Psychometric Properties of the Internet Addiction Test Among Historically Black University Students

Background and Purpose:The Internet has brought huge innovative changes in many areas including social work education, and with the rapid advancement of a technology such as a smartphone and tablet, its accessibility has been expanded almost everywhere. Despite many benefits the Internet has brought to students, emerging studies have reported the negative effects of problematic Internet use among college students (Ozdemir, Kuzucu, & Ak, 2014). Since Internet Addiction Test (IAT) was created by Young (1996), many studies utilized this measure to examine whether the Internet use of college students is problematic. However, there are just few studies about the Internet use in Historically Black Colleges and University (HBCU) students, and the results of studies about psychometric properties of IAT vary depending on the sample characteristics (Widyanto & McMurran 2004; Lai et al., 2013). This study investigated alternative factor structure using explanatory factor analyses (EFA) among HBCU students. 

 

Methods: Data were collected from a cross-sectional survey using a convenience and purposive sampling. A total of 322 undergraduate and graduate students in a Historically Black University participated in this study. The participants were mostly female students (80.7%) with a mean age of 23.4 (SD=6.54). Majority of participants (71.7%) were undergraduate students, and 10.6% reported they are married or cohabit with someone. About 60% of participants were fulltime or part time employees, and 53.2% of participants had an annual household income below $25,500.

Results: Bartlett’s test of sphericity indicated that this data set is appropriate for factor analysis (χ²= 3573.593,  p<.001), and Kaiser-Meyer-Olkin Measure of Sampling Adequacy indicated a value of .938, which showed that the degree of common variance is good. The factors loading for each item are all greater than the cutoff point ( <.4), and 20 items are retained in the final model. The three factors were generated from the IAT when using a basic scree-test and eigenvalue at <1.0 criteria: Problem in Time Management, Problem in Relationships and Social life, and Problem in Performance. These three factors which were rotated to position of maximum orthogonality in five iterations, explain 61% of variances. While the structure with three factors is similar to Lai et al.’s model (2013), a slight different structure emerged depending on the differences in factor loadings for some items. Internal consistency for each of the scales was examined using Cronbach’s alpha. The alphas were good:.75 for Problem in Performance (4 items), .82 for Problem in Time Management (5 items), and .92 for Problem in Relationship and Social Life (11 items).

Conclusions and Implications: The findings suggest that psychometric properties of IAT may vary by the sample characteristics and in order to examine the problematic Internet use among HBCU students with accuracy, empirical evaluation of the measure should precede further studies. Furthermore, future studies need to investigate how underlying structures of IAT vary depending on sample characteristics and try efforts to create alternative measures to examine the problematic Internet use with more accuracy.