Üniversite Öğrencilerinde Mobil Cihaz Bağımlılığı Beyin Sisine Neden Olabilir Mi?

Yıl 2026, Cilt: 28 Sayı: 1 , 198 - 210 , 30.04.2026

Muhammet Mavibaş , Nurullah Fırat

https://doi.org/10.15314/tsed.1740129

https://izlik.org/JA85YF24KH

Öz

Bu çalışmanın temel hedefi, üniversite öğrencileri arasında mobil cihaz bağımlılığı ile beyin sisi (zihinsel bulanıklık) arasındaki ilişkiyi araştırmak ve mobil cihaz kullanım düzeyinin beyin sisi üzerindeki etkileyici rolünü belirlemektir.
Araştırmada ilişkisel tarama modeli tercih edilmiştir. 2024-2025 eğitim-öğretim yılında Erzurum Teknik Üniversitesi'nde öğrenim gören lisans öğrencileri çalışma evrenini oluşturmuştur. Basit rastgele örnekleme yöntemiyle seçilen ve araştırmaya katılmayı kabul eden 421 öğrenci örnekleme dahil edilmiştir. Veri toplama sürecinde Kişisel Bilgi Formu, Fidan (25) tarafından geliştirilen Mobil Bağımlılık Ölçeği ve Atik & Manav (26) tarafından geliştirilen Beyin Sisi Ölçeği kullanılmıştır. Elde edilen veriler SPSS 25.0 programı aracılığıyla analiz edilmiş; tanımlayıcı istatistiklerin yanı sıra t-testi, tek yönlü ANOVA ve çoklu regresyon analizleri gerçekleştirilmiştir.
Analiz sonuçları, mobil bağımlılık düzeyinin beyin sisi düzeyini anlamlı biçimde öngördüğünü göstermiştir (β=0,486; p<0,001). Özellikle mobil bağımlılığın belirginlik, çatışma ve tekrarlama alt boyutlarının beyin sisi üzerinde anlamlı etkileri olduğu belirlenmiştir (R²=0,258). Kadın öğrencilerde mobil bağımlılık ve beyin sisi düzeyleri, erkek öğrencilere kıyasla daha yüksek bulunmuştur. Ayrıca mobil cihazlarını video, film veya müzik izlemek için kullanan öğrencilerin beyin sisi düzeyleri, cihazlarını iletişim için kullananlara göre daha yüksektir. Günlük mobil cihaz kullanım süresi arttıkça hem mobil bağımlılık hem de beyin sisi düzeylerinin yükseldiği görülmüştür.
Araştırma, üniversite öğrencilerinde mobil cihaz bağımlılığı ile beyin sisi arasında anlamlı ve pozitif bir ilişki olduğunu ortaya koymuştur. Bu ilişki özellikle mobil kullanım farkındalığı, içsel çatışmalar ve tekrarlayıcı kullanım davranışlarıyla açıklanabilir. Elde edilen sonuçlar, dijital farkındalık eğitimlerinin, öz-düzenleme tekniklerinin ve dijital detoks uygulamalarının üniversite öğrencileri için ne kadar önemli olduğunu vurgulamaktadır.

Anahtar Kelimeler

Mobil Bağımlılık , Beyin Sisi , Üniversite Öğrencileri , Davranışsal Bağımlılık , Dijital Sağlık

Etik Beyan

Bu çalışma, Erzurum Teknik Üniversitesi Bilimsel Araştırma ve Yayın Etik Kurulu tarafından onaylanmıştır (Toplantı No: 04, Tarih: 04.04.2024, Karar No: 25). Araştırma sürecinde katılım gönüllülük esasına dayalı olmuş, kişisel verilerin gizliliği korunmuş ve akademik etik ilkelere sıkı sıkıya bağlı kalınmıştır.

