ArticlePloS one2024
How Do Personal Attributes Shape AI Dependency in Chinese Higher Education Context? Insights from Needs Frustration Perspective.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Addicted, attached, or just delegating? A scoping review on "problematic artificial intelligence use".Frontiers in psychology · 2026Pooled it
- Using Machine-Learning and Network Analysis to Investigate the Risk Factors of AI Dependence: The Crucial Role of Escape and Social Motivation.Behavioral sciences (Basel, Switzerland) · 2026Article
- The Double-Edged Sword of AI Efficiency: Self-Efficacy Erosion as a Mediator Linking Instant Gratification and Perceived AI Efficacy to AI Dependency.Behavioral sciences (Basel, Switzerland) · 2026Article
- Technostress, digital fatigue, and AI dependency as antecedents of burnout and SDG-4 achievement in EFL classrooms.Scientific reports · 2026Article
- A transdiagnostic model for how general purpose AI chatbots can perpetuate OCD and anxiety disorders.NPJ digital medicine · 2026Review
- Task complexity and AI dependency among college students: the mediating roles of cognitive load, future anxiety, and task motivation.BMC psychology · 2026Article
- A study on AI-enabled course development, AI proficiency, and first-year students' academic and psychological adjustment.Frontiers in psychology · 2026Article
- Academic involution atmosphere and AI dependence among university students: the mediating role of academic stress and the moderating role of individual academic involution behaviors.Frontiers in psychology · 2026Article
- AI dependency and academic motivation in higher education: the mediating role of learned helplessness and the moderating role of AI literacy.Frontiers in psychology · 2026Article
- Are students dependent on AI in writing courses? Analyzing factors influencing dependence on generative AI through the I-PACE model.Frontiers in psychology · 2026Article
- Family-school autonomy support for children's responsible use of generative artificial intelligence: a self-determination theory synthesis and developmental research agenda.Frontiers in psychology · 2026Review
- Effect of GenAI Dependency on University Students' Academic Achievement: The Mediating Role of Self-Efficacy and Moderating Role of Perceived Teacher Caring.Behavioral sciences (Basel, Switzerland) · 2025Article
- Paradox of AI in Higher Education: Qualitative Inquiry Into AI Dependency Among Educators in Palestine.JMIR medical education · 2025Article
- Techno-emotional projection in human-GenAI relationships: a psychological and ethical conceptual perspective.Frontiers in psychology · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe adoption of Generative AI in education presents both opportunities and challenges, particularly regarding its potential to foster student dependency. However, the psychological drivers of this dependency remain unclear. This study addresses this gap by applying the Interaction of Person-Affect-Cognition-Execution (I-PACE) model and Basic Psychological Needs (BPN) theory to explore how specific personality traits-neuroticism, self-critical perfectionism, and impulsivity-contribute to AI dependency through needs frustration, negative academic emotions, and reinforced performance beliefs.
methodData were collected from 958 university students (Mage = 21.67) across various disciplines. Structural equation modeling (SEM) was used to analyze the relationships among the variables.
resultsNeuroticism, self-critical perfectionism, and impulsivity were found to be significantly associated with increase needs frustration and negative academic emotions, which in turn reinforced students' positive beliefs about performance of AI tools, deepening their dependency. The study also uncovered complex serial mediation effects, highlighting intricate psychological pathways that drive maladaptive AI use.
conclusionsThis research provides a critical insight into the interplay between personality traits and technology use, shedding light on the nuanced ways in which individual differences influence dependency on generative AI. The findings offer practical strategies for educators to promote balanced AI use and support student well-being in educational settings.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.