Araştırma Makalesi
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Türkiye'de COVID-19 aşı tereddütünün YouTube analiz yöntemi ile araştırılması

Yıl 2022, Cilt: 6 Sayı: 1, 8 - 16, 30.04.2022
https://doi.org/10.34084/bshr.1028620

Öz

Amaç: Günümüzde pek çok kişi, Coronavirüs hastalığı 2019 (COVID-19) aşıları da dahil olmak üzere sağlık bilgilerine ulaşmak için internette arama yapmaktadır. YouTube en yaygın kullanılan web sitelerinden biridir. Bununla birlikte, sağlıkla ilgili YouTube videolarının kalitesi ve doğruluğu hala tartışmalıdır. Bu çalışmada, YouTube analiz yöntemini kullanarak Türkiye'deki COVID-19 aşı tereddütünü araştırmayı amaçladık.
Gereç ve Yöntem: Bu çalışmada “COVID 19” VEYA “koronavirüs” VEYA “SARSCOV 2”' ve “aşı” VEYA “aşılama” ve “aşı tereddütü” VEYA “aşı kararsızlığı” anahtar kelimeleri kullanıldı. YouTube'da video aramak için ilk olarak, Türkçe dilinde olmayan videolar ve yinelenen videolar hariç tutuldu. Videolarla ilgili süre (saniye), izlenme sayısı, yorum sayısı, toplam beğeni/beğenmeme gibi bazı detaylar kaydedildi. Videoların DISCERN (Quality Criteria for Consumer Health Information), JAMA (Journal of the American Medical Association) puanları ve Video Güç İndeksi (VPI) değerleri hesaplandı.
Sonuçlar: Videoların çoğu haber ajansları tarafından yüklendi (%48). Videoların DISCERN puanları çok kötü ile iyi arasında değişiyordu. Ortalama JAMA puanı 2.9 olarak bulundu ve yüksek puan olarak kabul edildi. Videoların kaynakları arasında VPI ve JAMA puanlarında istatistiksel olarak anlamlı bir fark vardı (p < 0,05).
Sonuç: Akademik ve resmi kuruluşlar tarafından hazırlanan video içeriklerinin kalitesi artırılarak aşı tereddütü azaltılabilir. Topluluk aşılama davranışlarında YouTube videolarının doğru kullanımı, COVID 19'un topluluk arasında yayılmasında önemli bir rol oynayabilir ve pandeminin kontrol altına alınmasına yardımcı olabilir.

Kaynakça

  • 1. https://www.worldometers.info/coronavirus/ [Access date: 22.02.2021]
  • 2. Evolution of the COVID-19 vaccine development landscape. (n.d.). Retrieved September 8, 2020, from https://www.nature.com/articles/d41573-020-00151- 8?S=03
  • 3. Yıldırım, S. Salgınların Sosyal-Psikolojik Görünümü: Covid-19 (Koronavirüs) Pandemi Örneği. Electronic Turkish Studies.2020; 15(4):1331-1351.
  • 4. Rzymski P, Borkowski L, Drąg M, et al. The strategies to support the COVID-19 vaccination with evidence-based communication and tackling misinformation. Vaccines. 2021; 9(2):109.
  • 5. Yenal S. COVID-19 Salgınının Uluslararası Güvenlik Açısından Değerlendirilmesi. Electronic Turkish Studies.2020; 15(4): 1315-1329.
  • 6. Dindar Demiray E, Alkan Çeviker S. Aşı ve Toplumsal Korunma. J Biotechinol & Strategic Health Res. 2020; 4: 37-44.
  • 7. Kutlu HH, Altındiş M. Anti-Vaccination. Flora.2018;23(2):47-58.
  • 8. Bozkurt AP, Aras I. Cleft Lip and Palate YouTube Videos: Content Usefulness and Sentiment Analysis. Cleft Palate Craniofac J. 2021;58(3):362-368.
  • 9. Faul F, Erdfelder E, Lang AG, et al. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175-191.
  • 10. Abul-Fottouh D, Song MY, Gruzd A. Examining algorithmic biases in YouTube's recommendations of vaccine videos. Int J Med Inform. 2020; 140:104175. doi: 10.1016/j.ijmedinf.2020.104175.
  • 11. Charnock D, Shepperd S, Needham G, et al. DISCERN: an instrument for judging the quality of written consumer health information on treatment choices. J Epidemiol Community Health.1999;53(2):105-111. doi:10.1136/jech.53.2.105
  • 12. Wu V, Lee DJ, Vescan A, et al. Evaluating YouTube as a Source of Patient Information for Functional Endoscopic Sinus Surgery. Ear Nose Throat J. 2020:145561320962867. doi: 10.1177/0145561320962867.
  • 13. Gokcen HB, Gumussuyu G. A Quality Analysis of Disc Herniation Videos on YouTube. World Neurosurg. 2019: S1878-8750(19)30246-3. doi: 10.1016/j.wneu.2019.01.146.
  • 14. Silberg WM, Lundberg GD, Musacchio RA. Assessing, controlling, and assuring the quality of medical information on the internet: Caveant lector et viewor--let the reader and viewer beware. JAMA. 1997;277(15):1244–1245.
  • 15. Aydin MF, Aydin MA. Quality and reliability of information available on YouTube and Google pertaining gastroesophageal reflux disease. Int J Med Inform. 2020; 137:104107. doi: 10.1016/j.ijmedinf.2020.104107.
  • 16. Yilmaz H, Aydin MN. YouTube™ video content analysis on space maintainers. J Indian Soc Pedod Prev Dent. 2020;38(1):34-40.
  • 17. Covolo L, Ceretti E, Passeri C, et al. What arguments on vaccinations run through YouTube videos in Italy? A content analysis. Hum Vaccin Immunother. 2017;13(7):1693–1699.
  • 18. Teng S, Khong KW, Pahlevan Sharif S, et al. YouTube Video Comments on Healthy Eating: Descriptive and Predictive Analysis. JMIR Public Health Surveill. 2020;6(4): e19618. doi: 10.2196/19618.
  • 19. St Lawrence S, Hallman J, Sherony R. Video from user-generated content as a source of pre-crash scenario naturalistic driving data. Traffic Inj Prev. 2020:1-3. doi: 10.1080/15389588.2020.1829920. Epub ahead of print. PMID: 33155861.
  • 20. Hernández-García I, Giménez-Júlvez T. YouTube as a Source of Influenza Vaccine Information in Spanish. Int J Environ Res Public Health. 2021;18(2):727. doi: 10.3390/ijerph18020727.
  • 21. Aquino F, Donzelli G, De Franco E, et al. The web and public confidence in MMR vaccination in Italy. Vaccine. 2017; 35:4494–44948.
  • 22. Yiannakoulias N, Slavik CE, Chase M. Expressions of pro- and anti-vaccine sentiment on YouTube. Vaccine. 2019;37(15):2057-2064. doi: 10.1016/j.vaccine.2019.03.001.
  • 23. Tran BX, Boggiano VL, Nguyen LH, et al. Media representation of vaccine side effects and its impact on utilization of vaccination services in Vietnam. Patient Prefer Adherence. 2018;12:1717-1728.
  • 24. Donzelli G, Palomba G, Federigi I, Aquino F, Cioni L, Verani M, et al. Misinformation on vaccination: A quantitative analysis of YouTube videos. Hum Vaccin Immunother. 2018;14(7):1654-1659.

