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Journals / Türk Psikolojik Danışma ve Rehberlik Dergisi / 2020 / Cilt: 10 - Sayı: 59

Psychosocial Factors That Predict Internet Addiction

Önder BALTACI
Feride BACANLI
Pages
661–679
Publication Date
2020-12-28
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The article includes the discussion of the results based on the relevant literature and suggestions in regards to the theory and future research.

📌 3 Key Takeaways

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Objective & Hypothesis:This study aimed to determine the predictive power of university students' gender, sensation seeking, social support, loneliness levels and personality traits in predicting internet addiction by using the relational survey model.
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Key Findings & Data:The study group of this research was composed of a total of 873 university students (635 females and 238 males) attending the different departments of the Faculty of Education, the Faculty of Arts and Sciences, the School of Health and the School of Physical Therapy and Rehabilitation at a state university during the fall semester of the 2015-2016 academic year.
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Conclusion & Impact:The article includes the discussion of the results based on the relevant literature and suggestions in regards to the theory and future research.
🔬Design:Survey & Empirical Study
📍Scope:2015-2016 Verileri
⚙️Variables:Internet Addiction · Sensation Seeking · Personality Traits

Abstract

This study aimed to determine the predictive power of university students' gender, sensation seeking, social support, loneliness levels and personality traits in predicting internet addiction by using the relational survey model. The study group of this research was composed of a total of 873 university students (635 females and 238 males) attending the different departments of the Faculty of Education, the Faculty of Arts and Sciences, the School of Health and the School of Physical Therapy and Rehabilitation at a state university during the fall semester of the 2015-2016 academic year. The data were collected with the help of Internet Addiction Test, Adjective Based Personality Test, Arnett Inventory of Sensation Seeking, UCLA Loneliness Scale, Multidimensional Scale of Perceived Social Support and Personal Information Form. Pearson moments product correlation coefficient and hierarchical regression analysis were used in data analysis. Based on research results, neuroticism was found to be the most significant predictor of internet addiction followed by loneliness, gender, extraversion, openness to experience, sensation seeking, conscientiousness, agreeableness and social support variables followed this variable. The article includes the discussion of the results based on the relevant literature and suggestions in regards to the theory and future research.

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Cite This Article

BALTACI, Ö., BACANLI, F. (2020). Psychosocial Factors That Predict Internet Addiction. Türk Psikolojik Danışma ve Rehberlik Dergisi, Cilt: 10 - Sayı: 59, 661–679. https://ajindex.com/articles/86500

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