COVID-19 Salgınının Hızlı Yükseliş Döneminde Sağlık Çalışanlarının Yeni Koronavirüse (Sars-Cov-2) Yönelik Bilgi, Tutum ve Uygulamalarının Değerlendirilmesi

Öz

Bu çalışmanın temel amacı, COVID-19 salgınının hızlı yükseliş döneminde sağlık çalışanlarının yeni koronavirüse yönelik bilgi, tutum ve uygulamalarını değerlendirmek ve bilgi düzeyinin uygulamalar üzerine etkisinde tutumun aracılık etkisini tespit etmektir. Araştırmada hastane tabanlı kesitsel araştırma deseni uygulanmıştır. Araştırmanın evrenini İstanbul ilinde ikinci basamak tedavi sunan İstanbul Eğitim Araştırma Hastanesi ile üçüncü basamak tedavi sunan Yedikule Göğüs Hatalıkları ve Göğüs Cerrahisi Eğitim ve Araştırma Hastanesinin sağlık çalışanları oluşturmuştur. Araştırmada kolayda örnekleme yöntemi tercih edilmiştir. Veriler internet üzerinden anket tekniği ile bizzat araştırmacılar tarafından toplanmıştır. Değerlendirmeye alınan ve verilerin analizinde kullanılan toplam anket sayısı 409’dur. Verilerin analizinde SPSS ve AMOS paket programları kullanılmıştır. Verilere betimleyici analizler, bağımsız örneklem t testi, anova analizi ve yapısal eşitlik modellemesi uygulanmıştır. Yapısal eşitlik analizi ile elde edilen bulgular, modelin yapı geçerliliğinin sağlandığını göstermiştir. Ayrıca yol analizi, COVID-19'a yönelik bilgi düzeyinin COVID-19'a yönelik uygulamalar üzerindeki doğrudan ve dolaylı etkisinin (COVID-19'a yönelik tutumun aracılık ettiği) kabul edilebilir bir uyum indeksine sahip olduğunu ortaya koymuştur. Sağlık çalışanlarının büyük çoğunluğu COVID-19'un kaynakları, bulaşması, semptomları, belirtileri, prognozu, tedavisi, yönetimi ve önleyici tedbirleri hakkında yeterli bilgiye, olumlu bir tutuma ve iyi düzeyde uygulamalara sahipti. COVID-19'a yönelik bilgi düzeyi, COVID-19'a yönelik uygulamalar üzerinde hem doğrudan hem de tutumun aracılık rolüyle dolaylı etkiye sahiptir.

Anahtar Kelimeler

• COVID-19 salgını
• bilgi
• tutum
• uygulamalar
• sağlık çalışanları

Assessment of Knowledge, Attitudes and Practices Towards New Coronavirus (Sars-Cov-2) of Healthcare Workers During the Rapid Rise Period of the COVID-19 Outbreak

Öz

The main purpose of this study is to evaluate the knowledge, attitudes and practices of healthcare professionals towards the novel coronavirus during the rapid rise of the COVID-19 epidemic and to determine the mediating effect of attitude on the effect of knowledge level on practices. Hospital-based cross-sectional research design was used in the study. The population of the study consisted of the healthcare workers of Istanbul Training and Research Hospital, which provides secondary healthcare services, and Yedikule Chest Diseases and Thoracic Surgery Training and Research Hospital, which provides tertiary treatment, in Istanbul. Convenience sampling method was preferred in the study. The data were collected by the researchers themselves using the online questionnaire technique. The total number of questionnaires that were evaluated and used in the analysis of the data is 409. SPSS and AMOS package programs were used in the analysis of the data. Descriptive statistics, independent sample t-test, ANOVA test and structural equation modeling were applied to the data. The findings obtained with the structural equation analysis showed that the construct validity of the model was provided. In addition, the path analysis revealed that the direct and indirect impact of knowledge level about COVID-19 on practices towards COVID-19 (mediated by attitude towards COVID-19) has an acceptable index of fit. A great majority of the healthcare workers had sufficient knowledge, a favorable attitude and good practices about sources, transmission, symptoms, signs, prognosis, treatment, management and preventive measures of COVID-19. The knowledge level about COVID-19 has both a direct and indirect impact on practices towards COVID-19 through the mediating role of attitude.

