Lateral orbitofrontal gray matter abnormalities in subjects with problematic smartphone use
Open accessAbstract
Background and aims: Smartphone use is becoming commonplace and exerting adequate control over smartphone use has become an important mental health issue. Little is known about the neurobiology underlying problematic smartphone use. We hypothesized that structural abnormalities in the fronto-cingulate brain region could be implicated in problematic smartphone use, similar to that has been reported for Internet gaming disorder and Internet addiction. This study investigated fronto-cingulate gray matter abnormalities in problematic smartphone users, particularly those who spend time on social networking platforms. Methods: The study included 39 problematic smartphone users with excessive use of social networking platforms via smartphone and 49 normal control male and female smartphone users. We conducted voxel-based morphometric analysis with diffeomorphic anatomical registration using an exponentiated Lie algebra algorithm. Region of interest analysis was performed on the fronto-cingulate region to identify whether gray matter volume (GMV) differed between the two groups. Results: Problematic smartphone users had significantly smaller GMV in the right lateral orbitofrontal cortex (OFC) than healthy controls, and there were significant negative correlations between GMV in the right lateral OFC and the Smartphone Addiction Proneness Scale (SAPS) score, including the SAPS tolerance subscale. Conclusions: These results suggest that lateral orbitofrontal gray matter abnormalities are implicated in problematic smartphone use, especially in social networking platform overuse. Small GMV in the lateral OFC was correlated with an increasing tendency to be immersed in smartphone use. Our results suggest that orbitofrontal gray matter abnormalities affect regulatory control over previously reinforced behaviors and may underlie problematic smartphone use.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Excessive smartphone use is associated with changes in the brain's gray matter volume.
“Medical problems include sleep problems, reduced physical fitness, unhealthy eating habits, pain and migraines, reduced cognitive control and changes in the brain's gray matter volume.”
From Excessive Smartphone Use Is Associated With Health Problems in Adolescents and Young Adults (2021) · cites this paper as [84]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
An inventory for measuring clinical anxiety: Psychometric properties.
Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.56.6.893 · Cited by 14,407 · see citing works
SAUNDERS, J. B., AASLAND, O. G., BABOR, T. F., DE LA FUENTE, J. R., & GRANT, M. (1993) · Addiction · doi:10.1111/j.1360-0443.1993.tb02093.x · Cited by 13,482 · see citing works
A fast diffeomorphic image registration algorithm
Ashburner, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.007 · Cited by 8,122 · cited 1× · see citing works
“We used diffeomorphic anatomical registration with an exponentiated Lie algebra algorithm (DARTEL) to increase the accuracy of intersubject alignment by modeling the shape of each brain using a host of parameters (Ashburner, 2007).”
MethodBeck, A. T., Steer, R. A., & Brown, G. (2011) · PsycTESTS Dataset · doi:10.1037/t00742-000 · Cited by 7,535 · see citing works
Maldjian, J., Laurienti, P., Kraft, R., & Burdette, J. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00169-1 · Cited by 5,453 · see citing works
Separate neural systems value immediate and delayed monetary rewards
McClure, S. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2004) · Science · doi:10.1126/science.1100907 · Cited by 3,089 · see citing works
Wechsler Adult Intelligence Scale--Fourth Edition
Wechsler, D. (2012) · PsycTESTS Dataset · doi:10.1037/t15169-000 · Cited by 2,232 · see citing works
Brand, M., Young, K. S., Laier, C., Wölfling, K., & Potenza, M. N. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.08.033 · Cited by 2,153 · see citing works
Assessing the significance of focal activations using their spatial extent
Friston, K. J., Worsley, K. J., Frackowiak, R. S. J., Mazziotta, J. C., & Evans, A. C. (1994) · Human Brain Mapping · doi:10.1002/hbm.460010306 · Cited by 1,907 · see citing works
Elhai, J. D., Dvorak, R. D., Levine, J. C., & Hall, B. J. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.08.030 · Cited by 1,689 · see citing works
Prefrontal executive and cognitive functions in rodents: neural and neurochemical substrates
Dalley, J. W., Cardinal, R. N., & Robbins, T. W. (2004) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2004.09.006 · Cited by 1,329 · see citing works
Addiction, a disease of compulsion and drive: involvement of the orbitofrontal cortex
Volkow, N. D. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.3.318 · Cited by 1,240 · see citing works
Orbitofrontal cortex and its contribution to decision-making.
Wallis, J. D. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.30.051606.094334 · Cited by 938 · cited 1× · see citing works
“The OFC has been associated with reward-guided decision-making (Wallis, 2007).”
