AI-Supported E-Learning for Pressure Injury Prevention

Detailed Description

This study is a single-centre, two-arm, parallel-group randomised controlled educational trial comparing two different teaching methods for pressure injury prevention. The study was conducted with undergraduate nursing students in the nursing department of a faculty of health sciences.

Pressure injuries are an important patient safety problem, especially for patients with limited mobility, patients in intensive care, patients after surgery and patients using medical devices. Preventing pressure injuries requires regular risk assessment, skin inspection, appropriate positioning, pressure redistribution, nutritional assessment, monitoring of device-related pressure and continuity of care. Therefore, it is important that nursing students develop adequate knowledge, self-efficacy and positive attitudes before graduation.

In this study, students were randomly assigned to one of two groups. The first group received pressure injury prevention education through conventional face-to-face classroom instruction. The second group completed the same core content through an artificial intelligence-supported modular e-learning programme. Both educational methods covered key topics, including the causes of pressure injuries, classification, risk assessment, nutrition, preventive interventions, care for special patient groups and medical device-related pressure injuries.

The artificial intelligence-supported e-learning programme consisted of short video presentations, narration scripts, clinical examples, question-and-answer activities, short quizzes and feedback sections. The educational materials were prepared with the support of artificial intelligence, but they were not used directly. The materials were reviewed by experts in surgical nursing and related fields for clinical accuracy, consistency with current evidence, suitability for undergraduate nursing students and clarity of instruction. Necessary revisions were made according to expert feedback before the e-learning content was delivered.

Students' outcomes were assessed at three time points: before the education, immediately after the education and four weeks after the education. Knowledge of pressure injury prevention was measured using PUKAT 2.0-T. Self-efficacy in pressure injury management was measured using PUM-SES. Attitudes towards pressure injury prevention were measured using APuP. This allowed the study to examine not only immediate learning after the education but also whether learning was maintained after four weeks.

This study does not involve a direct clinical intervention with patients. The participants are nursing students. Therefore, the effect of the study on patient care is indirect. However, improving the way pressure injury prevention is taught may support future healthcare professionals' clinical decision-making and patient safety practices.

The study aims to show whether artificial intelligence-supported modular e-learning is a useful method for pressure injury prevention education, how it compares with face-to-face instruction and whether students retain what they have learned over a short follow-up period. The findings may contribute to the development of nursing education programmes, the standardisation of pressure injury prevention education and stronger patient safety-focused education strategies in tissue viability.