Aug 2026· The American Journal of Nursing· Vol 126 9, pp.
20-26
· 0 citations· 41 references
Medicine
TL;DR
The findings indicate that the excessive use of AI tools may contribute to cognitive fatigue and mental exhaustion, and can negatively impact foundational cognitive skills such as critical thinking and decision-making.
Abstract
Background
Artificial intelligence (AI) can be beneficial in tailoring learning experiences to each student's learning style, needs, and preferences. But the integration of AI into education has also raised a host of concerns, including AI dependency and brain rot. Thus far, there has been limited research on the relationship between the use of AI and brain rot.
Purpose
This study aimed to explore the relationship between AI dependency and brain rot, specifically among nursing students.
Methods
This mixed-methods study involved undergraduate nursing students at a university in Türkiye. Quantitative data were collected via an online survey that included a sociodemographic questionnaire, the eight-item Brain Rot Scale (BRS-8), and the Dependence on Artificial Intelligence (DAI) Scale. Qualitative data were collected via semistructured interviews. Quantitative data analysis included the use of descriptive statistics, independent samples t tests, one-way analysis of variance, Pearson correlational analysis, and simple linear regression analysis. Qualitative data were analyzed via thematic analysis.
Results
A total of 222 nursing students participated in the quantitative phase and 11 also participated in the qualitative interviews. Of the 222 nursing students in the quantitative phase, 90.1% were female; their mean age was 20.63 years. Quantitative analysis found a moderate, positive, and statistically significant correlation between DAI Scale and BRS-8 scores (r = 0.39). Qualitative analysis indicated that students often relied heavily on AI tools in preparing for or taking examinations, with some reporting that the overuse of AI led to reduced focus and dulled thinking.
Conclusions
This study found a moderate, positive, and statistically significant relationship between AI dependency and brain rot among nursing students. The findings indicate that the excessive use of AI tools may contribute to cognitive fatigue and mental exhaustion, and can negatively impact foundational cognitive skills such as critical thinking and decision-making. It is essential that nursing programs ensure the AI literacy of their students and develop a balance of traditional and AI-related pedagogical strategies that best support students' brain functions and cognitive abilities.
Findings show that nursing students who feel more prepared for AI tend to be less anxious about technology and add AI training more consistently throughout the nursing curriculum and building digital skills may help reduce fear and make it easier for students to use AI tools in the future.
Abstract Background AI is increasingly being integrated into education and health care, offering opportunities to improve learning, understanding of clinical cases, and students’ self-confidence. However, it remains necessary to assess nursing students’ perceptions of AI and its impact on their academic and professional development. Objective The aim of the study was to assess AI use among nursing students, their perceptions of AI, and its impact on learning, academic performance, and professional preparation. Methods A descriptive cross-sectional study with analytical components was conducted at the Faculty of Medical Technical Sciences in Elbasan, Albania. Data were collected through a structured questionnaire administered via Google Forms, which assessed AI use and its perceived impact on learning and professional preparation. Data were analyzed using SPSS (version 23.0). Descriptive statistics, chi-square tests for associations between variables (P<.05), and logistic regression to estimate crude odds ratios (CORs) and adjusted odds ratios (AORs) with 95% CIs were used. Results A total of 279 nursing students participated in the study (mean age 22.4, SD 5.7 years), the majority of whom were female (273/279, 97.8%), lived in urban areas (156/279, 55.9%), and were enrolled in the bachelor’s program (198/279, 71%). Overall, 83.9% (234/279) reported using AI, mainly virtual assistants such as ChatGPT or similar tools (183/234, 78.2%). The most common reason was information searching (216/234, 92.3%), followed by studying and understanding lecture content (96/234, 41%). Bivariate analysis showed no significant associations between AI use and residence or study cycle, whereas grade point average (GPA) was significantly associated with AI use. In the multivariable analysis, GPA remained the only independent predictor of AI use. Students with a GPA of 6.0 to 6.9 (AOR 5.55, 95% CI 1.53-20.14; P=.009) and those with a GPA of 8.0 to 8.9 (AOR 5.73, 95% CI 1.26-26.00; P=.02) were significantly more likely to use AI than the reference group. Students perceived AI as having a moderate impact on learning, particularly understanding lectures (mean 2.58, SD 1.10) and exam preparation (mean 2.58, SD 1.02), whereas its impact on self-confidence (mean 1.97, SD 1.17) and empathy (mean 1.90, SD 1.12) was perceived as low. Although AI was considered useful for supporting learning (mean 2.83, SD 1.12), students expressed concerns regarding the reliability of AI-generated information (mean 3.18, SD 1.22), dependence on AI (mean 2.75, SD 1.28), and its impact on critical thinking (mean 2.80, SD 1.18). Conclusions AI is widely used among nursing students, primarily supporting learning and academic performance. However, its impact on professional and interpersonal competencies remains limited. These findings suggest the need for integrating AI into nursing education curricula, with a focus on critical use and the development of students’ professional competencies.
