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Background In a previous study, we observed that the majority of interruptions experienced by nurses in a cardiovascular intensive care unit (CVICU) carried information directly related to their patient or other aspects of work affecting other patients or indirectly affecting their patient. Further, the proportion of interruptions with personal content was significantly higher during low-severity (in case of an error as defined by nurses) tasks compared to medium- and high-severity tasks suggesting that other personnel may have evaluated the criticality of the nurses' tasks before interrupting. However, this earlier study only collected data when an interruption happened and thus could not investigate interruption rate as a function of primary task type and severity while controlling for primary task duration as an exposure variable. Objectives We addressed this methodological limitation in a second observational study that was conducted to further study interruptions and also to evaluate an interruption mitigation tool. The data from the baseline condition (i.e., no tool) is analyzed in this paper to validate the results of our previous study and to report interruption rates observed during tasks of varying severities (low, medium, high), with a particular focus on comparing different interruption contents. Design and setting The study was conducted in a 24-bed closed CVICU at a Canadian hospital, during day shifts. Participants The baseline condition involved thirteen nurses. Methods Over a 3-week period, three researchers observed these nurses 46–120min each, with an average of 89min. Data were collected in real time, using a tablet computer and software designed for this purpose. The rate of interruptions with different content was compared across varying task severity levels as defined by CVICU nurses. Results Nurses spent about 50% of their time conducting medium-severity tasks (e.g., documentation), 35% conducting high-severity tasks (e.g., procedure), and 14% conducting low-severity tasks (e.g., general care). The rate of interruptions with personal content observed during low-severity tasks was 1.97 (95% confidence interval, CI: 1.04, 3.74) and 3.23 (95% CI: 1.51, 6.89) times the rate of interruptions with personal content observed during high- and medium-severity tasks, respectively. Conclusions Interrupters might have evaluated task severity before interrupting. Increasing the transparency of the nature and severity of the task being performed may help others further modulate when and how they interrupt a nurse. Overall, rather than try to eliminate all interruptions, mitigation strategies should consider the relevance of interruptions to a task or patient as well as their urgency.

The workplace environment for intensive care nursing is highly stressful, with long working hours and a dynamic workload that may induce fatigue. The resulting stress and fatigue may reduce nurses' efficiency and may contribute to medical errors. A smart wearable system is being designed to help nurses who experience high levels of stress and fatigue at work. This article documents the systematic process of deriving information requirements from 2 focus groups conducted separately with nurses and nurse managers working in various Southeastern Texas hospitals. While nurses expected functionality such as memory aid tools, health assessment, and stress-reducing exercises, nurse managers expected information about the overall status of the unit's fatigue/stress levels as well as nurses' communication and movement patterns. The derived information requirements will act as an objective assessment of needs and would set the stage for the design of a stress-monitoring tool.

With increasing complexity of safety analysis in sociotechnical systems, there is a need for a mechanism to accurately capture complex information and present it in an easily accessible and understandable form. While there are plenty of accident databases that have been created over the years for specific purposes, a tool that provides a holistic view of all the safety-related aspects of an accident customized specifically per user and industry is largely absent. This paper discusses the conceptual model of the system safety database (SSD), a tool that will offer tailored solutions to multiple classes of users and that will generate reports synthesizing lessons learned from a variety of disparate contexts, providing succinct and actionable information for decision support. The paper also proposes the concept and architecture of a System Safety Data Network (SSDN) that encapsulates a network of safety databases, thereby addressing some of the challenges of a stand-alone safety database. The data network will enable working with structured and unstructured data by integrating multiple relational and NoSQL databases. A full-fledged implementation of the SSDN will enable improved collaboration across industries and corporations. The System Safety Data Network will facilitate analysis across disciplines and contexts, allowing researchers and practitioners to use integrated mixed-methods approaches to conduct investigations, analyses, research, and development activities across multiple levels of a system. The paper also discusses the steps involved in the implementation of such a data network and the challenges involved. In addition, the current work in data categorization and interpretability of incident data is discussed. When completed, the System Safety Data Network will provide stakeholders at all levels, from individual operators to policymakers, with the tools and perspectives needed to improve the safety of complex sociotechnical systems.

BACKGROUND Telemedicine and telehealth solutions are emerging rapidly in health care and have the potential to decrease costs for insurers, providers, and patients in various settings. Pediatric populations that require specialty care are disadvantaged socially or economically or have chronic health conditions that will greatly benefit from results of studies utilizing telemedicine technologies. This paper examines the emerging trends in pediatric populations as part of a systematic literature review and provides a scoping review of the type, extent, and quantity of research available. OBJECTIVE This paper aims to examine the role of remote patient monitoring (RPM) and telemedicine in neonatal and pediatric settings. Findings can be used to identify strengths, weaknesses, and gaps in the field. The identification of gaps will allow for interventions or research to improve health care quality and costs. METHODS A systematic literature review is being conducted to gather an adequate amount of relevant research for telehealth in pediatric populations. The fields of RPM and telemedicine are not yet very well established by the health care services sector, and definitions vary across health care systems; thus, the terms are not always defined similarly throughout the literature. Three databases were scoped for information for this specific review, and 56 papers were included for review. RESULTS Three major telemedicine trends emerged from the review of 45 relevant papers—RPM, teleconsultation, and monitoring patients within the hospital, but without contact—thus, decreasing the likelihood of infection or other adverse health effects. CONCLUSIONS While the current telemedicine approaches show promise, limited studied conditions and small sample sizes affect generalizability, therefore, warranting further research. The information presented can inform health care providers of the most widely implemented, studied, and effective forms of telemedicine for patients and their families and the telemedicine initiatives that are most cost efficient for health systems. While the focus of this review is to summarize some telehealth applications in pediatrics, we have also presented research studies that can inform providers about the importance of data sharing of remote monitoring data between hospitals. Further reports will be developed to inform health systems as the systematic literature review continues.