Investigation of COVID-19 vaccine hesitation in Turkey with YouTube analysis method

Yıl 2022, Cilt: 6 Sayı: 1, 8 - 16, 30.04.2022
https://doi.org/10.34084/bshr.1028620

Öz

Aim: Nowadays many people search the internet to gain health information including Coronavirus disease 2019 (COVID-19) vaccines. YouTube™ is one of the most widely used websites. However, the quality and accuracy of health-related YouTube™ videos are still controversial. In this study we aimed to research the COVID-19 vaccine hesitation in Turkey by using YouTube analyses method.
Material and Method: In this study, “COVID 19’’ OR “coronavirus’’ OR “SARSCOV 2’’ ‘and “vaccine’’ OR “vaccination’’ and “vaccine hesitancy’’ OR “vaccine hesitation’’ keywords were used to search videos on YouTube™. Firstly, non-Turkish videos and duplicate videos were excluded. Some details about videos such as duration (seconds), view count, number of comments, total likes/ dislikes were recorded. DISCERN (Quality Criteria for Consumer Health Information), JAMA (Journal of the American Medical Association) scores, and Video Power Index (VPI) values of the videos were calculated.
Results: Most of the videos were uploaded by news agencies (48%). DISCERN scores of the videos were ranged between very poor and good. The mean JAMA score was found 2.9 that is accepted as a high score. There was a statistically significant difference in the VPI and JAMA scores among videos’ sources (p < 0,05).
Conclusion: Vaccine hesitation can be reduced by increasing the quality of the video content prepared by academic and govermental organizations. The correct use of YouTube videos in community vaccination behaviors can play an important role in the spread of COVID 19 among the community and help control the pandemic.

