scholarly journals Reassessing “Praecox Feeling” in Diagnostic Decision Making in Schizophrenia: A Critical Review

2018 ◽  
Vol 45 (5) ◽  
pp. 966-970 ◽  
Author(s):  
Tudi Gozé ◽  
Marcin Moskalewicz ◽  
Michael A Schwartz ◽  
Jean Naudin ◽  
Jean-Arthur Micoulaud-Franchi ◽  
...  

AbstractThe “Praecox Feeling” (PF) is a classical concept referring to a characteristic feeling of bizarreness experienced by a psychiatrist while encountering a person with schizophrenia. Although the PF used to be considered a core symptom of the schizophrenia spectrum, it fell into disuse since the spread of operationalized diagnostic methods (Diagnostic and Statistical Manual of Mental Disorders/International Classification of Diseases systems). In contemporary research on schizophrenia, it remains largely unaddressed. This critical review investigates the evolution of the PF in historical and contemporary literature and presents an exhaustive overview of empirical evidence on its prevalence in clinical decision making, its reliability and validity. The review demonstrates that the PF is a real determinant of medical decision making in schizophrenia, although, without further research, there is not enough evidence to sustain its rehabilitation as a reliable and valid clinical criterion. PF-like experiences should not be opposed to any criteriological attitude in diagnosis and would be clinically useful if the conditions of descriptive precaution and rigorous epistemology are maintained. The aim of teaching clinical expertise is to transform this basic experience into a well-founded clinical judgment. Finally, the article discusses the possible relevance of the PF for basic science and clinical research according to a translational approach inspired by phenomenology.

2014 ◽  
Vol 2 (1) ◽  
pp. 71
Author(s):  
Mark Tonelli

In their call to develop a consistent, coherent and comprehensive notion of person-centered medicine, Miles and Mezzich have elucidated several specific challenges that need to be urgently addressed. One of these foundational tasks is the development of a more complete understanding of person-centered clinical decision-making. Miles and Mezzich note that while the emphasis on clinical research in evidence-based medicine has served to de-emphasize the importance of the individual patient, the alternative of patient-centered medicine has the potential to de-emphasize the judgment of the clinician by making unfettered patient choice paramount. A practice of medicine that reduces professional healers to an informational role only, one where they lay out potential interventions devoid of context and allow patients to choose from amongst them, undervalues clinical expertise and will clearly not lead to better outcomes. Person-centered medicine (PCM), then, must be able to develop and defend a model of clinical judgment and practice that strikes the correct balance between the science of medicine and the personal experience of the individual in search of care.


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):  
Fábio da Costa Carbogim ◽  
Larissa Bertacchini de Oliveira ◽  
Vilanice Alves de Araújo Püschel

ABSTRACT Objective: to analyze the concept of critical thinking (CT) in Rodger's evolutionary perspective. Method: documentary research undertaken in the Cinahl, Lilacs, Bdenf and Dedalus databases, using the keywords of 'critical thinking' and 'Nursing', without limitation based on year of publication. The data were analyzed in accordance with the stages of Rodger's conceptual model. The following were included: books and articles in full, published in Portuguese, English or Spanish, which addressed CT in the teaching and practice of Nursing; articles which did not address aspects related to the concept of CT were excluded. Results: the sample was made up of 42 works. As a substitute term, emphasis is placed on 'analytical thinking', and, as a related factor, decision-making. In order, the most frequent preceding and consequent attributes were: ability to analyze, training of the student nurse, and clinical decision-making. As the implications of CT, emphasis is placed on achieving effective results in care for the patient, family and community. Conclusion: CT is a cognitive skill which involves analysis, logical reasoning and clinical judgment, geared towards the resolution of problems, and standing out in the training and practice of the nurse with a view to accurate clinical decision-making and the achieving of effective results.