Objective: Interruptions to secondary tasks resulting in multiple tasks to resume may tax working memory. The objective of this research is to study such interruptions experienced by intensive care unit (ICU) nurses. Background: ICU nurses are frequently interrupted, resulting in a switch from primary to secondary tasks. In two recent studies, we observed that some of these secondary tasks also get interrupted, resulting in multiple tasks that have to be resumed, a phenomenon we refer to as nested interruptions. Although completing multiple secondary tasks in a serial fashion during an interruption period can create context-switching costs, we hypothesize that nested interruptions tax the working memory even more than just performing multiple secondary tasks sequentially because the nurse would have to encode in working memory the resumption goals for both the primary and the interrupted secondary tasks. Method: We conducted a laboratory study with 30 ICU nurses, who performed an electronic order-entry task under three interruption conditions: (a) baseline—no secondary task during the interruption period; (2) serial—performance of two tasks one after the other during the interruption period; and (3) nested—performance of two tasks during the interruption period, one of which was also interrupted. Results: Nested interruptions resulted in significantly longer primary-task resumption lag and less accurate task resumption compared with both the serial interruption and baseline conditions. Conclusion: The nested nature of interruptions adds to the resumption lag and diminishes resumption accuracy by likely populating the working memory with goals associated with interrupted secondary tasks.

This paper investigates the effectiveness of providing interruption recovery assistance in the form of an interactive visual timeline of historical events on a peripheral display in support of team supervision in time-critical settings. As interruptions can have detrimental effects on task performance, particularly in time-critical work environments, there is growing interest in the design of tools to assist people in resuming their pre-interruption activity. A user study was conducted to evaluate the use of an interactive event timeline that provides assistance to human supervisors in time-critical settings. The study was conducted in an experimental platform that emulated a team of operators and a mission commander performing a time-critical unmanned aerial vehicle (UAV) mission. The study results showed that providing interruption assistance enabled people to recover from interruptions faster and more accurately. These results have implications for interface design that could be adopted in similar time-critical environments such as air-traffic control, process control, and first responders.

A common challenge with all opioid use disorder treatment paths is withdrawal management. When withdrawal symptoms are not effectively monitored and managed, they lead to relapse which often leads to deadly overdose. A prerequisite for effective opioid withdrawal management is early identification and assessment of withdrawal symptoms.The objective of this research was to describe the type and content of opioid withdrawal monitoring methods, including surveys, scales and technology, to identify gaps in research and practice that could inform the design and development of novel withdrawal management technologies.A scoping review of literature was conducted. PubMed, EMBASE and Google Scholar were searched using a combination of search terms.Withdrawal scales are the main method of assessing and quantifying opioid withdrawal intensity. The search yielded 18 different opioid withdrawal scales used within the last 80 years. While traditional opioid withdrawal scales for patient monitoring are commonly used, most scales rely heavily on patients' self-report and frequent observations, and generally suffer from lack of consensus on the criteria used for evaluation, mode of administration, type of reporting (e.g., scales used), frequency of administration, and assessment window.It is timely to investigate how opioid withdrawal scales can be complemented or replaced with reliable monitoring technologies. Use of noninvasive wearable sensors to continuously monitor physiologic changes associated with opioid withdrawal represents a potential to extend monitoring outside clinical setting.

Interruptions were studied extensively in the past but with a focus on their negative effects. Although many types of interruptions result in a break-in-task, in some cases interruptions communicate important information associated with patient’s safety. The majority of previous interruption research use a reductionist approach to minimize or prevent interruptions, and minimal attention has been given to the differentiation between positive and negative interruptions. Through the analysis of relevant healthcare literature, this paper first identifies the inconsistencies in the way interruptions are defined, and then categorizes potential sources of negative and positive interruptions.

