Exploring the connection between parental bonding and smartphone addiction in Chinese medical students

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Abstract

Background

Smartphone addiction bodes adverse consequences, affecting different populations, including medical students. Parental bonding in childhood had been associated with addiction and recovery in later life. Therefore, this study aimed to examine the associations between parental bonding and smartphone addiction among Chinese medical students.

Method

Binary logistic regressions were used to investigate the associations between parental bonding with mothers and fathers, respectively, and smartphone addiction. Interaction terms of care and protection were included in the models.

Results

A total of 517 medical students were included in the study. The prevalence of smartphone addiction was 48.16% ( n = 249). The estimated effects of maternal and paternal parenting on smartphone addiction differed. Maternal protection was positively associated with smartphone addiction (OR, 1.046;95% CI, 1.005-1.087), and maternal care enhanced the estimated effect of protection on smartphone addiction. Paternal care was negatively associated with smartphone addiction (OR, 0.954;95% CI, 0.919-0.989).

Conclusions

Chinese medical students with overprotective mothers or with indifferent fathers tended to exhibit traits of smartphone addiction. Further studies on factors influencing the associations between parental bonding and smartphone addiction may pave the way for potential family-oriented interventions for smartphone addiction.

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The Smartphone Addiction Scale: Development and Validation of a Short Version for Adolescents

Min Jo Kwon, Dai-Jin Kim, Joo Hyun Cho … (2013)

Objective This study was designed to investigate the revised and short version of the smartphone addiction scale and the proof of its validity in adolescents. In addition, it suggested cutting off the values by gender in order to determine smartphone addiction and elaborate the characteristics of smartphone usage in adolescents. Method A set of questionnaires were provided to a total of 540 selected participants from April to May of 2013. The participants consisted of 343 boys and 197 girls, and their average age was 14.5 years old. The content validity was performed on a selection of shortened items, while an internal-consistency test was conducted for the verification of its reliability. The concurrent validity was confirmed using SAS, SAPS and KS-scale. Receiver operating characteristics analysis was conducted to suggest cut-off. Results The 10 final questions were selected using content validity. The internal consistency and concurrent validity of SAS were verified with a Cronbach's alpha of 0.911. The SAS-SV was significantly correlated with the SAS, SAPS and KS-scale. The SAS-SV scores of gender (p<.001) and self-evaluation of smartphone addiction (p<.001) showed significant difference. The ROC analysis results showed an area under a curve (AUC) value of 0.963(0.888–1.000), a cut-off value of 31, sensitivity value of 0.867 and specificity value of 0.893 in boys while an AUC value of 0.947(0.887–1.000), a cut-off value of 33, sensitivity value of 0.875, and a specificity value of 0.886 in girls. Conclusions The SAS-SV showed good reliability and validity for the assessment of smartphone addiction. The smartphone addiction scale short version, which was developed and validated in this study, could be used efficiently for the evaluation of smartphone addiction in community and research areas.

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A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use

Daniel Kardefelt-Winther (2014)

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Model selection and psychological theory: a discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC).

Scott Vrieze (2012)

This article reviews the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) in model selection and the appraisal of psychological theory. The focus is on latent variable models, given their growing use in theory testing and construction. Theoretical statistical results in regression are discussed, and more important issues are illustrated with novel simulations involving latent variable models including factor analysis, latent profile analysis, and factor mixture models. Asymptotically, the BIC is consistent, in that it will select the true model if, among other assumptions, the true model is among the candidate models considered. The AIC is not consistent under these circumstances. When the true model is not in the candidate model set the AIC is efficient, in that it will asymptotically choose whichever model minimizes the mean squared error of prediction/estimation. The BIC is not efficient under these circumstances. Unlike the BIC, the AIC also has a minimax property, in that it can minimize the maximum possible risk in finite sample sizes. In sum, the AIC and BIC have quite different properties that require different assumptions, and applied researchers and methodologists alike will benefit from improved understanding of the asymptotic and finite-sample behavior of these criteria. The ultimate decision to use the AIC or BIC depends on many factors, including the loss function employed, the study's methodological design, the substantive research question, and the notion of a true model and its applicability to the study at hand. (c) 2012 APA, all rights reserved

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Author and article information

Contributors

Chunyu Xin: cyxin@cmu.edu.cn

Ning Ding: nding@cmu.edu.cn

Nan Jiang: nanjiang@cmu.edu.cn

Honghe Li: hhli@cmu.edu.cn

Deliang Wen: dlwen@cmu.edu.cn

Journal

Journal ID (nlm-ta): BMC Psychiatry

Journal ID (iso-abbrev): BMC Psychiatry

Title: BMC Psychiatry

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-244X

Publication date (Electronic): 16 November 2022

Publication date PMC-release: 16 November 2022

Publication date Collection: 2022

Volume: 22

Electronic Location Identifier: 712

Affiliations

GRID grid.412449.e, ISNI 0000 0000 9678 1884, Institute for International Health Professions Education and Research, , China Medical University, ; No.77 Puhe Road, Shenyang, Liaoning Province 110122 China

Article

Publisher ID: 4355

DOI: 10.1186/s12888-022-04355-7

PMC ID: 9670581

PubMed ID: 36384567

SO-VID: 70a73157-559e-4371-9730-bea7426657bb

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 7 June 2022

Date accepted : 31 October 2022

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ScienceOpen disciplines: Clinical Psychology & Psychiatry

Keywords: smartphone addiction,parental bonding,maternal parenting,paternal parenting,medical students,chinese

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ScienceOpen disciplines: Clinical Psychology & Psychiatry

Keywords: smartphone addiction, parental bonding, maternal parenting, paternal parenting, medical students, chinese

Exploring the connection between parental bonding and smartphone addiction in Chinese medical students

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Chinese Journal of School Health

Most cited references 93

The Smartphone Addiction Scale: Development and Validation of a Short Version for Adolescents

A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use

Model selection and psychological theory: a discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC).

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