Smartphone addiction, depression, distress, eustress, loneliness, and sleep deprivation in adolescents: a latent profile and network analysis approach.
Humans
Adolescent
Male
Loneliness
/ psychology
Female
Depression
/ psychology
Sleep Deprivation
/ psychology
Internet Addiction Disorder
/ psychology
Smartphone
/ statistics & numerical data
Stress, Psychological
/ psychology
Adolescent Behavior
/ psychology
Psychological Distress
Behavior, Addictive
/ psychology
Depression
Loneliness
Sleep deprivation
Smartphone addiction
Stress
Journal
BMC psychology
ISSN: 2050-7283
Titre abrégé: BMC Psychol
Pays: England
ID NLM: 101627676
Informations de publication
Date de publication:
31 Oct 2024
31 Oct 2024
Historique:
received:
10
07
2024
accepted:
24
10
2024
medline:
31
10
2024
pubmed:
31
10
2024
entrez:
31
10
2024
Statut:
epublish
Résumé
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. 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. 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. The theoretical and practical implications of the present results will provide contributions to researchers and practitioners in understanding smartphone addiction.
Sections du résumé
BACKGROUND
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
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
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
CONCLUSIONS
The theoretical and practical implications of the present results will provide contributions to researchers and practitioners in understanding smartphone addiction.
Identifiants
pubmed: 39478568
doi: 10.1186/s40359-024-02117-6
pii: 10.1186/s40359-024-02117-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
608Informations de copyright
© 2024. The Author(s).
Références
Olson JA, Sandra DA, Colucci ÉS, Bikaii A, Chmoulevitch A, Nahas D, Veissière J, S. P. <ArticleTitle Language=“En”>Smartphone addiction is increasing across the world: a meta-analysis of 24 countries. Comput Hum Behav. 2022;129:107138. https://doi.org/10.1016/j.chb.2021.107138 .
doi: 10.1016/j.chb.2021.107138
Kwon M, Kim DJ, Cho H, Yang S. The Smartphone Addiction Scale: Development and validation of a short version for adolescents. PLoS ONE. 2013;8(12):e83558. https://doi.org/10.1371/journal.pone.0083558 .
doi: 10.1371/journal.pone.0083558
pubmed: 24391787
pmcid: 3877074
Kim SG, Park J, Kim HT, Pan Z, Lee Y, McIntyre RS. The relationship between smartphone addiction and symptoms of depression, anxiety, and attention-deficit/hyperactivity in South Korean adolescents. Ann Gen Psychiatry. 2019;18(1):1–8. https://doi.org/10.1186/s12991-019-0224-8 .
doi: 10.1186/s12991-019-0224-8
pubmed: 30899316
pmcid: 6408841
Ding Y, Wan X, Lu G, Huang H, Liang Y, Yu J, Chen C. The associations between smartphone addiction and self-esteem, self-control, and social support among Chinese adolescents: A meta-analysis. Front Psychol. 2022;13:1029323. https://doi.org/10.3389/fpsyg.2022.1029323 .
doi: 10.3389/fpsyg.2022.1029323
pubmed: 36420390
pmcid: 9677120
Malinauskas R, Malinauskiene V. A meta-analysis of psychological interventions for Internet/smartphone addiction among adolescents. J Behav Addictions. 2019;8(4):613–24. https://doi.org/10.1556/2006.8.2019.72 .
doi: 10.1556/2006.8.2019.72
Cha SS, Seo BK. Smartphone use and smartphone addiction among middle school students in Korea: Prevalence, social network service, and game use. Health Psychol Open. 2018;5(1):2055102918755046. https://doi.org/10.1177/2055102918755046 .
doi: 10.1177/2055102918755046
pubmed: 29435355
pmcid: 5802650
Lee C, Lee SJ. Prevalence and determinants of smartphone addiction tendency among Korean adolescents. Child Youth Serv Rev. 2017;77:10–7. https://doi.org/10.1016/j.childyouth.2017.04.002 .
doi: 10.1016/j.childyouth.2017.04.002
Martinotti G, Villella C, Di Thiene D, Di Nicola M, Bria P, Conte G, La Torre G. Problematic mobile phone use during adolescence: A cross-sectional study. J Public Health. 2011;19:545–51. https://doi.org/10.1007/s10389-011 .
doi: 10.1007/s10389-011
Semerci A. Nomophobia as the predictor of secondary school students’ smartphone addiction. Bartın Univ J Fac Educ. 2019;8(3):947–65. https://doi.org/10.14686/buefad.592443 .
