发表机构
Beijing Normal University; The Ohio State University（北京师范大学; 俄亥俄州立大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过访谈和六个月的追踪调查，识别出人机情感互动影响感知的四种剖面，发现风险驱动型用户心理脆弱性更高，但总体心理危害有限且具选择性，需个体化保障。
AI 中文摘要
关系型人工智能日益成为人类的情感庇护所，其影响是混合的。以往研究侧重于积极或消极影响中的某一方面，尚不清楚这些影响如何在个体内部配置以及与心理功能的关系。为弥补这些空白，本研究采用顺序混合方法设计。研究1访谈了52名与AI有情感纽带的用户，识别出四个积极影响领域（情绪缓解、孤独缓解、人际功能增强和个人成长）和四个消极影响领域（虚实边界模糊、社会替代、认知-情绪强化和过度使用）。研究2对673名中国AI用户进行了为期六个月的追踪，识别出受关系型AI使用影响不同的四类个体剖面：最小影响型、收益驱动型、混合影响型和风险驱动型。混合影响型和风险驱动型用户在人与AI情感联结方面均较高，但表现出风险驱动影响的用户具有更大的脆弱性，表现为更高的人际需求挫败感和情绪调节困难、更多的抑郁和焦虑症状，以及更低的自尊和幸福感。收益驱动型和混合影响型用户表现出更有利的心理功能。在控制基线功能和相关协变量后，第一波剖面未能预测第二波六个指标中的五个；只有混合影响型用户报告的幸福感高于最小影响型用户。总体而言，与关系型AI参与相关的潜在心理危害似乎有限且具有选择性。这些发现将关系型AI描绘为一个异质性的社会情感环境，可能部分反映用户的当前状态和特质，需要个体化、适应性的保障措施。
英文摘要
Relational AI increasingly serves as an emotional shelter for humans, and its impact is mixed. Prior research has focused on either positive or negative impacts, leaving unclear how they are configured within individuals and relate to psychological functioning. To address these gaps, this study used a sequential mixed-methods design. Study 1 interviewed 52 users with emotional ties to AI and identified four positive impact domains (emotional relief, loneliness alleviation, enhanced interpersonal functioning, and personal growth) and four negative impact domains (virtual-real boundary blur, social replacement, cognitive-emotional reinforcement, and excessive use). Study 2 followed 673 Chinese AI users for six months and identified four profiles of individuals differently impacted by relational AI use: minimal impact, benefit-driven impact, mixed impact, and risk-driven impact. Users in the mixed impact and risk-driven impact profiles were both high in human-AI affective bonding, but those showing risk-driven impact had greater vulnerability, indicated by higher interpersonal need frustration and emotion-regulation difficulties, more depressive and anxiety symptoms, and lower self-esteem and flourishing. Users in the benefit-driven and mixed impact profiles showed more favorable psychological functioning. After controlling for baseline functioning and relevant covariates, Wave 1 profiles did not predict five of the six Wave 2 indicators; only users in the mixed impact profile reported higher flourishing than those in the minimal impact profile. Overall, potential psychological harms associated with relational AI engagement appeared limited and selective. These findings portray relational AI as a heterogeneous socio-emotional context that may partly mirror users' states and traits, warranting individualized, adaptive safeguards.
