotheses

2.1. research model.

Previous research usually regarded learning engagement as a variable of one or two dimensions, and scholars tend to favor the dimension of behavioral engagement. However, other ignored dimensions are inseparable parts of learning engagement ( Dincer et al., 2019 ). In a multi-dimensional model, the mutual terms of each dimension form a single composite structure. Therefore, the present study took the structure proposed by Fredricks et al. (2004) as a reference, divided learning engagement into behavioral, emotional, and cognitive dimensions as mediating variables, and explored the relationship between online game addiction, learning engagement, and reduced academic achievement motivation. The research frame diagram is shown in Figure 1 .

Figure 1 . The research model.

2.2. Research questions

2.2.1. the relationship between online game addiction and learning engagement.

Learning engagement has been viewed as a multidimensional concept in previous studies. Finn (1989) proposed the participation-identification model to make pioneering progress in learning engagement study. Schaufeli et al. (2002) suggested that learning engagement was an active, fulfilling mental state associated with learning. Chapman (2002) pointed out affective, behavioral, and cognitive criteria for assessing students’ learning engagement based on previous research. Fredricks et al. (2004) systematically outlined learning engagement as an integration of behavioral, emotional, and cognitive engagement. The updated International Classification of Diseases [ World Health Organization (WHO), 2018a , b ] specifies several diagnostic criteria for gaming addiction, including the abandonment of other activities, the loss of interest in other previous hobbies, and the loss or potential loss of work and social interaction because of gaming. Past studies have shown the adverse effects of excessive Internet usage on students’ learning. Short video addiction negatively affects intrinsic and extrinsic learning motivation ( Ye et al., 2022 ). Students’ cell phone addiction negatively affects academic commitment, academic performance, and relationship facilitation, all of which negatively affect their academic achievement ( Tian et al., 2021 ). The amount of time spent surfing the Internet and playing games has been identified to negatively affect students’ cognitive ability ( Pan et al., 2022 ). College students’ cell phone addiction, mainly reflected in cell phone social addiction and game entertainment addiction, has also been noted to impact learning engagement; specifically, the higher the level of addiction, the lower the learning engagement ( Qi et al., 2020 ). Gao et al. (2021) also showed that cell phone addiction among college students could negatively affect their learning engagement. Choi (2019) showed that excessive use of cell phones might contribute to smartphone addiction, which also affects students’ learning engagement. Accordingly, the following three research hypotheses were proposed.

H1 : Online game addiction negatively affects behavioral engagement.

H2 : Online game addiction negatively affects emotional engagement.

H3 : Online game addiction negatively affects cognitive engagement.

2.2.2. The relationship between learning engagement and reduced academic achievement motivation

Achievement motivation is people’s pursuit of maximizing individual value, which embodies an innate drive, including the need for achievement, and can be divided into two parts: the intention to succeed and the intention to avoid failure ( McClelland et al., 1976 ). On this basis, Weiner (1985) proposed the attributional theory of achievement motivation, suggesting that individuals’ personality differences, as well as the experience of success and failure, could influence their achievement attributions and that an individual’s previous achievement attributions would affect his or her expectations and emotions for the subsequent achievement behavior while expectations and emotions could guide motivated behavior. Birch and Ladd (1997) indicated that behavioral engagement involved positive behavioral attitudes such as hard work, persistence, concentration, willingness to ask questions, and active participation in class discussions to complete class assignments. Students’ attitudes toward learning are positively related to achievement motivation ( Bakar et al., 2010 ). Emotional engagement involves students’ sense of identity with their peers, teachers, and the school environment ( Stipek, 2002 ). Students’ perceptions of the school environment influence their achievement motivation ( Wang and Eccles, 2013 ). Cognitive engagement encompasses the ability to use cognitive strategies, self-regulation, investment in learning, and reflective thinking ( Khan et al., 2017 ). Learning independence and problem-solving abilities predict student motivation ( Saeid and Eslaminejad, 2017 ). Hu et al. (2021) indicated that cognitive engagement had the most significant effect on students’ academic achievement among the learning engagement dimensions, and that emotional engagement was also an important factor influencing students’ academic achievement. Therefore, the following three research hypotheses were proposed:

H4 : Behavioral engagement significantly and negatively affects the reduced academic achievement motivation.

H5 : Emotional engagement significantly and negatively affects the reduced academic achievement motivation.

H6 : Cognitive engagement significantly and negatively affects the reduced academic achievement motivation.

2.2.3. The relationship between online game addiction, learning engagement, and reduced academic achievement motivation

Past studies have demonstrated the relationship between online game addiction and students’ achievement motivation. For example, a significant negative correlation between social network addiction and students’ motivation to progress has been reported ( Haji Anzehai, 2020 ), and a significant negative correlation between Internet addiction and students’ achievement motivation has been reported ( Cao et al., 2008 ). Students addicted to online games generally have lower academic achievement motivation because they lack precise academic planning and motivation ( Chen and Gu, 2019 ). Yayman and Bilgin (2020) pointed out a correlation between social media addiction and online game addiction. Accordingly, there might be a negative correlation between online game addiction and academic achievement motivation among college students.

Students addicted to online games generally have lower motivation for academic achievement because they lack precise academic planning and learning motivation ( Chen and Gu, 2019 ). Similarly, Haji Anzehai (2020) reported a significant negative correlation between social network addiction and students’ motivation to progress.

Learning engagement is often explored as a mediating variable in education research. Zhang et al. (2018) found that learning engagement was an essential mediator of the negative effect of internet addiction on academic achievement in late adolescence and is a key factor in the decline in academic achievement due to students’ internet addiction. Li et al. (2019) noted that college students’ social networking site addiction significantly negatively affected their learning engagement, and learning engagement mediated the relationship between social networking addiction and academic achievement. Accordingly, the following research hypothesis was proposed.

H7 : Learning engagement mediates the relationship between online game addiction and reduced academic achievement motivation.

3. Research methodology and design

3.1. survey implementation.

The present study employed the Questionnaire Star application for online questionnaire distribution. Convenience sampling was adopted to recruit Chinese college students to participate voluntarily. The data were collected from October 2021 to January 2022 from a higher vocational college in Shandong province, China. Participants were first-and second-year students. According to Shumacker and Lomax (2016) , the number of participants in SEM studies should be approximately between 100 and 500 or more. In the present study, 500 questionnaires were returned, and 443 were valid after excluding invalid responses. The mean age of the participants was 18.77 years. There were 157 male students, accounting for 35.4% of the total sample, and 286 female students, accounting for 64.6%.

3.2. Measurement instruments

The present empirical study employed quantitative research methods by collecting questionnaires for data analysis. The items of questionnaires were adapted from research findings based on corresponding theories and were reviewed by experts to confirm the content validity of the instruments. The distributed questionnaire was a Likert 5-point scale (1 for strongly disagree , 2 for disagree , 3 for average , 4 for agree , and 5 for strongly agree ). After the questionnaire was collected, item analysis was conducted first, followed by reliability and validity analysis of the questionnaire constructs using SPSS23 to test whether the scale met the criteria. Finally, research model validation was conducted.

3.2.1. Online game addiction

In the present study, online game addiction referred to the addictive behavior of college students in online games, including mobile games and online games. The present study adopted a game addiction scale compiled by Wu et al. (2021) and adapted the items based on the definition of online game addiction. The adapted scale had 10 items. Two examples of the adapted items in the scale were: “I will put down what should be done and spend my time playing online games” and “My excitement or expectation of playing an online game is far better than other interpersonal interactions.”