doi: 10.14686/buefad.592443
Buctot DB, Kim N, Kim JJ. Factors associated with smartphone addiction prevalence and its predictive capacity for health-related quality of life among Filipino adolescents. Child Youth Serv Rev. 2020;110:104758. https://doi.org/10.1016/j.childyouth.2020.104758 .
doi: 10.1016/j.childyouth.2020.104758
Popescu AM, Balica RȘ, Lazăr E, Bușu VO, Vașcu JE. Smartphone addiction risk, technology-related behaviors and attitudes, and psychological well-being during the COVID-19 pandemic. Front Psychol. 2022;13:997253. https://doi.org/10.3389/fpsyg.2022.997253 .
doi: 10.3389/fpsyg.2022.997253
pubmed: 36051208
pmcid: 9424853
Lei LYC, Ismail MAA, Mohammad JAM, Yusoff MSB. The relationship of smartphone addiction with psychological distress and neuroticism among university medical students. BMC Psychol. 2020;8:97. https://doi.org/10.1186/s40359-0 .
doi: 10.1186/s40359-0
pubmed: 32917268
pmcid: 7488412
Van Velthoven MH, Powell J, Powell G. Problematic smartphone use: Digital approaches to an emerging public health problem. Digit Health. 2018;4:2055207618759167. https://doi.org/10.1177/2055207618759167 .
doi: 10.1177/2055207618759167
pubmed: 31463071
pmcid: 6034350
Lim SA. Relationship between Korean adolescents’ dependence on smartphones, peer relationships, and life satisfaction. Child Youth Care Forum. 2023;52:603–18. https://doi.org/10.1007/s10566-022-09703-y .
doi: 10.1007/s10566-022-09703-y
pubmed: 35814497
Kim C, Kwak K, Kim Y. The relationship between stress and smartphone addiction among adolescents: The mediating effect of grit. Curr Psychol. 2023;42(10):8451–9. https://doi.org/10.1007/s12144-022-03367-6 .
doi: 10.1007/s12144-022-03367-6
Enez-Darcin A, Kose S, Noyan CO, Nurmedov S, Yılmaz O, Dilbaz N. Smartphone addiction and its relationship with social anxiety and loneliness. Behav Inform Technol. 2016;35(7):520–5. https://doi.org/10.1080/0144929X.2016 .
doi: 10.1080/0144929X.2016
Cırcır O, Bayar Y. Uykusuzluk, akıllı telefon bağımlılığı, bilinçli farkındalık ve akran etkisine direnme arasındaki ilişkiler [The relationship between insomnia, smartphone addiction, resistance to peer influence and mindfulness]. Adıyaman Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2023;44563–92. https://doi.org/10.14520/adyusbd.1289515 .
Loleska S, Pop-Jordanova N. Is smartphone addiction in the younger population a public health problem? Prilozi. 2021;42(3):29–36. https://doi.org/10.2478/prilozi-2021-0032 .
doi: 10.2478/prilozi-2021-0032
pubmed: 35032372
Xiong S, Zhang A, Zhang B, Xu Y. Patterns of smartphone addiction in adolescents and their association with multiple ecological factors: A latent profile analysis. Child Youth Serv Rev. 2023;155:107223. https://doi.org/10.1016/j.childyouth.2023.107223 .
doi: 10.1016/j.childyouth.2023.107223
Yang H, Tng GY, Khoo SS, Yang S. Multidimensional profiles of addictive smartphone use: A latent profile analysis. Curr Psychol. 2022;41(12):8410–23. https://doi.org/10.1007/s12144-022-02881-x .
doi: 10.1007/s12144-022-02881-x
Spurk D, Hirschi A, Wang M, Valero D, Kauffeld S. Latent profile analysis: A review and how to guide of its application within vocational behavior research. J Vocat Behav. 2020;120:103445. https://doi.org/10.1016/j.jvb.2020.103445 .
doi: 10.1016/j.jvb.2020.103445
Geng Y, Gu J, Wang J, Zhang R. Smartphone addiction and depression, anxiety: The role of bedtime procrastination and self-control. J Affect Disord. 2021;293:415–21. https://doi.org/10.1016/j.jad.2021.06.062 .
doi: 10.1016/j.jad.2021.06.062
pubmed: 34246950
Matar-Boumosleh J, Jaalouk D. Depression, anxiety, and smartphone addiction in university students-A cross sectional study. PLoS ONE. 2017;12(8):e0182239. https://doi.org/10.1371/journal.pone.0182239 .
