Internet Addiction: Annotated Bibliography - For NCU PSY7102

Annotated Bibliography for Internet Addiction Sources

Laura Ann Collins

Northcentral University

Abstract

This paper is comprised of an annotated bibliography of several articles pertaining to internet addiction (IA).

Keywords:  IA, Internet Addiction, Annotated Bibliography

Annotated Bibliography for Internet Addiction Sources

References

Cheng, C., & Yee-Iam Li, A. (2014). Internet addiction prevalence and quality of (real) life: A meta-analysis of 31 nations across seven world regions. Cyberpsychology, Behavior, and Social Networking, 17(12), 755-760. doi: 10.1089/cyber.2014.0317.

Cheng and Li performed meta-analysis of 80 research papers utilizing the Young Internet Addiction Test (IAT) or Young Diagnostic Questionnaire (YDQ) which were published between 1996 and 2012.  They sought to identify global prevalence of internet addiction (IA).  Their second goal was to identify if prevalence of IA fit either the Accessibility Hypothesis or the Quality of (Real) Life (QOL) Hypothesis.  The researchers provide a limited description of their methodology and analyses.   They conclude that there is approximately a 6% global prevalence of IA.  They conclude that the evidence tentatively supports the QOL hypothesis.  However, significant concerns exist within the reporting of this research.  Limitations of the IAT are not discussed at all.  The researchers note that African data was not included due to lack of information available.  Perhaps the most significant deficiency of this report is in how data was selected.  The researchers chose to evaluate research which was based on the IAT or YDQ.  They then determined to follow the definition of IA as developed by Young, who also developed the tests used.  No mention was made of the lack of consensus for defining IA, the lack of a “gold standard” assessment for IA, or the lack of consensus of the structure of IA.  These deficits limit the applicability of the study.  However, with consideration of the limitations of the study, the information provided by Cheng and Li suggests additional questions to ask regarding cause/origin of IA and begins to establish a base for comparing prevalence of IA across nations.

Kuss, D. J., Shorter, G. W., van Rooij, A. J., Griffiths, M. D., & Schoenmakers, T. M. (2014). Assessing internet addiction using the parsimonious internet addiction components model - A preliminary study. International Journal of Mental Health Addiction, 12, 351-366. doi:10.1007/s11469-013-9459-9.

Kuss et al. sought to provide statistical evidence for a behavioral components model of IA through use of a “two sample/two instrument” approach.  They utilized the Compulsive Internet Use Scale and the Assessment for Internet and Computer Game Addiction Scale.  One of their stated goals was to validate a model which can be used to screen for IA in clinical settings.  The description of the statistical analyses is comprehensive and may be confusing for individuals who are not fluent in statistical processes/jargon.  There is a comprehensive discussion of limitations of the study, such as bias of self-report items, limitations of the assessments utilized, populations utilized, etc.  Further, they suggest that it might be possible for a different model, other than the one proposed, to better fit the data.  However, their conclusion is that the proposed Griffiths’ addiction components model is a possible way to organize the behaviors evidenced in IA. This significance of this article is that the authors identify a model for IA, which is a foundational need for this field of research.  Lack of cohesive definition and structure of IA has been identified as a barrier to future research (Cheng & Li, 2014; Kuss, Shorter, van Rooij, Griffiths, & Schoenmakers, 2014; Laconi, Rodgers, & Chabrol, 2014; Lee, et al., 2012; Lortie & Guitton, 2013).

Laconi, S., Rodgers, R., & Chabrol, H. (2014). The measurement of internet addiction: A critical review of existing scales and their psychometric properties. Computers in Human Behavior, 41, 190-202. doi: 10.1016/j.chb.2015.04.056.

Laconi, Rodgers, and Chabrol reviewed 92 research manuscripts published between 1996 and 2013 in order to identify IA assessment tools.  They identified 45 assessment tools, which they then analyzed by various statistical processes.  The purpose of this research was to identify which scales had validated psychometric properties in order to address the lack of a “gold standard” assessment for IA.  Laconi et al. were detailed and precise in their discussion of methodology, requiring some knowledge of statistics for adequate understanding of the methodology section of the report.  However, each assessment tool also had a thorough verbal discussion of what the analyses indicated, which allows those who are not conversant in statistical terms to understand the relevance of the analyses.  Laconi et al. identified the IAT as the most frequently utilized assessment.  They discussed the several areas in which the assessment needs further development, including but not limited to, validation across ethnic groups, factor structure variance, small sample size utilized in validation tests, and outdated items.  They conclude that researchers should refrain from developing new assessments and instead focus upon thorough validation of the current tools in order to develop a gold standard.  The information in this article is essential to understanding the possible limitations of research based upon the assessments reviewed.

