Differences in Narrative Language in Evaluations of Medical Students by Gender and Under-represented Minority Status.

BACKGROUND: In varied educational settings, narrative evaluations have revealed systematic and deleterious differences in language describing women and those underrepresented in their fields. In medicine, limited qualitative studies show differences in narrative language by gender and under-represented minority (URM) status. OBJECTIVE: To identify and enumerate text descriptors in a database of medical student evaluations using natural language processing, and identify differences by gender and URM status in descriptions. DESIGN: An observational study of core clerkship evaluations of third-year medical students, including data on student gender, URM status, clerkship grade, and specialty. PARTICIPANTS: A total of 87,922 clerkship evaluations from core clinical rotations at two medical schools in different geographic areas. MAIN MEASURES: We employed natural language processing to identify differences in the text of evaluations for women compared to men and for URM compared to non-URM students. KEY RESULTS: We found that of the ten most common words, such as "energetic" and "dependable," none differed by gender or URM status. Of the 37 words that differed by gender, 62% represented personal attributes, such as "lovely" appearing more frequently in evaluations of women (p < 0.001), while 19% represented competency-related behaviors, such as "scientific" appearing more frequently in evaluations of men (p < 0.001). Of the 53 words that differed by URM status, 30% represented personal attributes, such as "pleasant" appearing more frequently in evaluations of URM students (p < 0.001), and 28% represented competency-related behaviors, such as "knowledgeable" appearing more frequently in evaluations of non-URM students (p < 0.001). CONCLUSIONS: Many words and phrases reflected students' personal attributes rather than competency-related behaviors, suggesting a gap in implementing competency-based evaluation of students. We observed a significant difference in narrative evaluations associated with gender and URM status, even among students receiving the same grade. This finding raises concern for implicit bias in narrative evaluation, consistent with prior studies, and suggests opportunities for improvement.

Nanostructured silicon via metal assisted catalyzed etch (MACE): chemistry fundamentals and pattern engineering.

There are a range of different methods to generate a nanostructured surface on silicon (Si) but the most cost effective and optically interesting is the metal assisted wet chemical etching (MACE) (Koynov et al 2006 Appl. Phys. Lett. 88 203107). MACE of Si is a controllable, room-temperature wet-chemical technique that uses a thin layer of metal to etch the surface of Si, leaving behind various nano- and micro-scale surface features or 'black silicon'. MACE-fabricated nanowires (NWs) provide improved antireflection and light trapping functionality (Toor et al 2016 Nanoscale 8 15448-66) compared with the traditional 'iso-texturing' (Campbell and Green 1987 J. Appl. Phys. 62 243-9). The resulting lower reflection and improved light trapping can lead to higher short circuit currents in NW solar cells (Toor et al 2011 Appl. Phys. Lett. 99 103501). In addition, NW cells can have higher fill factors and voltages than traditionally processed cells, thus leading to increased solar cell efficiencies (Cabrera et al 2013 IEEE J. Photovolt. 3 102-7). MACE NW processing also has synergy with next generation Si solar cell designs, such as thin epitaxial-Si and passivated emitter rear contact (Toor et al 2016 Nanoscale 8 15448-66). While several companies have begun manufacturing black Si, and many more are researching these techniques, much of the work has not been published in traditional journals and is publicly available only through conference proceedings and patent publications, which makes learning the field challenging. There have been three specialized review articles published recently on certain aspects of MACE or black Si, but do not present a full review that would benefit the industry (Liu et al 2014 Energy Environ. Sci. 7 3223-63; Yusufoglu et al 2015 IEEE J. Photovolt. 5 320-8; Huang et al 2011 Adv. Mater. 23 285-308). In this feature article, we review the chemistry of MACE and explore how changing parameters in the wet etch process effects the resulting texture on the Si surface. Then we review efforts to increase the uniformity and reproducibility of the MACE process, which is critical for commercializing the black Si technology.

A novel approach to patient portal activation data to power equity improvements.

BACKGROUND: There are significant disparities in access and utilization of patient portals by age, language, race, and ethnicity. MATERIALS AND METHODS: We developed ambulatory and inpatient portal activation equity dashboards to understand disparities in initial portal activation, identify targets for improvement, and enable monitoring of interventions over time. We selected key metrics focused on episodes of care and filters to enable high-level overviews and granular data selection to meet the needs of health system leaders and individual clinical units. RESULTS: In addition to highlighting disparities by age, preferred language, race and ethnicity, and insurance payor, the dashboards enabled development and monitoring of interventions to improve portal activation and equity. DISCUSSION AND CONCLUSIONS: Data visualization tools that provide easily accessible, timely, and customizable data can enable a variety of stakeholders to understand and address healthcare disparities, such as patient portal activation. Further institutional efforts are needed to address the persistent inequities highlighted by these dashboards.