doi: 10.1371/journal.pone.0182239
pubmed: 28777828
Park Y, Lee S. Gender differences in smartphone addiction and depression among Korean adolescents: Focusing on the internal mechanisms of attention deficit and self-control. Comput Hum Behav. 2022;136:107400. https://doi.org/10.1016/j.chb.2022.107400 .
doi: 10.1016/j.chb.2022.107400
Demirci K, Akgönül M, Akpinar A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J Behav Addictions. 2015;4(2):85–92. https://doi.org/10.1556/2006.4.2015.010 .
doi: 10.1556/2006.4.2015.010
Lee EJ, Kim HO. Effects of depression and social interaction on smartphone addiction among female adolescents. J Child Adolesc Psychiatric Nurs. 2022;35(1):68–75. https://doi.org/10.1111/jcap.12349 .
doi: 10.1111/jcap.12349
Dana A, Nodeh H, Salehian MH, Saei M, S., Sarvari S. Smartphone usage status, sleep pattern, health-related quality of life, and physical activity among adolescents from before to during the COVID-19 confinement: A cross-sectional study. Int J School Health. 2022;9(1):1–9. https://doi.org/10.30476/intjsh.2021.92822.1178 .
doi: 10.30476/intjsh.2021.92822.1178
Chun J, Lee HK, Jeon H, Kim J, Lee S. Impact of COVID-19 on adolescents’ smartphone addiction in South Korea. Social Work Public Health. 2023;38(4):268–80. https://doi.org/10.1080/19371918.2022.2134252 .
doi: 10.1080/19371918.2022.2134252
Yang X, Hu H, Zhao C, Xu H, Tu X, Zhang G. A longitudinal study of changes in smart phone addiction and depressive symptoms and potential risk factors among Chinese college students. BMC Psychiatry. 2021;21(1):252. https://doi.org/10.1186/s12888-021-03265-4 .
doi: 10.1186/s12888-021-03265-4
pubmed: 33990181
pmcid: 8120756
Yang X, Liu RD, Ding Y, Hong W, Ding Z. Interpersonal relationships moderate the relation between academic stress and mobile phone addiction via depression among Chinese adolescents: A three-wave longitudinal study. Curr Psychol. 2023;42(22):19076–86. https://doi.org/10.1007/s12144-022-02951-0 .
doi: 10.1007/s12144-022-02951-0
Shi X, Wang A, Zhu Y. Longitudinal associations among smartphone addiction, loneliness, and depressive symptoms in college students: Disentangling between–and within–person associations. Addict Behav. 2023;142:107676. https://doi.org/10.1016/j.addbeh.2023.10767 .
doi: 10.1016/j.addbeh.2023.10767
pubmed: 36878182
Takahashi M, Adachi M, Hirota T, Nishimura T, Shinkawa H, Mori H, Nakamura K. Longitudinal association between addictive internet use and depression in early adolescents over a 2-year period: A study using a random intercept cross-lagged model. Comput Hum Behav. 2022;132:107251. https://doi.org/10.1016/j.chb.2022.107251 .
doi: 10.1016/j.chb.2022.107251
Alhassan AA, Alqadhib EM, Taha NW, Alahmari RA, Salam M, Almutairi AF. The relationship between addiction to smartphone usage and depression among adults: A cross sectional study. BMC Psychiatry. 2018;18:148. https://doi.org/10.1186/s12888-018-1745-4 .
doi: 10.1186/s12888-018-1745-4
pubmed: 29801442
pmcid: 5970452
Selye H. Stress and distress. Compr Ther. 1975;1(8):9–13.
pubmed: 1222562
Branson V, Dry MJ, Palmer E, Turnbull D. The Adolescent Distress-Eustress Scale: Development and validation. SAGE Open. 2019a;9(3):1–14. https://doi.org/10.1177/2158244019865802 .
doi: 10.1177/2158244019865802
Akgün N, Sevim E, Ekşi F, Ekşi H. Adaptation of Adolescent Distress-Eustress Scale into Turkish. Turkish J Child Adolesc Mental Health. 2021;28(2):102–9. https://doi.org/10.4274/tjcamh.galenos.2020.82905 .
doi: 10.4274/tjcamh.galenos.2020.82905
Stromájer GP, Csima M, Iváncsik R, Varga B, Takács K, Stromájer-Rácz T. Stress and anxiety among high school adolescents: Correlations between physiological and psychological indicators in a longitudinal follow-up study. Children. 2023;10(9):1548. https://doi.org/10.3390/children10091548 .
doi: 10.3390/children10091548
pubmed: 37761509
pmcid: 10529881
Branson V. (2019). The Adolescent Distress-Eustress Scale: Designing, evaluating, and utilising a holistic measure of adolescent stress [Doctoral dissertation, The University of Adelaide]. The University of Adelaide Research Repository.