Kaynakça

  • 1. https://www.worldometers.info/coronavirus/ [Access date: 22.02.2021]
  • 2. Evolution of the COVID-19 vaccine development landscape. (n.d.). Retrieved September 8, 2020, from https://www.nature.com/articles/d41573-020-00151- 8?S=03
  • 3. Yıldırım, S. Salgınların Sosyal-Psikolojik Görünümü: Covid-19 (Koronavirüs) Pandemi Örneği. Electronic Turkish Studies.2020; 15(4):1331-1351.
  • 4. Rzymski P, Borkowski L, Drąg M, et al. The strategies to support the COVID-19 vaccination with evidence-based communication and tackling misinformation. Vaccines. 2021; 9(2):109.
  • 5. Yenal S. COVID-19 Salgınının Uluslararası Güvenlik Açısından Değerlendirilmesi. Electronic Turkish Studies.2020; 15(4): 1315-1329.
  • 6. Dindar Demiray E, Alkan Çeviker S. Aşı ve Toplumsal Korunma. J Biotechinol & Strategic Health Res. 2020; 4: 37-44.
  • 7. Kutlu HH, Altındiş M. Anti-Vaccination. Flora.2018;23(2):47-58.
  • 8. Bozkurt AP, Aras I. Cleft Lip and Palate YouTube Videos: Content Usefulness and Sentiment Analysis. Cleft Palate Craniofac J. 2021;58(3):362-368.
  • 9. Faul F, Erdfelder E, Lang AG, et al. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175-191.
  • 10. Abul-Fottouh D, Song MY, Gruzd A. Examining algorithmic biases in YouTube's recommendations of vaccine videos. Int J Med Inform. 2020; 140:104175. doi: 10.1016/j.ijmedinf.2020.104175.
  • 11. Charnock D, Shepperd S, Needham G, et al. DISCERN: an instrument for judging the quality of written consumer health information on treatment choices. J Epidemiol Community Health.1999;53(2):105-111. doi:10.1136/jech.53.2.105
  • 12. Wu V, Lee DJ, Vescan A, et al. Evaluating YouTube as a Source of Patient Information for Functional Endoscopic Sinus Surgery. Ear Nose Throat J. 2020:145561320962867. doi: 10.1177/0145561320962867.
  • 13. Gokcen HB, Gumussuyu G. A Quality Analysis of Disc Herniation Videos on YouTube. World Neurosurg. 2019: S1878-8750(19)30246-3. doi: 10.1016/j.wneu.2019.01.146.
  • 14. Silberg WM, Lundberg GD, Musacchio RA. Assessing, controlling, and assuring the quality of medical information on the internet: Caveant lector et viewor--let the reader and viewer beware. JAMA. 1997;277(15):1244–1245.
  • 15. Aydin MF, Aydin MA. Quality and reliability of information available on YouTube and Google pertaining gastroesophageal reflux disease. Int J Med Inform. 2020; 137:104107. doi: 10.1016/j.ijmedinf.2020.104107.
  • 16. Yilmaz H, Aydin MN. YouTube™ video content analysis on space maintainers. J Indian Soc Pedod Prev Dent. 2020;38(1):34-40.
  • 17. Covolo L, Ceretti E, Passeri C, et al. What arguments on vaccinations run through YouTube videos in Italy? A content analysis. Hum Vaccin Immunother. 2017;13(7):1693–1699.
  • 18. Teng S, Khong KW, Pahlevan Sharif S, et al. YouTube Video Comments on Healthy Eating: Descriptive and Predictive Analysis. JMIR Public Health Surveill. 2020;6(4): e19618. doi: 10.2196/19618.
  • 19. St Lawrence S, Hallman J, Sherony R. Video from user-generated content as a source of pre-crash scenario naturalistic driving data. Traffic Inj Prev. 2020:1-3. doi: 10.1080/15389588.2020.1829920. Epub ahead of print. PMID: 33155861.
  • 20. Hernández-García I, Giménez-Júlvez T. YouTube as a Source of Influenza Vaccine Information in Spanish. Int J Environ Res Public Health. 2021;18(2):727. doi: 10.3390/ijerph18020727.
  • 21. Aquino F, Donzelli G, De Franco E, et al. The web and public confidence in MMR vaccination in Italy. Vaccine. 2017; 35:4494–44948.
  • 22. Yiannakoulias N, Slavik CE, Chase M. Expressions of pro- and anti-vaccine sentiment on YouTube. Vaccine. 2019;37(15):2057-2064. doi: 10.1016/j.vaccine.2019.03.001.
  • 23. Tran BX, Boggiano VL, Nguyen LH, et al. Media representation of vaccine side effects and its impact on utilization of vaccination services in Vietnam. Patient Prefer Adherence. 2018;12:1717-1728.
  • 24. Donzelli G, Palomba G, Federigi I, Aquino F, Cioni L, Verani M, et al. Misinformation on vaccination: A quantitative analysis of YouTube videos. Hum Vaccin Immunother. 2018;14(7):1654-1659.
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Sağlık Kurumları Yönetimi
Bölüm Araştırma Makalesi
Yazarlar

Sevil Alkan 0000-0003-1944-2477

Bülent Akkaya 0000-0003-1252-9334

Hatice Öntürk Akyüz 0000-0002-6206-2616

Yayımlanma Tarihi 30 Nisan 2022
Kabul Tarihi 8 Ocak 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 6 Sayı: 1

Kaynak Göster

AMA Alkan S, Akkaya B, Öntürk Akyüz H. Investigation of COVID-19 vaccine hesitation in Turkey with YouTube analysis method. J Biotechnol and Strategic Health Res. Nisan 2022;6(1):8-16. doi:10.34084/bshr.1028620
  • Dergimiz Uluslararası hakemli bir dergi olup TÜRKİYE ATIF DİZİNİ, TürkMedline, CrossREF, ASOS index, Google Scholar, JournalTOCs, Eurasian Scientific Journal Index(ESJI), SOBIAD ve ISIindexing dizinlerinde taranmaktadır. TR Dizin(ULAKBİM), SCOPUS, DOAJ için başvurularımızın sonuçlanması beklenmektedir.