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| Title: | 人機互動中的陪伴：LLM 聊天機器人在心理支持上的歷程分析
Companionship in Human–Computer Interaction: A Process Analysis of Psychological Support by LLM Chatbots |
| Authors: | 陳韋蓉
Rong, Chen Wei |
| Contributors: | 陳宜秀
廖峻鋒
YiSiu Chen
Chun-Feng Liao
陳韋蓉
Chen Wei Rong |
| Keywords: | 大型語言模型
心理健康支持
人工智慧
支持性溝通理論
信任自動化理論
聊天機器人
情感支持
使用者體驗
回應風格
Large Language Model
LLM
Mental Health Support
Artificial Intelligence
AI
Supportive Communication Theory
Trust in Automation
Chatbot
User Experience
Response Style |
| Date: | 2025 |
| Issue Date: | 2025-09-01 16:50:22 (UTC+8) |
| Abstract: | 本文旨在探討大型語言ế型(Large Language Model, LLM)為核心技術的聊天ỽ器人,在情緒支持與心理陪伴層面是否能展現近似輔導諮商時的支持效果。
隨著生成式人工智慧(artificial intelligence,AI)快速發展,具備自然語言處理能力的聊天ỽ器人日益被應用於心理健康領域,但其是否真能提供被理解、情感撫慰與信任建立的支持性互動,仍需深入驗證。本研究以支持性溝通理論(Supportive Communication Theory)為基礎,聚焦於聊天ỽ器人透過提示詞工程(Prompt engineering)ế擬情感支持、評價支持與資訊支持三種回應風格,是否能有效傳遞同理與關懷,進而提供情緒支持效能。本研究先進行了前導研究,邀請受過專ḋ訓練的諮商人員對聊天ỽ器人的支持回應進行評估及改進。正式研究則採用日記研究法(diary study),邀請參與者與經過前導研究驗證過的聊天ỽ器人連續互動十日,並於不同階⁓進行問卷與訪談,收集使用者感受與互動品質資料。研究結果以信任自動化理論(Trust in AutomationModel)與同理心量表架ṩ(ECSS 與 CARE)進行分析,從信任建立、回應適配、情緒感知與情感連結等面向進行評估,探究聊天ỽ器人是否能如擬人化輔助者般,承接使用者的情緒經驗與心理壓力。
研究結果透過紮根理論建ṩ出「信任建立」、「節奏調節」、「觀點轉化」三階⁓互動―程,提出「生成式 AI 心理支持互動―程ế型」,用以解釋人與生成式 AI 在情緒支持上的關係建ṩ過程。研究亦發現,同理心來自於系統記憶對話內容、主動提起過往經驗等連結,單一情緒ặ記更能引發被理解的感受,因 多數參與者仍認為 AI 難以取代真人的深層共感、經驗整合與價值理解,且部分人更多期待更具挑戰性與實用性的對話,並視之為支持一環,而非僅尋⃠陪伴與安慰性互動。本研究為 AI 諮商介面提供理論基礎與實務建議,指出未來應強化 AI 的支持性對話的設計面向。 |
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| Description: | 碩士
國立政治大學
數位內容碩士學位學程
108462008 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0108462008 |
| Data Type: | thesis |
| Appears in Collections: | [數位內容碩士學位學程] 學位論文
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