Objective: The adoption of Artificial Intelligence (AI) tools, including platforms like ChatGPT, in educational environments has garnered growing attention, especially among students in healthcare-related programs. While AI presents opportunities to enhance learning efficiency, concerns remain about its influence on students' academic performance and critical thinking capabilities. This study seeks to evaluate the level of dependence on AI among young healthcare professional students and explore its impact on both their academic achievements and critical thinking skills.
Materials and Methods: A cross-sectional survey was administered to undergraduate healthcare students. Total 395 students participated in the study. AI- Health Professionals & Students Dependency Index, academic performance scale and critical thinking evaluation scale was used. The questionnaire covered the frequency and manner of AI tool usage, self-reported academic outcomes, and measures of critical thinking. Data were analyzed using descriptive statistics and correlation techniques to explore the associations between AI use and academic metrics.
Results: Initial findings reveal that many students frequently use AI tools for academic purposes. Which may impair critical thinking, problem-solving abilities, academic performance and professional skills with the p- value of 0.05 of Pearson correlation coefficient.
Conclusion: This study highlights the importance of balanced AI integration in academic settings. It advocates for the establishment of structured guidelines to ensure AI tools complement, rather than replace, traditional educational practices—thereby maintaining and promoting critical thinking among healthcare students.
Dharmita Yogeshwar (pt), Janvhi Singh (pt), Ajeet Kumar Saharan (pt) et al.· Adolescência e Saúde· 0 citations
Objective: As the growing use of artificial intelligence in healthcare creates both new opportunities and emerging concerns for nursing practice, this study aimed to examine nursing students’ attitudes toward artificial intelligence and to explore the extent to which AI-related anxiety and technological dependency predict these attitudes.Methods: A descriptive, cross-sectional, and correlational design was employed with a sample of 373 nursing students studying at a public university in Türkiye. The data were collected using three instruments: the General Attitudes Toward Artificial Intelligence Scale, the Artificial Intelligence Anxiety Scale, and the Artificial Intelligence Dependency Scale. The statistical analyses encompassed a range of methodologies, including descriptive measures, Pearson correlation coefficients, and multiple regression models.Results: The mean score for the General Attitudes toward Artificial Intelligence Scale Positive Attitudes subscale was 42.17 ± 8.71, while the mean score for the Negative Attitudes subscale was 24.44 ± 6.69. The mean total scores for the Artificial Intelligence Anxiety Scale and the Dependence on Artificial Intelligence Scale were 73.57 ± 25.54 and 12.39 ± 4.28, respectively. Multiple regression analyses revealed that AI-related anxiety and dependency significantly predicted positive attitude scores (R² = 0.060, F = 11.722, p < 0.001) and negative attitude scores (R² = 0.349, F = 98.985, p < 0.001).Conclusions: The findings underscore the notion that nursing students’ perceptions of artificial intelligence are shaped by a complex interplay of emotional, cognitive, and behavioral factors. In accordance with a holistic nursing framework, incorporating artificial intelligence into education should extend beyond the acquisition of technical skills to encompass the maintenance of core care values, such as empathy, ethical awareness, and effective communication. Educational approaches that encourage critical engagement with technology and its balanced use may facilitate the ethical and efficient integration of artificial intelligence into nursing practice.
Eren Sarıtaş, Pınar ÇİÇEKOĞLU ÖZTÜRK· Sakarya Üniversitesi Holisti...· 0 citations
The findings indicate that nursing students had generally positive levels of AI literacy and attitudes toward AI, and higher AI literacy was associated with more positive attitudes toward AI.
M. Çil, Berna Eren Fidancı, D. Yildiz· Journal of Education and Res...· 0 citations
The findings indicate a significant negative association between AI dependence and achievement motivation, emphasizing the need to consider students' technology usage patterns concerning academic motivation.
Aya M. Nasr, Amira Mostafa Soliman, Nourhan Essam Hendawi et al.· Nurse Education Today· 0 citations
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