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Screen media activity and brain structure in youth: Evidence for diverse structural correlation networks from the ABCD study
Open accessAbstract
The adolescent brain undergoes profound structural changes which is influenced by many factors. Screen media activity (SMA; e.g., watching television or videos, playing video games, or using social media) is a common recreational activity in children and adolescents; however, its effect on brain structure is not well understood. A multivariate approach with the first cross-sectional data release from the Adolescent Brain Cognitive Development (ABCD) study was used to test the maturational coupling hypothesis, i.e. the notion that coordinated patterns of structural change related to specific behaviors. Moreover, the utility of this approach was tested by determining the association between these structural correlation networks and psychopathology or cognition. ABCD participants with usable structural imaging and SMA data (N = 4277 of 4524) were subjected to a Group Factor Analysis (GFA) to identify latent variables that relate SMA to cortical thickness, sulcal depth, and gray matter volume. Subject scores from these latent variables were used in generalized linear mixed-effect models to investigate associations between SMA and internalizing and externalizing psychopathology, as well as fluid and crystalized intelligence. Four SMA-related GFAs explained 37% of the variance between SMA and structural brain indices. SMA-related GFAs correlated with brain areas that support homologous functions. Some but not all SMA-related factors corresponded with higher externalizing (Cohen's d effect size (ES) 0.06-0.1) but not internalizing psychopathology and lower crystalized (ES: 0.08-0.1) and fluid intelligence (ES: 0.04-0.09). Taken together, these findings support the notion of SMA related maturational coupling or structural correlation networks in the brain and provides evidence that individual differences of these networks have mixed consequences for psychopathology and cognitive performance.
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In the citing paper
“Research has also shown that greater screen time in children is associated with lower cortical thickness, particularly in areas associated with language and literacy skills (Paulus et al., 2019).”
From The impact of digital technology, social media, and artificial intelligence on cognitive functions: a review (2023) · cites this paper as Paulus et al., 2019
Experimental — accuracy not yet measuredIn the citing paper
“which may negatively affect the functioning of other cortical networks, such as cognitive control regions, that interact with sensorimotor areas [33].”
In the citing paper
“In contrast, for crystallized intelligence, screen time in general and social media activity showed strong negative associations with occipital and orbitofrontal volume [33].”
In the citing paper
“Second, results showed a strong association between screen time, externalizing (but not internalizing) psychopathology, and changes in cortical and limbic structures (e.g., smaller orbitofrontal volume, thinner occipital and temporal cortices, thinner hippocampi) [33]”
In the citing paper
“The study identified several associations between screen time, brain structure (e.g., cortical thickness, gray matter volume, and sulcal depth), and cognition (e.g., fluid and crystallized intelligence) and mental health (e.g., internalizing and externalizing psychopathologies) [33].”
In the citing paper
“Changes in these cortical networks are thought to be influenced by early environmental experiences, including childhood abuse [83], urban upbringing [84], and screen time [33], and may have serious lifetime impacts on general cognitive ability, social-emotional behaviour, psychopathology, and substance use and abuse.”
In the citing paper
“Preliminary data from The Adolescent Brain and Cognitive Development (ABCD) Study, a multi-site longitudinal neuroimaging study, shows the significant impact that screen time has on the relationship between cognitive-behavioural maturational markers and normal patterns of brain development in children and adolescents [33,85].”
In the citing paper
“First, results showed a robust association between screen time and changes in visual system structural patterns (i.e., reduced volume, thinner cortex, variations in sulcal depth)”
In the citing paper
“For fluid intelligence, gaming activity showed positive associations with prefrontal cortex thinning, whereas social media activity showed negative associations with hippocampal thickness and temporal lobe volume [33].”
In the citing paper
“Total screen time was calculated separately for weekdays and weekend days, based on a previously validated measure [93–95].”
From Screen time and mental health: a prospective analysis of the Adolescent Brain Cognitive Development (ABCD) Study (2024) · cites this paper as [95]
In the citing paper
“Research so far shows mixed consequences of screen time on cognitive abilities related to intelligence10–13.”
