Co-designing an effective undergraduate course for the appropriate management of medical emergencies in dental practice

Introduction/background: There is an expectation within the community and from professional bodies, that dentists will have the capacity to manage common adverse reactions and medical emergencies that may occur in a dental setting. The Australian Dental Council (2016) defines the specific and supporting threshold competencies expected of all Australian dental graduates including the ability to manage both dental and medical emergencies. However, it is widely recognized that without appropriate teaching methods, a significant proportion of dental graduates both locally and internationally feel poorly equipped to manage a medical emergency. Dentists are required to perform invasive and occasionally extensive oral procedures in a community-based setting on a diverse clientele. An ageing population coupled with advances in medical management and an increased burden of chronic disease means that clients may on occasion have significant co-morbidities or risk factors. Consequently, dental practitioners in Northern Australia report frequently encountering medical events in their daily practice. The emphasis on emergency management in a dental setting in Australia is currently on recognizing, pre-empting and treating clinical deterioration before it escalates to an emergency situation (Oral & Dental Expert Group, 2012) The JCU Bachelor of Dental Surgery prepares work-ready graduates for practice in regional, rural and remote areas. Students are required to be competent managing both dental and medical emergencies in clinical and community settings. Through co-design with dentists and simulation-qualified emergency educators, an authentic, scenario-based training course has been developed in accordance with current guidelines. This effectively enables dental students to respond appropriately to medical emergencies in the dental clinic. Aim: The aim of this presentation is to share the lessons learnt through five years of co-designing, delivering and assessing medical emergency competency for the JCU Bachelor of Dental Surgery students. Methods: Post-workshop questionnaires and qualitative data from debriefing staff and students have informed the current training methodology. Through applying an iterative, participatory action approach to the medical emergency training has enabled the co-design of a high fidelity, simulation program that embeds authentic scenarios into the clinical setting. The objective has been to consolidate students’ existing theoretical knowledge while providing practical skills and strategies that enhance teamwork, communication, confidence as well as competence. Discussion: Following ongoing review and evaluation, the use of high fidelity simulated patients and authentic scenarios have been found to be the most effective strategy for enabling undergraduate dentistry students to respond competently and confidently to patients who are medically compromised. The results support the transition from manikins to authentic scenarios within the clinical setting enacted by emergency educators skilled in simulation followed by comprehensive debriefing. This has equipped senior students with adequate theoretical and practical knowledge to feel prepared for appropriately managing common emergency situations independently or with minimal assistance when practising in diverse regional, rural and remote contexts

Modelling optional infinitive phenomena: A computational account of tense optionality in children’s speech

The Optional Infinitive hypothesis proposed by Wexler (1994) is a theory of children’s early grammatical development that can be used to explain a variety of phenomena in children’s early multi-word speech. However, Wexler’s theory attributes a great deal of abstract knowledge to the child on the basis of rather weak empirical evidence. In this paper we present a computational model of early grammatical development which simulates Optional Infinitive phenomena as a function of the interaction between a performance-limited distributional analyser and the statistical properties of the input. Our findings undermine the claim that Optional Infinitive phenomena require an abstract grammatical analysis

Modeling children’s case marking errors with MOSAIC

We present a computational model of early grammatical development which simulates case-marking errors in children’s early multi-word speech as a function of the interaction between a performance-limited distributional analyser and the statistical properties of the input. The model is presented with a corpus of maternal speech from which it constructs a network consisting of nodes which represent words or sequences of words present in the input. It is sensitive to the distributional properties of items occurring in the input and is able to create ‘generative’ links between words which occur frequently in similar contexts, building pseudo-categories. The only information received by the model is that present in the input corpus. After training, the model is able to produce child-like utterances, including case-marking errors, of which a proportion are rote-learned, but the majority are not present in the maternal corpus. The latter are generated by traversing the generative links formed between items in the network

Modelling children's negation errors using probabilistic learning in MOSAIC.

Cognitive models of language development have often been used to simulate the pattern of errors in children’s speech. One relatively infrequent error in English involves placing inflection to the right of a negative, rather than to the left. The pattern of negation errors in English is explained by Harris & Wexler (1996) in terms of very early knowledge of inflection on the part of the child. We present data from three children which demonstrates that although negation errors are rare, error types predicted not to occur by Harris & Wexler do occur, as well as error types that are predicted to occur. Data from MOSAIC, a model of language acquisition, is also presented. MOSAIC is able to simulate the pattern of negation errors in children’s speech. The phenomenon is modelled more accurately when a probabilistic learning algorithm is used

Episode

Fiction by Barbara Croker

Baptism at Bull Run

Valor in high definition An obituary for American innocence Okay. Here\u27s my perspective on book reviews. You don\u27t know me from Adam\u27s housecat, so why should you give a good golly-darn whether or not I like the book I\u27m reviewing? Well, you shouldn\u27t. So what I am going to do is...