188Accesses
2Citations
Abstract
Associations exist between avatars’ behaviors in massive multiplayer online games (MMOGs) and their users’ depressive/manic levels; however, these causal relationships remain unclear. Therefore, we designed a parallel-group superiority trial to examine the causal effects of an avatar’s “likes” on its user’s depressive/manic levels. In total, 416 users of Pigg Party, a popular MMOG in Japan, were recruited and randomly assigned to the morning, evening, all-day, and waitlist groups. The morning and evening groups were asked to send likes to their peers at least five times during a specific period (7:00 AM to 8:00 AM and 7:00 PM to 8:00 PM, respectively) for four weeks, and the all-day group was asked to send likes anytime during the day (12:00 AM to 11:59 PM). The waitlist group did not receive any interventions. Depression and manic levels were measured before and after the intervention using self-reported questionnaires. In the all-day group, after sending a like to a peer, the frequency of receiving a like back from that peer was slightly higher, and its frequency was significantly negatively correlated with the level of depression. These results suggest that the exchange of likes on the MMOG can reduce depression levels of its users.
This is a preview of subscription content,log in via an institution to check access.
Access this article
Subscribe and save
- Get 10 units per month
- Download Article/Chapter or eBook
- 1 Unit = 1 Article or 1 Chapter
- Cancel anytime
Buy Now
Price includes VAT (Japan)
Instant access to the full article PDF.







Similar content being viewed by others
Data availability
Due to the contract with the funding organization, the current dataset is not publicly available in a repository. Especially in Japan, the confidentiality of communications between individual users is strictly enforced. Therefore, this study cannot analyze the contents of chats and their partners, and, of course, cannot disclose them to third parties.
References
Association, A. P. (2022).Diagnostic and Statistical Manual of Mental Disorders: DSM-5-TR, 第5版. Amer Psychiatric Pub Inc.
Chiang, K.-J., Tsai, J.-C., Liu, D., Lin, C.-H., Chiu, H.-L., & Chou, K.-R. (2017). Efficacy of cognitive-behavioral therapy in patients with bipolar disorder: A meta-analysis of randomized controlled trials.PLoS ONE,12(5), e0176849.https://doi.org/10.1371/journal.pone.0176849
W. H. Organization, “Depression and other common mental disorders: global health estimates,” World Health Organization, 2017.https://apps.who.int/iris/bitstream/handle/10665/254610/W?sequence=1. Retrieved 05 Jun 2024.
Clemente, A. S., et al. (2015). Bipolar disorder prevalence: A systematic review and meta-analysis of the literature.Braz. J. Psychiatry,37, 155–161.https://doi.org/10.1590/1516-4446-2012-1693
Hawton, K., Casañas i Comabella, C., Haw, C., & Saunders, K. (2013). Risk factors for suicide in individuals with depression: A systematic review.Journal of Affective Disorders,147(1), 17–28.https://doi.org/10.1016/j.jad.2013.01.004
Messer, T., Lammers, G., Müller-Siecheneder, F., Schmidt, R.-F., & Latifi, S. (2017). Substance abuse in patients with bipolar disorder: A systematic review and meta-analysis.Psychiatry Research,253, 338–350.https://doi.org/10.1016/j.psychres.2017.02.067
Zhang, Z., Zhang, L., Zhang, G., Jin, J., & Zheng, Z. (2018). The effect of CBT and its modifications for relapse prevention in major depressive disorder: A systematic review and meta-analysis.BMC Psychiatry,18(1), 50.https://doi.org/10.1186/s12888-018-1610-5
Gao, T., et al. (2020). When adolescents face both Internet addiction and mood symptoms: A cross-sectional study of comorbidity and its predictors.Psychiatry Research,284, 112795.https://doi.org/10.1016/j.psychres.2020.112795
Ostinelli, E. G., et al. (2021). Depressive symptoms and depression in individuals with internet gaming disorder: A systematic review and meta-analysis.Journal of Affective Disorders,284, 136–142.https://doi.org/10.1016/j.jad.2021.02.014
