Large Language Models (LLMs) and AI chatbots are increasingly used for emotional and mental health support due to their low cost, immediacy, and accessibility. However, when safety guardrails are triggered, conversations may be abruptly terminated, introducing a distinct form of emotional disruption that can exacerbate distress and elevate risk among already vulnerable users. As this phenomenon gains attention, this viewpoint introduces Abrupt Refusal Secondary Harm (ARSH) as a conceptual framework to describe the psychological impacts of sudden conversational discontinuation caused by AI safety protocols. Drawing on counseling psychology and communication science as conceptual heuristics, we argue that abrupt refusals can rupture perceived relational continuity, evoke feelings of rejection or shame, and discourage future help seeking. To mitigate these risks, we propose a design hypothesis, the Compassionate Completion Standard (CCS), a refusal protocol grounded in Human Centered Design (HCD) that maintains safety constraints while preserving relational coherence. CCS emphasizes empathetic acknowledgment, transparent boundary articulation, graded conversational transition, and guided redirection, replacing abrupt disengagement with psychologically attuned closure. By integrating awareness of ARSH into AI safety design, developers and policymakers can reduce preventable iatrogenic harm and advance a more psychologically informed approach to AI governance. Rather than presenting incremental empirical findings, this viewpoint contributes a timely conceptual framework, articulates a testable design hypothesis, and outlines a coordinated research agenda for improving psychological safety in human AI interaction.

翻译：大型语言模型(LLMs)和AI聊天机器人因其低成本、即时性和可访问性，正日益被用于情感与心理健康支持。然而，当安全防护机制被触发时，对话可能被突然终止，从而引入一种独特的情绪干扰形式，可能加剧已处于脆弱状态用户的痛苦并提升其风险。随着这一现象受到关注，本文提出"突发拒绝次级伤害"(Abrupt Refusal Secondary Harm, ARSH)作为概念框架，用以描述由AI安全协议引发的突然对话中断所造成的心理影响。借鉴咨询心理学与传播学的概念启发，我们认为突发拒绝可能破坏感知的关系连续性，引发拒绝感或羞耻感，并阻碍未来的求助行为。为缓解这些风险，我们提出一种设计假设——"共情完成标准"(Compassionate Completion Standard, CCS)，这是一种基于人本设计(Human Centered Design, HCD)的拒绝协议，能在维持安全约束的同时保持关系连贯性。CCS强调共情式确认、透明的边界阐述、渐进式对话过渡以及引导性转向，以心理调适的收尾方式取代突发性脱离。通过将ARSH认知融入AI安全设计，开发者和政策制定者可以减少可预防的医源性伤害，并推进更具心理科学依据的AI治理路径。本文并非呈现渐进式的实证发现，而是贡献了一个及时的概念框架，阐明了一个可检验的设计假设，并勾勒出改善人机交互心理安全的协同研究议程。