RESUMO
OBJECTIVES: The aim of this study is to determine the effect of the birth story of individuals on personality traits and death anxiety. METHODS: This descriptive and analytical research was completed with 1,635 people who participated voluntarily. The study data were collected with the Personal Information Form, Cervantes Personality Scale (CPS), and Abdel-Khalek Death Anxiety Scale (ASDA). RESULTS: The research sample is average means 31.63 ± 11.04 years, most of the female (72.7%) and married (54.6%). In our study, it was observed that women's death anxiety was higher than men's. Our study found that individuals born by caesarean section had greater neurotic personality traits, emotional stability/neuroticism score averages, and death anxiety scores compared to individuals born vaginally. CONCLUSION: In the model made with multiple regression analysis, birth type did not significantly predict death anxiety, while sex and emotional stability/neuroticism personality trait significantly predicted death anxiety.
RESUMO
BACKGROUND: Artificial intelligence technologies are one of the most important technologies of today. Developments in artificial intelligence technologies have widespread and increased the use of artificial intelligence in many areas. The field of health is also one of the areas where artificial intelligence technologies are widely used. For this reason, it is considered important that healthcare professionals be prepared for artificial intelligence and do not experience problems while training them. In this study, midwife and nurse candidates, as future healthcare professionals, were discussed. AIM: This study aims to examine the effect of the artificial intelligence readiness on the artificial intelligence anxiety and the effect of artificial intelligence characteristic variables (artificial intelligence knowledge, daily life, occupational threat, artificial intelligence trust) on the medical artificial intelligence readiness and artificial intelligence anxiety of students. METHODS: This study was planned and carried out as a relational survey study, which is a quantitative research. A total of 480 students, consisting of 240 nursing and 240 midwifery students, were included in this study. SPSS 26.0 and AMOS 26 package programs were used to analyse the data and descriptive statistics (frequency, percentage, mean, standard deviation) and path analysis for the structural equation model were used. RESULTS: No significant difference was found between the medical artificial intelligence readiness (p=0.082) and artificial intelligence anxiety (p=0.486) scores of midwifery and nursing students. The model of the relationship between medical artificial intelligence readiness and artificial intelligence anxiety had a good goodness of fit. Artificial intelligence knowledge and using artificial intelligence in daily life are predictors of medical artificial intelligence readiness. Using artificial intelligence in daily life, occupational threat and artificial intelligence trust are predictors of artificial intelligence anxiety. CONCLUSION: Midwifery and nursing students' AI anxiety and AI readiness levels were found to be at a moderate level and students' AI readiness affected AI anxiety.
