Race, Gender, and Information Technology Use: The New Digital Divide
Abstract
This research examined race and gender differences in the intensity and nature of IT use and whether IT use predicted academic performance. A sample of 515 children (172 African Americans and 343 Caucasian Americans), average age 12 years old, completed surveys as part of their participation in the Children and Technology Project. Findings indicated race and gender differences in the intensity of IT use; African American males were the least intense users of computers and the Internet, and African American females were the most intense users of the Internet. Males, regardless of race, were the most intense videogame players, and females, regardless of race, were the most intense cell phone users. IT use predicted children's academic performance. Length of time using computers and the Internet was a positive predictor of academic performance, whereas amount of time spent playing videogames was a negative predictor. Implications of the findings for bringing IT to African American males and bringing African American males to IT are discussed.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
The duration of mobile phone use has been poorly investigated, suggesting a lack of association with academic performance.
“whereas the duration of mobile phone use has been poorly investigated, suggesting a lack of association with academic performance.39,40,44”
From Association Between Screen Media Use and Academic Performance Among Children and Adolescents: A Systematic Review and Meta-analysis (2019) · cites this paper as [39]
With regard to the device used, the association between time of computer use and academic performance in children and adolescents remains equivocal, with both negative and positive associations found.
“With regard to the device used, the association between time of computer use and academic performance in children and adolescents remains equivocal, with both negative 53 and positive 39 associations found”
From Association Between Screen Media Use and Academic Performance Among Children and Adolescents: A Systematic Review and Meta-analysis (2019) · cites this paper as [39]
Cites
Digital divide: civic engagement, information poverty, and the Internet worldwide
Tefft, S. (2002) · Choice Reviews Online · doi:10.5860/choice.40-1165 · Cited by 2,940 · see citing works
Growing Up Digital: The Rise of the Net Generation
Tapscott, D. (1997) · Cited by 2,661 · see citing works
The Deepening Divide: Inequality in the Information Society
van Dijk, J. (2005) · doi:10.4135/9781452229812 · Cited by 2,243 · see citing works
Social media use in the United States: implications for health communication
Chou, W.-Y. S., Hunt, Y. M., Beckjord, E. B., Moser, R. P., & Hesse, B. W. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1249 · Cited by 1,082 · see citing works
Action-Video-Game Experience Alters the Spatial Resolution of Vision
Green, C. S., & Bavelier, D. (2007) · Psychological Science · doi:10.1111/j.1467-9280.2007.01853.x · Cited by 878 · see citing works
Gender and the Internet: Women Communicating and Men Searching
Jackson, L. A., Ervin, K. S., Gardner, P. D., & Schmitt, N. (2001) · Sex Roles · doi:10.1023/a:1010937901821 · Cited by 709 · see citing works
Self-citationThe Internet and Knowledge Gaps
Bonfadelli, H. (2002) · European Journal of Communication · doi:10.1177/0267323102017001607 · Cited by 650 · see citing works
Internet Use and Well‐Being in Adolescence
Gross, E. F., Juvonen, J., & Gable, S. L. (2002) · Journal of Social Issues · doi:10.1111/1540-4560.00249 · Cited by 581 · see citing works
The impact of computer use on children's and adolescents' development
Subrahmanyam, K., Greenfield, P. M., Kraut, R. E., & Gross, E. F. (2001) · Journal of Applied Developmental Psychology · doi:10.1016/s0193-3973(00)00063-0 · Cited by 565 · see citing works
Violent video game effects on children and adolescents: theory, research, and public policy
