تحلیل پرسشنامه "اعتیاد به شبکه‌های اجتماعی مبتنی بر موبایل" با استفاده از مدل راش

محورهای موضوعی : تکتونواستراتیگرافی

شیما حسینی ¹ (دانشجوی کارشناسی ارشد سنجش و اندازه‌گیری (روانسنجی)، گروه روانشناسی، دانشکده روانشناسی، دانشگاه آزاد اسلامی واحد الکترونیکی،)
زهرا نقش ² (دکترای روانشناسی تربیتی، استادیار دانشگاه تهران، تهران، ایران.)
اعظم مقدم ³ (دانشگاه علامه طباطبایی، تهران)

تاریخ دریافت : 1399/02/09 تاریخ پذیرش : 1399/04/30 تاریخ انتشار : 1399/03/01

کلید واژه: اعتیاد به شبکه‌های اجتماعی, مدل مقیاس رتبه‌بندی راش-اندریچ (RSM), نظریه سوال-پاسخ,

چکیده مقاله :

هدف پژوهش حاضر تحلیل پرسشنامه "اعتیاد به شبکه‌های اجتماعی مبتنی بر موبایل" با استفاده از مدل اندازه‌گیری راش بود. جامعه مورد بررسی دانش‌آموزان مقطع متوسطه دوم و نمونه انتخابی، مشتمل بر 345 نفر با شیوه انتخاب در دسترس بود. ابزار مورد بررسی پرسشنامه اعتیاد به شبکه‌های اجتماعی مبتنی بر موبایل بوده که توسط خواجه احمدی و همکاران (1395) تدوین گردید. روش‌ استفاده شده جهت تحلیل ابزار، مدل مقیاس رتبه­بندی راش-اندریچ (RSM) برای سوالات چندارزشی مبتنی بر نظریه سوال-پاسخ بود. نرم‌افزارهای مورد استفاده SPSS-25، jMetric-4 و winsteps بود. یافته‌ها نشان داد در صورتی که هر مولفه یک بُعد جداگانه در نظر گرفته شود، این پرسشنامه از مدل تک‌بعدی پیروی می‌کند و با استفاده از مدل مقیاس رتبه­بندی راش-اندریچ، دارای برازش مطلوب می‌باشد. همچنین پایایی ابزار نیز با استفاده از شاخص­های جداسازی فرد و سوال سنجیده شد. علاوه بر این شاخص جداسازی فرد و سوال و ضریب اعتبار نیز به مقدار مطلوب حاصل شد.

چکیده انگلیسی:

The aim of the present study was to analyze the "Addiction to Mobile-Based Social Networks" questionnaire using the Rasch measurement model. The study population of secondary school students. the sample selected included 345 people with the available method of selection. The study instrument was a mobile-based social network addiction questionnaire developed by Khajeh Ahmadi et al. (2016). The methods used for the analysis were one-dimensional partial validity of the Rush family model. The software used was spss version 25, winsteps and jMetric version 4. The findings showed that 2 questions 17 and 21 were inappropriate at the selected sample level, but the other 21 questions in this questionnaire followed the one dimensional model and had the desired fit. The reliability of the instrument was also measured using PSI and compared with the common method of measuring this index in CTT, which is the alpha coefficient, which showed more favorable results.

منابع و مأخذ:

Allen DD, Wilson M. (2006). Introducing multidimensional item response modeling in health behavior and health education research. Health Educ Res. 21(1):73-84.

Allen, M. J., & Yen, W. M. (1979). Introduction to measurement theory. Monterey, CA: Brooks/Cole.

Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43(4), 561-573. doi: 10.1007/bf02293814

Assunção, R. S., & Matos, P. M. (2017). The generalized problematic internet use scale 2: Validation and test of the model to Facebook use. Journal of Adolescence, 54, 51–59. http:// dx.doi.org/ 10.1016/ j.adolescence. 2016. 11.007.

Baghaei, p., Amrahi, N. (2011).  Validation of Multiple Choice English Vocabulary Test with the Rasch Model. Journal of Language Teaching and Research, Vol. 2, No. 5, pp. 1052-1060.

Barat Dastjerdi N, Sayadi S. (2013). Relationship between using social networks and internet addiction and depression among students. J Res Behav Sci. 10(5):332-41.

Bond, T., & Fox, C. M. (2015). Applying the Rasch model: Fundamental measurement in the human sciences. London: Routledge.

Bond, T., & Fox, C. M. (2015). Applying the Rasch model: Fundamental measurement in the human sciences. London: Routledge.

Caci, B., Cardaci, M., Scrima, F., & Tabacchi, M. E. (2017). The dimensions of Facebook addiction as measured by Facebook addiction Italian questionnaire and their relationships with individual differences. Cyberpsychology, Behavior and Social Networking, 20, 251–258. http:// dx.doi.org/ 10.1089/ cyber. 2016.0073.

Caplan, S. E. (2003). Preference for online social interaction. Communication Research, 30, 625–648. http://dx.doi.org/10.1177/0093650203257842.

Casale, S., Tella, L., & Fioravanti, G. (2013). Preference for online social interactions among young people: Direct and indirect effects of emotional intelligence. Personality and Individual Differences, 54, 524–529. http://dx.doi.org/10.1016/j.paid.2012.10. 023.

Chung, J. E. (2013). Social interaction in online support groups: Preference for online social interaction over offline social interaction. Computers in Human Behavior, 29, 1408–1414. http://dx.doi.org/10.1016/j.chb.2013.01.019.

Dong T, Cheng N. Wu, Y. J. (2014). A study of the social networking website service in digital content industries: The Face book case in Taiwan. Comput Hum Behv. 2014; (30):708-714.

Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Mahwah, NJ: Lawrence Erlbaum

Falahi A, Atif K, Elnaffar Y. (2010). International conference on green computing and communications. Proceedingsof the IEEE/ACM International Conference on Cyber, Physical and Social Computing (CPSCom 2010); 2010 Oct30-Nov 1;

Fioravanti, G., Dèttore, D., & Casale, S. (2012). Adolescent internet addiction: Testing the association between self-esteem, the perception of internet attributes, and preference for online social interactions. Cyberpsychology, Behavior and Social Networking, 15, 318–323. http://dx.doi.org/ 10.1089/ cyber.2011.0358.

Internet World Stats - Usage and Population Statistics 2016 [updated 2016; cited 2016]. Available from: www.internetworldstats.com.

Javadinia A, Erfanian M, Abedini MR, Askari M, Abbasi A, Bijari B. (2010). Pattern of Social Networking Sites Usage among Students of Birjand University of Medical Sciences. Teb Tazkiye. 22(2):39-44.

Khajeh Ahmadi, M., Pouladi, Sh., Bahreyni, M. (2016). Design Psychometric Questionnaire for Mobile-Based Social Networks, Journal of Nurse Psychology, 4 (4): 43-51.

Kuss, D. J., & Griffiths, M. D. (2017). Social networking sites and addiction: Ten lessons learned. International Journal of Environmental Research and Public Health, 14, 311. http://dx.doi.org/10.3390/ijerph14030311.

Lee, J, Lee H. (2010). The Computer- Mediated Communication Network: Exploring the Linkage between the Online Community and Social Capital”, New Media and So. (5): 12.

Licare, (2019). J.M. Winsteps (Version 4.3.3). Chicago IL: Winsteps.

Linacre, J. M. (1998a). Detecting multidimensionality: Which residual data-type works best? Journal of Outcome Measurement, 2, 266-283.

Linacre, J.M. (2020). A user’s guide to WINSTEPS. Chicago, IL: Winsteps.com.

Marino, C., Vieno, A., Altoè, G., & Spada, M. M. (2016). Factorial validity of the problematic Facebook use scale for adolescents and young adults. Journal of Behavioral Addictions, 6, 5–10.

McKnight D H, Chervany N L. (2006). Reflections on an initial trust-building model. Handbook of trust research. 29-51.

Messick, S. (1995). Validity of psychological assessment: Validation of inferences from persons’ responses and performances as scientific inquiry into score meaning. American Psychologist, 50, 741–749.

Nikpoor T. (2014). The Effect of Cellphone Oriented Social Networks Usage and its Relationship to Individuals’ Religiosity: Soore University Department of Culture and Communication.

Phanasathit, M., Manwong, M., Hanprathet, N., Khumsri, J., & Yingyeun, R. (2015). Validation of the Thai version of Bergen Facebook addiction scale (Thai-BFAS). Journal of the Medical Association of Thailand, 98, S108–S117.

Pontes, H. M., Andreassen, C. S., & Griffiths, M. D. (2016). Portuguese validation of the Bergen Facebook addiction scale: An empirical study. International Journal of Mental Health and Addiction, 14, 1–12. http://dx.doi.org/10.1007/s11469-016-9694-y.

Salem, A. A. M., Almenaye, N. S., & Andreassen, C. S. (2016). A psychometric evaluation of Bergen Facebook addiction scale (BFAS) of university students. International Journal of Psychology and Behavioral Sciences, 6, 199–205.

Smith, E. V. (2002). Detecting and evaluation the impact of multidimensionality using item fit statistics and principal component analysis of residuals. Journal of Applied Measurement, 3, 205–231.

Tennant & Conaghan, P. G. (2007). The Rasch measurement model in rheumatology: What is it and why use it? When should it be applied, and what should one look for in a Rasch paper? Arthritis and Rheumatism, 57(8), 1358–1362.

Van den Eijnden, R. J., Lemmens, J. S., & Valkenburg, P. M. (2016). The social media disorder scale. Computers in Human Behavior, 61, 478–487. http://dx.doi.org/10.1016/j.chb.2016.03.038.

Wang WC, Yao G, Tsai YJ, WangJ.D., Hsieh CL. Validating, improving reliability, and estimating correlation of the four subscales in the WHOQOL-BREF using multidimensional Rasch analysis. Quality of Life Research. 2006;15:607-20.

Wilson, M. (2005). Constructing measures: An item response modeling approach. Mahwah, NJ: Lawrence Erlbaum Association.

Wolfe, E. W., & Smith, E. V. J. r. (2007). Instrument development tools and activities for measure validation using Rasch models: Part I— Instrument development tools. In E. V. Smith Jr. & R. M. Smith (Eds.),Rasch measurement: Advanced and specialized applications (pp. 202-242). Maple Grove, MN: JAM Press.

Wright, B. D., & Stone, M. H. (1979). Best test design. Chicago: MESA Press.

Yu, Q., Zhang, L., Wu, S., Guo, Y., Jin, S., & Sun, Y. (2017). The influence of juvenile preference for online social interaction on problematic internet use: The moderating effect of sibling condition and the moderated moderating effect of age cohort. Computers in Human Behavior, 68, 345–351. http://dx.doi.org/10.1016/j.chb.2016. 11.026.

Zinivandnejad, F. (2018). Validation of tools using activity theories and questions and answers to assess students' understanding of virtual disciplines in mathematical learning. Educational Innovations, 65(17): 105-130.

Analysis of the Questionnaire "Addiction to Mobile Based Social Networks" Using Rasch Model