Destekleyen Kurum

TÜBİTAK | Türkiye Bilimsel ve Teknolojik Araştırma Kurumu

Proje Numarası

1919B012328076

Teşekkür

Bu araştırma, Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK) tarafından 2209-A Üniversite Öğrencileri Araştırma Projeleri Destek Programı kapsamında desteklenmiştir (Proje No: 1919B012328076). TÜBİTAK’a maddi ve bilimsel destekleri için içten teşekkürlerimizi sunarız.

Can Mobile Device Addiction Cause Brain Fog in University Students?

https://izlik.org/JA85YF24KH

Öz

The primary aim of this study is to investigate the relationship between mobile device addiction and brain fog (mental clouding) among university students and to determine the predictive role of mobile device usage levels on brain fog.
A relational survey model was employed in the study. The population consisted of undergraduate students enrolled at Erzurum Technical University during the 2024–2025 academic year. A total of 421 students were selected through simple random sampling and agreed to participate in the study. Data were collected using a Personal Information Form, the Mobile Addiction Scale developed by Fidan (25), and the Brain Fog Scale developed by Atik and Manav (26). The collected data were analyzed using SPSS 25.0, and descriptive statistics, independent samples t-tests, one-way ANOVA, and multiple regression analyses were conducted.
Analysis results indicated that the level of mobile addiction significantly predicted the level of brain fog (β = 0.486; p < .001). In particular, the subdimensions of mobile addiction—salience, conflict, and relapse—were found to have significant effects on brain fog (R² = 0.258). Female students reported higher levels of both mobile addiction and brain fog compared to male students. Moreover, students who primarily used their mobile devices for watching videos, movies, or listening to music showed higher levels of brain fog than those who used them mainly for communication purposes. Increased daily mobile device usage was associated with elevated levels of both mobile addiction and brain fog.
The study revealed a significant and positive relationship between mobile device addiction and brain fog among university students. This relationship can be explained particularly by heightened digital salience, internal conflicts, and repetitive usage behaviors. The findings highlight the importance of digital awareness programs, self-regulation strategies, and digital detox interventions for university students.

Anahtar Kelimeler

Mobile Addiction , Brain Fog , University Students , Behavioral Addiction , Digital Health

Etik Beyan

This study was approved by the Scientific Research and Publication Ethics Committee of Erzurum Technical University (Meeting No: 04, Date: 04.04.2024, Decision No: 25). Participation was voluntary throughout the research process, confidentiality of personal data was maintained, and academic ethical principles were strictly adhered to.

Destekleyen Kurum

TÜBİTAK | Türkiye Bilimsel ve Teknolojik Araştırma Kurumu

Proje Numarası

1919B012328076

Teşekkür

This research was supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) under the 2209-A University Students Research Projects Support Program (Project No: 1919B012328076). We would like to extend our sincere thanks to TÜBİTAK for their financial and scientific support.