With so many natural and man-made disasters bringing catastrophic losses worldwide, the initial response is the one during which real-time decision-making is particularly important for the overall performance. During the response phase, first responders with diverse backgrounds (e.g., fire, medical, law enforcement, or public work) need to work together as an ad hoc team to save lives and infrastructures at risk. For successful response operations, cognition (i.e., the ability to support timely and effective decision-making) needs to be understood not only at the individual level but also at the team level. Yet, team cognition still remains to be an inadequately addressed topic in emergency response literature (Bigley & Roberts, 2001; Comfort, 2007; Majchrzak, Jarvenpaa, & Hollingshead, 2007). While the need to study real-world teams in the context of “broader sociotechnical systems” has been documented in team cognition and behavior literature (Kozlowski & Ilgen, 2006; Salas, Cooke & Rosen, 2008; DeChurch and Zaccaro, 2010), emergency response literature lacks attention to emergency responders’ collective efforts. Unlike many other cognitive psychology research topics, the theoretical growth of team cognition has been primarily driven by application needs – i.e., “there was no time to wait for a psychology of team cognition” because applications were “needed yesterday” (Cooke et al. 2007). That is, the scarcity of literature can be traced back to lack of efforts in conceptualizing and operationalizing team cognition in the unique context of emergency response. Most of all, the emergency response field must first come to consensus on what it means by team cognition. As it stands, there are at least five research domains of team cognition (Wildman, Salas, & Scott, 2014), i.e., team mental models, transactive memory systems, team situation awareness, strategic consensus, and interactive team cognition (ITC). While each of these domains highlights some aspects of the multifaceted construct of team cognition, the direction of future research hinges on having a clear conceptualization of team cognition – particularly in the context of emergency response. A scoping review of literature was conducted as an initial effort to outline and synthesize how team cognition has been defined in the field of emergency response. Using targeted keyword searches in MEDLINE, COMPENDEX and CINAHL, the total of 1,799 articles published in English after 1994, which either empirically or otherwise investigated team cognition in emergency response were retrieved. After the initial search, paper titles, abstracts, and full texts were subsequently reviewed to exclude irrelevant ones and to define the subset for detailed review. Our qualitative analysis identified inconsistencies in definitions that may generate redundant research efforts and hinder the generalization of findings. Three main research gaps with respect to defining team cognition in emergency response are identified. (1) Team cognition needs to be defined at the team level, viewing a team either as an aggregated group of individuals or a cognitive system. (2) Product-based and process-based definitions of team cognition need to be clearly differentiated and aligned with two distinct views on a team. While team cognition has a nuanced literature that describes subtle distinctions between two perspectives (i.e., an emergent state vs. a cognitive process) (Durso, Rawson, & Girotto, 2007; Cooke et al. 2007; Saner et al. 2009), emergency response literature has yet to produce research that shows satisfactory exploration on those distinctions. (3) Team cognition needs to be redefined in the unique context of emergency response. As posited by the ITC theory (“team cognition is inextricably tied to context”, Cooke et al. 2013), team cognition in emergency response could differ depending on the nature of the surrounding dynamic context including team, task, and environment. However, different constructs are taken directly from other disciplines and only very few of them are redefined in the context of emergency response (Sætrevik, 2015). This research documents the first component of the multistage on-going project that investigates how interactions among human, team, and technology affect team cognition and performance in emergency response. Based on the synthesis, a working definition for future work is presented as: “a collective cognitive process of team members 1) perceiving changes in the status of critical elements, 2) adapting in response to the perceived changes, and 3) learning from past performance, which supports timely and effective coordinated decision-making and manifests itself as behavioral patterns of dynamic interactions among individuals and technologies”. Future work in progress includes developing an appropriate measurement technique for team cognition based on working definition, designing and evaluating potential technologies to support team cognition in the simulated emergency response environment (i.e., Emergency Operations Training Center, TEEX, College Station, TX).

Inherent limitations of controlling risks in complex socio-technical systems were revealed in several major catastrophic disasters such as nuclear meltdown in Fukushima Daiichi nuclear power plant in 2011, well blowout in Deepwater Horizon drilling rig in 2010, and Hurricane Katrina in 2005. While desired risk management leans toward the prevention of such unwanted events, the mitigation of their impact becomes more important and emergency response operations provide the last line of protection against disasters (Kanno, Makita, & Furuta, 2008). In response to September 11 terrorist attack at World Trade Center in New York, U.S. Government launched the National Incident Management System (NIMS), an integrated national and multi-jurisdictional emergency preparedness and response program (Department of Homeland Security, 2008). The NIMS framework is characterized by a common operating picture, interoperability, reliability, scalability and portability, and resilience and redundancy (Department of Homeland Security, 2008). Among these characteristics, effective emergency response operations require resilience because planned-for actions may not be implementable and therefore the emergency response organizations must adapt to and cope with uncertain and changing environment (Mendonca, Beroggi, & Wallace, 2003). There have been many attempts to define resilience in various disciplines (Hollnagel, Woods, & Leveson, 2007). Nevertheless, such attempts for emergency management systems (EMS) is still scarce in the existing body of resilience literature. By considering traits of EMS, this study proposes the definition of resilience as ‘ a system’s capability to respond to different kinds of disrupting events and to bring the system back to a desired state in a timely manner with efficient use of resources, and with minimum loss of performance capacity.’ In order to model resilience in EMS, the U.S. NIMS is chosen because it allows for investigation of resilient behavior among different components that inevitably involve both human agents and technological artifacts as joint cognitive systems (JCSs) (Hollnagel & Woods, 2005). In the NIMS, the largest JCS comprises five critical functions: Command, Planning, Operations, Logistics and Finance & Administration (F&A) (Department of Homeland Security, 2008). External stimuli or inputs to this JCS are events that occur outside of its boundary such as uncontrolled events. When these events do occur, they are typically perceived by the ‘boots-on-the-ground’ in the Operations function. The perceived data are reported and transported to the Planning function in which such data are transformed into useful and meaningful information. This information provides knowledge base for generating a set of decisions. Subsequently, Command function selects some of those decisions and authorizes them with adequate resources so that Operations actually take actions for such decisions to the uncontrolled events. This compensation process continues until the JCS achieves its systematic goal which is to put the event under control. On the other hand, Logistics feeds required and requested resources such as workforce, equipment and material for the system operations and F&A does the accounting of resources as those resources are actually used to execute its given missions. Such JCS utilizes two types of memory: a collective working memory (CWM) can be manifested in the form of shared displays, document or whiteboards used by teams; similarly, collective long-term memory (CLTM) can take forms of past accident reports, procedures and guidelines. Based on this conceptual framework for resilience of emergency operations, five Resilient Performance Factors (RPFs) are suggested to make resilience operational in EMS. Such RPFs are adaptive response, rapidity of recovery, resource utilization, performance stability and team situation awareness. Adaptation is one of the most obvious patterns of resilient performance (Leveson et al., 2006; Rankin, Lundberg, Woltjer, Rollenhagen, & Hollnagel, 2014). Another factor that typifies resilience of any socio- technical system is how quickly or slowly it bounces back from perturbations (Hosseini, Barker, & Ramirez-Marquez, 2016). In most systems, resources are constrained. Hence, resilience requires the effective and efficient use of resources to varying demands. As such demands persist over time, the system’s performance level tends to diminish. For the EMS to remain resilient, its performance should be maintained in a stable fashion. Finally, EMS is is expected to possess the ability to perceive what is currently taking place, to comprehend what such occurrence actually means, and to anticipate what may happen and decide what to do about it. When this occurs within a team, it is often referred to as team situation awareness (Endsley, 1995; McManus, Seville, Brunsden, & Vargo, 2007). This resilience model for EMS needs validation and many assumptions and simplifications made in this work require further justification. This model will be discussed and validated by using subsequent data collection from Emergency Operations Training Center operated by Texas A&M Engineering Extension Service (TEEX) and will be reported in future publications.

