| dc.description.abstract | There is a critical national nursing workforce shortage, with estimates of over 200,000 new job openings for Registered Nurses (RNs) annually through 2031 (AACN, 2022). These forecasted workforce needs challenge nursing programs to increase student enrollment (Dowling et al., 2021) while maintaining high-quality education standards. Student learning is facilitated by collaborative academic healthcare practices that provide active learning environments for students to engage in direct patient care under the direct supervision of a licensed nurse. The interactions between students and mentors within the clinical environment are essential for cultivating a sense of belonging while fostering the development of the professional nurse role. Exploring factors impacting the quality of learning experiences from a student’s perspective provides valuable information to support best practices in an ever-changing education and healthcare environment. Although research has examined nursing student perceptions of clinical learning experiences with trained faculty and preceptors (Chan, 2001; Blegen et al., 2015), there is a lack of survey instruments designed to explore the inviting behaviors of nursing staff. This project aimed to examine the psychometric properties of a new instrument designed to examine nursing student perceptions of nursing staff behaviors during clinical learning experiences. Collaborative academic healthcare practices facilitated the refinement and piloting of the survey instrument. Rasch methods were used to examine responses from nursing students enrolled in licensed practical, associate, and baccalaureate nursing programs who had attended clinical experiences at one hospital organization. Several aspects of validity were explored using Russell’s (2022) Justification of Use model and Messick’s (1994) unified framework of construct validity as a guide. Study findings reinforce the importance of examining more than one aspect of validity before using survey results to make inferences or generalizability claims. | en_US |