Kaynakça

• 1. Klemens G. The cellphone: The history and technology of the gadget that changed the world. Jefferson, NC: McFarland, 2014.
• 2. Park WK. Mobile phone addiction. In: A sense of place: The global and the local in mobile communication, Nyíri K, ed. Vienna: Passagen Verlag, 2005:253-272.
• 3. Walsh SP, White KM, Young RM. Needing to connect: The effect of self and others on young people's involvement with their mobile phones. Australian Journal of Psychology, 2010; 62(4): 194-203. https://doi.org/10.1080/00049530903567229
• 4. Sparrow B, Liu J, Wegner DM. Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 2011; 333(6043): 776-778. https://doi.org/10.1126/science.1207745
• 5. Toda M, Ezoe S, Takeshita T. Mobile phone use and stress-coping strategies of medical students. International Journal of Cyber Behavior, Psychology and Learning, 2014; 4(4): 41-46. https://doi.org/10.4018/ijcbpl.2014100104
• 6. Bianchi A, Phillips JG. Psychological predictors of problem mobile phone use. CyberPsychology & Behavior, 2005; 8(1): 39-51. https://doi.org/10.1089/cpb.2005.8.39
• 7. Lee H, Ahn H, Choi S, Choi W. The SAMS: Smartphone addiction management system and verification. Journal of Medical Systems, 2014; 38(1): 1. https://doi.org/10.1007/s10916-013-0001-1
• 8. Greenfield DN. Psychological characteristics of compulsive internet use: A preliminary analysis. CyberPsychology & Behavior, 1999; 2(5): 403-412. https://doi.org/10.1089/cpb.1999.2.403
• 9. Goodman A. Addiction: Definition and implications. British Journal of Addiction, 1990; 85(11): 1403-1408. https://doi.org/10.1111/j.1360- 0443.1990.tb01620.x
• 10. Davis RA. A cognitive-behavioral model of pathological internet use. Computers in Human Behavior, 2001; 17(2): 187-195. https://doi.org/10.1016/S0747-5632(00)00041-8
• 11. Young KS, Yue XD, Ying L. Prevalence estimates and etiologic models of internet addiction. In: Internet addiction: A handbook and guide to evaluation and treatment, Young KS, de Abreu CN, eds. Hoboken, NJ: John Wiley & Sons, 2007:1-17. https://doi.org/10.1002/9781118013991.ch1
• 12. Harari YN. 21. yüzyıl için 21 ders. İstanbul: Kolektif Kitap, 2018.
• 13. Griffiths MD. Technological addictions. Clinical Psychology Forum, 1995; 76: 14-19.
• 14. Griffiths MD. A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use, 2005; 10(4): 191- 197. https://doi.org/10.1080/14659890500114359
• 15. Kwon M, Kim D-J, 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
• 16. Twenge JM, Campbell WK. Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive Medicine Reports, 2018; 12: 271-283. https://doi.org/10.1016/j.pmedr.2018.10.003
• 17. Cash H, Rae CD, Steel AH, Winkler A. Internet addiction: A brief summary of research and practice. Current Psychiatry Reviews, 2012; 8(4): 292-298. https://doi.org/10.2174/157340012803520513
• 18. Vogel EA, Rose JP, Roberts LR, Eckles K. Social comparison, social media, and self-esteem. Psychology of Popular Media Culture, 2014; 3(4): 206-222. https://doi.org/10.1037/ppm0000047
• 19. Chang A-M, Aeschbach D, Duffy JF, Czeisler CA. Evening use of light-emitting eReaders negatively affects sleep, circadian timing, and next-morning alertness. Proceedings of the National Academy of Sciences, 2015; 112(4): 1232-1237. https://doi.org/10.1073/pnas.1418490112
• 20. Hansraj KK. Assessment of stresses in the cervical spine caused by posture and position of the head. Surgical Technology International, 2014; 25: 277-279.
• 21. Ophir E, Nass C, Wagner AD. Cognitive control in media multitaskers. Proceedings of the National Academy of Sciences, 2009; 106(37): 15583-15587. https://doi.org/10.1073/pnas.0903620106
• 22. Kolb B, Whishaw IQ, Teskey GC. An introduction to brain and behavior. New York: Worth Publishers, 2014:873.
• 23. Theoharides TC, Stewart JM, Hatziagelaki E, Kolaitis G. Brain “fog,” inflammation and obesity: Key aspects of neuropsychiatric disorders improved by luteolin. Frontiers in Neuroscience, 2015; 9: 225. https://doi.org/10.3389/fnins.2015.00225
• 24. Karasar N. Bilimsel araştırma yöntemi. Ankara: Nobel Yayıncılık, 2012.
