Pathways from AI Literacy to Sustained Engagement with AI-Powered Cognitive Behavioural Therapy: A Structural Equation Model with Moderated Mediation in a National UK Sample

结构方程建模 调解 心理学 调解 联盟 适度 心理健康 临床心理学 心理健康素养 读写能力 焦虑 认知 体验式学习 发展心理学 样品(材料) 自我效能感 柱头(植物学) 社会心理学 认知重构 数字素养 心理干预 脱离理论 计算机辅助网络访谈 计划行为理论 健康素养 技术接受模型 多元方差分析 应用心理学 分层抽样
作者
James Whitfield,Amaevia Goh
出处
期刊:medRxiv
标识
DOI:10.64898/2026.03.24.26349184
摘要

ABSTRACT Background AI-powered cognitive behavioural therapy (AI-CBT) tools hold significant promise for addressing the global mental health treatment gap, yet sustained user engagement remains critically low. While patient attitudes and experiential factors have been qualitatively documented, the psychological mechanisms through which AI literacy translates into long-term engagement remain poorly understood. Existing systematic evidence highlights trust, perceived therapeutic alliance, and stigma as salient themes, but no large-scale quantitative study has modelled these as a mediated pathway. Objective This study aimed to (1) examine whether trust in AI systems and perceived therapeutic alliance mediate the relationship between AI literacy and sustained AI-CBT engagement, and (2) determine whether mental health stigma moderates these mediated pathways. Methods A cross-sectional national online survey was conducted in the United Kingdom (N = 1,247). Eligible adults (18+) with a history of anxiety or depression who had used an AI-CBT tool in the preceding 12 months were recruited via stratified random sampling. Structural equation modelling (SEM) with moderated mediation was conducted in R (lavaan 0.6-17). Moderated mediation was evaluated using the PROCESS macro framework adapted for SEM, with 5,000 bootstrap replications for bias-corrected confidence intervals. Model fit was assessed using CFI, TLI, RMSEA, and SRMR indices. Results The final SEM demonstrated excellent fit (CFI = 0.967, TLI = 0.959, RMSEA = 0.043 [90% CI: 0.036–0.051], SRMR = 0.052). AI literacy exerted a significant indirect effect on sustained engagement through trust in AI (β = 0.213, SE = 0.031, p < .001) and perceived therapeutic alliance (β = 0.187, SE = 0.028, p < .001). Mental health stigma significantly moderated the trust→engagement pathway (ΔR 2 = 0.042, p = .003), with the indirect effect being stronger among individuals with lower stigma scores. The total indirect effect accounted for 58.4% of the total effect of AI literacy on engagement. Conclusions AI literacy promotes sustained AI-CBT engagement primarily through its effects on trust and perceived therapeutic alliance, pathways that are attenuated by mental health stigma. These findings underscore the need for stigma-reduction interventions and AI literacy programmes as implementation strategies. Findings have direct implications for the design and deployment of AI-CBT tools across UK NHS digital mental health services.

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