A Cross-sectional survey of internet use among medical faculty students

Author :  

Year-Number: 2021-TJHS Vol 2 Issue 1
Language : Turkish
Konu : Sports Sciences

Abstract

Background and Aim: The internet plays an important role in our lives and is gradually becoming an indispensable part of our lives. An increase in psychosocial problems together with excessive internet use resulted in a new definition under the name of “internet addiction.” Although there are studies on internet addiction in our country, the lack of a specific study for medical faculty students, one of the groups that use the internet most commonly, draws attention. The purpose of this research was to determine the rate of internet addiction among medical faculty students, and to reveal the sociodemographic and clinical factors associated with internet addiction. Method: The study population (n=260) in this cross-sectional research consisted of 2nd year (n=135), 3rd year (n=72), and 4th year (n=53) students at the Medical Faculty of Alanya Alaaddin Keykubat University (ALKU). The study data were collected using the Sociodemographic Data Form, the Beck Depression Inventory (BDI), the Beck Anxiety Inventory (BAI), the Young Internet Addiction Scale (YIAS), and the Eating Attitudes Test (EAT-40). Clinical scales were applied to the students who volunteered to participate in the study after the approval of the ethics committee. Results: The rate of internet addiction among medical faculty students was 43.1%. YIAS scores were higher in male students and the difference in mean YIAS scores between the genders was statistically significant (p=0.033). YIAS scores were also higher in students aged 18-19 and 20 compared to those aged 21 or over (p=0.009). The risky-addicted user rate was higher among second-year students than in those in their third or fourth years (p=0.003). The numbers of risky-addicted internet users increased in line with duration of use (p=0.032). Positive correlation was determined between YIAS scores and BDI scores (Spearman's rho, p=0.004). Mean YIAS scores increased significantly with the severity of depression (p=0.012). No statistically significant correlation was determined between YIAS scores and BAI scores (Spearman's rho, p=0.065), and EAT-40 scores (p=0.751). Conclusion: The present study shows that the problem of internet addiction is being neglected and is not receiving the attention it deserves. The association between depression and internet addiction in this study makes it even more important that internet addiction be investigated in medical students exhibiting depressive symptoms. In addition to depression, male gender, young age, being in the early years of medical school, and a greater length of time spent online were identified as factors associated with internet addiction. In programs for struggling internet addiction, considering the gender difference in the planning of the programs, and creating a subtitle for male students more successful results can be obtained. Also it seems important that the programs to struggle internet addiction for medical faculty students should be carried out while the students are in the preparatory or first class of medicine faculty.

Keywords

Abstract

Keywords


  • 2. Kawabe K, Horiuchi F, Ochi M, Oka Y,Ueno Si. Internet addiction: Prevalence andrelation with mental states in adolescents.Psychiatry Clin Neurosci. 2016;70(9):405-3. Nath K, Naskar S, Victor R. A cross-sectional study on the prevalence, riskfactors, and ill effects of internet addictionamong medical students in NortheasternIndia. The primary care companion for CNS disorders. 2016;18(2).

  • 4. Dong G, Lu Q, Zhou H, Zhao X.Precursor or sequela: pathological disordersin people with Internet addiction disorder. PLoS One. 2011;6(2):e14703.

  • 5. Young KS. Internet addiction: symptoms,evaluation and treatment. Innovations inclinical practice: A source book. 1999;17(17):351-2.

  • 6. Young KS. Internet addiction: Evaluationand treatment. British Medical Journal Publishing Group; 1999.

  • 7. Prabhakaran MA, Patel VR, GanjiwaleDJ, Nimbalkar MS. Factors associated withinternet addiction among school-goingadolescents in Vadodara. Journal of familymedicine and primary care. 2016;5(4):765.8. Sharma A, Sahu R, Kasar PK, Sharma R.Internet addiction among professionalcourses students: A study from centralIndia. Int J Med Sci Public Health. 2014;3(9):1069-73.

  • 9. Durkee T, Carli V, Floderus B,Wasserman C, Sarchiapone M, Apter A, etal. Pathological internet use and risk-behaviors among European adolescents. IntJ Environ Res Public Health. 2016;13(3):294.

  • 10. Amichai-Hamburger Y, Ben-Artzi E.Loneliness and Internet use. Comput Human Behav. 2003;19(1):71-80.

  • 11. Kormas G, Critselis E, Janikian M,Kafetzis D, Tsitsika A. Risk factors andpsychosocial characteristics of potentialproblematic and problematic internet useamong adolescents: a cross-sectional study. BMC Public Health. 2011;11(1):595.

