臺灣博碩士論文加值系統

背景與目的：近年來，青少年憂鬱已成為重要的公共衛生議題。從生命歷程觀點來看，早期負面暴露可能會增加未來發生心理疾病的風險，如：早期社經地位或出生體重等。然而，過去相關研究大多為橫斷面分析，較少探討早期負面暴露對青少年憂鬱的長期影響。因此，本研究目的在於釐清早期社經地位與出生體重對青少年憂鬱軌跡發展的影響。

研究方法：本研究資料來源為台灣長期教育追蹤資料庫，以四波皆有參與調查的學生為主要研究樣本，經排除資料填答不完整的個案後，共有3,600位學生納入後續分析。本研究納入早期社經地位 (早期經濟狀況、父親教育程度)、出生體重、壓力源和社會支持等相關因素，分別利用成長曲線模型和潛在類別成長模型分析青少年憂鬱軌跡變化及軌跡類型的影響因素。

研究結果：在成長曲線模型結果發現，女性憂鬱起始值會受到出生體重、早期經濟狀況、國中負面事件及家庭支持的影響，而女性憂鬱改變速率則受到家庭負面事件、國中負面事件與高中負面事件的影響，但僅國中負面事件會造成男性憂鬱起始值與改變速率的影響。在潛在類別成長模型方面，無論男女6年憂鬱軌跡類型皆可分為4類，但略有不同。女性憂鬱軌跡類型分別命名為持續低 (709人, 39%)、持續中等 (891人, 46.5%)、持續高 (174人, 9.5%)，與下降 (84人, 5%)；而男性憂鬱軌跡類型則分別命名為持續低 (836人, 48.1%)、持續中等 (762人, 42.8%)、下降 (57人, 3.7%)，和上升 (87人, 5.4%)。女性憂鬱軌跡類型會受到早期經濟狀況、家庭負面事件、學校負面事件、家庭支持與同儕支持的影響。而男性憂鬱軌跡類型則受到父親教育程度、學校負面事件、家庭支持與同儕支持的影響。

結論：早期社經地位對青少年憂鬱軌跡變化及軌跡類型有顯著的影響，且不同性別對早期社經地位測量指標的敏感度不同，而出生體重則僅會影響女性憂鬱軌跡變化的起始值。

Background and objectives: In recent years, adolescent depression has become a serious public health issue. From life course perspective, early life exposures, such as early socioeconomic status and birth weight, may increase risk for mental disorder in later life. However, little is known about the long-term effects of early life exposures on depression trajectories. This study aimed to investigate how early socioeconomic status and birth weight affect the depression trajectories among adolescents.

Methods: Data used in this study were obtained from the Taiwan Education Panel Survey (TEPS), Center for Survey Research, Academia Sinica. A total of 3,600 participants who completed four waves of survey between 2001 and 2007 were included in this study analysis. The measures collected included: (1) independent variable: depression (scale range: 6-24); (2) dependent variables: early socioeconomic status and birth weight; (3) confounders: sex, negative life events, social support, and parental mental illness. Growth curve model and group-based trajectory model were used to analyze the association between depression and early socioeconomic status while adjusting for confounders.

Result: In the growth cure analysis, the results reveal that birth weight, childhood economic hardship, school negative life events, and family support significantly influenced initial levels of depression in girls. Negative life events and parental mental illness significantly influenced development of depression in girls. However, both initial levels and development of depression were only correlated with school negative life events in boys. And in both genders four distinct developmental trajectories were identified. Among girls, the four depression trajectories were consistently low (n=709, 39%), moderate (n=891, 46.5%), chronically high (n=174, 9.5%) and decreasing (n=84, 5%). Among boys, four depression trajectories were consistently low (n=836, 48.1%), moderate (n=762, 42.8%), decreasing (n=57, 3.7%) and increasing (n=87, 5.4%). We found that girls’ trajectory classes were associated with childhood economic hardship, negative life events, and family and peer social support, whereas boys’ trajectory classes were associated with father education, school negative events and peer support.

Conclusion: Early socioeconomic status could contribute disparities of adolescent depression, and affect the developmental of depression trajectories. However, gender differences existed in sensitivity to different early socioeconomic status indicators, and birth weight was only correlated with initial levels of depression in girls.

致謝 ii
摘要 iii
Abstract iv
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 5
第二章 文獻探討 6
第一節 憂鬱的概念與測量 6
第二節 憂鬱的影響因素 16
第三節 憂鬱軌跡的相關研究 23
第四節 早期社經地位對未來健康的影響 28
第五節 健康與疾病發展起源說 32
第六節 早期家庭社經地位、出生體重與憂鬱的解釋機制 36
第三章 研究方法 43
第一節 研究架構 43
第二節 研究假說 44
第三節 資料來源 45
第四節 研究樣本 47
第五節 研究變項 47
第六節 資料分析 51
第四章 研究結果 53
第一節 研究樣本的基本特質 53
第二節 憂鬱量表之建構 55
第三節 憂鬱軌跡變化及其影響因素 57
第四節 憂鬱軌跡類型及其影響因素 62
第五章 討 論 67
第一節 青少年憂鬱發展趨勢與軌跡類型 67
第二節 青少年憂鬱軌跡的相關因素 71
第三節 早期社經地位對憂鬱軌跡變化的可能影響機制 75
第四節 研究限制 78
第六章 結論與建議 79
第一節 結論 79
第二節 政策意涵與未來研究建議 82
參考文獻 85
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表次
表2. 1 憂鬱的概念 109
表2. 2 憂鬱研究各學派主要理論 110
表2. 3 國內外常用青少年自述量表 111
表2. 4 生命歷程研究設計與分析概念 112
表3. 1 TEPS各波實際完訪數、完訪率、遞補率與追蹤率說明表115
表3. 2 TEPS追蹤樣本調查時間 116
表3. 3 各波調查追蹤人數 116
表3. 4 壓力源調查時間 117
表3. 5 各變項之操作型定義及資料來源 118
表4. 1 研究樣本基本特性依性別分層 121
表4. 2 研究樣本壓力源及社會支持依性別分佈 122
表4. 3 各波調查憂鬱測量題項分布 123
表4. 4 各波調查憂鬱題項因素負荷矩陣及信度分析結果 124
表4. 5 各波調查憂鬱分數相關矩陣 125
表4. 6 各波憂鬱分數與相關因素簡單迴歸分析之迴歸係數(標準誤)126
表4. 7 研究樣本憂鬱分數發展狀況 127
表4. 8女性憂鬱無條件成長模型之迴歸係數(標準誤) 128
表4. 9女性憂鬱條件成長模型之迴歸係數(標準誤) 129
表4. 10男性憂鬱無條件成長模型之迴歸係數(標準誤) 130
表4. 11 男性憂鬱條件成長模型之迴歸係數(標準誤) 131
表4. 12 早期社經地位與出生體重交互作用對憂鬱軌跡變化起始值之影響132
表4. 13 女性研究樣本憂鬱軌跡類型 133
表4. 14 女性憂鬱軌跡類型基本分佈 137
表4. 15 女性憂鬱軌跡類型與壓力源及社會支持之分佈 138
表4. 16 男性憂鬱軌跡類型基本分佈 139
表4. 17 男性憂鬱軌跡類型與壓力源及社會支持之分佈 140
表4. 18 女性憂鬱軌跡類型之多元邏輯斯迴歸分析 (持續中等比持續低)

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