3.2.2. Learning engagement

In the present study, learning engagement included students’ academic engagement in three dimensions: behavioral, emotional, and cognitive. The learning engagement scale compiled by Luan et al. (2020) was adapted based on its definition. The adapted scale had 26 questions in three dimensions: behavioral, emotional, and cognitive engagement. Two examples of the adapted items in the scale are: “I like to actively explore unfamiliar things when I am doing my homework” and “I will remind myself to double-check the places where I tend to make mistakes in my homework.”

3.2.3. Reduced academic achievement motivation

Reduced academic achievement motivation in the present study refers to the reduction in college students’ intrinsic tendency to enjoy challenges and achieve academic goals and academic success. The achievement motivation scale developed by Ye et al. (2020) was adapted to measure reduced academic achievement motivation. The adapted scale had 10 items. Two examples of the adapted items in the scale are: “Since playing online games, I do not believe that the effectiveness of learning is up to me, but that it depends on other people or the environment” and “Since I often play online games, I am satisfied with my current academic performance or achievement and do not seek higher academic challenges.”

4. Results and discussion

4.1. internal validity analysis of the measurement instruments.

In the present study, item analysis was conducted using first-order confirmatory factor analysis (CFA), which can reflect the degree of measured variables’ performance within a smaller construct ( Hafiz and Shaari, 2013 ). The first-order CFA is based on the streamlined model and the principle of independence of residuals. According to Hair et al. (2010) and Kenny et al. (2015) , it is recommended that the value of χ 2 / df in the model fitness indices should be less than 5; the root mean square error of approximation (RMSEA) value should be greater than 0.100; the values of the goodness of fit index (GFI) and adjusted goodness of fit index (AGFI) should not be lower than 0.800; the factor loading (FL) values of the constructs should also be greater than 0.500. Based on the criteria above, the items measuring the online game addiction construct were reduced from 10 to seven; the items measuring the behavioral engagement construct were reduced from nine to six; the items measuring the emotional engagement construct were reduced from nine to six; the items measuring the cognitive engagement construct were reduced from eight to six; and the items measuring the reduced academic achievement motivation construct was reduced from 10 to six, as shown in Table 1 .

Table 1 . First-order confirmatory factor analysis.

4.2. Construct reliability and validity analysis

In order to determine the internal consistency of the constructs, the reliability of the questionnaire was tested using Cronbach’ s α value. According to Hair et al. (2010) , a Cronbach’ s α value greater than 0.700 indicates an excellent internal consistency among the items, and the constructs’ composite reliability (CR) values should exceed 0.700 to meet the criteria. In the present study, the Cronbach’ s α values for the constructs ranged from 0.911 to 0.960, and the CR values ranged from 0.913 to 0.916, which met the criteria, as shown in Table 2 .

Table 2 . Construct reliability and validity of constructs.

In the present study, convergent validity was confirmed by two types of indicators, FL and average variance extracted (AVE). According to Hair et al. (2011) , an FL value should be greater than 0.500, and items with an FL value less than 0.500 should be removed; and AVE values should be greater than 0.500. In the present study, the FL values of the constructs ranged from 0.526 to 0.932, and the AVE values ranged from 0.600 to 0.805; all dimensions met the recommended criteria, as shown in Table 2 .

According to Awang (2015) and Hair et al. (2011) , the square root of the AVE of each construct (latent variable) should be greater than its correlation coefficient values with other constructs to indicate the ideal discriminant validity. The results of the present study showed that the three constructs of online game addiction, learning engagement, and reduced academic achievement motivation had good discriminant validity in the present study, as shown in Table 3 .

Table 3 . Discriminant validity analysis.

4.3. Correlation analysis

Pearson’s correlation coefficient is usually used to determine the closeness of the relationship between variables. A correlation coefficient greater than 0.8 indicates a high correlation between variables; a correlation coefficient between 0.3 and 0.8 indicates a moderate correlation between variables; while a correlation of less than 0.3 indicates a low correlation. Table 4 shows the Correlation Analysis results. Online game addiction was moderately negatively correlated with behavioral engagement ( r = −0.402, p < 0.001), moderately negatively correlated with emotional engagement ( r = −0.352, p < 0.001), slightly negatively correlated with cognitive engagement ( r = −0.288, p < 0.001), and slightly positively correlated with reduced academic achievement motivation ( r = 0.295, p < 0.001). Behavioral engagement was moderately positively correlated with emotional engagement ( r = 0.696, p < 0.001), moderately positively correlated with cognitive engagement ( r = 0.601, p < 0.001), and moderately negatively correlated with reduced academic achievement motivation ( r = −0.497, p < 0.001). Emotional engagement was moderately positively correlated with cognitive engagement ( r = 0.787, p < 0.001) and moderately negatively correlated with reduced academic achievement motivation ( r = −0.528, p < 0.001). Cognitive engagement was moderately negatively correlated with reduced motivation for academic achievement ( r = −0.528, p < 0.001).

Table 4 . Correlation analysis.

4.4. Analysis of fitness of the measurement model

According to Hair et al. (2010) and Abedi et al. (2015) , the following criteria should be met in the analysis for measurement model fitness: the ratio of chi-squared and degree of freedom ( χ 2 / df ) should be less than 5; the root mean square error of approximation (RMSEA) should not exceed 0.100; the goodness of fit index (GFI), adjusted goodness of fit index (AGFI), normed fit index (NFI), non-normed fit index (NNFI), comparative fit index (CFI), incremental fit index (IFI) and relative fit index (RFI) should be higher than 0.800; and the parsimonious normed fit index (PNFI) and the parsimonious fitness of fit index (PGFI) should be higher than 0.500. The model fitness indices in the present study were χ 2 = 1434.8, df = 428, χ 2 / df = 3.352, RMSEA = 0.073, GFI = 0.837, AGFI = 0.811, NFI = 0.899, NNFI = 0.920, CFI = 0.927, IFI = 0.927, RFI = 0.890, PNFI = 0.827, and PGFI = 0.722. The results were in accordance with the criteria, indicating a good fitness of the model in the present study ( Table 5 ).

Table 5 . Direct effects analysis.

4.5. Validation of the research model

Online game addiction had a negative effect on behavioral engagement ( β = −0.486; t = −9.143; p < 0.001). Online game addiction had a negative effect on emotional engagement ( β = −0.430; t = −8.054; p < 0.001). Online game addiction had a negative effect on cognitive engagement ( β = −0.370; t = −7.180; p < 0.001). Online game addiction had a positive effect on reduced academic achievement motivation ( β = 0.19; t = −2.776; p < 0.01). Behavioral engagement had a negative effect on reduced academic achievement motivation ( β = −0.238; t = −3.759; p < 0.001). Emotional engagement had a negative effect on reduced academic achievement motivation ( β = −0.221; t = −2.687; p < 0.01), and cognitive engagement had a negative effect on reduced academic achievement motivation ( β = −0.265; t = −3.581; p < 0.01), as shown in Figure 2 Table 6 .

Figure 2 . Validation of the research model. *** p < 0.001.

Table 6 . Indirect effects analysis.

Cohen’ s f 2 is an uncommon but valuable standardized effect size measure that can be used to assess the size of local effects ( Selya et al., 2012 ). When f 2 reaches 0.02 it represents a small effect size, 0.150 represents a medium effect size, and 0.350 represents a high effect size ( Hair et al., 2014 ). The explanatory power of online game addiction on behavioral engagement was 23.6%, and f 2 was 0.309. The explanatory power of online game addiction on emotional engagement was 18.5%, and f 2 was 0.227. The explanatory power of online game addiction on cognitive engagement was 13.7%, and f 2 was 0.159. The explanatory power of behavioral, emotional, and cognitive engagement on reduced academic achievement motivation was 23.9%, and f 2 was 0.314. Figure 2 illustrates the above findings.