Sublimation of GeTe nanowires and evidence of its size effect studied by in situ TEM.

We report sublimation of crystalline GeTe nanowires at elevated temperatures in vacuum imaged by in situ transmission electron microscopy. The GeTe nanowires exhibit significant melting point suppression in the presence of Au contamination. A nanosized effusion cell is formed by coating the GeTe core with a SiO(2) shell, where the core can be evaporated or sublimated from the open end of the shell at high temperatures. By measuring the speed of the moving interface between the condensed and vapor phases, we determined the vaporization coefficient of these nanowires to be greater than or equal to approximately 10(-3) over a wide range of temperatures. At the final stage of the nanowire vaporization, the material loss occurs at a higher rate, which is evidence of a higher vaporization coefficient for nanosized GeTe. This in situ technique offers a quantitative method of investigating phase transition dynamics and kinetics of nanomaterials, an important topic for designing nanoscale devices to be operated at high temperatures such as phase change memory.

Effects of psychological ownership on teachers' beliefs about a cloud-based virtual learning environment.

Perceived usefulness and perceived ease of use constitute important belief factors when technology adoption decisions are made within a non-mandatory setting. This paper investigated the role played by psychological ownership in shaping teachers' beliefs about using a cloud-based virtual learning environment (VLE). Psychological ownership is increasingly becoming a relevant phenomenon in technology adoption research, where people can feel psychologically attached to a particular technology. The study proposed that such phenomenon can also occur when using a VLE, and a hypothesised model with six constructs was tested with 629 Malaysian teachers from 21 schools. Results from structural equation modelling-partial least squares analysis found teachers' experiences with the VLE significantly influenced psychological ownership, which in turn significantly predicted perceived usefulness and perceived ease of use of the VLE. Overall, the model possesses predictive relevance for the outcome predictors as indicated by Stone-Geisser's Q 2, and accounted for 61.6% of variance in perceived usefulness and 62.0% of variance in perceived ease of use. This study provides insights into the motivation behind teachers' beliefs which are shaped by their experiences with the VLE. Implications for theory and practice were discussed based on the insights of the study.

Weighting Primary Care Patient Panel Size: A Novel Electronic Health Record-Derived Measure Using Machine Learning.

BACKGROUND: Characterizing patient complexity using granular electronic health record (EHR) data regularly available to health systems is necessary to optimize primary care processes at scale. OBJECTIVE: To characterize the utilization patterns of primary care patients and create weighted panel sizes for providers based on work required to care for patients with different patterns. METHODS: We used EHR data over a 2-year period from patients empaneled to primary care clinicians in a single academic health system, including their in-person encounter history and virtual encounters such as telephonic visits, electronic messaging, and care coordination with specialists. Using a combination of decision rules and k-means clustering, we identified clusters of patients with similar health care system activity. Phenotypes with basic demographic information were used to predict future health care utilization using log-linear models. Phenotypes were also used to calculate weighted panel sizes. RESULTS: We identified 7 primary care utilization phenotypes, which were characterized by various combinations of primary care and specialty usage and were deemed clinically distinct by primary care physicians. These phenotypes, combined with age-sex and primary payer variables, predicted future primary care utilization with R2 of .394 and were used to create weighted panel sizes. CONCLUSIONS: Individual patients' health care utilization may be useful for classifying patients by primary care work effort and for predicting future primary care usage.

Metal assisted catalyzed etched (MACE) black Si: optics and device physics.

Metal-assisted catalyzed etching (MACE) of silicon (Si) is a controllable, room-temperature wet-chemical technique that uses a thin layer of metal to etch the surface of Si, leaving behind various nano- and micro-scale surface features, including nanowires (NWs), that can be tuned to achieve various useful engineering goals, in particular with respect to Si solar cells. In this review, we introduce the science and technology of MACE from the literature, and provide an in-depth analysis of MACE to enhance Si solar cells, including the outlook for commercial applications of this technology.

Effects of quantum confinement on the doping limit of semiconductor nanowires.

We have calculated the effects of quantum confinement on maximum achievable free carrier concentrations in semiconductor nanowires. Our calculations are based on the amphoteric defect model, which describes the thermodynamic doping limit in semiconductors in terms of the compensation of external dopants by native defects. We find that the generation of amphoteric native defects strongly limits maximum achievable carrier concentrations for nanowires with small widths where quantum confinement is appreciable. The magnitude of this effect in a given material is found to be determined by two material properties: the effective mass of the free carriers, and the position of the conduction (n-type) or valence band (p-type) edge on the absolute energy scale. These results offer a simple, predictive guideline for designing nanostructure devices and contacts where high doping levels are needed.