Measuring Large Language Models Dependency: Validating the Arabic Version of the LLM-D12 Scale

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Main Authors: AlShakhsi, Sameha, Yankouskaya, Ala, Liebherr, Magnus, Ali, Raian
Format: Preprint
Published: 2025
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author AlShakhsi, Sameha
Yankouskaya, Ala
Liebherr, Magnus
Ali, Raian
author_facet AlShakhsi, Sameha
Yankouskaya, Ala
Liebherr, Magnus
Ali, Raian
contents 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 Dependency). External validation revealed that Instrumental Dependency was positively associated with AI acceptance and internet addiction, while Relationship Dependency was linked to lower need for cognition and greater trustworthiness of LLM, demonstrating sensitivity of this instrument to different use and personal factors. These findings confirm that Arabic LLM-D12 is a psychometrically sound, culturally appropriate instrument, offering a necessary tool for research, education, and policy concerning AI and LLMs engagement in Arab contexts.
format Preprint
id arxiv_https___arxiv_org_abs_2508_17063
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Measuring Large Language Models Dependency: Validating the Arabic Version of the LLM-D12 Scale
AlShakhsi, Sameha
Yankouskaya, Ala
Liebherr, Magnus
Ali, Raian
Human-Computer Interaction
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 Dependency). External validation revealed that Instrumental Dependency was positively associated with AI acceptance and internet addiction, while Relationship Dependency was linked to lower need for cognition and greater trustworthiness of LLM, demonstrating sensitivity of this instrument to different use and personal factors. These findings confirm that Arabic LLM-D12 is a psychometrically sound, culturally appropriate instrument, offering a necessary tool for research, education, and policy concerning AI and LLMs engagement in Arab contexts.
title Measuring Large Language Models Dependency: Validating the Arabic Version of the LLM-D12 Scale
topic Human-Computer Interaction
url https://arxiv.org/abs/2508.17063