From The impact of digital media on children’s intelligence while controlling for genetic differences in cognition and socioeconomic background (2022) · cites this paper as [11]
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Citations
Cites
Generalized Additive Models: An Introduction with R
Wood, S. N. (2017) · doi:10.1201/9781315370279 · Cited by 13,852
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610
Cortical Surface-Based Analysis
Fischl, B., Sereno, M. I., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1998.0396 · Cited by 6,147
Measuring the thickness of the human cerebral cortex from magnetic resonance images
Fischl, B. R., & Dale, A. M. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200033797 · Cited by 5,995
A hybrid approach to the skull stripping problem in MRI
Ségonne, F., Dale, A. M., Busa, E., Glessner, M., Salat, D. H., Hahn, H., & Fischl, B. R. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.03.032 · Cited by 2,227
The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites
Casey, B. J., Cannonier, T., Conley, M. I., Cohen, A. O., Barch, D. M., Heitzeg, M. M., Soules, M. E., Teslovich, T., Dellarco, D. V., Garavan, H., et al. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.03.001 · Cited by 2,167
Self-citationFischl, B. R., Liu, A., & Dale, A. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906426 · Cited by 1,755
Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018) · Clinical Psychological Science · doi:10.1177/2167702617723376 · Cited by 1,705
Research works printed but not linked: 1
- Tipping, 2001, Sparse Bayesian learning and the relevance vector machine, J. Mach. Learn. Res., 1, 211
Cited by
Sorted by citations
Hutton, J. S., Dudley, J., Horowitz-Kraus, T., DeWitt, T., & Holland, S. K. (2020) · JAMA Pediatrics · doi:10.1001/jamapediatrics.2019.3869 · Cited by 460
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
“Furthermore, a large study of 4,277 adolescents has shown a negative correlation between screen media activity and cortical thickness in fMRI implying premature aging of the brain (97).”
BackgroundThe ABCD study: understanding the development of risk for mental and physical health outcomes
Karcher, N. R., & Barch, D. M. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-020-0736-6 · Cited by 351
The associations between screen time and mental health in adolescents: a systematic review
Santos, R. M. S., Mendes, C. G., Sen Bressani, G. Y., de Alcantara Ventura, S., de Almeida Nogueira, Y. J., de Miranda, D. M., & Romano-Silva, M. A. (2023) · BMC Psychology · doi:10.1186/s40359-023-01166-7 · Cited by 311
Shanmugasundaram, M., & Tamilarasu, A. (2023) · Frontiers in Cognition · doi:10.3389/fcogn.2023.1203077 · Cited by 291
Sleep duration, brain structure, and psychiatric and cognitive problems in children
Cheng, W., Rolls, E., Gong, W., Du, J., Zhang, J., Zhang, X.-Y., Li, F., & Feng, J. (2021) · Molecular Psychiatry · doi:10.1038/s41380-020-0663-2 · Cited by 196
Neurobiological mechanisms underlying internet gaming disorder
Weinstein, A. M., & Lejoyeux, M. (2020) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2020.22.2/aweinstein · Cited by 194
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
The Challenges and Opportunities of Small Effects: The New Normal in Academic Psychiatry
Paulus, M. P., & Thompson, W. K. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2018.4540 · Cited by 160