4.6. Indirect effects analysis

Scholars are often interested in whether variables mediate the association between predicting and outcome variables. Therefore, mediating variables can partially or entirely explain the association ( Hwang et al., 2019 ). In research fields such as psychology and behavior, where the research situation is often more complex, multiple mediating variables are often required to clearly explain the effects of the independent variables on the dependent variables ( MacKinnon, 2012 ). Scientific quantitative research requires tests of confidence interval (CI; Thompson, 2002 ), and the standard value of the test numbers is often determined by 95% CI ( Altman and Bland, 2011 ). CI value not containing 0 indicates the statistical significance of the analysis results ( Nakagawa and Cuthill, 2007 ). According to the statistical results shown in Table 4 , behavioral engagement significantly positively mediated the relationship between online game addiction and reduced academic achievement motivation with a path coefficient of 0.230 and 95% CI ranging from 0.150 to 0.300 (excluding 0), p < 0.01; emotional engagement positively mediated the relationship between online game addiction and reduced academic achievement motivation with a path coefficient of 0.209, 95% CI ranging from 0.130 to 0.292 (excluding 0), p < 0.01; cognitive engagement positively mediated the relationship between online game addiction and reduced academic achievement motivation with a path coefficient of 0.170, 95% CI ranging from 0.100 to 0.250 (excluding 0), p < 0.01, as shown in Table 6 .

4.7. Discussion

4.7.1. analysis of the relationship between online game addiction and learning engagement.

Online game addiction is often negatively associated with students’ learning. For example, the problematic use of short videos was reported as negatively affecting students’ behavioral engagement, while behavioral engagement positively affected students’ emotional and cognitive engagement ( Ye et al., 2023 ). Meral (2019) highlighted that students’ learning attitudes and academic performance had a negative relationship with students’ addiction to online games. Demir and Kutlu (2018) found that online game addiction negatively affects students’ learning motivation. As the level of students’ game addiction increased, the level of their communication skills decreased ( Kanat, 2019 ). Furthermore, Tsai et al. (2020) pointed out a negative correlation between online game addiction and peer relationships as well as students’ learning attitudes. According to the results of the research model validation, it can be observed that: online game addiction negatively affected behavioral engagement, emotional engagement, and cognitive engagement. Therefore, it can be stated that online game addiction had significant and negative effects on all dimensions of learning engagement.

Online game addiction in the present study included aspects of computer game addiction and mobile phone game addiction. The results of the present study are consistent with the findings of Gao et al. (2021) , Choi (2019) , and Qi et al. (2020) , who pointed out that college students’ addiction to cell phones negatively affected their learning engagement.

4.7.2. Analysis of the relationship between learning engagement and reduced academic achievement motivation

For technology education in higher education, students’ intrinsic motivation for academic study predicts their learning engagement ( Dunn and Kennedy, 2019 ). In addition, learning engagement is positively correlated with academic achievement ( Fredricks and McColskey, 2012 ). Based on the research model validation results, behavioral, emotional, and cognitive engagement all negatively affected reduced academic achievement motivation. The findings are consistent with Hu et al.’s (2021) study which pointed out that cognitive engagement in the learning engagement dimension had the most significant effect on students’ academic achievement, and that emotional engagement was also an essential factor influencing students’ academic achievement. Lau et al. (2008) showed that achievement motivation positively predicted cognitive engagement in the learning engagement dimension. Mih et al. (2015) noted that achievement motivation positively predicted behavioral and emotional engagement in the learning engagement dimension. The present study supported the above discussion by confirming the association between learning engagement and reduced academic achievement motivation.

4.7.3. Analysis of the mediating role of learning engagement

According to the indirect effects analysis results of the present study, learning engagement negatively mediated the relationship between online game addiction and reduced academic achievement motivation. The findings support Haji Anzehai’s (2020) conclusion that social network addiction negatively correlated with students’ motivation to progress ( Haji Anzehai, 2020 ). It is also consistent with the findings of Chen and Gu (2019) that students addicted to online games generally had lower academic achievement motivation due to a lack of precise academic planning and motivation. Cao et al. (2008) found a significant negative correlation between Internet addiction and students’ achievement motivation. Similarly, Zhang et al. (2018) explored the intrinsic influencing mechanism of students’ Internet addiction on academic achievement decline in their late adolescence by identifying learning engagement as the important mediating variable. Li et al. (2019) proposed that social networking site addiction among college students significantly negatively affected learning engagement and that learning engagement mediated the relationship between social network addiction and students’ academic achievement. The present study findings also support the discussion above.

5. Conclusion and suggestions

5.1. conclusion.

Currently, the problem of online game addiction among college students is increasing. The relationship between online game addiction, learning engagement, and reduced academic achievement motivation still needs to be explored. The present study explored the relationships between the three aforementioned variables by performing SEM. The results of the study indicated that: (1) online game addiction negatively affected behavioral engagement; (2) online game addiction negatively affected emotional engagement; (3) online game addiction negatively affected cognitive engagement; (4) behavioral engagement negatively affected reduced academic achievement motivation; (5) emotional engagement negatively affected reduced academic achievement motivation; (6) cognitive behavioral engagement negatively affected reduced academic achievement motivation; (7) learning engagement mediated the relationship between online game addiction and reduced academic achievement motivation.

According to the research results, when college students are addicted to online games, their learning engagement can be affected, which may decrease their behavioral, emotional, and cognitive engagement; their academic achievement motivation may be further reduced and affect their academic success or even prevent them from completing their studies. The mediating role of learning engagement between online game addiction and reduced academic achievement motivation indicates that reduced academic achievement motivation influenced by online game addiction could be prevented or weakened by enhancing learning engagement.

5.2. Suggestions

Universities and families play a crucial role in preventing online game addiction among college students. One of the main reasons college students play online games may be that they lack an understanding of other leisure methods and can only relieve their psychological pressure through online games ( Fan and Gai, 2022 ). Therefore, universities should enrich college students’ after-school leisure life and help them cultivate healthy hobbies and interests. Besides, a harmonious parent–child relationship positively affects children’s learning engagement ( Shao and Kang, 2022 ). Parents’ stricter demands may aggravate children’s game addiction ( Baturay and Toker, 2019 ). Therefore, parents should assume a proper perspective on the rationality of gaming and adopt the right approach to guide their children.

One key factor influencing the quality of higher education is students’ learning engagement. The integration of educational information technology has disrupted traditional teaching methods. This trend has accelerated in the context of COVID-19. College students’ growth mindset can impact their learning engagement through the role of the perceived COVID-19 event strength and perceived stress ( Zhao et al., 2021 ). Moreover, students’ self-regulated learning and social presence positively affect their learning engagement in online contexts ( Miao and Ma, 2022 ). Students’ liking of the teacher positively affects their learning engagement ( Lu et al., 2022 ). Their perceived teacher support also positively affects their learning engagement ( An et al., 2022 ). Hence, educators should focus on teacher support and care in the teaching and learning process.

Students’ motivation for academic achievement can often be influenced by active interventions. Cheng et al. (2022) noted that the cumulative process of students gaining successful experiences contributed to an increased sense of self-efficacy, motivating them to learn. Zhou (2009) illustrated that cooperative learning motivated students’ academic achievement. In addition, Hong J. C. et al. (2021) showed that poor parent–child relationships (such as the behavior of “mama’ s boy” in adults) had a negative impact on students’ academic achievement motivation, and they concluded that cell phone addiction was more pronounced among students with low academic achievement motivation. Hence, enhancing students’ academic achievement motivation also requires family support.

