@2024 Afarand., IRAN
ISSN: 2383-2150 Journal of Education and Community Health 2018;5(1):4-12
ISSN: 2383-2150 Journal of Education and Community Health 2018;5(1):4-12
Evaluation of the Effectiveness of Collaborative Care Model on the Quality of Life and Metabolic Indexes in Patients with Type 2 Diabetes
ARTICLE INFO
Article Type
Original ResearchAuthors
Salehi Omran Ebrahim (1)Abedini Baltork Meimanat (1,*)
Azizi Shomami Mostafa (1)
Keshavarz Kosar (1)
(1) Department of Education, Faculty of Humanities and Social Sciences, University of Mazandaran, Tehran, Iran
Correspondence
Article History
Received: January 11, 2018Accepted: May 5, 2018
ePublished: June 1, 2018
ABSTRACT
Aims
The internet can sometimes endanger the users' mental health due to its improper use. Accordingly, this communication network has turned into an addictive factor in recent decades. This kind of addiction can lead to depression. Regarding this, the present study was conducted to determine the relationship between internet addiction and depression among secondary school students.
Materials & Methods This descriptive and correlational study was conducted on secondary school students in Kordokuy city, Golestan, Iran, in the academic year of 2016-2017. The sample size was determined as 288 cases based on the Morgan sampling table. The study population was selected using cluster sampling method. The data were collected using the Beck Depression Inventory and Internet Addiction Inventory by Young. Data analysis was performed in SPSS (version 21) using independent t-test, one-way ANOVA, and Spearman's correlation coefficient.
Findings According to the results, there was a direct relationship between addiction to internet and students' depression (r=0.324, P<0.001). The largest use of virtual networks was related to Telegram software with the mean value of 40.29. Furthermore, no significant difference was observed between the male and female students in terms of internet addiction and depression (P>0.05).
Conclusion Given the significant relationship between the internet addiction and depression among students, it is recommended to design and implement educational programs for students and parents.
Materials & Methods This descriptive and correlational study was conducted on secondary school students in Kordokuy city, Golestan, Iran, in the academic year of 2016-2017. The sample size was determined as 288 cases based on the Morgan sampling table. The study population was selected using cluster sampling method. The data were collected using the Beck Depression Inventory and Internet Addiction Inventory by Young. Data analysis was performed in SPSS (version 21) using independent t-test, one-way ANOVA, and Spearman's correlation coefficient.
Findings According to the results, there was a direct relationship between addiction to internet and students' depression (r=0.324, P<0.001). The largest use of virtual networks was related to Telegram software with the mean value of 40.29. Furthermore, no significant difference was observed between the male and female students in terms of internet addiction and depression (P>0.05).
Conclusion Given the significant relationship between the internet addiction and depression among students, it is recommended to design and implement educational programs for students and parents.
CITATION LINKS
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[34]Kaur K. Internet addiction among adolescents in relation to depression. Int J Manag Appl Sci. 2015;1(9):207-9.
[35]Seghati T, Jahanpour H, Amirshahi R. Depression and internet dependence in students at Islamic Azad University of Rasht. WALIA J. 2015;31(4):148-53.
