Emergency physician attitudes towards illness verification (sick notes).

INTRODUCTION: Emergency physicians frequently provide care for patients who are experiencing viral illnesses and may be asked to provide verification of the patient's illness (a sick note) for time missed from work. Exclusion from work can be a powerful public health measure during epidemics; both legislation and physician advice contribute to patients' decisions to recover at home. METHODS: We surveyed Canadian Association of Emergency Physicians members to determine what impacts sick notes have on patients and the system, the duration of time off work that physicians recommend, and what training and policies are in place to help providers. Descriptive statistics from the survey are reported. RESULTS: A total of 182 of 1524 physicians responded to the survey; 51.1% practice in Ontario. 76.4% of physicians write at least one sick note per day, with 4.2% writing 5 or more sick notes per day. Thirteen percentage of physicians charge for a sick note (mean cost $22.50). Patients advised to stay home for a median of 4 days with influenza and 2 days with gastroenteritis and upper respiratory tract infections. 82.8% of physicians believe that most of the time, patients can determine when to return to work. Advice varied widely between respondents. 61% of respondents were unfamiliar with sick leave legislation in their province and only 2% had received formal training about illness verification. CONCLUSIONS: Providing sick notes is a common practice of Canadian Emergency Physicians; return-to-work guidance is variable. Improved physician education about public health recommendations and provincial legislation may strengthen physician advice to patients.

A Primer on Constructing Plasticity Phenotypes to Classify Experience-Dependent Development of the Visual Cortex.

Many neural mechanisms regulate experience-dependent plasticity in the visual cortex (V1), and new techniques for quantifying large numbers of proteins or genes are transforming how plasticity is studied into the era of big data. With those large data sets comes the challenge of extracting biologically meaningful results about visual plasticity from data-driven analytical methods designed for high-dimensional data. In other areas of neuroscience, high-information content methodologies are revealing more subtle aspects of neural development and individual variations that give rise to a richer picture of brain disorders. We have developed an approach for studying V1 plasticity that takes advantage of the known functions of many synaptic proteins for regulating visual plasticity. We use that knowledge to rebrand protein measurements into plasticity features and combine those into a plasticity phenotype. Here, we provide a primer for analyzing experience-dependent plasticity in V1 using example R code to identify high-dimensional changes in a group of proteins. We describe using PCA to classify high-dimensional plasticity features and use them to construct a plasticity phenotype. In the examples, we show how to use this analytical framework to study and compare experience-dependent development and plasticity of V1 and apply the plasticity phenotype to translational research questions. We include an R package "PlasticityPhenotypes" that aggregates the coding packages and custom code written in RStudio to construct and analyze plasticity phenotypes.