3 research outputs found

    Predicting needlestick and sharps injuries in nursing students: Development of the SNNIP scale

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    © 2020 The Authors. Nursing Open published by John Wiley & Sons Ltd. Aim: To develop an instrument to investigate knowledge and predictive factors of needlestick and sharps injuries (NSIs) in nursing students during clinical placements. Design: Instrument development and cross-sectional study for psychometric testing. Methods: A self-administered instrument including demographic data, injury epidemiology and predictive factors of NSIs was developed between October 2018–January 2019. Content validity was assessed by a panel of experts. The instrument's factor structure and discriminant validity were explored using principal components analysis. The STROBE guidelines were followed. Results: Evidence of content validity was found (S-CVI 0.75; I-CVI 0.50–1.00). A three-factor structure was shown by exploratory factor analysis. Of the 238 participants, 39% had been injured at least once, of which 67.3% in the second year. Higher perceptions of “personal exposure” (4.06, SD 3.78) were reported by third-year students. Higher scores for “perceived benefits” of preventive behaviours (13.6, SD 1.46) were reported by second-year students

    Predicting needlestick and sharps injuries in nursing students: Development of the SNNIP scale

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    A three component model for superdiffusive motion effectively describes migration of eukaryotic cells moving freely or under a directional stimulus

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    : Although the simple diffusion model can effectively describe the movement of eukaryotic cells on a culture surface observed at relatively low sampling frequency, at higher sampling rates more complex models are often necessary to better fit the experimental data. Currently available models can describe motion paths by involving additional parameters, such as linearity or directional persistence in time. However sometimes difficulties arise as it is not easy to effectively evaluate persistence in presence of a directional bias. Here we present a procedure which helps solve this problem, based on a model which describes displacement as the vectorial sum of three components: diffusion, persistence and directional bias. The described model has been tested by analysing the migratory behaviour of simulated cell populations and used to analyse a collection of experimental datasets, obtained by observing cell cultures in time lapse microscopy. Overall, the method produces a good description of migration behaviour as it appears to capture the expected increase in the directional bias in presence of wound without a large concomitant increase in the persistence module, allowing it to remain as a physically meaningful quantity in the presence of a directional stimulus
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