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ORTAOKUL ÖĞRENCİLERİNİN AKILLI TELEFON KULLANIMLARI VE BAĞIMLILIK DÜZEYLERİYLE İLGİLİ UNSURLAR

Year 2018, Volume: 8 Issue: 1, 1 - 23, 22.01.2018
https://doi.org/10.17943/etku.288822

Abstract

Bu çalışmada ortaokul 5. ve 6. sınıf öğrencilerinin akıllı
telefon kullanım durumlarını ve bağımlılık düzeyi tespit etmek, bağımlılık
düzeylerine ilişkili demografik değişkenleri ortaya çıkarmak amaçlanmaktadır.
2015-2016 eğitim-öğretim yılı bahar döneminde 5. ve 6. sınıfta okuyan 156
öğrenciyle gerçekleştirilen bu çalışmada veriler “Kişisel Bilgi Formu” ve
“Akıllı Telefon Bağımlılık Ölçeği (ATBÖ)” aracılığıyla toplanmıştır. Çalışmada
ilişkisel tarama modeli kullanılmıştır. Çalışmaya katılan öğrencilerin yaklaşık
yarısı her gün yaklaşık 1 saatten az akıllı telefon kullanmakta ve üçte biri
ise akıllı telefonu 2-3 saatte bir kontrol etmektedir. Öğrencilerin akıllı
telefonda yaptıkları işlemlere bakıldığında en sık yapılan işlemin “oyun oynama”
olduğu görülmektedir. Akıllı telefon bağımlılık ölçeğinden elde edilen puanlara
göre öğrencilerin yarıdan fazlası “Bağımlılık Gösterenler” grubunda yer
almaktadır. Akıllı telefon bağımlılığı ölçeği için “cinsiyet, İnternet kullanım
süresi, günlük akıllı telefon kullanım süresi, akıllı telefonu kontrol etme
sıklığı, akıllı telefonla sosyal medya ortamlarına erişim/kontrol etme sıklığı”
gruplarına ilişkin anlamlı bir fark bulunmuştur. Diskriminant fonksiyonunun
toplam doğru sınıflandırma olasılığı yüzdesi %63,7’dir. Araştırma sonucunda
“akıllı telefonla sosyal medya ortamlarına erişim/kontrol etme sıklığı”
değişkeninin bağımlılık gösteren ve göstermeyen öğrencileri en iyi
sınıflandıran değişken olduğu saptanmıştır. Bu çalışmanın en temel sonucu kadın
ve erkek öğrencilerin akıllı telefon bağımlılık düzeylerinde belirgin bir fark
olduğu şeklindedir. Bu bağlamda bu farkın nedenlerinin incelenmesi ve diğer
ülkelerde bu konu üzerine yapılan araştırmalarla elde edilen sonuçların
karşılaştırılması önerilebilir.




