scholarly journals Beyond duty hours: leveraging large-scale paging data to monitor resident workload

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Amit Kaushal ◽  
Laurence Katznelson ◽  
Robert A. Harrington
Keyword(s):  
Data Streams ◽  
Data Stream ◽  
Large Scale ◽  
Digital Data ◽  
Internal Medicine Residency Program ◽  
Duty Hours ◽  
Individual Level ◽  
Hospital Operations ◽  
The Individual ◽  
Insight Into

Abstract Monitoring and managing resident workload is a cornerstone of policy in graduate medical education, and the duty hours metric is the backbone of current regulations. While the duty hours metric measures hours worked, it does not capture differences in intensity of work completed during those hours, which may independently contribute to fatigue and burnout. Few such metrics exist. Digital data streams generated during the usual course of hospital operations can serve as a novel source of insight into workload intensity by providing high-resolution, minute-by-minute data at the individual level; however, study and use of these data streams for workload monitoring has been limited to date. Paging data is one such data stream. In this work, we analyze over 500,000 pages—two full years of pages in an academic internal medicine residency program—to characterize paging patterns among housestaff. We demonstrate technical feasibility, validity, and utility of paging burden as a metric to provide insight into resident workload beyond duty hours alone, and illustrate a general framework for evaluation and incorporation of novel digital data streams into resident workload monitoring.

scholarly journals Parallel Distributed Networks Resolved at High Resolution Reveal Close Juxtaposition of Distinct Regions

2018 ◽  
Author(s):  
Rodrigo M. Braga ◽  
Koene R. A. Van Dijk ◽  
Jonathan R. Polimeni ◽  
Mark C. Eldaief ◽  
Randy L. Buckner
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Spatial Separation ◽  
Distributed Networks ◽  
Association Cortex ◽  
Default Network ◽  
Network Organization ◽  
Parahippocampal Cortex ◽  
The Individual ◽  
Insight Into

Examination of large-scale distributed networks within the individual reveals details of cortical network organization that are absent in group-averaged studies. One recent discovery is that a distributed transmodal network, often referred to as the ‘default network’, is comprised of two separate but closely interdigitated networks, only one of which is coupled to posterior parahippocampal cortex. Not all studies of individuals have identified the same networks and questions remain about the degree to which the two networks are separate, particularly within regions hypothesized to be interconnected hubs. Here we replicate the observation of network separation across analytical (seed-based connectivity and parcellation) and data projection (volume and surface) methods in 2 individuals each scanned 31 times. Additionally, 3 individuals were examined with high-resolution fMRI to gain further insight into the anatomical details. The two networks were identified with separate regions localized to adjacent portions of the cortical ribbon, sometimes inside the same sulcus. Midline regions previously implicated as hubs revealed near complete spatial separation of the two networks, displaying a complex spatial topography in the posterior cingulate and precuneus. The network coupled to parahippocampal cortex also revealed a separate region directly within the hippocampus at or near the subiculum. These collective results support that the default network is composed of at least two spatially juxtaposed networks. Fine spatial details and juxta-positions of the two networks can be identified within individuals at high resolution, providing insight into the network organization of association cortex and placing further constraints on interpretation of group-averaged neuroimaging data.

Getting Ahead

Teen Spirit ◽  
2020 ◽  
pp. 132-143
Author(s):  
Paul Howe
Keyword(s):  
Free Market ◽  
Economic Behavior ◽  
Social Fabric ◽  
Individual Level ◽  
Economic Decision Making ◽  
Economic Trends ◽  
Individual Decisions ◽  
The Individual ◽  
Adolescent Society ◽  
Insight Into

This chapter assesses how the pervasive influence of the adolescent character provides insight into the workings of another sector of modern life relevant to us all: the economy. Less of a collective undertaking than politics, economic activity is guided primarily by individual decisions and actions in the free market system; so many of the relevant effects are seen first and foremost at the individual level. But these individual effects can multiply and cascade to generate patterns that do have important consequences for the general economic and social fabric. Emotions, misperceptions, intangible costs and benefits, influenced in many instances by underlying character traits, lead people to act in ways that the traditional models do not anticipate. As in other fields, it is only recently that some researchers have started to link personality to economic behavior in interesting and enlightening ways to dig deeper into what makes people tick when it comes to economic decision making and activity. When we combine some of these findings with ideas about the changing contours of character in the adolescent society, we can develop new understandings of some of the more salient economic trends of the past number of years.

