Journals / International Journal of Psychology and Educational Studies / 2021 / Cilt: 8 - Sayı: 2

Parental Attitudes and Socio-demographic Factors as Predictors of Smartphone Addiction in University Students

Pages
158–169
Publication Date
2021-04-21
DOI
—
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AI Summary & Key Takeaways

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⚡ TL;DR(Too Long; Didn't Read)

The results showed that age, gender, parental education level, time spent on smartphone, number of siblings, and state of feeling social and parental attitudes predicted a significant amount of variance (11%) in smartphone addiction.

📌 3 Key Takeaways

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Objective & Hypothesis:The aim of the study is to examine predictive effect of parental attitudes and socio-demographic variables (age, gender, time spent on smartphone, number of siblings, students’ feeling social, and parental education level) in university students’ addiction to smartphones.
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Key Findings & Data:Participants included 670 university students whose age ranged between 18-30 years (M=21.6, SD=6.3).
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Conclusion & Impact:The results showed that age, gender, parental education level, time spent on smartphone, number of siblings, and state of feeling social and parental attitudes predicted a significant amount of variance (11%) in smartphone addiction.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:smartphone addiction · parental attitudes · socio-demographic factors

Abstract

The aim of the study is to examine predictive effect of parental attitudes and socio-demographic variables (age, gender, time spent on smartphone, number of siblings, students’ feeling social, and parental education level) in university students’ addiction to smartphones. Participants included 670 university students whose age ranged between 18-30 years (M=21.6, SD=6.3). Smartphone Addiction Scale (SAS) and Parental Attitude Scale (PAS) and Socio-Demographic Information Form were used to collect data. The results showed that age, gender, parental education level, time spent on smartphone, number of siblings, and state of feeling social and parental attitudes predicted a significant amount of variance (11%) in smartphone addiction. The students’ perception of feeling social and parental attitudes functioned as a moderator on their smartphone addiction. It was revealed that the perception to be social softened the relation between authoritarian parental attitude and smartphone addiction. Furthermore, students experienced less smartphone addiction when their perception of feeling social and democratic parental attitudes were taken together. A negative and significant relation was found between democratic and authoritarian parental attitudes and smartphone addiction. A positive and significant relation was established between protective parental attitude and smartphone addiction. The results have important implication for research and practice in the context of university students.

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Cite This Article

ÇİÇEK, İ., TANRIVERDİ, S., ŞANLI, M. E., BULUS, M. (2021). Parental Attitudes and Socio-demographic Factors as Predictors of Smartphone Addiction in University Students. International Journal of Psychology and Educational Studies, Cilt: 8 - Sayı: 2, 158–169. https://ajindex.com/articles/768155

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References (10)

  1. Alshehri, N. A., Yildirim, M., & Vostanis, P. (2020). Saudi adolescents’ reports of the relationship between parental factors, social support and mental health problems. Arab Journal of Psychiatry, 31(2), 130-143. doi-10.12816/0056864 Aslan, A. E., & Çiçek, İ. (2020). Ergenlerin ayrışma-bireyleşme düzeyleri ile akran ilişkilerinin bazı değişkenlere göre incelenmesi. Journal of Hasan Ali Yücel Faculty of Education/Hasan Ali Yücel Egitim Fakültesi Dergisi (HAYEF), 17(1), 83-102.
  2. Arslan, G., Yıldırım, M., & Aytaç, M. (2020). Subjective vitality and loneliness explain how coronavirus anxiety increases rumination among college students. Death Studies, 1-10.
  3. Arslan, G., Yıldırım, M., Karataş, Z., Kabasakal, Z., & Kılınç, M. (2020). Meaningful living to promote complete mental health among university students in the context of the COVID-19 pandemic. International Journal of Mental Health and Addiction, 1-13. Doi: https://doi.org/10.1007/s11469-020-00416-8
  4. Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01
  5. Bian, M., & Leung, L. (2015). Linking loneliness, shyness, smartphone addiction symptoms, and patterns of smartphone use to social capital. Social Science Computer Review, 33(1), 61-79.
  6. Bonilla-Zorita, G., Griffiths, M. D., & Kuss, D. J. (2020). Online dating and problematic use: a systematic review. International Journal of Mental Health and Addiction, 1-34.
  7. Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). New York, NY: Routledge. Choi, S. W., Kim, D. J., Choi, J. S., Ahn, H., Choi, E. J., Song, W. Y.,. & Youn, H. (2015). Comparison of risk and protective factors associated with smartphone addiction and internet addiction. Journal of Behavioral Addictions, 4(4), 308-314.
  8. Chen, B., Liu, F., Ding, S., Ying, X., Wang, L., & Wen, Y. (2017). Gender differences in factors associated with smartphone addiction: A cross-sectional study among medical college students. BMC psychiatry, 17(1), 1-9.
  9. Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1(1), 16-29.
  10. Conroy, R. (2015). Sample size A rough guide. Retreived from http://www. beaumontethics. ie/docs/application/samplesizecalculation. pdf. Çeri, V., & Çiçek, İ. (2021). Psychological