(2007) · Choice Reviews Online · doi:10.5860/choice.44-6518 · Cited by 492 · see citing works
The Digital Divide: The Role of Political Institutions in Technology Diffusion
Milner, H. V. (2006) · Comparative Political Studies · doi:10.1177/0010414005282983 · Cited by 433 · see citing works
Days and Nights on the Internet
Howard, P. N., Rainie, L., & Jones, S. (2001) · American Behavioral Scientist · doi:10.1177/0002764201045003003 · Cited by 403 · see citing works
Adolescents’ Exposure to Sexually Explicit Material on the Internet
Peter, J., & Valkenburg, P. M. (2006) · Communication Research · doi:10.1177/0093650205285369 · Cited by 310 · see citing works
Gender and the Internet: Causes of Variation in Access, Level, and Scope of Use*
Wasserman, I. M., & Richmond‐Abbott, M. (2005) · Social Science Quarterly · doi:10.1111/j.0038-4941.2005.00301.x · Cited by 285 · see citing works
Roberts, D. F., Foehr, U. G., Rideout, V. J., & Brodie, M. (2003) · Cambridge University Press eBooks · doi:10.1017/cbo9781139165112 · Cited by 272 · see citing works
Days and Nights on the Internet: The Impact of a Diffusing Technology
Howard, P. E. N., Rainie, L., & Jones, S. (2001) · American Behavioral Scientist · doi:10.1177/00027640121957259 · Cited by 258 · see citing works
Hoffman, D. L., Novak, T., & Schlosser, A. E. (2001) · The MIT Press eBooks · doi:10.7551/mitpress/2419.003.0007 · Cited by 175 · see citing works
The Racial Digital Divide: Motivational, Affective, and Cognitive Correlates of Internet Use1
Jackson, L. A., Ervin, K. S., Gardner, P. D., & Schmitt, N. (2001) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.2001.tb00162.x · Cited by 102 · see citing works
Self-citationWang, E. (2009) · CyberPsychology & Behavior · doi:10.1089/cyber.2009.0200 · Cited by 64 · see citing works
Jackson, L. A. (2008) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195342956.003.0014 · Cited by 53 · see citing works
Self-citationFortune, T., Wright, E., Juzang, I., & Bull, S. S. (2009) · Contemporary Clinical Trials · doi:10.1016/j.cct.2009.12.004 · Cited by 46 · see citing works
Social Capital and the Equalizing Potential of the Internet
Pruijt, H. (2002) · Social Science Computer Review · doi:10.1177/089443930202000201 · Cited by 41 · see citing works
DeBar, L., Dickerson, J. F., Clarke, G. N., Stevens, V. J., Ritenbaugh, C., & Aickin, M. G. (2008) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsn126 · Cited by 39 · see citing works
Emerging Technology Trends and Ethical Practices for the School Principal
Garland, V. E. (2009) · Journal of Educational Technology Systems · doi:10.2190/et.38.1.e · Cited by 31 · see citing works
The use of manufacturing technologies–an external influence perspective
Das, A., & Nair, A. (2009) · International Journal of Production Research · doi:10.1080/00207540903055719 · Cited by 15 · see citing works
Flagged first, then by citations
1 of the 26 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Systematic review of sedentary behaviour and health indicators in school-aged children and youth.
Tremblay, M. S., LeBlanc, A. G., Kho, M. E., Saunders, T. J., Larouche, R., Colley, R. C., Goldfield, G., & Gorber, S. (2011) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-8-98 · Cited by 2,085 · see citing works
Carson, V., Hunter, S., Kuzik, N., Gray, C. E., Poitras, V. J., Chaput, J.-P., Saunders, T. J., Katzmarzyk, P. T., Okely, A. D., Connor Gorber, S., et al. (2016) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2015-0630 · Cited by 1,380 · see citing works
Social media use in the United States: implications for health communication
Chou, W.-Y. S., Hunt, Y. M., Beckjord, E. B., Moser, R. P., & Hesse, B. W. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1249 · Cited by 1,082 · see citing works
Kontos, E., Blake, K. D., Chou, W.-Y. S., & Prestin, A. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3117 · Cited by 917 · see citing works
