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Young İnternet Bağımlılığı Testinin Boyutluluğunun Üniversite Öğrencileri İçin Mokken Ölçek Analizi Kullanılarak İncelenmesi

Year 2023, Volume: 23 Issue: 2, 542 - 558, 15.06.2023
https://doi.org/10.17240/aibuefd.2023..-923848

Abstract

İnternet Bağımlılığı Testi (İBT), araştırmacılar tarafından üniversite öğrencilerinden veri toplamak için yoğun bir şekilde kullanılmaktadır, ancak netleştirilmesi gereken bazı belirsizlikler mevcuttur. Gerçekte, İnternet Bağımlılığı Testinin psikometrik özellikleri üzerine yapılan görgül araştırmalar, faktör yapısı üzerinde çelişkili sonuçlar sağlamıştır. İnternet bağımlılığının yapısı genel olarak tek boyutlu olarak kabul edilmekle birlikte, bu çelişkili sonuçlar yapının tek boyutlu doğası için daha fazla kanıt gerektirmektedir. Benzer kafa karışıklığı, İnternet Bağımlılığı Testinin kısa formu için de geçerlidir. Parametrik olmayan Madde Tepki Kuramına dayalı geniş analiz ailesinin bir üyesi olan Mokken Ölçeklendirme Analizi, bir ölçüm aracının her bir maddesinin aynı temel özelliği ölçüp ölçmediğini ve homojen küme oluşturup oluşturmadığını değerlendirmek için kullanılabilir. İnternet Bağımlılığı Testi kısa formunun faktör yapısına ilişkin mevcut kafa karışıklıkları göz önüne alındığında, bu çalışmanın amacı Kısa İnternet Bağımlılığı Testinin Türk Üniversite Öğrencileri için faktör yapısını değerlendirmektir. İnternet Bağımlılığı Testi kısa formu, bir çevrimiçi veri toplama platformu üzerinden 636 üniversite öğrencisine uygulanmıştır. Katılımcıların yaşları 20 ile 65 arasında değişmektedir. Sonuçlar, İnternet Bağımlılığı Testi Kısa Formunun maddelerinin ölçeklenebilirlik özelliğine sahip olduğunu ve ayrı bir ölçek oluşturmaya yetecek kadar homojen olduğunu ortaya koymuştur. Öte yandan sonuçlar, İnternet Bağımlılığı Testi Kısa Formunun Değişmez Madde Sıralama özelliğine sahip olmadığını göstermiştir. Ayrıca, geriye doğru seçim yöntemi kullanılarak, Değişmez Madde Sıralama özelliği taşıyan İnternet Bağımlılığı Testi Kısa Formunun yedi maddelik formu önerilmiştir. Bu sonuçlar, internet bağımlılığının yapısının Türk üniversite öğrencileri için tek boyutlu olarak kabul edilebileceğini göstermiştir. Gelecekteki yürütülecek çalışmalarda farklı evrenlerin kullanılması önerilmektedir.

