Wu Xiaoli, Liew Kongmeng, Dorahy Martin J
School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand.
JMIR AI. 2025 Apr 22;4:e68960. doi: 10.2196/68960.
Conversational artificial intelligence (CAI) is increasingly used in various counseling settings to deliver psychotherapy, provide psychoeducational content, and offer support like companionship or emotional aid. Research has shown that CAI has the potential to effectively address mental health issues when its associated risks are handled with great caution. It can provide mental health support to a wider population than conventional face-to-face therapy, and at a faster response rate and more affordable cost. Despite CAI's many advantages in mental health support, potential users may differ in their willingness to adopt and engage with CAI to support their own mental health.
This study focused specifically on dispositional trust in AI and attachment styles, and examined how they are associated with individuals' intentions to adopt CAI for mental health support.
A cross-sectional survey of 239 American adults was conducted. Participants were first assessed on their attachment style, then presented with a vignette about CAI use, after which their dispositional trust and subsequent adoption intentions toward CAI counseling were surveyed. Participants had not previously used CAI for digital counseling for mental health support.
Dispositional trust in artificial intelligence emerged as a critical predictor of CAI adoption intentions (P<.001), while attachment anxiety (P=.04), rather than avoidance (P=.09), was found to be positively associated with the intention to adopt CAI counseling after controlling for age and gender.
These findings indicated higher dispositional trust might lead to stronger adoption intention, and higher attachment anxiety might also be associated with greater CAI counseling adoption. Further research into users' attachment styles and dispositional trust is needed to understand individual differences in CAI counseling adoption for enhancing the safety and effectiveness of CAI-driven counseling services and tailoring interventions.
Open Science Framework; https://osf.io/c2xqd.
对话式人工智能（CAI）越来越多地应用于各种咨询场景，以提供心理治疗、提供心理教育内容，并提供陪伴或情感支持等帮助。研究表明，当谨慎处理其相关风险时，CAI有潜力有效解决心理健康问题。与传统的面对面治疗相比，它可以为更广泛的人群提供心理健康支持，且响应速度更快、成本更低。尽管CAI在心理健康支持方面有诸多优势，但潜在用户在采用和使用CAI来支持自身心理健康的意愿上可能存在差异。
本研究特别关注对人工智能的性格信任和依恋风格，并研究它们如何与个人采用CAI进行心理健康支持的意图相关联。
对239名美国成年人进行了横断面调查。首先评估参与者的依恋风格，然后向他们展示一个关于使用CAI的小插曲，之后调查他们对CAI咨询的性格信任和随后的采用意图。参与者此前未使用过CAI进行心理健康支持的数字咨询。
对人工智能的性格信任成为CAI采用意图的关键预测因素（P<0.001），而在控制年龄和性别后，发现依恋焦虑（P=0.04）而非回避（P=0.09）与采用CAI咨询的意图呈正相关。
这些发现表明，更高的性格信任可能导致更强的采用意愿，更高的依恋焦虑也可能与更多采用CAI咨询相关。需要进一步研究用户的依恋风格和性格信任，以了解CAI咨询采用中的个体差异，从而提高CAI驱动的咨询服务的安全性和有效性，并量身定制干预措施。
开放科学框架；https://osf.io/c2xqd。