Bonnaire, C., & Baptista, D. (2019). Internet gaming disorder in male and female young adults: The role of alexithymia, depression, anxiety and gaming type.Psychiatry Research,272, 521–530.https://doi.org/10.1016/j.psychres.2018.12.158
Lee, Z. W. Y., Cheung, C. M. K., & Chan, T. K. H. (2021). Understanding massively multiplayer online role-playing game addiction: A hedonic management perspective.Information Systems Journal,31(1), 33–61.https://doi.org/10.1111/isj.12292
Sibilla, F., Musetti, A., & Mancini, T. (2021). Harmonious and obsessive involvement, self-esteem, and well-being. A longitudinal study on MMORPG players.Cyberpsychology: Journal of Psychosocial Research Cyberspace.https://doi.org/10.5817/CP2021-3-1
Cole, D. A., Nick, E. A., & Pulliam, K. A. (2020). Are massively multiplayer online role-playing games healthy or not and why? preliminary support for a compensatory social Interaction model.Computers in Human Behavior,102, 57–66.https://doi.org/10.1016/j.chb.2019.08.012
Mancini, T., Imperato, C., & Sibilla, F. (2019). Does avatar’s character and emotional bond expose to gaming addiction? Two studies on virtual self-discrepancy, avatar identification and gaming addiction in massively multiplayer online role-playing game players.Computers in Human Behavior,92, 297–305.https://doi.org/10.1016/j.chb.2018.11.007
Lu, L., Shen, C., & Williams, D. (2014). Friending your way up the ladder: Connecting massive multiplayer online game behaviors with offline leadership.Computers in Human Behavior,35, 54–60.https://doi.org/10.1016/j.chb.2014.02.013
Bacchini, D., De Angelis, G., & Fanara, A. (2017). Identity formation in adolescent and emerging adult regular players of massively multiplayer online role-playing games (MMORPG).Computers in Human Behavior,73, 191–199.https://doi.org/10.1016/j.chb.2017.03.045
Beard, C. L., & Wickham, R. E. (2016). Gaming-contingent self-worth, gaming motivation, and Internet Gaming Disorder.Computers in Human Behavior,61, 507–515.https://doi.org/10.1016/j.chb.2016.03.046
Entwistle, G. J. M., Blaszczynski, A., & Gainsbury, S. M. (2020). Are video games intrinsically addictive? An international online survey.Computers in Human Behavior,112, 106464.https://doi.org/10.1016/j.chb.2020.106464
Kardefelt-Winther, D. (2014). The moderating role of psychosocial well-being on the relationship between escapism and excessive online gaming.Computers in Human Behavior,38, 68–74.https://doi.org/10.1016/j.chb.2014.05.020
Liu, M., & Peng, W. (2009). Cognitive and psychological predictors of the negative outcomes associated with playing MMOGs (massively multiplayer online games).Computers in Human Behavior,25(6), 1306–1311.https://doi.org/10.1016/j.chb.2009.06.002
Schimmenti, A., Infanti, A., Badoud, D., Laloyaux, J., & Billieux, J. (2017). Schizotypal personality traits and problematic use of massively-multiplayer online role-playing games (MMORPGs).Computers in Human Behavior,74, 286–293.https://doi.org/10.1016/j.chb.2017.04.048
Sioni, S. R., Burleson, M. H., & Bekerian, D. A. (2017). Internet gaming disorder: Social phobia and identifying with your virtual self.Computers in Human Behavior,71, 11–15.https://doi.org/10.1016/j.chb.2017.01.044
Stetina, B. U., Kothgassner, O. D., Lehenbauer, M., & Kryspin-Exner, I. (2011). Beyond the fascination of online-games: Probing addictive behavior and depression in the world of online-gaming.Computers in Human Behavior,27(1), 473–479.https://doi.org/10.1016/j.chb.2010.09.015
Wang, H.-Y., & Cheng, C. (2022). The associations between gaming motivation and internet gaming disorder: Systematic review and meta-analysis.JMIR Mental Health,9(2), e23700.https://doi.org/10.2196/23700
Castillo, R. P. (2019). Exploring the differential effects of social and individualistic gameplay motivations on bridging social capital for users of a massively multiplayer online game.Computers in Human Behavior,91, 263–270.https://doi.org/10.1016/j.chb.2018.10.016
Worth, N. C., & Book, A. S. (2014). Personality and behavior in a massively multiplayer online role-playing game.Computers in Human Behavior,38, 322–330.https://doi.org/10.1016/j.chb.2014.06.009
