Araştırma Makalesi

Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye

Cilt: 6 Sayı: 10 1 Nisan 2024
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Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye

Öz

The aim of this research was to make a retrospective analysis of the Google Trends data related to birth methods and place according to the geographical regions of Turkey. The Google Trends data were collected according to six different time series between 01 Jan 2004 - 31 Dec 2022. The data were collected on 26 Jul 2021 from the seven geographical regions of Turkey and across Turkey using the keywords “normal birth”, “cesarean section”, “vaginal birth”, “home birth”, and “water birth”, which are among the methods of delivery. Considering Turkey, geographical regions, and time series, the data analysis was performed using percentages, Ethical permission was not required due to the nature of the study and due to the openness of the data. In all time series, it was seen that the search for “normal birth” was popular in the sample cities selected from Turkey and the seven geographical regions, and that the popularity, however, decreased over time. The Google searches of individuals for their birth preferences and place may vary depending on the cultural structure of the region they live in, cultural interaction, health policies during the COVID-19 pandemic, socioeconomic status, COVID-19 restrictions, fear of COVID-19, access to health services.

Anahtar Kelimeler

Kaynakça

  1. Akgül, I., 1994. Zaman Serisi Analizi ve Öngörü Modelleri. Öneri Dergisi. 1(1), 52-69.
  2. Aktaş, S., Yılar, Z., 2018. Annelerin vajinal doğumu tercih etme nedenlerinin incelenmesi: Bir nitel araştırma örneği. Gümüşhane Univ Sağlık Bilimleri Derg . 7(1):111-124.
  3. Ay, F., Ekmekçi, K. A., Batuhan, F., Oğuz, A., 2019. What do women share on social media about the normal delivery action? Example of (an example from) www.kadinlarkulubu.com. Acıbadem University Health Sciences Journal. 10(1), 49-54. Doi: 10.31067/0.2019.106.
  4. Aydın, O., Aslantaş Bostan, P., Özgür, E. M., 2018. Spatial distribution and modelling of the total fertility rate in Türkiye using spatial data analysis techniques. Journal of Geography. 37, 27-45. Doi: 10.26650/JGEOG434650
  5. Betran, A., Temmerman, M., Kingdon, C., Mohiddin, A., Opiyo, N., Torloni, M., Downe, S., 2018. Interventions to reduce unnecessary caesarean sections in healthy women and babies. The Lancet. 392(10155), 1358-1368. Doi: 10.1016/S0140-6736(18)31927-5
  6. Betran, A., Ye, J., Moller, A., 2021. Trends and projections of caesarean section rates: global and regional estimates. BMJ Global Health. 6:e005671. Doi: 10.1136/bmjgh-2021-005671
  7. Black, C., Kaye, J., Jick, H., 2005. Cesarean delivery in the United Kingdom: time trends in the general practice research database. Obstetrics & Gynecology. 5, 106-151. Doi: 10.1097/01.AOG.0000160429.22836.c0
  8. Boerma, T., Ronsmans, C., Melesse, D., 2018. Global epidemiology of use of and disparities in caesarean sections. The Lancet. 392(10155), 1341-8. Doi: 10.1016/S0140-6736(18)31928-7.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Aile ve Hanehalkı Çalışmaları

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

1 Nisan 2024

Gönderilme Tarihi

19 Kasım 2023

Kabul Tarihi

2 Şubat 2024

Yayımlandığı Sayı

Yıl 2024 Cilt: 6 Sayı: 10

Kaynak Göster

APA
Özsezer, G., Gür Boz, A., & Mermer, G. (2024). Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye. Uluslararası Sosyal Bilimler ve Eğitim Dergisi, 6(10), 127-144. https://izlik.org/JA42TZ68KL
AMA
1.Özsezer G, Gür Boz A, Mermer G. Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye. USBED. 2024;6(10):127-144. https://izlik.org/JA42TZ68KL
Chicago
Özsezer, Gözde, Arife Gür Boz, ve Gülengül Mermer. 2024. “Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye”. Uluslararası Sosyal Bilimler ve Eğitim Dergisi 6 (10): 127-44. https://izlik.org/JA42TZ68KL.
EndNote
Özsezer G, Gür Boz A, Mermer G (01 Nisan 2024) Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye. Uluslararası Sosyal Bilimler ve Eğitim Dergisi 6 10 127–144.
IEEE
[1]G. Özsezer, A. Gür Boz, ve G. Mermer, “Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye”, USBED, c. 6, sy 10, ss. 127–144, Nis. 2024, [çevrimiçi]. Erişim adresi: https://izlik.org/JA42TZ68KL
ISNAD
Özsezer, Gözde - Gür Boz, Arife - Mermer, Gülengül. “Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye”. Uluslararası Sosyal Bilimler ve Eğitim Dergisi 6/10 (01 Nisan 2024): 127-144. https://izlik.org/JA42TZ68KL.
JAMA
1.Özsezer G, Gür Boz A, Mermer G. Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye. USBED. 2024;6:127–144.
MLA
Özsezer, Gözde, vd. “Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye”. Uluslararası Sosyal Bilimler ve Eğitim Dergisi, c. 6, sy 10, Nisan 2024, ss. 127-44, https://izlik.org/JA42TZ68KL.
Vancouver
1.Gözde Özsezer, Arife Gür Boz, Gülengül Mermer. Using Google trends to predict birth methods and place: A retrospective analysis of data for Türkiye. USBED [Internet]. 01 Nisan 2024;6(10):127-44. Erişim adresi: https://izlik.org/JA42TZ68KL

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Baş Editör: Prof. Dr. Aytekin Demircioğlu

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