Research Article
BibTex RIS Cite

Pandemi Sırasında Hemşirelik Öğrencilerinin Dijital Tükenmişlik Düzeylerini Etkileyen Faktörler: Web Tabanlı Kesitsel Bir Araştırma

Year 2024, Volume: 9 Issue: 2, 199 - 216, 30.08.2024
https://doi.org/10.47115/jshs.1197919

Abstract

Amaç: Pandemi döneminde hemşirelik öğrencilerinin dijital tükenmişlik düzeylerini etkileyen faktörleri belirlemektir.
Yöntem: Tanımlayıcı ve kesitsel tipteki çalışma 1000 hemşirelik öğrencisi ile yürütülmüştür. Araştırmanın verileri Mart-Nisan 2021 tarihleri arasında "Tanıtıcı Bilgi Formu" ve "Dijital Tükenmişlik Ölçeği" kullanılarak online anket şeklinde toplanmıştır. Tanımlayıcı istatistiksel analizlerin yanı sıra, normal dağılmayan nicel değişkenlerin ikiden fazla grup arasında karşılaştırılmasında Kruskal-Wallis testi ve Dunn-Bonferroni testi kullanılmıştır. Nicel değişkenler arasındaki ilişkileri değerlendirmek için Spearman korelasyon analizi kullanılmıştır. İstatistiksel anlamlılık düzeyi p < 0.05 olarak kabul edilmiştir.
Bulgular: Öğrencilerin Dijital Tükenmişlik Ölçeği puanları incelendiğinde, toplam puan ortalamaları "Dijital Yaşlanma" boyutu için 2,70±0,92 (Min.=1-Max.=5, Medyan=2,67), "Dijital Yoksunluk" boyutu için 3,17±1,06 (Min.=1-Max.=5, Medyan=3,33) ve "Dijital Tükenme" boyutu için 2,76±0,93 (Min.=1,17-Max.=5, Medyan=2,67) olarak bulunmuştur. Ölçeğin toplam puan ortalaması 2,83±0,86 (Min.=1,04-Maks.=5, Ortanca=2,79)'dır.
Sonuçlar ve Öneriler: Hemşirelik öğrencileri pandemi sürecinde yüksek düzeyde dijital tükenmişlik yaşamıştır. Öğrencilerin öğrenim gördükleri yıl ve dijital ortamlarda geçirdikleri süre dijital tükenmişlik düzeyini etkilemektedir. Uzaktan hemşirelik eğitimi sırasında dijital tükenmişliği azaltmak için önlemler alınmalıdır.