BackgroundBechara, A., & Damasio, H. (2002) · Neuropsychologia · doi:10.1016/s0028-3932(02)00015-5 · Cited by 889 · see citing works
The neuropsychological basis of addictive behaviour
Everitt, B. J., Dickinson, A., & Robbins, T. W. (2001) · Brain Research Reviews · doi:10.1016/s0165-0173(01)00088-1 · Cited by 808 · see citing works
Social networking on smartphones: When mobile phones become addictive
Salehan, M., & Negahban, A. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.07.003 · Cited by 700 · see citing works
The benefits and dangers of enjoyment with social networking websites
Turel, O., & Serenko, A. (2012) · European Journal of Information Systems · doi:10.1057/ejis.2012.1 · Cited by 684 · see citing works
O'Doherty, J., Critchley, H., Deichmann, R., & Dolan, R. J. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-21-07931.2003 · Cited by 611 · see citing works
Yuan, P., & Raz, N. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.02.005 · Cited by 608 · cited 1× · see citing works
“These fronto-cingulate areas are associated with exerting executive control (Yuan & Raz, 2014), which is the ability to use higher-order cognitive functions appropriately to perform goal-directed behaviors (Miller & Wallis, 2009).”
BackgroundDecision-making and addiction (part II): myopia for the future or hypersensitivity to reward?
Bechara, A., Dolan, S., & Hindes, A. (2002) · Neuropsychologia · doi:10.1016/s0028-3932(02)00016-7 · Cited by 580 · see citing works
Dong, G., & Potenza, M. N. (2014) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2014.07.005 · Cited by 559 · see citing works
Wolniewicz, C. A., Tiamiyu, M. F., Weeks, J. W., & Elhai, J. D. (2018) · Psychiatry Research · doi:10.1016/j.psychres.2017.09.058 · Cited by 539 · see citing works
A fronto–striato–subthalamic–pallidal network for goal-directed and habitual inhibition
Jahanshahi, M., Obeso, I., Rothwell, J. C., & Obeso, J. A. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn4038 · Cited by 521 · see citing works
Orbitofrontal cortex, decision-making and drug addiction
Schoenbaum, G., Roesch, M. R., & Stalnaker, T. A. (2006) · Trends in Neurosciences · doi:10.1016/j.tins.2005.12.006 · Cited by 499 · see citing works
Development of Korean Smartphone Addiction Proneness Scale for Youth
Kim, D., Lee, Y., Lee, J., Nam, J. K., & Chung, Y. (2014) · PLoS ONE · doi:10.1371/journal.pone.0097920 · Cited by 434 · cited 1× · see citing works
“The SAPS test was developed by the Korean National Information Society Agency to evaluate problematic smartphone use (Kim et al., 2014).”
MethodSelf-citationBehavioural addiction: an issue for everybody?
Griffiths, M. (1996) · Employee Counselling Today · doi:10.1108/13665629610116872 · Cited by 392 · cited 1× · see citing works
“In behavioral addiction, tolerance is defined as the increasing amount of time required for participation in particular activities to achieve the same levels of satisfaction (Griffiths, 1996).”
BackgroundLong, J., Liu, T.-Q., Liao, Y.-H., Qi, C., He, H.-Y., Chen, S.-B., & Billieux, J. (2016) · BMC Psychiatry · doi:10.1186/s12888-016-1083-3 · Cited by 384 · cited 1× · see citing works
“Many people display “problematic smartphone user” behaviors and fail to regulate their excessive smartphone use, despite negative psychosocial consequences (Long et al., 2016; Lopez-Fernandez, Honrubia-Serrano, Freixa-Blanxart, & Gibson, 2014).”
BackgroundPrevalence of problematic mobile phone use in British adolescents.
Lopez-Fernandez, O., Honrubia-Serrano, L., Freixa-Blanxart, M., & Gibson, W. (2014) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2012.0260 · Cited by 371 · see citing works
Yao, Y.-W., Liu, L., Ma, S.-S., Shi, X.-H., Zhou, N., Zhang, J.-T., & Potenza, M. N. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.10.029 · Cited by 242 · see citing works
Depression and social anxiety in relation to problematic smartphone use
Elhai, J. D., Tiamiyu, M. F., & Weeks, J. W. (2018) · Internet Research · doi:10.1108/intr-01-2017-0019 · Cited by 220 · cited 1× · see citing works
“Some studies focused on the role of psychological factors, such as empathy, life satisfaction (Lachmann et al., 2018), and fear of missing out (Wolniewicz, Tiamiyu, Weeks, & Elhai, 2018).”
BackgroundSha, P., Sariyska, R., Riedl, R., Lachmann, B., & Montag, C. (2018) · Addictive Behaviors Reports · doi:10.1016/j.abrep.2018.100148 · Cited by 207 · see citing works
The Role of Empathy and Life Satisfaction in Internet and Smartphone Use Disorder
Lachmann, B., Sindermann, C., Sariyska, R., Luo, R., Melchers, M., Becker, B., Cooper, A., & Montag, C. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.00398 · Cited by 185 · see citing works
Impulsivity, compulsivity, and habit: the role of orbitofrontal cortex revisited.
