Clinical virtual simulation: predictors of user acceptance in nursing education
José Miguel Padilha, Patrício Costa, Paulino Sousa, Ana Ferreira
Abstract
BACKGROUND: Using virtual patients integrated in simulators expands students' training opportunities in healthcare. However, little is known about the usability perceived by students and the factors/determinants that predict the acceptance and use of clinical virtual simulation in nursing education. OBJECTIVES: To identify the factors/determinants that predict the acceptance and use of clinical virtual simulation in learning in nursing education. METHODS: Observational, cross-sectional, analytical study of the use of clinical virtual simulation in nursing to answer the research question: What factors/determinants predict the acceptance and use of a clinical virtual simulator in nursing education? We used a non-probabilistic sampling, more specifically a convenience sample of nursing degree students. The data were collected through a questionnaire adapted from the Technology Acceptance Model 3. In technology and education, the Technology Acceptance Model is a theoretical model that predicts the acceptance of the use of technology by users. RESULTS: The sample comprised 619 nursing students, who revealed mean values of perceived usefulness (M = 5.34; SD = 1.19), ease of use (M = 4.74; SD = 1.07), and intention to use the CVS (M = 5.21; SD = 1.18), in a Likert scale of seven points (1-the worst and 7 the best possible opinion). This study validated the use of Technology Acceptance Model 3 adapted and tested the related hypotheses, showing that the model explains 62% of perceived utility, 32% of ease of use, and 54% of intention to use the clinical virtual simulation in nursing by nursing students. The adequacy of the model was tested by analysis of the direct effects of the relationships between the internal constructs (PU-BI, β = 0.11, p = 0.012; PEOU-BI, β = -0.11, p = 0.002) and the direct relations between some of the constructs internal to the Technology Acceptance Model 3 and the external determinants Relevance for learning and Enjoyability. In the proposed model, the external constructs that best predicted perceived usefulness, ease of use, and behaviour intention to use the clinical virtual simulation in nursing were Relevance for learning and Enjoyability. CONCLUSIONS: These study results allowed us to identify relevance for learning and enjoyability as the main factors/determinants that predict the acceptance and use of clinical virtual simulation in learning in nursing.