Background: The aim of this study is to validate a newly developed nurses' self-efficacy sources inventory. We test the validity of a five-dimensional model of sources of self-efficacy, which we contrast with the traditional four-dimensional model based on Bandura's theoretical concepts. Methods: Confirmatory factor analysis was used in the development of the newly developed self-efficacy measure. Model fit was evaluated based upon commonly recommended goodness-of-fit indices, including the χ2 of the model fit, the Root Mean Square Error of approximation (RMSEA), the Tucker-Lewis Index (TLI), the Standardized Root Mean Square Residual (SRMR), and the Bayesian Information Criterion (BIC). Results: All 22 items of the newly developed five-factor sources of self-efficacy have high factor loadings (range .40-.80). Structural equation modeling showed that a five-factor model is favoured over the four-factor model. Conclusions and implications: Results of this study show that differentiation of the vicarious experience source into a peer- and expert based source reflects better how nursing students develop self-efficacy beliefs. This has implications for clinical learning environments: a better and differentiated use of self-efficacy sources can stimulate the professional development of nursing students.
Understanding how experiences unfold requires measuring participants' emotions, especially as they move from location to location. Measuring and mapping emotions over space is technically challenging, however. While a number of technologies to record and spatially resolve emotion data exist, they have not been systematically compared. We present emotion data collected at a natural and military heritage site in the Netherlands using three different methods, namely retrospective self report, experience reconstruction, and physiology. These data are applied to three corresponding mapping methods. The resulting maps lead to divergent findings, demonstrating that spatial mapping of emotion data accentuates differences between distinct dimensions of emotions.
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Understanding how experiences unfold requires measuring participants' emotions, especially as they move from location to location. Measuring and mapping emotions over space is technically challenging, however. While a number of technologies to record and spatially resolve emotion data exist, they have not been systematically compared. We present emotion data collected at a natural and military heritage site in the Netherlands using three different methods, namely retrospective self report, experience reconstruction, and physiology. These data are applied to three corresponding mapping methods. The resulting maps lead to divergent findings, demonstrating that spatial mapping of emotion data accentuates differences between distinct dimensions of emotions.
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