Gariépy, G., Honkaniemi, H., & Quesnel-Vallée, A. (2016). Social support and protection from depression: Systematic review of current findings in Western countries.British Journal of Psychiatry,209(4), 284–293.https://doi.org/10.1192/bjp.bp.115.169094
Yokotani, K., & Takano, M. (2022). Predicting cyber offenders and victims and their offense and damage time from routine chat times and online social network activities.Computers in Human Behavior,128, 107099.https://doi.org/10.1016/j.chb.2021.107099
Frank, E. (2007). Interpersonal and social rhythm therapy: A means of improving depression and preventing relapse in bipolar disorder.Journal of Clinical Psychology,63(5), 463–473.https://doi.org/10.1002/jclp.20371
Haynes, P. L., Gengler, D., & Kelly, M. (2016). Social rhythm therapies for mood disorders: An update.Current Psychiatry Reports,18(8), 75.https://doi.org/10.1007/s11920-016-0712-3
Frank, E., et al. (2008). The role of interpersonal and social rhythm therapy in improving occupational functioning in patients with bipolar I disorder.American Journal of Psychiatry,165(12), 1559–1565.https://doi.org/10.1176/appi.ajp.2008.07121953
Crowe, M., et al. (2020). Interpersonal and social rhythm therapy for patients with major depressive disorder.American Journal of Psychotherapy,73(1), 29–34.https://doi.org/10.1176/appi.psychotherapy.20190024
Steardo, L., et al. (2020). Efficacy of the interpersonal and social rhythm therapy (IPSRT) in patients with bipolar disorder: Results from a real-world, controlled trial.Annals of General Psychiatry,19(1), 15.https://doi.org/10.1186/s12991-020-00266-7
Lam, C., & Chung, M.-H. (2021). A meta-analysis of the effect of interpersonal and social rhythm therapy on symptom and functioning improvement in patients with bipolar disorders.Applied Research in Quality of Life,16(1), 153–165.https://doi.org/10.1007/s11482-019-09740-1
Gold, A. K., & Kinrys, G. (2019). Treating circadian rhythm disruption in bipolar disorder.Current Psychiatry Reports,21(3), 14.https://doi.org/10.1007/s11920-019-1001-8
Walker, W. H., Walton, J. C., DeVries, A. C., & Nelson, R. J. (2020). Circadian rhythm disruption and mental health.Translational Psychiatry,10(1), 1–13.https://doi.org/10.1038/s41398-020-0694-0
Tao, L., et al. (2020). Light therapy in non-seasonal depression: An update meta-analysis.Psychiatry Research,291, 113247.https://doi.org/10.1016/j.psychres.2020.113247
Crowe, M., et al. (2021). Patients’ perceptions of functional improvement in psychotherapy for mood disorders.American Journal of Psychotherapy,74(1), 22–29.https://doi.org/10.1176/appi.psychotherapy.202020200017
Martin, D. J., Garske, J. P., & Davis, M. K. (2000). Relation of the therapeutic alliance with outcome and other variables: A meta-analytic review.Journal of Consulting and Clinical Psychology,68(3), 438–450.https://doi.org/10.1037/0022-006X.68.3.438
Inder, M. L., et al. (2015). Randomized, controlled trial of interpersonal and social rhythm therapy for young people with bipolar disorder.Bipolar Disorders,17(2), 128–138.https://doi.org/10.1111/bdi.12273
Slatcher, R. B., Selcuk, E., & Ong, A. D. (2015). Perceived partner responsiveness predicts diurnal cortisol profiles 10 years later.Psychological Science,26(7), 972–982.https://doi.org/10.1177/0956797615575022
Stanton, S. C. E., Selcuk, E., Farrell, A. K., Slatcher, R. B., & Ong, A. D. (2019). Perceived partner responsiveness, daily negative affect reactivity, and all-cause mortality: A 20-year longitudinal study.Psychosomatic Medicine,81(1), 7–15.https://doi.org/10.1097/PSY.0000000000000618
Dias, L. P. S., Barbosa, J. L. V., & Vianna, H. D. (2018). Gamification and serious games in depression care: A systematic mapping study.Telemat. Inform.,35(1), 213–224.https://doi.org/10.1016/j.tele.2017.11.002
Ferrari, M., et al. (2022). Gaming my way to recovery: A systematic scoping review of digital game interventions for young people’s mental health treatment and promotion.Frontiers in Digital Health.https://doi.org/10.3389/fdgth.2022.814248
Kowal, M., Conroy, E., Ramsbottom, N., Smithies, T., Toth, A., & Campbell, M. (2021). Gaming your mental health: A narrative review on mitigating symptoms of depression and anxiety using commercial video games.JMIR Serious Games,9(2), e26575.https://doi.org/10.2196/26575