Torregrossa, M., Quinn, J., & Taylor, J. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2007.11.014 · Cited by 163 · see citing works
Gray matter and white matter abnormalities in online game addiction
Weng, C.-B., Qian, R.-B., Fu, X.-M., Lin, B., Han, X.-P., Niu, C.-S., & Wang, Y.-H. (2013) · European Journal of Radiology · doi:10.1016/j.ejrad.2013.01.031 · Cited by 158 · see citing works
ΔFosB Induction in Orbitofrontal Cortex Mediates Tolerance to Cocaine-Induced Cognitive Dysfunction
Winstanley, C., LaPlant, Q., Theobald, D., Green, T., Bachtell, R., Perrotti, L., DiLeone, R., Russo, S., Garth, W. J., Self, D., et al. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.2566-07.2007 · Cited by 149 · cited 1× · see citing works
“…studies on substance addiction showed that disruption of the lateral OFC is associated with enhanced tolerance to the deleterious effects of substance use (Nimitvilai, Lopez, Mulholland, & Woodward, 2016; 408 | Journal of Behavioral Addictions 8(3), pp. 404–411 (2019) Winstanley et al., 2007).”
BackgroundChen, J., Liang, Y.-S., Mai, C., Zhong, X., & Qu, C. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.00511 · Cited by 139 · cited 1× · see citing works
“This hypothesis is consistent with neurophysiological evidence suggesting that dysfunctional executive control, such as attention and inhibitory control, is related to problematic smartphone use (Chen et al., 2016; Hadar et al., 2017).”
ResultReduced orbitofrontal cortical thickness in male adolescents with internet addiction
Hong, S.-B., Kim, J.-W., Choi, E.-J., Kim, H.-H., Suh, J.-E., Kim, C.-D., Klauser, P., Whittle, S., Yűcel, M., Pantelis, C., et al. (2013) · Behavioral and Brain Functions · doi:10.1186/1744-9081-9-11 · Cited by 136 · see citing works
Are we addicted to our cell phones?
Sapacz, M., Rockman, G., & Clark, J. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.12.004 · Cited by 116 · see citing works
Nimitvilai, S., Lopez, M. F., Mulholland, P., & Woodward, J. (2016) · Neuropsychopharmacology · doi:10.1038/npp.2015.250 · Cited by 106 · see citing works
Hadar, A., Hadas, I., Lazarovits, A., Alyagon, U., Eliraz, D., & Zangen, A. (2017) · PLOS ONE · doi:10.1371/journal.pone.0180094 · Cited by 100 · cited 1× · see citing works
“This hypothesis is consistent with neurophysiological evidence suggesting that dysfunctional executive control, such as attention and inhibitory control, is related to problematic smartphone use (Chen et al., 2016; Hadar et al., 2017).”
ResultMontag, C., Zhao, Z.-Y., Sindermann, C., Xu, L., Fu, M.-N., Li, J., Zheng, X.-X., Li, K.-S., Kendrick, K., Dai, J., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-19904-y · Cited by 98 · cited 2× · see citing works
“Smartphone users who had higher tendencies toward addiction to Internet communication applications also had smaller GMVs in the subgenual anterior cingulate cortex (Montag et al., 2018).”
BackgroundResultMüller, J., Dreisbach, G., Goschke, T., Hensch, T., Lesch, K., & Brocke, B. (2007) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2007.05949.x · Cited by 94 · cited 1× · see citing works
“Habitual behaviors require less executive control than goal-directed actions (Dalley, Cardinal, & Robbins, 2004; Müller et al., 2007).”
BackgroundDevelopment of Smartphone Addiction Proneness Scale for Adults: Self-report
Kim, D.-I., Yeoju, Lee, J., Kim, M.-C., Lee, Y., 강, 은., Keum, C.-D., & Nam, J. (2012) · Korea Journal of Counseling · doi:10.15703/kjc.13.2.201204.629 · Cited by 87 · cited 2× · see citing works
“Participants were screened for excessive smartphone use with the Korean Smartphone Addiction Proneness Scale (SAPS; Kim et al., 2012; Kim, Lee, Lee, Nam, & Chung, 2014).”