Yazici-Kabadayi S. Relationships between mental toughness, eustress–distress, and mindfulness in adolescents: A network analysis and mediator model testing. Stress Health. 2024. https://doi.org/10.1002/smi.3480 . Advance online publication.
doi: 10.1002/smi.3480
pubmed: 39264855
Branson V, Palmer E, Dry MJ, Turnbull D. A holistic understanding of the effect of stress on adolescent well-being: A conditional process analysis. Stress Health. 2019b;35(5):626–41. https://doi.org/10.1002/smi.2896 .
doi: 10.1002/smi.2896
pubmed: 31469222
Parker KN, Ragsdale JM. Effects of distress and eustress on changes in fatigue from waking to working. Appl Psychology: Health Well-Being. 2015;7(3):293–315. https://doi.org/10.1111/aphw.12049 .
doi: 10.1111/aphw.12049
pubmed: 26227991
Wu Y, Zhou L, Zhang X, Yang X, Niedermann G, Xue J. Psychological distress and eustress in cancer and cancer treatment: Advances and perspectives. Sci Adv. 2022;8(47):eabq7982. https://doi.org/10.1126/sciadv.abq7982 .
doi: 10.1126/sciadv.abq7982
pubmed: 36417542
pmcid: 9683699
Hampel P, Petermann F. Perceived stress, coping, and adjustment in adolescents. J Adolesc Health. 2006;38(4):409–15. https://doi.org/10.1016/j.jadohealth.2005.02.014 .
doi: 10.1016/j.jadohealth.2005.02.014
pubmed: 16549302
Laustsen LM, Christiansen J, Maindal HT, Plana-Ripoll O, Lasgaard M. The longitudinal relation between loneliness and perceived stress: A structural equation modelling analysis of 10,159 individuals. Scand J Public Health. 2024;52(4):410–8. https://doi.org/10.1177/14034948231151716 .
doi: 10.1177/14034948231151716
pubmed: 36794680
Lazarus RS, Folkman S. Stress, appraisal, and coping. Springer Publishing Company; 1984.
Cepuch G, Kruszecka-Krówka A, Liber P, Micek A. Association between suicidal behaviors in adolescence and negative emotions, the level of stress, stress coping strategies and the quality of sleep. Healthcare. 2023;11(3):306. https://doi.org/10.3390/healthcare11030306 .
doi: 10.3390/healthcare11030306
pubmed: 36766881
pmcid: 9914235
Abolghasemi A, Varaniyab ST. Resilience and perceived stress: Predictors of life satisfaction in the students of success and failure. Procedia-Social Behav Sci. 2010;5:748–52. https://doi.org/10.1016/j.sbspro.2010.07.178 .
doi: 10.1016/j.sbspro.2010.07.178
Branson V, Palmer E, Dry MJ, Turnbull D. A holistic understanding of the effect of stress on adolescent well-being: A conditional process analysis. Stress Health. 2019;35(5):626–41. https://doi.org/10.1002/smi.2896 .
doi: 10.1002/smi.2896
pubmed: 31469222
Thorsén F, Antonson C, Palmér K, Berg R, Sundquist J, Sundquist K. Associations between perceived stress and health outcomes in adolescents. Child Adolesc Psychiatry Mental Health. 2022;16(1):75. https://doi.org/10.1186/s13034-w .
doi: 10.1186/s13034-w
Varghese R, Norman TS, Thavaraj S. Perceived stress and self efficacy among college students: A global review. Int J Hum Resource Manage Res. 2015;5(3):15–24. https://doi.org/10.2139/ssrn.2703908 .
doi: 10.2139/ssrn.2703908
Samaha M, Hawi NS. Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Comput Hum Behav. 2016;57:321–5. https://doi.org/10.1016/j.chb.2015.12.045 .
doi: 10.1016/j.chb.2015.12.045
Wang W, Mehmood A, Li P, Yang Z, Niu J, Chu H, Yang X. Perceived stress and smartphone addiction in medical college students: The mediating role of negative emotions and the moderating role of psychological capital. Front Psychol. 2021;12:660234. https://doi.org/10.3389/fpsyg.2021.660234 .
doi: 10.3389/fpsyg.2021.660234
pubmed: 34366978
pmcid: 8336678
Vujić A, Szabo A. Hedonic use, stress, and life satisfaction as predictors of smartphone addiction. Addict Behav Rep. 2022;15:100411. https://doi.org/10.1016/j.abrep.2022.100411 .
