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Sağlık Sektörü Çalışanları Kapsamında Teknoloji Kaygısı: Kuşaklar Arası Bir İnceleme

Year 2024, Volume: 2 Issue: 48, 212 - 226
https://doi.org/10.35343/kosbed.1581079

Abstract

Bu çalışma, sağlık sektöründeki teknolojiye yönelik kaygı düzeylerini kuşaklar bazında incelemeyi amaçlamaktadır. Araştırmada, bilişsel kaygı, duygusal kaygı ve davranışsal kaygı olmak üzere üç boyutta teknoloji kaygısı ele alınmıştır. Veriler, İstanbul’da sağlık sektöründe görev yapan 600 sağlık çalışanına gönderilen anket yoluyla toplanmış ve 270 katılımcının yanıtları analiz edilmiştir. Sonuçlar, X kuşağının bilişsel ve duygusal kaygı düzeylerinin Y kuşağına göre anlamlı derecede daha yüksek olduğunu, ancak davranışsal kaygı düzeylerinde anlamlı bir fark bulunmadığını göstermektedir. Bulgular, dijital dönüşüm sürecinde kuşaklar arasındaki farklılıkların, özellikle X kuşağının teknolojik adaptasyona yönelik zorlukları ve Y kuşağının dijital teknolojilere yatkınlığı ile şekillendiğini ortaya koymaktadır. Çalışma, bu farklılıkların dijital okuryazarlık ve uyum süreçlerinin yönetimi açısından önemli çıkarımlar sunduğunu vurgulamaktadır. Gelecek araştırmalar için kuşaklar arası teknoloji kaygısının boylamsal olarak incelenmesi ve daha geniş örneklem gruplarıyla çalışılması önerilmektedir.

Ethical Statement

Çalışmanın tüm süreçlerinin araştırma ve yayın etiğine uygun olduğunu, etik kurallara ve bilimsel atıf gösterme ilkelerine uyduğumu beyan ederim. Bununla birlikte İstanbul Beykent Üniversitesi Sosyal ve Beşeri Bilimler İçin Bilimsel Araştırma ve Yayın Etiği Kurulu 22.08.2023 tarih ve 131218 sayılı kararıyla çalışmanın etik açıdan uygun olduğuna karar vermiştir

