Artificial intelligence perceptions and career anxiety among health sciences students

Synthesis: AI perceptions and career anxiety among health sciences students — a cross-sectional study of 821 health sciences students across Turkish universities showing a moderate, positive, significant correlation (r = 0.233, p < 0.001) between AI anxiety and job search anxiety; AI anxiety remained a significant predictor of job search anxiety even after controlling socio-demographic variables (β = 0.234, p < 0.001).

Dağ, Nal, Topuz, Kılınç, Demir, & Bektaş (2026) extend the career-anxiety evidence base to health professions, showing that AI anxiety is not merely an attitude toward technology but a psychological factor shaping students' perceptions of their professional futures and fear of unemployment. This is the fourth empirical career-anxiety study linked to the Career Development and Readiness concept.

Method

• Sample: 821 health sciences students (Physical Therapy, Pharmacy Services, Medical Secretarial/Documentation, Nursing, Speech & Language Therapy, Midwifery, Health Management) from Turkish universities; 82.5% female, 59.6% undergraduates.
• Design: Cross-sectional online survey (distributed by class representatives via WhatsApp).
• Measures/analysis: Artificial Intelligence Anxiety Scale and Job Search Anxiety Scale; Pearson correlation and multiple linear regression (SPSS v26).

Key Findings

• AI anxiety predicts job search anxiety. Moderate positive correlation (r = 0.233, p < 0.001); AI anxiety remained a significant predictor (β = 0.234, p < 0.001) even controlling for socio-demographics.
• Demographic effects: income status (p = 0.011, β = −0.088) and educational attainment (p = 0.001, β = 0.208) significantly affected job search anxiety.
• Core conclusion: AI anxiety is not merely a technology attitude but an important psychological factor shaping students' perceptions of their professional futures and fears of unemployment.

What this means for practice

• Instructors. Position AI as a tool that complements professional practice rather than replaces it: in human-interaction fields such as physical therapy, nursing, and midwifery, teach clinical decision support alongside ethical responsibility, empathy, and digital leadership instead of technical proficiency alone.
• Administrators. Treat AI anxiety as a career-transition risk factor and embed AI Literacy in the health sciences curriculum at the institutional level, so AI is framed as a resource that transforms professional work rather than threatens professional identity.
• Administrators. Expand free or low-cost reskilling and mentoring for low-income students, whose job search anxiety was significantly higher (p = 0.011); their concern traces to limited access to continuous learning, not to personal inadequacy.
• Faculty developers. Have career counselors discuss AI and the labor market in terms of mixed skill sets, new job definitions, and adaptation strategies, not only risks, so students treat the job search as something they can act on.

Limitations

• Cross-sectional design: 821 health sciences students were surveyed once (January–June 2024) at Turkish state universities, so the direction of the AI anxiety–job search anxiety relationship cannot be established.
• The sample was 82.5% female, which makes meaningful gender comparisons difficult and weakens the model where gender matters.
• Distribution through class representatives on WhatsApp produced a homogeneous, selection-biased sample that likely over-represented students with high anxiety, limiting generalizability.
• Every variable was self-reported by the same respondents, risking common-method variance, and AIAS and JSAS total scores were used, so the results speak to general AI anxiety rather than its sub-dimensions.

Citation

Dağ, E., Nal, M., Topuz, İ., Kılınç, H., Demir, Y., & Bektaş, G. (2026). Artificial intelligence perceptions and career anxiety among health sciences students. Scientific Reports, 16, 42030.