The Smartphone Addiction Scale: Psychometric Properties, Invariance, Network Perspective, and Latent Profile Analysis Among a Sample of Chinese University Students

Li, Li; Niu, Zhimin; Griffiths, Mark D.; Mei, Songli

doi:10.1007/s11469-022-00857-3

Cited by 7 publications

(5 citation statements)

References 85 publications

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“…Previous research shows that the three latent groups consist of different proportions of participants (14). For instance, in a study involving Chinese university students, the normal smartphone user group had a proportion of 48.5%, the high-risk smartphone user group had a proportion of 41.1%, and the SA group had a proportion of 10.4% (53). In Chinese adolescents, the current study was the rst to use LPA to identify patterns of SA in relation to multiple ecological factors.…”

Section: Discussionmentioning

confidence: 88%

“…Our present ndings suggest that sleep deprivation may be of primary importance for researchers and mental health practitioners in adolescents with SA symptoms who are potentially at risk. Previous literature has shown that NA is rarely used for SA (53). According to the NA, the fact that sleep deprivation is strength to the risky group and distress is strength to the non-addicted group clari es the indicators accompanying SA.…”

Section: Discussionmentioning

confidence: 99%

“…First, LPA has increasingly become preferred to reveal the heterogeneity of addiction (e.g., Li et al, 2022;Xiong et al, 2023;Yang et al, 2022). For example, a previous study showed that there were three subgroups of SA among college students (Mok et al, 2014).…”

Section: The Present Studymentioning

confidence: 99%

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Smartphone addiction, depression, distress, eustress, loneliness, and sleep deprivation in adolescents: a latent profile and network analysis approach

KABADAYI

2024

Preprint

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Background Previous research on adolescent smartphone addiction has tended to focus on general populations that are assumed to be homogeneous, overlooking latent profiles. Furthermore, previous research has not focused on potentially important differences in the latent profiles of adolescent smartphone addiction in networks. The present study aimed to reveal the latent profiles of smartphone addiction, depression, stress, eustress, loneliness, and sleep deprivation in adolescents, and general and latent profiles were examined in the network. Methods The study group consisted of 436 (222 boys and 214 girls) adolescents, aged between 13 and 18 years. The findings of the present study were provided using Pearson correlation, ANOVA, latent profile analysis and network analysis. The data were analyzed using SPSS, JASP, and Mplus. Results The results of the study showed solutions with three latent profiles. The non-addicted group constituted 20.87%, the addicted group covered 29.82% and the risky group included 49.31% of the study group. Although the general profile and the addicted latent group had similar characteristics, the differences in the risky and non-addicted groups contributed to the current literature by providing a further and remarkable perspective on smartphone addiction, depression, distress, eustress, loneliness, and sleep deprivation in adolescents. Conclusions The theoretical and practical implications of the present results will provide contributions to researchers and practitioners in understanding smartphone addiction.

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Section: Discussionmentioning

confidence: 88%

Section: Discussionmentioning

confidence: 99%

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Smartphone addiction, depression, distress, eustress, loneliness, and sleep deprivation in adolescents: a latent profile and network analysis approach

KABADAYI

2024

Preprint

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“…Studies have also pointed out that MPA is closely related to various problems, such as headache, visual impairment, lack of sleep and even depression [6][7][8]. Because they lack the mental power and self-control to resist, college students are highly dependent on their mobile phones,compared with other groups [9][10]. According to research ndings, the current rate of MPA among Chinese college students has reached 23% and is still growing [8].…”

Section: Introductionmentioning

confidence: 99%

The relationship between mobile phone addiction and sleep quality in college students: the role of rumination and fear of missing out

Zhang,

He,

Zheng

et al. 2024

Preprint

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Purpose The impact of mobile phone addiction (MPA) on college students' sleep quality (SQ) has received increasing attention in recent years.On this basis, the mediating roles of rumination and FOMO (fear of missing out) on MPA and SQ were examined in this study. Methods In a cross-sectional study, preliminary data were gathered via questionnaires from 1401 college students (19.35 ± 0.81) from 5 universities in Jiangxi Province, China. Mobile Phone Addiction Tendency Scale, Rumination Response Scale, Fear of Missing Out Scale and Sleep Quality Scale were employed in the research. The mediation model was tested using SPSS 24.0 and AMOS21.0 software, with FOMO and rumination acting as the mediating variables. Results Between MPA and SQ, rumination and FOMO each had their own unique mediation effect. Furthermore, rumination and FOMO function as a chain of mediators between college students' MPA and SQ. Conclusion This study provided confirmation and clarification that in college students, the association between MPA and SQ was mediated by rumination and FOMO.This study improves our understanding of MPA, SQ and how MPA may affect SQ in college students. It also shows that the impact of MPA and SQ of college students should be given more consideration by educators, parents, and college students themselves.

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“…Cross-culture and cross-time SAS-SV invariance have been investigated previously, and the measurement equivalence is verified [ 31 , 47 ]. Cross-gender equivalence has been established for the revised Chinese Smartphone Addiction Scale (SAS-RC) [ 48 ]. However, this scale has been adapted from the Smartphone Addiction Scale long version [ 24 ] and lacks several items of the SAS-SV.…”

Section: Introductionmentioning

confidence: 99%

Short version of the smartphone addiction scale: Measurement invariance across gender

Yue

Yue²,

Liu³

et al. 2023

PLoS ONE

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The Smartphone Addiction Scale Short Version (SAS-SV) has been widely used in research, but little is known about the measurement invariance across gender. The current study measured SAS-SV invariance between male and female college students in a sample of 1112 participants. Single- and multiple-group confirmatory factor analyses (CFAs) of smartphone addiction symptom ratings were conducted using R program with RStudio. SAS-SV was psychometrically robust in measuring the severity of smartphone addiction among college students, as well as the gender-based invariance. The differences in SAS-SV between male and female participants were likely to represent true gender differences, and meaningful comparisons could be made.

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The Smartphone Addiction Scale: Psychometric Properties, Invariance, Network Perspective, and Latent Profile Analysis Among a Sample of Chinese University Students

Cited by 7 publications

References 85 publications

Smartphone addiction, depression, distress, eustress, loneliness, and sleep deprivation in adolescents: a latent profile and network analysis approach

Smartphone addiction, depression, distress, eustress, loneliness, and sleep deprivation in adolescents: a latent profile and network analysis approach

The relationship between mobile phone addiction and sleep quality in college students: the role of rumination and fear of missing out

Short version of the smartphone addiction scale: Measurement invariance across gender

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