2018 ◽  
Vol 38 (5) ◽  
pp. 593-600
Author(s):  
Marco Boeri ◽  
Alan J. McMichael ◽  
Joseph P. M. Kane ◽  
Francis A. O’Neill ◽  
Frank Kee

Background. In discrete-choice experiments (DCEs), respondents are presented with a series of scenarios and asked to select their preferred choice. In clinical decision making, DCEs allow one to calculate the maximum acceptable risk (MAR) that a respondent is willing to accept for a one-unit increase in treatment efficacy. Most published studies report the average MAR for the whole sample, without conveying any information about heterogeneity. For a sample of psychiatrists prescribing drugs for a series of hypothetical patients with schizophrenia, this article demonstrates how heterogeneity accounted for in the DCE modeling can be incorporated in the derivation of the MAR. Methods. Psychiatrists were given information about a group of patients’ responses to treatment on the Positive and Negative Syndrome Scale (PANSS) and the weight gain associated with the treatment observed in a series of 26 vignettes. We estimated a random parameters logit (RPL) model with treatment choice as the dependent variable. Results. Results from the RPL were used to compute the MAR for the overall sample. This was found to be equal to 4%, implying that, overall, psychiatrists were willing to accept a 4% increase in the risk of an adverse event to obtain a one-unit improvement of symptoms – measured on the PANSS. Heterogeneity was then incorporated in the MAR calculation, finding that MARs ranged between 0.5 and 9.5 across the sample of psychiatrists. Limitations. We provided psychiatrists with hypothetical scenarios, and their MAR may change when making decisions for actual patients. Conclusions. This analysis aimed to show how it is possible to calculate physician-specific MARs and to discuss how MAR heterogeneity could have implications for medical practice.


Author(s):  
Ken J. Farion ◽  
Michael J. Hine ◽  
Wojtek Michalowski ◽  
Szymon Wilk

Clinical decision-making is a complex process that is reliant on accurate and timely information. Clinicians are dependent (or should be dependent) on massive amounts of information and knowledge to make decisions that are in the best interest of the patient. Increasingly, information technology (IT) solutions are being used as a knowledge transfer mechanism to ensure that clinicians have access to appropriate knowledge sources to support and facilitate medical decision making. One particular class of IT that the medical community is showing increased interest in is clinical decision support systems (CDSSs).


2018 ◽  
Vol 13 (3) ◽  
pp. 151-158 ◽  
Author(s):  
Niels Lynøe ◽  
Gert Helgesson ◽  
Niklas Juth

Clinical decisions are expected to be based on factual evidence and official values derived from healthcare law and soft laws such as regulations and guidelines. But sometimes personal values instead influence clinical decisions. One way in which personal values may influence medical decision-making is by their affecting factual claims or assumptions made by healthcare providers. Such influence, which we call ‘value-impregnation,’ may be concealed to all concerned stakeholders. We suggest as a hypothesis that healthcare providers’ decision making is sometimes affected by value-impregnated factual claims or assumptions. If such claims influence e.g. doctor–patient encounters, this will likely have a negative impact on the provision of correct information to patients and on patients’ influence on decision making regarding their own care. In this paper, we explore the idea that value-impregnated factual claims influence healthcare decisions through a series of medical examples. We suggest that more research is needed to further examine whether healthcare staff’s personal values influence clinical decision-making.


Diagnosis ◽  
2014 ◽  
Vol 1 (1) ◽  
pp. 23-27 ◽  
Author(s):  
Pat Croskerry

AbstractPeople diagnose themselves or receive advice about their illnesses from a variety of sources ranging from their family or friends, alternate medicine, or through conventional medicine. In all cases, the diagnosing mechanism is the human brain which normally operates under the influence of a variety of biases. Most, but not all biases, reside in intuitive decision making, and no individual or group is immune from them. Two biases in particular, bias blind spot and myside bias, have presented obstacles to accepting the impact of bias on medical decision making. Nevertheless, there is now a widespread appreciation of the important role of bias in the majority of medical disciplines. The dual process model of decision making now seems well accepted, although a polarization of opinions has arisen with some arguing the merits of intuitive approaches over analytical ones and vice versa. We should instead accept that it is not one mode or the other that enables well-calibrated thinking but the discriminating use of both. A pivotal role for analytical thinking lies in its ability to allow decision makers the means to detach from the intuitive mode to mitigate bias; it is the gatekeeper for the final diagnostic decision. Exploring and cultivating such debiasing initiatives should be seen as the next major research area in clinical decision making. Awareness of bias and strategies for debiasing are important aspects of the critical thinker’s armamentarium. Promoting critical thinking in undergraduate, postgraduate and continuing medical education will lead to better calibrated diagnosticians.


