Understanding the informal aspects of medication processes to maintain patient safety in hospitals: a sociotechnical ethnographic study in paediatric units.

Adverse drug events (ADEs) are common in hospitals, affecting one in six child in-patients. Medication processes are complex systems. This study aimed to explore the work-as-done of medication safety in three English paediatric units using direct observation and semi-structured interviews. We found that a combination of the physical environment, traditional work systems and team norms were among the systemic barriers to medicines safety. The layout of wards discouraged teamworking and reinforced professional boundaries. Workspaces were inadequate, and interruptions were uncontrollable. A less experienced workforce undertook prescribing and verification while more experienced nurses undertook administration. Guidelines were inadequate, with actors muddling through together. Formal controls against ADEs included checking (of prescriptions and administration) and barcode administration systems, but these did not integrate into workflows. Families played an important part in the safe administration of medication and provision of information about their children but were isolated from other parts of the system.

Formal medicines safety processes in paediatric units are disjointed and disconnected. This has led actors in the system (e.g. nursing and medical staff) to develop informal adaptations to increase resilience. There is a need to incorporate these adaptations into a systems-focussed consideration of safety processes, in order to properly inform the development of medication safety interventions.

Human-artificial intelligence interaction in gastrointestinal endoscopy.

The number and variety of applications of artificial intelligence (AI) in gastrointestinal (GI) endoscopy is growing rapidly. New technologies based on machine learning (ML) and convolutional neural networks (CNNs) are at various stages of development and deployment to assist patients and endoscopists in preparing for endoscopic procedures, in detection, diagnosis and classification of pathology during endoscopy and in confirmation of key performance indicators. Platforms based on ML and CNNs require regulatory approval as medical devices. Interactions between humans and the technologies we use are complex and are influenced by design, behavioural and psychological elements. Due to the substantial differences between AI and prior technologies, important differences may be expected in how we interact with advice from AI technologies. Human-AI interaction (HAII) may be optimised by developing AI algorithms to minimise false positives and designing platform interfaces to maximise usability. Human factors influencing HAII may include automation bias, alarm fatigue, algorithm aversion, learning effect and deskilling. Each of these areas merits further study in the specific setting of AI applications in GI endoscopy and professional societies should engage to ensure that sufficient emphasis is placed on human-centred design in development of new AI technologies.

A conceptual framework for automation disengagements.

A better understanding of automation disengagements can lead to improved safety and efficiency of automated systems. This study investigates the factors contributing to automation disengagements initiated by human operators and the automation itself by analyzing semi-structured interviews with 103 users of Tesla's Autopilot and FSD Beta. The factors leading to automation disengagements are represented by categories. In total, we identified five main categories, and thirty-five subcategories. The main categories include human operator states (5), human operator's perception of the automation (17), human operator's perception of other humans (3), the automation's perception of the human operator (3), and the automation incapability in the environment (7). Human operators disengaged the automation when they anticipated failure, observed unnatural or unwanted automation behavior (e.g., erratic steering, running red lights), or believed the automation is not capable to operate safely in certain environments (e.g., inclement weather, non-standard roads). Negative experiences of human operators, such as frustration, unsafe feelings, and distrust represent some of the adverse human operate states leading to automation disengagements initiated by human operators. The automation, in turn, monitored human operators and disengaged itself if it detected insufficient vigilance or speed rule violations by human operators. Moreover, human operators can be influenced by the reactions of passengers and other road users, leading them to disengage the automation if they sensed discomfort, anger, or embarrassment due to the automation's actions. The results of the analysis are synthesized into a conceptual framework for automation disengagements, borrowing ideas from the human factor's literature and control theory. This research offers insights into the factors contributing to automation disengagements, and highlights not only the concerns of human operators but also the social aspects of this phenomenon. The findings provide information on potential edge cases of automated vehicle technology, which may help to enhance the safety and efficiency of such systems.

Call me Ishmael: addressing the white whale of team communication in the operating room with labelled surgical caps at an academic medical centre.