References

  • Akansel, N., Watson, R., Aydin, N., Özdemir, A. (2013). Mokken scaling of the Caring Dimensions Inventory (CDI-25). Journal of Clinical Nursing, 22(13-14), 1818-1826. https://doi.org/10.1111/j.1365-2702.2012.04068.x
  • Amin, L., Rosenbaum, P.L., Barr, R., Sung, L.G., Klaassen, R.J., Dix, D.B., & Klassen, A.F. (2012). Rasch analysis of the PedsQL: an increased understanding of the properties of a rating scale. Journal of clinical epidemiology, 65(10), 1117-23. https://doi.org/10.1016/j.jclinepi.2012.04.014
  • Bagnasco, A., Watson, R., Zanini, M., Rosa, F., Rocco, G., & Sasso, L. (2015). Preliminary testing using Mokken scaling of an Italian translation of the Edinburgh Feeding Evaluation in Dementia (EdFED-I) scale. Applied Nursing Research, 28(4), 391-396. https://doi.org/10.1016/j.apnr.2015.02.003
  • Boysan, M., Kuss, D.J., Barut, Y., Ayköse, N., Güleç, M., & Özdemir, O. (2017). Psychometric properties of the Turkish version of the Internet Addiction Test (IAT). Addictive behaviors, 64, 247-252 .
  • Černja, I., Vejmelka, L., & Rajter, M. (2019). Internet Addiction Test: Croatian preliminary study. BMC Psychiatry, 19, Article 388. https://doi.org/10.1186/s12888-019-2366-2
  • Davis, R. A. (2001). A Cognitive-Behavioral Model of Pathological Internet Use. Computers in Human Behavior, 17(2), 187-195. https://doi.org/10.1016/S0747-5632(00)00041-8
  • Embretson, S. E., & Reise, S. P. (2000). Multivariate Applications Books Series. Item response theory for psychologists. Lawrence Erlbaum Associates Publishers.
  • Faraci, P., Craparo, G., Messina, R., & Severino, S. (2013). Internet Addiction Test (IAT): which is the best factorial solution?. Journal of medical Internet research, 15(10), e2935. https://doi.org/10.2196/jmir.2935
  • Ferraro, G., Caci, B., D'amico, A., & Blasi, M. D. (2006). Internet addiction disorder: an Italian study. CyberPsychology & Behavior, 10(2), 170-175.
  • Finseras, T. R., Pallesen, S., Mentzoni, R. A., Krossbakken, E., King, D. L., & Molde, H. (2019). Evaluating an Internet Gaming Disorder Scale Using Mokken Scaling Analysis. Frontiers in psychology, 10, 911. https://doi.org/10.3389/fpsyg.2019.00911
  • Glass, G. V., & Hopkins, K. D. (1984). Statistical methods in education and psychology. Prentice-Hall. Guttman, L. (1949). The basis for scalogram analysis. Bobbs-Merrill.
  • Kaya, F., Delen, E., & Young, K. S. (2016). Psychometric properties of the Internet Addiction Test in Turkish. Journal of behavioral addictions, 5(1), 130–134. https://doi.org/10.1556/2006.4.2015.042
  • Kutlu, M., Savcı M., Demir, Y., & Aysan, F. (2016). Young İnternet Bağımlılığı Testi Kısa Formunun Türkçe uyarlaması: Üniversite öğrencileri ve ergenlerde geçerlilik ve güvenilirlik çalışması. Anadolu Psikiyatri Dergisi, 17(Ek 1), 69-76. https://doi.org/10.5455/apd.190501
  • Ligtvoet, R., L. A. van der Ark, J. M. te Marvelde & K. Sijtsma (2010). Investigating an invariant item ordering for polytomously scored items. Educational and Psychological Measurement, 70, 578-595. https://doi.org/10.1177/0013164409355697
  • Ligtvoet, R., van der Ark, L. A., te Marvelde, J. M., & Sijtsma, K. (2010). Investigating an invariant item ordering for polytomously scored items. Educational and Psychological Measurement, 70(4), 578–595. https://doi.org/10.1177/0013164409355697
  • Loevinger, J. (Ed.). (1947). A systematic approach to the construction and evaluation of tests of ability. Psychological Monographs, 61(4), i–49. https://doi.org/10.1037/h0093565
  • Mokken R.J. (1971). A theory and procedure of scale analysis: with applications in political research. In: Methods and models in the social sciences. De Gruyter Mouton.
  • Molenaar I.W. & Sijtsma K. (2000). MSP5 for Windows. iec ProGAMMA.
  • Molenaar I.W. (2002) Parametric and Nonparametric Item Response Theory Models in Health Related Quality of Life Measurement. In: Mesbah M., Cole B.F., Lee ML.T. (eds) Statistical Methods for Quality of Life Studies. Springer, Boston, MA
  • Molenaar, I. W. (1982). Mokken scaling revisited. Kwantitatieve Methoden, 3(8), 145-164.
  • Ostini, R., & Nering, M. L. (2006). Polytomous item response theory models (No. 144). Sage.
