@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
BRIEF TEXT
Million messages can be transferred through the Internet, which affect the values, attitudes and cultural identity of their users in small scale and the socio-cultural systems in big scale [1-3].
... [4-8]. Although the advancement of technology and communications and as a result using Internet for different purposes are positive, however it has led to excessive use of those negative aspects; in particular, today Internet has become one of the leisure options for teenagers and youth. Internet addiction was first introduced in 1995 by Goldberg. He believed that Internet addiction is considered as an incompatible pattern of Internet use, which results in significant harm and disturbance [9]. According to the American Psychiatric Association, Internet addiction is a pattern which causes functional impairment and is associated with an unpleasant sense over a two-month period. Internet addiction is like drug addiction and other dependencies [10]. Internet addiction refers is a kind of behavioral dependence on the Internet that is determined by features, such as depression, introversion, shyness, boredom and loneliness, fear, overactive and social anxiety [11]. ... [12-26]. On the other hand, the high school, in which independent identities and independency of students compared with the obedient elementary school students are formed is considered by educators. In this regard, the results of some relevant studies on internet addiction and anxiety, stress and depression indicate that there is a significant relationship between Internet addiction and these variables [22-24, 27-35]. In addition, mobile phones today have become more popular amongst students and virtual networks such as Telegram and Instagram are more used.
The present study was conducted to determine the relationship between Internet addiction and depression among secondary school students in Kordokuy city.
This research is a descriptive correlational study.
This study was conducted on secondary school students in Kordokuy city, Golestan, Iran, in the academic year of 2016-2017.
The sample size according to Morgan sampling table was estimated 288 subjects who were selected by cluster random sampling and entered the study. Accordingly, Kordokuy city was divided into two parts, the north and south. Two schools (a girls’ school and a boys’ school) were selected from each region (a total of four schools), and then 72 students were selected from each school.
The educators of Kordokuy city approved the study and the students were informed about the confidentiality of data and the informed consent was received from participants then the research tools were distributed among the subjects. It is notable that through the study, while referring to the classes and asking the students to complete the questionnaire, the subjects were informed that they are free to leave the class. Data was collected using the demographic information scale as well as Beck Depression Inventory and Internet Addiction Inventory by Young. The Beck Depression Inventory is a revised version of this scale designed to measure the severity of depression. This edition also is a 21-item scale and measures all dimensions of depression based on cognitive theory. In this questionnaire, those who are scored from 1 to 14 do not have depression and are at normal levels, and those who are scored above 14 are depressed. It should be noted that the reliability of this tool has reported 94.9 [36]. The Internet Addiction Inventory by Young was another used tool. It is notable that the two Internet addiction questionnaires by Young, including 8 and 20 questions are commonly used in studies to diagnosis Internet addiction. In the present study, those who were scored equal to or lower than 49 in IAT exam were considered as regular user group of the Internet, whereas those with higher scores were the addicted group. It should be noted that Persian version of this scale has been used in Iran and its reliability has been confirmed by the Cronbach's alpha of 0.81 [37]. To analyze the data, SPSS 21 software and one-sample t-test, independent t-test, one-way ANOVA and Spearman correlation coefficient were used. It is notable that the significance level in all tests was considered less than 0.05.
180 female students and 108 male students participated in the study. According to the results of independent t-test, there was no significant difference in the mean scores of depression and Internet addiction among boys and girls (p>0.05). Internet addiction and the mean depression scores were 37.57 and 7.72, respectively. The results of One-sample t-test showed that there was a significant difference between the mean of depression, Internet addiction and the test mean score (p<0.001; Table 2). The relationship between internet addiction and depression among students based on social networks is presented in Table 3. According to the findings, the lowest score of Internet addiction and depression belonged to the students who have not used any of the social networks such as telegrams and Instagram, whereas the highest score of internet addiction and depression were attributed to students who have used telegram. The results of one-way ANOVA showed that there was a significant difference between students in terms of the social network types (p<0.001); as students who have not used any of the social networks such as telegram and Instagram scored the lowest score significantly. In addition, studying the relationship between Internet addiction and depression among students indicated that there was a positive and significant correlation between Internet addiction and depression among students (p<0.001, r=0.324). In other words, by increasing the level of Internet addiction, the level of depression was also increased among students.
The results showed that there was a significant relationship between Internet addiction and depression; in other words, by increasing the level of Internet addiction, the level of depression was also increased among students, which is consistent with the results of similar studies [9, 23, 24, 27-29, 31-35]. It was also found that the studied students have used telegram, both and the Instagram, respectively. In fact, the lowest scores for Internet addiction and depression were for students who have not used any of the social networks such as Telegram and Instagram. Moreover, the results indicated that there was no significant difference between girls and boys. In this regard, other research results showed that there is no significant difference between the score of Internet addiction and depression among boys and girls [31]. ... [32]. In fact, the increased use of Internet is associated with the reduction of family relationships and participation in local social associations. In this regard, the results of another research showed that there is a negative and significant relationship between extraversion, conscientiousness, quality of social relationships, satisfaction, and psychological quality of users with Internet addiction [38]. A research on 732 Internet users aged 15-39 years showed that 30% of Internet addicts have different degrees of antisocial personality disorder and abnormal social behaviors [39].
More accurate studies on Internet addiction and depression should be done over time to provide assessment more confidently.
The type of present study as a cross-sectional research is one of the limitations of this study.
There is a significant relationship between Internet addiction and depression; in other words, by increasing the level of Internet addiction, the level of depression is also increased among students. In addition, Students have used Telegram more than Instagram or both, which is not different among boys and girls.
The authors are thankful to all the students participating in the research.
None declared.
This study was supported by the authors.
TABLES and CHARTS
Show attach fileCITIATION LINKS
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[20]American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Washington, DC: American Psychiatric Association; 2013.
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[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]
[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]