doi: 10.1016/j.abrep.2022.100411
pubmed: 35746955
pmcid: 9210358
Folkman S, Lazarus RS, Dunkel-Schetter C, DeLongis A, Gruen RJ. Dynamics of a stressful encounter: Cognitive appraisal, coping, and encounter outcomes. J Personal Soc Psychol. 1986;50(5):992–1003. https://doi.org/10.1037/0022-3514.50.5.992 .
doi: 10.1037/0022-3514.50.5.992
Asher SR, Paquette JA. Loneliness and peer relations in childhood. Curr Dir Psychol Sci. 2003;12(3):75–8. https://doi.org/10.1111/1467-8721.01233 .
doi: 10.1111/1467-8721.01233
Bian M, Leung L. Linking loneliness, shyness, smartphone addiction symptoms, and patterns of smartphone use to social capital. Social Sci Comput Rev. 2015;33(1):61–79. https://doi.org/10.1177/0894439314528779 .
doi: 10.1177/0894439314528779
Sönmez M, Gürlek-Kısacık Ö, Eraydın C. Correlation between smartphone addiction and loneliness levels in nursing students. Perspect Psychiatr Care. 2021;57(1):82–7. https://doi.org/10.1111/ppc.12527 .
doi: 10.1111/ppc.12527
pubmed: 32424870
Karaoglan-Yilmaz FG, Avci U, Yilmaz R. The role of loneliness and aggression on smartphone addiction among university students. Curr Psychol. 2023;42(21):17909–17. https://doi.org/10.1007/s12144-022-03018-w .
doi: 10.1007/s12144-022-03018-w
Mahapatra S. Smartphone addiction and associated consequences: Role of loneliness and self-regulation. Behav Inform Technol. 2019;38(8):833–44. https://doi.org/10.1080/0144929X.2018.1560499 .
doi: 10.1080/0144929X.2018.1560499
Sarman A, Çiftci N. Relationship between smartphone addiction, loneliness, and depression in adolescents: A correlational structural equation modeling study. J Pediatr Nurs. 2024;76:150–9. https://doi.org/10.1016/j.pedn.2024.02.019 .
doi: 10.1016/j.pedn.2024.02.019
pubmed: 38402746
Yalçin I, Özkurt B, Özmaden M, Yağmur R. Effect of smartphone addiction on loneliness levels and academic achievement of z generation. Int J Psychol Educational Stud. 2020;7(1):208–14. https://doi.org/10.17220/ijpes.2020.01.017 .
doi: 10.17220/ijpes.2020.01.017
Aktürk Ü, Budak F, Gültekin A, Özdemir A. Comparison of smartphone addiction and loneliness in high school and university students. Perspect Psychiatr Care. 2018;54(4):564–70. https://doi.org/10.1111/ppc.12277 .
doi: 10.1111/ppc.12277
pubmed: 29601080
Jiang Q, Li Y, Shypenka V. Loneliness, individualism, and smartphone addiction among international students in China. Cyberpsychology Behav Social Netw. 2018;21(11):711–8. https://doi.org/10.1089/cyber.2018.0115 .
doi: 10.1089/cyber.2018.0115
Wang K, Ma Z, Meng H. The short-term longitudinal associations between loneliness and smartphone addiction: The mediating role of depression. Curr Psychol. 2024;43:20545–57. https://doi.org/10.1007/s12144-024-05836-6 .
doi: 10.1007/s12144-024-05836-6
Heshmati S, Blackard MB, Beckmann B, Chipidza W. Family relationships and adolescent loneliness: An application of social network analysis in family studies. J Fam Psychol. 2021;35(2):182. https://doi.org/10.1037/fam0000660 .
doi: 10.1037/fam0000660
pubmed: 33871279
Bayat N, Fokkema T, Mujakovic S, Ruiter RA. Contextual correlates of loneliness in adolescents. Child Youth Serv Rev. 2021;127:106083. https://doi.org/10.1016/j.childyouth.2021.106083 .
doi: 10.1016/j.childyouth.2021.106083
Cena L, Trainini A, Zecca S, Bonetti Zappa S, Cunegatti F, Buizza C. Loneliness, affective disorders, suicidal ideation, and the use of psychoactive substances in a sample of adolescents during the COVID-19 pandemic: A cross‐sectional study. J Child Adolesc Psychiatric Nurs. 2023;36(3):188–98. https://doi.org/10.1111/jcap.12412 .
