Associations Between Symptoms of Problematic Smartphone, Facebook, WhatsApp, and Instagram Use: An Item-level Exploratory Graph Analysis Perspective

Overview

Journal J Behav Addict

Publisher Akademiai Kiado

Specialties Psychiatry
Social Sciences

Date 2020 Sep 28

PMID 32986606

Citations 20

Authors

Dmitri Rozgonjuk

Cornelia Sindermann

Jon D Elhai

Alexander P Christensen

Christian Montag

Affiliations

Soon will be listed here.

Abstract

Background And Aims: Studies have demonstrated associations between both problematic smartphone and social networks use with everyday life adversities. However, examination of associations between problematic smartphone use (PSU) and problematic use of specific social networking platforms, especially on item-level data, has received relatively little attention. Therefore, the aim of the current study was to explore how items of problematic smartphone, Facebook, WhatsApp, and Instagram use are associated.

Methods: 949 German-speaking adults participated in a web survey study. The participants were queried about their socio-demographics as well as levels of problematic smartphone, Facebook, WhatsApp, and Instagram use. In addition to bivariate correlation analysis, exploratory graph analysis (EGA), a type of network analysis, was conducted.

Results: The results showed that while problematic Facebook and Instagram use seem to be distinct phenomena, problematic smartphone and WhatsApp use were heavily intertwined. Furthermore, the only cross-platform symptom observed was the extent of reported pain in wrists and neck due to digital technology use. The EGA network models showed very good stability in bootstrap analyses.

Discussion And Conclusions: In general, the results of this study suggest that while Instagram and Facebook use may potentially constitute distinct problematic behaviors, problematic smartphone/WhatsApp use scales may be measuring highly similar or even the same construct.

Citing Articles

Could physical activity alleviate smartphone addiction in university students? A systematic literature review.

Pirwani N, Szabo A Prev Med Rep. 2024; 42:102744.

PMID: 38707250 PMC: 11068924. DOI: 10.1016/j.pmedr.2024.102744.

Neuroimaging the effects of smartphone (over-)use on brain function and structure-a review on the current state of MRI-based findings and a roadmap for future research.

Montag C, Becker B Psychoradiology. 2024; 3:kkad001.

PMID: 38666109 PMC: 10917376. DOI: 10.1093/psyrad/kkad001.

Testing the validity of the smartphone pervasiveness scale for adolescents with self-reported objective smartphone use data.

Chakraborty S, Gui M, Gerosa T, Marciano L Digit Health. 2024; 10:20552076241234744.

PMID: 38559580 PMC: 10981259. DOI: 10.1177/20552076241234744.

Effects of a 14-day social media abstinence on mental health and well-being: results from an experimental study.

de Hesselle L, Montag C BMC Psychol. 2024; 12(1):141.

PMID: 38481298 PMC: 10936093. DOI: 10.1186/s40359-024-01611-1.

Depressive inclinations mediate the association between personality (neuroticism/conscientiousness) and TikTok Use Disorder tendencies.

Montag C, Markett S BMC Psychol. 2024; 12(1):81.

PMID: 38368362 PMC: 10873925. DOI: 10.1186/s40359-024-01541-y.

References

Kim H . Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis. Restor Dent Endod. 2013; 38(1):52-4. PMC: 3591587. DOI: 10.5395/rde.2013.38.1.52. View

Panova T, Carbonell X . Is smartphone addiction really an addiction?. J Behav Addict. 2018; 7(2):252-259. PMC: 6174603. DOI: 10.1556/2006.7.2018.49. View

Sha P, Sariyska R, Riedl R, Lachmann B, Montag C . Linking Internet Communication and Smartphone Use Disorder by taking a closer look at the Facebook and WhatsApp applications. Addict Behav Rep. 2019; 9:100148. PMC: 6543448. DOI: 10.1016/j.abrep.2018.100148. View

Golino H, Shi D, Christensen A, Garrido L, Nieto M, Sadana R . Investigating the performance of exploratory graph analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial. Psychol Methods. 2020; 25(3):292-320. PMC: 7244378. DOI: 10.1037/met0000255. View

Kardefelt-Winther D, Heeren A, Schimmenti A, van Rooij A, Maurage P, Carras M . How can we conceptualize behavioural addiction without pathologizing common behaviours?. Addiction. 2017; 112(10):1709-1715. PMC: 5557689. DOI: 10.1111/add.13763. View

Sindermann C, Duke E, Montag C . Personality associations with Facebook use and tendencies towards Facebook Use Disorder. Addict Behav Rep. 2020; 11:100264. PMC: 7244926. DOI: 10.1016/j.abrep.2020.100264. View

Hallquist M, Wright A, Molenaar P . Problems with Centrality Measures in Psychopathology Symptom Networks: Why Network Psychometrics Cannot Escape Psychometric Theory. Multivariate Behav Res. 2019; 56(2):199-223. PMC: 7012663. DOI: 10.1080/00273171.2019.1640103. View

Billieux J, Van Rooij A, Heeren A, Schimmenti A, Maurage P, Edman J . Behavioural Addiction Open Definition 2.0-using the Open Science Framework for collaborative and transparent theoretical development. Addiction. 2017; 112(10):1723-1724. DOI: 10.1111/add.13938. View

Duke E, Montag C . Smartphone addiction, daily interruptions and self-reported productivity. Addict Behav Rep. 2018; 6:90-95. PMC: 5800562. DOI: 10.1016/j.abrep.2017.07.002. View

10.

Elhai J, Levine J, Hall B . The relationship between anxiety symptom severity and problematic smartphone use: A review of the literature and conceptual frameworks. J Anxiety Disord. 2018; 62:45-52. DOI: 10.1016/j.janxdis.2018.11.005. View

11.

Baggio S, Starcevic V, Studer J, Simon O, Gainsbury S, Gmel G . Technology-mediated addictive behaviors constitute a spectrum of related yet distinct conditions: A network perspective. Psychol Addict Behav. 2018; 32(5):564-572. DOI: 10.1037/adb0000379. View

12.

Epskamp S, Fried E . A tutorial on regularized partial correlation networks. Psychol Methods. 2018; 23(4):617-634. DOI: 10.1037/met0000167. View

13.

Yang G, Cao J, Li Y, Cheng P, Liu B, Hao Z . Association Between Internet Addiction and the Risk of Musculoskeletal Pain in Chinese College Freshmen - A Cross-Sectional Study. Front Psychol. 2019; 10:1959. PMC: 6733990. DOI: 10.3389/fpsyg.2019.01959. View

14.

Xie Y, Szeto G, Dai J, Madeleine P . A comparison of muscle activity in using touchscreen smartphone among young people with and without chronic neck-shoulder pain. Ergonomics. 2015; 59(1):61-72. DOI: 10.1080/00140139.2015.1056237. View

15.

Kwon M, Kim D, Cho H, Yang S . The smartphone addiction scale: development and validation of a short version for adolescents. PLoS One. 2014; 8(12):e83558. PMC: 3877074. DOI: 10.1371/journal.pone.0083558. View

16.

Epskamp S, Waldorp L, Mottus R, Borsboom D . The Gaussian Graphical Model in Cross-Sectional and Time-Series Data. Multivariate Behav Res. 2018; 53(4):453-480. DOI: 10.1080/00273171.2018.1454823. View

17.

Peterka-Bonetta J, Sindermann C, Elhai J, Montag C . Personality Associations With Smartphone and Internet Use Disorder: A Comparison Study Including Links to Impulsivity and Social Anxiety. Front Public Health. 2019; 7:127. PMC: 6579830. DOI: 10.3389/fpubh.2019.00127. View

18.

Hoffner C, Lee S . Mobile Phone Use, Emotion Regulation, and Well-Being. Cyberpsychol Behav Soc Netw. 2015; 18(7):411-6. DOI: 10.1089/cyber.2014.0487. View

19.

Rozgonjuk D, Sindermann C, Elhai J, Montag C . Fear of Missing Out (FoMO) and social media's impact on daily-life and productivity at work: Do WhatsApp, Facebook, Instagram, and Snapchat Use Disorders mediate that association?. Addict Behav. 2020; 110:106487. DOI: 10.1016/j.addbeh.2020.106487. View

20.

Lee H, Kim J, Fava M, Mischoulon D, Park J, Shim E . Development and validation study of the Smartphone Overuse Screening Questionnaire. Psychiatry Res. 2017; 257:352-357. DOI: 10.1016/j.psychres.2017.07.074. View