• 25. Fidan H. Mobil bağımlılık ölçeği'nin geliştirilmesi ve geçerliliği: Bileşenler modeli yaklaşımı. Addicta: The Turkish Journal on Addictions, 2016; 3(3): 433-469.
• 26. Atik D, Manav AI. A scale development study: Brain fog scale. Psychiatria Danubina, 2023; 35(1): 73-79. https://doi.org/10.24869/psyd.2023.73
• 27. Tabachnick BG, Fidell LS. Using multivariate statistics. 6th ed. Boston, MA: Pearson, 2013.
• 28. Ward AF, Duke K, Gneezy A, Bos MW. Brain drain: The mere presence of one’s own smartphone reduces available cognitive capacity. Journal of the Association for Consumer Research, 2017; 2(2): 140-154. https://doi.org/10.1086/691462
• 29. Wilmer HH, Sherman LE, Chein JM. Smartphones and cognition: A review of research editorial board exploring the links between mobile technology habits and cognitive functioning. Frontiers in Psychology, 2017; 8: 605. https://doi.org/10.3389/fpsyg.2017.00605
• 30. Loh KK, Kanai R. How has the internet reshaped human cognition? The Neuroscientist, 2015; 22(5): 506-520. https://doi.org/10.1177/1073858415595005
• 31. Thomée S, Härenstam A, Hagberg M. Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults–a prospective cohort study. BMC Public Health, 2011; 11: 66. https://doi.org/10.1186/1471-2458-11-66
• 32. Montag C, Blaszkiewicz K, Lachmann B, Sariyska R, Andone I, Trendafilov B, Markowetz A. Recorded behavior as a valuable resource for diagnostics in mobile phone addiction: Evidence from psychoinformatics. Behavioral Sciences, 2015; 5(4): 434-442. https://doi.org/10.3390/bs5040434
• 33. Firth J, Torous J, Stubbs B, Firth JA, Steiner GZ, Smith L, Sarris J. The "online brain": How the internet may be changing our cognition. World Psychiatry, 2019; 18(2): 119-129. https://doi.org/10.1002/wps.20617
• 34. Hadlington LJ. Cognitive failures in daily life: Exploring the link with internet addiction and problematic mobile phone use. Computers in Human Behavior, 2015; 51: 75-81. https://doi.org/10.1016/j.chb.2015.04.036
• 35. Horvath J, Mundinger C, Schmitgen MM, Wolf ND, Sambataro F, Hirjak D, Kubera KM. Structural and functional correlates of smartphone addiction. Addictive Behaviors, 2020; 105: 106334. https://doi.org/10.1016/j.addbeh.2020.106334
• 36. Barr N, Pennycook G, Stolz JA, Fugelsang JA. The brain in your pocket: Evidence that smartphones are used to supplant thinking. Computers in Human Behavior, 2015; 48: 473-480. https://doi.org/10.1016/j.chb.2015.02.029
• 37. Carr N. The shallows: What the internet is doing to our brains. New York: W. W. Norton & Company, 2020.
• 38. Elhai JD, Dvorak RD, Levine JC, Hall BJ. Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders, 2017; 207: 251-259. https://doi.org/10.1016/j.jad.2016.08.030
• 39. Brand M, Wegmann E, Stark R, Müller A, Wölfling K, Robbins TW, Potenza MN. The interaction of person-affect-cognition-execution (I- PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neuroscience & Biobehavioral Reviews, 2019; 104: 1-10. https://doi.org/10.1016/j.neubiorev.2019.06.032
• 40. Turel O, Bechara A. A triadic reflective-impulsive-interoceptive awareness model of general and impulsive information system use: Behavioral tests of neuro-cognitive theory. Frontiers in Psychology, 2016; 7: 601. https://doi.org/10.3389/fpsyg.2016.00601
• 41. Dempsey AE, O'Brien KD, Tiamiyu MF, Elhai JD. Fear of missing out (FoMO) and rumination mediate relations between social anxiety and problematic Facebook use. Addictive Behaviors Reports, 2019; 9: 100150. https://doi.org/10.1016/j.abrep.2018.100150
• 42. Rozgonjuk D, Levine JC, Hall BJ, Elhai JD. The association between problematic smartphone use, depression and anxiety symptom severity, and objectively measured smartphone use over one week. Computers in Human Behavior, 2018; 87: 10-17. https://doi.org/10.1016/j.chb.2018.05.019
• 43. Demirci K, Akgönül M, Akpinar A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. Journal of Behavioral Addictions, 2015; 4(2): 85-92. https://doi.org/10.1556/2006.4.2015.010
• 44. Kuss DJ, Griffiths MD. Internet addiction in psychotherapy. London: Palgrave Macmillan, 2015.