Predicting human response to memory retrieval, vigilance and task novelty using GSR and artificial neural networks

Human operators continue to be subject to workload, and predicting their load levels becomes important in time and safety critical operations. This study is a pilot research investigating the effects of short-term memory retrieval, cognitive set shifting, and visual monitoring on the electrodermal response of humans, since electrodermal activity is one of the first responses in critical scenarios. 9 participants, 8 males and 1 female undergraduate student (Mean age = 22 years) from UTEP Industrial Engineering department participated in the study. Sternberg short-term working memory task, Wisconsin card sorting task and a standard tracking task respectively were used as the experimental tasks for each of the independent variables. Biosemi and Brain Products system was used for data acquisition and analysis. A linear mixed model fit to the data indicated that short-term memory retrieval (with amplitude as dependent variable Mean = 0.012μS, SD = 0.141μS, p = 0.022), (with reaction time as the dependent variable Mean = 1136.8030μS, SD = 472.705μS, p = 0.001) was significant. Significant correlations (p = 0.022) were obtained between GSR amplitude and reaction time. Visual monitoring significantly affected the electrodermal response (Mean = 0.0975μS, SD = 0.09290μS; p = 0.000). Electrodermal activity was also significantly affected by task novelty (Mean = -2.65079E-4μS, SD = 0.025μS, p = 0.001). Electrodermal responses were integrated into an artificial neural network for classification of load levels. Neuroshell 2 software was used for modeling the neural architecture. Artificial neural network classified the electrodermal responses into task load levels namely, low, medium and high

A qualitative investigation of healthcare workers’ strategies in response to readmissions

Abstract Background Readmission of a patient to a hospital is typically associated with significant clinical changes in the patient’s condition, but it is unknown how healthcare workers modify their provision of care when considering these changes. The purpose of the present study was to determine how healthcare workers shift their care strategies when treating readmitted patients. Methods A typical case sampling study of healthcare workers was conducted using the grounded theory approach. The study setting comprised several patient care units at an academic center and tertiary-care hospital. We purposively sampled 34 healthcare workers (19 women, 15 men) to participate in individual interviews, either face-to-face or by telephone. We asked the participants semi structured questions regarding their thoughts on readmissions and how they altered their process and behavior for readmitted patients. Interviews were audio-recorded and transcribed. We used a qualitative data analyses based on an inductive approach to generate themes about how healthcare workers shift their strategies for readmitted patients. Results Healthcare workers’ shifts in strategy for readmissions were reflected in three major themes: clinical assessment, use and management of information, and communication patterns. Participants reported that they became more conservative in their assessment of the clinical condition of a readmitted patient. The participants also indicated that readmitted patients would be treated in a similar way to normal admission based on care requirements; however, somewhat paradoxically, they also expressed that having access to prior patient information changed the way they treated a readmitted patient. Conclusions Although healthcare workers may exhibit a tendency to become more conservative with readmissions, readily available patient information from the previous admission played a large part in guiding their thinking. A more conservative approach with a readmitted patient, on its own, does not necessarily lead to improved documentation or better patient care

Usability of State Public Health Department Websites for Communication During a Pandemic: A Heuristic Evaluation

Study aims were to investigate how usable COVID-19 dedicated state public health websites in the US were, and whether case counts in different geographical regions in the US were related to website usability. 16 state websites representing the 2 highest and the 2 lowest case count states in each region were selected. Five experts used a heuristic evaluation procedure to independently rate all 16 websites on a severity scale of 0–4. Usability criteria published by the US Department of Health and Human Services and criteria on risk communication and data dashboards were used. Analyses involved cross tabulation of usability criteria with case counts, comparison of usability scores using Mood's median tests, test of differences in average usability scores using ANOVA and post-hoc tests, and identification of correlations between case counts and usability scores. Results from the Mood's median test showed that the median usability scores for the states were significantly different from each other at the 5% level of significance (df = 15, chi-square = 38.40; p = 0.001). ANOVA showed statistically significant differences between the mean usability scores for the states at the 5% level of significance (F = 6.33, p < 0.05). Although not statistically significant, results from a correlation analysis between case count and usability scores showed a negative correlation (r = -0.209, p = 0.437) indicating that the higher the case count, the better the usability score. Overall, the websites fared well on usability, but many websites were used as an information and data repository. These websites must communicate infection risk better. RELEVANCE TO INDUSTRY: The study applies to public health agency websites that communicate essential information during a pandemic

Additional file 1: of A qualitative investigation of healthcare workers’ strategies in response to readmissions

Interview Guide. Contains semi-structured interview questions used in this study. Only questions that directly relate to the manuscript’s research goals are provided. Other interview questions that were a part of a larger study are not included. (DOCX 51 kb