  • Pawlikowski, M., Altstötter-Gleich, C., & Brand, M. (2013). Validation and psychometric properties of a short version of Young’s Internet Addiction Test. Computers in Human Behavior, 29(3), 1212-1223. https://doi.org/10.1016/j.chb.2012.10.014
  • R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
  • Sijtsma, K., & Ark, L.A. (2017). A tutorial on how to do a Mokken scale analysis on your test and questionnaire data. The British journal of mathematical and statistical psychology, 70(1), 137-158. https://doi.org/10.1111/bmsp.12078
  • Sijtsma, K., & Junker, B. W. (1996). A survey of theory and methods of invariant item ordering. British Journal of Mathematical and Statistical Psychology, 49(1), 79-105. https://doi.org/10.1111/j.2044-8317.1996.tb01076.x
  • Sijtsma, K., & Meijer, R. R. (1992). A method for investigating the intersection of item response functions in Mokken's nonparametric IRT model. Applied Psychological Measurement, 16(2), 149–157. https://doi.org/10.1177/014662169201600204
  • Sijtsma, K., & Molenaar, I. W. (2002). Measurement Methods for the Social Science: Introduction to nonparametric item response theory. SAGE Publications, Inc.
  • Sijtsma, K., Emons, W. H., Bouwmeester, S., Nyklícek, I., & Roorda, L. D. (2008). Nonparametric IRT analysis of Quality-of-Life Scales and its application to the World Health Organization Quality-of-Life Scale (WHOQOL-Bref). Quality of life research: an international journal of quality of life aspects of treatment, care and rehabilitation, 17(2), 275-290. https://doi.org/10.1007/s11136-007-9281-6
  • Sijtsma, K., van der Ark, L. A. & Straat, J. H. (2015) Goodness of fit methods for nonparametric IRT models. In L. A. van der Ark, D. M. Bolt, W.-C. Wang, J. Douglas & S.-M. Chow (Eds.), Quantitative psychology research: The 79th Annual Meeting of the Psychometric Society, Madison, Wisconsin, 2014. (pp. 109 - 120). Springer.
  • Stochl, J., Jones, P. B., & Croudace, T. J. (2012). Mokken scale analysis of mental health and well-being questionnaire item responses: a non-parametric IRT method in empirical research for applied health researchers. BMC medical research methodology, 12(1), 1-16. https://doi.org/10.1186/1471-2288-12-74
  • Straat, J. H., Van der Ark, L. A. & Sijtsma, K. (2013). Comparing optimization algorithms for item selection in Mokken scale analysis. Journal of Classification, 30, 72-99. https://doi.org/10.1007/s00357-013-9122-y
  • Straat, J. H., Van der Ark, L. A. & Sijtsma, K. (2016). Using conditional association to identify locally independent item sets. Methodology, 12, 117-123. https://doi.org/10.1027/1614-2241/a000115
  • Streiner D & Norman G. (2008). Health Measurement Scales: A Practical Guide to Their Development and Use. (4th ed.). Oxford University Press.
  • Thompson, D. R., & Watson, R. (2011). Mokken scaling of the Myocardial Infarction Dimensional Assessment Scale (MIDAS). Journal of evaluation in clinical practice, 17(1), 156–159. https://doi.org/10.1111/j.1365-2753.2010.01415.x
  • Van der Ark L. A. (2007). Mokken Scale Analysis in R. Journal of Statistical Software, 20(11), 1-19.
  • Van Schuur, W. (2003). Mokken scale analysis: between the Guttman scale and parametric item response theory. Political Analysis, 11(2), 139-163. https://doi.org/10.1093/pan/mpg002
  • Watson, R., Wang, W., Ski, C. F., & Thompson, D. R. (2012). The Chinese version of the Myocardial Infarction Dimensional Assessment Scale (MIDAS): Mokken scaling. Health and quality of life outcomes, 10, 2. https://doi.org/10.1186/1477-7525-10-2
  • Xin, M., Xing, J., Pengfei, W., Houru, L., Mengcheng, W. & Hong, Z. (2018). Online activities, prevalence of ınternet addiction and risk factors related to family and school among adolescents in China. Addictive Behaviors Reports, 7, 14-18. https://doi.org/10.1016/j.abrep.2017.10.003
  • Young, K. S. (1996). Internet addiction: the emergence of a new clinical disorder. CyberPsychology & Behavior, 1, 237-244. https://doi.org/10.1089/cpb.1998.1.237
  • Young, K. S. (1998). Caught in the net: How to Recognize the signs of internet addiction and a winning strategy for recovery. John Wiley & Sons.
  • Zhang, J., & Xin, T. (2013). Measurement of internet addiction: an item response analysis approach. Cyberpsychology, behavior and social networking, 16(6), 464–468. https://doi.org/10.1089/cyber.2012.0525

