Skip to main content
NCBI home page
Addictive Behaviors Reports logoLink to Addictive Behaviors Reports
. 2025 Nov 5;22:100641. doi: 10.1016/j.abrep.2025.100641

Psychophysiological response of individuals with internet gaming disorder to gaming content from social media

Daisuke Jitoku a,b, Nanase Kobayashi a,b, Yuka Fujimoto a,b,c, Chenyu Qian a, Shoko Okuzumi a, Shisei Tei d,e,f,g, Takehiro Tamura a, Hidehiko Takahashi a,d,h, Takefumi Ueno i, Junya Fujino a,d,⁎
PMCID: PMC12648693  PMID: 41312193

Highlights

  • •

    Gaming content from social media increased gaming desire and SCR in IGD and healthy gamers.

  • •

    IGD group showed stronger SCR than healthy gamers.

  • •

    The levels of SCR correlated with gaming history in healthy gamers.

  • •

    Interventions should address subjective and physiological aspects of gaming behavior.

Keywords: Cue reactivity, Gaming history, Internet gaming disorder, Skin conductance response, Social media

Abstract

Despite the increasing clinical recognition of internet gaming disorder (IGD), treatment options remain scarce, and relapse rates are high. One major challenge is the pervasive presence of digital triggers that reinforce gaming behaviors, particularly through social media platforms, which are integral to gaming culture. Further research is needed on how gaming-related social media content affects gaming desire and physiological reactions because this topic remains understudied. This study investigated the effects of gaming-related social media videos on gaming desire and skin conductance response (SCR) in individuals with IGD and healthy controls (HCs) who casually play online games. While participants viewed gaming-related and neutral videos from social media, their gaming desire and SCR were assessed. Correlations between SCR and clinical variables were also examined. Notably, both groups exhibited increased gaming desire and SCR after viewing gaming-related videos compared with those after viewing neutral ones. Although self-reported gaming desire was comparable between groups, the SCR was significantly higher in the IGD group. In the HC group, SCR levels were positively correlated with gaming history. The dissociation between subjective and physiological outcomes may indicate implicit sensitization to gaming-related cues in IGD, suggesting that physiological reactivity could occur independently of self-reported cravings. Our findings can help elucidate the underlying mechanisms of IGD and highlight the need for further research on strategies aimed at managing gaming-related cue exposure in digital environments.

1. Introduction

Online gaming has experienced significant growth, providing both entertainment and cognitive stimulation. In line with this, cases of internet gaming disorder (IGD), characterized by impaired control and functioning resulting from excessive gaming (Hein et al., 2024, Kim et al., 2021), have been increasingly reported in clinical settings (Burleigh et al., 2025, Castro and Neto, 2025, Footitt et al., 2024). However, available treatments for IGD show limited effectiveness, and patients experience high rates of relapse (Flayelle et al., 2025, Kobayashi et al., 2025, Stevens et al., 2021). An emerging concern is the rising number of digital cues via social networks (e.g., TikTok, Instagram, YouTube) (Fioravanti et al., 2025, Kuss and Griffiths, 2017), which may serve as potent triggers for craving and consumption (Fujimoto et al., 2024, Fujimoto et al., 2025a, Fujimoto et al., 2025b, Jitoku et al., 2024). The incentive sensitization theory (Berridge and Robinson, 2016, Robinson and Berridge, 2025) proposes that repeated exposure to addiction-related cues enhances their motivational salience through conditioning, resulting in increased cue reactivity even without conscious craving. The implicit sensitization process in IGD patients would lead to stronger physiological reactions when they encounter gaming-related content on social media platforms.

The cue-reactivity framework explains how addictive behaviors lead people to develop stronger reactions when they encounter cues that trigger their addiction (Carter and Tiffany, 1999, Starcke et al., 2018). Cue-reactivity studies on IGD patients have demonstrated increased brain activity in reward-processing regions, heightened autonomic arousal, and increased attentional biases in response to gaming-related stimuli (Dong et al., 2021, Kim et al., 2021, Liu et al., 2017). However, most studies focused on direct in-game cues, with little research examining indirect exposure through passive social media engagement.