5.3. Research limitations and suggestions for future research

Most of the past studies on the impact of online game addiction on academics have used quantitative research as the research method. The qualitative research approach regarding students’ online game addiction should not be neglected. By collecting objective factual materials in the form of qualitative research such as interviews a greater understanding of students’ actual views on games and the psychological factors of addiction can be achieved. Therefore, future studies could introduce more qualitative research to study online game addiction.

To pay attention to the problem of students’ online game addiction, universities and families should not wait until they become addicted and try to remedy it, but should start to prevent it before it gets to that stage. In terms of developing students’ personal psychological qualities, students’ sensation-seeking and loneliness can significantly affect their tendency to become addicted to online games ( Batmaz and Çelik, 2021 ). Adolescents’ pain intolerance problems can also contribute to Internet overuse ( Gu, 2022 ). Emotion-regulation methods affect the emotional experience and play a vital role in Internet addiction ( Liang et al., 2021 ). In this regard, it is necessary to pay attention to students’ mental health status and to guide them to establish correct values and pursue goals through psychological guidance and other means.

In addition to individual factors, different parenting can considerably impact adolescents. Adolescents who tend to experience more developmental assets are less likely to develop IGD ( Xiang et al., 2022a ), and external resources can facilitate the development of internal resources, discouraging adolescents from engaging in IGD ( Xiang et al., 2022b ). Relevant research indicates that the most critical factor in adolescents’ game addiction tendency comes from society or their parents rather than being the adolescents’ fault ( Choi et al., 2018 ). Adolescents who tend to be addicted to online games may have discordant parent–child relationships ( Eliseeva and Krieger, 2021 ). Better father-child and mother–child relationships predict lower initial levels of Internet addiction in adolescents ( Shek et al., 2019 ). Family-based approaches such as improved parent–child relationships and increased communication and understanding among family members can be a direction for adolescent Internet addiction prevention ( Yu and Shek, 2013 ).

At the school level, a close teacher-student relationship is one of the main factors influencing students’ psychological state. Students’ participation in and control over the teaching and learning process as well as their closeness to teachers can increase their satisfaction and thus enhance their learning-related well-being ( Yang J. et al., 2021 ). More school resources can lead to higher adolescent self-control, attenuating students’ online gaming disorders ( Xiang et al., 2022c ).

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. Written informed consent was not obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

R-QS, and J-HY: concept and design and drafting of the manuscript. R-QS, and J-HY: acquisition of data and statistical analysis. G-FS, and J-HY: critical revision of the manuscript. All authors contributed to the article and approved the submitted version.

This work was supported by Beijing Normal University First-Class Discipline Cultivation Project for Educational Science (Grant number: YLXKPY-XSDW202211). The Project Name is “Research on Theoretical Innovation and Institutional System of Promoting the Modernization of Vocational Education with Modern Chinese Characteristics”.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: college students, online game addiction, learning engagement, reduced academic achievement motivation, online games

Citation: Sun R-Q, Sun G-F and Ye J-H (2023) The effects of online game addiction on reduced academic achievement motivation among Chinese college students: the mediating role of learning engagement. Front. Psychol . 14:1185353. doi: 10.3389/fpsyg.2023.1185353

Received: 13 March 2023; Accepted: 08 June 2023; Published: 13 July 2023.

Reviewed by:

Copyright © 2023 Sun, Sun and Ye. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jian-Hong Ye, [email protected]

† These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Cent Asian J Glob Health
v.9(1); 2020

Online Game Addiction and the Level of Depression Among Adolescents in Manila, Philippines

Ryan v. labana.

1 Department of Biology, College of Science, Polytechnic University of the Philippines, Manila, Philippines

Jehan L. Hadjisaid

2 Senior High School, Polytechnic University of the Philippines, Manila, Philippines

Adrian R. Imperial

Kyeth elmerson jumawid, marc jayson m. lupague, daniel c. malicdem, introduction:.

World Health Organization recognizes online game addiction as a mental health condition. The rise of excessive online gaming is emerging in the Philippines, with 29.9 million gamers recorded in the country. The incidence of depression is also increasing in the country. The current correlational analysis evaluated the association between online game addiction and depression in Filipino adolescents.

A paper-and-pencil self-administered questionnaire assessing depression and online game addiction was distributed from August to November, 2018. The questionnaire included socio-demographic profiles of the respondents, and the 14-item Video Game Addiction Test (VAT) (Cronbach's α=0.91) and the Patient Health Questionnaire-9 (Cronbach's α=0.88) to determine levels of online game addiction and depression, respectively. Multiple regression analyses were used to test the association between depression and online game addiction.

Three hundred adolescents (59% males, 41% females) participated in the study. Fifty-three out of 300 respondents (12.0% males, 5.7% females) had high level of online game addiction as reflected in their high VAT scores. In this study, 37 respondents (6.7% males, 5.7% females) had moderately severe depression and 6 (2.0%) females had severe depression. Online game addiction was positively correlated with depression in this study ( r =0.31; p <0.001). When multiple regression analysis was computed, depression was found to be a predictor of online game addiction ( Coefficient =0.0121; 95% CI-8.1924 - 0.0242; p =0.05).

Conclusions:

Depression, as associated with online game addiction, is a serious threat that needs to be addressed. High level of online game addiction, as positively correlated to the rate of depression among adolescents in Manila, could potentially be attributed to the booming internet industry and lack of suffiicent mental health interventions in the country. Recommended interventions include strengthening depression management among adolescents and improving mental health services for this vulnerable population groups in schools and within the communities.

Based on the report of the European Mobile Game Market in 2016, there were more than 2.5 billion video gamers across the globe. 1 Several studies have found that the majority of these players were adolescents aged 12-17 years, 2 - 5 with more usage among males than females. 6 In 2017, newzoo.com reported that the active gamers in the Philippines were 52% males and 48% females. 7 In the US, 60% of the video gamers were males and 40% are females. 6 Studies have shown that there are similarities between males and females in regard to choice of games, behavior toward video gaming, and motives for engaging in this activity. 8 Some of the reported reasons to engage in video games include having fun and for recreation, 9 - 10 to de-stress, 11 – 12 and to avoid real life issues. 13 – 14 The prevalence of video gaming addiction varies from region to region based on the socio-cultural context and the criteria used for the assessment. 15 However, it is well established that video gaming is addictive, 16 – 18 and there is clinical evidence for the symptoms of biopsychosocial problems among video game addicts. 19 It is a serious threat to the mental and psychosocial aspects of an individual, as it lead to stress, loss of control, aggression, anxiety, and mood modification. 20 – 21

In the Philippines, online gaming is an emerging industry. The country ranks 29 th in game revenues across the globe. In 2017, there were more than 29.9 million gamers recorded in the country. Most of the gamers were 21–35 years of age, followed by the adolescents 10–20 years of age. 7 Adolescents accounted for 30.5% of the total population in the country. 22 In general, this age group is already facing mental health issues, such as anxiety, mood disorders, and depression. This concern gets more alarming as rates of suicide among high school and college students are growing worldwide. 23

World Health Organization lists video game addiction as a mental health problem. 24 Psychiatric research reported evidence on the links between depression and video game addiction. Among the findings are MRI scans of video game addicts showing disruption of some brain parts and overriding of the 'emotional' part with the 'executive' part. 25 A study in China has also reported that gamers are at increased risk of being depressed in comparison to those who did not play video games. 26 In the field of neuroscience, depression caused by online game addiction is explained as a reduction of synaptic activities due to permanent changes in the dopaminergic pathways. This means that long exposure to online gaming causes changes in a person's sense of natural rewards, often making activities less pleasurable. This neuroadaptation is also associated with chronic depression. 27

There is a paucity of studies on video game addiction in the Philippines, making its implications not well understood. There are reports of the impact of video game addiction on the academic performance of the gamers, 28 – 30 but no study has been found associating video game addiction and depression in the Philippine setting. Based on the 2004 report from the Department of Health in the Philippines, over 4.5 million cases of depression were reported in the country. Recently, World Health Organization reported that 11.6% of the 8,761 surveyed young Filipinos considered committing suicide; 16.8% of them (of 8,761) had attempted it. 31 This phenomenon is said to be instigated by several factors, including the individual's exposures to technology. Video game addiction and depression are two emerging public health issues among adolescents in the Philippines. 31 – 32 This small-scale study aims to understand the association between these two factors and produce baseline information that can be used in formulating evidence-based public health policies in the country.

