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2024 | 75 | 1 |

Tytuł artykułu

Adaptation of the scale of effects of social media on eating behavior in Hungarian university students

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Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
Background. People live in a technological world, where social media is used very commonly. Social media has effects on eating behaviors, as in other aspects. For this reason, it is important to measure social media effect. Objective. This study aimed to adapt the Scale of Effects of Social Media on Eating Behaviour (SESMEB) that examines the effect of social media on eating behavior in Hungarian university students. Material and methods. The SESMEB was translated into the target language by taking various stages. The online questionnaire including general information, social media use, and the eighteen-item SESMEB was used to collect data. The scale was administered to the study group consisting of 213 Hungarian university students, and data from 203 of them were analyzed. Confirmatory factor analyses were performed to test construct validity, and the Cronbach alpha coefficient was calculated for the reliability of the scale in Hungarian. Results. Total correlation value was higher than 0.50 for all items of the scale. The fit indices were at an acceptable level or had a perfect fit. The t-values were significant at the level of 0.1 and ranged between 2.927 and 5.706. The Spearman– Brown coefficient was calculated at 0.894. The reliability coefficient of the scale was calculated to be 0.866. SESMEB scores were different according to spending time daily, sharing content, and using filters or Photoshop on social media (p<0.05). Conclusions. Higher than 0.80 Cronbach’s alpha coefficient and other results show that Hungarian SESMEB is a valid and reliable tool. Therefore, Hungarian SESMEB will be useful for further studies to determine the impact of social media on eating behaviors.

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Wydawca

-

Rocznik

Tom

75

Numer

1

Opis fizyczny

p.59-65,fig.,ref.

Twórcy

  • First and Emergency Aid Program, Vocational School of Health Services, Kirikkale University, Kirikkale, Turkiye
autor
  • Department of Biostatistics, Faculty of Medicine, Hacettepe University, Ankara, Turkiye
autor
  • Department of Marketing and Commerce, Faculty of Economics and Business, Debrecen University, Debrecen, Hungary

Bibliografia

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  • 2. Digital Around the World: Datareportal; 2021. Available https://datareportal.com/global-digital-overview (Accessed 01.09.2021)
  • 3. Internet usage in Hungary is expanding: Hungarian Central Statistical Office; 2020. Available https://www.ksh.hu/infografika/2021/internethasznalat_2021_eng.pdf (Accessed 01.09.2021)
  • 4. Hawkins LK, Farrow C, Thomas JM. Do perceived norms of social media users’ eating habits and preferences predict our own food consumption and BMI? Appetite 2020;149:104611. doi:10.1016/j.appet.2020.104611.
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  • 7. Rodgers RF, Slater A, Gordon CS, McLean SA, Jarman HK, Paxton SJ. A biopsychosocial model of social media use and body image concerns, disordered eating, and muscle-building behaviors among adolescent girls and boys. J Youth Adolesc 2020; 49 (2): 399-409. doi:10.1007/s10964-019-01190-0.
  • 8. Holland G, Tiggemann M. A systematic review of the impact of the use of social networking sites on body image and disordered eating outcomes. Body Image 2016;17:100-110. doi:10.1016/j.bodyim.2016.02.008.
  • 9. Keser A, Bayındır-Gümüş A, Kutlu H, Öztürk E. Development of the scale of effects of social media on eating behaviour: a study of validity and reliability. Public Health Nutr 2020;23 (10):1677-1683. doi:10.1017/S1368980019004270.
  • 10. SPSS I. IBM SPSS statistics for windows. Armonk, New York, USA: IBM SPSS. 2013;2.
  • 11. Arbuckle J. Amos 23.0 User’s Guide. Chicago: IBM SPSS. IBM; 2014.
  • 12. Kalaycı Ş. SPSS applied multivariate statistical techniques. Ankara: Asil Publishing. 2009.
  • 13. Tavşancıl E. Measurement of Attitudes and Data Analysis with SPSS [Tutumların ölçülmesi ve SPSS ile veri analizi]. Nobel Yayıncılık, Ankara. 2002 (in Turkish).
  • 14. Erkorkmaz U, Etikan İ, Demir O, Özdamar K. Confirmatory factor analysis and fit indices: Review [Doğrulayıcı Faktör Analizi ve Uyum İndeksleri]. Türkiye Klinikleri J Med Sci 2013;33(1):201-223.doi:10.5336/medsci.2011-26747.
  • 15. Tabachnick BG, Fidell LS, Ullman JB. Using multivariate statistics: pearson Boston, MA; 2007.
  • 16. Social Media Stats Hungary: statcounter; 2021. Available https://gs.statcounter.com/social-media-stats/all/hungary. (Accessed 25.09.2021)
  • 17. Sidani JE, Shensa A, Hoffman B, Hanmer J, Primack BA. The association between social media use and eating concerns among US young adults. J Acad Nutr Diet 2016;116(9):1465-1472. doi:10.1016/j.jand.2016.03.021.
  • 18. Charry K, Tessitore T. I tweet, they follow, you eat: Number of followers as nudge on social media to eat more healthily. Soc Sci Med 2021; 269: 113595. doi:10.1016/j.socscimed.2020.113595.
  • 19. Blundell K-L, Forwood S. Using a social media app, Instagram, to affect what undergraduate university students choose to eat. Appetite 2021; 157: 104887. doi:10.1016/j.appet.2020.104887.
  • 20. Watanabe-Ito M, Kishi E, Shimizu Y. Promoting healthy eating habits for college students through creating dietary diaries via a smartphone app and social media interaction: Online survey study. JMU 2020; 8(3): e17613. doi:10.2196/17613.
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Bibliografia

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