Assessment of Worldwide Internet Data on the interest in Orthodontics: A Google Trends Analysis

Öz

Objective: The aim of study is to examine the interest in orthodontics in the last 5 years using Google Trends data all over the world.

Materials and Methods: On July 6, 2020, the Google Trends application was searched for the last five years. Search results were recorded separately for all keywords and separately for 26 countries with sufficient data. The mean of all search results is taken and a Google Trends Value (GTV) is obtained for the countries. These data are correlated with population, Gross Domestic Product (GDP) and knowledge of English (English Proficiency Index – EPI) in countries. Pearson correlation test was used for correlation values between Population, GDP and EPI with Google Trend values.

Results: According to the table, the highest GTV were observed in United States (65.33); lowest GTV were observed in France. According to the statistically analysis, a positive correlation was found between GTV with both population and GDP and EPI values. Finally, a positive correlation was found between GDP and EPI values and this positive correlation was statistically significant(p<0.05).

Conclusion: No significant relationship was found between the interest in orthodontics and the population. There is a significant positive correlation between the Gross National Product and the level of knowledge of English.

Anahtar Kelimeler

• internet data
• orthodontics
• Google trends

Ortodontiye İlişkin Dünya Genelindeki İnternet Verilerinin Değerlendirilmesi: Google Trends Analizi

Öz

Amaç: Çalışmanın amacı, tüm dünyada Google Trends arama verilerini kullanarak son 5 yılda ortodonti konusuna olan ilgiyi incelemektir.

Materyal ve Metot: 6 Temmuz 2020’de, Google Trends uygulamasında son beş yıldaki arama verileri tarandı. Arama sonuçları, tüm anahtar kelimeler için ayrı ayrı ve yeterli veriye sahip 26 ülke için ayrı olarak kaydedildi. Tüm arama sonuçlarının ortalaması alındı ve ülkeler için bir Google Trends Değeri (GTV) elde edildi. Bu veriler nüfus, Gayri Safi Yurtiçi Hâsıla (GDP) ve ülkelerdeki İngilizce bilgisi (İngilizce Yeterlilik Endeksi – EPI) ile ilişkilidir. Nüfus, GDP ve EPI ile Google Trends değerleri arasındaki korelasyon değerleri için Pearson korelasyon testi kullanıldı.

Bulgular: Tabloya göre, en yüksek GTV değeri ABD'de gözlenmiştir (65,33); Fransa'da en düşük GTV değeri görülmüştür. İstatistiksel analize göre, GTV ile hem nüfus hem de GDP ile EPI değerleri arasında pozitif bir korelasyon bulundu. Son olarak GDP ve EPI değerleri arasında pozitif korelasyon bulundu ve bu pozitif korelasyon istatistiksel olarak anlamlı bulunmuştur (p<0,05).

Sonuç: Ortodontiye olan ilgi ile nüfus arasında anlamlı bir ilişki bulunamamıştır. Gayri Safi Milli Hasıla ile İngilizce bilgi düzeyi arasında ise anlamlı bir pozitif ilişki vardır.

Anahtar Kelimeler

• Google Trends
• internet verileri
• ortodonti

Kaynakça

1. Tamer G. Demographic characteristics affecting service demand in private health ınstitutions; aesthetic medical centers example. Int J Entrepr Manag Inquir (EMI). 2018;2(3):91-105.
2. Germa A, Kaminski M, Nabet C. Impact of social and economic characteristics on orthodontic treatment among children and teenagers in France. Community Dent Oral Epidemiol. 2010;38(2):171–179.
3. Van Wezel NA, Bos A, Prahl C. Expectations of treatment and satisfaction with dentofacial appearance in patients applying for orthodontic treatment. Am J Orthod Dentofacial Orthop. 2015;147(6):698-703.
4. Bresnahan BW, Kiyak HA, Masters SH, McGorray SP, Lincoln A, King G. Quality of life and economic burdens of malocclusion in U.S. patients enrolled in Medicaid. J Am Dent Assoc. 2010;141(10):1202-1212.
5. Kim Y. Study on the perception of orthodontic treatment according to age: A questionnaire survey. Korean J Orthod. 2017;47:215-221.
6. Proffit WR, Fields HW Jr, Moray LJ. Prevalence of malocclusion and orthodontic treatment need in the United States: estimates from the NHANES IIIsurvey. Int J Adult Orthodon Orthognath Surg. 1998;13:97-106.
7. Chestnutt IG, Burden DJ, Steele JG, Pitts NB, Nuttall NM, Morris AJ. The orthodontic condition of children in the United Kingdom, 2003. Br Dent J. 2006;200:609–612.
8. Kamak H, Çağlaroğlu M, Çatalbaş B, Keklik H. İç anadolu bölgesi ortodontik tedavi ihtiyacının ICON indeksi kullanılarak değerlendirilmesi. Atatürk Üniv Diş Hek Fak Derg. 2012;22:149-153.