Lee, A. R., Son, S.-M., & Kim, K. K. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.08.011 · Cited by 814 · see citing works
The invisible addiction: Cell-phone activities and addiction among male and female college students
Roberts, J., Yaya, L., & Manolis, C. (2014) · Journal of Behavioral Addictions · doi:10.1556/jba.3.2014.015 · Cited by 711 · see citing works
Twenge, J. M., Martin, G. N., & Spitzberg, B. H. (2019) · Psychology of Popular Media Culture · doi:10.1037/ppm0000203 · Cited by 703 · see citing works
Effects of flipping the classroom on learning outcomes and satisfaction: A meta-analysis
van Alten, D. C. D., Phielix, C., Janssen, J. J. H. M., & Liesbeth Kester, A. (2019) · Educational Research Review · doi:10.1016/j.edurev.2019.05.003 · Cited by 633 · see citing works
An acceptance model for smart watches
Kim, K. J., & Shin, D. (2015) · Internet Research · doi:10.1108/intr-05-2014-0126 · Cited by 488 · see citing works
van Deursen, A. J. A. M., & van Dijk, J. A. G. M. (2015) · The Information Society · doi:10.1080/01972243.2015.1069770 · Cited by 353 · see citing works
Web 2.0 for Health Promotion: Reviewing the Current Evidence
Chou, W.-Y. S., Prestin, A., Lyons, C., & Wen, K.-Y. (2013) · American Journal of Public Health · doi:10.2105/ajph.2012.301071 · Cited by 309 · see citing works
Adelantado-Renau, M., Moliner-Urdiales, D., Cavero-Redondo, I., Beltran-Valls, M. R., Martínez-Vizcaíno, V., & Álvarez-Bueno, C. (2019) · JAMA Pediatrics · doi:10.1001/jamapediatrics.2019.3176 · Cited by 313 · see citing works
Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy
Siddiq, F., & Scherer, R. (2019) · Educational Research Review · doi:10.1016/j.edurev.2019.03.007 · Cited by 297 · see citing works
The Effects of COVID-19 Among the Elderly Population: A Case for Closing the Digital Divide
Jaarsveld, G. M. V. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.577427 · Cited by 290 · see citing works
Splicing the Divide: A Review of Research on the Evolving Digital Divide Among K–12 Students
Dolan, J. E. (2015) · Journal of Research on Technology in Education · doi:10.1080/15391523.2015.1103147 · Cited by 231 · see citing works
Defining digital literacy development: An examination of pre-service teachers’ beliefs
List, A. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.03.009 · Cited by 224 · see citing works
Prestin, A., Vieux, S. N., & Chou, W. S. (2015) · Journal of Health Communication · doi:10.1080/10810730.2015.1018590 · Cited by 222 · see citing works
Exploring the Digital Divide: Age and Race Disparities in Use of an Inpatient Portal
Walker, D. M., Hefner, J. L., Fareed, N., Huerta, T. R., & McAlearney, A. S. (2019) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2019.0065 · Cited by 218 · see citing works
Magee, J. C., Bigelow, L., DeHaan, S., & Mustanski, B. S. (2012) · Health Education & Behavior · doi:10.1177/1090198111401384 · Cited by 215 · see citing works
COVID-19 and Adolescent Depression and Suicide Risk Screening Outcomes
Mayne, S. L., Hannan, C., Davis, M., Young, J. F., Kelly, M. K., Powell, M., Dalembert, G., McPeak, K. E., Jenssen, B. P., & Fiks, A. G. (2021) · PEDIATRICS · doi:10.1542/peds.2021-051507 · Cited by 205 · see citing works
Barnes, S. J., Pressey, A. D., & Scornavacca, E. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.09.013 · Cited by 200 · see citing works
Digital inequalities 2.0: Legacy inequalities in the information age
Robinson, L., Schulz, J., Blank, G., Ragnedda, M., Ono, H., Hogan, B., Mesch, G. S., Cotten, S. R., Kretchmer, S. B., Hale, T. M., et al. (2020) · First Monday · doi:10.5210/fm.v25i7.10842 · Cited by 199 · see citing works
Ritzhaupt, A. D., Liu, F., Dawson, K., & Barron, A. E. (2013) · Journal of Research on Technology in Education · doi:10.1080/15391523.2013.10782607 · Cited by 196 · see citing works
Use of Active Video Games to Increase Physical Activity in Children: A (Virtual) Reality?
