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Artificial intelligence perceptions and career anxiety among health sciences students
Erhan Dağ1, Mustafa Nal2, İbrahim Topuz3
1Gediz Health Services Vocational School, Kutahya Health Sciences University, Kutahya, Turkey.
Abstract:
Recent rapid developments in artificial intelligence (AI) technologies are leading to significant changes in social and economic structures. These changes are having a direct impact on young people's transition to the labour market and their expectations regarding employment. Against this backdrop, the relationship between university students' concerns about AI and their anxieties about job searching is emerging as a multidisciplinary field of research. This study aims to evaluate the impact of AI-related anxiety on university students' anxieties about finding employment. This cross-sectional study involved 821 health sciences students from various departments at Turkish universities, including Physical Therapy and Rehabilitation, Pharmacy Services, Medical Secretarial and Documentation, Nursing, Speech and Language Therapy, Midwifery and Health Management. Participants were selected via an online survey distributed by class representatives on WhatsApp. Data were collected using the Artificial Intelligence Anxiety Scale and the Job Search Anxiety Scale, and analysed using Pearson's correlation and multiple linear regression in the SPSS (v26.0) programme. Of these participants, 82.5% are female, and 59.6% are undergraduates. Studies in Turkey have shown that the proportion of female university students is higher than that of male students. This may partly explain the higher proportion of female participants in the sample. The mean scores on the artificial intelligence anxiety scale and the job search anxiety scale were 3.02 ± 0.80 and 3.16 ± 0.60, respectively. The study revealed a moderate, positive, and significant correlation (r = 0.233, p < 0.001) between artificial intelligence anxiety and job search anxiety. The study revealed that, even when socio-demographic variables were controlled, artificial intelligence anxiety remained a significant predictor of job search anxiety (β = 0.234, p < 0.001). Additionally, it was found that demographic variables such as income status (p = 0.011, β = - 0.088) and educational attainment (p = 0.001, β = 0.208) significantly affected job search anxiety. The findings show that concerns about artificial intelligence are closely linked to students' expectations regarding employment after graduation. It has therefore been concluded that artificial intelligence anxiety is not merely an attitude toward technology but an important psychological factor shaping students' perceptions of their professional futures and fears of unemployment. The research results suggest that enhancing educational programmes and career counselling services to boost artificial intelligence literacy at the university level could play a significant role in alleviating students' anxiety about job hunting.
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