A behavioural study of obedience in health professional students.

Interprofessional Education and Collaborative Practice (IPECP) is a field of study suggested to improve team functioning and patient safety. However, even interprofessional teams are susceptible to group pressures which may inhibit speaking up (positive deviance). Obedience is one group pressure that can inhibit positive deviance leading to negative patient outcomes. To examine the influence of obedience to authority in an interprofessional setting, an experimental simulated clinical scenario was conducted with Respiratory Therapy (RT) (n = 40) and Advanced Care Paramedic (ACP) (n = 20) students. In an airway management scenario, it was necessary for students to challenge an authority, a senior anesthesiologist, to prevent patient harm. In a 2 × 2 design cognitive load and an interventional writing task designed to increase positive deviance were tested. The effect of individual characteristics, including Moral Foundations, and displacement of responsibility were also examined. There was a significant effect for profession and cognitive load: RT students demonstrated lower levels of positive deviance in the low cognitive load scenario than students in other conditions. The writing task did not have a significant effect on RT or ACP students' behaviour. The influence of Moral Foundations differed from expectations, In Group Loyalty was selected as a negative predictor of positive deviance while Respect for Authority was not. Displacement of responsibility was influential for some participants thought not for all. Other individual variables were identified for further investigation. Observational analysis of the simulation videos was conducted to obtain further insight into student behaviour in a compliance scenario. Individual differences, including experience, should be considered when providing education and training for positive deviance. Simulation provides an ideal setting to use compliance scenarios to train for positive deviance and for experimentation to study interprofessional team behaviour.

Impact of the stringency of lockdown measures on covid-19: A theoretical model of a pandemic.

BACKGROUND: How effective have lockdowns been at reducing the covid-19 infection and mortality rates? Lockdowns influence contact among persons within or between populations including restricting travel, closing schools, prohibiting public gatherings, requiring workplace closures, all designed to slow the contagion of the virus. The purpose of the present study was to assess the impact of lockdown measures on the spread of covid-19 and test a theoretical model of the covid-19 pandemic employing structural equation modelling. METHODS: Lockdown variables, population demographics, mortality rates, infection rates, and health were obtained for eight countries: Austria, Belgium, France, Germany, Italy, Netherlands, Spain, and the United Kingdom. The dataset, owid-covid-data.csv, was downloaded on 06/01/2020 from: https://github.com/owid/covid-19-data/tree/master/public/data. Infection spread and mortality data were depicted as logistic growth and analyzed with stepwise multiple regression. The overall structure of the covid-19 data was explored through factor analyses leading to a theoretical model that was tested using latent variable path analysis. RESULTS: Multiple regression indicated that the time from lockdown had a small but significant effect (ß = 0.112, p< 0.01) on reducing the number of cases per million. The stringency index produced the most important effect for mortality and infection rates (ß = 0.588,ß = 0.702, ß = 0.518, ß = 0.681; p< 0.01). Exploratory and confirmatory analyses resulted in meaningful and cohesive latent variables: 1) Mortality, 2) Infection Spread, 3) Pop Health Risk, and 4) Health Vulnerability (Comparative Fit Index = 0.91; Standardized Root Mean Square Residual = 0.08). DISCUSSION: The stringency index had a large impact on the growth of covid-19 infection and mortality rates as did percentage of population aged over 65, median age, per capita GDP, diabetes prevalence, cardiovascular death rates, and ICU hospital beds per 100K. The overall Latent Variable Path Analysis is theoretically meaningful and coherent with acceptable fit indices as a model of the covid-19 pandemic.