Anahtar Kelimeler

• COVID-19 outbreak
• knowledge
• attitudes
• practices
• healthcare workers

Kaynakça

1. Ahmed, M. A., Rehab, H. E., Mahdi, A. A., and Maher, E. (2020). Knowledge and attitudes towards Middle East respiratory sydrome-coronavirus (MERS-CoV) among health care workers in south-western Saudi Arabia. East Mediterr Health J., 26 (4), 435-442. , https://doi.org/10.26719/emhj.19.079.
2. Ali, S., Noreen, S., Farooq, I., Bugshan, A., and Vohra, F. (2020). Risk Assessment of Healthcare Workers at the Frontline against COVID-19. Pak J Med Sci., 36, 99-103. doi:10.12669/pjms.36. COVID19-S4.2790
3. Asaad, A. M., El-Sokkary, R., Alzamanan, M., and El-Shafei, M. (2020). Knowledge and attitudes towards Middle East respiratory syndrome-coronavirus (MERS-CoV) among health care workers in south-western Saudi Arabia. East Mediterr Health J., 26 (4), 435-442. https://doi.org/10.26719/emhj.19.079.
4. Atkinson, P., French, J., Lang, E., McColl, T., and Mazurik L. (2020). Just the Facts: Protecting frontline clinicians during the COVID-19 pandemic. Canadian Journal of Emergency Medicine, 1-5.
5. Bhagavathula, A. S., Aldhaleei, W. A., Rahmani, J., Mahabadi, M. A., and Bandari, D. K. (2020). Novel Coronavirus (COVID-19) Knowledge and Perceptions: A Survey on Healthcare workers. medRxiv, https://doi.org/10.1101/2020.03.09.20033381
6. Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.
7. Byrne, B. M. (2001). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Lawrence Erlbaum Associates.
8. Cetintepe, S. P., and İlhan, M. N. (2020). COVID-19 Salgınında Sağlık Çalışanlarında Risk Azaltılması. Journal of Biotechnology and Strategic Health Research, 4, 50-54.