MethodSelf-citationTurel, O., He, Q., Brevers, D., & Bechara, A. (2018) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-018-0597-1 · Cited by 84 · see citing works
Wang, Y., Zou, Z., Song, H., Xu, X., Wang, H., Uquillas, F. D., & Huang, X. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.00597 · Cited by 73 · see citing works
Abnormal gray matter volume and impulsivity in young adults with Internet gaming disorder
Lee, D., Namkoong, K., Lee, J., & Jung, Y.-C. (2018) · Addiction Biology · doi:10.1111/adb.12552 · Cited by 73 · see citing works
Self-citationRole of Frontostriatal Connectivity in Adolescents With Excessive Smartphone Use
Chun, J.-W., Choi, J.-Y., Cho, H., Choi, M.-R., Ahn, K., Choi, J.-S., & Kim, D. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00437 · Cited by 65 · see citing works
Zhou, F., Montag, C., Sariyska, R., Lachmann, B., Reuter, M., Weber, B., Trautner, P., Kendrick, K., Markett, S., & Becker, B. (2019) · Addiction Biology · doi:10.1111/adb.12570 · Cited by 60 · see citing works
Wegmann, E., Stodt, B., & Brand, M. (2018) · Addiction Research & Theory · doi:10.1080/16066359.2017.1367385 · Cited by 36 · see citing works
Facebook addiction and impulsive decision-making
Delaney, D., Stein, L. A. R., & Gruber, R. (2018) · Addiction Research & Theory · doi:10.1080/16066359.2017.1406482 · Cited by 29 · see citing works
Structural Brain Imaging and Internet Addiction
Lin, F., & Lei, H. (2015) · Studies in neuroscience, psychology and behavioral economics · doi:10.1007/978-3-319-07242-5_2 · Cited by 7 · see citing works
Factor structure of the Barratt impulsiveness scale
Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995) · Journal of Clinical Psychology · doi:10.1002/1097-4679(199511)51:6
Flagged first, then by citations
6 of the 58 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Miller E. Wallis J. (2009). Executive function and higher-order cognition: Definition and neural substrates In Squire L. R. (Ed.), Encyclopedia of neuroscience (Vol. 4, pp. 99– 104). Oxford, UK: Academic Press.
- Young K. S. (1998). Caught in the net: How to recognize the signs of Internet addiction–and a winning strategy for recovery. New York, NY: John Wiley & Sons.
Cited by
Sorted by citations
Excessive Smartphone Use Is Associated With Health Problems in Adolescents and Young Adults
Wacks, Y., & Weinstein, A. M. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.669042 · Cited by 424 · see citing works
“Reduced Gray Matter Volume (GMV) was shown in problematic smartphone users and negative correlations between GMV in the right lateral Orbito Frontal Cortex (OFC) and measures of smartphone addiction (84).”
BackgroundSmartphone Addiction and Associated Health Outcomes in Adult Populations: A Systematic Review
Ratan, Z. A., Parrish, A., Zaman, S. B., Alotaibi, M. S., & Hosseinzadeh, H. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182212257 · Cited by 322 · see citing works
“Lee et al. (2019) found that smartphone-addicted participants had significantly smaller grey matter volume (GMV) in the right lateral orbitofrontal cortex (OFC) [23].”
BackgroundInfluentialStructural and functional correlates of smartphone addiction
Horvath, J., Mundinger, C., Schmitgen, M. M., Wolf, N. D., Sambataro, F., Hirjak, D., Kubera, K. M., Koenig, J., & Christian Wolf, R. (2020) · Addictive Behaviors · doi:10.1016/j.addbeh.2020.106334 · Cited by 190 · see citing works
Social media usage and development of psychiatric disorders in childhood and adolescence: a review
Cataldo, I., Lepri, B., Neoh, M. J. Y., & Esposito, G. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.508595 · Cited by 186 · see citing works
“Recent evidence also suggests the involvement of the right lateral orbitofrontal cortex, linking a decreased volume in that area with an excessive usage of social media sites (119).”
BackgroundNeural correlates of cue reactivity in individuals with smartphone addiction.
Schmitgen, M., Horvath, J., Mundinger, C., Wolf, N. D., Sambataro, F., Hirjak, D., Kubera, K., Koenig, J., & Wolf, R. C. (2020) · Addictive Behaviours · doi:10.1016/j.addbeh.2020.106422 · Cited by 73 · see citing works
Elhai, J., Yang, H.-B., Dempsey, A. E., & Montag, C. (2020) · Psychiatry Research · doi:10.1016/j.psychres.2020.112845 · Cited by 69 · see citing works
Gao, L., Zhang, J., Xie, H.-P., Nie, Y.-F., Zhao, Q.-B., & Zhou, Z. (2020) · Addictive Behaviours · doi:10.1016/j.addbeh.2020.106363 · Cited by 65 · see citing works
Role of Frontostriatal Connectivity in Adolescents With Excessive Smartphone Use
Chun, J.-W., Choi, J.-Y., Cho, H., Choi, M.-R., Ahn, K., Choi, J.-S., & Kim, D. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00437 · Cited by 65 · see citing works
Montag, C., & Becker, B. (2023) · Psychoradiology · doi:10.1093/psyrad/kkad001 · Cited by 57 · see citing works
“Accordingly, between-group designs comparing participants with high versus low SmUD often revealed decreased regional brain volumes in the group of excessive smart-phone users compared to control individuals (e.g. Lee et al. , 2019; Yoo et al. , 2021).”
