The effects of response time on older and young adults’ interaction experience with Chatbot

聊天机器人 心理学 人际关系 发展心理学 年轻人 即时性 人际交往 偏爱 社会关系 即时消息 社会化 社会心理学 经济 人工智能 微观经济学 哲学 认识论 计算机科学 计算机网络
作者
Ya‐Ling Wang,Chi-Wen Lo
出处
期刊:BMC Psychology [BioMed Central]
卷期号:13 (1): 150-150 被引量:6
标识
DOI:10.1186/s40359-025-02459-9
摘要

Abstract Background Chatbots, such as Siri, Alexa, and ChatGPT, are increasingly integrated into various domains, including customer service and virtual companionship, transforming human-computer interactions. However, there remains limited understanding of how response time—a critical social cue—affects user experience across different age groups, particularly in virtual companionship contexts. This gap is especially relevant in aging societies where older adults’ emotional and relational needs require tailored technological solutions. Methods A 2 × 2 between-subjects experiment was conducted with 160 Taiwanese participants from two age groups: young adults (18–23 years old) and older adults (56–81 years old). Participants interacted with chatbots under two conditions: instant responses (approximately 3 s) and delayed responses (10–60 s). User experience was measured using social presence (SP), service encounter satisfaction (SAT), and intention of use (IOU) through validated questionnaires. Two-way ANOVA was employed to analyze the main and interaction effects of response time and age group. Results The findings revealed a significant interaction effect between response time and age group. While younger adults preferred instant responses, older adults showed a preference for delayed responses. Specifically: (1) Instant responses led to higher satisfaction and engagement for younger adults, who value efficiency and immediacy. (2) Delayed responses facilitated cognitive comfort and enhanced relational value for older adults, emphasizing the importance of conversational pacing. Conclusions This study highlights the critical role of response time in chatbot design, revealing how age-specific preferences influence user satisfaction in virtual companionship scenarios. Findings underscore the need for adaptive chatbot designs that align with cognitive and emotional needs across age groups. Broader implications emphasize the importance of balancing digitally assisted companionship with the risks of dehumanization. Future research should explore long-term interaction effects and cultural differences to enhance chatbot inclusivity and effectiveness.
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