David, O. A., Predatu, R., & Cardoș, R. A. I. (2021). Effectiveness of the REThink therapeutic online video game in promoting mental health in children and adolescents.Internet Interventions,25, 100391.https://doi.org/10.1016/j.invent.2021.100391
Li, J., Theng, Y.-L., & Foo, S. (2014). Game-based digital interventions for depression therapy: A systematic review and meta-analysis.Cyberpsychology, Behavior and Social Network.,17(8), 519–527.https://doi.org/10.1089/cyber.2013.0481
Huberty, J., et al. (2021). A mindfulness meditation mobile app improves depression and anxiety in adults with sleep disturbance: Analysis from a randomized controlled trial.General Hospital Psychiatry,73, 30–37.https://doi.org/10.1016/j.genhosppsych.2021.09.004
Domhardt, M., et al. (2021). Mediators and mechanisms of change in internet- and mobile-based interventions for depression: A systematic review.Clinical Psychology Review,83, 101953.https://doi.org/10.1016/j.cpr.2020.101953
Rice, S. M., et al. (2014). Online and social networking interventions for the treatment of depression in young people: A systematic review.Journal of Medical Internet Research,16(9), e3304.https://doi.org/10.2196/jmir.3304
Wilkinson, N., Ang, R. P., & Goh, D. H. (2008). Online video game therapy for mental health concerns: A review.International Journal of Social Psychiatry,54(4), 370–382.https://doi.org/10.1177/0020764008091659
Ahmed, A., et al. (2021). A review of mobile chatbot apps for anxiety and depression and their self-care features.Computer Methods and Programs in Biomedicine Update,1, 100012.https://doi.org/10.1016/j.cmpbup.2021.100012
Nicholas, J., Larsen, M. E., Proudfoot, J., & Christensen, H. (2015). Mobile apps for bipolar disorder: A systematic review of features and content quality.Journal of Medical Internet Research,17(8), e4581.https://doi.org/10.2196/jmir.4581
Anmella, G., et al. (2022). Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force.Bipolar Disorders,24(6), 580–614.https://doi.org/10.1111/bdi.13243
Patoz, M.-C., et al. (2021). Patients’ adherence to smartphone apps in the management of bipolar disorder: A systematic review.International Journal of Bipolar Disorders,9(1), 19.https://doi.org/10.1186/s40345-021-00224-6
Dunster, G. P., Swendsen, J., & Merikangas, K. R. (2021). Real-time mobile monitoring of bipolar disorder: A review of evidence and future directions.Neuropsychopharmacology,46(1), 197–208.https://doi.org/10.1038/s41386-020-00830-5
Yokotani, K., & Takano, M. (2022). Avatars’ social rhythms in online games indicate their players’ depression.Cyberpsychology, Behavior and Social Networking.,25(11), 718–732.https://doi.org/10.1089/cyber.2022.0058
Zhang, F., & Kaufman, D. (2017). Massively multiplayer online role-playing games (MMORPGs) and socio-emotional wellbeing.Computers in Human Behavior,73, 451–458.https://doi.org/10.1016/j.chb.2017.04.008
McCloud, T., Jones, R., Lewis, G., Bell, V., & Tsakanikos, E. (2020). Effectiveness of a mobile app intervention for anxiety and depression symptoms in university students: Randomized controlled trial.JMIR mHealth and uHealth,8(7), e15418.https://doi.org/10.2196/15418
Birney, A. J., Gunn, R., Russell, J. K., & Ary, D. V. (2016). MoodHacker mobile web app with email for adults to self-manage mild-to-moderate depression: Randomized controlled trial.JMIR mHealth and uHealth,4(1), e4231.https://doi.org/10.2196/mhealth.4231
Takano, M. (2023). Synchronization of online social rhythms via avatar communications.Journal of Physics: Complexity.,4(1), 015010.https://doi.org/10.1088/2632-072X/acbd7d
Yokotani, K., & Takano, M. (2021). Differences in victim experiences by gender/sexual minority statuses in Japanese virtual communities.Journal of Community Psychology,49(6), 1598–1616.https://doi.org/10.1002/jcop.22528
K. Yokotani, M. Takano, and N. Abe, Effects of social rhythm therapy on mood symptoms on a massive multiplayer online game: A double-blind, randomized controlled trial, Jul. 2022.https://doi.org/10.17605/OSF.IO/TCU9H.
