How to communicate with patients about future illness progression and end of life: a systematic review

Background: Conversation and discourse analytic research has yielded important evidence about skills needed for effective, sensitive communication with patients about illness progression and end of life. Objectives To: Locate and synthesise observational evidence about how people communicate about sensitive future matters; Inform practice and policy on how to provide opportunities for talk about these matters; Identify evidence gaps. Design: Systematic review of conversation/ discourse analytic studies of recorded interactions in English, using a bespoke appraisal approach and aggregative synthesis. Results: 19 publications met the inclusion criteria. We summarised findings in terms of eight practices: fishing questions - open questions seeking patients’ perspectives (5/19); indirect references to difficult topics (6/19); linking to what a patient has already said — or noticeably not said (7/19); hypothetical questions (12/19); framing difficult matters as universal or general (4/19); conveying sensitivity via means other than words, for example, hesitancy, touch (4/19); encouraging further talk using means other than words, for example, long silences (2/19); and steering talk from difficult/negative to more optimistic aspects (3/19). Conclusions: Practices vary in how strongly they encourage patients to engage in talk about matters such as illness progression and dying. Fishing questions and indirect talk make it particularly easy to avoid engaging — this may be appropriate in some circumstances. Hypothetical questions are more effective in encouraging on- topic talk, as is linking questions to patients’ cues. Shifting towards more ‘optimistic’ aspects helps maintain hope but closes off further talk about difficulties: practitioners may want to delay doing so. There are substantial gaps in evidence

Strong Baselines for Simple Question Answering over Knowledge Graphs with and without Neural Networks

We examine the problem of question answering over knowledge graphs, focusing on simple questions that can be answered by the lookup of a single fact. Adopting a straightforward decomposition of the problem into entity detection, entity linking, relation prediction, and evidence combination, we explore simple yet strong baselines. On the popular SimpleQuestions dataset, we find that basic LSTMs and GRUs plus a few heuristics yield accuracies that approach the state of the art, and techniques that do not use neural networks also perform reasonably well. These results show that gains from sophisticated deep learning techniques proposed in the literature are quite modest and that some previous models exhibit unnecessary complexity.Comment: Published in NAACL HLT 201

Improved Neural Relation Detection for Knowledge Base Question Answering

Relation detection is a core component for many NLP applications including Knowledge Base Question Answering (KBQA). In this paper, we propose a hierarchical recurrent neural network enhanced by residual learning that detects KB relations given an input question. Our method uses deep residual bidirectional LSTMs to compare questions and relation names via different hierarchies of abstraction. Additionally, we propose a simple KBQA system that integrates entity linking and our proposed relation detector to enable one enhance another. Experimental results evidence that our approach achieves not only outstanding relation detection performance, but more importantly, it helps our KBQA system to achieve state-of-the-art accuracy for both single-relation (SimpleQuestions) and multi-relation (WebQSP) QA benchmarks.Comment: Accepted by ACL 2017 (updated for camera-ready

Quantifying the impact and relevance of scientific research

Qualitative and quantitative methods are being developed to measure the impacts of research on society, but they suffer from serious drawbacks associated with linking a piece of research to its subsequent impacts. We have developed a method to derive impact scores for individual research publications according to their contribution to answering questions of quantified importance to end users of research. To demonstrate the approach, here we evaluate the impacts of research into means of conserving wild bee populations in the UK. For published papers, there is a weak positive correlation between our impact score and the impact factor of the journal. The process identifies publications that provide high quality evidence relating to issues of strong concern. It can also be used to set future research agendas

Evidence-Based Dialogue Maps as a research tool to evaluate the quality of school pupils’ scientific argumentation

This pilot study focuses on the potential of Evidence-based Dialogue Mapping as a participatory action research tool to investigate young teenagers’ scientific argumentation. Evidence-based Dialogue Mapping is a technique for representing graphically an argumentative dialogue through Questions, Ideas, Pros, Cons and Data. Our research objective is to better understand the usage of Compendium, a Dialogue Mapping software tool, as both (1) a learning strategy to scaffold school pupils’ argumentation and (2) as a method to investigate the quality of their argumentative essays. The participants were a science teacher-researcher, a knowledge mapping researcher and 20 pupils, 12-13 years old, in a summer science course for “gifted and talented” children in the UK. This study draws on multiple data sources: discussion forum, science teacher-researcher’s and pupils’ Dialogue Maps, pupil essays, and reflective comments about the uses of mapping for writing. Through qualitative analysis of two case studies, we examine the role of Evidence-based Dialogue Maps as a mediating tool in scientific reasoning: as conceptual bridges for linking and making knowledge intelligible; as support for the linearisation task of generating a coherent document outline; as a reflective aid to rethinking reasoning in response to teacher feedback; and as a visual language for making arguments tangible via cartographic conventions

Comment on “Temporal and spatial variation in harbor seal (Phoca vitulina L.) roar calls from southern Scandinavia” [J. Acoust. Soc. Am. 141, 1824-1834 (2017)]

In their recent article, Sabinsky and colleagues investigated heterogeneity in harbor seals' vocalizations. The authors found seasonal and geographical variation in acoustic parameters, warning readers that recording conditions might account for some of their results. This paper expands on the temporal aspect of the encountered heterogeneity in harbor seals' vocalizations. Temporal information is the least susceptible to variable recording conditions. Hence geographical and seasonal variability in roar timing constitutes the most robust finding in the target article. In pinnipeds, evidence of timing and rhythm in the millisecond range—as opposed to circadian and seasonal rhythms—has theoretical and interdisciplinary relevance. In fact, the study of rhythm and timing in harbor seals is particularly decisive to support or confute a cross-species hypothesis, causally linking the evolution of vocal production learning and rhythm. The results by Sabinsky and colleagues can shed light on current scientific questions beyond pinniped bioacoustics, and help formulate empirically testable predictions

The source ambiguity problem: Distinguishing the effects of grammar and processing on acceptability judgments

Judgments of linguistic unacceptability may theoretically arise from either grammatical deviance or significant processing difficulty. Acceptability data are thus naturally ambiguous in theories that explicitly distinguish formal and functional constraints. Here, we consider this source ambiguity problem in the context of Superiority effects: the dispreference for ordering a wh-phrase in front of a syntactically “superior” wh-phrase in multiple wh-questions, e.g., What did who buy? More specifically, we consider the acceptability contrast between such examples and so-called D-linked examples, e.g., Which toys did which parents buy? Evidence from acceptability and self-paced reading experiments demonstrates that (i) judgments and processing times for Superiority violations vary in parallel, as determined by the kind of wh-phrases they contain, (ii) judgments increase with exposure, while processing times decrease, (iii) reading times are highly predictive of acceptability judgments for the same items, and (iv) the effects of the complexity of the wh-phrases combine in both acceptability judgments and reading times. This evidence supports the conclusion that D-linking effects are likely reducible to independently motivated cognitive mechanisms whose effects emerge in a wide range of sentence contexts. This in turn suggests that Superiority effects, in general, may owe their character to differential processing difficulty