Bu araştırmanın amacı, orijinal formu İngilizce olarak Song, J., Kim, J. ve Cho, K. (2018) tarafından geliştirilen Giyilebilir Teknolojik Spor Ürünleri Kullanım Algısı Ölçeği’ni Türkçeye uyarlayarak geçerlik ve güvenirlik çalışmalarını yapmaktır. Çalışmanın örneklemini giyilebilir teknolojik spor ürünü kullanan ve çalışmaya gönüllü olarak katılan 550 kişi oluşturmaktadır. Giyilebilir Teknolojik Spor Ürünleri Kullanım Algısı Ölçeği’nin orijinali 5’li likert tipi 31 madde ve 9 alt boyuttan oluşmaktadır. Açımlayıcı ve doğrulayıcı faktör analizleri sonucu açıklanan varyans değeri %64,9 olarak tespit edilen ölçeğin, Türkçe formunun 30 maddeli ve 6 faktörlü yapıyı desteklediği sonucuna ulaşılmıştır. Ölçeğin alt boyutlarına ait güvenirlik katsayıları ise 0.77-0.87 aralığında değişmektedir. Sonuç olarak elde edilen veriler kapsamında Giyilebilir Teknolojik Spor Ürünleri Kullanım Algısı Ölçeği’nin Türkçe formunun geçerli ve güvenilir bir ölçme aracı olduğu belirlenmiştir.
The purpose of this study is to adapt the Wearable Technological Sports Products Perception Scale, original developed in English by Song, J., Kim, J., and Cho, K. (2018), to Turkish and conduct the reliability and validity studies. The sample of the study is five hundred fifty people who use wearable technological sports products and participate voluntarily in the study. The original Wearable Technological Sports Products Perception Scale is a five point likert scale and includes thirty-one items and nine sub-dimensions. As a result of exploratory and confirmatory factor analyzes, it was found that the Turkish version of the scale supported the 30 item and 6 factor structure. The reliability coefficients of the subscales of the scale vary between 0.77- 0.87. As a result of the data obtained, it can be stated that the Turkish form of Wearable Technological Sports Products Perception Scale is a valid and reliable measurement tool.
Adapa, A., Nah, F.F.H., Hall, R.H., Siau, K., Smith, S.N. (2018). Factors influencing the adoption of smart wearable devices. International Journal of Human-Computer Interaction, 34(5), 399-409.
Brislin, R.W. (1970). Back translation for cross-cultural research. Journal of Cross-Cultural Pyschology, 1(3), 185-216.
Caddy, B. (2019). Are fitness trackers the future of healthcare. https://www.techradar.com/news/are-fitnesstrackers-the-future-of-healthcare
Campbell, D.T., Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105.
Canhoto, A.I., Arp, S. (2017). Exploring the factors that support adoption and sustained use of health and fitness wearables. Journal of Marketing Management, 33(1-2), 32-60.
CCS Insight (2015). https://www.ccsinsight.com/press/company-news/2332-wearables-market-to-be-worth-25- billion-by-2019-reveals-ccs-insight/
Chau, K. Y., Lam, M. H. S., Cheung, M. L., Tso, E. K. H., Flint, S. W., Broom, D. R., ... Lee, K. Y. (2019). Smart technology for healthcare: Exploring the antecedents of adoption intention of healthcare wearable technology. Health Psychology Research, 7(1).
Coelho, G.L., Monteiro, R.P., Hanel, P.H., Vilar, R., Gouveia, V.V., Maio, G.R. (2018). Psychometric parameters of an abbreviated vengeance scale across two countries. Personality and Individual Differences, 120, 185-192.
Cortina, J.M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98-104.
Cottle K.E. (2017). Current patterns of ownership and usage of mobile technology in older adults. MsC Thesis, Brigham Young University. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=7521&context=etd
Creswell, J.W. (2005). Educational research: Planning, conducting and evaluating quantitative and qualitative research. (4th Edition). Boston: Pearson Prentice Hall.
Dehghani, M., Kim, K.J., Dangelico, R.M. (2018). Will smartwatches last? Factors contributing to intention to keep using smart wearable technology. Telematics and Informatics, 35(2), 480-490.
Dehghani, M., Dangelico, R.M. (2017). Smart wearable technologies: Current status and market orientation through a patent analysis. In Industrial Technology (ICIT), 2017 IEEE International Conference on (pp. 1570– 1575). IEEE.