Patino, C. M., & Ferreira, J. C. (2018). Inclusion and exclusion criteria in research studies: Definitions and why they matter.Jornal Brasileiro de Pneumologia,44(2), 84.https://doi.org/10.1590/S1806-37562018000000088
Kernan, W. N., Viscoli, C. M., Makuch, R. W., Brass, L. M., & Horwitz, R. I. (1999). Stratified randomization for clinical trials.Journal of Clinical Epidemiology,52(1), 19–26.https://doi.org/10.1016/S0895-4356(98)00138-3
Matsumoto, M., & Nishimura, T. (1998). Mersenne twister: A 623-dimensionally equidistributed uniform pseudo-random number generator.ACM Transactions on Modeling and Computer Simulation,8(1), 3–30.https://doi.org/10.1145/272991.272995
Rush, A. J., et al. (2003). The 16-Item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): A psychometric evaluation in patients with chronic major depression.Biological Psychiatry,54(5), 573–583.https://doi.org/10.1016/S0006-3223(02)01866-8
Fujisawa, D., Nakagawa, A., Tajima, M., Sado, M., Kikuchi, T., & Ono, Y. (2010). Development of the Japanese version of quick inventory of depressive symptomatology self-reported (QIDS-SR16-J).Stress Science,25, 43–52.
Reilly, T. J., MacGillivray, S. A., Reid, I. C., & Cameron, I. M. (2015). Psychometric properties of the 16-item quick inventory of depressive symptomatology: A systematic review and meta-analysis.Journal of Psychiatric Research,60, 132–140.https://doi.org/10.1016/j.jpsychires.2014.09.008
Hirschfeld, R. M. A., et al. (2000). Development and validation of a screening instrument for bipolar spectrum disorder: The mood disorder questionnaire.American Journal of Psychiatry,157(11), 1873–1875.https://doi.org/10.1176/appi.ajp.157.11.1873
Tanaka T., Inoue T., Suzuki katsuharu, Masui T., and Koyama T., Unipolar depression? Bipolar depression? a study of the usefulness of a self-administered rating scale(In Japanese),Bipolar Disorders, vol. 5, pp. 21–27, 2007.https://jglobal.jst.go.jp/detail?JGLOBAL_ID=200902233253603662. Retrieved 23 Jan 2023
Nagata, T., Yamada, H., Teo, A. R., Yoshimura, C., Kodama, Y., & van Vliet, I. (2013). Using the mood disorder questionnaire and bipolar spectrum diagnostic scale to detect bipolar disorder and borderline personality disorder among eating disorder patients.BMC Psychiatry,13(1), 69.https://doi.org/10.1186/1471-244X-13-69
Yokotani, K. (2022). Spread of gambling abstinence through peers and comments in online self-help chat forums to quit gambling.Scientific Reports.https://doi.org/10.1038/s41598-022-07714-2
Margraf, J., Lavallee, K., Zhang, X., & Schneider, S. (2016). Social rhythm and mental health: A cross-cultural comparison.PLoS ONE,11(3), e0150312.https://doi.org/10.1371/journal.pone.0150312
D. Cai, M. Zhu, M. Lin, X. C. Zhang, and J. Margraf, The bidirectional relationship between positive mental health and social rhythm in college students: A three-year longitudinal study,Frontiers in Psychology., vol. 8, 2017. https://www.frontiersin.org/articles/https://doi.org/10.3389/fpsyg.2017.01119. Retrieved 23 Jan 2023
Cohen, J. (1988).Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Routledge.
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses.Behavior Research Methods,41(4), 1149–1160.https://doi.org/10.3758/BRM.41.4.1149
J. Cohen,A power primer. in Methodological issues and strategies in clinical research, 4th ed. Washington, DC, US: American Psychological Association, 2016, p. 284.https://doi.org/10.1037/14805-018.
Ito, M., et al. (2022). Efficacy of the unified protocol for transdiagnostic cognitive-behavioral treatment for depressive and anxiety disorders: a randomized controlled trial.Psychological Medicine.https://doi.org/10.1017/S0033291721005067
K. Yokotani, M. Takano, and N. Abe, Abnormal behavior of following peers in an online game indicates bipolar disorder and manic/hypomanic episodes, inProceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, in ASONAM ’23. New York, NY, USA: Association for Computing Machinery, Mar. 2024, pp. 464–469.https://doi.org/10.1145/3625007.3627319.
Hoffman, M. D., & Gelman, A. (2014). The No-U-Turn sampler: Adaptively setting path lengths in Hamiltonian Monte Carlo.Journal of Machine Learning Research,15(1), 1593–1623.