BackgroundSolly, J., Hook, R., Grant, J., Cortese, S., & Chamberlain, S. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01315-7 · Cited by 51 · see citing works
Gao, Y., Hu, Y., Wang, J., Liu, C., Im, H., Jin, W., Zhu, W., Ge, W., Zhao, G., Yao, Q., et al. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121029 · Cited by 43 · see citing works
“…SPA and gray matter volume (GMV) in the middle cingulate cortex, anterior cingulate cortex (ACC), orbitofrontal cortex (OFC) (Horvath et al., 2020; Lee et al., 2019), and DLPFC (Solly et al., 2022), suggesting dysfunctions in reward processing, inhibitory control, and behavioral regulation as key…”
Lee, D., Lee, J., Namkoong, K., & Jung, Y.-C. (2021) · Addictive Behaviors · doi:10.1016/j.addbeh.2021.106823 · Cited by 37 · see citing works
Self-citationImpact of digital addiction on youth health: A systematic review and meta-analysis
Shiferaw, B. D., Tang, J., Wang, Y.-X., Wang, Y.-H., Wang, Y.-H., Mackay, L., Luo, Y.-J., Yan, N., Shen, X.-Y., Zhou, T., et al. (2025) · Journal of Behavioral Addictions · doi:10.1556/2006.2025.00081 · Cited by 36 · see citing works
“Regarding SA (Hirjak et al., 2022; Horvath et al., 2020; D. Lee, Namkoong, Lee, Lee, & Jung, 2019; Schmitgen et al., 2020; Zou et al., 2021; Zou et al., 2022), and (Y. Wang et al., 2016) elucidated the potential structural and functional brain alterations associated with problematic smartphone use…”
Lee, S.-Y., Lee, H., Choi, J.-S., Bang, S.-Y., Park, M.-H., Jung, K., & Kweon, Y. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17134751 · Cited by 33 · see citing works
“A previous structural imaging study demonstrated a significantly lower gray matter volume of the orbitofrontal cortex, an important structure involved in impulse control, in subjects with PSU compared to normal smartphone users [59].”
BackgroundWadsley, M. G., & Ihssen, N. (2023) · Brain Sciences · doi:10.3390/brainsci13050787 · Cited by 34 · see citing works
“[35] used the same sample of smartphone users (n = 88) as a resting-state fMRI study by Lee et al.”
BackgroundMethodInfluentialVideo gaming, but not reliance on GPS, is associated with spatial navigation performance
Yavuz, E., He, C., Goodroe, S., Ganstrom, C., Coutrot, A., Hornberger, M., Hegarty, M., & Spiers, H. (2023) · bioRxiv · doi:10.1101/2023.08.10.552365 · Cited by 30
“This finding is consistent with a range of studies that found greater hours of phone use significantly associated with poorer performance on various cognitive tasks (Chen et al., 2016; Chun et al., 2017, 2018; Hadar et al., 2017; Hovarth et al., 2020; Hutton et al., 2019; Lee et al., 2019; Paik et al., 2019; Paulus et…”
Zou, L.-W., Wu, X.-Y., Tao, S.-M., Yang, Y.-J., Zhang, Q., Hong, X., Xie, Y., Li, T.-T., Zheng, S.-S., & Tao, F. (2021) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsab016 · Cited by 27 · see citing works
“left anterior insula, left inferior temporal cortex and left parahippocampal cortex of the PMPU group than healthy controls (Wang et al., 2016; Lee et al., 2019; Horvath et al., 2020).”
BackgroundLin, H.-M., Chang, Y.-T., Chen, M.-H., Liu, S.-T., Chen, B.-S., Li, L., Lee, C.-Y., Sue, Y.-R., Sung, T.-M., Sun, C.-K., et al. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192316277 · Cited by 26 · see citing works
“Regarding the evaluation of depression, three studies [32, 33, 38] adopted the Beck depression inventory (BDI) [44], which assesses the severity of depression base on the participa t’s responses to 21 items, each of which is scored on a four-point Likert scale of 0, 1, 2, and 3 epresenting no, mild, moderat , and seve…”
BackgroundMethodInfluentialZou, L.-W., Wu, X.-Y., Tao, S.-M., Yang, Y.-J., Zhang, Q., Hong, X., Xie, Y., Li, T.-T., Zheng, S.-S., & Tao, F. (2022) · Journal of Behavioral Addictions · doi:10.1556/2006.2021.00090 · Cited by 26 · see citing works
“Thus, it seems that interference with decision-making results due to abnormalities in the OrG and dysfunction of decision-making have been related to addiction behaviours (Lee et al., 2019).”
BackgroundMusetti, A., Brazzi, F., Folli, M. C., Plazzi, G., & Franceschini, C. (2020) · The Open Psychology Journal · doi:10.2174/1874350102013010242 · Cited by 25 · see citing works
Liu, X.-X. L. (2021) · Journal of Evidence-Based Psychotherapies · doi:10.24193/jebp.2021.2.9 · Cited by 23 · see citing works
Wang, Y., Qin, Y., Li, H., Yao, D., Sun, B., Gong, J.-N., Dai, Y., Wen, C., Zhang, L.-R., Zhang, C., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.665578 · Cited by 22 · see citing works
Wong, S. M., Chen, E. Y., Wong, C. S., Suen, Y., Chan, D. L., Tsang, S. H., Wong, T., Cheung, C., Chan, K., Lui, S. S., et al. (2022) · Psychiatry Research · doi:10.1016/j.psychres.2022.114939 · Cited by 21 · see citing works
Yoo, J., Chun, J.-W., Choi, M.-R., Cho, H., Kim, J.-Y., Choi, J.-Y., & Kim, D. (2021) · Journal of Behavioral Addictions · doi:10.1556/2006.2021.00024 · Cited by 21 · see citing works
Kwon, M., Jung, Y., Lee, D., & Lee, J. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1008557 · Cited by 21 · see citing works
“To consider a number of existing studies – structural magnetic resonance imaging (MRI) studies have demonstrated that problematic smartphone users exhibit smaller gray matter volume in the right orbitofrontal cortex (26).”