2019 ◽  
Vol 43 (1 suppl 1) ◽  
pp. 513-524
Author(s):  
Álisson Oliveira dos Santos ◽  
Alexandre Sztajnberg ◽  
Tales Mota Machado ◽  
Daniel Magalhães Nobre ◽  
Adriano Neves de Paula e Souza ◽  
...  

ABSTRACT The medical education for clinical decision-making has undergone changes in recent years. Previously supported by printed material, problem solving in clinical practice has recently been aided by digital tools known as summaries platforms. Doctors and medical students have been using such tools from questions found in practice scenarios. These platforms have the advantage of high-quality, evidence-based and always up-to-date content. Its popularization was mainly due to the rise of the internet use and, more recently, of mobile devices such as tablets and smartphones, facilitating their use in clinical practice. Despite this platform is widely available, the most of them actually present several access barriers as costs, foreign language and not be able to Brazilian epidemiology. A free national platform of evidence-based medical summaries was proposed, using the crowdsourcing concept to resolve those barriers. Furthermore, concepts of gamification and content evaluation were implemented. Also, there is the possibility of evaluation by the users, who assigns note for each content created. The platform was built with modern technological tools and made available for web and mobile application. After development, an evaluation process was conducted by researchers to attest to the valid of content, usability, and user satisfying. Consolidated questionnaires and evaluation tools by the literature were applied. The process of developing the digital platform fostered interdisciplinarity, from the involvement of medical and information technology professionals. The work also allowed the reflection on the innovative educational processes, in which the learning from real life problems and the construction of knowledge in a collaborative way are integrated. The assessment results suggest that platform can be real alternative form the evidence-based medical decision-making.


2011 ◽  
Vol 1 (1) ◽  
pp. 42-60 ◽  
Author(s):  
Luca Anselma ◽  
Alessio Bottrighi ◽  
Gianpaolo Molino ◽  
Stefania Montani ◽  
Paolo Terenziani ◽  
...  

Knowledge-based clinical decision making is one of the most challenging activities of physicians. Clinical Practice Guidelines are commonly recognized as a useful tool to help physicians in such activities by encoding the indications provided by evidence-based medicine. Computer-based approaches can provide useful facilities to put guidelines into practice and to support physicians in decision-making. Specifically, GLARE (GuideLine Acquisition, Representation and Execution) is a domain-independent prototypical tool providing advanced Artificial Intelligence techniques to support medical decision making, including what-if analysis, temporal reasoning, and decision theory analysis. The paper describes such facilities considering a real-world running example and focusing on the treatment of therapeutic decisions.


1991 ◽  
Vol 11 (4_suppl) ◽  
pp. S2-S14 ◽  
Author(s):  
Edward H. Shortliffe

There are important scientific and pragmatic synergies between the medical decision making field and the emerging discipline of medical informatics. In the 1970s, the field of medicine forced clinically oriented artificial intelligence (AI) researchers to develop ways to manage explicit statements of uncertainty in expert systems. Classic probability theory was considered and discussed, but it tended to be abandoned because of complexities that limited its use. In medical AI systems, uncertainty was handled by a variety of ad hoc models that simulated probabilistic considerations. To illustrate the scientific interactions between the fields, the author describes recent work in his laboratory that has attempted to show that formal normative models based on probability and decision theory can be practically melded with AI methods to deliver effective advisory tools. In addition, the practical needs of decision makers and health policy planners are increasingly necessitating collaborative efforts to develop a computing and communications infrastructure for the decision making and informatics communities. This point is illustrated with an example drawn from outcomes management research.


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