Volume 9, Issue 4 (Autumn 2020)                   JOHE 2020, 9(4): 206-212 | Back to browse issues page


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Jafarzadeh M, Cheshmi M, Ranjbar Kolagari M, Madadi R, Seyed Jafari J. Comparing Rumination and Depression Scores in Employed and Unemployed Mothers of Children with Smartphone Addiction in Tehran, 2019-2020. JOHE. 2020; 9 (4) :206-212
URL: http://johe.rums.ac.ir/article-1-408-en.html
1- MSc in Family Counseling, Ardakan University, Ardakan, Iran.
2- MSc in Clinical Psychology, Family Therapy, Tehran University of Science and Culture, Tehran, Iran.
3- MSc in Educational Psychology, Islamic Azad University, Sari Branch, Sari, Iran.
4- MSc in Clinical Psychology, Master of Counseling and Guidance, Islamic Azad University, Roudehen Branch, Roudehen, Iran.
5- PhD Candidate in Psychology, Allameh Tabataba'i University, Tehran, Iran. , Javad-jafari90@yahoo.com
Abstract:   (322 Views)

Background: Smartphone addiction is a serious growing problem with similarities to game addiction and even drug addiction. Nowadays, a large number of Iranian children and teenagers find themselves addicted to their smartphones. This type of addiction has a serious impact on mental health among mothers. This study aimed to compare depression and rumination scores among employed and unemployed mothers of preschool children with smartphone addiction.
Materials and Methods: This is a descriptive correlational study, in which 150 mothers of preschool children were selected as the sample group. In this study, the Cellphone Overuse Scale (COS), the Beck Depression Questionnaire, and the Intellectual Rumination Questionnaire were utilized. In addition, the Pearson's correlation coefficient and the independent samples t-test methods were used for data analysis.
Results: According to the results, the mean and standard deviation of depression and rumination among employed and unemployed mothers were (M= 3.83, SD= 3.78) and (M=8.48, SD= 7.83), respectively. In addition, the mean of rumination among unemployed mothers (M= 24.08 SD=13.65) was significantly higher than that among employed mothers (M= 14.42, SD= 8.34) (p < 0.05).
Conclusion: The findings provide the preliminary foundation for further studies on designing effective prevention programs to prevent depression and rumination among mothers with children addicted to smartphones.

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Short Report: Original Article | Subject: Epidemiology
Received: 2020/11/26 | Accepted: 2021/01/27 | ePublished: 2021/06/21