INTRODUCTION: Effective communication in the operating room (OR) is crucial. Addressing a colleague by their name is respectful, humanising, entrusting and associated with improved clinical outcomes. We aimed to enhance team communication in the perioperative environment by offering personalised surgical caps labelled with name and provider role to all OR team members at a large academic medical centre. MATERIALS AND METHODS: This was a quasi-experimental, uncontrolled, before-and-after quality improvement study. A survey regarding perceptions of team communication, knowledge of names and roles, communication barriers, and culture was administered before and after cap delivery. Survey results were measured on a 5-point Likert Scale; descriptive statistics and mean scores were compared. All cause National Surgical Quality Improvement Project (NSQIP) morbidity and mortality outcomes for surgical specialties were examined. RESULTS: 1420 caps were delivered across the institution. Mean survey scores increased for knowing the names and roles of providers around the OR, feeling that people know my name and feeling comfortable communicating without barriers across disciplines. The mean score for team communication around the OR is excellent was unchanged. The highest score both before and after was knowing the name of an interdisciplinary team member is important for patient care. A total of 383 and 212 providers participated in the study before and after cap delivery, respectively. Participants agreed or strongly agreed that labelled surgical caps made it easier to talk to colleagues (64.9%) while improving communication (66.0%), team culture (60.5%) and patient care (56.8%). No significant differences were noted in NSQIP outcomes. CONCLUSIONS: Personalised labelled surgical caps are a simple, inexpensive tool that demonstrates promise in improving perioperative team communication. Creating highly reliable surgical teams with optimal communication channels requires a multifaceted approach with engaged leadership, empowered front-line providers and an institutional commitment to continuous process improvement.

Challenges With Robot-Assisted Surgery Setup for Complex Minimally Invasive Upper Gastrointestinal Surgery.

BACKGROUND: The utilization of robot-assisted approaches to surgery has increased significantly over the last two decades. This has introduced novel complexities into the operating room environment, requiring management of new challenges and workflow adaptation. This study aimed to analyze challenges in the surgical setup for complex upper gastrointestinal robot-assisted surgery (UGI-RAS) and identify opportunities for solutions. METHODS: Direct observations of surgical setup processes for UGI-RAS were performed by a trained Human Factors researcher at a non-profit academic medical center in Southern California. Setup tasks were subdivided into five phases: (1) before wheels-in; (2) patient transfer and anesthesia induction; (3) patient preparation; (4) surgery preparation; and (5) robot docking. Start/end times for each phase/task were documented along with workflow disruption (FD) narratives and timestamps. Setup tasks and FDs were analyzed using descriptive statistics. RESULTS: Twenty UGI-RAS setup procedures were observed between May-November 2023: sleeve gastrectomy +/- hiatal hernia repair (n = 9, 45.00%); para-esophageal hernia repair +/- fundoplication (n = 8, 40.00%); revision to Roux-en-Y gastric bypass (n = 2, 10.00%); and gastric band removal (n = 1, 5.00%). Frequent FDs included planning breakdowns (n = 20, 29.85%), equipment/supply management (n = 17, 25.37%), patient care coordination (n = 8, 11.94%), and equipment challenges (n = 8, 11.94%). Eleven of 20 observations were first-start cases, of which 10 experienced delayed starts. DISCUSSION: Interventions aimed at improving workflows during UGI-RAS setup include performing pre-operative team huddles and conducting trainings aimed at team coordination and equipment challenges. These solutions could result in improved teamwork, efficiency, and communication while reducing case start delays and turnover time.

Academic Detailing as a Health Information Technology Implementation Method: Supporting the Design and Implementation of an Emergency Department-Based Clinical Decision Support Tool to Prevent Future Falls.

