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Global collaboration in teaching root cause analysis with healthcare professional students
No full textPurposeThe purpose of this paper is to describe an example of how universities can develop unique synchronous educational opportunities to engage students in an online environment, especially since study abroad opportunities have slowed or halted due to the COVID-19 pandemic crisis.Design/methodology/approachTwo affiliated universities, in the United States and Scotland, selected a simulated root cause analysis (RCA) of a medical error for a collaborative activity.FindingsTogether the students analyzed the event within assumed roles of healthcare professions in a systematic way using the “Swiss Cheese Model,” identified opportunities for improvement, debriefed using the Promoting Excellence and Reflective Learning in Simulation (PEARLS) method and submitted a reflective assignment. The RCA resulted in several process improvement suggestions and positive feedback from the participants.Research limitations/implicationsThe approach was for graduate students from two affiliated universities, in the United States and Scotland, to simulate a RCA of a medical error as a collaborative activity.Practical implicationsThis example using simulation of healthcare roles demonstrates the application of international collaboration, problem-solving models and methodologies and recognition of the similarities and differences between the United Kingdom and the United States approaches to patient safety. Especially with the ongoing COVID-19 pandemic, the students' ability to internationally collaborate can be limited without such unique opportunities.Social implicationsThe students were provided with a side-by-side comparison of the patient safety efforts in each country and written and didactic material about an RCA and the Swiss cheese model.Originality/valueStudents come from different perspectives of health services administration, nursing and nursing leadership from Scotland and the United States to solve patient safety problems
Games Futures I
Get PDFGames Futures collect short opinion pieces by industry and research veterans and new voices envisioning possible and desirable futures and needs for games and playable media. This inaugural series features eight of over thirty pieces
Which COVID-19 information really impacts stock markets?
No full textInformation about the COVID-19 pandemic abounds, but which COVID-19 data actually impacts stock prices? We investigate which measures of COVID-19 matter most by applying elastic net regression for measure selection using a sample of the 35 largest stock markets. Out of 24 measures, COVID-19 related Google search trends, the stringency of government responses and media hype prevail during the height of the COVID-19 crisis. These measures proxy for COVID-19 related uncertainty, the economic impact of lockdowns and panic-driven media attention, respectively, summarizing key aspects of COVID-19 that move stock markets. Moreover, geographical proximity to the virus’s outbreak and a country’s development level also matter in terms of impact
Patient, family members and community pharmacists' views of a proposed overdose prevention intervention delivered in community pharmacies for patients prescribed high‐strength opioids for chronic non‐cancer pain: An explorative intervention development study
Get PDFIntroductionDespite opioid prescribing for chronic non-cancer pain (CNCP) having limited therapeutic benefits, recent evidence indicates significant increases in the prescribing of high-strength opioids for individuals with CNCP. Patients prescribed opioids for CNCP have overdose risk factors but generally have low opioid overdose awareness and low perceptions of risk related to prescribed opioids. Currently, there are few bespoke overdose prevention resources for this group.MethodsThis qualitative study investigated views on a naloxone intervention for people prescribed high-strength opioids for CNCP delivered via community pharmacies. The intervention included overdose risk awareness and naloxone training and provision. Interviews were conducted with eight patients, four family members and two community pharmacists. Participants were convenience sampled and recruited through networks within the Scottish pain community. The Framework approach was used to analyse findings.ResultsAll participants had positive attitudes towards the intervention, but patients and family members considered risk of overdose to be very low. Three themes were identified: potential advantages of the intervention; potential barriers to the intervention; and additional suggestions and feedback about the intervention. Advantages included the intervention providing essential overdose information for CNCP patients. Barriers included resource and time pressures within community pharmacies.Discussion and ConclusionWhile patients had low overdose knowledge and did not see themselves as being at risk of opioid overdose, they were receptive to naloxone use and positive about the proposed intervention. A feasibility trial is merited to further investigate how the intervention would be experienced within community pharmacy settings
The effect of a game-based mobile app “MyHeartMate” to promote lifestyle change in coronary disease patients: a randomised controlled trial
Get PDFAimsSecondary prevention reduces coronary heart disease (CHD) progression. Traditional prevention programs including cardiac rehabilitation are under-accessed, which smartphone apps may overcome. To evaluate the effect of a game-based mobile app intervention (MyHeartMate) to improve cardiovascular risk factors and lifestyle behaviours.Methods and resultsSingle-blind randomized trial of CHD patients in Sydney, 2017–2021. Intervention group were provided the MyHeartMate app for 6 months. Co-designed features included an avatar of the patient’s heart and tokens earned by risk factor work (tracking, challenges, and quizzes). The control group received usual care. Primary outcome was self-reported physical activity [metabolic equivalents (METs), Global Physical Activity Questionnaire] and secondary outcomes included lipid levels, blood pressure (BP), body mass index, and smoking. Pre-specified sample size was achieved (n = 390), age 61.2 ± 11.5 years; 82.5% men and 9.2% current smokers. At 6 months, adjusted for baseline levels, the intervention group achieved more physical activity than control (median difference 329 MET mins/wk), which was not statistically significant (95% CI −37.4, 696; P = 0.064). No differences occurred between groups on secondary outcomes except for lower triglyceride levels in the intervention [mean difference −0.3 (95% CI −0.5, −0.1 mmoL/L, P = 0.004)]. Acceptability was high: 94.8% of intervention participants engaged by tracking exercise or BP and completing missions; 26.8% continued to engage for ≥30 days. Participants (n = 14) reported the app supported tracking behaviours and risk factors, reinforcing and improving self-care confidence, and decreasing anxiety.ConclusionA game-based app proved highly acceptable for patients with CHD but did not improve risk factors or lifestyle behaviours other than triglyceride levels