Investigating the Dimensionality of Young’s Internet Addiction Test for University Students Using Mokken Scale Analysis

Year 2023, Volume: 23 Issue: 2, 542 - 558, 15.06.2023
https://doi.org/10.17240/aibuefd.2023..-923848

Abstract

The Internet Addiction Test has been used extensively by researchers to collect data from university students, However, empirical studies on the psychometric properties of this test have revealed conflicting results on the factor structure. Although the structure of Internet addiction is generally accepted as unidimensional, these contradictory results require further evidence for the unidimensional nature of the construct. Considering the existing problems regarding the factor structure of the Internet Addiction construct, the aim of this study was set as evaluating the unidimensionality of the Short Internet Addiction Test for University Students by using Mokken Scaling Analysis. The Internet Addiction Test short form was administered to 636 university students studying in Turkey in the 2020-21 academic year via an online data collection platform. The ages of the participants ranged from 20 to 65. The results revealed that the items of the Internet Addiction Test Short Form were scalable and homogeneous enough to form a separate scale. On the other hand, the results showed that the Internet Addiction Test Short Form did not have the Invariant Item Ranking feature. In addition, using the backward selection method, a seven-item form of the Internet Addiction Test Short Form, which has Invariant Item Ordering feature, is proposed. These results showed that the structure of internet addiction can be accepted as one-dimensional for Turkish university students. It is recommended to examine whether the results obtained in future studies can be generalized to different universes.
Keywords: Mokken scaling analysis, internet addiction, dimensionality, university students.