References

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  • Aydın, M. (2023). Technology adoption and digital adaptation in healthcare. Journal of Healthcare Management, 12(3), 45-58.
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  • Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006). Factors predicting the use of technology: Findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychology and Aging, 21(2), 333-352.
  • Deal, J. J., Altman, D. G., & Rogelberg, S. G. (2010). Millennials at work: What we know and what we need to do (if anything). Journal of Business and Psychology, 25(2), 191-199.
  • Durndell, A., & Haag, Z. (2002). Computer self-efficacy and gender: A cross-cultural study of Scotland and Romania. Personality and Individual Differences, 33(5), 1395-1411.
  • Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer-Mediated Communication, 6(1), JCMC611.
  • Eroğlu, S. (2009). Introduction to descriptive research methods. Educational Research Publications.
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  • Fry, R. (2020). Millennials overtake Baby Boomers as America’s largest generation. Pew Research Center.
  • Fuglseth, A. M., & Sørebø, Ø. (2014). The effects of technostress within the context of employee use of ICT. Computers in Human Behavior, 40, 161-170.
  • Gatti, E., Brivio, E., & Galimberti, C. (2017). The future is now: Generation Y’s expectations and personal values. Futures, 87, 50-62.
  • Hauk, N., Hüffmeier, J., & Krumm, S. (2019). Ready to be a Silver Surfer? A meta-analysis on the relationship between chronological age and technology acceptance. Computers in Human Behavior, 84, 304-319.
  • Heinrichs, J. H., & Lim, J. S. (2008). Impact of virtual office on workforce productivity and work-life balance. Journal of Business Research, 61(4), 344-353.
  • Hong, S., & Koh, J. (2002). Computer anxiety and attitude towards using information technology among social workers: A case study in Korea. Behavior & Information Technology, 21(5), 321-327.
  • Igbaria, M., & Parasuraman, S. (1989). A path analytic study of individual characteristics, computer anxiety, and attitudes toward microcomputers. Journal of Management, 15(3), 373-388.
  • Jurkiewicz, C. L., & Brown, R. G. (1998). GenXers vs. Boomers vs. Matures: Generational comparisons of public employee motivation. Review of Public Personnel Administration, 18(4), 18-37.
  • Kaya, E., & Demir, K. (2023). The Role of Digital Competence in Improving Health Workers' Performance. Healthcare Innovation Journal, 14(2), 120-134.
  • Keim, A. (2020). Statistical methods in social sciences: Parametric tests and data analysis. Journal of Applied Social Research, 7(1), 112-130.
  • Kogan, M. (2001). Bridging the gap between generations in the workplace. Harvard Business Review, 79(9), 71-78.
  • Kupperschmidt, B. R. (2000). Multigenerational employees: Strategies for effective management. The Health Care Manager, 19(1), 65-76.
  • Laguna, K., & Babcock, R. L. (1997). Computer anxiety in young and older adults: Implications for human-computer interactions in older populations. Computers in Human Behavior, 13(3), 317-326.
  • Lyons, S., & Kuron, L. (2013). Generational differences in the workplace: A review of the evidence and directions for future research. Journal of Organizational Behavior, 35(S1), S139-S157.
  • Mannheim, K. (1952). The problem of generations. Essays on the Sociology of Knowledge. Routledge & Kegan Paul.
  • Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. I. (2003). The influence of technology anxiety on consumer use and adoption of self-service technologies. Journal of Business Research, 56(11), 899-906.
  • Mitzner, T. L., Boron, J. B., Fausset, C. B., Adams, A. E., Charness, N., Czaja, S. J., ... & Rogers, W. A. (2010). Older adults talk technology: Technology usage and attitudes. Computers in Human Behavior, 26(6), 1710-1721.
  • Myers, K. K., & Sadaghiani, K. (2010). Millennials in the workplace: A communication perspective on Millennials’ organizational relationships and performance. Journal of Business and Psychology, 25(2), 225-238.
  • Ng, E. S. W., Schweitzer, L., & Lyons, S. T. (2010). New generation, great expectations: A field study of the Millennial generation. Journal of Business and Psychology, 25(2), 281-292.
  • Ono, H., & Zavodny, M. (2008). Immigrants, English ability and the digital divide. Social Forces, 86(4), 1455-1479.
  • Pew Research Center. (2019). The generations defined. Pew Research Center.
  • Prensky, M. (2001). Digital Natives, Digital Immigrants. On the Horizon, 9(5), 1-6.
  • Ragu-Nathan, T. S., Tarafdar, M., Ragu-Nathan, B. S., & Tu, Q. (2008). The consequences of technostress for end users in organizations: Conceptual development and empirical validation. Information Systems Research, 19(4), 417-433.
  • Ritz, A., & Alfes, K. (2021). The aging workforce: Implications for human resource management research and practice. Human Resource Management Journal, 31(1), 1-7.
  • Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.
  • Rosen, L. D., & Weil, M. M. (1990). Computer anxiety: A cross-cultural comparison of university students in ten countries. Computers in Human Behavior, 6(3), 361-379.
  • Ryder, N. B. (1965). The cohort as a concept in the study of social change. American Sociological Review, 30(6), 843-861.
  • Schroth, H. (2019). Are you ready for Gen Z in the workplace? California Management Review, 61(3), 5-18.
  • Seemiller, C., & Grace, M. (2019). Generation Z: A century in the making. Routledge.
  • Smola, K. W., & Sutton, C. D. (2002). Generational differences: Revisiting generational work values for the new millennium. Journal of Organizational Behavior, 23(4), 363-382.
  • Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2011). Crossing to the dark side: Examining creators, outcomes, and inhibitors of technostress. Communications of the ACM, 54(9), 113-120.
  • Top, M., & Gider, Ö. (2022). Adaptation of digital health technologies in the healthcare sector: Challenges and opportunities. Digital Health Journal, 10(2), 85-98.
  • TÜİK (2023). Türkiye İstatistik Kurumu Yıllık Sağlık İstatistikleri. Türkiye İstatistik Kurumu.
  • Twenge, J. M. (2010). A review of the empirical evidence on generational differences in work attitudes. Journal of Business and Psychology, 25(2), 201-210.
  • Twenge, J. M. (2017). iGen: Why Today's Super-Connected Kids Are Growing Up Less Rebellious, More Tolerant, Less Happy--and Completely Unprepared for Adulthood. Atria Books.
  • Van Dyne, L., Vandewalle, D., Kostova, T., Latham, M. E., & Cummings, L. L. (2000). Collective efficacy: Its measurement and impact on team performance. Academy of Management Journal, 43(3), 445-455.
  • Venkatesh, V., & Morris, M. G. (2000). Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
  • Wang, Y. M., Chen, Y. C., & Lin, J. (2008). A technology acceptance model for a Chinese-based BPO company. International Journal of Innovation and Technology Management, 5(1), 1-15.
  • World Health Organization. (2021). The impact of digital health technologies on healthcare delivery. WHO Press.
  • Yıldırım, S., & Demir, O. (2021). Healthcare workforce dynamics in large-scale urban settings. Health Economics and Policy Journal, 13(4), 245-263.
Year 2024, Volume: 2 Issue: 48, 212 - 226
https://doi.org/10.35343/kosbed.1581079

