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

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 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.

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Publication Details

Journal
Arabian Journal for Science and Engineering
Published
2026-07-24
DOI
https://doi.org/10.1007/s13369-026-11386-9
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Sameha Ahmed Ali Alshakhsi, Raian Ali, Ala Yankouskaya, Magnus Liebherr
Arabian Journal for Science and Engineering
Artificial Intelligence in Healthcare and Education
article

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

Sameha Ahmed Ali Alshakhsi, Raian Ali, Ala Yankouskaya, Magnus Liebherr
article en

Abstract

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 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.

Arabian Journal for Science and Engineering
Hamad bin Khalifa University (QA), University of Duisburg-Essen (DE), Bournemouth University (GB)
Qatar Foundation, Hamad Bin Khalifa University, Fonds National de la Recherche Luxembourg, Qatar National Research Fund, Qatar National Library
Quality Education
Openalex Percentile: Top 12%
Artificial Intelligence in Healthcare and Education
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