Evidence map›Paper›PMID 41872241›Full record

ArticleScientific reports2026

Artificial intelligence perceptions and career anxiety among health sciences students.

Erhan Dağ, Mustafa Nal, İbrahim Topuz, Hatice Kılınç, Yaşar Demir, Gülfer Bektaş

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Erhan DağGediz Health Services Vocational School, Kutahya Health Sciences University, Kutahya, Turkey.ORCID http://orcid.org/0000-0003-3474-1344
Mustafa NalDepartment of Healthcare Management, Faculty of Health Sciences, Kutahya Health Sciences University, Kutahya, Turkey.ORCID http://orcid.org/0000-0002-3282-1124
İbrahim TopuzPublic Health Nursing Department, Faculty of Health Sciences, Kutahya Health Sciences University, Kutahya, Turkey.ORCID http://orcid.org/0000-0003-0540-2095
Hatice KılınçDepartment of Journalism, Faculty of Communication, Süleyman Demirel University, Ispa, Turkey.ORCID http://orcid.org/0000-0002-4443-2564
Yaşar DemirDepartment of Statistics, Samsun Training and Research Hospital, Samsun, Turkey.ORCID http://orcid.org/0000-0001-9930-8440
Gülfer BektaşDepartment of Healthcare Management, Graduate School of Health Sciences, Faculty of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey. gulfer.bektas@acibadem.edu.tr.ORCID http://orcid.org/0000-0002-0110-4181

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AnxietyArtificial IntelligenceCareer ChoiceStudentsAdolescentAdultCross-Sectional StudiesEmploymentFemaleHumansMaleSurveys and QuestionnairesTurkeyUniversitiesYoung AdultArtificial intelligence anxietyEmploymentJob search anxietyUniversity students

Identifiers

PMID41872241
PMCPMC13168701

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LicenceCC BY-NC-ND
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Registered trials

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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.