Self-citationSaragosa‐Harris, N. M., Chaku, N., MacSweeney, N., Williamson, V. G., Scheuplein, M., Feola, B., Cardenas‐Iniguez, C., Demir-Lira, E., McNeilly, E. A., Huffman, L. G., et al. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101115 · Cited by 172
Time for the Human Screenome Project
Reeves, B. B., Robinson, T. N., & Ram, N. (2020) · Nature · doi:10.1038/d41586-020-00032-5 · Cited by 142
Inter-individual variability in structural brain development from late childhood to young adulthood
Mills, K. L., Siegmund, K. D., Tamnes, C. K., Ferschmann, L., Wierenga, L. M., Bos, M. G. N., Luna, B., Li, C., & Herting, M. M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118450 · Cited by 145
Compton, W. M., Dowling, G. J., & Garavan, H. (2019) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2019.2081 · Cited by 146
Sedentary behavior and lifespan brain health
Zou, L., Herold, F., Cheval, B., Wheeler, M. J., Pindus, D. M., Erickson, K. I., Raichlen, D. A., Alexander, G. E., Müller, N. G., Dunstan, D. W., et al. (2024) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2024.02.003 · Cited by 147
Tomasi, D. G., & Volkow, N. D. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01130-0 · Cited by 127
Manwell, L. A., Tadros, M., Ciccarelli, T. M., & Eikelboom, R. (2022) · Journal of Integrative Neuroscience · doi:10.31083/j.jin2101028 · Cited by 122
Neville, R. D., McArthur, B. A., Eirich, R., Lakes, K. D., & Madigan, S. (2021) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13425 · Cited by 109
Sociodemographic Correlates of Contemporary Screen Time Use among 9- and 10-Year-Old Children
Nagata, J. M., Ganson, K. T., Iyer, P., Chu, J., Baker, F. C., Pettee Gabriel, K., Garber, A. K., Murray, S. B., & Bibbins-Domingo, K. (2022) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2021.08.077 · Cited by 117
Herting, M. M., Uban, K. A., Gonzalez, M. R., Baker, F. C., Kan, E., Thompson, W. K., Granger, D. A., Albaugh, M. D., Anokhin, A. P., Bagot, K. S., et al. (2021) · Frontiers in Endocrinology · doi:10.3389/fendo.2020.549928 · Cited by 110
Self-citationSéguin, D., Kuenzel, E., Morton, J. B., & Duerden, E. G. (2021) · Journal of Affective Disorders Reports · doi:10.1016/j.jadr.2021.100217 · Cited by 101
Wade, N. E., Ortigara, J., Sullivan, R. M., Tomko, R. L., Breslin, F. J., Baker, F. C., Fuemmeler, B. F., Howlett, K. D., Lisdahl, K. M., Marshall, A. T., et al. (2021) · JMIR Mental Health · doi:10.2196/29426 · Cited by 106
Self-citationNagata, J. M., Al-Shoaibi, A. A. A., Leong, A. W., Zamora, G., Testa, A., Ganson, K. T., & Baker, F. C. (2024) · BMC Public Health · doi:10.1186/s12889-024-20102-x · Cited by 103
“Total screen time was calculated separately for weekdays and weekend days, based on a previously validated measure [93–95].”
MethodThe Association between Screen Time and Attention in Children: A Systematic Review
Santos, R. M. S., Mendes, C. G., de Miranda, D. M., & Romano‐Silva, M. A. (2022) · Developmental Neuropsychology · doi:10.1080/87565641.2022.2064863 · Cited by 118
Associations between duration and type of electronic screen use and cognition in US children
Walsh, J. J., Barnes, J. D., Tremblay, M. S., & Chaput, J.-P. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106312 · Cited by 87
Effect sizes of associations between neuroimaging measures and affective symptoms: A meta‐analysis
Feng, C., Thompson, W. K., & Paulus, M. P. (2021) · Depression and Anxiety · doi:10.1002/da.23215 · Cited by 89
Self-citationСолдатова, Г. У., & Войскунский, А. Е. (2021) · Психология Журнал Высшей школы экономики · doi:10.17323/1813-8918-2021-3-431-450 · Cited by 86