References
1. Thimbleby H. Technology and the future of healthcare. J Public Health Res 2013; 2(3):e28. [DOI] [PMID] [PMCID]
2. Parasuraman S, Sam AT, Yee SWK, Chuon BLC, Ren LY. Smartphone usage and increased risk of mobile phone addiction: A concurrent study. Int J Pharm Investig 2017; 7(3):125-31. [DOI] [PMID] [PMCID]
3. 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. [DOI] [PMID] [PMCID]
4. Alavi AH, Buttlar WG. An Overview of Smartphone Technology for Citizen-Centered, Real-Time and Scalable Civil Infrastructure Monitoring. Future Gener Comput Syst 2019; 93(2019):651-72. [Article]
5. Kuss DJ, Kanjo E, Crook-Rumsey M, Kibowski F, Wang GY, Sumich A. Problematic Mobile Phone Use and Addiction Across Generations: The Roles of Psychopathological Symptoms and Smartphone Use. J Technol Behav Sci 2018; 3(3):141-9. [DOI] [PMID] [PMCID]
6. Cheever NA, Rosen LD, Carrier LM, Chavez A. Out of sight is not out of mind: The impact of restricting wireless mobile device use on anxiety levels among low, moderate and high users. Comput Human Behav 2014; 37:290-7. [DOI]
7. Panova T, Lleras A. Avoidance or boredom: Negative mental health outcomes associated with use of Information and Communication Technologies depend on users’ motivations. Comput Human Behav 2016; 58:249-58. [DOI]
8. Cha SS, Seo BK. Smartphone use and smartphone addiction in middle school students in Korea: Prevalence, social networking service, and game use. Health Psychol Open 2018; 5(1):2055102918755046. [DOI] [PMID] [PMCID]
9. Kim HH, Chun J. Is the relationship between parental abuse and mobile phone dependency (MPD) contingent across neighborhood characteristics? A multilevel analysis of Korean Children and Youth Panel Survey. PLoS One 2018; 13(5):e0196824. [DOI] [PMID] [PMCID]
10. Samaha M, Hawi NS. Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Comput Human Behav 2016; 57:321-5. [DOI]
11. Kim HJ, Min JY, Kim HJ, Min KB. Accident risk associated with smartphone addiction: A study on university students in Korea. J Behav Addict 2017; 6(4):699-707. [DOI] [PMID] [PMCID]
12. Ihm J. Social implications of children’s smartphone addiction: The role of support networks and social engagement. J Behav Addict 2018; 7(2):473-81. [DOI] [PMID] [PMCID]
13. Lyubomirsky S, Layous K, Chancellor J, Nelson SK. Thinking about rumination: the scholarly contributions and intellectual legacy of Susan Nolen-Hoeksema. Annu Rev Clin Psychol 2015; 11:1-22. [DOI] [PMID]
14. Bonifacci P, Tobia V, Marra V, Desideri L, Baiocco R, Ottaviani C. Rumination and Emotional Profile in Children with Specific Learning Disorders and Their Parents. Int J Environ Res Public Health 2020; 17(2):389. [DOI] [PMID] [PMCID]
15. Michl LC, McLaughlin KA, Shepherd K, Nolen-Hoeksema S. Rumination as a mechanism linking stressful life events to symptoms of depression and anxiety: Longitudinal evidence in early adolescents and adults. J Abnorm Psychol 2013; 122(2):339-52. [DOI] [PMID] [PMCID]
16. Karabati S, Ensari N, Fiorentino D. Job Satisfaction, Rumination, and Subjective Well-Being: A Moderated Mediational Model. J Happiness Stud 2019; 20(1):251-68. [DOI]
17. Sun H, Tan Q, Fan G, Tsui Q. Different effects of rumination on depression: key role of hope. Int J Ment Health Syst 2014; 8:53. [DOI] [PMID] [PMCID]
18. Hasegawa A, Kunisato Y, Morimoto H, Nishimura H, Matsuda Y. How do Rumination and Social Problem Solving Intensify Depression? A Longitudinal Study. J Ration Emot Cogn Behav Ther 2018; 36(1):28-46. [DOI] [PMID] [PMCID]
19. Hasegawa A, Kunisato Y, Morimoto H, Nishimura H, Matsuda Y. Depressive rumination and urgency have mutually enhancing relationships but both predict unique variance in future depression: A longitudinal study. Cogent Psychology 2018; 5(1):1450919. [DOI]
20. Jenaro C, Flores N, Gómez-Vela M, González-Gil F, Caballo C. Problematic internet and cell-phone use: Psychological, behavioral, and health correlates. Addict Res Theory 2007; 15(3):309-20. [DOI]
21. Golmohammadian M, Yaseminejad P. Normalization, Validity and Reliability of Cell-Phone Over-Use Scale (COS) among University Students. Journal of Social Psychology 2011; 6(19):37-52 [Article]
22. Beck AT, Epstein N, Brown G, Steer RA. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol 1988; 56(6):893-7. [DOI] [PMID]
23. Beck AT, Clarck DA. Anxiety and depression: an information processing perspective. Anxiety Res 1988; 1(1):23-36 [DOI]
24. Zemestani M, Davoodi I, Mehrabi-Zadeh Honarmand M, Zargar Y. Effectiveness of Group Behavioral Activation on Depression, Anxiety and Rumination in Patients with Depression and Anxiety. Journal of Clinical Psychology 2014; 5(4):73-84. [DOI]
25. Nolen-Hoeksema S. Responses to depression and their effects on the duration of depressive episodes. J Abnorm Psychol 1991; 100(4):569-82. [DOI] [PMID]
26. Bagherinezhad M, Salehi Fadardi J, Tabatabayi SM. The relationship between rumination and depression in a sample of Iranian student. Research in Clinical Psychology and Counseling 2010; 11(1):21-38. [DOI]
27. Hasegawa A, Yoshida T, Hattori Y, Nishimura H, Morimoto H, Tanno Y. Depressive Rumination and Social Problem Solving in Japanese University Students. J Cogn Psychother 2015; 29(2):134-52. [DOI] [PMID]
28. Moberly NJ, Watkins ER. Ruminative self-focus and negative affect: An experience sampling study. J Abnorm Psychol 2008; 117(2):314-23. [DOI] [PMID] [PMCID]
29. Nolen-Hoeksema S, Larson J, Grayson C. Explaining the gender difference in depressive symptoms. J Pers Soc Psychol 1999; 77(5):1061-72. [DOI] [PMID]
30. Sharma K, Mishra S. Comparative study of well-being of working and non-working women. Indian Journal of Health & Well-being 2018; 9(5):799-801.
31. Neubert M, Süssenbach P, Rief W, Euteneuer F. Unemployment and mental health in the German population: the role of subjective social status. Psychol Res Behav Manag 2019; 12:557-64. [DOI] [PMID] [PMCID]
32. McMunn A, Kelly Y, Cable N, Bartley M. 082 Maternal employment and child socio-emotional behaviour: longitudinal evidence from the Millennium Cohort Study. J Epidemiol Community Health 2010; 64(Suppl 1):A32-3. [DOI]
33. Rashid T, Mustafa S. To Measure the Level of Depression among Working and Non-Working Married Women. Annals of Punjab Medical College 2015; 9(2):95-9. [Article]

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