The skin conductance response (SCR) is a widely used psychophysiological indicator which measures autonomic nervous system changes when people encounter emotionally and motivationally salient stimuli (Schneider et al., 2022). It searves as a useful tool in addiction research to evaluate how people react to both substance-based and non-substance-based cues (Metcalf and Pammer, 2013, Ordoñana et al., 2012, Trotzke et al., 2014, Wang et al., 2019). Previous research has shown that IGD patients exhibit altered physiological responses to in-game stimuli (Kim et al., 2018, Kim et al., 2021), but it remains unclear whether gaming-related social media content would elicit similar effect. As social media becomes more integrated into daily life, it is important to determine if passive exposure to game-related content on these platforms increases SCR responses in IGD patients.

This study compared the effects of gaming-related videos on social media on subjective and physiological responses in IGD individuals and healthy controls (HC) who play online games casually. All IGD participants were diagnosed through structured clinical interviews based on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria by experienced psychiatrists to ensure diagnostic accuracy and consistency with previous cue reactivity studies. We hypothesized that exposure to gaming-related social media content would significantly increase both subjective gaming desire and physiological responses, as measured via SCR, in both groups, with more pronounced effects in the IGD group.

2. Methods

2.1. Participants

For this study, we initially recruited 26 individuals with IGD and 26 HC volunteers who played online games casually. The sample size was determined based on previous studies examining skin conductance in individuals with behavioral addictions (Metcalf and Pammer, 2013, Trotzke et al., 2014), as well as on a power analysis based on the effect sizes in these studies (Cohen’s d = ∼0.6–0.9) using G*Power software (α = 0.05, 1 − β = 0.8) (Faul et al., 2007). Seven individuals (five with IGD and two HCs) withdrew, resulting in 21 individuals with IGD (20 males, 21.8 ± 4.9 years [mean ± SD]) and 24 HC volunteers (22 males, 21.6 ± 2.4 years) participating the study. Please see Supplementary Methods for details. Participants with IGD were recruited from outpatient units at the Department of Psychiatry, Institute of Science Tokyo Hospital, whereas HC volunteers were recruited from the general population in the Tokyo area.

All IGD participants were diagnosed through structured clinical interviews based on DSM-5 criteria by experienced psychiatrists (>10 years of clinical experience). Psychiatric comorbidities were also assessed using the Structured Clinical Interview for DSM-5 (SCID-5). Conversely, the HC group included participants who were regularly engaged in online gaming for at least an hour weekly without meeting the DSM-5 criteria for IGD. There were no significant differences between the HC and IGD groups in terms of age, sex, and IQ (all p > 0.63). Please see Supplementary Methods for details.

The institutional review board of the Institute of Science Tokyo Hospital approved this study, which conformed to the Code of Ethics of the World Medical Association. All participants provided written informed consent after receiving an explanation of the entire study.

2.2. Experimental task

This study used 16 gaming-related videos sourced from social media, including content such as individuals enjoying a game, introducing a game, and providing gameplay instructions. In addition, 16 neutral videos (i.e., nongaming videos related to furniture, hygiene, travel, work, etc.) were also selected from social media platforms. Using methodology from previous studies (Chen et al., 2018, Ueno et al., 2025, Vollstädt-Klein et al., 2011), these neutral videos were chosen to closely match each gaming-related video in terms of complexity, content, design, luminance, color, action, and presence of faces. The videos were displayed pseudo-randomly, and after each video was presented, participants were asked to rate their gaming desire from 1 (no desire) to 9 (extreme desire) (Fig. 1). Please see Supplementary Methods for details.

Fig. 1.

Fig. 1

Open in a new tab

Experimental task. After each video was presented, participants were asked to rate their gaming desire from 1 (no desire) to 9 (extreme desire). For illustration purposes, the comic-style pictures represent a video.

