Measuring Large Language Models Dependency: Validating the Arabic Version of the LLM-D12 Scale
Sameha AlShakhsi, Ala Yankouskaya, Magnus Liebherr, Raian Ali

TL;DR
This study validates the Arabic version of the LLM-D12 scale, a reliable tool for assessing dependency on large language models among Arabic speakers, facilitating research and policy development in this context.
Contribution
It is the first to culturally validate the LLM-D12 scale in Arabic, confirming its structure, reliability, and sensitivity to use and personal factors.
Findings
The Arabic LLM-D12 has a confirmed 2-factor structure.
The scale shows high internal reliability (Cronbach's alpha > 0.85).
Instrumental dependency correlates with AI acceptance and internet addiction.
Abstract
There is an urgent need for reliable, culturally validated instruments to assess psychological responses to AI in general and large language models (LLMs). This need is global issue, but it is especially urgent among Arabic-speaking populations, where AI and LLMs adoption is accelerating, yet psychometric tools remain limited. This study presents the first validation of the LLM-D12, a dual-dimensional scale assessing Instrumental and Relationship Dependency on LLMs, in an Arab sample. A total of 250 Arab participants completed the Arabic version of the LLM-D12. Confirmatory Factor Analysis confirms the original 2-factor structure of LLM-D12 with all items showing good loading of corresponding Instrumental and Relationship Dependency. The scale showed good to excellent internal reliability (Cronbach alpha is 0.90 for Total, 0.85 for Instrumental Dependency, and 0.90 for Relationship…
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