  • 12. Koo HJ, Kwon J-H. Risk and protectivefactors of Internet addiction: a meta-analysis of empirical studies in Korea. Yonsei Med J. 2014;55(6):1691-711.

  • 13. Association AP. Diagnostic andstatistical manual of mental disorders(DSM-5): American Psychiatric Pub; 2013.14. Dalal P, Basu D. Twenty years ofInternet addiction… Quo Vadis? Indian J Psychiatry. 2016;58(1):6.

  • 15. Beck AT, Ward C, Mendelson M, MockJ, Erbaugh J. Beck depression inventory(BDI). Arch Gen Psychiatry.16. Hisli N. Beck depresyon envanterininuniversite ogrencileri icin gecerliligi,guvenilirligi.(A reliability and validitystudy of Beck Depression Inventory in auniversity student sample). J Psychol. 1989;7:3-13.

  • 17. Beck AT, Epstein N, Brown G, SteerRA. An inventory for measuring clinicalanxiety: psychometric properties. J Consult Clin Psychol. 1988;56(6):893.

  • 18. Ulusoy M, Sahin NH, Erkmen H. TheBeck anxiety inventory: psychometricproperties. J Cogn Psychother.19. Young KS. Internet addiction: Theemergence of a new clinical disorder.Cyberpsychology & behavior.20. Bayraktar F. İnternet KullanımınınErgen Gelişimindeki Rolü: Yüksek LisansTezi, Ege Üniversitesi Sosyal Bilimler Enstitüsü, İzmir.; 2001.

  • of anorexia nervosa. Psychol Med.22. Savaşır I, Testi ENYT. AnoreksiNervoza belirtileri indeksi. Psikoloji Dergisi. 1989;7(23):19-25.

  • 23. Corp I. IBM SPSS statistics forwindows, version 22.0. Armonk, NY: IBM Corp2013.

  • 24. Cheng C, Li AY. Internet addictionprevalence and quality of (real) life: a meta-analysis of 31 nations across seven worldregions. Cyberpsychol Behav Soc Netw. 2014;17(12):755–60.

  • 25. Fatehi F, Monajemi A, Sadeghi A,Mojtahedzadeh R, Mirzazadeh A. Qualityof life in medical students with Internetaddiction. Acta Med Iran.2016;54(10):662–6. doi:10.4103/0253- 7176.92068.

  • 26. Zhang MW, Ho RC. Smartphoneapplications for immersive virtual realitytherapy for internet addiction and internetgaming disorder. Technol Health Care.2017;25(2):367–72. doi:10.3233/THC-27. Li W, O’Brien JE, Snyder SM, HowardMO. Characteristics of internetaddiction/pathological internet use in U.S.university students: a qualitative-methodinvestigation. PLoS One. 2015;10(2):e0117372.

  • 28. Zhang MW, Lim RB, Lee C, Ho RC.Prevalence of internet addiction in medicalstudents: a meta-analysis. Acad Psychiatry.29. Ali R, Mohammed N, Aly H. Internetaddiction among medical students of SohagUniversity, Egypt. Journal of EgyptianPublic Health Association. 2017;92(2):86-30. Pramanik T, Sherpa M, Shrestha R.Internet addiction in a group of medicalstudents: a cross sectional study. NepalMedical College Journal: NMCJ.31. Ghamari F, Mohammadbeigi A,Mohammadsalehi N, Hashiani AA. Internetaddiction and modeling its risk factors inmedical students, Iran. Indian J Psychol Med. 2011;33(2):158.

  • 32. Tsimtsiou Z, Haidich A-B, Spachos D,Kokkali S, Bamidis P, Dardavesis T, et al.Internet addiction in Greek medicalstudents: an online survey. Acad Psychiatry. 2015;39(3):300-4.

  • 33. Durmuş H, Günay O, Yıldız S, Timur A,Balcı E, Karaca S. Üniversiteöğrencilerinde internet bağımlılığı veüniversite yaşamı boyunca değişimi.Anadolu Psikiyatri Dergisi.34. Günay O, Öztürk A, Arslantaş EE.Üniversite Öğrencilerinde İnternetBağımlılığı ve Depresyon Düzeyleri. Neurol Sci. 2018;31:79-88.

  • 35. Ergin A, Uzun SU, Bozkurt Aİ. Tıpfakültesi öğrencilerinde internet bağımlılığısıklığı ve etkileyen etmenler. Pamukkale Tıp Dergisi. 2013(3):134-42.