Foley, L. S., & Maddison, R. (2010) · Pediatric Exercise Science · doi:10.1123/pes.22.1.7 · Cited by 196 · see citing works
Reeves, B., Ram, N., Robinson, T. N., Cummings, J. J., Giles, C. L., Pan, J., Chiatti, A., Cho, M., Roehrick, K. C., Yang, X., et al. (2019) · Hum. Comput. Interact. · doi:10.1080/07370024.2019.1578652 · Cited by 199 · see citing works
Closing the gap: gender parity in political engagement on social media
Bode, L. (2016) · Information Communication & Society · doi:10.1080/1369118x.2016.1202302 · Cited by 179 · see citing works
Kim, K. J., & Sundar, S. S. (2014) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2013.0492 · Cited by 172 · see citing works
Eagleman, A. N. (2013) · Sport Management Review · doi:10.1016/j.smr.2013.03.004 · Cited by 163 · see citing works
THEORIZING DIGITAL AND URBAN INEQUALITIES
Gilbert, M. R. (2010) · Information Communication & Society · doi:10.1080/1369118x.2010.499954 · Cited by 156 · see citing works
Almenara, J. C., Guillén‐Gámez, F. D., Ruiz‐Palmero, J., & Palacios‐Rodríguez, A. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10476-5 · Cited by 141 · see citing works
Wang, H.-Y., Sigerson, L., & Cheng, C. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.08.031 · Cited by 128 · see citing works
A socioeconomic related 'digital divide' exists in how, not if, young people use computers
Harris, C. J., Straker, L. M., & Pollock, C. M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0175011 · Cited by 124 · see citing works
Predictors of online health information seeking behavior: Changes between 2002 and 2012
Li, J., Theng, Y., & Foo, S. S.-B. (2015) · Health Informatics Journal · doi:10.1177/1460458215595851 · Cited by 121 · see citing works
The effectiveness of casual advergames on adolescents' brand attitudes
Redondo, I. (2012) · European Journal of Marketing · doi:10.1108/03090561211260031 · Cited by 120 · see citing works
Gender and the Digital Divide in Latin America*
Gray, T. J., Gainous, J., & Wagner, K. M. (2016) · Social Science Quarterly · doi:10.1111/ssqu.12270 · Cited by 117 · see citing works
Youth and Digital Media: From Credibility to Information QualityPreprint
Gasser, U., Cortesi, S., Malik, M. M., & Lee, A. (2012) · SSRN Electronic Journal · doi:10.2139/ssrn.2005272 · Cited by 117 · see citing works
Internet Use Habits and Risk Behaviours in Preadolescence
Fernández‐Montalvo, J., Vélez, A. P., & Irazabal, I. (2014) · Comunicar · doi:10.3916/c44-2015-12 · Cited by 108 · see citing works
Gender differences in information behavior concerning Wikipedia, an unorthodox information source?
Lim, S., & Kwon, N. (2010) · Library & Information Science Research · doi:10.1016/j.lisr.2010.01.003 · Cited by 102 · see citing works
Time spent online: Latent profile analyses of emerging adults' social media use
Scott, C. F., Bay‐Cheng, L. Y., Prince, M. A., Nochajski, T. H., & Collins, R. L. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.05.026 · Cited by 108 · see citing works
Xie, X.-Z., & Tsai, N.-C. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2020.101503 · Cited by 101 · see citing works
Kingsley, K., Galbraith, G. M. P., Herring, M., Stowers, E. D., Stewart, T., & Kingsley, K. V. (2011) · BMC Medical Education · doi:10.1186/1472-6920-11-17 · Cited by 97 · see citing works
Age-Related Digital Divide during the COVID-19 Pandemic in China
Song, Y., Qian, C., & Pickard, S. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182111285 · Cited by 100 · see citing works
Revisiting the Digital Divide: Generational Differences in Technology Use in Everyday Life
Volkom, M. V., Stapley, J. C., & Amaturo, V. (2014) · North American journal of psychology · Cited by 91 · see citing works
Case Study: An Ethics Case Study of HIV Prevention Research on Facebook: The Just/Us Study
Bull, S. S., Breslin, L. T., Wright, E. E., Black, S. R., Levine, D., & Santelli, J. S. (2011) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsq126 · Cited by 87 · see citing works