Lee, H., Choi, J.-S., Shin, Y.C., Lee, J.Y., Jung, H., & Kwon, J. (2012). Impulsivity in internet addiction: A comparison with pathological gambling. Cyberpsychology, Behavior, and Social Networking, 15(7), 373-377. doi: 10.1089/cyber.2012.0063.

Lee et al. consider in how IA compares to pathological gambling through consideration of the trait of impulsivity.  They hypothesized that increased impulsivity would be seen in both individuals diagnosed with IA and with pathological gambling.  They utilized the IAT, Korean Version, as well as an assessment to measure gambling and an assessment to measure impulsivity.  They elected to use a cut-off more stringent than the arbitrary one indicated by Young for differentiating between excessive use and IA.  The authors state that this is the first, to their knowledge, study to measure and compare the trait of impulsivity between IA and pathological gambling.  Interestingly, when discussion their results they included physical correlates of addiction (ex. Abnormal glucose metabolism in the brain) and explained that such brain abnormalities are observed in people experiencing other addictions.  They conclude that their study confirms IA can be considered an impulse control disorder.  Sample size is discussed by the authors as a limitation which impacts generalizability.  Whether the study shows correlation or causation is also an area for future research.  The value of this study is that it provides a specific factor (impulsivity) which has some relationship with IA.  Further, the authors suggest future studies include neurobiological data to assess properties of IA as an addiction disorder. 

Lortie, C. L., & Guitton, M. J. (2013). Internet addiction assessment tools: dimensional structure and methodological status. Addiction, 108, 1207-1216. doi: 10.1111/add.12202.

Lortie and Guitton evaluated 14 different questionnaires for identifying IA and which were contained within 360 papers published between 1993 and 2011.  The authors evaluated the assessments for how well factors of IA were evaluated in order to determine the structure of IA.  Their stated purpose was to suggest improvements to the questionnaires in order to better encompass the structure/conceptualization of the disorder.  While the authors conclude that no one assessment is able to be recommended over the others, they found most questionnaires were valid in assessing excessive internet use and the consequences thereof.  However, they also found that most questionnaires lacked validated cut-off points, lacked adequate differentiation between normal users of the internet and pathological users of the internet, and are based on self-report data which has been shown to often include bias.  Further, they state that the lack of predictive properties of the questionnaires is a significant concern about the usefulness of these tools.  This article contributes to the body of literature in evaluating how well the 14 assessments reveal factors of IA.  However, while the assessments are analyzed, this paper is most relevant in illuminating how IA may or may not be structured.  The researchers call for differentiation between heavy users and pathological users, which is significant when discussing what is addiction and what is not.  This article, when combined with the information from Laconi et al (2014), provides a good foundation for understanding the strengths and weaknesses of the extant assessment tools.

NA. (2015a, December). Article: Impulsivity in internet addiction: a comparison with pathological gambling. Retrieved from http://www.researchgate.net/publication/225183971_Impulsivity_in_Internet_Addiction_A_Comparison_with_Pathological_Gambling

These items (the preceding entry and the 2 following entries) retrieved from researchgate.net are relevant in that they provide metrics showing the impact factor of the selected articles – which indicates frequency of citation of the articles in the journals.  This is a number which can be utilized to assess comparative visibility of articles and how often one article has been cited compared to other articles.  While impact factor is not the only criteria by which to evaluate value of the article, it is a place at which to begin evaluation.

NA. (2015b, December). Article: Internet addiction assessment tools: Dimensional structure and methodological status. Retrieved from http://www.researchgate.net/publication/236652610_Internet_addiction_assessment_tools_Dimensional_structure_and_methodological_status

NA. (2015c, December). Article: Assessing internet addiction using the parsimonious internet addiction components model - a preliminary study. Retrieved from http://www.researchgate.net/publication/257473225_Assessing_Internet_Addiction_Using_the_Parsimonious_Internet_Addiction_Components_Model-A_Preliminary_Study

OReilly, M. (June 15, 1996). Internet addiction: A new disorder enters the medical lexicon. CMAJ: Canadian Medical Association Journal = Journal De L'association Medicale Canadienne [serial online].154(12), 1882-1883.

This article is relevant in that it is the first scholarly article identified through Roadrunner database search with the term “Internet Addiction”.  Further, the article describes how Dr. Young developed criteria for IA and notes that Young had developed an assessment tool.  This tool was later (in 1998) published at the Young Internet Addiction Test.  While the article does not contain research, it’s value lies in the historical value of establishing when IA emerged as a concern for researchers to explore.