A Three-Layered Framework and Measurement Toolkit for Understanding Emotional and Relational Engagement with AI

As generative artificial intelligence (AI) becomes increasingly embedded in emerging adults’ academic, work, and social lives, interactions with AI increasingly involve emotional disclosure and relational engagement beyond instrumental use. However, empirical research has been constrained by the lack of validated instruments capturing behavioral, cognitive, and emotional aspects of human-AI engagement. This study developed and validated a three-scale measurement toolkit using a regionally representative sample of college students from 26 universities in Shanghai (N = 1406, Mage = 18.98, SD = 1.25, 59.7% female). The toolkit includes a Multidimensional AI Use Scale, a Perceived Uniqueness of AI Interaction Scale, and an AI Emotional Attachment Scale. Split-sample exploratory and confirmatory factor analyses supported clear factor structures, satisfactory reliability, and evidence of discriminant and criterion-related validity. Together, these instruments provide a psychometrically sound framework for examining behavioral use, cognitive perceptions, and affective attachment in human-AI engagement among emerging adults.

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Publication Details

Journal
International Journal of Human-Computer Interaction
Published
2026-09-07
DOI
https://doi.org/10.1080/10447318.2026.2725999
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

A Three-Layered Framework and Measurement Toolkit for Understanding Emotional and Relational Engagement with AI

Junsheng Liu, Huiguang Ren, Chuqi Chen, Fangfang Tian
International Journal of Human-Computer Interaction
Ethics and Social Impacts of AI
article

A Three-Layered Framework and Measurement Toolkit for Understanding Emotional and Relational Engagement with AI

Junsheng Liu, Huiguang Ren, Chuqi Chen, Fangfang Tian
article en

Abstract

As generative artificial intelligence (AI) becomes increasingly embedded in emerging adults’ academic, work, and social lives, interactions with AI increasingly involve emotional disclosure and relational engagement beyond instrumental use. However, empirical research has been constrained by the lack of validated instruments capturing behavioral, cognitive, and emotional aspects of human-AI engagement. This study developed and validated a three-scale measurement toolkit using a regionally representative sample of college students from 26 universities in Shanghai (N = 1406, Mage = 18.98, SD = 1.25, 59.7% female). The toolkit includes a Multidimensional AI Use Scale, a Perceived Uniqueness of AI Interaction Scale, and an AI Emotional Attachment Scale. Split-sample exploratory and confirmatory factor analyses supported clear factor structures, satisfactory reliability, and evidence of discriminant and criterion-related validity. Together, these instruments provide a psychometrically sound framework for examining behavioral use, cognitive perceptions, and affective attachment in human-AI engagement among emerging adults.

International Journal of Human-Computer Interaction
East China Normal University (CN)
Reduced inequalities
Openalex Percentile: Top 85%
Ethics and Social Impacts of AI
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