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Differences in Factors Associated with Depressive Symptoms between Urban and Rural Female Adolescents in Korea

  • Lee, Gyuyoung (Redcross College of Nursing, Chung-Ang University) ;
  • Ham, Ok Kyung (Department of Nursing, Inha University) ;
  • Lee, Bo Gyeong (College of Nursing.The Research Institute of Nursing Science, Catholic University of Daegu) ;
  • Kim, Abuan Micah (Department of Nursing, Inha University)
  • Received : 2018.03.19
  • Accepted : 2018.08.19
  • Published : 2018.08.31

Abstract

Purpose: To examine the prevalence of depressive symptoms and differentiate factors associated with them in urban and rural areas by applying the Ecological Models of Health Behavior. Methods: We employed a cross-sectional design and convenience sample of 460 female adolescents. The instruments included the Adolescent Mental-Health Problem-Behavior Questionnaire (AMPQ-II) and the Beck Depression Inventory (BDI). Results: Depressive symptoms were confirmed in 15.7% of urban adolescents and 22.9% of rural adolescents (p<.05). In the urban group, perception of health and stress associated with school performance were significantly associated with depressive symptoms. In the rural group, academic/internet related problems and rule violations were significantly associated with depressive symptoms (p<.05). General life happiness, worry/anxiety, and mood/suicidal ideation were common factors in both urban and rural areas (p<.05). Conclusion: Multiple factors were associated with depressive symptoms, and those significant factors differed between urban and rural female youths. Accordingly, tailored approaches are required considering urban and rural differences. The approaches should include intrapersonal, interpersonal, and organizational levels of interventions.