References

  • Bao, Y., Sun, Y., Meng, S., Shi, J. & Lu, L. (2020). 2019-nCoV epidemic: Address mental health care to empower society. Lancet, 395(10224), e37–e38. https://doi.org/10.1016/S0140-6736(20)30309-3.
  • Breytenbach, C. (2015). Tackling digital burnout in the workplace. Retrieved from http://www.destinyman.com/2015/02/10/tackling-digital-burnout-in-the-workplace/
  • Chang, D. (2014). Digital burnout the new, invisible threat to businesses. Retrieved from: http://fluxtrends.co.za/digital-burnout-the-new-invisible-threat-to-businesses/.
  • Çelik Durmuş, S., Gülnar, E., Özveren, H. (2022). Determining digital burnout in nursing students: A descriptive research study. Nurse Education Today, 111, 105300. https://doi.org/10.1016/j.nedt.2022.105300.
  • Eidi, A. R. & Delam, H. (2020). Internet addiction is likely to increase in home quarantine caused by Coronavirus Disease 2019 (COVID 19). J Health Sci Surveillance Sys, 8 (3), 136-137.
  • Erten, P. & Özdemir, O. (2020). The Digital Burnout Scale development study. Inonu University Journal of the Faculty of Education, 21 (2), 668-683. https://doi.org/10.17679/inuefd.597890.
  • Friedman, L. (2016). Exhausted? After-hours emails may be to blame. Lehigh Business, 2, 18-19.
  • Göldağ, B. (2022). An investigation of the relationship between university students' digital burnout levels and perceived stress levels. Journal of Learning and Teaching in Digital Age, 7(1), 90-98. https://doi.org/10.53850/ joltida.958039.
  • Hossmann, K. A. & Hermann, D. M. (2003). Effects of electromagnetic radiation of mobile phones on the central nervous system. Bioelectromagnetics, 24, 49-62. https://doi.org/10.1002/bem.10068.
  • Kemp, S. (2020). Digital 2020: Global digital overview 2020, https://datareportal.com/reports/digital-2020-global-digital-overview (Accessed date: 30.05.2021).
  • Khouja, J. N., Munafò, M. R., Tilling, K., Wiles, N. J., Joinson, C., Etchells, P. J., et al. (2019). Is screen time associated with anxiety or depression in young people? Results from a UK birth cohort. BMC Public Health, 19, 82. https://doi.org/110.1186/s12889-018-6321-9.
  • Kırca, K. & Kutlutürkan, S. (2019). Effect of smart phone addiction levels of nursing students on their communication skills. Kocaeli University Journal of Health Sciences, 5 (2), 81-85. https://doi.org/10.30934/kusbed.523924.
  • Király, O., Potenza, M. N., Stein, D. J., King, D. L., Hodgins, D. C., Saunders, J. B., et al. (2020). Preventing problematic internet use during the COVID-19 pandemic: Consensus guidance. Compr Psychiatry, 100, 152180. https://doi.org/10.1016/j.comppsych.2020.152180. Epub 2020 May 12.
  • Kumpikaitė-Valiūnienė, V., Aslan, I., Duobienė, J., Glińska, E., Anandkumar, V. (2021). Influence of digital competence on perceived stress, burnout and well-being among students studying online during the COVID-19 lockdown: A 4-country perspective. Psychology Research and Behavior Management, 14, 1483-1498, https://doi.org/10.2147/PRBM.S325092
  • Lemola, S., Perkinson-Gloor, N., Brand, S., Dewald-Kaufmann, J. F., Grob, A. (2015). Adolescents’ electronic media use at night, sleep disturbance, and depressive symptoms in the smartphone age. J Youth Adolesc., 44, 405-18. https://doi.org/10.1007/s10964-014-0176-x.
  • Madhav, K. C., Sherchand, S. P., Sherchan, S. (2017). Association between screen time and depression among US adults. Prev Med Rep., 1, 67-71. https://doi.org/10.1016/j.pmedr.2017.08.005.
  • Maslach, C. & Jackson, S. (1981). The measurement of experienced burnout. Journal of Occupational Behavior, 22, 99-113.
  • Meymandpour, R. & Bagheri, Z. (2017). A study of personality traits, viz., extraversion and introversion on telecommuters’ burnout. Telecom Business Rev., 10, 1-7.
  • Mheidly, N., Fares, M. Y. & Fares, J. (2020). Coping with stress and burnout associated with telecommunication and online learning. Front. Public Health, 8, 574969. https://doi.org/10.3389/fpubh.2020.574969.
  • Quill, M. (2017). The Harmful Effects of Digital Burnout on Organisational Effectiveness. TMS Consulting, Brisbane, Sydney, Melbourne. Retrieved November 5, 2017 from. http://www.t
  • Sansone, R. A. & Sansone, L. A. (2013). Cell phones: the psychosocial risks. Innov Clin Neurosci., 10, 33-7.
  • Suliman, W. A., Abu-Moghli, F. A., Khalaf, I., Zumot, A. F., Nabolsi, M. (2021). Experiences of nursing students under the unprecedented abrupt online learning format forced by the national curfew due to COVID-19: A qualitative research study. Nurse Education Today, 100, 104829. https://doi.org/10.1016/j.nedt.2021.104829.
  • Sun, L., Tang, Y., Zuo, W. (2020). Coronavirus pushes education online. Nature Materials, 19, 687. https://doi.org/10.1038/s41563-020-0678-8.
  • Şenyuva, E. (2013). Nurses' view about distance education. EducTechnol Theory Pract., 3(2), 23‐41.
  • Terzi, B., Azizoğlu, F., Özhan, F. (2021). Factors affecting attitudes of nursing students towards distance education during the COVID‐19 pandemic: A web‐based cross‐sectional survey. Perspect Psychiatr Care, 1-9. https://doi.org/10.1111/ppc.12747.
  • Višnjić, A., Veličković, V., Sokolović, D., Stanković, M., Mijatović, K., Stojanović, M., et al. (2018). Relationship between the manner of mobile phone use and depression, anxiety, and stress in University Students. Int J Environ Res Public Health., 15 (4), 697. https://doi.org/10.3390/ijerph15040697.

FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY

Year 2024, Volume: 9 Issue: 2, 199 - 216, 30.08.2024
https://doi.org/10.47115/jshs.1197919

Abstract

Aim: To identify factors affecting the digital burnout levels of nursing students during the pandemic period.
Method: The descriptive and cross-sectional study was conducted with 1000 nursing students. Data of the research was collected between March-April, 2021 as online survey by using “Introductory Information Form” and “Digital Burnout Scale”. In addition to descriptive statistical analyses, Kruskal-Wallis test and Dunn-Bonferroni test were used for the comparison of non-normally distributed quantitative variables between more than two groups. Spearman correlational analysis was used for evaluating the relationships between quantitative variables. Statistical significance level was accepted as p < 0.05.
Results: Regarding the Digital Burnout Scale scores of the students, average total scores were 2.70±0.92 (Min.=1-Max.=5, Median=2.67) for “Digital Aging” dimension, 3.17±1.06 (Min.=1-Max.=5, Median=3.33) for “Digital Deprivation” dimension and 2.76±0.93 (Min.=1.17-Max.=5, Median=2.67) for “Digital Exhaustion” dimension. Average total score of the overall scale was 2.83±0.86 (Min.=1.04-Max.=5, Median=2.79).
Conclusions and Suggestions: Nursing students experienced high level of digital burnout during the pandemic. The year of study of students and the time they spend on digital environments affects the level of digital burnout. Measures should be taken to reduce digital burnout during the distance nursing education.

References

  • Bao, Y., Sun, Y., Meng, S., Shi, J. & Lu, L. (2020). 2019-nCoV epidemic: Address mental health care to empower society. Lancet, 395(10224), e37–e38. https://doi.org/10.1016/S0140-6736(20)30309-3.
  • Breytenbach, C. (2015). Tackling digital burnout in the workplace. Retrieved from http://www.destinyman.com/2015/02/10/tackling-digital-burnout-in-the-workplace/
  • Chang, D. (2014). Digital burnout the new, invisible threat to businesses. Retrieved from: http://fluxtrends.co.za/digital-burnout-the-new-invisible-threat-to-businesses/.
  • Çelik Durmuş, S., Gülnar, E., Özveren, H. (2022). Determining digital burnout in nursing students: A descriptive research study. Nurse Education Today, 111, 105300. https://doi.org/10.1016/j.nedt.2022.105300.
  • Eidi, A. R. & Delam, H. (2020). Internet addiction is likely to increase in home quarantine caused by Coronavirus Disease 2019 (COVID 19). J Health Sci Surveillance Sys, 8 (3), 136-137.
  • Erten, P. & Özdemir, O. (2020). The Digital Burnout Scale development study. Inonu University Journal of the Faculty of Education, 21 (2), 668-683. https://doi.org/10.17679/inuefd.597890.
  • Friedman, L. (2016). Exhausted? After-hours emails may be to blame. Lehigh Business, 2, 18-19.
  • Göldağ, B. (2022). An investigation of the relationship between university students' digital burnout levels and perceived stress levels. Journal of Learning and Teaching in Digital Age, 7(1), 90-98. https://doi.org/10.53850/ joltida.958039.
  • Hossmann, K. A. & Hermann, D. M. (2003). Effects of electromagnetic radiation of mobile phones on the central nervous system. Bioelectromagnetics, 24, 49-62. https://doi.org/10.1002/bem.10068.
  • Kemp, S. (2020). Digital 2020: Global digital overview 2020, https://datareportal.com/reports/digital-2020-global-digital-overview (Accessed date: 30.05.2021).
  • Khouja, J. N., Munafò, M. R., Tilling, K., Wiles, N. J., Joinson, C., Etchells, P. J., et al. (2019). Is screen time associated with anxiety or depression in young people? Results from a UK birth cohort. BMC Public Health, 19, 82. https://doi.org/110.1186/s12889-018-6321-9.
  • Kırca, K. & Kutlutürkan, S. (2019). Effect of smart phone addiction levels of nursing students on their communication skills. Kocaeli University Journal of Health Sciences, 5 (2), 81-85. https://doi.org/10.30934/kusbed.523924.
  • Király, O., Potenza, M. N., Stein, D. J., King, D. L., Hodgins, D. C., Saunders, J. B., et al. (2020). Preventing problematic internet use during the COVID-19 pandemic: Consensus guidance. Compr Psychiatry, 100, 152180. https://doi.org/10.1016/j.comppsych.2020.152180. Epub 2020 May 12.
  • Kumpikaitė-Valiūnienė, V., Aslan, I., Duobienė, J., Glińska, E., Anandkumar, V. (2021). Influence of digital competence on perceived stress, burnout and well-being among students studying online during the COVID-19 lockdown: A 4-country perspective. Psychology Research and Behavior Management, 14, 1483-1498, https://doi.org/10.2147/PRBM.S325092
  • Lemola, S., Perkinson-Gloor, N., Brand, S., Dewald-Kaufmann, J. F., Grob, A. (2015). Adolescents’ electronic media use at night, sleep disturbance, and depressive symptoms in the smartphone age. J Youth Adolesc., 44, 405-18. https://doi.org/10.1007/s10964-014-0176-x.
  • Madhav, K. C., Sherchand, S. P., Sherchan, S. (2017). Association between screen time and depression among US adults. Prev Med Rep., 1, 67-71. https://doi.org/10.1016/j.pmedr.2017.08.005.
  • Maslach, C. & Jackson, S. (1981). The measurement of experienced burnout. Journal of Occupational Behavior, 22, 99-113.
  • Meymandpour, R. & Bagheri, Z. (2017). A study of personality traits, viz., extraversion and introversion on telecommuters’ burnout. Telecom Business Rev., 10, 1-7.
  • Mheidly, N., Fares, M. Y. & Fares, J. (2020). Coping with stress and burnout associated with telecommunication and online learning. Front. Public Health, 8, 574969. https://doi.org/10.3389/fpubh.2020.574969.
  • Quill, M. (2017). The Harmful Effects of Digital Burnout on Organisational Effectiveness. TMS Consulting, Brisbane, Sydney, Melbourne. Retrieved November 5, 2017 from. http://www.t
  • Sansone, R. A. & Sansone, L. A. (2013). Cell phones: the psychosocial risks. Innov Clin Neurosci., 10, 33-7.
  • Suliman, W. A., Abu-Moghli, F. A., Khalaf, I., Zumot, A. F., Nabolsi, M. (2021). Experiences of nursing students under the unprecedented abrupt online learning format forced by the national curfew due to COVID-19: A qualitative research study. Nurse Education Today, 100, 104829. https://doi.org/10.1016/j.nedt.2021.104829.
  • Sun, L., Tang, Y., Zuo, W. (2020). Coronavirus pushes education online. Nature Materials, 19, 687. https://doi.org/10.1038/s41563-020-0678-8.
  • Şenyuva, E. (2013). Nurses' view about distance education. EducTechnol Theory Pract., 3(2), 23‐41.
  • Terzi, B., Azizoğlu, F., Özhan, F. (2021). Factors affecting attitudes of nursing students towards distance education during the COVID‐19 pandemic: A web‐based cross‐sectional survey. Perspect Psychiatr Care, 1-9. https://doi.org/10.1111/ppc.12747.
  • Višnjić, A., Veličković, V., Sokolović, D., Stanković, M., Mijatović, K., Stojanović, M., et al. (2018). Relationship between the manner of mobile phone use and depression, anxiety, and stress in University Students. Int J Environ Res Public Health., 15 (4), 697. https://doi.org/10.3390/ijerph15040697.
There are 26 citations in total.