BackgroundResultSelf-citationGuo, N., Luk, T., Wang, M., Ho, S., Fong, D., Wan, A., Chan, S., & Lam, T.-H. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.614061 · Cited by 19 · see citing works
“Neuroscience studies supported the notion by identifying the lateral orbitofrontal gray matter abnormalities in young people with PSU and particularly in those spent time on SNS, and the lateral orbitofrontal cortex is important in regulatory control and reward-related decisionmaking (3).”
BackgroundBrain and Smartphone Addiction: A Systematic Review
Anbumalar, C., & Sahayam, D. B. (2024) · Human Behavior and Emerging Technologies · doi:10.1155/2024/5592994 · Cited by 18 · see citing works
“This suggests that problematic smartphone use may be caused by a loss of regulatory control over previously reinforced behaviors [16].”
BackgroundThe Modulation of Reward and Habit Systems by Acupuncture in Adolescents with Internet Addiction
Wang, Y., Qin, Y., Li, H., Yao, D., Sun, B., Li, Z., Li, X., Dai, Y., Wen, C., Zhang, L.-R., et al. (2020) · Journal of Neural Transplantation and Plasticity · doi:10.1155/2020/7409417 · Cited by 18 · see citing works
“As to IA, altered microstructure and function in the cerebellum, OFC, and vmPFC were also observed by previous neuroimaging studies [22, 48, 49].”
ResultUnveiling the grip of mobile phone addiction: an in-depth review
Li, J., & Yang, H. Y. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1429941 · Cited by 15 · see citing works
“People with MPA have less gray matter in this region, which may contribute to their dif fi culty in making choices (49).”
BackgroundXiang, M.-Q., Lin, L., Song, Y.-T., Hu, M., & Hou, X.-H. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1097375 · Cited by 16 · see citing works
“In addition, a smaller gray-matter volume in the orbitofrontal cortex (OFC) was found in individuals with PSPU compared to controls (17).”
Mindfulness mediates relations between anxiety with problematic smartphone use severity
Hallauer, C., Rooney, E. A., Billieux, J., Hall, B. J., & Elhai, J. (2022) · Cyberpsychology: Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2022-1-4 · Cited by 16 · see citing works
“(2021), we use the term “PSU” to capture the predominantly mobile form of PIU and to account for an uncontrolled and excessive use of the smartphone engendering tangible negative consequences, such as interpersonal and school/work impairment (Billieux, 2012; Busch & McCarthy, 2021; Elhai, Levine, et al., 2019; Lee et…”
BackgroundMethodHallauer, C., Rooney, E. A., Yang, H.-B., Meng, Q., Montag, C., & Elhai, J. (2021) · Human Behavior and Emerging Technologies · doi:10.1002/hbe2.319 · Cited by 16 · see citing works
“2021;3:788–797.wileyonlinelibrary.com/journal/hbe2 of the smartphone which leads to tangible negative consequences, such as interpersonal and school/work impairment (Billieux, 2012; Busch & McCarthy, 2020; Elhai, Levine, & Hall, 2019; Lee et al., 2019).”
BackgroundScreens and brains: multimodal neuroimaging insights into mechanisms of problematic smartphone use.
Wolf, N. D., Henemann, G. M., Schmitgen, M., Koenig, J., Bach, P., & Wolf, R. C. (2025) · Progress in Neuro-psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2025.111531 · Cited by 15 · see citing works
Reduced Volume of a Brainstem Substructure in Adolescents with Problematic Smartphone Use
Cho, I., Yoo, J., Chun, J.-W., Cho, H., Kim, J.-Y., Choi, J.-Y., & Kim, D. (2021) · Soa--ch'ongsonyon chongsin uihak = Journal of child & adolescent psychiatry · doi:10.5765/jkacap.210007 · Cited by 14 · see citing works
Zou, L.-W., Wu, X.-Y., Tao, S.-M., Yang, Y.-J., Zhang, Q., Hong, X., Xie, Y., Li, T.-T., Zheng, S.-S., & Tao, F. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2021.749194 · Cited by 10 · see citing works
The impact of childhood trauma on short video addiction: psychological and morphological correlates
Yao, Q., Gao, Y., Liu, C., Li, X., Jin, W., & Wang, Q. (2025) · Scientific Reports · doi:10.1038/s41598-025-04020-5 · Cited by 7 · see citing works
“For example, some studies have reported gray matter atrophy in the right orbitofrontal cortex (OFC), bilateral insula, and right supplementary motor area in individuals with problematic smartphone use 24 .”
