The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Online game addiction among adolescents: motivation and prevention factors
Abstract
Online game addiction has become a common phenomenon that affects many individuals and societies. In this study we rely on the functionalist perspective of human behavior and propose and test a balanced model of the antecedents of online game addiction among adolescents, which simultaneously focuses on motivating, and prevention and harm reduction forces. First, a sample of 163 adolescents was used for validating and refining a survey instrument. Second, survey data collected from 623 adolescents were analyzed with Partial Least Squares techniques. The findings point to several functional needs (e.g., need for relationship and need for escapism) that drive online game playing and addiction, as well as to several prevention and harm reduction factors (e.g., education, attention switching activities) that reduce game playing time and alleviate online game addiction. The effects of motivation and prevention factors on online game addiction are often partially mediated by online game playing. Implications for research and practice are discussed.
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Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
Maslow, A. H. (1943) · Psychological Review · doi:10.1037/h0054346 · Cited by 21,563
Guidelines for the process of cross-cultural adaptation of self-report measures
Beaton, D. E., Bombardier, C., Guillemin, F., & Ferraz, M. B. (2000) · Spine · doi:10.1097/00007632-200012150-00014 · Cited by 14,542
Understanding information technology usage: a test of competing models
Taylor, S., & Todd, P. A. (1995) · Information Systems Research · doi:10.1287/isre.6.2.144 · Cited by 8,815
Modern Methods for Business Research
(1998) · doi:10.4324/9781410604385 · Cited by 6,534
Internet Addiction: The Emergence of a New Clinical Disorder
YOUNG, K. S. (1998) · CyberPsychology & Behavior · doi:10.1089/cpb.1998.1.237 · Cited by 5,513
Diamantopoulos, A., & Siguaw, J. A. (2006) · British Journal of Management · doi:10.1111/j.1467-8551.2006.00500.x · Cited by 3,410 · cited 1×
“The highest VIF calculated was 1.461 (Table 3) and was thus below the recommended upper border (Diamantopoulos & Siguaw, 2006).”
BackgroundInfluentialUnderstanding and assessing the motivations of volunteers: A functional approach.
Clary, E. G., Snyder, M., Ridge, R. D., Copeland, J., Stukas, A. A., Haugen, J., & Miene, P. (1998) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.74.6.1516 · Cited by 2,994
Wu, J.-H., & Wang, S.-C. (2005) · Information & Management · doi:10.1016/j.im.2004.07.001 · Cited by 2,284
Robinson, T. E., & Berridge, K. C. (2003) · Annual Review of Psychology · doi:10.1146/annurev.psych.54.101601.145237 · Cited by 1,509
Cited by
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 2,416
“Features of Internet addiction may co-vary positively with both positive expectancies (e.g., to experience pleasure) and avoidance expectancies (e.g., to escape from reality) on a bivariate level (Brand et al., 2014a; Lee et al., 2014; Turel et al., 2011; Xu et al., 2012).”
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
Self-citationThe Needs–Affordances–Features Perspective for the Use of Social Media1
Karahanna, E., Xu, S. X., Xu, Y., & Zhang, N. (. (2018) · MIS Quarterly · doi:10.25300/misq/2018/11492 · Cited by 518
Müller, K. W., Dreier, M., Beutel, M. E., Duven, E., Giralt, S., & Wölfling, K. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.09.007 · Cited by 263
Vaala, S. E., & Bleakley, A. (2015) · Journal of Children and Media · doi:10.1080/17482798.2015.997103 · Cited by 195
Metadata
- Authors
- Xu, Z., Turel, O., & Yuan, Y.
- Venue
- European Journal of Information Systems
- Publisher
- Informa UK Limited
- Published
- 2012-05
- Volume
- 21
- Issue
- 3
- Pages
- 321-340
- ISSN
- 0960-085X (ISSN-L)
- 1476-9344
- OpenAlex
- W2029289146
- Cited by
- 364
- References
- 22
- FWCI
- 36.43
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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