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| Title: | 探討生成式 AI 聊天機器人對睡眠拖延行為改善的影響
Exploring the Impact of Generative AI Chatbot on Improving Bedtime Procrastination Behavior |
| Authors: | 陳玟諭
Chen, Wen-Yu |
| Contributors: | 鄭霈絨
廖峻鋒
Cheng, Pei-Jung
Liao, Chun-Feng
陳玟諭
Chen, Wen-Yu |
| Keywords: | 生成式AI
睡眠拖延行為
BED-PRO 對話架構
聊天機器人
報復性熬夜
Generative AI
Bedtime procrastination behavior
BED-PRO
Chatbot
Revenge bedtime procrastination |
| Date: | 2025 |
| Issue Date: | 2025-09-01 16:51:34 (UTC+8) |
| Abstract: | 睡眠拖延(Bedtime Procrastination)為一種常見於年輕族群的行為問題，其核心成 因多與自我調節困難、報復性熬夜、時間管理不足及情緒壓力相關，長期可能導致睡眠 品質下降、白天清醒感降低與心理健康風險上升。隨著生成式人工智慧(Generative AI) 對話技術的發展，類的聊天機器人具備即時對話、情緒支持與個別化建議的特性受到 重視。因，本研究採用生成式 AI 聊天機器人(Linebot)結合 BED-PRO 的對話架構， 探究其改善睡眠拖延行為的成效，以及其對於睡眠拖延者之自我覺察、情緒調控與時間 管理能力的影響。本研究針對有睡眠拖延傾向的大專院校學生，進行為期三週的睡眠拖 延改善實驗，研究資料包含睡眠日記與每週的睡眠回顧對話。
研究結果顯示，參與者於實驗後睡眠拖延量表(BPS)與睡眠拖延時間(BPD)皆 顯著下降，顯示對話機制具行為改變效果。質性資料亦指出，Linebot 有助於睡眠拖 延者辨識報復性熬夜與任務逃避等拖延成因，並培養自我調節與反思能力。多數睡眠拖 延者肯定 Linebot 溫柔、不批判的對話風格與穩定互動，視其為情緒支持與睡眠儀式建 立的重要助力。本研究主要貢獻在於結合生成式 AI 技術與 BED-PRO 對話架構，以實 證結果展現出提升睡眠自我調節與行為改變的潛力，將能提供未來在行為改善或養成工 具之互動形式與個人化設計方面的具體參考。
Bedtime procrastination is a widespread issue among young adults, often linked to poor self-regulation, revenge bedtime procrastination, and time management difficulties. These factors negatively affect sleep quality and mental well-being. With advances in generative AI, behavior-change chatbots capable of providing real-time interaction and personalized support have gained significant attention.
This study evaluated the effectiveness of a generative AI chatbot (Linebot), designed with the BED-PRO framework, in reducing bedtime procrastination and improving users’ self- reflection, emotional regulation, and time management. A three-week intervention was conducted among university students with a high tendency toward bedtime procrastination. The intervention included daily sleep diary entries and weekly reflective dialogue sessions.
Post-intervention data showed significant reductions in Bedtime Procrastination Scale (BPS) scores and Bedtime Procrastination Delay (BPD), indicating behavioral improvement. Qualitative results further revealed that Linebot helped participants recognize procrastination triggers, such as revenge bedtime procrastination and task avoidance, while encouraging self- regulation and reflection. Participants also valued the chatbot’s non-judgmental tone and consistent support in developing bedtime routines.
This study contributes by integrating generative AI with the BED-PRO framework, providing empirical support for its potential to enhance self-regulation and behavioral change related to sleep. The findings offer practical insights for designing future interactive and personalized digital tools for behavior improvement and habit formation. |
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| Description: | 碩士
國立政治大學
數位內容碩士學位學程
112462016 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0112462016 |
| Data Type: | thesis |
| Appears in Collections: | [數位內容碩士學位學程] 學位論文
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