Ma, P., Xia, Z.-L., Zhao, Y.-B., & Zhao, Y. (2024) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2024.04.018 · Cited by 7 · see citing works
Alwazzeh, M., Harfouch, M., Hasan, M., Alqatari, S. G., Alsaid, A., & Alwazzeh, M. (2024) · Clinical Practice and Epidemiology in Mental Health · doi:10.2174/0117450179295575240520064919 · Cited by 6 · see citing works
Wan, Z., Qin, X.-C., Wan, Q., Xu, B., Lin, H., Ouyang, F., & Wang, G. (2024) · Journal of Medical Internet Research · doi:10.2196/63485 · Cited by 4 · see citing works
“Furthermore, previous studies have identified abnormal brain activity in young individuals with smartphone addiction, such as a reduction in fronto-limbic resting-state functional connectivity and smaller gray matter volume in the right lateral orbitofrontal cortex [16,17].”
Kobayashi, N., Jitoku, D., Mochimatsu, R., Hamamura, T., Honjo, M., Takagi, S., Sugihara, G., & Takahashi, H. (2024) · Psychiatry and Clinical Neurosciences · doi:10.1002/pcn5.172 · Cited by 4 · see citing works
Liu, X., Liu, H., Kendrick, K. M., Montag, C., & Becker, B. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.13.598945 · Cited by 3 · see citing works
Ünsal, F., & Korkmaz, Z. (2025) · Psikiyatride Guncel Yaklasimlar · doi:10.18863/pgy.1644556 · Cited by 3 · see citing works
Addictive-like Dimensions of Problematic Use of Social Media
Yuste, R., Baler, R., & Volkow, N. D. (2025) · Journal of Addiction Medicine · doi:10.1097/adm.0000000000001525 · Cited by 3 · see citing works
Hu, M., Song, K. S., Choi, J.-Y., Pyeon, A., Cho, H., Choi, J.-S., Choi, I., Chun, J.-W., & Kim, D.-J. (2025) · Life · doi:10.3390/life15121899 · Cited by 2 · see citing works
Qu, B., Chen, J., Tian, Q., Niu, Q., Sun, J., Xie, M., Huang, Y.-E., Xue, B., Tong, X., & Wu, R.-P. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100890 · Cited by 2 · see citing works
Ge, J.-M., & Zhang, A.-B. (2026) · Behaviour & Information Technology · doi:10.1080/0144929x.2026.2671387 · Cited by 1 · see citing works
Hubungan antara Motives dengan Problematic Smartphone Use (PSU): A Systematic Review
Ramadhan, R., Rachmasari, C., Sudrajat, Z. K., Mote, E. S., Susanto, A. V., Heng, P. H., & Idulfilastri, R. M. (2025) · RIGGS: Journal of Artificial Intelligence and Digital Business · doi:10.31004/riggs.v4i4.4072 · Cited by 1
Faro, H., Franchini, E., Albuquerque, M., Cavalcante-Silva, D., Pereira, D. C., de Lima, L. A. D., Machado, D. G. D. S., & Fortes, L. D. S. (2025) · Experimental Brain Research · doi:10.1007/s00221-025-07185-7 · Cited by 1 · see citing works
“Nonetheless, given the evidence that social media use can cause long-term brain modulation over time (Chun et al. 2017 ; Horvath et al. 2020; Lee et al. 2019), future studies should explore the neurophysiological effects of extended social media exposure.”
Anghelescu, L. A. M., Anghelescu, A., & Onose, G. (2024) · Balneo and PRM Research Journal · doi:10.12680/balneo.2024.750 · Cited by 1 · see citing works
“(69 ) The lack of objective longitudinal imagery records to investigate the neuro-plastic neuroadaptations secondary to cyber-addiction currently prevents recognition of phone addiction.”