DeVellis, R.F. (2016). Scale development: Theory and applications (Vol. 26). Sage publications.
Duffy, J. (2014). The best activity trackers for fitness. http://www.pcmag.com/article2/0,2817,2404445,00.asp
Fang, Y.M., Chang, C.C. (2016). Users’ psychological perception and perceived readability of wearable devices for elderly people. Behaviour & Information Technology, 35(3), 225-232.
Field, A. (2005). Discovering statistics using SPSS. (2th Edition). London: SAGE Publications.
Fotopoulou, A., O’Riordan, K. (2017). Training to self-care: Fitness tracking, biopedagogy and the healthy consumer. Health Sociology Review, 26(1), 54-68.
Hair, J.F., Black, W.C., Babin, B.J., Anderson, R. E., Tatham, R.L. (2014). Multivariate data analysis (7th Edition). Harlow: Pearson Education Limited.
Holbrook, M.B., Hirschman, E.C. (1982). The experiential aspects of consumption: consumer fantasies, feelings, and fun. Journal of Consumer Research, 9(2), 132-140.
Hoyle, R.H. (Ed.) (2012). Handbook of structural equation modeling. New York: The Guilford Press ket outlook 2020: Drivers and new markets https://www.i-scoop.eu/wearablesmarket-outlook-2020-drivers-new-markets/
Kaewkannate, K., Kim, S. (2018). The comparison of wearable fitness devices. Wearable Technologies, 197.
Kline, R.B. (2016). Principles and practice of structural equation modeling. (4th Edition), New York: Guilford Press.
Lee, S., Kim, Y., Heere, B. (2018). Sport team emotion: Conceptualization, scale development and validation. Sport Management Review, 21(4), 363-376.
Loewenthal, K., Lewis, C.A. (2018). An introduction to psychological tests and scales. Psychology press.
Loncar-Turukalo, T., Zdravevski, E., da Silva, J. M., Chouvarda, I., & Trajkovik, V. (2019). Literature on Wearable Technology for Connected Health: Scoping Review of Research Trends, Advances, and Barriers. Journal of Medical Internet Research, 21(9), e14017.
Lunney, A., Cunningham, N.R., Eastin, M.S. (2016). Werable fitness technology: A structural investigation into acceptance and perceived fitness outcomes. Computers in Human Behavior, 65, 114-120.
Morgado, F.F., Meireles, J.F., Neves, C.M., Amaral, A.C., Ferreira, M.E. (2018). Scale development: ten main limitations and recommendations to improve future research practices. Psicologia: Reflexão e Crítica, 30(1), 3.
Odabaşı, Y., Barış, G. (2014). Tüketici davranışı. (14. Baskı). İstanbul: MediaCat Yayınları.
Porter, M.E., Heppelmann, J.E. (2014). How smart: Connected products are transforming competition. Harvard Business Review, 92, 64–88.
Raskovic, D., Martin, T., Jovanov, E., (2004). Medical monitoring applications for wearable computing. Comput. J, 47(4), 495–504.
Rauschnabel, P.A., Hein, D.W.E., He, J., Ro, Y.K., Rawashdeh, S., Krulikowski, B. (2016). Fashion or technology? A fashnology perspective on the perception and adoption of augmented reality smart glasses. Journal of Interactive Media, 15(2), 179–194.
Robinson, M.A. (2018). Using multi‐item psychometric scales for research and practice in human resource management. Human Resource Management, 57(3), 739-750.
Song, J., Kim, J., Cho, K. (2018). Understanding users’ continuance intentions to use smart-connected sports products. Sport Management Review, 21(5), 477-490.
Tabachnick, B., Fidell, L. (2012). Using multivariate statistics. (6th Edition). Harlow: Pearson Education.
Temporal, P. (2010). Advanced brand management: Managing brands in a changing world. (2th Edition). Singapore: John Wiley & Sons.
Tinsley, H.E., Tinsley, D.J. (1987). Uses of factor analysis in counseling psychology research. Journal of Counseling Psychology, 34(4), 414-424.
Santos, J.R.A. (1999). Cronbach's alpha: A tool for asssessing the reliability of scales. Journal of Extension, 37(2), https://www.joe.org/joe/1999april/tt3.php
Wright, R., Keith, L. (2014). Wearable technology: If the tech fits, wear it. Journal of Electronic Resources in Medical Libraries, 11(4), 204-216