doi: 10.1111/jcap.12412
Dunn C, Sicouri G. The relationship between loneliness and depressive symptoms in children and adolescents: A meta-analysis. Behav Change. 2022;39(3):134–45. https://doi.org/10.1017/bec.2022.13 .
doi: 10.1017/bec.2022.13
Zee PC, Turek FW. Sleep and health: Everywhere and in both directions. Arch Intern Med. 2006;166(16):1686–8. https://doi.org/10.1001/archinte.166.16.1686 .
doi: 10.1001/archinte.166.16.1686
pubmed: 16983044
Luyster FS, Strollo PJ Jr, Zee PC, Walsh JK. Sleep: A health imperative. Sleep. 2012;35(6):727–34. https://doi.org/10.5665/sleep.1846 .
doi: 10.5665/sleep.1846
pubmed: 22654183
pmcid: 3353049
Killgore WD. Effects of sleep deprivation on cognition. Prog Brain Res. 2010;185:105–29. https://doi.org/10.1016/B978-0-444-53702-7.00007-5 .
doi: 10.1016/B978-0-444-53702-7.00007-5
pubmed: 21075236
Talbot LS, McGlinchey EL, Kaplan KA, Dahl RE, Harvey AG. Sleep deprivation in adolescents and adults: changes in affect. Emotion. 2010;10(6):831–41. https://doi.org/10.1037/a0020138 .
doi: 10.1037/a0020138
pubmed: 21058849
pmcid: 3163498
Roberts RE, Duong HT. The prospective association between sleep deprivation and depression among adolescents. Sleep. 2014;37(2):239–44. https://doi.org/10.5665/sleep.3388 .
doi: 10.5665/sleep.3388
pubmed: 24497652
pmcid: 3900610
Acikgoz A, Acikgoz B, Acikgoz O. The effect of internet addiction and smartphone addiction on sleep quality among Turkish adolescents. PeerJ. 2022;10:e12876. https://doi.org/10.7717/peerj.12876 .
doi: 10.7717/peerj.12876
pubmed: 35178305
pmcid: 8817630
Chatterjee S, Kar SK. Smartphone addiction and quality of sleep among Indian medical students. Psychiatry. 2021;84(2):182–91. https://doi.org/10.1080/00332747.2021.1907870 .
doi: 10.1080/00332747.2021.1907870
pubmed: 33856961
Zhang MX, Zhou H, Yang HM, Wu AM. The prospective effect of problematic smartphone use and fear of missing out on sleep among Chinese adolescents. Curr Psychol. 2023;42(7):5297–305. https://doi.org/10.1007/s12144-021-01863-9 .
doi: 10.1007/s12144-021-01863-9
Li L, Niu Z, Griffiths MD, Mei S. The Smartphone Addiction Scale: Psychometric properties, invariance, network perspective, and latent profile analysis among a sample of Chinese university students. Int J Mental Health Addict. 2022;1–23. https://doi.org/10.1007/s11469 .
Mok JY, Choi SW, Kim DJ, Choi JS, Lee J, Ahn H, Song WY. Latent class analysis on internet and smartphone addiction in college students. Neuropsychiatr Dis Treat. 2014;817–28. https://doi.org/10.2147/NDT.S59293 .
Borsboom D, Deserno MK, Rhemtulla M, Epskamp S, Fried EI, McNally RJ, Waldorp LJ. Network analysis of multivariate data in psychological science. Nat Reviews Methods Primers. 2021;1(1):58. https://doi.org/10.1038/s43586-021-00055-w .
doi: 10.1038/s43586-021-00055-w
Golino HF, Epskamp S. Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PLoS ONE. 2017;12(6):e0174035. https://doi.org/10.1371/journal.pone.0174035 .
doi: 10.1371/journal.pone.0174035
pubmed: 28594839
pmcid: 5465941
Opsahl T, Agneessens F, Skvoretz J. Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks. 2010;32(3):245–51. https://doi.org/10.1016/j.socnet.2010.03.006 .
doi: 10.1016/j.socnet.2010.03.006
Şata M, Karip F. Turkish culture adaptation of Smartphone Addiction Scale-Short version for adolescents. Cumhuriyet Int J Educ. 2017;6(4):426–40. https://doi.org/10.30703/cije.346614 .
doi: 10.30703/cije.346614
LeBlanc JC, Almudevar A, Brooks SJ, Kutcher S. (2002). Screening for adolescent depression: Comparison of the Kutcher Adolescent Depression Scale with the Beck Depression Inventory. Journal of Child and Adolescent Psychopharmacology, 12(2), 113–126. https://doi.org/10.1089/104454602760219153
Tatar A, Bekiroğlu B. Translation of the short form Kutcher Adolescent Depression Scale (Kads-6-tr) into Turkish and examination of its psychometric properties. Social Mentality Researcher Thinkers J. 2019;5(22):1200–9. https://doi.org/10.31576/smryj.331 .