References

  • Augner, C., & Hacker, G. W. (2012). Associations between problematic mobile phone use and psychological parameters in young adults. International Journal of Public Health, 57(2), 437-441.
  • Billieux, J., & Van der Linden, M. (2012). Problematic use of the Internet and selfregulation: A review of the initial studies. The Open Addiction Journal, 5, 24–29.
  • Choi, K., Son, H., Park, M., Han, J., Kim, K., Lee, B., et al. (2009). Internet overuse and excessive daytime sleepiness in adolescents. Psychiatry and clinical neurosciences, 63(4), 455–462.
  • Choliz, M. (2012). Mobile-phone addiction in adolescence: The test of mobile phone dependence. Progress in Health Science, 2(1), 33-44.
  • Demirci, K., Orhan, H., Demirdas, A., Akpınar, A., & Sert, H. (2014). Validity and reliability of the Turkish Version of the Smartphone Addiction Scale in a younger population. Bulletin of Clinical Psychopharmacology, 24(3), 226-234.
  • Hong, F. Y., Chiu, S. I., & Huang, D. H. (2012). A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students. Computers in Human Behavior, 28(6), 2152-2159.
  • Kim H. (2013). Exercise rehabilitation for smartphone addiction. J Exerc Rehabil, 9(6), 500-5.
  • Kim, S., & Kim, R. (2002). A study of internet addiction: status, causes, and remedies. Journal of Korean Home Economics Association English Edition, 3(1).
  • Kwon, M., Kim, D-J., Cho, H., Yang, S. (2013). The Smartphone Addiction Scale: Development and Validation of a Short Version for Adolescents. PLoS ONE, 8(12): e83558. doi:10.1371/journal.pone.0083558
  • Kwon, M., Lee, J. Y., Won, W. Y., Park, J. W., Min, J. A., Hahn, C., & Kim, D. J. (2013). Development and validation of a smartphone addiction scale (SAS). PloS one, 8(2).
  • Lee, H., Ahn, H., Choi, S., & Choi, W. (2014). The SAMS: Smartphone addiction management system and verification. Journal of medical systems, 38(1), 1-10.
  • Lin, Y. H., Lin, Y. C., Lee, Y. H., Lin, P. H., Lin, S. H., Chang, L. R., Kuo, T. B. (2015). Time distortion associated with smartphone addiction: identifying smartphone addiction via a mobile application. Journal of Psychiatric Research, 65, 139-145.
  • Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological internet use among college students. Computers in Human Behavior, 16(1), 13–29.
  • Nolen-Hoeksema, S. (2012). Emotion regulation and psychopathology: The role of gender. Annual Review of Clinical Psychology, 8, 61–87.
  • Oulasvirta, A., Rattenbury, T., Ma, L., & Raita, E. (2012). Habits make smartphone use more pervasive. Personal and Ubiquitous Computing, 16(1), 105-114.
  • Park, N., & Lee, H. (2012). Social implications of smartphone use: Korean college students’ smartphone use and psychological well-being. Cyberpsychology, Behavior, and Social Networking, 15(9), 491-497.
  • Park, C., & Park, Y. R. (2014). The conceptual model on smartphone addiction among early childhood. International Journal of Social Science and Humanity, 2(4), 147-150.
  • Pi, S. Y. (2013). Self-diagnostic system for smartphone addiction using multiclass SVM. Journal of the Korean Data and Information Science Society, 24(1), 13-22.
  • Roberts, J. A. P., Yaya, L. H., & Manolis, C. (2014). The invisible addiction: Cell-phone activities and addiction among male and female college students. Journal of Behavioral Addictions, 3(4), 254-265.
  • Salehan, M., & Negahban, A. (2013). Social networking on smartphones: When mobile phones become addictive. Computers in Human Behavior, 29(6), 2632-2639.
  • Statista (2016a). Number of smartphone users worldwide from 2014 to 2019 (in millions). http://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/ 10.10.2016 tarihinde adresinden erişilmiştir.
  • Statista (2016b). Number of smartphone users in Turkey from 2013 to 2019 (in millions). http://www.statista.com/statistics/467181/forecast-of-smartphone-users-in-turkey/ 10.10.2016 tarihinde adresinden erişilmiştir.
  • Thomee, S., Harenstam, A., & Hagberg, M. (2011). Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults a prospective cohort study. BMC Public Health, 11(1), 66-76.
  • Van Deursen, A. J., Bolle, C. L., Hegner, S. M., & Kommers, P. A. (2015). Modeling habitual and addictive smartphone behavior: the role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender. Computers in Human Behavior, 45, 411-420.
  • Yıldırım, C., Sumuer, E., Adnan, M., & Yıldırım, S. (2015). A growing fear Prevalence of nomophobia among Turkish college students. Information Development, 1-10.

FACTORS ASSOCIATED WITH SMARTPHONE USE AND ADDICTION AMONG MIDDLE SCHOOL STUDENTS

Year 2018, Volume: 8 Issue: 1, 1 - 23, 22.01.2018
https://doi.org/10.17943/etku.288822

Abstract

This study aims to determine the smart phone use and
addiction levels of secondary school students from 5th and 6th grades and
reveal the demographic variables concerning their addiction levels. In this
study that was conducted with 156 students from 5th and 6th grades in the
spring term of the school year of 2015-2016; the data were collected via
“Personal Information Form” and “Smart Phone Addiction Scale (SPAS)”.
Relational screening model was used in the study. Almost half of students that
participated in the study use smart phones for less than an hour every day and
one third of them check their smart phones every 2-3 hours. Considering the
actions taken by students on their smart phones; it is observed that they
mainly “play games”. According to the scores obtained from the Smart Phone
Addiction Scale, more than half of students are involved in the group
“Addiction Tendency”. Regarding the Smart Phone Addiction Scale, a significant
difference was determined in the groups of “gender, duration of using internet,
duration of using smart phones a day, frequency of checking smart phones,
frequency of accessing/checking social media environments via smart phones”.
The total percentage of accurately classifying the discriminant function was
determined as 63,7%. As a result of the study, it was determined that the
variable of “frequency of accessing/checking social media environments via
smart phones” classified students displaying and not displaying addiction the
best. Basic result of this study is that there is a distinct difference between
the smart phone addiction levels of female and male students. In this context,
it is recommended to examine the reasons of this difference and compare the
results with relevant studies being conducted in other countries.