  • 36. Balta ÖÇ. Web Tabanlı ÖğretimOrtamındaki Öğrencilerin İnternetBağımlılığını Etkileyen Faktörler. 2008.

  • 37. Kelleci M, Güler N, Sezer H, Gölbası Z.Lise Öğrencilerinde İnternet KullanmaSüresinin Cinsiyet ve Psikiyatrik Belirtilerile İlişkisi. TAF Preventive Medicine Bulletin. 2009;8(3).

  • 39. Duraimurugan S, Jayarin PJ, editors.Analysis and Study of MultimediaStreaming and Congestion EvadingAlgorithms in Heterogeneous NetworkEnvironment. 2018 Second InternationalConference on Intelligent Computing andControl Systems (ICICCS); 2018: IEEE.

  • Internet use among college students.Comput Human Behav. 2000;16(1):13-29.42. Yuen CN, Lavin MJ. Internetdependence in the collegiate population: therole of shyness. CyberPsychology & Behavior. 2004;7(4):379-83.

  • 43. Chaudhari B, Menon P, Saldanha D,Tewari A, Bhattacharya L. Internetaddiction and its determinants amongmedical students. Industrial psychiatry journal. 2015;24(2):158.

  • 44. Islam MA, Hossin MZ. Prevalence andrisk factors of problematic internet use andthe associated psychological distress amonggraduate students of Bangladesh. AsianJournal of Gambling Issues and Public Health. 2016;6(1):11.

  • 45. Balhara YPS, Doric A, Stevanovic D,Knez R, Singh S, Chowdhury MRR, et al.Correlates of Problematic Internet Useamong college and university students ineight countries: An international cross-sectional study. Asian J Psychiatr. 2019;45:113-20.

  • 46. Boonvisudhi T, Kuladee S. Associationbetween Internet addiction and depressionin Thai medical students at Faculty ofMedicine, Ramathibodi Hospital. PLoS One. 2017;12(3):e0174209.

  • 47. Lin SSJ, Tsai CC. Sensation seeking andinternet dependence of Taiwanese highschool adolescents. Comput Hum Behav. 2002; 18: 411–26.

  • 48. Özdemir Y, Kuzucu Y, Ak Ş.Depression, loneliness and Internetaddiction: How important is low self-control? Comput Human Behav.49. Dalbudak E, Evren C. The relationshipof Internet addiction severity with AttentionDeficit Hyperactivity Disorder symptoms inTurkish University students; impact ofpersonality traits, depression and anxiety.Compr Psychiatry. 2014;55(3):497-503.

  • 50. Pies R. Should DSM-V designate“Internet addiction” a mental disorder? Psychiatry (Edgmont). 2009;6(2):31.

  • 51. O'Brien CP. Commentary on Tao etal.(2010): Internet addiction and DSM‐V. Addiction. 2010;105(3):565-.

  • 52. Grant JE, Potenza MN, Weinstein A,Gorelick DA. Introduction to behavioraladdictions. The American journal of drug and alcohol abuse. 2010;36(5):233-41.

  • 53. Puthran R, Zhang MW, Tam WW, HoRC. Prevalence of depression amongstmedical students: A meta‐analysis. Med Educ. 2016;50(4):456-68.

  • 54. Lee YS, Han DH, Yang KC, DanielsMA, Na C, Kee BS, et al. Depression-likecharacteristics of 5HTTLPR polymorphismand temperament in excessive Internetusers. J Affect Disord. 2008; 109: 165-9. doi:10.1016/j.jad.2007.10.020.

  • 55. Tayhan KF, Yabancı AN. Relationshipbetween eating disorders and internet andsmartphone addiction in college students.Eat Weight Disord. 2020 Oct 9. doi:10.1007/s40519-020-01027-x. Online ahead of print. PMID: 33034868.

  • 56. Ivezaj V, Marc N, Potenza MD, GriloCM, White MA. An ExploratoryExamination of At-Risk/ProblematicInternet Use and Disordered Eating inAdults. Addict Behav 2017; 64: 301-307. doi: 10.1016/j.addbeh.2015.11.015.

  • 57. Tao ZL, Liu Y. Eat Weight Disord Isthere a relationship between Internetdependence and eating disorders? Acomparison study of Internet dependentsand non-Internet dependents. 2009; 14(2-3): e77-83. doi: 10.1007/BF03327803.

                                                                                                                                                                                                        
  • Article Statistics