Disasters have revealed persistent challenges for incident management systems in preparing for, responding to, and recovering from disruptive events. Such challenges have been reflected in recent catastrophic events such as natural disasters, industrial accidents, and terrorist attacks. To address the challenges, a need for resilience of incident management systems has been increasingly recognized (Comfort, Boin, & Demchak, 2010). Resilience is defined as a system’s capacity to adjust its performance before, during and after a disturbance (Hollnagel, Woods, & Leveson, 2007). From the theory of Joint Cognitive System (JCS), resilient performance is rendered through an interplay among the JCS triad: human operators, technological artifacts, and demands from the world (Hollnagel & Woods, 2005; Woods & Hollnagel, 2006). Hence, this study aims to identify resilient performance of an incident management system (e.g., Incident Management Team (IMT)) by investigating interac-tions among the JCS triad. The research team conducted two naturalistic observations at a high-fidelity emergency exercise facility and collected audio and video recordings from participants. These recordings were then weaved together to facilitate the analysis of interactions. To represent the interactions among humans and technological tools that cope with demands from an incident, an Interactive Episode Analysis (IEA) was developed and applied to the collected data. The IEA was designed to capture three C’s of an interaction: Context, Content and Characteristics. Context refers to an initiator, a receiver of the interaction, and a technology used. Content indicates actions and communications that occur between human operators and technical tools. Characteristics refer to frequency and time duration of the interaction. To identify the IMT’s performance to cope with incident demands, an episode was constructed after an inject (a piece of simulated information input) was given to the IMT. Using the IEA, two episodes were extracted as preliminary results. Both similar and different patterns of information management were observed. First, both episodes suggest that the IMT follows a common information flow: collecting incident data (e.g., field report), documenting the data, and disseminating the data to other members of the IMT. In both episodes, participants tended to use similar technologies for a certain information management task. For example, a telephone was used for collection of incident data, a photocopying machine (i.e., printer and photocopier) for documentation, and a paper form for dissemination. On the other hand, dissimilar patterns were captured. As members of I/I Unit in the second episode struggled to find out a preferred method of communication (e.g., paper vs. email), the members interacted with instructors that were not seen in the first episode. As such, the second episode took almost twice the duration of the first episode. The findings from the current study, albeit preliminary, suggest non-linear and dynamic interactions among emergency operators, technical tools, and demands from an incident. As Woods (2006) noted, resilience of a system may not be visible until the system faces disruptive events. In such regards, the IEA would serve as a tool to represent the system’s resilient performance after a work demand. In addition, the IEA showed promise as a diagnostic tool that examines the interactions among the JCT triad. To gather more evidence to support findings in the preliminary analysis, future research will focus on extracting more episodes from the collected data and identifying emerging patterns of resilient performance of the IMT.

Understanding the sources of complexity in advanced Nuclear Power Plant (NPP) control rooms and their effects on human reliability is critical for ensuring safe performance of both operators and the entire system. New generation control rooms will rely more heavily on automation and computerized Human-System Interfaces (HSI). Without proper management, information representation and required operator-system interaction could challenge operator information processing capabilities. This paper provides an initial step in assessing the sources of complexity in the NPP control rooms and introduces a systems-theoretic descriptive model of these sources of complexity leveraging network theory.

User performance with a tabletop display was tested using touch-based and mouse-based interaction in a traditional pointing task. Dependent variables were throughput, error rate, and movement time. In a study with 12 participants, touch had a higher throughput with average of 5.53 bps compared to 3.83 bps for the mouse. Touch also had a lower movement time on average, with block means ranging from 403 ms to 1051 ms vs. 607 ms to 1323 ms with the mouse. Error rates were lower for the mouse at 2.1%, compared to 9.8% for touch. The high error rates using touch were attributed to problems in selecting small targets with the finger. It is argued that, overall, touch input is a preferred and efficient input technique for tabletop displays, but that more research is needed to improve touch selection of small targets.