Kaye, L. K., Kowert, R., & Quinn, S. (2017). The role of social identity and online social capital on psychosocial outcomes in MMO players.Computers in Human Behavior,74, 215–223.https://doi.org/10.1016/j.chb.2017.04.030
Martončik, M., & Lokša, J. (2016). Do World of Warcraft (MMORPG) players experience less loneliness and social anxiety in online world (virtual environment) than in real world (offline)?Computers in Human Behavior,56, 127–134.https://doi.org/10.1016/j.chb.2015.11.035
L. Raithet al., Massively multiplayer online games and well-being: A Systematic Literature Review,Frontiers in Psychology., vol. 12, 2021. https://www.frontiersin.org/articles/https://doi.org/10.3389/fpsyg.2021.698799. Retrieved 12 Jan 2023
Billieux, J., et al. (2013). Why do you play World of Warcraft? An in-depth exploration of self-reported motivations to play online and in-game behaviours in the virtual world of Azeroth.Computers in Human Behavior,29(1), 103–109.https://doi.org/10.1016/j.chb.2012.07.021
Yokotani, K., & Takano, M. (2021). Social contagion of cyberbullying via online perpetrator and victim networks.Computers in Human Behavior.https://doi.org/10.1016/j.chb.2021.106719
Linardon, J., & Fuller-Tyszkiewicz, M. (2020). Attrition and adherence in smartphone-delivered interventions for mental health problems: A systematic and meta-analytic review.Journal of Consulting and Clinical Psychology,88, 1–13.https://doi.org/10.1037/ccp0000459
Galimard, J.-E., Chevret, S., Protopopescu, C., & Resche-Rigon, M. (2016). A multiple imputation approach for MNAR mechanisms compatible with Heckman’s model.Statistics in Medicine,35(17), 2907–2920.https://doi.org/10.1002/sim.6902
Fielding, S., Fayers, P. M., McDonald, A., McPherson, G., Campbell, M. K., the RECORD study group. (2008). Simple imputation methods were inadequate for missing not at random (MNAR) quality of life data.Health and Quality of Life Outcomes,6(1), 57.https://doi.org/10.1186/1477-7525-6-57
D. P. Kingma and M. Welling, Auto-encoding variational Bayes. 2022.https://doi.org/10.48550/arXiv.1312.6114.
K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition. 2015.https://doi.org/10.48550/arXiv.1409.1556.
Acknowledgements
We thank Dr. Tai Kurosawa of Ibaraki Christian University for his help in back-translating the Brief Social Rhythm Scale. Part of this study was orally presented in Japanese at the 85th National Conference of the Information Processing Society of Japan, 2023.
Funding
Kenji Yokotani was funded by a grant from CyberAgent, Inc. (Grant number: akblab-0005).
Author information
Authors and Affiliations
Graduate School of Technology, Industrial and Social Sciences, Tokushima University, 1-1, Minamijosanjimacho, Tokushima-Shi, Tokushima, 770-0814, Japan
Kenji Yokotani
Multidisciplinary Information Science Center, CyberAgent, Inc., Tokyo, Japan
Masanori Takano
Institute for the Future of Human Society, Kyoto University, Kyoto, Japan
Nobuhito Abe
- Kenji Yokotani
You can also search for this author inPubMed Google Scholar
- Masanori Takano
You can also search for this author inPubMed Google Scholar
- Nobuhito Abe
You can also search for this author inPubMed Google Scholar
Contributions
Kenji Yokotani: Conceptualization, interpretation, writing of the original draft, writing of the review, data collection, data review, and data analysis. Masanori Takano: conceptualization, investigation, interpretation, data collection, and data review. Nobuhito Abe Conceptualization, interpretation, and data review. All authors have read and agreed to the published version of the manuscript.
Corresponding author
Correspondence toKenji Yokotani.
Ethics declarations
Conflict of interest
Kenji Yokotani was funded by CyberAgent, Inc. Masanori Takano was an employee of CyberAgent, Inc. Nobuhito Abe does not have any conflicts of interest with respect to this study.
Ethical consideration
This study was approved by the Ethics Committee of the Graduate School of Technology, Industrial, and Social Sciences, Tokushima University, on March 22, 2022 (registration number 262). Informed consent was obtained from all participants. All procedures were conducted in accordance with the 1964 Declaration of Helsinki and its later amendments, or comparable ethical standards.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Yokotani, K., Takano, M. & Abe, N. Can likes returned by peers within a day improve users’ depressive/manic levels in a massive multiplayer online game? A randomized controlled trial.J Comput Soc Sc7, 2333–2357 (2024). https://doi.org/10.1007/s42001-024-00312-4
Received:
Accepted:
Published:
Issue Date:
Share this article
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative