Is There Any Relation Between Smartphone Usage and Loneliness During the COVID-19 Pandemic?: A Study by Exploring Two Objective App Usage Datasets
DOI:
https://doi.org/10.4108/eetpht.9.3663Keywords:
Smartphone, Loneliness, Students, App categories, Social Media, Communication, Books apps, Education appsAbstract
BACKGROUND: Though smartphone is popular and loneliness is higher among the youth, in low-and-middle income countries (LMICs) such as Bangladesh, the relation of loneliness with actual app usage is unexplored amid pandemic. Also, the studies conducted in developed countries are limited by exploration of some app categories.
METHODS: We conducted two studies in Bangladesh: in 2020 (N1=100) and 2021 (N2=105). We collected participant’s ULS-8 score and 7 days’ actual app usage. We extracted app usage behavioral data from 1.69 million events and did semi-partial and partial correlation analyses.
RESULTS: Our analysis did not present any significant relation which may indicate a negative impact on loneliness. However, we found higher usage of Social Media, Communication, Education, Books, and Shopping apps and higher entropy of Browser apps had significant (q<.05) relation with lower loneliness.
CONCLUSION: Smartphone may not negatively impact loneliness. Instead, some app categories can play a role to mitigate loneliness.
Downloads
References
Killgore WDS, Cloonan SA, Taylor EC, Dailey NS. Loneliness: A signature mental health concern in the era of COVID-19. Psychiatry Res. 2020;290(113117):113117. http://dx.doi.org/10.1016/j.psychres.2020.113117 DOI: https://doi.org/10.1016/j.psychres.2020.113117
Fumagalli E, Dolmatzian MB, Shrum LJ. Centennials, FOMO, and loneliness: An investigation of the impact of social networking and messaging/VoIP apps usage during the initial stage of the Coronavirus pandemic. Front Psychol. 2021;12:620739. http://dx.doi.org/10.3389/fpsyg.2021.620739 DOI: https://doi.org/10.3389/fpsyg.2021.620739
Varrella S. Loneliness among adults worldwide by country 2021. Statista. [accessed 29 Jan 2022] Available from: https://www.statista.com/statistics/1222815/loneliness-among-adults-by-country/
Lee CM, Cadigan JM, Rhew IC. Increases in loneliness among young adults during the COVID-19 pandemic and association with increases in mental health problems. J Adolesc Health. 2020;67(5):714–7. http://dx.doi.org/10.1016/j.jadohealth.2020.08.009 DOI: https://doi.org/10.1016/j.jadohealth.2020.08.009
Serra G, Lo Scalzo L, Giuffrè M, Ferrara P, Corsello G. Smartphone use and addiction during the coronavirus disease 2019 (COVID-19) pandemic: cohort study on 184 Italian children and adolescents. Ital J Pediatr. 2021;47(1):150. http://dx.doi.org/10.1186/s13052-021-01102-8 DOI: https://doi.org/10.1186/s13052-021-01102-8
Hunt MG, Marx R, Lipson C, Young J. No more FOMO: Limiting social media decreases loneliness and depression. J Soc Clin Psychol. 2018;37(10):751–68. http://dx.doi.org/10.1521/jscp.2018.37.10.751 DOI: https://doi.org/10.1521/jscp.2018.37.10.751
Wetzel B, Pryss R, Baumeister H, Edler J-S, Gonçalves ASO, Cohrdes C. “how come you don’t call me?” smartphone communication app usage as an indicator of loneliness and social well-being across the adult lifespan during the COVID-19 pandemic. Int J Environ Res Public Health. 2021;18(12):6212. http://dx.doi.org/10.3390/ijerph18126212 DOI: https://doi.org/10.3390/ijerph18126212
Bonsaksen T, Ruffolo M, Leung J, Price D, Thygesen H, Schoultz M, et al. Loneliness and its association with social media use during the COVID-19 outbreak. Soc Media Soc. 2021;7(3):205630512110338. http://dx.doi.org/10.1177/20563051211033821 DOI: https://doi.org/10.1177/20563051211033821
Gao Y, Li A, Zhu T, Liu X, Liu X. How smartphone usage correlates with social anxiety and loneliness. PeerJ. 2016;4(e2197):e2197. http://dx.doi.org/10.7717/peerj.2197 DOI: https://doi.org/10.7717/peerj.2197
Li Z, Shi D, Wang F, Liu F. Loneliness Recognition Based on Mobile Phone Data. In: Proceedings of the 2016 International Symposium on Advances in Electrical, Electronics and Computer Engineering. Paris, France: Atlantis Press; 2016. DOI: https://doi.org/10.2991/isaeece-16.2016.34
Ceci L. Google Play most popular app categories 2021. Statista. [accessed 29 Jan 2022] Available from: https://www.statista.com/statistics/279286/google-play-android-app-categories/
Pulekar G, Agu E. Autonomously sensing loneliness and its interactions with personality traits using smartphones. In: 2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT). IEEE; 2016. http://dx.doi.org/10.1109/hic.2016.7797715 DOI: https://doi.org/10.1109/HIC.2016.7797715
Petersen J, Thielke S, Austin D, Kaye J. Phone behaviour and its relationship to loneliness in older adults. Aging Ment Health. 2016;20(10):1084–91. http://dx.doi.org/10.1080/13607863.2015.1060947 DOI: https://doi.org/10.1080/13607863.2015.1060947
Islam MR, Jannath S, Moona AA, Akter S, Hossain MJ, Islam SMA. Association between the use of social networking sites and mental health of young generation in Bangladesh: A cross-sectional study. J Community Psychol. 2021;49(7):2276–97. http://dx.doi.org/10.1002/jcop.22675 DOI: https://doi.org/10.1002/jcop.22675
LaMorte WW. Mann Whitney U test (wilcoxon rank sum test). Bumc.bu.edu. [accessed 2 Feb 2022] Available from: https://sphweb.bumc.bu.edu/otlt/mph-modules/bs/bs704_nonparametric/BS704_Nonparametric4.html
Mobile operating system market share Bangladesh. StatCounter Global Stats. [accessed 16 Feb 2022] Available from: https://gs.statcounter.com/os-market-share/mobile/bangladesh
Ahmed MS. Info bin. Google.com. [accessed 29 Jan 2022] Available from: https://play.google.com/store/apps/details?id=bd.me.sabbireubdesh.www.datacollector
Felisoni DD, Godoi AS. Cell phone usage and academic performance: An experiment. Comput Educ. 2018;117:175–87. http://dx.doi.org/10.1016/j.compedu.2017.10.006 DOI: https://doi.org/10.1016/j.compedu.2017.10.006
UsageStatsManager. Android Developers. [accessed 29 Jan 2022] Available from: https://developer.android.com/reference/android/app/usage/UsageStatsManager.html
Mindefy Labs. YourHour - phone addiction tracker & controller. Google.com. [accessed 29 Jan 2022] Available from: https://play.google.com/store/apps/details?id=com.mindefy.phoneaddiction.mobilepe
Hays RD, DiMatteo MR. A short-form measure of loneliness. J Pers Assess. 1987 Spring;51(1):69–81. http://dx.doi.org/10.1207/s15327752jpa5101_6 DOI: https://doi.org/10.1207/s15327752jpa5101_6
Das R, Hasan MR, Daria S, Islam MR. Impact of COVID-19 pandemic on mental health among general Bangladeshi population: a cross-sectional study. BMJ Open. 2021;11(4):e045727. http://dx.doi.org/10.1136/bmjopen-2020-045727 DOI: https://doi.org/10.1136/bmjopen-2020-045727
Doryab A, Villalba DK, Chikersal P, Dutcher JM, Tumminia M, Liu X, et al. Identifying behavioral phenotypes of loneliness and social isolation with passive sensing: Statistical analysis, data mining and machine learning of smartphone and Fitbit data. JMIR MHealth UHealth. 2019;7(7):e13209. http://dx.doi.org/10.2196/13209 DOI: https://doi.org/10.2196/13209
Böhmer M, Hecht B, Schöning J, Krüger A, Bauer G. Falling asleep with Angry Birds, Facebook and Kindle: A large scale study on mobile application usage. In: Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services - MobileHCI ’11. New York, New York, USA: ACM Press; 2011. http://dx.doi.org/10.1145/2037373.2037383 DOI: https://doi.org/10.1145/2037373.2037383
Zhao S, Ramos J, Tao J, Jiang Z, Li S, Wu Z, et al. Discovering different kinds of smartphone users through their application usage behaviors. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, NY, USA: ACM; 2016. DOI: https://doi.org/10.1145/2971648.2971696
BSS. BUET to take term-final exams online. The Daily Star. 2021. [accessed 16 Feb 2022] Available from: https://www.thedailystar.net/youth/education/news/buet-take-term-final-exams-online-2141496
Wikipedia contributors. Hamming distance. Wikipedia, The Free Encyclopedia. 2021. Available from: https://en.wikipedia.org/w/index.php?title=Hamming_distance&oldid=1054348646
Ahmed S, Ahmed N. Exploring unique app signature of the depressed and non-depressed through their fingerprints on apps. In: Proceedings of 15th EAI International Conference on Pervasive Computing Technologies for Healthcare. 2022. DOI: 10.1007/978-3-030-99194-4_15 DOI: https://doi.org/10.31234/osf.io/6mbua
Tu Z, Li R, Li Y, Wang G, Wu D, Hui P, et al. Your apps give you away: Distinguishing mobile users by their app usage fingerprints. Proc ACM Interact Mob Wearable Ubiquitous Technol. 2018;2(3):1–23. http://dx.doi.org/10.1145/3264948 DOI: https://doi.org/10.1145/3264948
Shannon CE. A mathematical theory of communication. ACM SIGMOBILE Mob Comput Commun Rev. 2001;5(1):3–55. http://dx.doi.org/10.1145/584091.584093 DOI: https://doi.org/10.1145/584091.584093
Kim S. Ppcor: An R package for a fast calculation to semi-partial correlation coefficients. Commun Stat Appl Methods. 2015;22(6):665–74. http://dx.doi.org/10.5351/CSAM.2015.22.6.665 DOI: https://doi.org/10.5351/CSAM.2015.22.6.665
Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat Methods. 2020;17(3):261–72. http://dx.doi.org/10.1038/s41592-019-0686-2 DOI: https://doi.org/10.1038/s41592-020-0772-5
Benjamini Y, Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc. 1995;57(1):289–300. http://dx.doi.org/10.1111/j.2517-6161.1995.tb02031.x DOI: https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Park S, Kim I, Lee SW, Yoo J, Jeong B, Cha M. Manifestation of depression and loneliness on social networks: A case study of young adults on Facebook. In: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing. New York, NY, USA: ACM; 2015. DOI: https://doi.org/10.1145/2675133.2675139
Hill R. WHAT SAMPLE SIZE is “ENOUGH” in INTERNET SURVEY RESEARCH. Pbworks.com. [accessed 29 Jan 2022] Available from: http://cadcommunity.pbworks.com/f/what%20sample%20size.pdf
Chou W-P, Wang P-W, Chen S-L, Chang Y-P, Wu C-F, Lu W-H, et al. Voluntary reduction of social interaction during the COVID-19 pandemic in Taiwan: Related factors and association with perceived social support. Int J Environ Res Public Health. 2020;17(21):8039. http://dx.doi.org/10.3390/ijerph17218039 DOI: https://doi.org/10.3390/ijerph17218039
Yeo SC, Tan J, Lo JC, Chee MWL, Gooley JJ. Associations of time spent on homework or studying with nocturnal sleep behavior and depression symptoms in adolescents from Singapore. Sleep Health. 2020;6(6):758–66. http://dx.doi.org/10.1016/j.sleh.2020.04.011 DOI: https://doi.org/10.1016/j.sleh.2020.04.011
Miyata H. Impacts of reading habits on mindfulness and psychological status: A further analysis. WASEDA RILAS JOURNAL. [accessed 29 Jan 2022] Available from: https://www.waseda.jp/flas/rilas/assets/uploads/2020/10/207-218_Hiromitsu-MIYATA.pdf
Rane-Szostak D, Herth KA. Pleasure reading, other activities, and loneliness in later life. Journal of Adolescent & Adult Literacy. 1995;39(2). Available from: https://www.jstor.org/stable/40034518
Schønning V, Hjetland GJ, Aarø LE, Skogen JC. Social media use and mental health and well-being among adolescents – A scoping review. Front Psychol. 2020;11. http://dx.doi.org/10.3389/fpsyg.2020.01949 DOI: https://doi.org/10.3389/fpsyg.2020.01949
Twenge JM, Haidt J, Blake AB, McAllister C, Lemon H, Le Roy A. Worldwide increases in adolescent loneliness. J Adolesc. 2021;93:257–69. http://dx.doi.org/10.1016/j.adolescence.2021.06.006 DOI: https://doi.org/10.1016/j.adolescence.2021.06.006
Diefenbach S, Borrmann K. The Smartphone as a Pacifier and its Consequences: Young adults’ smartphone usage in moments of solitude and correlations to self-reflection. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM; 2019. http://dx.doi.org/10.1145/3290605.3300536 DOI: https://doi.org/10.1145/3290605.3300536
Hiniker A, Schoenebeck SY, Kientz JA. Not at the dinner table: Parents’ and children’s perspectives on family technology rules. In: Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. New York, NY, USA: ACM; 2016. http://dx.doi.org/10.1145/2818048.2819940 DOI: https://doi.org/10.1145/2818048.2819940