References

  • Augner, C., & Hacker, G. W. (2012). Associations between problematic mobile phone use and psychological parameters in young adults. International Journal of Public Health, 57(2), 437-441.
  • Billieux, J., & Van der Linden, M. (2012). Problematic use of the Internet and selfregulation: A review of the initial studies. The Open Addiction Journal, 5, 24–29.
  • Choi, K., Son, H., Park, M., Han, J., Kim, K., Lee, B., et al. (2009). Internet overuse and excessive daytime sleepiness in adolescents. Psychiatry and clinical neurosciences, 63(4), 455–462.
  • Choliz, M. (2012). Mobile-phone addiction in adolescence: The test of mobile phone dependence. Progress in Health Science, 2(1), 33-44.
  • Demirci, K., Orhan, H., Demirdas, A., Akpınar, A., & Sert, H. (2014). Validity and reliability of the Turkish Version of the Smartphone Addiction Scale in a younger population. Bulletin of Clinical Psychopharmacology, 24(3), 226-234.
  • Hong, F. Y., Chiu, S. I., & Huang, D. H. (2012). A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students. Computers in Human Behavior, 28(6), 2152-2159.
  • Kim H. (2013). Exercise rehabilitation for smartphone addiction. J Exerc Rehabil, 9(6), 500-5.
  • Kim, S., & Kim, R. (2002). A study of internet addiction: status, causes, and remedies. Journal of Korean Home Economics Association English Edition, 3(1).
  • Kwon, M., Kim, D-J., Cho, H., Yang, S. (2013). The Smartphone Addiction Scale: Development and Validation of a Short Version for Adolescents. PLoS ONE, 8(12): e83558. doi:10.1371/journal.pone.0083558
  • Kwon, M., Lee, J. Y., Won, W. Y., Park, J. W., Min, J. A., Hahn, C., & Kim, D. J. (2013). Development and validation of a smartphone addiction scale (SAS). PloS one, 8(2).
  • Lee, H., Ahn, H., Choi, S., & Choi, W. (2014). The SAMS: Smartphone addiction management system and verification. Journal of medical systems, 38(1), 1-10.
  • Lin, Y. H., Lin, Y. C., Lee, Y. H., Lin, P. H., Lin, S. H., Chang, L. R., Kuo, T. B. (2015). Time distortion associated with smartphone addiction: identifying smartphone addiction via a mobile application. Journal of Psychiatric Research, 65, 139-145.
  • Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological internet use among college students. Computers in Human Behavior, 16(1), 13–29.
  • Nolen-Hoeksema, S. (2012). Emotion regulation and psychopathology: The role of gender. Annual Review of Clinical Psychology, 8, 61–87.
  • Oulasvirta, A., Rattenbury, T., Ma, L., & Raita, E. (2012). Habits make smartphone use more pervasive. Personal and Ubiquitous Computing, 16(1), 105-114.
  • Park, N., & Lee, H. (2012). Social implications of smartphone use: Korean college students’ smartphone use and psychological well-being. Cyberpsychology, Behavior, and Social Networking, 15(9), 491-497.
  • Park, C., & Park, Y. R. (2014). The conceptual model on smartphone addiction among early childhood. International Journal of Social Science and Humanity, 2(4), 147-150.
  • Pi, S. Y. (2013). Self-diagnostic system for smartphone addiction using multiclass SVM. Journal of the Korean Data and Information Science Society, 24(1), 13-22.
  • Roberts, J. A. P., Yaya, L. H., & Manolis, C. (2014). The invisible addiction: Cell-phone activities and addiction among male and female college students. Journal of Behavioral Addictions, 3(4), 254-265.
  • Salehan, M., & Negahban, A. (2013). Social networking on smartphones: When mobile phones become addictive. Computers in Human Behavior, 29(6), 2632-2639.
  • Statista (2016a). Number of smartphone users worldwide from 2014 to 2019 (in millions). http://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/ 10.10.2016 tarihinde adresinden erişilmiştir.
  • Statista (2016b). Number of smartphone users in Turkey from 2013 to 2019 (in millions). http://www.statista.com/statistics/467181/forecast-of-smartphone-users-in-turkey/ 10.10.2016 tarihinde adresinden erişilmiştir.
  • Thomee, S., Harenstam, A., & Hagberg, M. (2011). Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults a prospective cohort study. BMC Public Health, 11(1), 66-76.
  • Van Deursen, A. J., Bolle, C. L., Hegner, S. M., & Kommers, P. A. (2015). Modeling habitual and addictive smartphone behavior: the role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender. Computers in Human Behavior, 45, 411-420.
  • Yıldırım, C., Sumuer, E., Adnan, M., & Yıldırım, S. (2015). A growing fear Prevalence of nomophobia among Turkish college students. Information Development, 1-10.
There are 25 citations in total.

Details

Journal Section Articles
Authors

Hatice Durak

Süleyman Sadi Seferoğlu

Publication Date January 22, 2018
Published in Issue Year 2018 Volume: 8 Issue: 1

Cite

APA Durak, H., & Seferoğlu, S. S. (2018). ORTAOKUL ÖĞRENCİLERİNİN AKILLI TELEFON KULLANIMLARI VE BAĞIMLILIK DÜZEYLERİYLE İLGİLİ UNSURLAR. Eğitim Teknolojisi Kuram Ve Uygulama, 8(1), 1-23. https://doi.org/10.17943/etku.288822

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