Gong, W., Rolls, E. T., Du, J., Feng, J., & Cheng, W. (2021) · Nature Communications · doi:10.1038/s41467-021-23994-0 · Cited by 84
Firth, J., Torous, J. B., López‐Gil, J. F., Linardon, J., Milton, A. C., Lambert, J. D., Smith, L., Jarić, I., Fabian, H., Vancampfort, D., et al. (2024) · World Psychiatry · doi:10.1002/wps.21188 · Cited by 109
Sauce, B., Liebherr, M., Judd, N., & Klingberg, T. (2022) · Scientific Reports · doi:10.1038/s41598-022-11341-2 · Cited by 74
Chen, C., Chen, S., Wen, P., & Snow, C. E. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106462 · Cited by 76
Nagata, J. M., Iyer, P., Chu, J., Baker, F., Gabriel, K. P., Garber, A., Murray, S. B., Bibbins-Domingo, K., & Ganson, K. (2021) · International Journal of Eating Disorders · doi:10.1002/eat.23489 · Cited by 60
Is the US Gender Gap in Depression Changing Over Time? A Meta-Regression
Platt, J. M., Bates, L. M., Jager, J., McLaughlin, K. A., & Keyes, K. M. (2021) · American Journal of Epidemiology · doi:10.1093/aje/kwab002 · Cited by 71
A meta-analysis of technology use and cognitive aging
Benge, J. F., & Scullin, M. K. (2025) · Nature Human Behaviour · doi:10.1038/s41562-025-02159-9 · Cited by 103
Hutton, J. S., Huang, G., Sahay, R. D., DeWitt, T., & Ittenbach, R. F. (2020) · Pediatric Research · doi:10.1038/s41390-020-0765-1 · Cited by 61
Zivan, M., Bar, S., Xiang, J., Hutton, J., Farah, R., & Horowitz‐Kraus, T. (2019) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2019.100117 · Cited by 65
Editorial: Educational technology and addictions
Melo, C., Madariaga, L., Nussbaum, M., Heller, R. S., Bennett, S., Tsai, C., & van Braak, J. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.103730 · Cited by 61
Roffman, J. L., Sipahi, E. D., Dowling, K. F., Hughes, D., Hopkinson, C. E., Lee, H., Eryilmaz, H., Cohen, L. S., Gilman, J. M., Doyle, A. E., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0250235 · Cited by 49
Fung, H., Yeo, B. T. T., Chen, C., Lo, J. C.-Y., Chee, M. W. L., & Ong, J. L. (2022) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2022.10.019 · Cited by 55
Hutton, J., Dudley, J. A., DeWitt, T. G., & Horowitz‐Kraus, T. (2022) · Scientific Reports · doi:10.1038/s41598-022-20922-0 · Cited by 54
Zavala-Crichton, J. P., Esteban‐Cornejo, I., Solis‐Urra, P., Mora-González, J., Cadenas‐Sánchez, C., Rodríguez‐Ayllón, M., Migueles, J. H., Molina‐García, P., Verdejo‐Román, J., Kramer, A. F., et al. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9041101 · Cited by 50
Chen, Y., Yim, H., & Lee, T. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101218 · Cited by 61
Screen media activity in youth: A critical review of mental health and neuroscience findings
Paulus, M. P., Zhao, Y., Potenza, M. N., Aupperle, R. L., Bagot, K. S., & Tapert, S. F. (2023) · Journal of Mood and Anxiety Disorders · doi:10.1016/j.xjmad.2023.100018 · Cited by 44
Self-citationWang, H., Rolls, E. T., Du, X., Du, J., Yang, D., Li, J., Li, F., Cheng, W., & Feng, J. (2020) · BMC Medicine · doi:10.1186/s12916-020-01701-y · Cited by 42
Screen time and suicidal behaviors among U.S. children 9–11 years old: A prospective cohort study
Chu, J., Ganson, K. T., Baker, F. C., Testa, A. M., Jackson, D. B., Murray, S. B., & Nagata, J. M. (2023) · Preventive Medicine · doi:10.1016/j.ypmed.2023.107452 · Cited by 42
Nagata, J. M., Chu, J., Ganson, K. T., Murray, S. B., Iyer, P., Gabriel, K. P., Garber, A. K., Bibbins‐Domingo, K., & Baker, F. C. (2023) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13673 · Cited by 39