Research site and participants

This study was conducted in the months of August-November 2018 in the city of Manila, the capital of the Philippines. Manila is situated on the eastern shores of Manila Bay, on the western edge of Luzon (14∘35’45”N 120∘58’38”E). It is one of the most urbanized areas and the center of technological innovation in the country. It has a population of 1.78 million, based on 2016 census. 33 Manila covers 896 barangays (villages), which are grouped into six districts. Based on the 2010 census, the total population of Filipino adolescents, regardless of sex, was 166,391. 34 This population estimate was used for computing the sample size needed for this study. Sample size calculation was estimated using the online calculator from OpenEpi. 35 The completion rate of the questionnaires was 78.13%, for a total of 300 consenting respondents who were all online video gamers. They were selected if they were residents of Manila City and reported playing video games on the regular basis.

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Map of Manila from the National Capital Region of the Philippines

Instruments

The study used a paper-and-pencil self-administered questionnaire. To determine the level of online game addiction of the respondents, the study used the Video Game Addiction Test (VAT) developed by van Rooij et al . 36 from the 14-item version of the Compulsive Internet Use Scale (CIUS). 37 VAT was utilized in several studies among adolescents in the past, and it has demonstrated excellent reliability and validity. The scale outcomes were found to be comparable across gender, ethnicity, and learning year, making it a helpful tool in studying video game addiction among various subgroups. 36 The survey contains questions in five categories: loss of control, conflict, salience, mood modification, and withdrawal symptoms. Each question was measured on a 5-point scale: 0–never to 4–very often. The results were then used as an indicator of the level of addiction. This study adapted the calculations conducted by van Rooij et al. 38 wherein the average scale scores of all the respondents were arranged from 0-4 and then were divided into two groups. The first group had an average of 0-2 or 'never' to 'sometimes', while the second group had an average of 3-4 or 'often' to 'very often'. The latter group was considered to have the highest level of problematic gaming or, in this study, with online game addiction. 38 The internal reliability of the VAT in this study was excellent at Cronbach's α of 0.91.

The level of depression of the respondents was determined by using the Patient Health Questionnaire-9 (PHQ-9). 39 It is a 9-item depression module taken from the full PHQ. The questionnaire allows the respondents to rate their health status in the past six weeks. There are 9 diagnostic questions in which the respondents rated 0 for 'not at all', 1 for 'several days', 2 for 'more than half the days', and 3 for 'nearly every day'. The total of the PHQ-9 scores was used to measure severity of depression. Since there are 9 items in the questionnaire and each question can be rated from 0-3, the PHQ-9 scores can range from 0-27. The score was interpreted as ‘no depression’ (0-4 points), ‘mild depression’ (5-9 points), ‘moderate depression’ (10-14 points), ‘moderately severe depression’ (15-19 points), and ‘severe depression’ (20-27 points). 39 In this study, the internal reliability of PHQ-9 had a Cronbach's α of 0.88.

Data gathering procedure

The study randomly surveyed gamers in various parts of Manila. Since there are no reliable records of the gamers in the area available for research, various sampling techniques were utilized. A convenience sampling was done by visiting internet cafes in the city and requesting the gamers to answer the questionnaire during their time-out (from the game). A verbal consent was provided by each respondent after hearing a brief explanation of the research objectives and the necessary instructions. While answering the questionnaire, the respondents were assisted by the investigator for any clarifications and questions. The questionnaire was completed by the respondents in approximately 2.5 minutes. Other procedures included snowball sampling, accidental, and voluntary response sampling after the distribution of invitation to respond among internet cafes, gamers’ social media groups/sites, and online gamers’ organizations. The study was approved by the ethical board of the Polytechnic University of the Philippines.

Statistical analysis

All the responses from the questionnaires were inputted into MS Excel and into SPSS version 23.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics of responses were computed and included the frequencies ( f ), percentages (%), averages x and standard deviations (SD). The association between online game addiction and depression was analyzed using Pearson's correlation and was further analyzed using a multiple regression analysis. The study hypothesized that there is no significant correlation between online game addiction and level of depression among adolescents in the City of Manila, Philippines. All statistical results were considered significant at the p value <0.05.

Profile of the respondents

A total of 300 consenting adolescents participated in the study. There were more males ( n =176; 59%) than females ( n =124; 41%) who participated in the study. Most of the respondents were adolescents (aged less than 19 years), except for the six respondents who were already 20 years old during the data gathering. The mean age of the participants was 17 years old (SD=0.90). Figure 2 presents the profiles of the respondents based on their gender and age characteristics. The VAT analysis shows that there were more males (12.0%) who were addicted to online games than females (5.7%). Meanwhile, 15-, 17-, and 18-year old respondents had the highest VAT scores among the six age groups.

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Profiles of the respondents based on gender and age

Level of online game addiction

The 14-item VAT was ranked from the highest to the lowest mean score to understand the common conditions experienced by the respondents. The item with the highest mean was No. 13: Do you game because you are feeling down? ( x =2.1, SD=1.40). This question had the third greatest number of “4-very often” ratings ( N =46/300). It was followed by the item No. 3: Do others (e.g., parents or friends) say you should spend less time on games? ( x =2.06, SD=1.41).. The third item with the highest mean score was item No. 7: Do you look forward to the next time you can game? ( x =2.0, SD=1.27). The item with the highest number of “4-very often” rating was item No. 14: Do you game to forget about problem? ( N =67/300). Items 12 and 2 also had high mean scores: Do you neglect to do your homework because you prefer to game? (Item 12; x =1.98, SD=1.34); and Do you continue to use the games despite your intention to stop ? (Item 2; x =1.84, SD=1.20).

Levels of online game addiction based on gender and age

Profiles	Overall Profile		Respondents with high VAT scores		Respondents with high VAT scores
Profiles		%		%		%

Male	176	58.7	36	12.0	36	20.5
Female	124	41.3	17	5.7	17	13.7

15 years old	12	4.0	3	1.0	3	25.0
16 years old	42	14.0	3	1.0	3	7.1
17 years old	168	56.0	34	11.3	34	22.0
18 years old	60	20.0	12	4.0	12	20.0
19 years old	12	4.0	1	0.3	1	8.3
20 years old	6	2.0	0	0.0	0	0.0

Level of depression

The PHQ-9 was used to quantify the symptoms of depression of the respondents and identify its severity. The majority of the respondents demonstrated no depression (47%), followed by having mild depression (22%), and moderate depression (17%). Of note, the current study revealed 12% of the respondents had moderately severe depression and 2% had severe depression. We found that higher PHQ-9 scores were associated with decreased functional status. The most common symptoms reported by the respondents based on the mean scores of each item in PHQ-9 include …feeling tired or having little energy ( x =1.89, SD=1.30), …poor appetite or overeating ( x =1.87, SD=1.37), … feeling down, depressed or hopeless ( x =1.81, SD=1.18), …trouble falling or staying asleep, or sleeping too much ( x =1.78, SD=1.33), and …trouble concentrating on things, such as reading newspaper or watching television ( x =1.75, SD=1.40). Interestingly, the six respondents who were identified to have “severe” depression were all females, and four of them had high VAT scores.

