Endoscopic ultrasound in cystic pancreatic lesions: operator training needs to be improved, EUS-guided sampling should be standardized, and decision-making should be multidisciplinary and evidence-based

Endoscopy ◽  
2011 ◽  
Vol 43 (07) ◽  
pp. 557-559 ◽  
Author(s):  
L. Palazzo ◽  
D. O’Toole
2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.


2011 ◽  
Vol 20 (4) ◽  
pp. 121-123
Author(s):  
Jeri A. Logemann

Evidence-based practice requires astute clinicians to blend our best clinical judgment with the best available external evidence and the patient's own values and expectations. Sometimes, we value one more than another during clinical decision-making, though it is never wise to do so, and sometimes other factors that we are unaware of produce unanticipated clinical outcomes. Sometimes, we feel very strongly about one clinical method or another, and hopefully that belief is founded in evidence. Some beliefs, however, are not founded in evidence. The sound use of evidence is the best way to navigate the debates within our field of practice.


Author(s):  
John Hunsley ◽  
Eric J. Mash

Evidence-based assessment relies on research and theory to inform the selection of constructs to be assessed for a specific assessment purpose, the methods and measures to be used in the assessment, and the manner in which the assessment process unfolds. An evidence-based approach to clinical assessment necessitates the recognition that, even when evidence-based instruments are used, the assessment process is a decision-making task in which hypotheses must be iteratively formulated and tested. In this chapter, we review (a) the progress that has been made in developing an evidence-based approach to clinical assessment in the past decade and (b) the many challenges that lie ahead if clinical assessment is to be truly evidence-based.


2016 ◽  
Vol 53 (2) ◽  
pp. 215-223 ◽  
Author(s):  
Lauren K. Richards ◽  
Eric Bui ◽  
Meredith Charney ◽  
Katherine Clair Hayes ◽  
Allison L. Baier ◽  
...  

2014 ◽  
Vol 67 (5) ◽  
pp. 790-794 ◽  
Author(s):  
Iván Arribas ◽  
Irene Comeig ◽  
Amparo Urbano ◽  
José Vila

2021 ◽  
Vol 13 (4) ◽  
pp. 2060
Author(s):  
Doriane Desclee ◽  
David Sohinto ◽  
Freddy Padonou

Contributing to Sustainable Development Goals and Agenda 2030 is a shared objective of all institutions and people. The challenges differ according to the characteristics of every context. In developing countries, strongly dependent on the agricultural sector, agricultural supply chains are recognized as crucial for economic growth and enablers for livelihood improvement. Moreover, sustainable development issues are correlated and can meet in agricultural supply chains. For several decades, parallel to decision-makers, the research community has elaborated sustainability assessment tools. Such tools evolved to fit with actuality, but it is challenging to find decision-making support tools for sustainable development adequate in agricultural supply chains and developing countries contexts. There is a necessity to define evidence-based tools and exhaustive analytical frameworks according to sustainability multidimensionality and strategical tradeoffs necessity. The VCA4D method aims to go beyond the limits of previous methods. It proposes a combination of multidisciplinary analytical tools applied empirically to analyze agricultural supply chains in their context. It provides evidence-based analytical results allowing to identify enablers for strategic sustainable and inclusive interventions. However, to even better meet contextual exhaustiveness’s expectations and indicators’ robustness to lead to relevant interventions, we should insist on a stricter framing of contextual data collection processes.


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