Measuring and understanding emotional attachment in human–AI relationships

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Authors: Nuo Cheng, Ruifeng Yu
Cited by: 7
References: 94

Abstract

Users increasingly develop emotional connections with AI chatbots that extend beyond utilitarian functions, yet no validated multidimensional scale exists to measure these bonds. This research developed and validated the AI Attachment Scale (AIAS) through two studies: scale development (Study 1) followed by validation and framework testing (Study 2). Study 1 employed exploratory factor analysis (N = 531) to establish a 15-item scale capturing three dimensions: Emotional Support, Separation Distress, and Secure Base. Study 2 used confirmatory factor analysis (N = 375) to validate the scale structure and propose a theoretical framework linking individual differences to AI attachment and behavioural outcomes. Results showed anthropomorphism as the strongest predictor of AI attachment orientations. Attachment anxiety positively predicted AI attachment (β = 0.44), while attachment avoidance negatively predicted it (β = -0.53). AI attachment significantly predicted behavioural intentions (β = 0.50). This research provides a validated measure of human-AI attachment and practical guidance for emotional design in AI chatbots.

Fields of Study & Subjects

AI in Service Interactions Ethics and Social Impacts of AI Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Ergonomics
Publisher
Informa UK Limited
Pages
1–20
Publication date
2 February 2026
Language
EN