Level of depression of the respondents based on the PHQ-9 scores

Profiles	No Depression	Mild	Moderate	Moderately Severe	Severe
Profiles	(%)	(%)	(%)	(%)	(%)

	87 (29.0)	38 (12.7)	31 (10.3)	20 (6.7)	0 (0.0)
Female	54 (18.0)	28 (9.3)	19 (6.3)	17 (5.7)	6 (2.0)
Age
15 years	5 (1.7)	1 (0.3)	2 (0.7)	2 (0.7)	0 (0.0)
16 years	24 (8.0)	9 (3.0)	3 (1.0)	7 (2.3)	0 (0.0)
17 years	77 (25.7)	34 (11.3)	31 (10.3)	22 (7.3)	5 (1.7)
18 years	26 (8.7)	17 (5.7)	10 (3.3)	5 (1.7)	1 (0.3)
19 years	5 (1.7)	4 (1.3)	3 (1.0)	1 (0.3)	0 (0.0)
20 years	4 (1.3)	1 (0.3)	1 (0.3)	0 (0.0)	0 (0.0)

Association between online game addiction and depression

The association between online game addiction based on the VAT scores and the level of depression among the respondents was evaluated through Pearson's correlation analysis. Results ( Table 3 ) show that the level of online game addiction was positively correlated with the level of depression ( r =0.31, p <0.001) but was not significantly correlated with age or gender ( r =-0.80, p <0.171 and r = 0.10, p <0.097, respectively).

Pearson's correlation coefficient among gender, age, online game addiction, and depression of the adolescents in Manila

Gender	Age	Online game addiction	Depression
1	−.080	.100	.070
	.171	.097	.212
−.080	1	−.080	−.020
.171		.171	.739
.100	−.080	1	.310
.097	.171		.000
.070	−.020	0.310	1
.212	.739	.000	1

A multiple linear regression was calculated to predict online game addiction based on gender and depression. This regression analysis was performed with all participants and with the subset of participants with high VAT scores, which indicated online game addiction. A significant regression equation was found (F(2.50)= 2.247, 0.10), with an R 2 of 0.082. Table 4 shows that depression was a significant predictor of online game addiction.

Multiple regression analysis for prediction of online game addiction based on age and level of depression

Variable	Regression coefficient	95% CI	value

Age	–0.0224	–0.1298 – 0.0850	0.68
Depression	0.0418	0.0271 – 0.0565	0.47

Age	–0.0443	–0.1305 – 0.0417	0.30
Depression	0.0121	–8.1924 – 0.0242	0.05

The correlation between online game addiction and the levels of depression in this study was weak but statistically significant. This positive correlation was previously reported in other research studies across the globe. 40 – 41 In a study conducted by Rikkers et al. 40 among children and adolescents (11-17 years old) in Australia, electronic gaming was positively associated with emotional and behavioral problems including depression. Longer gaming hours were also associated with severe depressive symptoms, somatic symptoms, and pain symptoms among young people in Taiwan. 41 Online game addiction was associated by Zamani et al. 42 not only with depression but also with sleep disorder, physical complaints, and social dysfunctions of students in Iran. In a study conducted by Dong et al., 43 depression came out as one of the outcomes of the internet addiction disorder.

In the current study, most of the respondents looked forward to the next time they would game, with the most common reason of engaging in games reported to be easing the moments of feeling down. Another reason of the respondents’ addiction to online games was that they want to forget about problems. It is considered as one of the core symptoms of addiction as described by Brown. 44 The second most common experience of the respondents was the 'inability to voluntarily reduce the time spent on online games', which is another core symptom of addiction. 45 Most of the respondents admitted that they were getting advice from their parents or friends to spend less time on games, but they could not control it, despite their intention to stop. In fact, gaming negatively affected homework completion among many study participants. This effect was previously studied among high school students in Los Baños, Philippines, where the video gamers had 39% probability to fail in school. In this previously published study, 6 out of 10 video gamers spent their daily allowances on computer games, giving them access to continuously spend their time playing. 29 The addiction of the adolescents in Manila could have been influenced by the ubiquitous nature of internet in the city. Internet cafes are very accessible in the country, and they are thriving in almost all corners of the city. In addition, the rent for internet and online games in Metro Manila costs 10 to 20 pesos per hour only (US $0.19 to US $0.38 per hour), making playing video games affordable. Some internet hubs are even offering discounts and promotions for longer stays of 10-12 straight hours of playing online games.

Based on the most cited symptoms of the respondents in this study, it could be implied that adolescents cope with their emotional distress by playing online games. This means that the high occurrence of online game addiction goes along with the high occurrence of depression among the same group. In regard to depression, most respondents in this study were feeling tired, having poor appetite, feeling hopeless, having trouble falling asleep, or having trouble concentrating on things that require enough attention, like reading books. These symptoms were also reported by Schmit et al. 45 as related to online game addiction, where the people who spent longer hours playing online games got higher scores for loneliness and isolation. This study did not capture the number of hours spent by the respondents in online games, which could be incorporated in the next study for further analysis.

Depression, as associated to online game addiction, may lead to anxiety, compulsion, and suicide ideations. 46 This is a serious threat to the population health that needs to be addressed. Interventions may include strengthening depression management among adolescents, either in school or in the community. There are several ways to manage depression. The schools and the community should reinforce sports by making it more challenging, engaging, and motivating. In the Philippines, numerous factors make receiving mental health care a challenge. There is only one psychiatrist for every 250,000 mentally ill patients, budget dedicated to mental health interventions is limited, 47 a guidance and counseling system has not yet matured, 48 and there was even a report that online counseling was preferred by the students than its face-to-face counterpart. 49 The poor availability of the mental health interventions in the country may lead to upsurge of depression cases among adolescents. Meanwhile, the booming online game industry in the country leads to the increased numbers of addicted adolescents to online game addiction. Policy makers, the government, and its stakeholders should start addressing these issues before it becomes an even bigger health concern, especially in the face of ongoing COVID-19 pandemic.

The Philippine government should also assess their existing intervention programs in mental health issues. In 2016, “Hopeline” was launched in the Philippines. It was a national hotline for mental health assistance for the prevention of depression and suicide cases in the country. The hotline is equipped with a professional team of counselors as responders. 50 No study has been found to assess the effectiveness of this intervention for depression. National trainings and workshop programs have been implemented in other countries to empower the people in dealing with the stigma of depression which includes mental health literacy campaign, peer services, and advocacies. 51 This is an essential step to correct various misconceptions on depression, especially among adolescents.

This study was cross-sectional and cannot determine causality. This is the first report on the association between online game addiction and the levels of depression among adolescents in the city of Manila, Philippines. Despite the small sample and the limited scope of the research, the current study has shown interesting preliminary results that could be instrumental in the conduct of a bigger scale study in the country. To facilitate participation of the larger number of respondents, the future investigators are suggested to coordinate with various high schools in Metro Manila and use these schools as a sampling frame for a robust sampling technique. In this study, the level of online game addiction has no statistically significant association with age and gender. The association between age and online game addiction could have been improved by including older age groups in this study. Data from a group of young adults (college students), who are also exposed to online gaming, could be compared to these data for further analysis. Gender is commonly associated with the level of online game addiction in many studies, but it is not statistically significant in this present study. The sample size in this study was only 300 and may not have been representative enough of a general population. Also, our sample size was not large enough to capture distinctions between males and females. This could also be addressed by a wider scale of surveys in the future research.

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Positive energy districts: fundamentals, assessment methodologies, modeling and research gaps.