Abstract

References

  • Anderson, M., & Jiang, J. (2018). Teens, Social Media & Technology 2018. Pew Research Center. https://www.pewresearch.org
  • Aydın, M. (2023). Technology adoption and digital adaptation in healthcare. Journal of Healthcare Management, 12(3), 45-58.
  • Brosnan, M. J. (1998). Technophobia: The psychological impact of information technology. Routledge.
  • Büyükköztürk, Ş., Çakmak, E. K., Akgün, Ö. E., Karadeniz, Ş., & Demirel, F. (2012). Bilimsel Araştırma Yöntemleri. Pegem Akademi Yayıncılık.
  • Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
  • Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006). Factors predicting the use of technology: Findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychology and Aging, 21(2), 333-352.
  • Deal, J. J., Altman, D. G., & Rogelberg, S. G. (2010). Millennials at work: What we know and what we need to do (if anything). Journal of Business and Psychology, 25(2), 191-199.
  • Durndell, A., & Haag, Z. (2002). Computer self-efficacy and gender: A cross-cultural study of Scotland and Romania. Personality and Individual Differences, 33(5), 1395-1411.
  • Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer-Mediated Communication, 6(1), JCMC611.
  • Eroğlu, S. (2009). Introduction to descriptive research methods. Educational Research Publications.
  • Francis, T., & Hoefel, F. (2018). 'True Gen': Generation Z and its implications for companies. McKinsey & Company.
  • Fry, R. (2020). Millennials overtake Baby Boomers as America’s largest generation. Pew Research Center.
  • Fuglseth, A. M., & Sørebø, Ø. (2014). The effects of technostress within the context of employee use of ICT. Computers in Human Behavior, 40, 161-170.
  • Gatti, E., Brivio, E., & Galimberti, C. (2017). The future is now: Generation Y’s expectations and personal values. Futures, 87, 50-62.
  • Hauk, N., Hüffmeier, J., & Krumm, S. (2019). Ready to be a Silver Surfer? A meta-analysis on the relationship between chronological age and technology acceptance. Computers in Human Behavior, 84, 304-319.
  • Heinrichs, J. H., & Lim, J. S. (2008). Impact of virtual office on workforce productivity and work-life balance. Journal of Business Research, 61(4), 344-353.
  • Hong, S., & Koh, J. (2002). Computer anxiety and attitude towards using information technology among social workers: A case study in Korea. Behavior & Information Technology, 21(5), 321-327.
  • Igbaria, M., & Parasuraman, S. (1989). A path analytic study of individual characteristics, computer anxiety, and attitudes toward microcomputers. Journal of Management, 15(3), 373-388.
  • Jurkiewicz, C. L., & Brown, R. G. (1998). GenXers vs. Boomers vs. Matures: Generational comparisons of public employee motivation. Review of Public Personnel Administration, 18(4), 18-37.
  • Kaya, E., & Demir, K. (2023). The Role of Digital Competence in Improving Health Workers' Performance. Healthcare Innovation Journal, 14(2), 120-134.
  • Keim, A. (2020). Statistical methods in social sciences: Parametric tests and data analysis. Journal of Applied Social Research, 7(1), 112-130.
  • Kogan, M. (2001). Bridging the gap between generations in the workplace. Harvard Business Review, 79(9), 71-78.
  • Kupperschmidt, B. R. (2000). Multigenerational employees: Strategies for effective management. The Health Care Manager, 19(1), 65-76.
  • Laguna, K., & Babcock, R. L. (1997). Computer anxiety in young and older adults: Implications for human-computer interactions in older populations. Computers in Human Behavior, 13(3), 317-326.
  • Lyons, S., & Kuron, L. (2013). Generational differences in the workplace: A review of the evidence and directions for future research. Journal of Organizational Behavior, 35(S1), S139-S157.
  • Mannheim, K. (1952). The problem of generations. Essays on the Sociology of Knowledge. Routledge & Kegan Paul.
  • Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. I. (2003). The influence of technology anxiety on consumer use and adoption of self-service technologies. Journal of Business Research, 56(11), 899-906.
