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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張弘潔(Hung-Chieh Chang) | |
| dc.contributor.author | Jung-Fang Liang | en |
| dc.contributor.author | 梁容方 | zh_TW |
| dc.date.accessioned | 2021-06-08T03:37:24Z | - |
| dc.date.copyright | 2019-08-26 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-07-22 | |
| dc.identifier.citation | 1. Vos, T., et al., Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. The Lancet, 2016. 388(10053): p. 1545-1602. 2. Depression, W., Other Common Mental Disorders: Global Health Estimates. Geneva: World Health Organization, 2017: p. 1-24. 3. Mezuk, B., et al., Depression and type 2 diabetes over the lifespan: a meta-analysis. Diabetes care, 2008. 31(12): p. 2383-2390. 4. Martin-Subero, M., et al., Depression as measured by PHQ-9 versus clinical diagnosis as an independent predictor of long-term mortality in a prospective cohort of medical inpatients. Psychosomatic medicine, 2017. 79(3): p. 273-282. 5. Johnston, K., et al., The burden of treatment-resistant depression: a systematic review of the economic and quality of life literature. Journal of Affective Disorders, 2018. 6. 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Edelbrock, Manual for the child behavior checklist: and revised child behavior profile. 1983: University of Vermont, Department of Psychiatry. 26. Birmaher, B., et al., Childhood and adolescent depression: a review of the past 10 years. Part I. Journal of the American Academy of Child Adolescent Psychiatry, 1996. 35(11): p. 1427-1439. 27. Weller, E.B. and R.A. Weller, Depression in adolescents: Growing pains or true morbidity? Journal of Affective Disorders, 2000. 61: p. S9-S13. 28. Beckham, E.E., et al., Development of an instrument to measure Beck's cognitive triad: The Cognitive Triad Inventory. Journal of consulting and clinical psychology, 1986. 54(4): p. 566. 29. Kaslow, N.J., et al., Cognitive Triad Inventory for Children: Development and relation to depression and anxiety. Journal of Clinical Child Psychology, 1992. 21(4): p. 339-347. 30. Bennett, D.S., et al., Relationship of Beck Depression Inventory factors to depression among adolescents. Journal of affective disorders, 1997. 45(3): p. 127-134. 31. Kendall, P.C., et al., Issues and recommendations regarding use of the Beck Depression Inventory. Cognitive therapy and research, 1987. 11(3): p. 289-299. 32. Kovacs, M., Children's depression inventory. 1992: Multi-Health Systems North Tonawanda, NY. 33. Gilman, S.E., et al., Socioeconomic status in childhood and the lifetime risk of major depression. International journal of epidemiology, 2002. 31(2): p. 359-367. 34. Twenge, J.M. and S. Nolen-Hoeksema, Age, gender, race, socioeconomic status, and birth cohort difference on the children's depression inventory: A meta-analysis. Journal of abnormal psychology, 2002. 111(4): p. 578. 35. Goodman, E., G.B. Slap, and B. Huang, The public health impact of socioeconomic status on adolescent depression and obesity. American journal of public health, 2003. 93(11): p. 1844-1850. 36. Weissman, M.M. and G.L. Klerman, Sex differences and the epidemiology of depression. Archives of general psychiatry, 1977. 34(1): p. 98-111. 21. Petersen, A.C., et al., Depression in adolescence. American psychologist, 1993. 48(2): p. 155. 22. Petersen, A.C., et al., A self-image questionnaire for young adolescents (SIQYA): Reliability and validity studies. Journal of Youth and Adolescence, 1984. 13(2): p. 93-111. 23. Kovacs, M., Rating scales to assess depression in school-aged children. Acta Paedopsychiatrica: International Journal of Child Adolescent Psychiatry, 1981. 24. Achenbach, T.M., Integrative guide for the 1991 CBCL/4-18, YSR, and TRF profiles. 1991: Department of Psychiatry, University of Vermont. 25. Achenbach, T.M. and C.S. Edelbrock, Manual for the child behavior checklist: and revised child behavior profile. 1983: University of Vermont, Department of Psychiatry. 26. Birmaher, B., et al., Childhood and adolescent depression: a review of the past 10 years. Part I. Journal of the American Academy of Child Adolescent Psychiatry, 1996. 35(11): p. 1427-1439. 27. Weller, E.B. and R.A. Weller, Depression in adolescents: Growing pains or true morbidity? Journal of Affective Disorders, 2000. 61: p. S9-S13. 28. Beckham, E.E., et al., Development of an instrument to measure Beck's cognitive triad: The Cognitive Triad Inventory. Journal of consulting and clinical psychology, 1986. 54(4): p. 566. 29. Kaslow, N.J., et al., Cognitive Triad Inventory for Children: Development and relation to depression and anxiety. Journal of Clinical Child Psychology, 1992. 21(4): p. 339-347. 30. Bennett, D.S., et al., Relationship of Beck Depression Inventory factors to depression among adolescents. Journal of affective disorders, 1997. 45(3): p. 127-134. 31. Kendall, P.C., et al., Issues and recommendations regarding use of the Beck Depression Inventory. Cognitive therapy and research, 1987. 11(3): p. 289-299. 32. 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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21544 | - |
