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通过审视认知信任、人格和亲密关系恐惧的作用预测心理健康治疗中与对话代理的互动:基于网络的横断面调查研究

Predicting Engagement With Conversational Agents in Mental Health Therapy by Examining the Role of Epistemic Trust, Personality, and Fear of Intimacy: Cross-Sectional Web-Based Survey Study.

作者信息

Guglielmucci Fanny, Di Basilio Daniela

机构信息

Department of Philosophy, Communication and Performing Arts, Roma Tre University, Rome, Italy.

Faculty of Health and Medicine, Division of Health Research, Lancaster University, Sir John Fisher Drive, Lancaster, LA1 4AT, United Kingdom, 44 07312255301.

出版信息

JMIR Hum Factors. 2025 Jul 30;12:e70698. doi: 10.2196/70698.

Abstract

BACKGROUND

The use of conversational agents (CAs) in mental health therapy is gaining traction due to their accessibility, anonymity, and nonjudgmental nature. However, understanding the psychological factors driving preferences for CA-based therapy remains critical to ensure ethical and effective application. Variables such as epistemic trust, attachment styles, personality traits, and fear of intimacy appear central in shaping attitudes toward these artificial intelligence (AI)-driven interventions.

OBJECTIVE

This study aimed to investigate the role of epistemic trust, attachment styles, personality traits, and fear of intimacy in influencing individuals' willingness to engage with CA-based therapy.

METHODS

An online survey was administered to 876 psychology students, yielding 736 responses (84.01% response rate). Variables measured included epistemic trust, attachment styles, personality traits, and fear of intimacy. A 5-point ordinal scale assessed willingness to engage in CA-based therapy. The data were analyzed using ordinal logistic regression models, including proportional odds models (POMs), nonproportional odds models (NPOMs), and partial proportional odds models (PPOMs), with residual deviance used to compare model fit.

RESULTS

The PPOM provided the best model fit (residual deviance=3530.47), outperforming both the NPOM (deviance=6244.01) and the POM based on Brant test results indicating violations of the proportional odds assumption (χ²105=187.8; P<.001). In the final model (n=735), epistemic trust significantly increased willingness to engage in CA-based therapy across all ordinal thresholds (odds ratio [OR] 1.75, 95% CI 1.50, 2.03; P<.001). Fear of sharing demonstrated a nonuniform effect, with stronger associations at higher levels of willingness (OR 1.086; P=.001). Among personality traits, detachment negatively predicted CA preference (OR 0.95; P=.001), while psychoticism showed a positive association (OR 1.12; P=.003). Being single emerged as a strong predictor of preference for CA-based therapy (OR 3.717; P<.001). Attachment styles showed more nuanced effects. While dismissing and fearful-avoidant individuals were descriptively less inclined to engage in traditional human-based therapy, this association was nonsignificant in the case of fearful-avoidant attachment (P=.34) and should therefore be interpreted cautiously.

CONCLUSIONS

Epistemic trust and fear of intimacy emerged as pivotal factors influencing preferences for CA-based therapy, underscoring the role of interpersonal dynamics and emotional vulnerabilities. The findings suggest that individuals with avoidant attachment styles or maladaptive personality traits are more inclined toward AI-mediated interventions, driven by reduced fear of judgment and increased perceived safety. The relative homogeneity of the sample considered-particularly in terms of age, education level, and cultural exposure-limits the generalizability of these findings to broader or more diverse populations. Nonetheless, these insights highlight the need for ethical considerations and personalized approaches in deploying CA-based mental health tools to balance user reliance with human-centric therapeutic values.

摘要

背景

对话代理(CA)在心理健康治疗中的应用因其可及性、匿名性和无评判性而越来越受到关注。然而,了解驱动对基于CA的治疗偏好的心理因素对于确保道德和有效的应用仍然至关重要。诸如认知信任、依恋风格、人格特质和对亲密关系的恐惧等变量似乎在塑造对这些人工智能(AI)驱动的干预措施的态度方面起着核心作用。

目的

本研究旨在调查认知信任、依恋风格、人格特质和对亲密关系的恐惧在影响个体参与基于CA的治疗意愿方面的作用。

方法

对876名心理学专业学生进行了一项在线调查,共获得736份回复(回复率84.01%)。测量的变量包括认知信任、依恋风格、人格特质和对亲密关系的恐惧。使用5点有序量表评估参与基于CA的治疗的意愿。使用有序逻辑回归模型分析数据,包括比例优势模型(POM)、非比例优势模型(NPOM)和部分比例优势模型(PPOM),并使用残差偏差来比较模型拟合度。

结果

PPOM提供了最佳的模型拟合(残差偏差=3530.47),优于NPOM(偏差=6244.01)和基于布兰特检验结果表明违反比例优势假设的POM(χ²105=187.8;P<.001)。在最终模型(n=735)中,认知信任在所有有序阈值上均显著增加了参与基于CA的治疗的意愿(优势比[OR]1.75,95%置信区间1.50,2.03;P<.001)。对分享的恐惧表现出不一致的影响,在较高意愿水平上有更强的关联(OR 1.086;P=.001)。在人格特质中,超脱对CA偏好有负向预测作用(OR 0.95;P=.001),而精神质则表现出正向关联(OR 1.12;P=.003)。单身成为基于CA的治疗偏好的一个强有力预测因素(OR 3.717;P<.001)。依恋风格的影响更为细微。虽然轻视型和恐惧回避型个体在描述上不太倾向于参与传统的基于人的治疗,但这种关联在恐惧回避型依恋的情况下并不显著(P=.34),因此应谨慎解释。

结论

认知信任和对亲密关系的恐惧是影响基于CA的治疗偏好的关键因素,凸显了人际动态和情感脆弱性的作用。研究结果表明,具有回避型依恋风格或适应不良人格特质的个体更倾向于人工智能介导的干预措施,这是由于对评判的恐惧降低和感知到的安全性增加所致。所考虑样本的相对同质性——特别是在年龄、教育水平和文化接触方面——限制了这些发现对更广泛或更多样化人群的普遍性。尽管如此,这些见解强调了在部署基于CA的心理健康工具时进行道德考量和个性化方法的必要性,以平衡用户的依赖与以人为主的治疗价值观。

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