1,720,970 research outputs found
Enhancing Learning Systems in Using Patient Experience Data: An Exploratory Mixed-Method Study in Two Italian Regions
Full text linkIn the quest for healthcare systems enhancement, the improvement of patient experience plays a central role. The challenge lies in converting patient-reported experience data into actionable knowledge for quality improvement. This study aims to investigate the use of patient-reported data as knowledge base for actions and to identify and map actions derived from the use of patient-experience data within two Italian regional healthcare systems. Patient Experience Data are systematically collected in both systems, providing real-time updates accessible by professionals and managers through web-based reporting systems and including a collaborative network among practitioners. A sequential exploratory mixed-method study was carried out in several qualitative and quantitative phases. In the first phase, a qualitative method was conducted to discuss the actionability of patient-reported data and to design a tool for collecting the improvement actions based on these data. In the second phase, a quali-quantitative survey was performed to explore the professionals' use of patient-reported information and the types of actions implemented. Finally, a workshop was held to discuss, interpret and validate the results. The initial workshop identified key dimensions for improvement initiatives. After design and distribution of survey, a total of 189 responses was collected, respectively 96 from Region A and 93 from Region B. Both regions ensured widespread use of patient-reported data (89%). The establishment of a collaborative network seemed to reduce the learning curve in using patient-reported data and fostered a culture of using patient feedback effectively. The results reveal a difference between the two regions, with a more extensive patient-reported data use in Region A, attributed to its systematic joining the PREMs Observatory, prior experiences with patient-feedback collection and use, and patient-experience indicators integrated into the performance evaluation system. Regarding practices of data use, four themes emerged, namely, internal actions addressed to hospital staff (35.9%), external actions addressed to users (18.6%), comfort and hospitality aspects (34.7%) and review of processes and procedures (10.8%). The study highlights the importance of effectively using patient-reported data to achieve organisational goals, by combining different managerial strategies. It demonstrates how professionals use such data for improvement actions and underscores the significance of various forms of knowledge dissemination and sharing. It advocates for fostering a culture of continuous learning and improvement within and across healthcare organisations
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
The stochastic quantization method and its application to the numerical simulation of volcanic conduit dynamics under random conditions
No full textStochastic Quantization (SQ) is a method for the approximation of a continuous probability distribution with a discrete one. The proposal made in this paper is to apply this technique to reduce the number of numerical simulations for systems with uncertain inputs, when estimates of the output distribution are needed. This question is relevant in volcanology, where realistic simulations are very expensive and uncertainty is always present. We show the results of a benchmark test based on a one-dimensional steady model of magma flow in a volcanic conduit
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
From One to Many Lorikeets: Discovering Image Analogies in the CLIP Space
No full textDrawing analogies between two pairs of entities in the form of A:B::C:D (i.e. A is to B as C is to D) is a hallmark of human intelligence, as evidenced by sufficient findings in cognitive science for the last decades. In recent years, this property has been found far beyond cognitive science. Notable examples are word2vec and GloVe models in natural language processing. Recent research in computer vision also found the property of analogies in the feature space of a pretrained ConvNet feature extractor. However, analogy mining in the semantic space of recent strong foundation models such as CLIP is still understudied, despite the fact that they have been successfully applied to a wide range of downstream tasks. In this work, we show that CLIP possesses the similar ability of analogical reasoning in the latent space, and propose a novel strategy to extract analogies between pairs of images in the CLIP space. We compute all the difference vectors of a pair of any two images that belong to the same class in the CLIP space, and employ k-means clustering to group the difference vectors into clusters irrespective of their classes. This procedure results in cluster centroids representative of class-agnostic semantic analogies between images. Through extensive analysis, we show that the property of drawing analogies between images also exists in the CLIP space, which are interpretable by humans through a visualisation of the learned clusters
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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