| dc.description.abstract | 近年來,憂鬱已成為重要的公共心理衛生議題。根據世界衛生組織(WHO)的估算,全球約有10%~20%的兒童及青少年有心理方面疾病。然而,過去的研究大多為橫斷性研究,較少的研究在於探討童年的社經地位以及青少年時期的社會因素對於青少年及成年憂鬱的長期影響。本研究透過長期追蹤樣本,探討13-22歲之憂鬱情緒發展情形,以及13-22歲憂鬱情緒軌跡之社會因素。
本研究樣本採用「兒童與青少年行為之長期發展研究計畫(Child and Adolescent Behaviors in Long-term Evolution,簡稱CABLE)」,進行次級資料分析。採用2005年至2016年之部份資料,在去除遺失值後,最後納入2382位追蹤個案進行分析。本研究以群體基礎軌跡模型(Group-based trajectory model)進行憂鬱情緒軌跡分析,最後以多元邏輯思迴歸探討軌跡類型之影響因素。 本研究樣本之憂鬱情緒趨勢呈現先上升後下降之趨勢,並以18歲(2012年)為最高峰,兩性在統計上呈現不同的憂鬱情緒軌跡。就男性而言,憂鬱情緒軌跡可分為三組: 「輕微下降組」,「中等後期下降組」以及「中等且嚴重上升組」。就女性而言,憂鬱情緒軌跡可分為四組: 「輕微下降組」,「中等後期下降組」以及「中等且嚴重上升組」以及「持續嚴重組」。在影響因素方面,不論在男性還是女性樣本,父親教育程度、國中家庭支持、國中同儕支持、高中同儕支持以及國高中重大事件在統計上對13-22歲之憂鬱情緒軌跡均有顯著關係。 本研究結論13-22歲憂鬱情緒軌跡具有性別差異,女性之憂鬱情緒分數顯著高於男性,且國高中重大事件皆會影響13-22歲之憂鬱情緒軌跡。因此建議在制定或執行心理健康政策時,應將性別差異納入考量,並加強對於壓力適應技巧之教學。 | zh_TW |
| dc.description.abstract | In recent years, depression has become an important public mental health issue. According to the World Health organization (WHO), about 10% to 20% of children and adolescents around the world have mental illness. However, most of studies used cross-sectional analysis, few studies explored the long-term effects of childhood socioeconomic status and social determinants of depression from adolescence to young adulthood. This study aimed to investigate the development of depressive mood in 13-22 years of age, and the social factors of the trajectory of their depressive mood with a cohort sample in Taiwan.
Data used in this study were obtained from the Child and Adolescent Behaviors in Long-term Evolution (CABLE) study. A total of 2382 participants were included in the analysis. Group-based trajectory model were used to analyze the depressive mood trajectory and the multinomial logistic regression was to explore the associated factors of the depressive mood trajectory. The trajectory of depressive mood in this study showed an inverse-u shape, while it reached its peak when the sample was 18 years old. In the male sample, the trajectory of depressive mood can be divided into three groups: a slight decline, a moderate to late decline, and a moderate and severe rise. Among female, the trajectory of depressive mood can be divided into four groups: a slight decline, a moderate to late decline group, a moderate and severely elevated group, as well as a persistent severe group. In both male and female samples, father education, family support in the middle school, family support in high school, support from colleagues in the middle school, support from high school colleagues, and negative life events in the high school are associated with the trajectory of depressive mood. This study indicated the trajectory of depressive mood in 13-22 years had gender differences. The trajectory of depressive mood in females is significantly higher than that in males, and negative life events in the high school affect the trajectory of depressive mood in 13-22 years. Therefore, when formulating or implementing mental health policies, gender differences should be taken into account and strengthen the teaching of stress coping skills. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T03:37:24Z (GMT). No. of bitstreams: 1 ntu-108-R06848019-1.pdf: 1671752 bytes, checksum: 3f0214b0cb42d4c70e50dcbc5d099d63 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 誌謝 i 中文摘要 ii ABSTRACT iii 第一章 緒論 1 第二章 文獻探討 3 第一節 青少年憂鬱的概念與測量 3 第二節 青少年憂鬱的社會影響因素 11 第三節 青少年憂鬱軌跡的發展 13 第四節 青少年憂鬱軌跡的社會影響因素 14 第三章 研究方法 17 第一節 研究架構 17 第二節 研究目的 18 第三節 資料來源 19 第四節 研究對象 20 第五節 研究工具 22 第六節 資料分析 32 第四章 研究結果 35 第一節 研究樣本特性 35 第二節 研究樣本之憂鬱傾向分佈情形 40 第三節 研究樣本的憂鬱情緒發展軌跡類型 43 第四節 憂鬱情緒軌跡類型之相關影響因素分布情形 52 第五節 憂鬱情緒軌跡類型之影響因素:多變項邏輯思迴歸分析 64 第五章 討論 72 第一節 13-22歲憂鬱情緒發展趨勢與軌跡類型 72 第二節 13-22歲憂鬱軌跡之社會決定因素 75 第三節 研究限制 77 第六章 結論與建議 78 第一節 結論 78 第二節 政策建議與未來研究建議 80 參考資料 82 | |
| dc.language.iso | zh-TW | |
| dc.title | 13-22歲憂鬱情緒軌跡與社會因素之關係 | zh_TW |
| dc.title | The association between social factors and trajectory of depressive mood among people aged 13-22 years | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 江東亮(Tung-Liang Chiang),李思賢 | |
| dc.subject.keyword | 憂鬱情緒軌跡,性別差異,縱貫研究,社會因素,心理健康, | zh_TW |
| dc.subject.keyword | depressive mood trajectory,gender difference,longitudinal study,social factors,mental health, | en |
| dc.relation.page | 87 | |
| dc.identifier.doi | 10.6342/NTU201901782 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2019-07-23 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 健康政策與管理研究所 | zh_TW |
| 顯示於系所單位: | 健康政策與管理研究所 | |
文件中的檔案:
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-108-1.pdf 未授權公開取用 | 1.63 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。
