研究背景與目的：過往研究與臨床現象顯示，生氣為憂鬱症（狀）患者常經歷的負面情緒，亦常為憂鬱症患者帶來負向後果。相關理論指出各面向自尊（外顯自尊程度、內隱自尊程度、外顯自尊不穩定性、內外自尊落差）可能為憂鬱和生氣的共享因子。有鑑於過往研究大多聚焦於憂鬱或生氣程度的個體差異，且得到不一致的研究結果，本研究認為過往的研究較少去探討什麼樣的心理歷程使得憂鬱或生氣程度出現個體內變異。因此，本研究使用長期密集追蹤資料（intensive longitudinal data, ILD）配合多階層統計模型，同時探討各面向自尊是否影響憂鬱症（狀）患者的憂鬱與生氣之個人平均程度（個體間差異），以及憂鬱與生氣在短時間內偏離其個人平均值的程度（個體內變異）。其中本研究以三種情緒動態歷程──情緒惰性（emotional inertia）、壓力敏感度（stress sensitivity），以及憂鬱與生氣在短時間內的交叉延宕效果，來探究個體內變異的問題。因此本研究將先探討各面向自尊在控制前測憂鬱與特質生氣後，對後測憂鬱與生氣是否有額外的解釋力。參考四元模式（quad model），本研究藉由認知模擬（cognitive modeling）分析內隱聯結測驗（implicit association test, IAT）的資料，並以四元模式中代表自動化激發連結程度（association activation, AC）的AC參數作為內隱自尊指標，探討其心理計量特性。有了以上基礎，本研究將探討憂鬱與生氣是否各自受到情緒惰性以及壓力敏感度影響，並進一步探究各面向自尊是否影響了憂鬱與生氣的情緒惰性和壓力敏感度。最後，本研究探討憂鬱與生氣在短時間內是否相互影響，以及各面向自尊於此關係中扮演的角色。研究方法：本研究納入110位憂鬱症（狀）患者的資料進行分析。本研究於前測以紙本問卷收集參與者的背景資料，測量憂鬱、特質生氣、狀態生氣，以及外顯自尊程度，並以IAT測量參與者的內隱自尊。接著於隔天開啟日程紀錄，連續14天於晚上9點以手機簡訊傳送網路問卷連結給參與者，請參與者依照「當天的經驗」填答當天的日常壓力、憂鬱、狀態生氣與外顯自尊程度。在14天日程紀錄結束的隔天，以網路問卷測量參與者當天的憂鬱與狀態生氣程度作為後測資料。統計分析方面，本研究將藉由階層迴歸模型、潛在特質多項式歷程樹模型（Latent-trait multinomial process tree model, latent-trait MPT）、多階層一階自迴歸模型（Multilevel AR (1) model）及動態階層模型（Dynamic multilevel model）來分析資料，以回答本研究的研究問題。研究結果：於階層迴歸模型分析中，本研究發現在控制了前測的憂鬱程度後，僅有外顯自尊不穩定性能對後測憂鬱有顯著解釋力。所有面向自尊在控制了前測特質生氣後對後測狀態生氣皆無顯著預測力。於AC作為內隱自尊指標的分析中，本研究發現AC的信度與效度優於IAT效果值。多階層一階自迴歸模型的分析結果顯示，憂鬱症（狀）患者的憂鬱與生氣都具有情緒惰性，並受當天壓力程度正向影響。外顯自尊不穩定性會正向影響憂鬱的壓力敏感度，並負向影響憂鬱的情緒惰性，生氣的情緒惰性則受外顯自尊程度負向影響。於短時間內憂鬱與生氣之間的預測關係中，由動態階層模型的分析結果顯示，僅有t-1點憂鬱能正向預測t點生氣，且內隱自尊程度越高，t-1點憂鬱對t點生氣的影響越大，而t-1點生氣對t點憂鬱則沒有影響效果。憂鬱症（狀）患者在憂鬱與生氣的個人平均程度方面，外顯自尊會負向影響個人平均的憂鬱程度，而內外自尊落差則會正向影響個人平均的憂鬱程度。個人平均的生氣程度則不受任何一種面向自尊的影響。結論：外顯自尊程度越低／內外自尊落差越大，平均憂鬱程度越高，而外顯自尊不穩定性與內隱自尊程度，則是影響了憂鬱的個體內變異。由此可見，不同面向自尊對憂鬱均會有影響，只是影響到的是個體間差異與個體內變異的不同，此為本研究突破之處。狀態生氣方面，僅有壓力以及憂鬱對其有正向影響效果，各面向自尊則沒有影響力。