Perceived Trust and Confidence for Cryptocurrency Adoption

2022 ◽  
pp. 250-279
Author(s):  
Ewilly Jie Ying Liew ◽  
Wei Li Peh ◽  
Zhuan Kee Leong
Keyword(s):  
Large Scale ◽  
Social Impact ◽  
Public Perceptions ◽  
Middle Income ◽  
Individual Level ◽  
Perceived Trust ◽  
Middle Income Countries ◽  
Regulatory Bodies ◽  
The Individual ◽  
National Databases

This chapter seeks to examine the influence of public perceptions of trust in people and confidence in institutions on cryptocurrency adoption, taking into account the individual-level demographic factors and the regional-level contextual factors. Data is obtained from three large-scale international surveys and national databases and analyzed using R software. The multivariate results demonstrate that individuals' public perceptions of trust and confidence significantly contribute to cryptocurrency adoption. Lower perceived trust in people and higher perceived confidence in civil service and international regulatory bodies increase cryptocurrency adoption, while perceived confidence in political and financial institutions discourages cryptocurrency adoption. Additionally, the univariate results find significant comparisons of gender and perceived trust differences on the predictors of cryptocurrency adoption. This chapter discusses and provides insights on the social impact and future of cryptocurrency adoption, particularly among the upper- and lower-middle-income countries.

Children’s Height and Parental Unemployment: A Large-Scale Anthropometric Study on Eastern Germany, 1994–2006

2010 ◽  
Vol 11 (1) ◽  
pp. 1-24 ◽  
Author(s):  
Jörg Baten ◽  
Andreas Böhm
Keyword(s):  
Employment Status ◽  
Large Scale ◽  
Psychological Effects ◽  
Average Height ◽  
Panel Analysis ◽  
Individual Level ◽  
Parental Unemployment ◽  
The Individual ◽  
Anthropometric Study

Abstract The average height of children is an indicator of the quality of nutrition and healthcare. In this study, we assess the effect of unemployment and other factors on this variable. In the Eastern German Land of Brandenburg, a dataset of 253,050 preschool height measurements was compiled and complemented with information on parents’ schooling and employment status. Unemployment might have negative psychological effects, with an impact on parental care. Both a panel analysis of districts and an assessment at the individual level yield the result that increasing unemployment, net out-migration and fertility were in fact reducing height.

The Effect of Public Service Motivation at Individual, Group, and Organisational Levels of Citizenship Behaviour

2020 ◽  
Vol 33 (1) ◽  
pp. 39-58
Author(s):  
Kuo-Tai Cheng ◽  
Yuan-Chieh Chang ◽  
Changyen Lee
Keyword(s):  
Public Service ◽  
Organizational Citizenship Behavior ◽  
Large Scale ◽  
Public Service Motivation ◽  
Employee Attitudes ◽  
Public Utility ◽  
Citizenship Behavior ◽  
Perceived Effectiveness ◽  
Individual Level ◽  
The Individual

This study conceptualizes and empirically investigates how dimensions of public service motivation affect perceived citizenship behaviour in the context of government-owned utilities. This study used a large-scale questionnaire survey from four utility sectors in Taiwan (N = 1,087). The emergent model suggests that compassion (COM) and self-sacrifice (SS) affect the perceived effectiveness of individual-level Organizational Citizenship Behavior (OCB). Commitment to the Public Interest (CPI) and Attraction to Public Policy making (APP) affect perceived effectiveness of OCB at the group and organisational levels, respectively. The results support the expected contribution of OCB, from the individual to the group levels, and from the group level to the organisational level. Public utility managers should strive to improve employee attitudes and motivation towards greater levels of OCB.

