Analyzing the complex maze of content and flow in communication between team members could help unlock researchers’ understanding of team performance. This research analyzes the communication patterns of two teams, based on their team performance, in order to test and expand a developing team mapping technique to assess content and flow between team members. A two-pronged methodology was executed: (1) communication data processing by (a) classifying utterances into content topics and flow, (b) indexing the speech acts, and (c) validation, and (2) analyzing the communication patterns using augmented fuzzy cognitive maps (FCMs). The strengths of the relationships among key communication concepts were estimated and compared between the two, low and high, performance teams’ FCMs. The results indicated that FCMs could apply to larger teams and in an alternate domain. The FCM communication patterns recognized that the “providing information” concept was significantly different between the high and low team performances. This research demonstrates that, using fuzzy logic, different patterns can assist in understanding team performance while providing insights into complex team communication dynamics.
The primary objective of this study is to explore how nurse experience influences the patterns of documenting in electronic medical records (EMR) in an intensive care unit (ICU). To understand the time and work patterns related to EMR documentation, the real-time measurement system data was used. This log data is a representation of actions taken by ICU nurses during EMR documentation. To analyze the ICU nurse’s workflow related to EMR documentation, a hierarchical task analysis (HTA) was conducted. Multiple HTA charts were used to identify different patterns of EMR documentation between more experienced nurses and less experienced nurses. The results revealed that the nurse’s experience had significant impacts on the frequency of updating the assessment result page and reviewing clinical results in EMR. The findings from this study will contribute to revealing unknown usability problems of EMR documentation process.
This study examines the ergonomic impact of augmented reality (AR) technologies in educational contexts, with a focus on understanding how prolonged AR engagement affects postural dynamics and physical demands on users. By analyzing slouching scores alongside NASA Task Load Index (TLX) Physical Demand (PD) values, we assess the physical strain experienced by participants during the initial modules of an AR-based lecture series. Our findings demonstrate a notable decline in slouching scores as participants progress through the lecture modules, indicating increased postural deviations. To quantify these effects, we developed a regression model that effectively predicts the physical demands imposed by various AR modules, based on the observed slouching scores.
Natural Goals Operators Methods and Selection Rules Language (NGOMSL) model of the clinical process in an Emergency Department (ED) was developed using Micro Saint Sharp. This model advanced our understanding of a care provider's cognitive behavior in a dynamic ED environment. It also revealed the understanding of proximal workflow in the ED and the workload related to clinical processes. The benefits of this study are (a) improved understanding of the relevant form factors of the clinical process that contribute to a heavy workload in the ED and (b) prevention of potential errors caused by the workload. To understand the current ED workflow, hierarchical task analysis (HTA) charts were developed. The HTA charts were used to understand the detailed process mappings of nurses in the ED. Based on this multi-level analysis of the HTA charts, the NGOMSL simulation model was developed.
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