Understanding collaboration patterns on funded research projects: A network analysis
Get PDFThis paper provides an examination of inter-organizational collaboration in the UK research system. Data are collected on organizational collaboration on projects funded by four key UK research councils: Arts and Humanities Research Council, Economic and Social Research Council, Engineering and Physical Sciences Research Council, and Biotechnology and Biological Sciences Research Council. The organizational partnerships include both academic and nonacademic institutions. A collaboration network is created for each research council, and an exponential random graph model is applied to inform on the mechanisms underpinning collaborative tie formation on research council-funded projects. We find that in the sciences, collaborative patterns are much more hierarchical and concentrated in a small handful of actors compared to the social sciences and humanities projects. Institutions that are members of the elite Russell Group (a set of 24 high-ranking UK universities) are much more likely to be involved in collaborations across research councils
An efficient message passing algorithm for decentrally controlling complex systems
No full textThis paper proposes a decentralised stochastic control framework for a class of large-scale and complex dynamic networks. The proposed framework describes a decentralised probabilistic control and message passing architecture of mutually interacting quasi-independent subsystems. Within this framework, the outputs of the subsystems are communicated back to topologically-connected neighbours through output probabilistic message passing. This communication approach constitutes the main contribution of the current paper and allow the achievement of the global system goal. The proposed framework reduces the amount of communication required given the low dimensionality of the output space compared to the state space. The updated knowledge through the output message passing is then applied to induce a fully probabilistic local control strategy affecting only the local subsystem. Finally, a numerical example is presented to illustrate the effectiveness and usefulness of our novel proposed framework
Morpho-evolution with learning using a controller archive as an inheritance mechanism
Get PDFMost work in evolutionary robotics centres on evolving a controller for a fixed body-plan. However, previous studiessuggest that simultaneously evolving both controller and body-plan could open up many interesting possibilities. However, thejoint optimisation of body-plan and control via evolutionaryprocesses can be challenging in rich morphological spaces. Thisis because offspring can have body-plans that are very differentfrom either of their parents, leading to a potential mismatchbetween the structure of an inherited neural controller and thenew body. To address this, we propose a framework that combinesan evolutionary algorithm to generate body-plans and a learning algorithm to optimise the parameters of a neural controller. The topology of this controller is created once the body-plan of each offspring has been generated. The key novelty of the approach is to add an external archive for storing learned controllers that map to explicit ‘types’ of robots (where this is defined with respect to the features of the body-plan). By initiating learning froma controller with an appropriate structure inherited from thearchive, rather than from a randomly initialised one, we show that both the speed and magnitude of learning increases over time when compared to an approach that starts from scratch, using two tasks and three environments. The framework also provides new insights into the complex interactions between evolution and learnin
The End of the 90s in Porochista Khakpour's The Last Illusion, Rachel Kushner's The Mars Room and Ottessa Moshfegh’s My Year of Rest and Relaxation
Get PDFThis article argues that three contemporary novels – Porochista Khakpour's The Last Illusion (2014), Rachel Kushner's The Mars Room (2017), and Ottessa Moshfegh’s My Year of Rest and Relaxation (2018) – offer correctives to prevalent histories of the American 1990s that depict this period as a time of stability, tolerance, and optimism. These novels offer specific vectors of critique, attending to the advance of social and cultural forms of neoliberalism, popular notions of the “alternative” or liberal 90s, and address a sequence of ruptures and social turbulence preceding “9/11” – often seen as the abrupt conclusion of the “long 90s.” Additionally, the historical narratives of these novels each build in depictions of the September 11 attacks, which decenter them and question the exceptionalization of this event. I argue for the value in reading these novels together and demonstrate how they speak to and mirror each other in productive ways
Distributed Event-triggered Bipartite Consensus for Multi-agent Systems Against Injection Attacks
Get PDFThis paper studies fully distributed data-driven problems for nonlinear discrete-time multi-agent systems (MASs) with fixed and switching topologies preventing injection attacks. We first develop an enhanced compact form dynamic linearization model by applying the designed distributed bipartite combined measurement error function of the MASs. Then, a fully distributed event-triggered bipartite consensus (DETBC) framework is designed, where the dynamics information of MASs is no longer needed. Meanwhile, the restriction of the topology of the proposed DETBC method is further relieved. To prevent the MASs from injection attacks, neural network-based detection and compensation schemes are developed. Rigorous convergence proof is presented that the bipartite consensus error is ultimately boundedness. Finally, the effectiveness of the designed method is verified through simulations and experiment
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