Comparing Internet Addiction in Students with High and Low Socioeconomic Status Levels

Kayrı, Murat; Günüç, Selim

doi:10.15805/addicta.2016.3.0110

Cited by 21 publications

(12 citation statements)

References 3 publications

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“…In fact, smartphone addiction is changing exponentially every year. For example, the study by Kayri and G€ un€ uç (2016) offered a typology according to the level of Internet addiction and found 9% addicts, while our study shows almost 30% of addict smartphone users). Finally, (4) it helps policymakers and managers design strategies to address each of the three clusters to overcome smartphone addiction's potential adverse effects and derive recommendations for managers.…”

Section: Discussioncontrasting

confidence: 53%

What colour are you? Smartphone addiction traffic lights and user profiles

Gutiérrez

Jiménez

2021

EJMBE

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PurposeThe key concern nowadays is smartphone addiction and user profiles. Following the risk and protective factors framework, the authors aim to characterize smartphone users according to two levels: (1) individual: referred to the use (i.e. boredom proneness, compulsive app downloading smartphone addiction) and (2) microsystem: referred to family and peers (i.e. family harmony and phubbing). Besides, the authors will derive useful managerial implications and strategies.Design/methodology/approachFirst, an extensive literature revision and in-depth interviews with experts were employed to identify the addiction-related variables at the individual and microsystem level. Second, information was collected from a sample of 275 Spanish smartphone users, and a K-means clustering algorithm was employed to classify smartphone users.FindingsThe proposed traffic lights schema identifies three users’ profiles (red, yellow and green) regarding their smartphone addiction and considering individual and microsystem critical variables.Originality/valueThis study proposes a practical and pioneer traffic lights schema to classify smartphone users and facilitate each cluster's strategies development.

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Section: Discussioncontrasting

confidence: 53%

What colour are you? Smartphone addiction traffic lights and user profiles

Gutiérrez

Jiménez

2021

EJMBE

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“…The results of the present study are important since they are the first ones in the literature. In a study conducted on internet addiction of adolescents, the addictions of the adolescents with low socioeconomic level were lower . This result of the present study may be associated with the fact that adolescents with low income had more limited social life due to various economic concerns and thus they wanted to maintain their social relations through smartphones.…”

Section: Discussionmentioning

confidence: 52%

“…The results of the present study are important since they are the first ones in the literature. In a study conducted on internet addiction with adolescents, it was found that the children from the families with fewer children fulfilled their technological demands more and the siblings in families with more children spent more time together and experienced less technology addiction . All these reasons might have been associated with the smartphone addiction in high school students with fewer siblings.…”

Section: Discussionmentioning

confidence: 99%

Comparison of smartphone addiction and loneliness in high school and university students

Aktürk

Budak

Gültekin

et al. 2018

Perspect Psychiatr Care

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“…In a recent Turkish study (Kayri & Günüç, 2016) researchers discussed the possible impact of different socioeconomic levels on problematic use. Youth (N = 453) were divided into two groups according to their reported socioeconomic level.…”

Section: Youth Clusters By Problematic Usementioning

confidence: 99%

The digital divide: Risk and protective factors and the differences in problematic use of digital devices among Hungarian youth

Kiss

Fitzpatrick

Pikó

2020

Children and Youth Services Review

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A number of psychological factors have been found to be relevant in terms of problematic use of digital devices. Some of them may serve as risk factors, while others mean protection. The main goal of present study was to determine user profiles and to examine differences among them based on several psychological variables using cluster analysis. Data were collected from high school and university students via an online questionnaire from November 2017 to January 2018 (N = 249; females: 62.2%, Mean age = 22.5 years, SD = 3.5). Based on bivariate correlations, sensation seeking, flow and boredom proneness acted as risk factors for developing problematic technological use. However, self-esteem, self-regulation and resilience were significant protective factors against problematic technological use. In an effort to develop a set of profiles that would capture this student population and their usage relative to risk, we identified four distinct user profiles through the use of cluster analysis. The first cluster was labeled as strongly protected sensation-seekers who were more prone to problematic use (18.5%) with moderately high levels of protection, but with the highest scores on the boredom proneness and sensation seeking scales. The second cluster consisted of more balanced and non-vulnerable users (26.1%), who achieved average scores on both risk and protective factors scales. The third cluster was labeled protected, conscious users who were slightly prone to problematic use (39.8%) with lower levels of problematic use and risk factors, and with higher levels of protective factors. The fourth cluster was labeled as strongly problematic, unprotected users (15.7%), who achieved the highest scores of problematic use, and were the less protected having the lowest levels of protective factors scores. We conclude that cluster analysis was suitable for detecting differences in vulnerability to problematic Internet and smartphone use. Psychological factors, such as sensation seeking, flow and boredom, self-esteem, self-regulation and resilience serve as useful tools for providing information to better understanding the role of risk and protective factors in the prevention of youth's problematic use of digital devices. Problematic Internet and smartphone useStudies apply the terms 'addiction' and 'problematic use'

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Comparing Internet Addiction in Students with High and Low Socioeconomic Status Levels

Cited by 21 publications

References 3 publications

What colour are you? Smartphone addiction traffic lights and user profiles

What colour are you? Smartphone addiction traffic lights and user profiles

Comparison of smartphone addiction and loneliness in high school and university students

The digital divide: Risk and protective factors and the differences in problematic use of digital devices among Hungarian youth

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