Background: Posttraumatic stress disorder (PTSD) is a prevalent mental health issue among veterans. Access to PTSD treatment is influenced by geographic (ie, travel distance to facilities), temporal (ie, time delay between services), financial (ie, eligibility and cost of services), and cultural (ie, social stigma) barriers. Objective: The emergence of mobile health (mHealth) apps has the potential to bridge many of these access gaps by providing remote resources and monitoring that can offer discrete assistance to trauma survivors with PTSD and enhance patient-clinician relationships. In this study, we investigate the current mHealth capabilities relevant to PTSD. Methods: This study consists of two parts: (1) a review of publicly available PTSD apps designed to determine the availability of PTSD apps, which includes more detailed information about three dominant apps and (2) a scoping literature review performed using a systematic method to determine app usage and efforts toward validation of such mHealth apps. App usage relates to how the end users (eg, clinicians and patients) are interacting with the app, whereas validation is testing performed to ensure the app’s purpose and specifications are met. Results: The results suggest that though numerous apps have been developed to aid in the diagnosis and treatment of PTSD symptoms, few apps were designed to be integrated with clinical PTSD treatment, and minimal efforts have been made toward enhancing the usability and validation of PTSD apps. Conclusions: These findings expose the need for studies relating to the human factors evaluation of such tools, with the ultimate goal of increasing access to treatment and widening the app adoption rate for patients with PTSD. [JMIR Mhealth Uhealth 2017;5(10):e156]

With advancements in accident investigation models, we now have the means to capture rich and complex accident information. Sophisticated analysis of accidents using systematic frameworks (Leveson et al., 2003; 2009; Sklet, 2004) have shown promise in providing tools to conduct systematic in-depth analysis of multiple socio-technical layers involved in accidents, however these methods are sometimes very large in size or exacerbate the perceived complexity of the accident. In addition, a lack of coding standards, inconsistencies in accident database designs and the sheer amount of data generated has made understanding of this rich set of information a time-consuming and intimidating endeavor for even a well-versed scholar. The goal of this research is to establish the efficacy of network visualization of complex nuclear accident information. A four-phased sequential methodology was developed to create the network representation of incidents. First phase is to generate a list of known and potential sources contributing to accidents using a triangulation of sources and methods including the review of literature, ethnographic observations, expert opinion solicitation, and analysis of previous incidents. Using a systems-theoretic model, the identified sources can be organized into environmental, organizational, instrumentation, and cognitive sources to facilitate the investigation of sources at different systems levels in isolation. Phase two involves mining the existing incident databases for evidence to support the identified sources as well as to identify new accident-specific sources. The output of this phase is an evidence database that holds identifiers that relate to different sources. Several incident databases in the nuclear industry use coding mechanisms where human faults and success, as well as equipment fault are coded separately to facilitate human reliability analysis (HRA) methods. After detailed content analysis, the relevant subcodes could be used as evidence to support the identified sources contributing to accidents. Phase three involves the analysis of actual and potential interactions between sources. Systems-theoretic methods such as STAMP (system-theoretic accident modeling and prevention) (Leveson, 1995, 2009), HAZOP (hazard and operability study) (Kletz, 1983), SAfER and FRAM (Functional Resonance Analysis Method) (Hollnagel, 2012), that use systematic retrospective analyses of accident have shown promise in unveiling complex interactions between sources. Another approach is a simplified method that utilizes the wealth of information coded into accident databases to infer potential interaction between sources. The last phase involves visualizing the accidents as networks where nodes represent sources contributing to the accident and links between nodes represent actual or potential interactions (Sasangohar, Thornburg, Cummings & D’Agostino, 2010). Network representation of accidents enables the measurement and evaluation of characteristics of networks such as connectivity and creates an emergent visual property that facilitates the identification of major sources and interactions. Understanding connectivity and modularity of accident networks can provide insight into the interrelation between sources of failure in an accident. Using accident networks as an analytical approach in identifying the potential interactions between the sources, retrospective and preventative efforts can be made to mitigate the propagation effect of potential interactions between the sources of failures and reducing the connectivity of the network. Using this framework, we visualized 24 major nuclear incidents in United States and analyzed their corresponding networks. While such simplistic method has several limitations, the visualized accident networks have shown promise in facilitating the understanding of complex accidents. Future efforts should evaluate the efficacy of this method to evaluate incidents in other domains.