2.3. Skin conductance response (SCR) data acquisition and analysis

During the experimental task, electrodermal activity (EDA) was recorded using a psychophysiological monitoring system (MP36; Biopac Systems, CA). To record EDA, Ag/AgCl electrodes filled with a gelled isotonic electrolyte were attached to the palmar and second phalanges of the index and middle fingers of the nondominant hand. The electrodermal data was analyzed using the Acknowledge software (Biopac Systems, CA). To normalize the distribution of the SCR, a log transformation (log [1 + SCR]) was applied for the analyses (Matsuda et al., 2020, Osumi, 2019). Statistical analyses were performed using SPSS 29, with statistical significance set at p < 0.05 (two-tailed). Please see Supplementary Methods for details.

3. Results

The study population generally performed the task well, missing an average of only 0.42 ± 0.84 trials out of 32 trials. Participants in both groups reported significantly higher gaming desire in response to gaming-related cues on social media versus neutral ones (HC: 4.16 ± 1.48 vs. 2.08 ± 1.21, p < 0.01, d = 1.76; IGD: 4.66 ± 1.33 vs. 2.56 ± 1.22, p < 0.01, d = 1.64). There were no significant differences between the groups in Δgaming desireG–N levels (HC: 2.07 ± 1.18, IGD: 2.10 ± 1.28, p = 0.93, d = 0.03).

Fig. 2A presents the mean SCR levels during the gaming and neutral conditions for both groups. The condition had a significant main effect on SCR, with significantly higher SCR observed during the gaming condition compared with the neutral condition (F = 16.26, p < 0.01, η2p = 0.27; 0.05 ± 0.06 [game] vs. 0.04 ± 0.03 [neutral]). Additionally, the group had a significant main effect on SCR, with the IGD group exhibiting higher SCR than the HC group (F = 4.16, p = 0.048, η2p = 0.09; 0.03 ± 0.03 [HC] vs. 0.06 ± 0.05 [IGD]). A significant group × condition interaction was also observed (F = 4.71, p = 0.04, η2p = 0.10). Post-hoc comparisons indicated that SCR levels were higher in the gaming condition than in the neutral condition for both groups (HC: 0.04 ± 0.03 vs. 0.03 ± 0.03, p = 0.03, d = 0.48 [not significant after Bonferroni correction]; IGD: 0.07 ± 0.07 vs. 0.04 ± 0.04, p < 0.01, d = 0.70). In the gaming condition, SCR levels were higher in the IGD group versus the HC group (p = 0.04, d = 0.66), but this difference did not remain significant after Bonferroni correction for multiple testing (α corrected = 0.0125 [0.05/4]). In the neutral condition, there were no significant differences in SCR levels between groups (p = 0.13, d = 0.46). Please see Fig. S1 regarding the SCR levels for each trial in both the gaming and neutral conditions.

Fig. 2.

Fig. 2

Open in a new tab

SCR levels. (A) ANOVA for SCR levels. Error bars indicate ± standard errors. (B) ΔSCRG–N and gaming history. In the HC group, ΔSCRG–N positively correlated with gaming history (r = 0.44, p = 0.03). Abbreviations: ANOVA, analysis of variance; HC, healthy control; IGD, internet gaming disorder; SCR, skin conductance response; ΔSCRG–N, difference in skin conductance response between game-related and neutral conditions. *p < 0.05, **p < 0.01.

The difference in SCR between the gaming and neutral conditions was calculated (ΔSCRG–N; HC: 0.01 ± 0.02; IGD: 0.03 ± 0.04; p = 0.048; d = 0.65), along with its correlations with Δgaming desireG–N, familiarity ratings, and clinical characteristics across participants. No significant correlations were observed between ΔSCRG–N and either Δgaming desireG–N or familiarity ratings in either group (all, p > 0.09). However, ΔSCRG–N was positively correlated with gaming history in the HC group (r = 0.44, p = 0.03, Fig. 2B). No other clinical characteristics were significantly correlated with ΔSCRG–N in either group (all p > 0.14).