[36]Dabson KS, Mohammad KP. Psychometric characteristics of Beck depression inventory-II in patients with major depressive disorder. J Rehabil. 2007;8(29):80-6. [Persian]
[37]Bahrei N, Sadegh Moghadam L, Khodadost L, Mohammadzadeh J, Banafsheh E. Internet addiction status and its relation with students’ general health at Gonabad Medical University. Mod Care J. 2011;8(3):166-73. [Persian]
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[39]Dargahi H, Razavi M. Internet addiction and factors related with it in Tehran city. J Payesh. 2007;6(3):265-72. [Persian]
[2]Bagheri Benjar A, Heshmati MR, Kermani B. The effect of internet addiction on academic failure among students of Shahed University in Tehran, The first National Student Conference on Social Determinants of Health; 2010. [Persian]
[3]Abdel-Aziz AA, Abdel-Salam H, El-Sayad Z. The role of ICTs in creating the new social public place of the digital era. Alexandri Eng J. 2016;55(1):487-93. DOI: 10.1016/j.aej.2015.12.019
[4]Bashir H, Sadegh Afrasyabi M. Internet social networks and youth lifestyles. Rahavarenoor. 2013;12(43):2-15. [Persian]
[5]Akhavan MF, Noghaani M, Mazlum KM. Virtual social networks and happiness. Rasane Farhang. 2014;4(2):1-24. [Persian]
[6]Shekari NS, Hajiyani E. A study on effects of virtual social networks (facebook) on youngsters’lifestyle. J Cult Manag. 2014;8(26):63-79. [Persian]
[7]Miniwatts marketing group. Internet World State. Available at: URL: http://www.internet world stats .com; 2017.
[8]Soltanifar M. Modern public diplomacy and electricity public relations. Tehran: Simaye Shargh; 2010. [Persian]
[9]Tamannaeifar MR, Seddighi Arfaei F, Gandomi Z. Relationship between Internet use and academic achievement among high school students in Kashan. J Qazvin Univ Med Sci. 2013;17(2):78-82. [Persian]
[10]Hosseinpour E, Asgari A, Ayati M. The relationship between internet and cell-phone addictions and academic burnout in university students. J Informat Communict Technol Educ Sci. 2016;6(4):59-73. [Persian]
[11]Bakhshayesh AR. Prediction of internet addiction through personality traits and its relationship with perception of social interaction among female university students. Woman Culture Art. 2014;6(1):29-44. [Persian]
[12]World Health Organization. Depression: a global crisis. World mental health day, October 10 2012. Occoquan, Va, USA: World Federation for Mental Health; 2012.
[13]National Institute of Mental Health. Depression basics. Bethesda: National Institute of Mental Health; 2016.
[14]Zahn R, Lythe KE, Gethin JA, Green S, Deakin JF, Young AH, et al. The role of self-blame and worthlessness in the psychopathology of major depressive disorder. J Affect Disord. 2015;186:337-41. PMID: 26277271 DOI: 10.1016/j.jad.2015.08.001
[15]Bajraktarov S, Gudeva-Nikovska D, Manuševa N, Arsova S. Personality characteristics as predictive factors for the occurrence of depressive disorder. Open Access Maced J Med Sci. 2017;5(1):48-53. PMID: 28293316 DOI: 10.3889/oamjms.2017.022
[16]Deumic E, Butcher BD, Clayton AD, Dindo LN, Burns TL, Calarge CA. Sexual functioning in adolescents with major depressive disorder. J Clin Psychiatry. 2016;77(7):957-62. PMID: 27464316 DOI: 10.4088/JCP.15m09840
[17]Depression. Anxiety and Depression Association of Amrica. Available at: URL: https://adaa.org/understanding-anxiety/depression; 2016.
[18]Ferreira TS, Moreira CZ, Guo J, Noce F. Effects of a 12-hour shift on mood states and sleepiness of Neonatal Intensive Care Unit nurses. Rev Esc Enferm USP. 2017; 51:e03202. PMID: 28300964 DOI: 10.1590/S1980-220X2016033203202
[19]Karimi ZA, Mazaheri M. A study of the spiritual intelligence and quality of life among imprisoned women of Zahedan city. Soc Sci. 2016;11(12):3059-62.
[20]American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Washington, DC: American Psychiatric Association; 2013.
