Alerts as Coordination Mechanisms

In this study, we explore how clinical decision support features can be designed to aid teams in caring for patients during time-critical medical emergencies. We interviewed 12 clinicians with experience in leading pediatric trauma resuscitations to elicit design requirements for decision support alerts and how these alerts should be designed for teams with shared leadership. Based on the interview data, we identified three types of decision support alerts: reminders to perform tasks, alerts to changes in patient status, and suggestions for interventions. We also found that clinicians perceived alerts in this setting as coordination mechanisms and that some alert preferences were associated with leader experience levels. From these findings, we contribute three perspectives on how alerts can aid coordination and discuss implications for designing decision support alerts for shared leadership in time-critical medical processes.

Context Matters in Evidence Implementation Globally; Comment on "Stakeholder Perspectives of Attributes and Features of Context Relevant to Knowledge Translation in Health Settings: A Multi-Country Analysis"

Context influences the effectiveness of healthcare interventions and should be considered to inform their implementation. However, context remains poorly defined in the knowledge translation (KT) literature. The paper by Squires and colleagues constitutes a valuable contribution to the field of KT as it provides the basis for a comprehensive framework to assess the influence of context on implementation success. In their study, Squires et al. identified 66 context features, grouped into 16 attributes. Their findings highlight a great convergence in the context features mentioned by stakeholders across countries, experience levels and roles in KT. Thus, the proposed framework could eventually transfer to several implementation settings. However, all study participants were from high-income countries. It would therefore be important to replicate this research in low- and middle-income countries. A common understanding of what context means is essential to assessing its influence on the implementation of healthcare interventions globally.

Development of The Music Background Experience Questionnaire

People with different levels of music experience have been reported to differ significantly in cognitive abilities such as verbal memory, phonological awareness and reading development. However, studies often comparing the cognitive ability between musicians and non-musicians. Among the non-musicians, there are differences in music experience levels. Besides, many non-musicians with higher music experience than musicians. However, at present there is no reliable and valid measure of music experience in the literature. In the current study we developed the Music Background Experience Questionnaire for use in the field of music psychology. An initial set of 45 items was compiled based on the literature and on semi-structured interviews with 10 musicians and psychologists. These items were then tested in a pilot study of 402 participants. Based on exploratory and confirmatory factor analysis, 11 items were selected and classified into the two dimensions of "music training" and "music contact." A sample of 2,228 participants (1,465 women, average age 27.62 years) then completed the new measure. A subsample of 49 completed the questionnaire again after three weeks. The internal consistency, test-retest reliability, structural validity and construct validity were strong. These strong psychometric properties suggest that the Music Background Experience Questionnaire is appropriate for use in music psychology research.

Thinking Time in Music Practice

We asked school- and college-aged instrumentalists ( N = 32) to imagine an ideal performance of a brief passage of music, record a performance of the passage, and describe discrepancies they noticed between their imagined and actual performances. The more experienced participants took at least as much time to imagine their idealized performances as it took to perform them; less experienced participants took less time to imagine what they were about to play. There were no differences among experience levels in the numbers or types of discrepancies identified. The differences between more and less experienced participants were also evident in a subsequent practice period. More experienced musicians’ practice included more frequent moments of pause, whereas school-aged participants seldom paused and tended to address performance issues other than those identified in their commentaries.

Patient Mistreatment of Health Care Providers

BackgroundMistreatment of medical professionals by patients is an ongoing problem. We aimed to construct and evaluate a curriculum that would prepare medical professionals for mistreatment by patients. MethodsLessons learned from 15 interviews and 2 focus groups with medical professionals were distilled into a multi-modal curriculum including didactics, simulation videos and role-play scenarios aimed to improve confidence in addressing mistreatment. This curriculum was disseminated at five educational workshops to medical professionals of various training groups and experience levels. Pre- and post-surveys were distributed to assess changes in participant’s perspectives on readiness to address mistreatment. The signed-rank test was implemented to compare pre- and post- data. ResultsParticipants were more likely to agree post-workshop that they had the right words to say, had a plan for what to do, and were more willing to speak up when they themselves or someone else was mistreated (p < .001). They were also more likely to agree post-workshop that there was something they could do to address patient mistreatment (p < .001).ConclusionsParticipant familiarity and confidence in responding to patient mistreatment increased. Our curriculum may serve as a foundation for institutions seeking to equip their educators, providers, and trainees with strategies for addressing this important issue.

