The influence of AI literacy on fear of negative evaluation among students and researchers: a multisite cross-sectional study

BACKGROUND: Generative artificial intelligence (AI) tools are increasingly used in academia to retrieve information, draft manuscripts, and support learning activities. Despite growing research on AI use and literacy in academia, few studies have examined negative perceptions of such use. This study aimed to assess the relationship between AI literacy and fear of negative evaluation among students and researchers in Saudi Arabia. METHODS: A cross-sectional, correlational, descriptive study was conducted among researchers and students from private and public institutions. Data were collected from August to October 2025 using the Meta Artificial Intelligence Literacy Scale and the Brief Fear of Negative Evaluation Scale. Data were analyzed using an independent t-test and multiple linear regression. RESULTS: Among the 154 participants who responded to the questionnaire, moderate AI literacy and low fear of negative evaluation were reported, with strongest agreement on evaluating AI's advantages and disadvantages and on solving complex tasks. However, researchers reported significantly stronger concerns than students across multiple items, particularly on items related to being judged when using AI. Age and AI self-efficacy were significant positive predictors of fear of negative evaluation, indicating that older participants and those with higher AI confidence reported slightly higher levels of concern. CONCLUSIONS: This study highlights the need for structured AI education, clear guidelines, and supportive environments to ensure responsible and confident use. Despite the low overall fear of negative evaluation, researchers' concerns about using AI highlight the importance of supportive environments and clear guidelines. Stronger concern among older and more confident participants indicates the need to reinforce ethical practice and accountability to promote confident, responsible engagement with AI.

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Publication Details

Journal
BMC Medical Education
Published
2026-06-16
DOI
https://doi.org/10.1186/s12909-026-09721-7
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

The influence of AI literacy on fear of negative evaluation among students and researchers: a multisite cross-sectional study

Adnan Innab, Alwah Alkathiri, Latifah Alenazi, Fahad Zeed Alanezi
BMC Medical Education
Artificial Intelligence in Healthcare and Education
article

The influence of AI literacy on fear of negative evaluation among students and researchers: a multisite cross-sectional study

Adnan Innab, Alwah Alkathiri, Latifah Alenazi, Fahad Zeed Alanezi
article en

Abstract

BACKGROUND: Generative artificial intelligence (AI) tools are increasingly used in academia to retrieve information, draft manuscripts, and support learning activities. Despite growing research on AI use and literacy in academia, few studies have examined negative perceptions of such use. This study aimed to assess the relationship between AI literacy and fear of negative evaluation among students and researchers in Saudi Arabia. METHODS: A cross-sectional, correlational, descriptive study was conducted among researchers and students from private and public institutions. Data were collected from August to October 2025 using the Meta Artificial Intelligence Literacy Scale and the Brief Fear of Negative Evaluation Scale. Data were analyzed using an independent t-test and multiple linear regression. RESULTS: Among the 154 participants who responded to the questionnaire, moderate AI literacy and low fear of negative evaluation were reported, with strongest agreement on evaluating AI's advantages and disadvantages and on solving complex tasks. However, researchers reported significantly stronger concerns than students across multiple items, particularly on items related to being judged when using AI. Age and AI self-efficacy were significant positive predictors of fear of negative evaluation, indicating that older participants and those with higher AI confidence reported slightly higher levels of concern. CONCLUSIONS: This study highlights the need for structured AI education, clear guidelines, and supportive environments to ensure responsible and confident use. Despite the low overall fear of negative evaluation, researchers' concerns about using AI highlight the importance of supportive environments and clear guidelines. Stronger concern among older and more confident participants indicates the need to reinforce ethical practice and accountability to promote confident, responsible engagement with AI.

BMC Medical Education
Alfaisal University (SA), King Saud Medical City (SA), Sulaiman Al Rajhi Colleges (SA), King Saud University (SA)
Quality Education
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
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