4. Discussion

As expected, exposure to gaming-related footage on social media (compared to neutral one) significantly increased both subjective gaming desire and SCR in both groups. These findings indicate that gaming-related social media content serves as a salient cue for both casual gamers and IGD patients, highlighting social media as an important context for studying the psychological and physiological mechanisms underlying gaming engagement and potential addiction.

Although both HC and IGD groups exhibited increased gaming desire after exposure to gaming-related videos, there were no significant differences between groups, suggesting that, at a conscious level, individuals with IGD do not necessarily experience a stronger urge to play than their healthy counterparts. However, the IGD group had a significantly greater SCR, which reflects their heightened physiological reactivity to gaming cues. This dissociation between subjective craving and physiological arousal suggests that individuals with IGD may have an implicit sensitized response to gaming stimuli. This may contribute to compulsive gaming behavior even in the absence of conscious cravings. Similarly, previous studies have reported no significant differences in self-reported gaming desire between IGD and HC individuals, despite heightened physiological or neurobiological reactivity in those with IGD. For example, Kim et al. (2021) reported that, despite comparable levels of subjective craving, individuals with IGD exhibited increased late positive potential amplitudes in response to gaming stimuli compared with controls. Furthermore, Dong et al. (2017) showed that gaming elicited increased activation in the lateral and prefrontal cortex at post-test in individuals with IGD but not in recreational gamers, despite comparable self-reported craving levels. Our results suggest that SCR is a more sensitive measure of gaming cue reactivity than self-reported assessments. In contrast, other studies have reported that, when exposed to gaming cues, individuals with IGD had significantly higher self-reported gaming desire than controls (Dong et al., 2021, Wang et al., 2017). These discrepancies can be attributed to differences in study design, including the type of gaming stimuli, participant characteristics, or assessment methods for craving. Furthermore, individual variabilities in craving awareness or self-reporting biases may contribute to these inconsistencies. Future research employing standardized assessment methods can clarify the conditions under which IGD patients report higher gaming desire.

Interestingly, SCR levels were positively correlated with gaming history in the HC group. This suggests that physiological responses to gaming cues develop over time with gaming exposure but remain within a regulated range in healthy gamers. In contrast, no such an association was observed among individuals with IGD, even though the variance in gaming history was not smaller than that in the HC group. One possible explanation is that the heightened autonomic reactivity in IGD may represent a trait-like or intrinsic characteristic of the disorder rather than a consequence of cumulative gaming exposure. In other words, individuals with IGD may exhibit persistently elevated physiological sensitivity to gaming-related cues, independent of gaming duration or frequency. Longitudinal studies investigating whether this hyper-reactivity precedes or results from prolonged gaming could help clarify the causal direction of this relationship.

Our findings have several important clinical implications. For instance, the heightened physiological response to gaming cues, despite the absence of consciously perceived craving, may promote compulsive gaming by reinforcing automatic cue reactivity. Future research should explore the long-term impact of repeated exposure to social media gaming content and its potential role in IGD. In addition, interventions targeting physiological regulation, such as biofeedback training or mindfulness-based approaches, can attenuate the heightened autonomic responses to gaming cues and improve self-regulation in individuals with IGD (Kim et al., 2018, Hsieh et al., 2020). Digital well-being strategies, such as limiting exposure to gaming-related content on social media and increasing awareness of its effects, can help promote healthier gaming habits.