References

  • Akansel, N., Watson, R., Aydin, N., Özdemir, A. (2013). Mokken scaling of the Caring Dimensions Inventory (CDI-25). Journal of Clinical Nursing, 22(13-14), 1818-1826. https://doi.org/10.1111/j.1365-2702.2012.04068.x
  • Amin, L., Rosenbaum, P.L., Barr, R., Sung, L.G., Klaassen, R.J., Dix, D.B., & Klassen, A.F. (2012). Rasch analysis of the PedsQL: an increased understanding of the properties of a rating scale. Journal of clinical epidemiology, 65(10), 1117-23. https://doi.org/10.1016/j.jclinepi.2012.04.014
  • Bagnasco, A., Watson, R., Zanini, M., Rosa, F., Rocco, G., & Sasso, L. (2015). Preliminary testing using Mokken scaling of an Italian translation of the Edinburgh Feeding Evaluation in Dementia (EdFED-I) scale. Applied Nursing Research, 28(4), 391-396. https://doi.org/10.1016/j.apnr.2015.02.003
  • Boysan, M., Kuss, D.J., Barut, Y., Ayköse, N., Güleç, M., & Özdemir, O. (2017). Psychometric properties of the Turkish version of the Internet Addiction Test (IAT). Addictive behaviors, 64, 247-252 .
  • Černja, I., Vejmelka, L., & Rajter, M. (2019). Internet Addiction Test: Croatian preliminary study. BMC Psychiatry, 19, Article 388. https://doi.org/10.1186/s12888-019-2366-2
  • Davis, R. A. (2001). A Cognitive-Behavioral Model of Pathological Internet Use. Computers in Human Behavior, 17(2), 187-195. https://doi.org/10.1016/S0747-5632(00)00041-8
  • Embretson, S. E., & Reise, S. P. (2000). Multivariate Applications Books Series. Item response theory for psychologists. Lawrence Erlbaum Associates Publishers.
  • Faraci, P., Craparo, G., Messina, R., & Severino, S. (2013). Internet Addiction Test (IAT): which is the best factorial solution?. Journal of medical Internet research, 15(10), e2935. https://doi.org/10.2196/jmir.2935
  • Ferraro, G., Caci, B., D'amico, A., & Blasi, M. D. (2006). Internet addiction disorder: an Italian study. CyberPsychology & Behavior, 10(2), 170-175.
  • Finseras, T. R., Pallesen, S., Mentzoni, R. A., Krossbakken, E., King, D. L., & Molde, H. (2019). Evaluating an Internet Gaming Disorder Scale Using Mokken Scaling Analysis. Frontiers in psychology, 10, 911. https://doi.org/10.3389/fpsyg.2019.00911
  • Glass, G. V., & Hopkins, K. D. (1984). Statistical methods in education and psychology. Prentice-Hall. Guttman, L. (1949). The basis for scalogram analysis. Bobbs-Merrill.
  • Kaya, F., Delen, E., & Young, K. S. (2016). Psychometric properties of the Internet Addiction Test in Turkish. Journal of behavioral addictions, 5(1), 130–134. https://doi.org/10.1556/2006.4.2015.042
  • Kutlu, M., Savcı M., Demir, Y., & Aysan, F. (2016). Young İnternet Bağımlılığı Testi Kısa Formunun Türkçe uyarlaması: Üniversite öğrencileri ve ergenlerde geçerlilik ve güvenilirlik çalışması. Anadolu Psikiyatri Dergisi, 17(Ek 1), 69-76. https://doi.org/10.5455/apd.190501
  • Ligtvoet, R., L. A. van der Ark, J. M. te Marvelde & K. Sijtsma (2010). Investigating an invariant item ordering for polytomously scored items. Educational and Psychological Measurement, 70, 578-595. https://doi.org/10.1177/0013164409355697
  • Ligtvoet, R., van der Ark, L. A., te Marvelde, J. M., & Sijtsma, K. (2010). Investigating an invariant item ordering for polytomously scored items. Educational and Psychological Measurement, 70(4), 578–595. https://doi.org/10.1177/0013164409355697
  • Loevinger, J. (Ed.). (1947). A systematic approach to the construction and evaluation of tests of ability. Psychological Monographs, 61(4), i–49. https://doi.org/10.1037/h0093565
  • Mokken R.J. (1971). A theory and procedure of scale analysis: with applications in political research. In: Methods and models in the social sciences. De Gruyter Mouton.
  • Molenaar I.W. & Sijtsma K. (2000). MSP5 for Windows. iec ProGAMMA.
  • Molenaar I.W. (2002) Parametric and Nonparametric Item Response Theory Models in Health Related Quality of Life Measurement. In: Mesbah M., Cole B.F., Lee ML.T. (eds) Statistical Methods for Quality of Life Studies. Springer, Boston, MA
  • Molenaar, I. W. (1982). Mokken scaling revisited. Kwantitatieve Methoden, 3(8), 145-164.
  • Ostini, R., & Nering, M. L. (2006). Polytomous item response theory models (No. 144). Sage.
  • Pawlikowski, M., Altstötter-Gleich, C., & Brand, M. (2013). Validation and psychometric properties of a short version of Young’s Internet Addiction Test. Computers in Human Behavior, 29(3), 1212-1223. https://doi.org/10.1016/j.chb.2012.10.014
  • R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