  • Mitzner, T. L., Boron, J. B., Fausset, C. B., Adams, A. E., Charness, N., Czaja, S. J., ... & Rogers, W. A. (2010). Older adults talk technology: Technology usage and attitudes. Computers in Human Behavior, 26(6), 1710-1721.
  • Myers, K. K., & Sadaghiani, K. (2010). Millennials in the workplace: A communication perspective on Millennials’ organizational relationships and performance. Journal of Business and Psychology, 25(2), 225-238.
  • Ng, E. S. W., Schweitzer, L., & Lyons, S. T. (2010). New generation, great expectations: A field study of the Millennial generation. Journal of Business and Psychology, 25(2), 281-292.
  • Ono, H., & Zavodny, M. (2008). Immigrants, English ability and the digital divide. Social Forces, 86(4), 1455-1479.
  • Pew Research Center. (2019). The generations defined. Pew Research Center.
  • Prensky, M. (2001). Digital Natives, Digital Immigrants. On the Horizon, 9(5), 1-6.
  • Ragu-Nathan, T. S., Tarafdar, M., Ragu-Nathan, B. S., & Tu, Q. (2008). The consequences of technostress for end users in organizations: Conceptual development and empirical validation. Information Systems Research, 19(4), 417-433.
  • Ritz, A., & Alfes, K. (2021). The aging workforce: Implications for human resource management research and practice. Human Resource Management Journal, 31(1), 1-7.
  • Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.
  • Rosen, L. D., & Weil, M. M. (1990). Computer anxiety: A cross-cultural comparison of university students in ten countries. Computers in Human Behavior, 6(3), 361-379.
  • Ryder, N. B. (1965). The cohort as a concept in the study of social change. American Sociological Review, 30(6), 843-861.
  • Schroth, H. (2019). Are you ready for Gen Z in the workplace? California Management Review, 61(3), 5-18.
  • Seemiller, C., & Grace, M. (2019). Generation Z: A century in the making. Routledge.
  • Smola, K. W., & Sutton, C. D. (2002). Generational differences: Revisiting generational work values for the new millennium. Journal of Organizational Behavior, 23(4), 363-382.
  • Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2011). Crossing to the dark side: Examining creators, outcomes, and inhibitors of technostress. Communications of the ACM, 54(9), 113-120.
  • Top, M., & Gider, Ö. (2022). Adaptation of digital health technologies in the healthcare sector: Challenges and opportunities. Digital Health Journal, 10(2), 85-98.
  • TÜİK (2023). Türkiye İstatistik Kurumu Yıllık Sağlık İstatistikleri. Türkiye İstatistik Kurumu.
  • Twenge, J. M. (2010). A review of the empirical evidence on generational differences in work attitudes. Journal of Business and Psychology, 25(2), 201-210.
  • Twenge, J. M. (2017). iGen: Why Today's Super-Connected Kids Are Growing Up Less Rebellious, More Tolerant, Less Happy--and Completely Unprepared for Adulthood. Atria Books.
  • Van Dyne, L., Vandewalle, D., Kostova, T., Latham, M. E., & Cummings, L. L. (2000). Collective efficacy: Its measurement and impact on team performance. Academy of Management Journal, 43(3), 445-455.
  • Venkatesh, V., & Morris, M. G. (2000). Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
  • Wang, Y. M., Chen, Y. C., & Lin, J. (2008). A technology acceptance model for a Chinese-based BPO company. International Journal of Innovation and Technology Management, 5(1), 1-15.
  • World Health Organization. (2021). The impact of digital health technologies on healthcare delivery. WHO Press.
  • Yıldırım, S., & Demir, O. (2021). Healthcare workforce dynamics in large-scale urban settings. Health Economics and Policy Journal, 13(4), 245-263.
There are 52 citations in total.

Details

Primary Language Turkish
Subjects Business Administration
Journal Section Articles
Authors

Murat Günsel 0009-0004-6944-554X

Ülkü Uzunçarşılı 0000-0001-7855-2268

Early Pub Date January 4, 2025
Publication Date
Submission Date November 7, 2024
Acceptance Date November 13, 2024
Published in Issue Year 2024 Volume: 2 Issue: 48

Cite

APA Günsel, M., & Uzunçarşılı, Ü. (2025). Sağlık Sektörü Çalışanları Kapsamında Teknoloji Kaygısı: Kuşaklar Arası Bir İnceleme. Kocaeli Üniversitesi Sosyal Bilimler Dergisi, 2(48), 212-226. https://doi.org/10.35343/kosbed.1581079

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