How Early Digital Experience Shapes Young Brains During 0-12 Years: A Scoping Review
Wu, D., Dong, X., Liu, D., & Li, H. (2023) · Early Education and Development · doi:10.1080/10409289.2023.2278117 · Cited by 40
Screen use, sleep duration, daytime somnolence, and academic failure in school-aged adolescents
Pérez-Chada, D., Arias, S., Schönfeld, D., Gozal, D., Perez‐Lloret, S., & On behalf of the Sleep in Adolescents Collaborative study group (2023) · PLoS ONE · doi:10.1371/journal.pone.0281379 · Cited by 38
Digital Media and Developing Brains: Concerns and Opportunities
Hutton, J., Piotrowski, J. T., Bagot, K. S., Blumberg, F. C., Canli, T., Chein, J. M., Christakis, D., Grafman, J. H., Griffin, J. A., Hummer, T. A., et al. (2024) · Current Addiction Reports · doi:10.1007/s40429-024-00545-3 · Cited by 38
Self-citationLong-term impact of digital media on brain development in children
Nivins, S., Sauce, B., Liebherr, M., Judd, N., & Klingberg, T. (2024) · Scientific Reports · doi:10.1038/s41598-024-63566-y · Cited by 51
Khundrakpam, B. S., Lewis, J. D., Jeon, S., Kostopoulos, P., Medina, Y. I., Chouinard-Decorte, F., & Evans, A. C. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx317 · Cited by 35
Achterberg, M., Becht, A., van der Cruijsen, R., van de Groep, I. H., Spaans, J. P., Klapwijk, E., & Crone, E. A. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101088 · Cited by 37
Understanding Digital Dementia and Cognitive Impact in the Current Era of the Internet: A Review
Ali, Z., Janarthanan, J., & Mohan, P. (2024) · Cureus · doi:10.7759/cureus.70029 · Cited by 59
Martins, C., Bandeira, P. F. R., Lemos, N. B. A. G., Bezerra, T. A., Clark, C. C. T., Mota, J. A. P. S., & Duncan, M. J. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17238861 · Cited by 45
Wu, X., Palaniyappan, L. K., Yu, G., Zhang, K., Seidlitz, J., Liu, Z., Kong, X., Schumann, G., Feng, J., Sahakian, B. J., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01896-x · Cited by 34
Adolescent brain and the natural allure of digital media
Giedd, J. N. (2020) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2020.22.2/jgiedd · Cited by 35
Media screen time use and mental health in school aged children during the pandemic
Hmidan, A., Séguin, D., & Duerden, E. G. (2023) · BMC Psychology · doi:10.1186/s40359-023-01240-0 · Cited by 38
Umbach, R., & Tottenham, N. (2020) · Development and Psychopathology · doi:10.1017/s0954579420000401 · Cited by 27
Zhao, Y., Paulus, M. P., & Potenza, M. N. (2023) · Journal of Behavioral Addictions · doi:10.1556/2006.2023.00006 · Cited by 35
Self-citationCausal Relationships Between Screen Use, Reading, and Brain Development in Early Adolescents
Li, M., Zhao, R., Dang, X., Xu, X., Chen, R., Chen, Y., Zhang, Y., Zhao, Z., & Wu, D. (2024) · Advanced Science · doi:10.1002/advs.202307540 · Cited by 32
Keller, A. S., Moore, T. M., Luo, A. C., Visoki, E., Gataviņš, M. M., Shetty, A., Cui, Z., Yong Fan, A., Feczko, E., Houghton, A., et al. (2024) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2024.101370 · Cited by 34
Song, K., Zhang, J., Zhou, N., Fu, Y., Zou, B., Xu, L., Wang, Z., Li, X., Zhao, Y., Potenza, M. N., et al. (2022) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2023.02.014 · Cited by 30
Koob, G. F., Kandel, D. B., Baler, R., & Volkow, N. D. (2023) · Springer eBooks · doi:10.1007/978-3-030-42825-9_29-1 · Cited by 31