doi: 10.31576/smryj.331
Hays RD, DiMatteo MR. A short-form measure of loneliness. J Pers Assess. 1987;51(1):69–81. https://doi.org/10.1207/s15327752jpa5101_6 .
doi: 10.1207/s15327752jpa5101_6
pubmed: 3572711
Yıldız MA, Duy B. Adaptation of the short-form of the UCLA Loneliness Scale (Uls-8) to Turkish for the adolescents. Düşünen Adam: J Psychiatry Neurol Sci. 2014;27(3):194–203. https://doi.org/10.5350/DAJPN2014270302 .
doi: 10.5350/DAJPN2014270302
Kandemir M, Bozdemir E, Hayran Y, Tonga Z, Kandemir A. Sleep Deprivation Scale for Children and Adolescents. J Interdisciplinary Education: Theory Pract. 2021;3(1):48–61. https://doi.org/10.47157/jietp.875187 .
doi: 10.47157/jietp.875187
Tabachnick BG, Fidell LS. Using multivariate statistics. 6th ed. Pearson Education; 2013.
SPSS PASW. Statistics 18 core system user’s guide. SPSS; 2009.
Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equation Modeling: Multidisciplinary J. 1999;6(1):1–55. https://doi.org/10.1080/10705519909540118 .
doi: 10.1080/10705519909540118
Kelloway EK. Using Mplus for structural equation modeling: A researcher’s guide. 2nd ed. London: Sage; 2015.
Goss–Sampson M. (2022). Statistical analysis in JASP: A guide for students (4th Ed.).
Muthén LK, Muthén BO. Mplus user’s guide. 7th ed. Los Angeles, CA: Author; 2015.
Nylund KL, Asparouhov T, Muthén BO. Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Struct Equation Modeling: Multidisciplinary J. 2007;14(4):535–69. https://doi.org/10.1080/10705510701575396 .
doi: 10.1080/10705510701575396
Tein JY, Coxe S, Cham H. Statistical power to detect the correct number of classes in latent profile analysis. Struct Equation Modeling: Multidisciplinary J. 2013;20(4):640–57. https://doi.org/10.1080/10705511.2013.824781 .
doi: 10.1080/10705511.2013.824781
Wagenmakers E-J, Kucharský Š. The JASP data library. JASP Publishing. 2020. https://doi.org/10.31234/osf.io/vr2u8 .
doi: 10.31234/osf.io/vr2u8
Ferguson SL, Moore EWG, Hull DM. Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers. Int J Behav Dev. 2020;44(5):458–68. https://doi.org/10.1177/0165025419881721 .
doi: 10.1177/0165025419881721
Kock N. Harman’s single factor test in PLS-SEM: Checking for common method bias. Data Anal Perspect J. 2020;2(2):1–6.
Choi DH, Jung YS. Temperament, character and cognitive emotional regulation in the latent profile classification of smartphone addiction in university students. Sustainability. 2022;14(18):11643. https://doi.org/10.3390/su141811643 .
doi: 10.3390/su141811643
Elhai JD, Yang H, Dempsey AE, Montag C. Rumination and negative smartphone use expectancies are associated with greater levels of problematic smartphone use: A latent class analysis. Psychiatry Res. 2020;285:112845. https://doi.org/10.1016/j.psychres.2020.112845 .
doi: 10.1016/j.psychres.2020.112845
pubmed: 32045821
Yue H, Zhang X, Sun J, Liu M, Li C, Bao H. The relationships between negative emotions and latent classes of smartphone addiction. PLoS ONE. 2021;16(3):e0248555. https://doi.org/10.1371/journal.pone.0248555 .
doi: 10.1371/journal.pone.0248555
pubmed: 33720952
Lei LYC, Ismail MAA, Mohammad JAM, Yusoff MSB. The relationship of smartphone addiction with psychological distress and neuroticism among university medical students. BMC Psychol. 2020;8:1–9. https://doi.org/10.1186/s40359-020-00466-6 .
doi: 10.1186/s40359-020-00466-6
Psychological Reports, 00332941231180119. https://doi.org/10.1177/00332941231180119.
