THE RELATIONSHIP BETWEEN INTERNET ADDICTION AND PERSONALITY TRAITS IN MOROCCAN NURSING STUDENTS

IF 1 Q4 PSYCHOLOGY
Jamal Ksiksou, Lhoussaine Maskour, Smail Alaoui
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引用次数: 0

Abstract

Internet addiction has been identified as a major mental health problem, particularly among young nursing students. The purpose of this study was to determine the relationship between the Big Five personality traits and Internet addiction in this population.This study adopts a descriptive, quantitative, and correlational approach among 388 nursing students enrolled in a Higher Institute of Nursing Professions and Health Techniques in Morocco. The Internet Addiction Test (IAT), the Big Five Inventory (BFI) were used. A student-test was used to compare the differences in Internet addiction between different categorical groups. Pearson correlation was used to determine correlations between Internet addiction and personality traits. Linear regression analysis was performed to explore the effects of independent variable groups on Internet addiction.The overall prevalence of Internet addiction was 68.3% (AI > 30). There were significant differences in Internet addiction by age group (p = 0.001), gender (p = 0.004), grade (p = 0.003), and reasons for using the Internet (p = 0.004). Neuroticism ( = .493, p < .05) and extraversion ( = .479, p < .05) were positive predictors of Internet addiction, whereas agreeableness ( = -.461 p < .05) and conscientiousness ( = -.395, p < .05) were negative predictors.Personality traits are critical contributors when designing individualized intervention strategies that contribute to the prevention and reduction of Internet addiction in nursing students.
摩洛哥护生网络成瘾与人格特质的关系
网络成瘾已被确定为一个主要的心理健康问题,尤其是在年轻的护理专业学生中。本研究的目的是确定这一人群中五大人格特征与网络成瘾之间的关系。本研究采用描述性、定量和相关性的方法,对摩洛哥护理专业与健康技术高等学院的388名护理专业学生进行了调查。采用网络成瘾测试(IAT)、五大调查量表(BFI)。一项学生测试用于比较不同类别组之间的网络成瘾差异。Pearson相关用于确定网络成瘾与人格特征之间的相关性。采用线性回归分析方法探讨自变量组对网络成瘾的影响。网络成瘾的总体患病率为68.3%(AI>30)。年龄组(p=0.001)、性别(p=0.004)、年级(p=0.003)和使用互联网的原因(p=0.004。在设计有助于预防和减少护生网络成瘾的个性化干预策略时,人格特征是关键因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.50
自引率
42.90%
发文量
8
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