Sending humans to other planets requires an understanding of the effects of the partial gravity on human motion before attempting to design or build buildings or plan mission tasks. Architecture is the most basic example of human-centered design as everything in a building is to “human” scale. While some modern studies (e.g., Capps, et. al, 1989) reference a study which looked at the humans and forces for the Moon landing (Hewes et. al, 1966), this study was never correlated with the actual lunar data and has many erroneous assumptions. Previous work in Biomechanics was reviewed and the elements of physics required to analyze human motion in partial gravity was analyzed and several basic questions were generated. Included in these studies are NASA studies which look at parabolic flight and apparatus to simulate the effects of partial gravity (NASA/TM-2010-216139, 2010). The key part of physics that drives the changes in human motion is the fact that the momentum of a human or object in motion remains the same while gravity reduces the normal forces on the feet which in turn cause a reduction in the friction reaction forces available for maneuvering or stopping. The study investigates design of several building features for space architecture. These include: Ceiling Height, Door Size, Railing Height, Stairs, Ladders, and Ramps. The first of these the ceiling height relates to the question of does a person “bounce” when they walk in partial gravity. Typical ceilings on Earth range from 2.44 m (8 feet) to 3.05 m (10 feet) Studies of walk to run transition speed for partial gravity were reviewed and they measured the vertical displacement of the hip. This measurement varied by less than 1 cm and correlated to a minimal head height change. Door sizes and railing heights related to the height of 99th percentile humans projected to the year of launch to Mars or the Moon and also included spinal growth caused by 0 g transit. These projections do lead to a taller door opening (25 cm) and raised railing (14.3 cm) as compared to earth. Stairs and ladders both ended up being related to joint angles and human preferences such that they remain the same as on Earth. Chair heights which also relate to counter heights were looked at by reviewing studies of the sit-to-stand motion and comparing the foot and buttocks reaction forces to the friction forces available on Mars and the Moon verses Earth standard. This leads to a recommendation to use Pub height chairs and counters. Flooring and ramps required scaling and also calculating equivalency values to make comparisons. It was determined that the required friction when scaled to Mars would be possible with fairly standard flooring materials. The Lunar case however, would require a combination of high friction flooring and training for nominal movement. To analyze ramps independent calculations were used for friction requirements and then correlated to a study of emergency personnel pushing a trolley with a patient up or down a ramp. Both these methods correlated to an extremely shallow 2.86 degrees (slope 1 in 20) ramp being possible on Mars and ramps not being usable on the Moon. Based on these factors it is recommended that many of features follow standards used on earth and that only the required changes be made such that the habitation resemble Earth structures as much as possible. In addition, Astronaut training should incorporate these factors into their procedures.

Multicomponent products that combine hardware and software (cars, airplanes, and telephones, to name a few) are everywhere in our lives. The commercial release of such products is a compromise between performance capabilities, competitive pricing, and time to market (Challa, Rundle, & Pecht, 2013). As product performance increases, system complexity and the number of failure modes also increase. Of particular importance are “No Fault Found” (NFF) events that occur when a user records a system error and subsequent investigations fail to uncover the reason for the system malfunction – the root cause is unknown (Jones & Hayes, 2001). NFF can result in high warranty costs, product recalls, and diminished reputation (Challa et al., 2013). Surprisingly, most organizations do not explicitly calculate the costs of NFF or use a framework to estimate them (Erkoyuncu, Khan, Hussain, & Roy, 2016). A defining aspect of NFF is the discrepancy between actual and anticipated use conditions (Challa et al., 2013). Anticipated use is often defined by qualification, the passing of tests that demonstrate when a product meets nominal design and manufacturing specifications (Challa et al., 2013). A popular form of qualification is standards-based testing due to its speed, low cost, and applicability to many products (Challa et al., 2013). Standards such as Military Standard (MIL-STD) meet these criteria, but are often inappropriate for specific, actual-use conditions in the field. For example, the Ford Motor Company designed thick film integrated (TFI) ignition modules based on a set of laboratory standards. Cars used in hot climates experienced numerous failures that were initially classified as NFF (because these failures could not be reproduced under the milder laboratory conditions) (Thomas et al., 2002). One remedy to this problem would be to adopt more stringent engineering specifications for qualification. In this research, we analyzed NFF across four industries – automotive electronics, aerospace, medical equipment, and consumer electronics. The analysis is based on four contributors to NFF: testing procedures, intermittent failures, environmental factors, and human factors. Intermittent failures are the re-appearance of equipment failure after remedial actions have taken place (Thomas et al., 2002). Environmental factors (also referred to as environmental monitoring) are the context (or “background”) conditions in which the NFF event occurs. These factors can take on a variety of forms, from vibration and humidity in an aircraft to the diverse demographics of users of a consumer electronic product (Kim & Christiaans, 2016; Moffat, Abraham, Desmulliez, Koltsov, & Richardson, 2008). Case studies (representing each of the four industries) demonstrate that the existing strategies for reducing the occurrence of NFF events are limited. Addressing the four contributors to NFF (testing procedures, intermittent failures, environmental factors, and human factors) allows for the development of a systematic approach to reduce these events. First, one must distinguish between “hard” and “soft” failures. Hard failures are technical or equipment reliability failures (den Ouden, Yuan, Sonnemans, & Brombacher, 2006; Kushniruk & Patel, 2004). Soft failures occur when products fail to meet usability expectations, despite functioning from a technical, reliability standpoint (den Ouden et al., 2006). Hard failures are relevant to the aerospace and automotive electronics industry case studies, while soft failures pertain to medical equipment and consumer electronics. Analysis reveals a number of key insights, including the impact of proper failure classification (what is or is not a NFF event). Proper classification enables organizations to quantify how products perform in the field and which corrective actions are needed to improve reliability and usability.