Kang, H., & Kim, K. J. (2019) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2019.09.002 · Cited by 84 · see citing works
Overload and exhaustion: Classifying SNS discontinuance intentions
Nawaz, M., Shah, Z., Nawaz, A., Asmi, F., Hassan, Z., & Raza, J. (2018) · Cogent Psychology · doi:10.1080/23311908.2018.1515584 · Cited by 84 · see citing works
Bach, A. J., Shaffer, G. L., & Wolfson, T. (2013) · Journal of Information Policy · doi:10.5325/jinfopoli.3.1.247 · Cited by 82 · see citing works
Long, Q., & Tefertiller, A. C. (2020) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2020.1746060 · Cited by 79 · see citing works
Cognitive-Based E-Learning Design for Older Adults
Pappas, M. A., Demertzi, E., Papagerasimou, Y., Koukianakis, L., Voukelatos, N., & Drigas, A. S. (2019) · Social Sciences · doi:10.3390/socsci8010006 · Cited by 82 · see citing works
Do We Care About Diversity in Human Computer Interaction
Himmelsbach, J., Schwarz, S., Gerdenitsch, C., Wais-Zechmann, B., Bobeth, J., & Tscheligi, M. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300720 · Cited by 78 · see citing works
Kim, K. J. (2016) · Journal of Computer-Mediated Communication · doi:10.1111/jcc4.12177 · Cited by 79 · see citing works
Literature review on effectiveness of the use of social media: a report for Peel public health
Schein, R., Wilson, K. R., Keelan, J. E., & Rebecca, S. (2010) · Cited by 73 · see citing works
Kim, K. J., Shin, D., & Park, E. (2015) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2014.0675 · Cited by 74 · see citing works
The smart wearables-privacy paradox: A cluster analysis of smartwatch users
Kang, H., & Jung, E. H. (2020) · Behaviour and Information Technology · doi:10.1080/0144929x.2020.1778787 · Cited by 69 · see citing works
Mobile Phone Feature Preferences, Customer Satisfaction and Repurchase Intent among Male Users
Haverila, M. J. (2011) · Australasian Marketing Journal (AMJ) · doi:10.1016/j.ausmj.2011.05.009 · Cited by 68 · see citing works
Military Masculinity and the Travails of Transitioning
Semaan, B., Britton, L. M., & Dosono, B. (2017) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/2998181.2998221 · Cited by 66 · see citing works
Charleston, L. J. (2012) · Journal of Diversity in Higher Education · doi:10.1037/a0028918 · Cited by 64 · see citing works
The Use of Mobile Phones by South African University Students
North, D., Johnston, K. A., & Ophoff, J. (2014) · Issues in Informing Science and Information Technology · doi:10.28945/1984 · Cited by 61 · see citing works
Yingling, L., Mitchell, V. M., Ayers, C. R., Peters-Lawrence, M. H., Wallen, G. R., Brooks, A. T., Troendle, J. F., Adu‐Brimpong, J., Thomas, S., Henry, J. L., et al. (2017) · Translational Behavioral Medicine · doi:10.1007/s13142-016-0454-0 · Cited by 59 · see citing works
Kim, K. J. (2016) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2016.0136 · Cited by 60 · see citing works
Race and gender in play practices
DiSalvo, B. J., & Bruckman, A. S. (2010) · International Conference on the Foundations of Digital Games (FDG) · doi:10.1145/1822348.1822356 · Cited by 60 · see citing works
Pal, A., De', R., & Herath, T. (2020) · Inf. Syst. Frontiers · doi:10.1007/s10796-020-09982-7 · Cited by 56 · see citing works
Wang, E. (2009) · CyberPsychology & Behavior · doi:10.1089/cyber.2009.0200 · Cited by 64 · see citing works
The Perceived Influence of Media and Technology on Adolescent Romantic Relationships
Vaterlaus, J. M., Tulane, S., Porter, B. D., & Beckert, T. E. (2018) · Journal of Adolescent Research · doi:10.1177/0743558417712611 · Cited by 58 · see citing works
Wang, J.-Y., Wu, H., & Hsu, Y. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.09.032 · Cited by 56 · see citing works
Using Big Data and Machine Learning in Personality Measurement: Opportunities and Challenges