1. Introduction

State of the art on positive energy districts, 2. methodology.

Setting: a café-like environment with small, round tables, tablecloths, colored pens, sticky notes and any interaction tool available.
Welcome and Introduction: the host offers a welcome, introduces the World Café process, and sets the context.
Small-Group Rounds: three or more twenty-minute rounds of conversations occur in small groups. Participants switch tables after each round, with one person optionally remaining as the “table host” to brief newcomers.
Questions: each round starts with a context-specific question. Questions may remain constant or be built upon each other to guide the discussion.
Harvest: participants share their discussion insights with the larger group, often visually represented through graphic recording.
Objectives of the workshop and preparation. The first step of the World Café approach is to identify the main objectives. For this workshop, there was the need to investigate the current landscape of PED research, as well as to have a benchmark and collect feedback on the current research activities within Annex 83. Questions were structured in order to frame the current state-of-the-art understanding of the topic. A mapping of the potential different stakeholders in the PED design and implementation process was carried out at this stage. As a result, municipalities, community representatives, energy contractors, real estate companies and commercial facilitators, as well as citizens, were identified as main target groups. Later, the follow-up discussions were built around these main actors. Further, the mapping of the stakeholders’ involvement was carried out for better understanding the complexity of relationships, roles and synergies as well as the impact on the design, implementation and operation stages of PEDs.
Positive Energy Districts’ definitions and fundamentals ( Section 3.1 ).
Quality-of-life indicators in Positive Energy Districts ( Section 3.2 ).
Technologies in Positive Energy Districts: development, use and barriers ( Section 3.3 ).
Positive Energy Districts modeling: what is further needed to model PEDs? ( Section 3.4 ).
Sustainability assessment of Positive Energy Districts ( Section 3.5 ).
Stakeholder engagement within the design process ( Section 3.6 ).
Tools and guidelines for PED implementation ( Section 3.7 ).

3.1. Positive Energy Districts Definitions and Fundamentals

3.2. quality-of-life indicators in positive energy districts, 3.3. technologies in positive energy districts: development, use and barriers, 3.4. positive energy districts modeling: what is further needed to model peds, 3.5. sustainability assessment of positive energy districts, 3.6. stakeholder engagement within the design process, 3.7. tools and guidelines for ped implementation, 4. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest.

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Question #1	Question #2	Question #3
What are the essential PED DNAs? Can generic PED archetypes be created based on them?	What are the categories of quality-of-life indicators relevant for PED development?	How would you use a database tool to learn about PED development process (e.g., using static information for dynamic decision-making)?
Which future technologies would you expect to be adopted in PEDs and cities?	What can be the challenges and the barriers in the future (regarding e.g., control, smart solutions, modeling, technologies) to PED development and diffusion?	What is your expectation for urban and district energy modeling? How can models help to shape PEDs and cities?
What is the impact of stakeholders in the PED design/decision process, what are their interests and how are stakeholders likely to be involved in the overall process?	What costs do you expect to bear and what revenues do you expect to realize from the PED implementation? Which aspects should be included in the organizational/business models?	What would you prioritize in terms of energy aspects or efficiency and social implications of living in a PED? Which aspects are more relevant for you?
Annex 83 together with other PED initiatives is developing a database of PEDs and PED-Labs: what would be your main interest in consulting the database?	Having the outcomes from PED guidelines analysis, what information would be the most interesting for you to see?	Who can benefit from the PED research studies and Annex 83 results? Which stakeholders are interested?

Categories	Key Characteristics
Facts and Figures	Physical sizes/population size
	Geographical location
	Climate
	Density
	Built form
	Land use
	Energy demand
	Renewable energy potential
Technologies	Renewable energy supplies
	Energy-efficiency measures
	Energy distribution (e.g., co-generation, district network)
	Energy storage
	Mobility solutions
Quality of Life	User comfort
	Social-economic conditions
	Health impacts (e.g., air pollution, noise pollution)
	Accessibility to green space
	Accessibility to services (e.g., bike lane, public transportation)
	Local value/sense of community
Others	Regulations/Policies
	Stakeholder involvement
	Local targets and ambitions
	Local challenges
	Impacts of PEDs

Type	Quality Categories
Tangible	Indoor and outdoor environmental quality	Physical quality and comfort of the environment
	Indoor and outdoor environmental quality	Security and safety
	Level and accessibility of servicing	Public and active transport facilities including walkability, energy services (access to affordable energy including access to energy efficiency), sustainable waste management
		Access to daily life amenities including education, culture, sports, coworking and study places, provisions for children, but even common gardens or community kitchens
		Aesthetic quality
		Functional mix
		Future-proofness
		Acceptable cost of life (affordability, inclusivity)
		Equity and just transition
		Functional links to realizing circularity and reducing emissions
	Citizen engagement	Involvement in decision-making
	Citizen engagement	Social diversity in participation
	Access to greenery	The possibility to reconnect with nature
	Access to greenery	Sufficient open space
	Information flow	From creating awareness over enhancing knowledge and literacy up to capacity of control
		Transparency on energy flows and information for the end prosumer
		Insight in applicable PED solutions and in healthy lifestyles
Intangible	Sense of well-being
	Quality of social connections
	Sense of personal achievement
	Level of self-esteem
	Sense of community
	Degree of cooperation and engagement for the common interest
	Time spent with friends (outdoor)
	Budget available at the end of the month to spend freely
	Not being aware or realizing of living in a PED

Technology Groups	Solutions
Energy efficiency	New energy-efficient buildings and building retrofitting.
	Nature-based solutions (natural sinks) and carbon capture solutions (CCS)
	Efficient resource management
	Efficient water systems for agriculture (smart agriculture, hydroponics, agrivoltaics, etc.)
	Organic photovoltaics and a circular approach (second life materials, like batteries)
Energy flexibility	Hardware	Storage (long-term and short-term)
		Monitoring systems (sensors, smart meters, PLCs *, energy management systems, etc.)
		Vehicle to grid
		Heat pumps
		Electronic devices like IoT * technologies
		Buildings fully automated with real time monitoring behind-the-meter and automated actions
		Cybersecurity, data rights and data access
		Demand management and remote control of devices
	Software	Edge computing
		Machine learning
		Blockchain
		Digital twins
		5G
		City management platform and platforms for city planning (space, refurbishment, climate change, etc.)
E-mobility	Promotion of shared vehicles over individual car use, lift sharing, and alternative ways (like micromobility) to collective transports
Soft mobility	Promotion of a lifestyle that require less use of cars, i.e., “soft mobility” solutions like low emission zones or banning the entrance of some type of car (e.g., Singapore and Iran have policies in place to allow only certain car groups to drive freely in certain periods)
Soft mobility	E-vehicle charging stations and vehicle-to-grid solutions
Low-carbon generation	Photovoltaics
	Energy communities
	Electrification of heating and cooling (H&C) using heat pumps, district heating networks utilizing waste heat, or solar thermal technologies
	Virtual production
	Fusion technology