“Reinventing the wheel, over and over again”. organizational learning, memory and forgetting in doing diversity work

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marieke van den Brink
Keyword(s):  
Organizational Change ◽  
Organizational Learning ◽  
Performance Management ◽  
Research Question ◽  
Content Type ◽  
Individual Level ◽  
Management Plans ◽  
The Individual ◽  
Diversity Studies ◽  
Insight Into

Purpose The purpose of this paper is to advance knowledge of organizational change towards diversity by bringing together concepts from organizational learning and diversity studies. Design/methodology/approach This longitudinal study was conducted over two years. It involved interviews, observation of meetings and consultation of documentation and the analysis focused on organizational learning. The key research question was how do organizational members institutionalize their individual learning process to change in organizational cultures, routines and structures in a sustainable way? Findings The results showed that there had been learning at the individual level but this did not necessarily mean that participants had been able to transfer their learning into behaviour change. Research limitations/implications The research suggested that training alone may not be sufficient to promote effective organizational change regarding diversity. Additional measures are likely to be required, for example, including diversity targets in performance management plans and reviews. Practical implications In order to achieve greater diversity, organizations are likely to need to use a number of methods to supplement initial training. Social implications This research gives insight into how greater diversity may be achieved in organizations. Originality/value Previous literature understates the complexity of the change processes for enhanced diversity to be sustained in organizations. This study has originality in its focus on organizational learning.

Data Streaming Processing Window Joined With Graphics Processing Units (GPUs)

2021 ◽  
pp. 602-623
Author(s):  
Shen Lu ◽  
Richard S. Segall
Keyword(s):  
Big Data ◽  
Data Streams ◽  
Graphics Processing Units ◽  
Data Stream ◽  
Large Scale ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Data Streaming ◽  
Large Scale Data ◽  
Graphics Processing

Big data is large-scale data and can be either discrete or continuous. This article entails research that discusses the continuous case of big data often called “data streaming.” More and more businesses will depend on being able to process and make decisions on streams of data. This article utilizes the algorithmic side of data stream processing often called “stream analytics” or “stream mining.” Data streaming Windows Join can be improved by using graphics processing unit (GPU) for higher performance computing. Data streams are generated by two independent threads: one thread can be used to generate Data Stream A, and the other thread can be used to generate Data Stream B. One would use a Windows Join thread to merge the two data streams, which is also the process of “Data Stream Window Join.” The Window Join process can be implemented in parallel that can efficiently improve the computing speed. Experiments are provided for Data Stream Window Joins using both static and dynamic data.

scholarly journals A difference that matters: comparisons of structured and semi-structured psychiatric diagnostic interviews in the general population

1999 ◽  
Vol 29 (5) ◽  
pp. 1013-1020 ◽  
Author(s):  
T. S. BRUGHA ◽  
P. E. BEBBINGTON ◽  
R. JENKINS
Keyword(s):  
General Population ◽  
Psychiatric Disorders ◽  
Large Scale ◽  
Population Level ◽  
Individual Level ◽  
Case Identification ◽  
Diagnostic Interviews ◽  
Health Project ◽  
The Individual ◽  
General Populations

Psychiatric case-identification in general populations allows us to study both individuals with functional psychiatric disorders and the populations from which they come. The individual level of analysis permits disorders to be related to factors of potential aetiological significance and the study of attributes of the disorders that need to be assessed in non-referred populations (an initially scientific endeavour). At the population level valid case identification can be used to evaluate needs for treatment and the utilization of service resources (a public health project). Thus, prevalence is of interest both to scientists and to those responsible for commissioning and planning services (Brugha et al. 1997; Regier et al. 1998). The quality of case identification techniques and of estimates of prevalence is thus of general concern (Bartlett & Coles, 1998).Structured diagnostic interviews were introduced into general population surveys in the 1970s as a method ‘to enable interviewers to obtain psychiatric diagnoses comparable to those a psychiatrist would obtain’ (Robins et al. 1981). The need to develop reliable standardized measures was partly driven by an earlier generation of prevalence surveys showing rates ranging widely from 10·9% (Pasamanick et al. 1956) to 55% (Leighton et al. 1963) in urban and rural North American communities respectively. If the success of large scale psychiatric epidemiological enquiries using structured diagnostic interviews and standardized classifications is measured in terms of citation rates it would seem difficult to question. But the development of standardized interviews of functional psychiatric disorders has not solved this problem of variability: the current generation of large scale surveys, using structured diagnostic interviews and serving strictly defined classification rules, have generated, for example, 12-month prevalence rates of major depression in the US of 4·2% (Robins & Regier, 1991) and 10·1% (Kessler et al. 1994). This calls into question the validity of the assessments, such that we must reopen the question of what they should be measuring and how they should do it.