Miller, J. W., Mills, K. L., Vuorre, M., Orben, A. C., & Przybylski, A. K. (2023) · Cortex · doi:10.1016/j.cortex.2023.09.009 · Cited by 37
Kirlić, N., Colaizzi, J. M., Cosgrove, K. T., Cohen, Z. P., Yeh, H., Breslin, F. J., Morris, A. S., Aupperle, R. L., Singh, M. K., & Paulus, M. P. (2021) · Child Development · doi:10.1111/cdev.13578 · Cited by 32
Self-citationSukumaran, K., Botternhorn, K. L., Schwartz, J. D., Gauderman, J., Cardenas‐Iniguez, C., McConnell, R., Hackman, D. A., Berhane, K. T., Ahmadi, H., Abad, S., et al. (2024) · Environmental Health Perspectives · doi:10.1289/ehp14418 · Cited by 28
Al-Amri, A., Abdulaziz, S., Bashir, S., Ahsan, M., & Abualait, T. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1182749 · Cited by 40
Passively sensing smartphone use in teens with rates of use by sex and across operating systems
Alexander, J. D., Linkersdörfer, J., Toda-Thorne, K., Sullivan, R. M., Cummins, K. M., Tomko, R. L., Allen, N. B., Bagot, K. S., Baker, F. C., Fuemmeler, B. F., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-68467-8 · Cited by 28
Self-citationNagata, J. M., Chu, J., Zamora, G., Ganson, K., Testa, A., Jackson, D. B., Costello, C. R., Murray, S. B., & Baker, F. (2022) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2022.10.023 · Cited by 21
Brooks, S. J., Smith, C., & Stamoulis, C. (2023) · International Journal of Obesity · doi:10.1038/s41366-023-01303-7 · Cited by 27
Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development
Bottenhorn, K. L., Sukumaran, K., Cardenas‐Iniguez, C., Habre, R., Schwartz, J. D., Chen, J., & Herting, M. M. (2024) · Environment International · doi:10.1016/j.envint.2024.108769 · Cited by 28
Probing the digital exposome: associations of social media use patterns with youth mental health
Pagliaccio, D., Tran, K. T., Visoki, E., DiDomenico, G. E., Auerbach, R. P., & Barzilay, R. (2024) · NPP—Digital Psychiatry and Neuroscience · doi:10.1038/s44277-024-00006-9 · Cited by 23
Almeida, M. L., Garon‐Carrier, G., Çınar, E., Frizzo, G. B., & Fitzpatrick, C. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1053146 · Cited by 30
Brain structural covariation linked to screen media activity and externalizing behaviors in children
Zhao, Y., Paulus, M. P., Bagot, K. S., Constable, R. T., Yaggi, H. K., Redeker, N. S., & Potenza, M. N. (2022) · Journal of Behavioral Addictions · doi:10.1556/2006.2022.00044 · Cited by 25
Self-citationOnyeaka, H., Muoghalu, C., Baiden, P., Okine, L., Szlyk, H. S., Peoples, J. E., Kasson, E. M., Cavazos‐Rehg, P. A., Firth, J., & Torous, J. B. (2022) · Psychiatry Research · doi:10.1016/j.psychres.2022.114740 · Cited by 23
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Bradley, R. H. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108866040 · Cited by 20
Zhou, X., Tan, Y., Yu, H. L., Liu, J., Lan, X., Deng, Y., Yu, F., Wang, C., Chen, J., Zeng, X., et al. (2022) · Human Brain Mapping · doi:10.1002/hbm.25969 · Cited by 19
Meri, R., Hutton, J., Farah, R., DiFrancesco, M. W., Gozman, L., & Horowitz‐Kraus, T. (2022) · Child Neuropsychology · doi:10.1080/09297049.2022.2110577 · Cited by 20
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Weigard, A. S., McCurry, K. L., Shapiro, Z. R., Martz, M. E., Angstadt, M., Heitzeg, M. M., Dinov, I. D., & Sripada, C. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02502-6 · Cited by 19
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Gluckman, P. D., Low, F. M., & Hanson, M. A. (2020) · Evolution Medicine and Public Health · doi:10.1093/emph/eoaa042 · Cited by 16
