Tıp Fakültesi Öğrencilerinin Yapay Zekâ Hazırbulunuşluk Durumları

Year 2024, Volume: 16 Issue: 1, 88 - 95, 14.03.2024

Büşra Emir , Tulin Yurdem , Tulin Ozel , Toygar Sayar , Teoman Atalay Uzun , Umit Akar , Unal Arda Colak

https://doi.org/10.18521/ktd.1387826

Abstract

Amaç: Bu araştırmada Tıp Fakültesi öğrencilerinin tıbbi yapay zekâ teknolojileri hakkındaki bilgi düzeyleri ve farkındalıklarının incelenmesi amaçlanmıştır.

Gereç ve Yöntem: Türkiye’deki Tıp Fakültelerinde öğrenim gören öğrencilerin katıldığı bu çalışmada, tanımlayıcı bir anket ve Tıp Fakültesi öğrencileri için Tıbbi Yapay Zekâ Hazır Bulunuşluk ölçeği (Medical Artificial Intelligence Readiness Scale for Medical Students-MAIRS-MS) kullanılmıştır. Sürekli değişkenlerin normal dağılıma uygunluğu Shapiro-Wilk testi ile test edilmiştir. Sürekli değişkenler için betimleyici istatistikler ortalama ve standart sapma ya da medyan (Q1-Q3) olarak verilmiştir. Kategorik değişkenler için betimleyici istatistikler frekans ve yüzde olarak belirtilmiştir. Varyansların homojenliği Levene testi ile değerlendirilmiştir. Ölçek alt boyut ve toplam puanlarının iki bağımsız gruba göre karşılaştırılmasında Mann Whitney U testi, ikiden fazla bağımsız gruba göre karşılaştırılmasında Tek Yönlü Varyans Analizi ya da Kruskal Wallis testi, gruplar arasında önemli farklılık bulunması durumunda çoklu karşılaştırmalarda Dunn-Bonferroni test kullanılmıştır. MAIRS-MS alt boyutları ve MAIRS-MS puanı arasındaki ilişki Spearman korelasyon katsayısı ile değerlendirilmiştir. MAIRS-MS güvenilirliği Cronbach alpha değeri ile belirlenmiştir. p<0.05 değeri istatistiksel önemlilik düzeyi olarak belirlenmiştir.
Bulgular: Yapay zekâ teknolojilerinin mesleğin gelişmesinde katkısı olacağını (p=0,003), iş yükünü azaltacağını (p<0,001) düşünen öğrencilerin, MAIRS-MS puan dağılımlarının daha yüksek olduğu bulunmuştur.
Sonuç: Öğrencilerin tıbbi yapay zekâ konusundaki farkındalık düzeylerinin yüksek olduğu ve yapay zekâ teknolojilerini kullanma becerilerine sahip oldukları görülmüştür.

Keywords

Yapay zekâ, Tıpta yapay zekâ uygulamaları, Eğitim, MAIRS-MS, Teknoloji

Artificial Intelligence Readiness Status of Medical Faculty Students

Abstract

Objective: This research aims to examine the knowledge level and awareness of Faculty of Medicine students about medical artificial intelligence technologies.
Methods: In this study involving students studying at Medical Faculties in Turkey, descriptive questionnaire, and the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS) were used. The suitability of continuous variables for normal distribution was tested with the Shapiro-Wilk test. Descriptive statistics for continuous variables are presented as mean and standard deviation or median (Q1-Q3). Descriptive statistics for categorical variables are reported as frequencies and percentages. Homogeneity of variances was evaluated with the Levene test. Mann Whitney U test was used to compare the scale subdimension and total scores according to two independent groups; One-way Analysis of Variance or Kruskal Wallis test was used to compare the scale subdimensions and total scores according to more than two independent groups. Dunn-Bonferroni test was used for multiple comparisons if there was a significant difference between the groups. The relationship between MAIRS-MS subdimensions and MAIRS-MS score was evaluated with the Spearman correlation coefficient. MAIRS-MS reliability was determined by Cronbach alpha value. The value of p<0.05 was determined as the level of statistical significance.
Results: MAIRS-MS scores of students who thought that artificial intelligence technologies would contribute to the development of the profession and reduce the workload were found to be higher (p=0.003; p<0.001).
Conclusions: It is seen that the students' awareness level about medical artificial intelligence is high, and they have the ability to use artificial intelligence technologies.

Keywords

Artificial intelligence, Artificial intelligence applications in medicine, Education, MAIRS-MS, Technology.

Ethical Statement

Ethics committee approval for this study, which aims to examine the knowledge level and awareness of Faculty of Medicine students about medical artificial intelligence technologies, was received on 26.04.2022 in Izmir Katip Celebi University Social Research Ethics Committee (2022/08-03).

Supporting Institution

None

Thanks

We would like to thank all participants

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