This study has several limitations. First, although we closely matched each gaming-related stimulus with a neutral counterpart, it was challenging to perfectly match these across multiple parameters because we used natural stimuli from real-world social media content. Despite our efforts to carefully select neutral stimuli, factors such as the foreground–background ratio and zooming speed could not be fully controlled. Moreover, future studies can incorporate alternative reward-related stimuli (e.g., shopping, food) instead of neutral videos to assess the stimulus-specificity of gaming cue reactivity. Comparing gaming cues with other rewarding but nongaming stimuli would help determine whether the observed responses are unique to gaming content or reflect a broader sensitivity to rewarding cues. Such designs would strengthen interpretations of cue-specific sensitization mechanisms underlying IGD. Second, our sample size was small, although still comparable to that of previous studies examining skin conductance on behavioral addictions (Metcalf and Pammer, 2013, Trotzke et al., 2014). Due to the unexpected withdrawal of several volunteers and experimental scheduling constraints, we proceeded with a sample size that allowed for a preliminary examination of our hypotheses. We emphasize the need for future studies to replicate and extend the present findings with larger samples. Third, some IGD participants had comorbid psychiatric conditions (ASD, ADHD, OCD, and combinations of these), which could influence our findings because these individuals can sometimes exhibit altered psychophysiological responses to various stimuli (Schoen et al., 2008, Starcke et al., 2009). On the other hand, since these disorders are prevalent in IGD, their presence may reflect shared biological features (Ko et al., 2020, Yen et al., 2017), suggesting that our IGD sample is representative of a typical IGD population. Fourth, some participants with IGD were taking psychotropic medications. In particular, antipsychotics have been repeatedly reported to influence autonomic and emotional reactivity (Blessing et al., 2011, Wiedemann, 2011). Although the post hoc analyses excluding the participant who was taking antipsychotic medication did not materially change the results, this factor should be taken into account when interpreting the present findings. Fifth, as mentioned above, self-reported measures of gaming desire may be influenced by participants’ tendency to present themselves in a socially acceptable manner. Finally, the current study focused exclusively on SCR as the physiological indicator. To provide a more comprehensive characterization, future research should incorporate other physiological indices which include heart rate variability and eye-blink frequency. Despite these limitations, the current findings enhance our understanding of the mechanisms underlying IGD and emphasize the need for further research on strategies for managing gaming-related cue exposure in digital environments.

CRediT authorship contribution statement

Daisuke Jitoku: Writing – review & editing, Writing – original draft, Project administration, Methodology, Investigation, Data curation, Conceptualization. Nanase Kobayashi: Writing – review & editing, Writing – original draft, Methodology, Investigation, Data curation, Conceptualization. Yuka Fujimoto: Writing – review & editing, Investigation, Data curation, Conceptualization. Chenyu Qian: Writing – review & editing, Validation, Investigation, Data curation. Shoko Okuzumi: Writing – review & editing, Methodology, Investigation, Data curation. Shisei Tei: Writing – review & editing, Validation, Methodology, Formal analysis. Takehiro Tamura: Writing – review & editing, Supervision, Investigation, Conceptualization. Hidehiko Takahashi: Writing – review & editing, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization. Takefumi Ueno: Writing – review & editing, Supervision, Project administration, Methodology, Investigation, Conceptualization. Junya Fujino: Writing – review & editing, Writing – original draft, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors wish to extend their gratitude to the research team of Department of Psychiatry and Behavioral Sciences, Institute of Science Tokyo for their assistance in data acquisition. We would like to thank Aray Inc. for their technical support in the SCR analysis. This work was supported by the Japan Agency for Medical Research and Development (JP23dk0307102, JP24dk0307128), Intramural Research Grant (4-1) for Neurological and Psychiatric Disorders of NCNP and KDDI Corporation (KDDI Research, Inc). This study was also supported in part by KAKENHI JP (23K06981, 25K10811) from the Ministry of Education, Culture, Sports, Science and Technology of Japan. These agencies had no further role in the study design, the collection, analysis, and interpretation of data, the writing of the report, or the decision to submit the paper for publication.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.abrep.2025.100641.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Supplementary Data 1
mmc1.docx (259.5KB, docx)

Data availability

Data will be made available on request.

