Almaatouq et al. propose an integrative experiment design space combined with large samples for scientific advancement. We argue recent innovative designs combining closed-loop experiment designs and Bayesian optimisation allow for integrative experiments at an individual level during a single session, circumventing the necessity for large samples. This method can be applied across disciplines, including developmental and clinical research.

Providing nursing care for people with dementia residing in long-term care facilities poses specific challenges regarding pain practices. With underlying communication barriers unique to dementia pathologies, this population is often unable to communicate verbal sentiments and descriptions of pain. In turn, nurses caring for older persons with dementia have difficulty assessing, managing and treating pain. Objectivity is an imperative factor in healthcare pain practices; however, it is difficult to objectively evaluate someone who cannot accurately communicate their experience of pain. Therefore, (...) the authors believe that subjectivity is also an essential part of evaluating the person with dementia's experience of pain. In this critical reflection, the authors explore objectivity and subjectivity in relation to pain practices for dementia in long-term care. A historical summary of pain is provided outlining the evolution of objectivity and subjectivity related to pain practices. The authors discuss the complexities of assessing and managing pain and offer a new perspective about the role of objectivity (and co-existence of subjectivity) for nurses treating pain in the older adults with dementia. (shrink)

Research that has been sponsored by pharmaceutical, medical device and biotechnology companies is often presented at scientific and medical conferences. However, practices vary between organizations and it can be difficult to follow both individual conference requirements and good publication practice guidelines. Until now, no specific guidelines or recommendations have been available to describe best practice for conference presentations.This document was developed by a working group of publication professionals and uploaded to PeerJ Preprints for consultation prior to publication; an additional 67 (...) medical societies, medical conference sites and conference companies were also asked to comment. The resulting recommendations aim to complement current good publication practice and authorship guidelines, outline the general principles of best practice for conference presentations and provide recommendations around authorship, contributorship, financial transparency, prior publication and copyright, to conference organizers, authors and industry professionals.While the authors of this document recognize that individual conference guidelines should be respected, they urge organizers to consider authorship criteria and data transparency when designing submission sites and setting parameters around word/character count and content for abstracts. It is also important to recognize that conference presentations have different limitations to full journal publications, for example, in the case of limited audiences that necessitate refocused abstracts, or where lead authors do not speak the local language, and these have been acknowledged accordingly. The authors also recognize the need for further clarity regarding copyright of previously published abstracts and have made recommendations to assist with best practice.By following Good Practice for Conference Abstracts and Presentations: GPCAP recommendations, industry professionals, authors and conference organizers will improve consistency, transparency and integrity of publications submitted to conferences worldwide. (shrink)

_Purpose:_ In order to develop an evidence-based, sport-specific minimum impairment criteria (MIC) for the sport of vision-impaired (VI) shooting, this study aimed to determine the relative influence of losses in visual acuity (VA) and contrast sensitivity (CS) on shooting performance. Presently, VA but not CS is used to determine eligibility to compete in VI shooting. _Methods:_ Elite able-sighted athletes ( n = 27) shot under standard conditions with their habitual vision, and with their vision impaired by the use of simulation (...) spectacles (filters which reduce both VA and CS) and refractive blur (lenses which reduce VA with less effect on CS). Habitual shooting scores were used to establish a cut-off in order to determine when shooting performance was ‘below expected’ in the presence of vision impairment. Logistic regression and decision tree analyses were then used to assess the relationship between visual function and shooting performance. _Results:_ Mild reductions in VA and/or CS did not alter shooting performance, with greater reductions required for shooting performance to fall below habitual levels (below 87% of normalized performance). Stepwise logistic regression selected CS as the most significant predictor of shooting performance, with VA subsequently improving the validity of the model. In an unconstrained decision tree analysis, CS was selected as the sole criterion (80%) for predicting ‘below expected’ shooting score. _Conclusion:_ Shooting performance is better predicted by losses in CS than by VA. Given that it is not presently tested during classification, the results suggest that CS is an important measure to include in testing for the classification of vision impairment for athletes competing in VI shooting. (shrink)

Artificial intelligent (AI) systems used in medicine are often very reliable and accurate, but at the price of their being increasingly opaque. This raises the question whether a system’s opacity undermines the ability of medical doctors to acquire knowledge on the basis of its outputs. We investigate this question by focusing on a case in which a patient’s risk of recurring breast cancer is predicted by an opaque AI system. We argue that, given the system’s opacity, as well as the (...) possibility of malfunctioning AI systems, practitioners’ inability to check the correctness of their outputs, and the high stakes of such cases, the knowledge of medical practitioners is indeed undermined. They are lucky to form true beliefs based on the AI systems’ outputs, and knowledge is incompatible with luck. We supplement this claim with a specific version of the safety condition on knowledge, Safety*. We argue that, relative to the perspective of the medical doctor in our example case, his relevant beliefs could easily be false, and this despite his evidence that the AI system functions reliably. Assuming that Safety* is necessary for knowledge, the practitioner therefore doesn’t know. We address three objections to our proposal before turning to practical suggestions for improving the epistemic situation of medical doctors. (shrink)