Arató, Á., Darnai, G., Dudás, B., Szente, A., Alhour, H., Perlaki, G., Orsi, G., Nagy, S., & Janszky, J. (2026) · iScience · doi:10.1016/j.isci.2026.117913
Zeng, Y.-Y., Li, Z.-X., Li, W., Kan, Q.-Y., Xie, Y.-X., Zhao, X.-S., Li, J.-B., Zhang, M.-Z., Yang, L.-Y., Abudukadier, A., et al. (2026) · Progress in Neuro-psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2026.111956
SCROLL-BLINDED: THE ASSOCIATION BETWEEN SOCIAL MEDIA USE LEVELS, AFFECTIVE STATE AND DECISION-MAKING
Martínez-Maldonado, A., & Benito-Lázaro, M. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101324
Repercusiones neurobiológicas, cognitivas y clínicas de adicción a redes sociales
Díaz-Rodríguez, M., Mestres-Vázquez, L., Pérez-Banchilleria, P., & Adan, A. (2026) · Revista de Psicología Universidad de Antioquia · doi:10.17533/udea.rp.e364626
Wang, Y.-L., Ding, K.-M., Zhu, J., Zhao, B., Zhang, D.-W., Chang, X.-L., Li, G.-H., Pan, Y., Zhu, L., Hu, Q., et al. (2026) · Scientific Reports · doi:10.1038/s41598-026-62981-7
Hyperconnected Minds: A Systematic Review of the Neurobiology of Problematic Internet Use
Molnar, R., Butiu, O., & Mihai, A. (2026) · Psychiatry International · doi:10.3390/psychiatryint7030113
Petro, N. M., Webert, L. K., McDonald, K. M., Son, J. J., Ward, T. W., Rice, D. L., Ende, G. C., Coutant, A. T., Steiner, E. L., Livermore, C. L., et al. (2026) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2026.101735
“The location of this effect is consistent with previous reports linking frontal cortical differences with excessive social media use (D. Lee et al., 2019; Loh and Kanai, 2014; Moisala et al., 2016; Montag et al., 2018) and other problematic internet-related behaviors (Brand et al., 2014; Hong, Kim,…”
Shi, Y., & Zhang, X.-W. (2025) · Psychiatry Investigation · doi:10.30773/pi.2025.0026
Wacks, Y., Koslowsky, M., Bloch, A., & Weinstein, A. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1691748
“Recent brain imaging studies have shown structural alterations in the prefrontal cortex that were related to problematic smartphone use (23, 24).”
Mechanismen problematischer Smartphone-Nutzung
Wolf, N. D., Henemann, G. M., Schmitgen, M., & Wolf, R. (2025) · Nervenheilkunde · doi:10.1055/a-2625-7090
“Vergleichbare Befunde wurden auch für die INA des insu-lären Kortex berichtet, wobei insbesondere eine Assoziation zwischen insulärer/striataler und insulärer/OFC-Konnektivität und pro-longierter Smartphone-Nutzung im Bett hergestellt wurde [29].”
Smartphone addiction as a risk factor for medication non-adherence in renal transplant recipients
Helvacı, Ö., Demirezen, A., Akçay, Ö., Aksu, M., & Derici, U. (2025) · Archives of medical science : AMS · doi:10.5114/aoms/209207
Ge, J.-M., Chen, I.-J., Cao, W.-J., Shu, T.-Y., Peng, D., & Zhang, A.-B. (2025) · Behavior and Information Technology · doi:10.1080/0144929x.2025.2517209
“Additionally, Lee et al. (2019) found through an MRI (magnetic resonance imaging) study that PSUs had lower grey matter volume in the orbitofrontal cortex (OFC) of the basal ganglia compared to controls.”
Das Smartphone als ständiger Begleiter
Kohler, S., & Fauth-Bühler, M. (2024) · Sucht : Zeitschrift für Wissenschaft und Praxis · doi:10.1024/0939-5911/a000876
Lestari, D. (2022) · Journal of Health Literacy and Qualitative Research · doi:10.61194/jhlqr.v2i2.540
“As excessive gaming replaces real-world interactions, children may experience diminished social skills, leading to difficulties in establishing meaningful relationships(Lee et al., 2019).”
Zou, L.-W., Wu, X.-Y., Tao, S.-M., Yang, Y.-J., Zhang, Q., Hong, X., Xu, H., Xie, Y., Li, T.-T., Zheng, S.-S., et al. (2020) · doi:10.21203/rs.3.rs-30314/v1
“Moreover, the study report smaller GMV in right lateral orbitofrontal cortex in problematic smartphone users than controls (29).”
Background
- Authors
- Lee, D., Namkoong, K., Lee, J., Lee, B. O., & Jung, Y.-C.
- Affiliations
- Yonsei University (KR)
- Corresponding author
- Jung, Young-Chul
- Venue
- Journal of Behavioral Addictions
- Publisher
- Akademiai Kiado Zrt.
- Published
- 2019-09
- Volume
- 8
- Issue
- 3
- Pages
- 404-411
- ISSN
- 2062-5871 (ISSN-L)
- 2063-5303
- PMC
- PMC7044619
- OpenAlex
- W2976669220
- Cited by
- 64
- References
- 58
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 10 · 2023: 3 · 2022: 8 · 2021: 12 · 2020: 8 · 2018: 1
- FWCI
- 14.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- Journal of Behavioral Addictions (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
- YUHSpace (Yonsei University Medical Library) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Psychology › Clinical Psychology › Sexuality, Behavior, and Technology
- Social Sciences › Psychology › Clinical Psychology › Gambling Behavior and Treatments
- Keywords
- smartphone addiction, lateral orbitofrontal cortex, gray matter volume, addiction proneness, behavioral addiction, behavioral regulation
- MeSH terms
- Smartphone, Adolescent, Adult, Female, Gyrus Cinguli, Humans, Magnetic Resonance Imaging, Male, Behavior, Addictive, Prefrontal Cortex, Young Adult, Social Networking
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review