Alexander, L., Mulfinger, E., & Oswald, F. L. (2020) · European Journal of Personality · doi:10.1002/per.2305 · Cited by 53 · see citing works
Ruben, M. A., Stosic, M. D., Correale, J., & Blanch‐Hartigan, D. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.611670 · Cited by 62 · see citing works
Kuo, F., Tseng, C.-Y., Tseng, F.-C., & Lin, C. S. (2013) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2012.0345 · Cited by 53 · see citing works
Fitton, V. A., Ahmedani, B. K., Harold, R. D., & Shifflet, E. D. (2013) · Child and Adolescent Social Work Journal · doi:10.1007/s10560-013-0296-2 · Cited by 53 · see citing works
Self-citationUrban–rural differences in parental Internet mediation and adolescents’ Internet risks in Taiwan
Chang, F., Miao, N., Chiu, C., Chen, P., Lee, C., Chiang, J., & Chuang, H. (2016) · Health Risk & Society · doi:10.1080/13698575.2016.1190002 · Cited by 53 · see citing works
Attractive phones don't have to work better
Quinn, J. M., & Tran, T. Q. (2010) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1753326.1753380 · Cited by 52 · see citing works
Wu, Y. P., Steele, R. G., Connelly, M. A., Palermo, T. M., & Ritterband, L. M. (2014) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsu022 · Cited by 52 · see citing works
Personality traits, gender, and information competency among college students
Kwon, N., & Song, H. (2011) · Malaysian Journal of Library & Information Science · Cited by 51 · see citing works
Anthony, A. B., & Clark, L. M. (2011) · Urban Education · doi:10.1177/0042085911416015 · Cited by 50 · see citing works
Guðmundsdóttir, G. B. (2010) · NORA - Norwegian Open Research Archives · Cited by 50 · see citing works
Developing Digital and Media Literacies in Children and Adolescents
Turner, K. H., Jolls, T., Hagerman, M. S., O’Byrne, W. I., Hicks, T. W., Eisenstock, B., & Pytash, K. E. (2017) · PEDIATRICS · doi:10.1542/peds.2016-1758p · Cited by 50 · see citing works
Counselor-assisted problem solving improves caregiver efficacy following adolescent brain injury.
Wade, S. L., Karver, C. L., Taylor, H. G., Cassedy, A. E., Stancin, T., Kirkwood, M. W., & Brown, T. M. (2014) · Rehabilitation Psychology · doi:10.1037/a0034911 · Cited by 48 · see citing works
Yingling, L., Brooks, A. T., Wallen, G. R., Peters-Lawrence, M. H., McClurkin, M., Cooper-McCann, R., Wiley, K. L., Mitchell, V. M., Saygbe, J. N., Johnson, T. D., et al. (2016) · JMIR mhealth and uhealth · doi:10.2196/mhealth.4489 · Cited by 47 · see citing works
Fortune, T., Wright, E., Juzang, I., & Bull, S. S. (2009) · Contemporary Clinical Trials · doi:10.1016/j.cct.2009.12.004 · Cited by 46 · see citing works
Rabiu, H., Muhammed, A. I., Umaru, Y., & Tukur, H. A. (2016) · European Scientific Journal ESJ · doi:10.19044/esj.2016.v12n1p466 · Cited by 46 · see citing works
Strebinger, A., & Treiblmaier, H. (2022) · Information Technology & Tourism · doi:10.1007/s40558-021-00219-0 · Cited by 46 · see citing works
Cheng, C.-C., Huang, P.-L., & Huang, K.-H. (2013) · Journal of Networks · doi:10.4304/jnw.8.7.1529-1535 · Cited by 45 · see citing works
Effectiveness of web-based social sensing in health information dissemination—A review
Sharma, P., & Kaur, P. D. (2016) · Telematics and Informatics · doi:10.1016/j.tele.2016.04.012 · Cited by 49 · see citing works
Calderón-Garrido, D., Gustems-Carnicer, J., & Farrán, F. X. C. (2020) · International Journal of Music Education · doi:10.1177/0255761420954303 · Cited by 45 · see citing works
DiSalvo, B. J. (2014) · IEEE Computer Graphics and Applications · doi:10.1109/mcg.2014.112 · Cited by 44 · see citing works
Wilson, S. N., & Tiefenbacher, J. P. (2012) · Environmental Hazards · doi:10.1080/17477891.2011.649711 · Cited by 44 · see citing works
CyVerse: Cyberinfrastructure for open science
Swetnam, T. L., Antin, P. B., Bartelme, R. P., Bucksch, A., Camhy, D., Chism, G., Choi, I., Cooksey, A. M., Cosi, M., Cowen, C., et al. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011270 · Cited by 43 · see citing works