Purpose Intensive care unit (ICU) nurses get interrupted frequently. Although interruptions take cognitive resources from a primary task and may hinder performance, they may also convey critical information. Effective management of interruptions in ICUs requires the understanding of interruption characteristics, the context in which interruption happens, and interruption content. Methods An observational study was conducted in a cardiovascular ICU at a Canadian teaching hospital. Four observers (1 PhD and 3 undergraduate students) trained in human factors research observed 40 nurses, approximately 1 hour each, over a 3-week period. Data were recorded by the observers in real time, using touchscreen tablet PCs and special software designed for this purpose. Results Although approximately half of the interruptions (~ 51%) happened during high-severity tasks, more than half of these interruptions, which happened during high-severity tasks, conveyed either work- or patient-related information. Furthermore, the rate of interruptions with personal content was significantly higher during low-severity tasks compared with medium- and high-severity tasks. Conclusions Mitigation strategies other than blocking should also be explored. In addition, interrupters might have evaluated primary task severity before interrupting. Therefore, making task severity more transparent may help others modulate when and how they interrupt a nurse.

The Engineering Communication Program at the University of Toronto has recently begun using engineering graduate students as Communication Instructors (CIs) in the Mechanical Engineering portfolio courses and our work in the Mechanical and Industrial Engineering capstone design courses. The move was an attempt to bridge the discipline chasm between communication and disciplinary expertise; this paper begins to document the impact of this interdisciplinarity. Through an analysis of narratives of CI experiences using Engeström’s model of activity theory, we narrowed our focus to an exploration of the changing rules and division of labour that occurred over the duration of the courses. We found that while students and CIs bring different understandings of rules and division of labour to the work, these elements can be changed—and that affect plays a key role in the changes.

Burnout among shiftwork personnel such as nurses are prevalent, and the evidence suggests an increasing trend of nurse drop out in complex healthcare settings. While nurses’ acute and chronic fatigue have been studied, current models of fatigue do not capture the pre-chronic phase we refer to as “aggregate fatigue” – the buildup of fatigue and stress exceeding the capacity for physiological and cognitive recovery processes. Understanding aggregate fatigue requires a holistic understanding of a wide range of contributors including sleep, work, non-work-related stress, cognitive load and other psychosocial factors. This paper proposes an integrated model of fatigue in hospital nursing and presents a comparison to the common models of fatigue and burnout. We use a narrative review of literature to ground this multi-attribute model of aggregate fatigue which may shed light on future methods to identify and mitigate fatigue build-up contributing to burnout.

Post-Traumatic Stress Disorder (PTSD) is a psychiatric condition affecting as much as 20% of the returning veterans from the current wars in Afghanistan and Iraq (Ramchand et al., 2010). Due to its prevalence, assessment and intervention methods for PTSD symptoms among veterans are timely to ensure veterans’ faster recovery and their reintegration into society. A narrative review of literature was conducted to examine the literature on techniques and methods for detection and measurement of PTSD symptoms. Relevant reviews and seminal papers associated with psychophysiological measurements with emphasis on heart rate, the prevalence of PTSD in military veterans, and detection of PTSD were included. Psychophysiology involves the non-invasive recording of biological processes simultaneously (Pole, 2007). The measures that were found to be reliably related to PTSD are: (1) higher resting heart rate; (2) larger heart rate responses to standardized trauma cues; and (3) for idiographic cues facial muscle electromyography (EMG) and heart rate responses (Pole, 2007). Studies based on heart rate found that there were five beats per minute (bpm) increase in resting heart rates for combat veterans who suffer from PTSD compared to those who were not diagnosed (Beckham et al., 2000, Woodward et al., 2009). Buckley et al. (2004) found that for a mixed population (veterans and civilians) PTSD patients had a resting heart rate increase of 6.6 bpm compared to non-PTSD patients while adjusting for covariates. The exact mechanisms of how stress affects heart rate are not well-known; however, it is possible to observe stressful events and relate these to physiological changes in heart rate that can be measured using modern sensors (Andreoli et al., 2010). In the literature, heart rate is analyzed using statistical, geometric, frequency domain, time-frequency and non-linear feature analysis (Acharya et al., 2006). Non-linear features have been developed to quantify the dynamics of heart rate fluctuations. These include approximate entropy, Detrended Fluctuation Analysis (DFA), Lyapunov exponent, Recurrence Plots (RPs) and Correlation Dimension (CD) (Pincus, 1991; Huikuri et al., 2000; Acharya et al., 2004; Acharya et al., 2006). Our synthesis resulted in identification of three research gaps. Heart rate analysis has shown promise to link PTSD symptoms to differences in PTSD and non-PTSD subjects (Pole, 2007) but a characterization of PTSD symptoms from heart rate data seems to remain a research gap. While continuous monitoring of physiological parameters is gaining momentum, this particular method has not been studied to infer key characteristics associated with PTSD among military veterans. Continuous monitoring might be able to highlight muted response to startle or treatment. There is also a research gap in the assessment of heart rate accelerations and decelerations in response to specific PTSD symptoms (Khanade et al., 2017). The investigation into accelerations/decelerations associated with PTSD hyper-arousal triggers might have a potential to detect hyper-arousal instantaneously and would shed light on trigger-specific interventions to reduce harmful effects of PTSD triggers in a timely manner. In addition, most studies were conducted to observe differences among PTSD and non-PTSD populations. More work is warranted to focus on PTSD patients in isolation to explain variety of triggers and their specific physiological reactions.