Background and aims: Patients with depressive disorders commonly report anger. Anger is an eruptive and turbulent emotion that often leads to negative consequences in patients with depression. The literature suggests that multiple facets of self-esteem (i.e., level of explicit self-esteem, level of implicit self-esteem, instability of explicit self-esteem, and discrepancy between explicit and implicit self-esteem) could be a common factor in depression and anger. However, these results were inconsistent. Additionally, previous studies mainly focused on between-person differences and did not explore within-person variability. Therefore, the present study analyzed intensive longitudinal data with multilevel statistical models, simultaneously exploring the influences of multiple facets of self-esteem on within-person means (between-person differences) and temporal deviations from these within-person means (within-person variability). Among the within-person variability, this study focused on three affect dynamics: emotional inertia, stress sensitivity, and the cross-lagged effect between depression and anger. This study initially examined whether multiple facets of self-esteem could predict depression/state anger in the post-test after controlling for depression/trait anger in the pre-test. Furthermore, it applied the Quad model to estimate the association activation (AC) parameter in the implicit association test (IAT) using the AC parameter as an index of implicit self-esteem. Additionally, it employed the daily diary methodology to elucidate the day-to-day relationship between depression, anger, and self-esteem. This study also examined the effects of emotional inertia and stress on depression and anger. Moreover, it investigated the impact of multiple facets of self-esteem on emotional inertia and stress sensitivity. Finally, it examined the predictive relationships between depression and anger across short time intervals and explored the role of explicit and implicit self-esteem in this predictive relationship. Methods: The study sample comprised 110 patients with depressive disorders/symptoms. In the pre-test, participants completed the IAT with a computer, filling out the measurements regarding demographic variables, depression, trait anger, state anger, and explicit self-esteem. The following day, participants received text messages every evening at 9 pm for 14 consecutive days, reminding them to complete their daily survey regarding their depression, state anger, stress, and explicit self-esteem online. On the day after the 14th day of the daily survey, participants received an online survey for the post-test regarding depression and state anger. This study analyzed the data using multiple hierarchical regression analysis, a latent-trait multinomial process tree model (latent-MPT), a multilevel autoregressive lag-1 model (multilevel AR(1) model), and a dynamic multilevel model. Results: The multiple hierarchical regression analysis results showed that after controlling for demographic variables and depression in the pre-test, only instability of self-esteem could predict depression in the post-test. None of the facets of self-esteem could predict state anger after controlling for demographic variables and trait anger in the pre-test. Compared to the IAT effect, the AC parameter showed better reliability and validity as an index of implicit self-esteem. The multilevel AR(1) model results showed that depression and anger had emotional inertia and were positively influenced by concurrent stress. Instability of Self-esteem positively affects the stress sensitivity of depression and negatively impacts the emotional inertia of depression. The dynamic multilevel model results showed that preceding depression positively predicted subsequent state anger, with no opposite effect. Notably, the higher the implicit self-esteem, the larger the impact of preceding depression on subsequent anger. The within-person mean of depression was negatively influenced by explicit self-esteem and positively influenced by the discrepancy between implicit and explicit self-esteem. None of the facets of self-esteem affected the within-person mean of anger. Conclusions: Within-person mean of depression was negatively influenced by explicit self-esteem and positively influenced by the discrepancy between implicit and explicit self-esteem. The within-person variability in depression was influenced by the instability of self-esteem and the level of implicit self-esteem. The different facets of self-esteem impacted the within-person mean and within-person variability of depression differently. Conversely, only stress and depression affected state anger, whereas none of the facets of self-esteem did.

第一章、緒論 1
第二章、文獻回顧 7
第一節、生氣與憂鬱的共享因子──容易受威脅的自尊 7
第二節、自尊與憂鬱的關係 8
第三節、自尊與生氣的關係 30
第四節、使用內隱聯結測驗測量內隱自尊的評論 37
第五節、以微觀角度檢視短時間內的憂鬱、生氣與自尊的關係 46
第六節、以日程紀錄法探索自尊、壓力與憂鬱，以及自尊、壓力與生氣的關係 53
第七節、憂鬱與生氣的關係 59
第八節、以動態階層模型探討外顯自尊、內隱自尊、憂鬱與狀態生氣的關係 68
第九節、研究問題與預測 69
第三章、研究方法 83
第一節、研究參與者 83
第二節、研究流程 83
第三節、研究工具 84
第四節、統計方法 89
第四章、研究結果 98
第一節、描述性統計與事前分析 98
第二節、研究問題一之統計結果 103
第三節、研究問題二之統計結果 105
第四節、研究問題三之研究結果 107
第五節、研究問題四之統計結果 114
第六節、研究問題五之統計結果 126
第七節、研究問題六之統計結果 128
第五章、討論 131
第一節、短時間內憂鬱對生氣的預測效果 133
第二節、微觀角度檢視憂鬱症（狀）患者的情緒惰性與壓力敏感度 138
第三節、不同面向自尊對憂鬱平均程度與個體內變異的影響 144
第四節、憂鬱症（狀）患者的生氣 147
第五節、本研究與過去理論的對話 150
第六節、使用四元模型分析內隱聯結測驗 151
第七節、本研究結果於臨床應用的意涵 153
第八節、研究限制 157
參考文獻 160
附錄一、基本資料表 195
附錄二、近期生活經驗調查表 196
附錄三、羅森堡自尊量表 198

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