Challenges and Barriers	Key Topics
Capacity building and policy issues	Political and legal barriers
	Regulatory frameworks and policy constraints
	Tailored legislation
	Bridging the knowledge gap
	Inadequate data sharing practices
	Securing sufficient financial resources
	Lack of clear regulations defining PED classification
	Active involvement of policymakers
	Widespread dissemination of knowledge
	Collaborative data-sharing efforts
	Securing adequate funding
	Establishing supportive policies and regulations
Social challenges and considerations	Cultural barriers
	Access to affordable and sustainable energy for all
	Building social agreements and fostering collaboration
	Energy literacy
	Addressing personal behavior acceptance
	Transition strategy for inclusivity
	Social inclusion and trust-building
	Data sharing and privacy concerns
	Overcoming public opposition and promoting knowledge dissemination
Financial barriers	Long-term storage investment and space competition
	Insufficient investment
	High upfront costs
	Allocation of costs among stakeholders
	Incentives for participation
	Addressing investment challenges for different stakeholders
	Accounting for battery costs
Data management	Data standardization
	Data security measures and protocols
	Sustainability and maintenance of data infrastructure
	Privacy regulations and data anonymization techniques
Sustainable business models and ownership structures	Standardization of control technologies and replication strategies
	Grid management approaches
	Deep penetration of sustainable technologies
	Implementation of predictive models Long-term maintenance activities and resident data collection
	Balancing diverse requirements
	Addressing grid operation challenges
	Managing multiple independent energy districts
	Inclusivity strategies for digital technology reliance
	Managing production peaks and defining the role of buildings and districts
	Effective management strategies for grid congestion and stability

Categories of Innovation	Innovation Types	Possible Revenues/Advantages in PED Business Model/Governance	Possible Costs/Drawbacks in PED Business Model/Governance
Configuration	Profit Model	Providing thermal comfort instead of a certain amount of thermal energy to inhabitants	Misconducts or rebound effect
	Network	Inclusion of the PED into larger projects and international networks, possibility of co-financing and knowledge sharing	Misalignment or delay of the PED project to the original timeline due to constrains related to international activities and networking
	Structure	Participation of the real estate companies/investors in the development and management of the energy infrastructure and EV mobility services as well as building management	Lack of knowledge, involvement in activities out of the usual business of investors
	Structure	Free or almost free thermal energy supply from “waste energy” sources	Failure of the network due to unliteral decisions of a member in ceasing the provision of energy
	Process	Involvement of future inhabitants in the design phase of the energy community since the early stage, to share the sense of belonging and ownership	Reluctancy of inhabitants to participate in additional expenses or being involved in “entrepreneurial” activities or bored by the participation in boards and governance structures
Offering	Product Performance	Investors and companies involved in the PED development take profit from their role of frontrunner placing them before the competitors or entering in new market niches	Hi-tech BA and BEM systems may result costly in O&M, because of digital components, cloud and computing services, rapid aging of technology
Offering	Product System	Including EV available for PED users may generate new incomes and reduce the need of individual cars. The integration of EV in the energy system may offer “flexibility services”	Lack of knowledge, involvement in activities out of the usual business of investors/real estate companies. Low interest of users in participating to the flexibility market, because of discomfort (unexpected empty battery of the EV)
Experience	Services	Provision of high tech and high-performance buildings, with outstanding energy performances (lower heating/cooling costs) and sophisticated Building Automation and Energy Management systems	Sophisticated Building Automation and Energy Management systems may result “invasive” to users, asking for continuous interaction with complicate systems, or leaving them not enough freedom to choose (e.g., opening the windows is not possible to achieve some energy performance)
	Channel	The PED is promoted as a rewarding sustainable investment, this allows the city to attract more clean investments (public funds, investment funds, donors), speeding up the energy transition	The communication of the characteristics of the PED is not done in the proper way
	Brand	Gold class rated buildings may have an increased value on the market, resulting in higher selling and rental costs, occupancy rate. The high architectural quality is appreciated by the market	The Branding/certification of the PED is not recognized by the market as an added value.
	Brand		The development of the PED takes longer as expected. Technology failures during the implementation or operation phase create a bad reputation and discourage future similar activities
	Customer Engagement	The PED is available as a digital twin, users are engaged via a dedicated app, allowing interaction, communication, reporting, monitoring of bills, etc.	The PED is perceived by users (e.g., social housing tenants) as a hassle and not responding to their needs, because they have not been involved in the identification of peculiar traits since the beginning

Category	Beneficiaries
Citizens and communities	Citizens, inhabitants, residents, general public, local communities and neighborhoods, municipalities and provinces, energy communities, and socially disadvantaged groups.
City decision-makers and planners	City decision-makers, city planners, local authorities, policy-makers, public administrations, politicians, local and national governments.
Research	Scientists, publishers, and research organizations.
Private companies and technology developers	Private companies of RES technologies, ICT companies, start-ups and new companies, entrepreneurs, technology developers and other companies involved in local development (tech development and evaluation).
Energy providers	Energy providers, grid operators.
Education stakeholders	Students and teachers.
Non-governmental organizations (NGOs)	NGOs and other civil society groups

Category	Comments
Strategies	Most comments dealt with the strategies on how to achieve PEDs, that should focus on success factors of PED initiatives, technologies and stakeholders rather than a standardized approach
References	Useful information, special attention to Liwen Li, planning principles for integrating community empowerment into zero-carbon transformation
Definitions	Help to reduce uncertainty
Boundaries	Energy balance calculations, mobility, definition (of buildings)
Finance	Financial mechanisms, support schemes
Citizen engagement	From engagement to empowerment
Management	Process management, organizing involvement, information provision
Policy	Incentives, regional policies
Flexibility/Grid interaction	Timesteps, credit system
Form	Dissemination through video and other forms (not only written information)

Category	Comments
Lessons learned	Special reference to real life implementation
Results	Data analysis and potential research on the field
	Metadata as the useful information that can the real goal of consultation
	Benchmarking to compare PEDs
	Need to normalize results depending on a number of factors (size, location…) to really compare different initiatives
	Privacy and data protection
Sets of technologies and solutions	-
Economic parameters	As a way to benchmark the different PED technologies
Citizen engagement	Energy poverty
	Prosumers
	From engagement to empowerment
Definition and boundaries	Need to standardize and have a reference framework to establish the energy balance
Contact persons	It is very valuable to have a contact address to ask more about the initiative
Regulatory framework	Drivers and Enablers

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

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Kozlowska, A.; Guarino, F.; Volpe, R.; Bisello, A.; Gabaldòn, A.; Rezaei, A.; Albert-Seifried, V.; Alpagut, B.; Vandevyvere, H.; Reda, F.; et al. Positive Energy Districts: Fundamentals, Assessment Methodologies, Modeling and Research Gaps. Energies 2024 , 17 , 4425. https://doi.org/10.3390/en17174425

Kozlowska A, Guarino F, Volpe R, Bisello A, Gabaldòn A, Rezaei A, Albert-Seifried V, Alpagut B, Vandevyvere H, Reda F, et al. Positive Energy Districts: Fundamentals, Assessment Methodologies, Modeling and Research Gaps. Energies . 2024; 17(17):4425. https://doi.org/10.3390/en17174425

Kozlowska, Anna, Francesco Guarino, Rosaria Volpe, Adriano Bisello, Andrea Gabaldòn, Abolfazl Rezaei, Vicky Albert-Seifried, Beril Alpagut, Han Vandevyvere, Francesco Reda, and et al. 2024. "Positive Energy Districts: Fundamentals, Assessment Methodologies, Modeling and Research Gaps" Energies 17, no. 17: 4425. https://doi.org/10.3390/en17174425

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1. Introduction. In the past decade, research has accumulated suggesting that excessive Internet use can lead to the development of a behavioral addiction (e.g., [1,2,3,4]).Clinical evidence suggests that Internet addicts experience a number of biopsychosocial symptoms and consequences [].These include symptoms traditionally associated with substance-related addictions, namely salience, mood ...
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ORIGINAL RESEARCH article

1. Introduction

2. Research model and hypotheses

2.2. Research questions

2.2.2. The relationship between learning engagement and reduced academic achievement motivation

2.2.3. The relationship between online game addiction, learning engagement, and reduced academic achievement motivation

3. Research methodology and design

3.2. Measurement instruments

3.2.1. Online game addiction

3.2.2. Learning engagement