Diabetes is a prevalent condition affecting millions of patients globally. Some diabetic patients suffer from a deadly condition called Hypoglycemia (sudden drop in blood glucose levels). Continuous Glucose Monitors (CGMs) have been the most pervasive tool used to track blood glucose levels but these tools are invasive and costly. While early detection of hypoglycemia has been studied, current approaches do not leverage tremors; which are a primary symptom of hypoglycemia. A scoping review was conducted to understand the relationship between tremors and hypoglycemia, and to document any efforts that utilized tremor signatures non-invasively to detect hypoglycemic events. Findings suggest that hypoglycemic tremors are a medium frequency tremor, more resistant to hypoglycemic impairment than other symptoms, and have not been fully explored yet. This paper also documents the work in progress to utilize a novel wearable device that predicts the onsets of hypoglycemia using hand tremor sensing.

Nurses represent a large portion of shift workers in United States. Nurses often work long hours, have high workload, and usually participate in multitasking, all of which may lead to high stress, turnover, and burn-out. The turnover rate among nurses tends to be higher than other healthcare professions. Some studies have analyzed the nursing culture to determine the factors that lead to such high turnover and stress. How-ever, most of the studies have relied on self-reported instruments. While objective metrics to assess stress using physiological measures exist, these methods are rarely used in healthcare. The current study documents the findings from a literature review of stress detection techniques in other work domains (e.g., aviation, transportation). Stress detection techniques are explained, along with potential applications to the healthcare sector.

Background Biopharmaceutical products have become an important sector of the pharmaceutical industry in the United States (U.S.). This fast-growing sector is in a critical position in which therapeutic biological products represent over a third of all new drugs in clinical trials or awaiting approval from the U.S. Food and Drug Administration (FDA) (International Trade Administration, n.d.). The development and review of a new therapeutic biological product is a complex process that requires considerable monetary and time investment. This process takes, on average, twelve years, and the estimated average cost of taking a new drug from concept to market exceeds $1 billion (Van Norman, 2016a). After the significant expenditure of manufacturer time and resources, many drugs fail to achieve FDA approval late in the process. Criticism has arisen from the fact that the increasingly complex regulatory environment and expense associated with drug development have caused a lag in the release of new pharmaceuticals to the drug market. Advocacy groups and experts in the area are demanding a more rapid approval and release of new products because they consider the current process to be risk averse, slow, and inefficient (Ty Williams, 2016; Van Norman, 2016a). The FDA has created programs to expedite the approval of drugs and biological products (FDA, 2018). Despite all of these efforts, FDA scrutiny remains a long, costly, and risky process. The goal of this work is the exploration of the factors and gaps relevant to the FDA review and approval process which contribute to process inefficiencies, as well as proposed methods and solutions to address such gaps. Review Findings Researchers who investigated the FDA review and approval operations have identified challenges and constraints in the process (e.g. Baylor, 2014; Conner et al., 2014; Kinch, 2016; Ty Williams, 2016; Van Norman, 2016a, 2016b). Van Norman (2016a) and Ty Williams (2016) emphasizes that the main challenges for the pharmaceuticals are in terms of cost and time. Complexities in the flow of information and the communications network have been identified due to the fact that the process involves multiple FDA resources and constant communication with the applicant. Additionally, complexities could arise from the review team not only having to deal with the flow of new submissions but also with the flow of resubmitted applications, which puts a strain on FDA normal operations by having to share resources between both types of submissions. Other relevant challenges are in terms of bias due to the user fees collected from sponsors and drug manufacturers to support the drug approval process (Ty Williams, 2016) and lack of transparency of non-published drug trial data (Van Norman, 2016b). The review of methods and solutions to address such challenges and constraints has identified a lack of research activity in studying the approval process from the regulatory agency point of view (i.e. from FDA internal operations). Most research efforts are directed toward the incorporation of modeling tools to the drugs development and production practices (e.g. Gernaey & Gani, 2010; Horner, Joshi, & Waghmare, 2017). Reform models to the current FDA review and approval process have been published with the purpose of providing flexible approaches to change the way medical products are brought to market (Thierer & Wilt, 2016; Williams, Joffe, & Slonim, 2016; Klein & Tabarrok, 2016; Conko & Madden, 2000; Gulfo, Briggeman, & Roberts, 2016). The implementation of any of these reform models may imply a shift in the responsibilities of the FDA and therefore may change the organizational structure of the regulatory agency – something that must be addressed and measured for effectiveness. Conclusions Suggesting changes to the review and approval of therapeutic biological products is a challenging task. To the best of our knowledge, none of the academic articles identified in this scoping review have modeled the FDA review and approval process to address issues related to the robustness, reliability and efficiency of its operations from an internal point of view. The reform models identified in the literature are limited in several aspects. For example, there is a general lack of application of scientific methodologies and modeling techniques in understanding FDA as a complex sociotechnical system. In addition, tools and methods to assess their efficacy before implementation are largely absent. Findings from this scoping review suggest an opportunity to employ Model-Based Systems Engineering (MBSE) approaches to provide a systems-oriented descriptive model of the FDA approval process for therapeutic biological products as a service network, with the objective of providing a method to support individual, team, and organizational decision-making to balance the process structure in terms of enforcement and in-formation. This holistic approach will serve several investigative purposes: (1) identify influential sources of variability that cause major delays including individual, team, and organiza-tional decision-making, (2) identify the human-system bottle-necks, (3) identify areas of opportunity for design-driven im-provements, (4) study the effect of induced changes in the sys-tem, and (5) assess the robustness of the structure of the FDA approval process in terms of enforcement and information sym-metry.