Inter-Variability Study of COVLIAS 1.0: Hybrid Deep Learning Models for COVID-19 Lung Segmentation in Computed Tomography

Background: For COVID-19 lung severity, segmentation of lungs on computed tomography (CT) is the first crucial step. Current deep learning (DL)-based Artificial Intelligence (AI) models have a bias in the training stage of segmentation because only one set of ground truth (GT) annotations are evaluated. We propose a robust and stable inter-variability analysis of CT lung segmentation in COVID-19 to avoid the effect of bias. Methodology: The proposed inter-variability study consists of two GT tracers for lung segmentation on chest CT. Three AI models, PSP Net, VGG-SegNet, and ResNet-SegNet, were trained using GT annotations. We hypothesized that if AI models are trained on the GT tracings from multiple experience levels, and if the AI performance on the test data between these AI models is within the 5% range, one can consider such an AI model robust and unbiased. The K5 protocol (training to testing: 80%:20%) was adapted. Ten kinds of metrics were used for performance evaluation. Results: The database consisted of 5000 CT chest images from 72 COVID-19-infected patients. By computing the coefficient of correlations (CC) between the output of the two AI models trained corresponding to the two GT tracers, computing their differences in their CC, and repeating the process for all three AI-models, we show the differences as 0%, 0.51%, and 2.04% (all < 5%), thereby validating the hypothesis. The performance was comparable; however, it had the following order: ResNet-SegNet > PSP Net > VGG-SegNet. Conclusions: The AI models were clinically robust and stable during the inter-variability analysis on the CT lung segmentation on COVID-19 patients.

Employable identities

Navigating the labour market in a new context can be a challenge for any migrant, and particularly so for former refugees, who are often unable to find employment appropriate for their qualification and experience levels. This study takes an Interactional Sociolinguistic approach to exploring how three former refugees navigate employability in narrative, from the social constructionist perspective of employable identities, emergent from and negotiated within discourse. The study focuses specifically on the participants’ discursive navigation of their various (Bourdieusian) social and cultural capital and its importance to labour market performance. Evident in the data are the difficulties of translating – or having recognised – a lifetime’s accumulation of capital, often rendered worthless upon migration. Such challenges impact upon forced migrants’ ability to successfully enact employability, and subsequently upon their imagined (future) identities. This research highlights former refugees’ complex challenges involved with successful navigation of employability in a new context.

Diagnosing thyroid nodules with atypia of undetermined significance/follicular lesion of undetermined significance cytology with the deep convolutional neural network

To compare the diagnostic performances of physicians and a deep convolutional neural network (CNN) predicting malignancy with ultrasonography images of thyroid nodules with atypia of undetermined significance (AUS)/follicular lesion of undetermined significance (FLUS) results on fine-needle aspiration (FNA). This study included 202 patients with 202 nodules ≥ 1 cm AUS/FLUS on FNA, and underwent surgery in one of 3 different institutions. Diagnostic performances were compared between 8 physicians (4 radiologists, 4 endocrinologists) with varying experience levels and CNN, and AUS/FLUS subgroups were analyzed. Interobserver variability was assessed among the 8 physicians. Of the 202 nodules, 158 were AUS, and 44 were FLUS; 86 were benign, and 116 were malignant. The area under the curves (AUCs) of the 8 physicians and CNN were 0.680–0.722 and 0.666, without significant differences (P > 0.05). In the subgroup analysis, the AUCs for the 8 physicians and CNN were 0.657–0.768 and 0.652 for AUS, 0.469–0.674 and 0.622 for FLUS. Interobserver agreements were moderate (k = 0.543), substantial (k = 0.652), and moderate (k = 0.455) among the 8 physicians, 4 radiologists, and 4 endocrinologists. For thyroid nodules with AUS/FLUS cytology, the diagnostic performance of CNN to differentiate malignancy with US images was comparable to that of physicians with variable experience levels.