Interlocking Inequalities: Digital Stratification Meets Academic Stratification
Robinson, L., Wiborg, Ø. N., & Schulz, J. (2018) · American Behavioral Scientist · doi:10.1177/0002764218773826 · Cited by 43 · see citing works
Sankaran, R., & Chakraborty, S. (2022) · IIM Kozhikode Society & Management Review · doi:10.1177/2277975220975219 · Cited by 49 · see citing works
A case study for teaching information literacy skills
Kingsley, K. V., & Kingsley, K. (2009) · BMC Medical Education · doi:10.1186/1472-6920-9-7 · Cited by 40 · see citing works
Kononova, A. G. (2013) · International journal of communication · Cited by 39 · see citing works
Cell phone usage and broad feature preferences: A study among Finnish undergraduate students
Haverila, M. J. (2012) · Telematics and Informatics · doi:10.1016/j.tele.2012.05.002 · Cited by 39 · see citing works
Blomberg, M., Altschwager, D., Seo, H., Booton, E., & Nwachukwu, M. (2021) · Information Communication & Society · doi:10.1080/1369118x.2021.1963462 · Cited by 39 · see citing works
DeBar, L., Dickerson, J. F., Clarke, G. N., Stevens, V. J., Ritenbaugh, C., & Aickin, M. G. (2008) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsn126 · Cited by 39 · see citing works
eHealth patient-provider communication in the United States: interest, inequalities, and predictors
Spooner, K. K., Salemi, J. L., Salihu, H. M., & Zoorob, R. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw087 · Cited by 38 · see citing works
The Intersectional Impact of Race/Ethnicity and Sex on Access to Technology Among Older Adults
Suntai, Z., & Beltran, S. J. (2022) · The Gerontologist · doi:10.1093/geront/gnac178 · Cited by 37 · see citing works
Mossey, S., Bromberg, D. E., & Manoharan, A. (2018) · Journal of Information Technology & Politics · doi:10.1080/19331681.2018.1552224 · Cited by 37 · see citing works
Qaisar, S., Chu, J., Shah, Z., & Hassan, Z. (2021) · Behaviour and Information Technology · doi:10.1080/0144929x.2021.2002411 · Cited by 38 · see citing works
Digitally Deprived Children in Europe
Ayllón, S., Holmarsdottir, H. B., & Lado, S. (2023) · Child Indicators Research · doi:10.1007/s12187-022-10006-w · Cited by 31 · see citing works
Igniting research for outdoor recreation: linking science, policy, and action
Selin, S., Cerveny, L. K., Blahna, D. J., & Miller, A. B. (2020) · doi:10.2737/pnw-gtr-987 · Cited by 36 · see citing works
- Authors
- Jackson, L. A., Zhao, Y., Kolenic, A., Fitzgerald, H. E., Harold, R., & Von Eye, A.
- Affiliations
- Michigan State University (US)
- Department of Psychology, Michigan State University, East Lansing, Michigan.
- Venue
- CyberPsychology & Behavior
- Publisher
- SAGE Publications
- Published
- 2008-08-01
- Volume
- 11
- Issue
- 4
- Pages
- 437-442
- ISSN
- 1094-9313 (ISSN-L)
- 1557-8364
- OpenAlex
- W2094331245
- Cited by
- 396
- References
- 26
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 12 · 2023: 22 · 2022: 23 · 2021: 30 · 2020: 33 · 2019: 29 · 2018: 21 · 2017: 35 · 2016: 29 · 2015: 33 · 2014: 25 · 2013: 24 · 2012: 21
- FWCI
- 36.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- CyberPsychology & Behavior (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Gender Studies › Gender and Technology in Education
- Social Sciences › Education › Child Development and Digital Technology
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Keywords
- digital divide, racial differences, gender differences, information technology use, African American children, academic performance, internet use, computer use, mobile phone use
- MeSH terms
- Analysis of Variance, Attitude to Computers, Black or African American, Child, Computers, Educational Status, Female, Humans, Male, Sex Factors, Socioeconomic Factors, Video Games, Internet, White People
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