  • Sijtsma, K., & Ark, L.A. (2017). A tutorial on how to do a Mokken scale analysis on your test and questionnaire data. The British journal of mathematical and statistical psychology, 70(1), 137-158. https://doi.org/10.1111/bmsp.12078
  • Sijtsma, K., & Junker, B. W. (1996). A survey of theory and methods of invariant item ordering. British Journal of Mathematical and Statistical Psychology, 49(1), 79-105. https://doi.org/10.1111/j.2044-8317.1996.tb01076.x
  • Sijtsma, K., & Meijer, R. R. (1992). A method for investigating the intersection of item response functions in Mokken's nonparametric IRT model. Applied Psychological Measurement, 16(2), 149–157. https://doi.org/10.1177/014662169201600204
  • Sijtsma, K., & Molenaar, I. W. (2002). Measurement Methods for the Social Science: Introduction to nonparametric item response theory. SAGE Publications, Inc.
  • Sijtsma, K., Emons, W. H., Bouwmeester, S., Nyklícek, I., & Roorda, L. D. (2008). Nonparametric IRT analysis of Quality-of-Life Scales and its application to the World Health Organization Quality-of-Life Scale (WHOQOL-Bref). Quality of life research: an international journal of quality of life aspects of treatment, care and rehabilitation, 17(2), 275-290. https://doi.org/10.1007/s11136-007-9281-6
  • Sijtsma, K., van der Ark, L. A. & Straat, J. H. (2015) Goodness of fit methods for nonparametric IRT models. In L. A. van der Ark, D. M. Bolt, W.-C. Wang, J. Douglas & S.-M. Chow (Eds.), Quantitative psychology research: The 79th Annual Meeting of the Psychometric Society, Madison, Wisconsin, 2014. (pp. 109 - 120). Springer.
  • Stochl, J., Jones, P. B., & Croudace, T. J. (2012). Mokken scale analysis of mental health and well-being questionnaire item responses: a non-parametric IRT method in empirical research for applied health researchers. BMC medical research methodology, 12(1), 1-16. https://doi.org/10.1186/1471-2288-12-74
  • Straat, J. H., Van der Ark, L. A. & Sijtsma, K. (2013). Comparing optimization algorithms for item selection in Mokken scale analysis. Journal of Classification, 30, 72-99. https://doi.org/10.1007/s00357-013-9122-y
  • Straat, J. H., Van der Ark, L. A. & Sijtsma, K. (2016). Using conditional association to identify locally independent item sets. Methodology, 12, 117-123. https://doi.org/10.1027/1614-2241/a000115
  • Streiner D & Norman G. (2008). Health Measurement Scales: A Practical Guide to Their Development and Use. (4th ed.). Oxford University Press.
  • Thompson, D. R., & Watson, R. (2011). Mokken scaling of the Myocardial Infarction Dimensional Assessment Scale (MIDAS). Journal of evaluation in clinical practice, 17(1), 156–159. https://doi.org/10.1111/j.1365-2753.2010.01415.x
  • Van der Ark L. A. (2007). Mokken Scale Analysis in R. Journal of Statistical Software, 20(11), 1-19.
  • Van Schuur, W. (2003). Mokken scale analysis: between the Guttman scale and parametric item response theory. Political Analysis, 11(2), 139-163. https://doi.org/10.1093/pan/mpg002
  • Watson, R., Wang, W., Ski, C. F., & Thompson, D. R. (2012). The Chinese version of the Myocardial Infarction Dimensional Assessment Scale (MIDAS): Mokken scaling. Health and quality of life outcomes, 10, 2. https://doi.org/10.1186/1477-7525-10-2
  • Xin, M., Xing, J., Pengfei, W., Houru, L., Mengcheng, W. & Hong, Z. (2018). Online activities, prevalence of ınternet addiction and risk factors related to family and school among adolescents in China. Addictive Behaviors Reports, 7, 14-18. https://doi.org/10.1016/j.abrep.2017.10.003
  • Young, K. S. (1996). Internet addiction: the emergence of a new clinical disorder. CyberPsychology & Behavior, 1, 237-244. https://doi.org/10.1089/cpb.1998.1.237
  • Young, K. S. (1998). Caught in the net: How to Recognize the signs of internet addiction and a winning strategy for recovery. John Wiley & Sons.
  • Zhang, J., & Xin, T. (2013). Measurement of internet addiction: an item response analysis approach. Cyberpsychology, behavior and social networking, 16(6), 464–468. https://doi.org/10.1089/cyber.2012.0525
There are 41 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Akif Avcu 0000-0003-1977-7592

Publication Date June 15, 2023
Submission Date April 20, 2021
Published in Issue Year 2023 Volume: 23 Issue: 2

Cite

APA Avcu, A. (2023). Investigating the Dimensionality of Young’s Internet Addiction Test for University Students Using Mokken Scale Analysis. Abant İzzet Baysal Üniversitesi Eğitim Fakültesi Dergisi, 23(2), 542-558. https://doi.org/10.17240/aibuefd.2023..-923848