Ahmed N, Urmi T, Tasmin M. Challenges and opportunities for young female learners in STEM from the perspective of Bangladesh. In: 2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE). IEEE; 2020. DOI: https://doi.org/10.1109/TALE48869.2020.9368378
Wang R, Chen F, Chen Z, Li T, Harari G, Tignor S, et al. StudentLife: Assessing mental health, academic performance and behavioral trends of college students using smartphones. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, NY, USA: ACM; 2014. http://dx.doi.org/10.1145/2632048.2632054 DOI: https://doi.org/10.1145/2632048.2632054
Ben-Zeev D, Scherer EA, Wang R, Xie H, Campbell AT. Next-generation psychiatric assessment: Using smartphone sensors to monitor behavior and mental health. Psychiatr Rehabil J. 2015;38(3):218–26. http://dx.doi.org/10.1037/prj0000130 DOI: https://doi.org/10.1037/prj0000130
Austin J, Dodge HH, Riley T, Jacobs PG, Thielke S, Kaye J. A smart-home system to unobtrusively and continuously assess loneliness in older adults. IEEE J Transl Eng Health Med. 2016;4:2800311. http://dx.doi.org/10.1109/JTEHM.2016.2579638 DOI: https://doi.org/10.1109/JTEHM.2016.2579638
Ahmed M. 86pc university students own smartphones in Bangladesh: Survey. Prothomalo. Prothom Alo English; 2020. [accessed 29 Jan 2022] Available from: https://en.prothomalo.com/youth/education/86pc-university-students-own-smartphones-in-bangladesh-survey
Ahmed MS, Rony RJ, Hasan T, Ahmed N. Smartphone usage behavior between depressed and non-depressed students: An exploratory study in the context of Bangladesh. In: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers. New York, NY, USA: ACM; 2020. DOI: https://doi.org/10.1145/3410530.3414441
Mezuk B, Choi M, DeSantis AS, Rapp SR, Diez Roux AV, Seeman T. Loneliness, depression, and inflammation: Evidence from the multi-ethnic study of atherosclerosis. PLoS One. 2016;11(7):e0158056. http://dx.doi.org/10.1371/journal.pone.0158056 DOI: https://doi.org/10.1371/journal.pone.0158056
Jackson SE, Hackett RA, Grabovac I, Smith L, Steptoe A. Perceived discrimination, health and wellbeing among middle-aged and older lesbian, gay and bisexual people: A prospective study. PLoS One. 2019;14(5):e0216497. http://dx.doi.org/10.1371/journal.pone.0216497 DOI: https://doi.org/10.1371/journal.pone.0216497
Zhang H, Yang J, Li Y, Ren G, Mu L, Cai Y, et al. The patterns and predictors of loneliness for the Chinese medical students since post-lockdown to new normal with COVID-19. Front Public Health. 2021;9:679178. Available from: http://dx.doi.org/10.3389/fpubh.2021.679178 DOI: https://doi.org/10.3389/fpubh.2021.679178
Sarsenbayeva Z, Marini G, van Berkel N, Luo C, Jiang W, Yang K, et al. Does Smartphone Use Drive our Emotions or vice versa? A Causal Analysis. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM; 2020. DOI: https://doi.org/10.1145/3313831.3376163
Shi Y, Koval P, Kostakos V, Goncalves J, Wadley G. “Instant Happiness”: Smartphones as tools for everyday emotion regulation. Int J Hum Comput Stud. 2023;170(102958):102958. Available from: http://dx.doi.org/10.1016/j.ijhcs.2022.102958 DOI: https://doi.org/10.1016/j.ijhcs.2022.102958
Morris ME, Kuehn KS, Brown J, Nurius PS, Zhang H, Sefidgar YS, et al. College from home during COVID-19: A mixed-methods study of heterogeneous experiences. PLoS One. 2021;16(6):e0251580. Available from: http://dx.doi.org/10.1371/journal.pone.0251580 DOI: https://doi.org/10.1371/journal.pone.0251580
Suresh R, Alam A, Karkossa Z. Using peer support to strengthen mental health during the COVID-19 pandemic: A review. Front Psychiatry. 2021;12:714181. Available from: http://dx.doi.org/10.3389/fpsyt.2021.714181 DOI: https://doi.org/10.3389/fpsyt.2021.714181
Ahmed MS, Hasan T, Rahman M, Ahmed N. A rule mining and Bayesian network analysis to explore the link between depression and digital behavioral markers of Games app usage. In: Proceedings of PervasiveHealth’22 [In Press]. 2022. DOI: 10.1007/978-3-031-34586-9_37 DOI: https://doi.org/10.31234/osf.io/d93zu
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Md. Sabbir Ahmed, Syeda Shabnam Khan, Nova Ahmed
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.