Keywords

References

  1. Dunn EC, Milliren CE, Evans CR, Subramanian SV, Richmond TK. Disentangling the relative influence of schools and neighborhoods on adolescents' risk for depressive symptom. American Journal of Public Health. 2015;105(4):732-740. https://doi.org/10.2105/AJPH.2014.302374
  2. Kann L, McManus T, Harris WA, Shanklin SL, Flint KH, Hawkins J, et al. Youth risk behavior surveillance-United States, 2015. Morbidity and Mortality Weekly Report Surveillance Summaries. 2016;65(6):1-174. https://doi.org/10.15585/mmwr.ss6506a1
  3. Hankin BL, Mermelstein R, Roesch L. Sex differences in adolescent depression: Stress exposure and reactivity models. Child Development. 2007;78(1):279-295. https://doi.org/10.1111/j.1467-8624.2007.00997.x
  4. Korea Centers for Disease Control and Prevention (KCDC). The 2015 Korea youth risk behavior web-based survey [Internet]. Cheongju: Korea Centers for Disease Control and Prevention (KCDC); c2016 [cited 2017 Jan 10]. Available from: https://yhs.cdc.go.kr/new/pages/main.asp.
  5. Lee H, Jung HY, Yun E, Um HY, Jee YJ. Factors influencing depression among middle-school girls. Journal of Korean Academy of Nursing. 2011;41(4):550-557. https://doi.org/10.4040/jkan.2011.41.4.550
  6. Kim JH, Choi YH. Influencing factors on middle school girls’ sense of coherence and depression. Crisis and Emergency Management: Theory and Praxis. 2015;11(3):177-187.
  7. Kim EY. Factors causing depression in middle school students [master's thesis]. Daejeon: Chungnam National University; 2014. p. 1-87.
  8. Kang HW, Park KM. Comparison of correlates of depression in late-life between urban and rural areas. Journal of the Korean Gerontological Society. 2012;32(1):129-143.
  9. Kim YS, Jun HY, Kim CH, Hwang SH. Comparison on the depression and quality of life in low-income elderly between urban and rural area. Journal of Korean Society of Living Environmental System. 2012;19(1):42-50.
  10. Sallis J, Owen N, Fisher E. Ecological models of health behavior. In: Glanz K, Rimer BK, Viswanath K, editors. Health Behaviors and Health Education. 4th ed. San Francisco (CA): John Wiley & Sons; 2008. p. 465-485.
  11. Kaufman MR, Cornish F, Zimmerman RS, Johnson BT. Health behavior change models for HIV prevention and AIDS care: Practical recommendations for a multi-level approach. Journal of Acquired Immune Deficiency Syndromes. 2014;66 Suppl 3:S250-S258. https://doi.org/10.1097/QAI.0000000000000236
  12. Gu J, Lau JT, Li M, Li H, Gao Q, Feng X, et al. Socio-ecological factors associated with depression, suicidal ideation and suicidal attempt among female injection drug users who are sex workers in China. Drug and Alcohol Dependence. 2014;144: 102-110. https://doi.org/10.1016/j.drugalcdep.2014.08.011
  13. Goodman JF. School discipline in moral disarray. Journal of Moral Education. 2006;35(2):213-230. https://doi.org/10.1080/03057240600681736
  14. Lee G, Ham OK. Behavioral and psychosocial factors associated with suicidal ideation among adolescents. Nursing & Health Sciences. 2018;10. Forthcoming. https://doi.org/10.1111/nhs.12422
  15. Bhang SY, Yoo HK, Kim JH, Kim B, Bahn GH, Ahn D, et al. Revision of adolescent mental health and problem behavior screening questionnaire: Development of adolescent mental health and problem behavior screening questionnaire-II. Journal of the Korean Academy of Child and Adolescent Psychiatry. 2011;22:271-286. https://doi.org/10.5765/jkacap.2011.22.4.271
  16. Beck AT, Steer RA, Ball R, Ranieri WF. Comparison of beck depression inventories-Ia and II in psychiatric outpatients. Journal of Personality Assessment. 1996;67(3):588-597. https://doi.org/10.1207/s15327752jpa6703_13
  17. Lee YH, Song JY. A study of the reliability and the validity of the BDI, SDS, and MMPI-D scales. Korean Journal of Clinical Psychology. 1991;10(1):98-113.
  18. Park HJ, Kim HN, Kim IB, Jeon SA. Reliability of the beck depression inventory in adolescence. Journal of Korean Academy of Family Medicine. 2000;21(2):244-253.
  19. Pallant J. SPSS survival manual: A step by step guide to data analysis using SPSS. Philadelphia (PA): Open University Press;2001. p. 217.
  20. Yeresyan I, Lohaus A. Stress and wellbeing among Turkish and German adolescents living in rural and urban areas. Rural and Remote Health. 2014;14(2):2695.
  21. Byeon H. The relationship between BMI, weight perception and depression-like symptoms in Korean middle school students. Journal of the Korea Academia-Industrial Cooperation Society. 2013;14(12):6317-6323. https://doi.org/10.5762/KAIS.2013.14.12.6317
  22. Park JS. The direct and indirect effects of career risk on excessive use of internet for rural adolescents, through depression and withdrawal coping. Korean Journal of Youth Studies. 2011;18(8):21-43.
  23. Yoon MS, Cho HJ, Lee HJ. Effects of internet use and alcohol use on the adolescent’s depression. Social Science Research Review. 2009;25(4):347-370.
  24. Ybarra ML, Alexander C, Mitchell KJ. Depressive symptomatology, youth internet use, and online interactions: A national survey. Journal of Adolescent Health. 2005;36(1):9-18. https://doi.org/10.1016/j.jadohealth.2003.10.012
  25. Bak SA. Study on the internet addiction of middle school students in farming community [master's thesis]. Muan: Mokpo National University; 2006. p. 1-79.
  26. Litheko SRS. The difference in performance between schools situated in the urban areas and those in the rural areas of Lesotho. Electronic Journal for Inclusive Education [Internet]. 2012;2(9):Article 2. Available From: https://corescholar.libraries.wright.edu/cgi/viewcontent.cgi?article=1138&context=ejie.
  27. Park YS, Park YK, Kim UC, Han KH. Academic achievement and quality of life among urban and rural students: A comparative analysis of the influence of residence, parental expectations of academic achievement, parent-child conflict and self-efficacy. Studies on Korean Youth. 2011;22(3):5-41.
  28. Shaver AE. Patterns of rule-violating behavior in children and adolescents [dissertation]. Columbus (OH): The Ohio State University; 2003. p. 1-125.
  29. Kim JY, Lee IS. A study on the effect of behavioral maladjustment of youth experiencing domestic violence in urban and rural areas: Moderating effect of protective factors. Journal of Korean Association of Victimology. 2008;16(1):199-228.

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