Mastering Stress: Mental Skills and Emotional Regulation for Surgical Performance and Life

Mental skills and emotional regulation training are gaining acceptance in surgical education as vital elements of surgeon development. These skills can effectively enhance technical skill development, improve well-being, and promote career longevity. There is evidence emerging in the surgical education literature to support the incorporation of mental skills and emotional regulation training curricula in residency training. In this study, we present the existing evidence supporting the use of this training with high performers to reduce stress and optimize well-being and performance. We also consider the recent research emerging in surgical education that offers validity evidence for use of mental skills training with surgeons. Finally, we provide a framework to guide the incorporation of these skills throughout the career of a surgeon and suggest methods to promote the development of mental skills training efforts nationally

Rapid online assessment of reading ability

Published18 March 2021An accurate model of the factors that contribute to individual differences in reading ability depends on data collection in large, diverse and representative samples of research participants. However, that is rarely feasible due to the constraints imposed by standardized measures of reading ability which require test administration by trained clinicians or researchers. Here we explore whether a simple, two-alternative forced choice, time limited lexical decision task (LDT), self-delivered through the webbrowser, can serve as an accurate and reliable measure of reading ability. We found that performance on the LDT is highly correlated with scores on standardized measures of reading ability such as the Woodcock-Johnson Letter Word Identification test (r = 0.91, disattenuated r = 0.94). Importantly, the LDT reading ability measure is highly reliable (r = 0.97). After optimizing the list of words and pseudowords based on item response theory, we found that a short experiment with 76 trials (2–3 min) provides a reliable (r = 0.95) measure of reading ability. Thus, the self-administered, Rapid Online Assessment of Reading ability (ROAR) developed here overcomes the constraints of resourceintensive, in-person reading assessment, and provides an efficient and automated tool for effective online research into the mechanisms of reading (dis)ability.We would like to thank the Pavlovia and PsychoPy team for their support on the browser-based experiments. This work was funded by NIH NICHD R01HD09586101, research grants from Microsoft and Jacobs Foundation Research Fellowship to J.D.Y

Gaps in knowledge relevant to the “guidelines for limiting exposure to time-varying electric and magnetic fields (1 Hz-100 kHz)"

Sources of low-frequency fields are widely found in modern society. All wires or devices carrying or using electricity generate extremely low frequency (ELF) electric fields (EFs) and magnetic fields (MFs), but they decline rapidly with distance to the source. High magnetic flux densities are usually found in the vicinity of power lines and close to equipment using strong electrical currents, but can also be found in buildings with unbalanced return currents, or indoor transformer stations. For decades, epidemiological as well as experimental studies have addressed possible health effects of exposure to ELF-MFs. The main goal of ICNIRP is to protect people and the environment from detrimental exposure to all forms of non-ionizing radiation (NIR). To this end, ICNIRP provides advice and guidance by developing and disseminating exposure guidelines based on the available scientific research. Research in the low-frequency range began more than 40 years ago, and there is now a large body of literature available on which ICNIRP set its protection guidelines. A review of the literature has been carried out to identify possible relevant knowledge gaps, and the aim of this statement is to describe data gaps in research that would, if addressed, assist ICNIRP in further developing guidelines and setting revised recommendations on limiting exposure to electric and magnetic fields. It is articulated in two parts: the main document, which reviews the science related to LF data gaps, and the annex, which explains the methodology used to identify the data gaps

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets

Malignant Tumors of the Central Nervous System

Malignant tumors of the central nervous system in adults comprise a heterogeneous group of malignancies, the largest subgroups comprising astrocytomas, ependymomas, and oligodendrogliomas. Glioblastomas are the most common tumor type, and they have dismal prognosis. Due to differences in cell type of origin, as well as pathogenesis, it is plausible that their etiology also differs between tumor types. The etiology of malignant CNS tumors is largely unknown and no occupational risk factors have been definitively identified. High doses of ionizing radiation increase the risk, but in occupational settings the dose levels appear too small to result in discernible excesses. Several studies have assessed possible effect of extremely low frequency and radiofrequency electromagnetic fields, but the results are inconsistent. Increased brain tumor risk has been reported in agricultural workers, but no specific exposure has been linked to them. Pesticides have been analyzed in several studies without showing a clear increase in risk.acceptedVersionPeer reviewe