Incidents in high-volume elongated crowd facilities: A simulation-based study

SIMULATION ◽  
2018 ◽  
Vol 95 (9) ◽  
pp. 823-843
Author(s):  
Ahmed Abdelghany ◽  
Hani Mahmassani ◽  
Khaled Abdelghany ◽  
Hasan Al-Ahmadi ◽  
Wael Alhalabi
Keyword(s):  
Large Scale ◽  
Real Life ◽  
Linear Structure ◽  
High Volume ◽  
Heterogeneous Traffic ◽  
Individual Level ◽  
Stop And Go ◽  
Simulation Based ◽  
The Individual ◽  
Inefficient Operation

This paper presents the main findings of a simulation-based study to evaluate incidents in pedestrian/crowd tunnels and similar elongated confined facilities, with high-volume heterogeneous traffic. These incidents, when occur, imposes hazardous conditions that always result in significant number of fatalities. The aim of this study is to understand how these facilities perform under different irregular scenarios and possibly identify potential causes of accidents. The problem of studying incidents in large-scale high-volume pedestrian facilities is that these incidents are difficult to expect or replicate. Thus, studying these facilities through real-life scenarios is almost impossible. Accordingly, a micro-simulation assignment model for multidirectional pedestrian movement is used for this purpose. The model adopts a Cellular Automata (CA) discrete system, which allows detailed representation of the pedestrians’ walkways in the tunnel. The modeling approach captures crowd dynamics through representation of behavioral decisions of heterogeneous pedestrians at the individual level. Several experiments are conducted to study the pedestrian flow in the proposed tunnel considering different operational scenarios including demand levels, heterogeneous traffic, evacuation scenario, and tunnel blockage. Results show that flow of large pedestrian volumes through a long confined linear structure, such as a tunnel, are subject to the same flow dynamics as we observe with vehicular traffic. In particular, they are subject to the formation of “clumps” and shock waves that can rapidly propagate and lead to inefficient operation, including flow breakdown with stop-and-go waves.

A Bioecological Model of Mass Trauma

2011 ◽  
Vol 39 (8) ◽  
pp. 1087-1127 ◽  
Author(s):  
Mary Ann Hoffman ◽  
Theresa Kruczek
Keyword(s):  
Large Scale ◽  
Systems Approach ◽  
Relevant Literature ◽  
Psychosocial Interventions ◽  
Future Research ◽  
Catastrophic Events ◽  
Mass Trauma ◽  
Individual Level ◽  
Bioecological Model ◽  
The Individual

Biopsychosocial consequences of catastrophic events create an ongoing need for research that examines the effects of mass traumas, developing psychosocial interventions, and advocacy to address the needs of affected individuals, systems, and communities. Because it is neither possible nor necessarily desirable to intervene with all touched by disasters at an individual level, a systems approach that allows conceptualization and response at the individual, family, community, and societal levels seems optimal. Many of the models commonly used in counseling psychology to explain coping with difficult events focus on individual effects and do not adequately capture the complex, multisystemic effects of large-scale catastrophic events and disasters. A bioecological model of mass trauma, which provides a conceptual framework for understanding the effects, intervening in the aftermath, addressing prevention, and researching aspects of large-scale disasters, catastrophes, and mass traumas, is presented. Relevant literature and illustrative examples from three categories of mass traumas or catastrophic events (disasters, war, and terrorism or violence) that currently contribute to a persistent atmosphere of stress for many are reviewed using the bioecological model. Recommendations for future research are provided.

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