References

  1. Berridge K.C., Robinson T.E. Liking, wanting, and the incentive-sensitization theory of addiction. American Psychologist. 2016;71(8):670. doi: 10.1037/amp0000059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Blessing E., Kader L., Arpandy R., Ootsuka Y., Blessing W.W., Pantelis C. Atypical antipsychotics cause an acute increase in cutaneous hand blood flow in patients with schizophrenia and schizoaffective disorder. Australian & New Zealand Journal of Psychiatry. 2011;45(8):646–653. doi: 10.3109/00048674.2011.5873. [DOI] [PubMed] [Google Scholar]
  3. Burleigh T.L., Footitt T., Carras M.C., Conkey-Morrison C., Poulus D.R., Stavropoulos V. Flowing in the net of disordered gaming: A network analysis approach. Addictive Behaviors Reports. 2025;21 doi: 10.1016/j.abrep.2025.100606. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Carter B.L., Tiffany S.T. Meta-analysis of cue-reactivity in addiction research. Addiction. 1999;94(3):327–340. doi: 10.1046/j.1360-0443.1999.9433273.x. [DOI] [PubMed] [Google Scholar]
  5. Castro C.M., Neto D.D. Profiling gamers: The role of mental health, attachment and social factors in gaming behaviors. Addictive Behaviors. 2025;158 doi: 10.1016/j.addbeh.2025.108390. [DOI] [PubMed] [Google Scholar]
  6. Chen Y., Fowler C.H., Papa V.B., Lepping R.J., Brucks M.G., Fox A.T., Martin L.E. Adolescents’ behavioral and neural responses to e-cigarette advertising. Addiction Biology. 2018;23(2):761–771. doi: 10.1111/adb.12510. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Dong G., Wang L., Du X., Potenza M.N. Gaming increases craving to gaming-related stimuli in individuals with internet gaming disorder. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. 2017;2(5):404–412. doi: 10.1016/j.bpsc.2017.01.002. [DOI] [PubMed] [Google Scholar]
  8. Dong G.H., Wang M., Zheng H., Wang Z., Du X., Potenza M.N. Disrupted prefrontal regulation of striatum-related craving in internet gaming disorder revealed by dynamic causal modeling: Results from a cue-reactivity task. Psychological Medicine. 2021;51(9):1549–1561. doi: 10.1017/S003329172000032X. [DOI] [PubMed] [Google Scholar]
  9. Faul F., Erdfelder E., Lang A.G., Buchner A. G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods. 2007;39(2):175–191. doi: 10.3758/BF03193146. [DOI] [PubMed] [Google Scholar]
  10. Fioravanti G., Benucci S.B., Ghinassi S. Psychological risk factors for problematic social network use: An overview of systematic reviews and meta-analyses. Addictive Behaviors Reports. 2025;21 doi: 10.1016/j.abrep.2025.100600. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Flayelle M., Andronicos M., King D.L., Billieux J. Understanding the interplay between video game design features and dysregulated gaming patterns: A call to anchor future research directions in interactionist frameworks. Addictive Behaviors Reports. 2025;21 doi: 10.1016/j.abrep.2025.100609. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Footitt T., Christofi N., Poulus D.R., Carras M.C., Stavropoulos V. Gaming disorder: The role of a gamer’s flow profile. Addictive Behaviors Reports. 2024;19 doi: 10.1016/j.abrep.2024.100555. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Fujimoto Y., Fujino J., Matsuyoshi D., Jitoku D., Kobayashi N., Qian C., Takahashi H. Neural responses to gaming content on social media in young adults. Behavioural Brain Research. 2024;459 doi: 10.1016/j.bbr.2024.115004. [DOI] [PubMed] [Google Scholar]
  14. Fujimoto Y., Fujino J., Matsuyoshi D., Jitoku D., Kobayashi N., Qian C., Takahashi H. Effects of gaming content from social media on individuals with internet gaming disorder: An fMRI study. Cerebral Cortex. 2025;35(4) doi: 10.1093/cercor/bhaf096. [DOI] [PubMed] [Google Scholar]