9. Çobanoğlu, N. (2009). Ölümcül Olabilen Bulaşıcı Hastalıklarla İlgili Tıbbi Araştırmalarda Etik, Sağlık Bilimlerinde Süreli Yayıncılık, Ed. Orhan Yılmaz, TÜBİTAK, Ulakbim, Ankara, s.29-38.
10. Ergün, E., Ergün, Ş., and Çelebi, İ. (2020). Acil Sağlık Hizmetleri Personellerinin COVID-19 Hakkında Bilgi, Korunma Düzeyleri ve Etkileyen Etmenler. Paramedik ve Acil Sağlık Hizmetleri Dergisi, 1(1), 16-27.
11. Fornell, C. and Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error, Journal of Marketing Research, 48, 39-50.
12. Guan, W. J., Ni, Z. Y., Hu, Y, Liang, W. H., Ou, C. Q., and He, J. X. et al. (2020). Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med., 1-13.
13. Hartmann, S., Rubin, Z., and Sato, H. et al. (2020). Coronavirus 2019 (COVID-19) Infections Among Healthcare Workers, Los Angeles County, Clin Infect Dis. 2020 Aug 17:ciaa1200. doi:10.1093/cid/ciaa1200. Epub ahead of print. PMID: 32803237; PMCID: PMC7454348.
14. Huynh, G., Nguyen, T. N. H., Tran, V. K., Vo, K. N., Vo, V. T., and Pham, L. A. (2020). Knowledge and attitude toward COVID-19 among healthcare workers at District 2 Hospital, Ho Chi Minh City. Asian Pacific Journal of Tropical Medicine, 13(6), 260-265. https://doi.org/10.4103/1995-7645.280396.
15. Jespersen, S., Mikkelsen, S., and Greve, T. et al. (2020). Severe Acute Respiratory Syndrome Coronavirus 2 Seroprevalence Survey Among 17 971 Healthcare and Administrative Personnel at Hospitals, Prehospital Services, and Specialist Practitioners in the Central Denmark Region. Clinical Infectious Diseases, ciaa1471, doi: 10.1093/cid/ciaa1471.
16. Kalaycı, Ş. (2008). SPSS Uygulamalı Çok Değişkenli İstatistik Teknikleri (3. Baskı) Ankara: Asil Yayın Dağıtım.
17. Khasawneh, A. I., Humeidan, A. A., Alsulaiman, J. W., Bloukh, S., and Ramadan, M. (2020). Medical students and COVID-19: Knowledge, attitudes, and precautionary measures. a descriptive study from Jordan. Frontiers in Public Health. https://dx.doi.org/10.3389/fpubh.2020.00253
18. Kim, O. S. and Oh, J. H. (2016). The Convergence Study on Anxiety, Knowledge, Infection Possibility, Preventive Possibility and Preventive Behavior Level of MERS in Nursing Students. Journal of the Korea Convergence Society, 7(3), 59-69.
19. Limbu, D. K., Piryani, R. M., and Sunny, A. K. (2020). Healthcare workers’ knowledge, attitude and practices during the COVID-19 pandemic response in a tertiary care hospital of Nepal. PLoS ONE, 15(11): e0242126. https://doi.org/10.1371/journal.pone.0242126
20. Micceri, T. (1989). The unicorn, the normal curve, and other improbable creatures. Psychological Bulletin, 105, 156-166, DOI:10.1037/0033-2909.105.1.156.
21. Munro, B. H. (2005). Statistical Methods For Health Care Research. Philadelphia: Lippincott Williams and Wilkins, p.351-376.
22. Nguyen, L. H., Drew, D. A., and Graham, M. S., et al. (2020). Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Health, 5: e475–83.
23. Papagiannis, D., Malli, F., Raptis, D. G., Papathanasiou, I. V., and Fradelos, E. C. et al. (2020). Assessment of Knowledge, Attitudes, and Practices towards New Coronavirus (SARS-CoV-2) of Health Care Professionals in Greece before the Outbreak Period. International Journal of Environmental Research and Public Health, 17, 4925; doi:10.3390/ijerph17144925
24. Puspitasari, I. M., Yusuf, L., Sinuraya, R. K., Abdullah, R., and Koyama, H. (2020). Knowledge, Attitude, and Practice During the COVID-19 Pandemic: A Review. Journal of Multidisciplinary Healthcare, 13, 727–733.
25. Rajakaruna, S. J., Liu, W. B., Ding, Y. B., and Cao, G. W. (2017). Strategy and technology to prevent hospital-acquired infections: Lessons from SARS, Ebola, and MERS in Asia and West Africa. Military Medical Research, 4(1), 32.
26. Rothe, C., Schunk, M., Sothmann, P., Bretzel, G., Froeschl, G., and Wallrauch, C. et al. (2020). Transmission of 2019-NCOV infection from an asymptomatic contact in Germany. N Engl J Med., 382(10), 970-971.
27. Sayed, M. E., Kue, R., Mcneil, C., and Dyer, K. S. (2011). A Descriptive Analysis of Occupational Health Exposure in an Emergency Medical Services System. Prehosp Emerg Care, 15, 506-510.
28. Smidt, R. K., Levine, D. M., & Ramsey, P. P. (2001). Applied Statistics. Prentice Hall.
29. Söğüt, S., Dolu, I. and Cangol, E. (2020). The relationship between COVID‐19 Knowledge Levels and Anxiety States of Midwifery Students During the Outbreak: A Cross‐ Sectional Web‐Based Survey. Perspectives in Psychiatric Care, https://dx.doi.org/10.1111/ppc.12555
30. Tabachnick, B. G. and Fidell, L. S. (2013). Using Multivariate Statistics (6th ed.). Boston, MA: Pearson.
31. Wang, D., Hu, B., and Hu, C., et al. (2020). Clinical characteristics of 138 hospitalised patients with 2019 novel coronavirusinfected pneumonia in Wuhan, China. JAMA, 323, 1061–1069.
32. Wang, C., Hornby, P.W., Hayden, F.G., and Gao, G.F. (2020). A Novel Coronavirus Outbreak of Global Health Concern. Lancet, 395(10223), 496.
33. World Health Organization (WHO). (2020). Coronavirus Disease (COVID-19) Dashboard.: https://COVID19.who.int/table
34. Yen, M-Y., Lin, Y-E., Lee, C-H., Ho, M-S., Huang, F-Y., and Chang, S-C., et al. (2011). Taiwan's traffic control bundle and the elimination of nosocomial severe acute respiratory syndrome among healthcare workers. Journal of Hospital Infection, 77(4), 332-337.
35. Yen, M-Y., Schwartz, J., Wu, J-SJ., and Hsueh, P-R. (2015). Controlling Middle East respiratory syndrome: lessons learned from severe acute respiratory syndrome. Clinical Infectious Diseases, 61(11), 1761-1762.
36. Zhang, M., Zhou, M., Tang, F., Wang, Y., and Nie, H. (2020). Knowledge, Attitude and Practice Regarding COVID-19 Among Health Care Workers in Henan, China. Journal of Hospital Infection,105, 183-187. https://dx.doi.org/10.1016/j.jhin.2020.04.012
37. Zheng, L., Wang, X., and Zhou, C. et al. (2020). Analysis of the Infection Status of Healthcare Workers in Wuhan During the COVID-19 Outbreak: A Cross-sectional Study. Clin Infect Dis, 71(16), 2109-2113. doi:10.1093/cid/ciaa588. PMID: 32409825; PMCID: PMC7239233.