Abstract
BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. TRIAL REGISTRATION: Open Science Framework; https://osf.io/c2xqd.