Knowledge and Attitude regarding Artificial Intelligence in Health Care among Nursing Students

Abstract

Background of Study The earliest research into thinking machines was inspired by a confluence of ideas that became prevalent in the late 1930s, 1940s, and early 1950s.The idea of “artificial intelligence” goes back thousands of years, to ancient philosophers considering questions of life and death. In ancient times, inventors made things called “automatons” which were mechanical and moved independently of human intervention. The field of "artificial intelligence research" was founded as an academic discipline in 1956. AI plays a crucial and vital role in healthcare because it can significantly improve diagnostic accuracy, personalize treatment plans, streamline administrative tasks, enable remote patient monitoring, identify high-risk populations, accelerate drug discovery, and ultimately enhance patient care quality while potentially reducing costs by optimizing resource allocation, all by leveraging its ability to analyse vast amounts of medical data rapidly and efficiently. AI in the health care system helps not only in expediting diagnosis and management but also injudicious resource all location. Researches on artificial intelligence (AI) in healthcare are essential because it can greatly enhance the knowledge and skills of health care workers and improve patient outcomes by facilitating early disease detection, personalized treatment plans, faster and more accurate diagnoses, effective drug discovery, and optimized healthcare management which will eventually result in better preventative and curative intervention Developing countries like India are lagging in the implementation of AI-based solutions in healthcare. There is a need of educational interventions, researches on AI to bridge the knowledge gaps and develop a favourable attitude among healthcare professionals regarding AI in health care.

Research Objectives

1) To assess the knowledge and Attitude regarding Artificial Intelligence in healthcare.

2) To find out a correlation between knowledge & attitude regarding Artificial Intelligence in health care.

3) To find out the association between knowledge score regarding Artificial Intelligence in health care with selected socio demographic variables.

4) To find out the association between Attitude regarding Artificial Intelligence in health care with selected socio demographic variables.

Methods The research approach adopted for the study was a quantitative survey approach. Research design was Nonexperimental, Descriptive Correlational research design. By using probability stratified random sampling technique 120 nursing students studying in D. Y. Patil College of Nursing were selected for the study. Structured knowledge questionnaire and Structured attitude scale was used to assess the knowledge and attitude of nursing students regarding Artificial Intelligence in Healthcare. The reliability of the tool was tested by using Karl Pearson’s Correlation coefficient. The reliability computed was r = 0.81. Data was analysed by using mean, median, mode, range, standard deviation, paired ‘t’ test & chi square test.

Results: The findings of the study revealed thatmajority of the subjects 73 (60.83%) had good knowledge, 46 (38.33%) had average knowledge and minimum 01 (0.83%) had poor knowledge.In attitude majority of the subjects 111 (92.50%) had positive attitude and minimum 9 (7.50%) had negative attitude. Thecalculatedcorrelation value of knowledge and attitude was (tcal=0.132) greater than 0, which shows a weakly positive relationship. This indicated that there was a strongly positive correlation between knowledge and attitude which was statistically significant at p <0.05 level, regarding artificial intelligence in healthcare. There was no any significant association between knowledge scores and selected socio-demographic variables. The calculated Chi-square values was lesser than tabulated value at p< 0.05 level of significance. This indicated that there was no any significant association between knowledge scores with their selected socio-demographic variables at p< 0.05 level of significance. There was no any significant association between attitude scores and selected socio-demographic variables. The calculated Chi-square values was lesser than tabulated value at p< 0.05 level of significance. This indicated that there was no any significant association between knowledge scores with their selected socio-demographic variables at p< 0.05 level of significance.

Interpretation and Conclusion: The overall finding shows that majority of nursing students had good knowledge and positive attitude regarding artificial intelligence in health care and there was no any significant association between knowledge and attitude regarding artificial intelligence in healthcare with their socio demographic variables.