  15. Fujimoto Y., Fujino J., Matsuyoshi D., Jitoku D., Kobayashi N., Qian C., Takahashi H. Neural correlates of resistance to gaming desire induced by social media content. Addiction Biology. 2025;30(9) doi: 10.1111/adb.70085. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Hein K., Burleigh T.L., Gorman A., Prokofieva M., Stavropoulos V. Proteus effect avatar profiles: Associations with disordered gaming and activity levels. Addictive Behaviors Reports. 2024;20 doi: 10.1016/j.abrep.2024.100562. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Hsieh H.F., Hsu H.T., Lin P.C., Yang Y.J., Huang Y.T., Ko C.H., Wang H.H. The effect of age, gender, and job on skin conductance response among smartphone users who are prohibited from using their smartphone. International Journal of Environmental Research and Public Health. 2020;17(7):2313. doi: 10.3390/ijerph17072313. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Jitoku D., Kobayashi N., Fujimoto Y., Qian C., Okuzumi S., Tei S., Fujino J. Explicit and implicit effects of gaming content on social media on the behavior of young adults. Frontiers in Psychology. 2024;15 doi: 10.3389/fpsyg.2024.1332462. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kim H., Ha J., Chang W.D., Park W., Kim L., Im C.H. Detection of craving for gaming in adolescents with internet gaming disorder using multimodal biosignals. Sensors. 2018;18(1):102. doi: 10.3390/s18010102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kim B.M., Lee J., Choi A.R., Chung S.J., Park M., Koo J.W., Choi J.S. Event-related brain response to visual cues in individuals with internet gaming disorder: Relevance to attentional bias and decision-making. Translational Psychiatry. 2021;11(1):258. doi: 10.1038/s41398-021-01375-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Ko C.H., Lin H.C., Lin P.C., Yen J.Y. Validity, functional impairment and complications related to internet gaming disorder in the DSM-5 and gaming disorder in the ICD-11. Australian & New Zealand Journal of Psychiatry. 2020;54(7):707–718. doi: 10.1177/0004867419881499. [DOI] [PubMed] [Google Scholar]
  22. Kobayashi N., Jitoku D., Nishihara M., Fujimoto Y., Qian C., Okuzumi S., Tei S., Fujino J. Facial emotional expression in reaction to internet gaming videos among young adults: A preliminary and exploratory study. Neuropsychopharmacology Reports. 2025;45(2) doi: 10.1002/npr2.70031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kuss D.J., Griffiths M.D. Social networking sites and addiction: Ten lessons learned. International Journal of Environmental Research and Public Health. 2017;14(3):311. doi: 10.3390/ijerph14030311. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Liu L., Yip S.W., Zhang J.T., Wang L.J., Shen Z.J., Liu B., Fang X.Y. Activation of the ventral and dorsal striatum during cue reactivity in internet gaming disorder. Addiction Biology. 2017;22(3):791–801. doi: 10.1111/adb.12338. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Matsuda I., Matsumoto A., Nittono H. Time passes slowly when you are concealing something. Biological Psychology. 2020;155 doi: 10.1016/j.biopsycho.2020.107932. [DOI] [PubMed] [Google Scholar]
  26. Metcalf O., Pammer K. Physiological arousal deficits in addicted gamers differ based on preferred game genre. European Addiction Research. 2013;20(1):23–32. doi: 10.1159/000349907. [DOI] [PubMed] [Google Scholar]
  27. Ordoñana J.R., González-Javier F., Gómez-Amor J. Psychophysiological reactivity to environmental tobacco smoke on smokers and non-smokers. Addictive Behaviors. 2012;37(7):838–843. doi: 10.1016/j.addbeh.2012.03.005. [DOI] [PubMed] [Google Scholar]