Al-shoaibi, A. A. A., Zamora, G., Chu, J., Patel, K. P., Ganson, K., Testa, A. M., Jackson, D. B., Tapert, S., Baker, F. C., & Nagata, J. M. (2024) · Acta paediatrica · doi:10.1111/apa.17349 · Cited by 21
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Liu, J., Yang, Y., Kong, T., Liu, R., & Luo, L. (2025) · Journal of Environmental Psychology · doi:10.1016/j.jenvp.2025.102625 · Cited by 13
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Demidenko, M. I., Weigard, A. S., Ganesan, K., Jang, H., Jahn, A., Huntley, E. D., & Keating, D. P. (2021) · Brain and Behavior · doi:10.1002/brb3.2093 · Cited by 18
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Rauschecker, A. M., Nedelec, P., Pan, S., Olaru, M., Nillo, R. M., Palmer, C. E., Pecheva, D., Dale, A. M., Jernigan, T. L., & Sugrue, L. P. (2025) · Scientific Reports · doi:10.1038/s41598-025-88398-2 · Cited by 14
Gonçalves, P. D., Martins, S. S., Gebru, N. M., Ryan-Pettes, S. R., Allgaier, N. A., Potter, A., Thompson, W. K., Johnson, M. E., Garavan, H., Talati, A., et al. (2023) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2023.100284 · Cited by 13
Self-citationVolkow, N. D., Gordon, J. A., Koob, G. F., Birnbaum, L. S., Clayton, J. A., Koroshetz, W. J., Bianchi, D. W., Gibbons, G. H., Riley, W. T., Pérez‐Stable, E. J., et al. (2020) · Public Health Reports · doi:10.1177/0033354919900889 · Cited by 12
Zhao, Y., Han, X., Bagot, K. S., Tapert, S. F., Potenza, M. N., & Paulus, M. P. (2025) · npj Mental Health Research · doi:10.1038/s44184-025-00131-z · Cited by 12
Self-citationCui, J., Li, G., Zhang, M., Xu, J., Qi, H., Ji, W., Wu, F., Zhang, Y., Jiang, F., Hu, Y., et al. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad267 · Cited by 15
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Self-citation
Metadata
- Authors
- Paulus, M. P., Squeglia, L. M., Bagot, K., Jacobus, J., Kuplicki, R., Breslin, F. J., Bodurka, J., Morris, A. S., Thompson, W. K., Bartsch, H., & Tapert, S. F.
- Affiliations
- University of California San Diego (US)
- Medical University of South Carolina (US)
- Laureate Institute for Brain Research (US)
- Oklahoma State University (US)
- Corresponding author
- Paulus, Martin P.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 185
- Pages
- 140-153
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC6487868
- OpenAlex
- W2897654119
- Cited by
- 254
- References
- 72
- Citations by year
- 2026: 14 · 2025: 29 · 2024: 95 · 2023: 30 · 2022: 26 · 2021: 27 · 2020: 24 · 2019: 8
- FWCI
- 33.49
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (U01DA041022, U01DA041025, U01DA041028, U01DA041048, U01DA041089, U01DA041093, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, U24DA041147)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Education › Child Development and Digital Technology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- adolescent brain development, video games, social media use, television viewing, cortical thickness, sulcal depth, gray matter volume, internalizing psychopathology, externalizing psychopathology, fluid intelligence, crystallized intelligence, Adolescent Brain Cognitive Development Study
- MeSH terms
- Screen Time, Adolescent, Mental Disorders, Brain, Child, Cognition, Cross-Sectional Studies, Female, Humans, Image Interpretation, Computer-Assisted, Individuality, Longitudinal Studies, Male, Nerve Net, Adolescent Development
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