[21]Rivaz M, Shokrollahi P, Ghadakpour S, Zarshenas L. Depression and its associated effects on nursing and midwifery school female students. J Women Soc. 2013;4(3):63-85. [Persian]
[22]Turi A, Miri MR, Beheshti D, Yari E, Khodabakhshi H, Sarab GR. The prevalence of internet addiction and its relationship with anxiety, stress and depression in high school students in Birjand in 2014. J Birjand Univ Med Sci. 2014;22(1):67-75. [Persian]
[23]Shahbazirad A, Mirderikvand F. The relationship of internet addiction with depression, mental health and demographic characteristic in the students of Kermanshah University of Medical Sciences. J Ilam Univ Med Sci. 2014;22(4):1-8. [Persian]
[24]Barat Dastjerdi N, Sayadi S. Relationship between using social networks and internet addiction and depression among students. J Res Behav Sci. 2013;10(5):332-41. [Persian]
[25]Steadman K, Taskila T. Symptoms of depression and their effects on employment. London: The Work Foundation; 2015.
[26]Stander MP, Korb FA, De Necker M, De Beer JC, Miller-Janson HE, Moont HE. Depression and the impact on productivity in the workplace: findings from a South African survey on depression in the workplace. J Depress Anxiety. 2016;2(12):1-8. DOI: 10.4172/2167-1044.S2-012
[27]Kemijani S. The relationship between Internet addiction and anxiety depression and introverted and extrovert learning styles. [Master Thesis]. Tehran: Tarbiat Moallem University; 2014. [Persian]
[28]Jafari N, Fatehizadeh M. Investigation of the relationship between internet addiction and depression, anxiety, stress and social phobia among students in Isfahan University. Sci J Kurdistan Univ Med Sci. 2012;17(4):1-9. [Persian]
[29]Gholamian B, Shahnazi H, Hassanzadeh A. the prevalence of internet addiction and its association with depression, anxiety, and stress, among high-school students. Int J Pediatr. 2017;5(4):4763-70. DOI: 10.22038/ijp.2017.22516.1883
[30]Matar Boumosleh J, Jaalouk D. Depression, anxiety, and smartphone addiction in university students- a cross sectional study. PLoS One. 2017;12(8):e0182239. PMID: 28777828 DOI: 10.1371/journal.pone.0182239
[31]Shirazi M, Pour BA, Ghaffari P, Jahangir F, Daryaee E, Pour ZA, et al. The relationship between internet addiction and depression in nursing students of Larestan school of nursing and gerash paramedical school. J Obstet Gynecol Cancer Res. 2016;1(1).e7148. DOI: 10.17795/jogcr-7148
[32]Ostovar S, Allahyar N, Aminpoor H, Moafian F, Nor MB, Griffiths MD. Internet addiction and its psychosocial risks (depression, anxiety, stress and loneliness) among Iranian adolescents and young adults: a structural equation model in a cross-sectional study. Int J Mental Health Addict. 2016;14(3): 257-67. DOI: 10.1007/s11469-015-9628-0
[33]Jamwali A, Shekhar C, Choudhary N. Internet addiction as a predictor of depression, anxiety and stress (DASS). Int J Appl Home Sci. 2016;3(3-4):110-7.
[34]Kaur K. Internet addiction among adolescents in relation to depression. Int J Manag Appl Sci. 2015;1(9):207-9.
[35]Seghati T, Jahanpour H, Amirshahi R. Depression and internet dependence in students at Islamic Azad University of Rasht. WALIA J. 2015;31(4):148-53.
[36]Dabson KS, Mohammad KP. Psychometric characteristics of Beck depression inventory-II in patients with major depressive disorder. J Rehabil. 2007;8(29):80-6. [Persian]
[37]Bahrei N, Sadegh Moghadam L, Khodadost L, Mohammadzadeh J, Banafsheh E. Internet addiction status and its relation with students’ general health at Gonabad Medical University. Mod Care J. 2011;8(3):166-73. [Persian]
[38]Nadi MA, Sajjadian I. Path analysis of relationship between personality traits and Internet addiction with quality of life of Internet users in Isfahan city. J Res Behav Sci. 2010;8(1):34-45.
[39]Dargahi H, Razavi M. Internet addiction and factors related with it in Tehran city. J Payesh. 2007;6(3):265-72. [Persian]