Details

Primary Language English
Subjects Nurse Education, Nursing (Other)
Journal Section Original Research
Authors

Banu Terzi 0000-0002-9500-6872

Fatma Azizoğlu 0000-0002-7102-9797

Çağla Seven 0000-0002-1279-3664

Early Pub Date August 29, 2024
Publication Date August 30, 2024
Submission Date November 1, 2022
Published in Issue Year 2024 Volume: 9 Issue: 2

Cite

APA Terzi, B., Azizoğlu, F., & Seven, Ç. (2024). FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY. Samsun Sağlık Bilimleri Dergisi, 9(2), 199-216. https://doi.org/10.47115/jshs.1197919
AMA Terzi B, Azizoğlu F, Seven Ç. FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY. JSHS. August 2024;9(2):199-216. doi:10.47115/jshs.1197919
Chicago Terzi, Banu, Fatma Azizoğlu, and Çağla Seven. “FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY”. Samsun Sağlık Bilimleri Dergisi 9, no. 2 (August 2024): 199-216. https://doi.org/10.47115/jshs.1197919.
EndNote Terzi B, Azizoğlu F, Seven Ç (August 1, 2024) FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY. Samsun Sağlık Bilimleri Dergisi 9 2 199–216.
IEEE B. Terzi, F. Azizoğlu, and Ç. Seven, “FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY”, JSHS, vol. 9, no. 2, pp. 199–216, 2024, doi: 10.47115/jshs.1197919.
ISNAD Terzi, Banu et al. “FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY”. Samsun Sağlık Bilimleri Dergisi 9/2 (August 2024), 199-216. https://doi.org/10.47115/jshs.1197919.
JAMA Terzi B, Azizoğlu F, Seven Ç. FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY. JSHS. 2024;9:199–216.
MLA Terzi, Banu et al. “FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY”. Samsun Sağlık Bilimleri Dergisi, vol. 9, no. 2, 2024, pp. 199-16, doi:10.47115/jshs.1197919.
Vancouver Terzi B, Azizoğlu F, Seven Ç. FACTORS AFFECTING NURSING STUDENTS’ DIGITAL BURNOUT LEVELS DURING IN PANDEMIC: A WEB-BASED CROSS-SECTIONAL STUDY. JSHS. 2024;9(2):199-216.

22657

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).