Academic Stress, Self-Efficacy, and Generative AI Dependency: A Cross-Sectional Study at a Saudi University
7 affiliations
- 1Department of Clinical Neurosciences, College of Medicine, King Faisal University, Al Ahsa, 31982, Saudi Arabia
- 2Department of Psychology, University of Kashmir, Srinagar, 190006, India
- 3Riphah Institute of Clinical and Professional Psychology, Riphah International University, Gulberg Campus, Lahore, Pakistan
- 4Department of Psychology, Jamia Millia Islamia, New Delhi, 110025, India
- 5College of Medicine, King Faisal University, AlAhsa, 31982, Saudi Arabia
- 6Department of School Education, Ministry of Education, Srinagar, Jammu and Kashmir, India
- 7Division of ENT, Department of Surgery, College of Medicine, King Faisal University, Al Ahsa, 31982, Saudi Arabia
Abstract
Background: Generative artificial intelligence (GenAI) offers academic benefits but raises concerns about student dependency. Limited research has examined the psychological factors underlying GenAI dependency among university students.
Aim: This study examined how academic self-efficacy and academic stress relate to GenAI dependency, testing performance expectancy as a mediator and academic self-efficacy as a moderator of the stress–GenAI dependency relationship.
Methods: This cross-sectional study surveyed 305 undergraduate students recruited through convenience sampling from a public university in the Eastern Province of Saudi Arabia between March and May 2026. Participants completed an Arabic measures of GenAI dependency, academic self-efficacy, academic stress, and performance expectancy. Direct, mediating, and moderating pathways were tested with partial least squares structural equation modeling (PLS-SEM), using 5,000 bootstrap resamples and a supplementary robustness check controlling for demographic covariates.
Results: Academic self-efficacy was negatively associated with GenAI dependency (β = −0.245, p <0.001) and positively associated with performance expectancy (β = 0.237, p <0.001). Academic stress was positively associated with both performance expectancy (β = 0.315, p <0.001) and GenAI dependency (β = 0.287, p <0.001). Performance expectancy was positively associated with GenAI dependency (β = 0.411, p <0.001) and showed statistically significant indirect associations of academic self-efficacy (β = 0.098, p <0.001) and academic stress (β = 0.130, p <0.001) with GenAI dependency. Academic self-efficacy significantly moderated the relationship between academic stress and GenAI dependency (β = 0.102, p =0.010, 95% CI (0.024, 0.179); contrary to the hypothesized buffering effect, this positive association became stronger at higher levels of self-efficacy. The model explained 36.3% of GenAI dependency and 13.8% of performance expectancy variance.
Conclusion: GenAI dependency was associated with academic stress and academic self-efficacy, while performance expectancy showing significant indirect associations. Self-efficacy reduced GenAI dependency directly but amplified the stress-dependency relationship. These results support encouraging balanced GenAI use, managing academic stress, and calibrating students’ expectations of GenAI.
Related
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- AI Dependency, Academic Self-Efficacy, and Depressive Symptoms Among Medical Students: A Structural Equation Modeling Study in Saudi Arabia
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- Self-Perceived Knowledge, Self-Efficacy, and Reported Integration of Generative Artificial Intelligence Among University Faculty: An Exploratory Profile Analysis
- Generative artificial intelligence literacy profiles differ in academic self-efficacy and subjective well-being among adolescents.
BibTeX
@article{lone2026academic,
title = {{Academic Stress, Self-Efficacy, and Generative AI Dependency: A Cross-Sectional Study at a Saudi University}},
author = {Ayoob Lone and Imtiyaz Ahmad Dar and Arooj Arshad and Naved Iqbal and Mohammad Abdullah Alnoaim and Hosam Hussain Alkishi and Khalid Bandar Alnaim and Abdulaziz Abdullah Albanyan and Abdullah Abdulbaqi Aljadaan and Maryam Jan and Ibrahim K Al jabr},
journal = {Psychology Research and Behavior Management},
year = {2026},
month = oct,
doi = {10.2147/prbm.s656511},
url = {https://doi.org/10.2147/prbm.s656511},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Academic Stress, Self-Efficacy, and Generative AI Dependency: A Cross-Sectional Study at a Saudi University
AU - Ayoob Lone
AU - Imtiyaz Ahmad Dar
AU - Arooj Arshad
AU - Naved Iqbal
AU - Mohammad Abdullah Alnoaim
AU - Hosam Hussain Alkishi
AU - Khalid Bandar Alnaim
AU - Abdulaziz Abdullah Albanyan
AU - Abdullah Abdulbaqi Aljadaan
AU - Maryam Jan
AU - Ibrahim K Al jabr
PY - 2026
DA - 2026/10/30
JO - Psychology Research and Behavior Management
DO - 10.2147/prbm.s656511
UR - https://doi.org/10.2147/prbm.s656511
AB - Background: Generative artificial intelligence (GenAI) offers academic benefits but raises concerns about student dependency. Limited research has examined the psychological factors underlying GenAI dependency among university students. Aim: This study examined how academic self-efficacy and academic stress relate to GenAI dependency, testing performance expectancy as a mediator and academic self-efficacy as a moderator of the stress–GenAI dependency relationship. Methods: This cross-sectional study surveyed 305 undergraduate students recruited through convenience sampling from a public university in the Eastern Province of Saudi Arabia between March and May 2026. Participants completed an Arabic measures of GenAI dependency, academic self-efficacy, academic stress, and performance expectancy. Direct, mediating, and moderating pathways were tested with partial least squares structural equation modeling (PLS-SEM), using 5,000 bootstrap resamples and a supplementary robustness check controlling for demographic covariates. Results: Academic self-efficacy was negatively associated with GenAI dependency (β = −0.245, p <0.001) and positively associated with performance expectancy (β = 0.237, p <0.001). Academic stress was positively associated with both performance expectancy (β = 0.315, p <0.001) and GenAI dependency (β = 0.287, p <0.001). Performance expectancy was positively associated with GenAI dependency (β = 0.411, p <0.001) and showed statistically significant indirect associations of academic self-efficacy (β = 0.098, p <0.001) and academic stress (β = 0.130, p <0.001) with GenAI dependency. Academic self-efficacy significantly moderated the relationship between academic stress and GenAI dependency (β = 0.102, p =0.010, 95% CI (0.024, 0.179); contrary to the hypothesized buffering effect, this positive association became stronger at higher levels of self-efficacy. The model explained 36.3% of GenAI dependency and 13.8% of performance expectancy variance. Conclusion: GenAI dependency was associated with academic stress and academic self-efficacy, while performance expectancy showing significant indirect associations. Self-efficacy reduced GenAI dependency directly but amplified the stress-dependency relationship. These results support encouraging balanced GenAI use, managing academic stress, and calibrating students’ expectations of GenAI.
SN - 1179-1578
ER -