  28. Osumi T. Mediating role of attenuated physiological arousal on the association between psychopathic traits and fairness norm violation. Scientific Reports. 2019;9(1):18053. doi: 10.1038/s41598-019-54676-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Robinson T.E., Berridge K.C. The incentive-sensitization theory of addiction 30 years on. Annual Review of Psychology. 2025;76:1–25. doi: 10.1146/annurev-psych-011624-024031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Schneider M., Obsuth I., Szymanska M., Mathieu J., Nezelof S., Lyons-Ruth K., Vulliez-Coady L. Attachment-based parent–adolescent interaction linked to visual attention and autonomic arousal to distress and comfort stimuli. BMC Psychology. 2022;10(1):112. doi: 10.1186/s40359-022-00821-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Schoen S.A., Miller L.J., Brett-Green B., Hepburn S.L. Psychophysiology of children with autism spectrum disorder. Research in Autism Spectrum Disorders. 2008;2(3):417–429. doi: 10.1016/j.rasd.2007.09.002. [DOI] [Google Scholar]
  32. Starcke K., Tuschen-Caffier B., Markowitsch H.J., Brand M. Skin conductance responses during decisions in ambiguous and risky situations in obsessive-compulsive disorder. Cognitive Neuropsychiatry. 2009;14(3):199–216. doi: 10.1080/13546800902996831. [DOI] [PubMed] [Google Scholar]
  33. Starcke K., Antons S., Trotzke P., Brand M. Cue-reactivity in behavioral addictions: A meta-analysis and methodological considerations. Journal of Behavioral Addictions. 2018;7(2):227–238. doi: 10.1556/2006.7.2018.39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Stevens M.W., Dorstyn D., Delfabbro P.H., King D.L. Global prevalence of gaming disorder: A systematic review and meta-analysis. Australian & New Zealand Journal of Psychiatry. 2021;55(6):553–568. doi: 10.1177/0004867420962851. [DOI] [PubMed] [Google Scholar]
  35. Trotzke P., Starcke K., Pedersen A., Brand M. Cue-induced craving in pathological buying: Empirical evidence and clinical implications. Psychosomatic Medicine. 2014;9(1):694–700. doi: 10.1097/PSY.0000000000000126. [DOI] [PubMed] [Google Scholar]
  36. Ueno T., Nakayama N., Fukushima S., Matsuguchi K., Tojiki K., Qian C., Fujino J. Inhibitory control in response to alcohol-promoting commercials in individuals with alcohol use disorder. Alcohol and Alcoholism. 2025;60(5) doi: 10.1093/alcalc/agaf056. [DOI] [PubMed] [Google Scholar]
  37. Vollstädt-Klein S., Kobiella A., Bühler M., Graf C., Fehr C., Mann K., Smolka M.N. Severity of dependence modulates smokers’ neuronal cue reactivity and cigarette craving elicited by tobacco advertisement. Addiction Biology. 2011;16(1):166–175. doi: 10.1111/j.1369-1600.2010.00207.x. [DOI] [PubMed] [Google Scholar]
  38. Wang L., Wu L., Wang Y., Li H., Liu X., Du X., Dong G. Altered brain activities associated with craving and cue reactivity in people with internet gaming disorder: Evidence from the comparison with recreational internet game users. Frontiers in Psychology. 2017;8:1150. doi: 10.3389/fpsyg.2017.01150. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Wang W., Zhornitsky S., Le T.M., Dhingra I., Zhang S., Krystal J.H., Chiang-Shan R.L. Cue-elicited craving, thalamic activity, and physiological arousal in adult non-dependent drinkers. Journal of Psychiatric Research. 2019;116:74–82. doi: 10.1016/j.jpsychires.2019.06.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Wiedemann K. Biomarkers in development of psychotropic drugs. Dialogues in Clinical Neuroscience. 2011;13(2):225–234. doi: 10.31887/DCNS.2011.13.2/kwiedemann. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Yen J.Y., Liu T.L., Wang P.W., Chen C.S., Yen C.F., Ko C.H. Association between internet gaming disorder and adult attention deficit and hyperactivity disorder and their correlates: Impulsivity and hostility. Addictive Behaviors. 2017;64:308–313. doi: 10.1016/j.addbeh.2016.04.024. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Data 1
mmc1.docx (259.5KB, docx)

Data Availability Statement

Data will be made available on request.

Articles from Addictive Behaviors Reports are provided here courtesy of Elsevier

RESOURCES