Application of an outcome present test-peer learning model to improve clinical reasoning of nursing students in the intensive care unit

Abstract

Aim: High clinical reasoning skills are required by nurses in the intensive care unit (ICU). Nurses should perform clinical reasoning and make important clinical assessments and decisions for the provision of nursing care in the ICU. However, they often have difficulty in making decisions because of a lack of skills and proficiency in clinical reasoning methods. The outcome present test model through peer learning (OPT-peer learning) constitutes one of the important strategies to improve clinical reasoning skills. This research is aimed to explore the experience of nursing students and clinical instructors, following the application of the OPT-peer learning model. This phenomenology study was conducted with eight students of the nursing profession and four clinical instructors after applying the model of OPT-peer learning for 6 weeks. Materials and Methods: Data were collected through focus group discussions and in-depth interviews. Thematic analysis techniques were applied using Atlas.ti software version 6.1. There are six themes identified from participants pertaining to their experience in using the OPT-peer learning model: The model facilitates the guidance process; improves clinical reasoning skills; strengthens self-directed learning; triggers a successful group process; strengthens use of interrelated terminology of the North American Nursing Diagnosis Association (NANDA), Nursing Intervention Classification (NIC), and Nursing Outcome Classification (NOC); and facilitates the preparation of report documentation. Results: The OPT-peer learning model can be applied as an effective learning strategy for developing clinical reasoning skills in the students of the nursing profession who take specialization in the ICU. Training on the OPT-peer learning model, especially the mastery of its modules and terminologies of NANDA, NIC, and NOC, is needed before the model is applied.