9. Kılıçoğlu H, Arman S, Par C, Çifter M, Akar B. İstanbul Üniversitesi ortodonti anabilim dalına başvuran hastaların profilinin incelenmesi. Türk Ortodonti Derg. 2003;16:167-174.
10. Ugur T, Ciger S, Aksoy A, Telli A. An epidemiological survey using the Treatment Priority Index (TPI). Eur J Orthod. 1998;20:189-193.
11. Noll D. Mahon B. Shroff B. Carrico C. Lindauer SJ. Twitter analysis of the orthodontic patient experience with braces vs Invisalign. Angle Orthod. 2017;87:377–383.
12. Al Ghamdi KM. Moussa NA. Internet use by the public to search for health-related information. Int J Med Inform. 2012;81:363–373.
13. Allem JP, Leas EC, Caputi TL, et al. The Charlie Sheen effect on rapid in-home human immunodeficiency virus test sales. Prev Sci. 2017;18(5):541-544
14. Ayers JW, Althouse BM, Johnson M, Cohen JE. Circaseptan (weekly) rhythms in smoking cessation considerations. JAMA Intern Med. 2014;174:146–148.
15. Zotti F, Zotti R, Albanese M, Nocini PF, Paganelli C. Implementing post-orthodontic compliance among adolescents wearing removable retainers through Whatsapp: a pilot study. Patient Prefer Adherence. 2019;13:609-615.
16. Papadimitriou A, Kakali L, Pazera P, Doulis I, Kloukos D. Social media and orthodontic treatment from the patient's perspective: a systematic review. Eur J Orthod. 2019;pii: cjz029. doi: 10.1093/ejo/cjz029.
17. Lena Y, Dindaroğlu F. Lingual orthodontic treatment: A YouTube™ video analysis. Angle Orthod. 2018;88(2):208-214.
18. Noll D, Mahon B, Shroff B, Carrico C, Lindauer SJ. Twitter analysis of the orthodontic patient experience with braces vs Invisalign. Angle Orthod. 2017;87(3):377-383.
19. Chan A, Antoun JS, Morgaine KC, Farella M. Accounts of bullying on Twitter in relation to dentofacial features and orthodontic treatment. J Oral Rehabil. 2017;44(4):244-250.
20. DiBiase AT, Sandler PJ. Malocclusion, orthodontics and bullying. Dental update. 2001;28(9):464-466.
21. Kuo E, Miller RJ. Automated custom-manufacturing technology in orthodontics. Am J Orthod Dentofacial Orthop. 2003;123(5):578-581.
22. Melkos AB. Advances in digital technology and orthodontics: a reference to the Invisalign method. Med Sci Monit. 2005;11(5):39-42.
23. McCrostie HS. Lingual orthodontics: the future. Semin Orthod. 2006;12(3):211-214.
24. Almuzian M, Gardner A. Adult orthodontics part 1: special considerations in treatment. Orthodontic Update. 2014;7(3):89-92.
25. McDonald F, Cobourne M. Adult orthodontics: perils and pitfalls. Prog Orthod. 2007;8(2):308-313.
26. Malik OH, McMullin A, Waring DT. Invisible orthodontics part 1: Invisalign. Dental update, 2013;40(3):203-215.
27. Panula K, Keski-Nisula L, Keski-Nisula K, Oikarinen K, Keski-Nisula S. Costs of surgical-orthodontic treatment in community hospital care: an analysis of the different phases of treatment. Int J Orthod Orthognath Surg. 2002;17(4):297-306.
28. Richmond S, Phillips CJ, Dunstan F, Daniels C, Durning P, Leahy F. Evaluating the cost-effectiveness of orthodontic provision. Dental Update. 2004;31(3):146-152.
29. Mondria J, Wu T. Imperfect financial integration and asymmetric information: competing explanations of the home bias puzzle? Canadian Journal of Economics 2013;46:310-337.
30. Mishra P, Newhouse D. “Does health aid matter ?” Journal of Health Economics, Corrected Proof. 2009;28(4):855-872.