Wenmackers and Romeijn (2016) formalize ideas going back to Shimony (1970) and Putnam (1963) into an open-minded Bayesian inductive logic, that can dynamically incorporate statistical hypotheses proposed in the course of the learning process. In this paper, we show that Wenmackers and Romeijn’s proposal does not preserve the classical Bayesian consistency guarantee of merger with the true hypothesis. We diagnose the problem, and offer a forward-looking open-minded Bayesians that does preserve a version of this guarantee.

Volker Kessler argues two points to Rudolf Bohren’s list of four areas where God becomes beautiful should be extended with a fifth one: mathematics and mathematics can be argued as a place where God becomes beautiful. In this response, we would like to argue that the extension of Bohren’s list that Kessler argues in favour of is superfluous and that Kessler makes a number of questionable assumptions about mathematics. By arguing against Kessler, we intend to make an interdisciplinary contribution to (...) the discussion about the relationship between mathematics and theology by pushing the debate into direction of a more careful consideration of mathematics as an area in which God’s beauty may become apparent.Contribution: Contributing to the interdisciplinary exploration of theology in HTS Teologiese Studies/Theological Studies, this article further develops the consideration of the fundamental theological topic of God, the beautiful and mathematics as it was proposed in this journal by Volker Kessler, by discussing it from a systematic theological and mathematical perspective. (shrink)

There is increasing criticism on the use of big data and algorithms in public governance. Studies revealed that algorithms may reinforce existing biases and defy scrutiny by public officials using them and citizens subject to algorithmic decisions and services. In response, scholars have called for more algorithmic transparency and regulation. These are useful, but ex post solutions in which the development of algorithms remains a rather autonomous process. This paper argues that co-design of algorithms with relevant stakeholders from government and (...) society is another means to achieve responsible and accountable algorithms that is largely overlooked in the literature. We present a case study of the development of an algorithmic tool to estimate the populations of refugee camps to manage the delivery of emergency supplies. This case study demonstrates how in different stages of development of the tool—data selection and pre-processing, training of the algorithm and post-processing and adoption—inclusion of knowledge from the field led to changes to the algorithm. Co-design supported responsibility of the algorithm in the selection of big data sources and in preventing reinforcement of biases. It contributed to accountability of the algorithm by making the estimations transparent and explicable to its users. They were able to use the tool for fitting purposes and used their discretion in the interpretation of the results. It is yet unclear whether this eventually led to better servicing of refugee camps. (shrink)

Background Relatively little information is available regarding the level of acceptance of evolution and knowledge about evolution in different educational settings in Europe. The aim of the present study is to fill this gap and provide a comprehensive overview of the current state of research regarding evolutionary knowledge and acceptance of students and teachers across Europe, based on a systematic literature review. -/- Results We identified 56 papers for the period 2010–2020, presenting results for 29 European countries. Both knowledge and (...) acceptance of evolution were assessed in 17 studies. Out of 13 instruments most commonly used in the literature, five have been used in the European context so far: ACORNS, CINS, I-SEA, KEE and MATE. Thirty-one other instruments were identified of which 16 were used in studies on knowledge and 15 in studies on acceptance. The extent of knowledge was hard to compare even within groups of the same education level due to the application of different instruments and assessment of different key concepts. Our results illustrate the persistence of misconceptions through all education levels. Comparing acceptance among different education levels and countries revealed a high diversity. However, a lack of evolution in curricula tended to be associated with rejection of evolution in some countries. European studies that investigated both acceptance of evolution and knowledge about evolution varied highly concerning the existence and strength of the relationship between these factors. However, some trends are visible, such as an increase of strength of the relationship the higher the education level. -/- Conclusions The present review highlights the lack of a standardized assessment of evolutionary knowledge and acceptance of evolution across Europe and, therefore, of reasonably comparable data. Moreover, the review revealed that only about one-third of all studies on acceptance and/or knowledge about evolution provided evidence for local validity and reliability. We suggest the use of assessment categories for both knowledge and acceptance instruments to allow for interpretation and comparison of sum scores among different sample groups. This, along with prospective comparative research based on similar samples, paves the way for future research aimed at overcoming current biases and inconsistencies in results. (shrink)