Chen C, Zhang KZK, Gong X, Lee M. Dual mechanisms of reinforcement reward and habit in driving smartphone addiction: The role of smartphone features. Internet Res. 2019;29(6):1551–70. https://doi.org/10.1108/INTR-11-2018-0489 .
doi: 10.1108/INTR-11-2018-0489
Park JH. The convergent effects of smartphone addiction on sleeping time and sleep deprivation among college students. J Digit Convergence. 2019;17(9):311–20. https://doi.org/10.14400/JDC.2019.17.9.311 .
doi: 10.14400/JDC.2019.17.9.311
Kortesoja L, Vainikainen MP, Hotulainen R, Merikanto I. Late-night digital media use in relation to chronotype, sleep and tiredness on school days in adolescence. J Youth Adolesc. 2023;52(2):419–33. https://doi.org/10.1007/s10964-022-01703-4 .
doi: 10.1007/s10964-022-01703-4
pubmed: 36401709
Dikeç G, Yalniz T, Bektaş B, Turhan A, Çevik S. Relationship between smartphone addiction and loneliness among adolescents. J Depend. 2017;18(4):103–11.
Karakaya EN, Ersoy AF, Karakaya C. Ergenlerde teknoloji bağımlılığı: Pandemi dönemi üzerinden bir inceleme [Technology Addiction in Adolescents: A Research of the Pandemic Process]. Online J Technol Addict Cyberbullying. 2023;10(1):37–57.
Ayar D, Bektas M, Bektas I, Kudubes AA, Ok YS, Altan SS, Celik I. The effect of adolescents’ internet addiction on smartphone addiction. J Addictions Nurs. 2017;28(4):210–4. https://doi.org/10.1097/JAN.0000000000000196 .
doi: 10.1097/JAN.0000000000000196
Liu H, Zhou Z, Huang L, Zhu E, Yu L, Zhang M. Prevalence of smartphone addiction and its effects on subhealth and insomnia: A cross-sectional study among medical students. BMC Psychiatry. 2022;22(1):1–7. https://doi.org/10.1186/s12888-022-03956-6 .
doi: 10.1186/s12888-022-03956-6
Al Battashi N, Omari A, Sawalha O, Al Maktoumi M, Alsuleitini S, A., Qadire A, M. The relationship between smartphone use, insomnia, stress, and anxiety among university students: A cross-sectional study. Clin Nurs Res. 2021;30(6):734–40. https://doi.org/10.1177/1054773820983161 .
doi: 10.1177/1054773820983161
pubmed: 33375850
Sleep, 34(8), 1013–1020. https://doi.org/10.5665/SLEEP.1152.
Lemola S, Perkinson-Gloor N, Brand S, Dewald-Kaufmann JF, Grob A. Adolescents’ electronic media use at night, sleep disturbance, and depressive symptoms in the smartphone age. J Youth Adolesc. 2015;44(2):405–18. https://doi.org/10.1007/s10964-014-0176-x .
doi: 10.1007/s10964-014-0176-x
pubmed: 25204836
Gedik S, Gezgin DM. Üniversite öğrencilerinin akıllı telefon bağımlılığının rekreatif faaliyetlere katılım davranışları açısından incelenmesi [Smartphone addiction in university students: Is participation in recreative activities a dissuading factor]. Gençlik Araştırmaları Dergisi. 2022;10(28):1–20. https://doi.org/10.52528/genclikarastirmalari.973348 .
doi: 10.52528/genclikarastirmalari.973348
Bütüner R, Bütüner N, Bütüner M. Ergenlerde sosyal medya bağımlılığı konusunda son beş yılda yapılmış çalışmaların incelenmesi [About social media addiction in adolescents analysis of the studies made in the last 5 years]. J Inform Syst Manage Res. 2022;4(2):17–34.
Yıldırım M, Çiçek İ, Öztekin GG, Aziz IA, Hu J. Associations between problematic social media use and psychological adjustment in Turkish adolescents: Mediating roles of family relationships. Int J Mental Health Addict. 2023;1–19. https://doi.org/10.1007/s11469-023-01138-3 .
Moral R, Kumcağız H. Ergenlerdeki internet bağımlılığı: Anne, baba ve akran ilişkileri açısından bir değerlendirme [Internet addiction in adolescence: Evaluation from mother, father and peer relationship perspectives]. Ordu Üniversitesi Sosyal Bilimler Enstitüsü. Sosyal Bilimler Araştırmaları Dergisi. 2019;9(2):335–46.
Kawabe K, Horiuchi F, Oka Y, Ueno SI. Association between sleep habits and problems and internet addiction in adolescents. Psychiatry Invest. 2019;16(8):581–7. https://doi.org/10.30773/pi.2019.03.21.2 .
doi: 10.30773/pi.2019.03.21.2