BACKGROUND: Clinical decision support (CDS) tools that incorporate machine learning-derived content have the potential to transform clinical care by augmenting clinicians' expertise. To realize this potential, such tools must be designed to fit the dynamic work systems of the clinicians who use them. We propose the use of academic detailing-personal visits to clinicians by an expert in a specific health IT tool-as a method for both ensuring the correct understanding of that tool and its evidence base and identifying factors influencing the tool's implementation. OBJECTIVE: This study aimed to assess academic detailing as a method for simultaneously ensuring the correct understanding of an emergency department-based CDS tool to prevent future falls and identifying factors impacting clinicians' use of the tool through an analysis of the resultant qualitative data. METHODS: Previously, our team designed a CDS tool to identify patients aged 65 years and older who are at the highest risk of future falls and prompt an interruptive alert to clinicians, suggesting the patient be referred to a mobility and falls clinic for an evidence-based preventative intervention. We conducted 10-minute academic detailing interviews (n=16) with resident emergency medicine physicians and advanced practice providers who had encountered our CDS tool in practice. We conducted an inductive, team-based content analysis to identify factors that influenced clinicians' use of the CDS tool. RESULTS: The following categories of factors that impacted clinicians' use of the CDS were identified: (1) aspects of the CDS tool's design (2) clinicians' understanding (or misunderstanding) of the CDS or referral process, (3) the busy nature of the emergency department environment, (4) clinicians' perceptions of the patient and their associated fall risk, and (5) the opacity of the referral process. Additionally, clinician education was done to address any misconceptions about the CDS tool or referral process, for example, demonstrating how simple it is to place a referral via the CDS and clarifying which clinic the referral goes to. CONCLUSIONS: Our study demonstrates the use of academic detailing for supporting the implementation of health information technologies, allowing us to identify factors that impacted clinicians' use of the CDS while concurrently educating clinicians to ensure the correct understanding of the CDS tool and intervention. Thus, academic detailing can inform both real-time adjustments of a tool's implementation, for example, refinement of the language used to introduce the tool, and larger scale redesign of the CDS tool to better fit the dynamic work environment of clinicians.

Managing acoustic noise within MRI: A qualitative interview study among Swedish radiographers.

INTRODUCTION: Acoustic noise from magnetic resonance imaging (MRI) can cause hearing loss and needs to be mitigated to ensure the safety of patients and personnel. Capturing MR personnel's insights is crucial for guiding the development and future applications of noise-reduction technology. This study aimed to explore how MR radiographers manage acoustic noise in clinical MR settings. METHODS: Using a qualitative design, we conducted semi-structured individual interviews with fifteen MR radiographers from fifteen hospitals around Sweden. We focused on the clinical implications of participants' noise management, using an interpretive description approach. We also identified sociotechnical interactions between People, Environment, Tools, and Tasks (PETT) by adopting a Human Factors/Ergonomics framework. Interview data were analyzed inductively with thematic analysis (Braun and Clarke). RESULTS: The analysis generated three main themes regarding MR radiographers' noise management: (I) Navigating Occupational Noise: Risk Management and Adaptation; (II) Protecting the Patient and Serving the Exam, and (III) Establishing a Safe Healthcare Environment with Organizational Support. CONCLUSION: This study offers insights into radiographers' experiences of managing acoustic noise within MRI, and the associated challenges. Radiographers have adopted multiple strategies to protect patients and themselves from adverse noise-related effects. However, they require tools and support to manage this effectively, suggesting a need for organizations to adopt more proactive, holistic approaches to safety initiatives. IMPLICATIONS FOR PRACTICE: The radiographers stressed the importance of a soundproofed work environment to minimize occupational adverse health effects and preserve work performance. They acknowledge noise as a common contributor to patient distress and discomfort. Providing options like earplugs, headphones, mold putty, software-optimized "quiet" sequences, and patient information were important tools. Fostering a safety culture requires proactive safety efforts and support from colleagues and management.

The influence of digital technologies on resilient performance: Contributions, drawbacks, and a research agenda.

The growing use of digital technologies (DTs) has a myriad of implications to socio-technical systems, which are not yet fully recognised. This paper investigates the contributions and drawbacks of DTs to resilient performance (RP), an aspect that so far has received less attention in comparison to others such as efficiency. To this end, a survey questionnaire was applied to 79 academics and practitioners linked to resilience engineering. Data analysis involved descriptive statistics and a thematic analysis of the open-text responses to the survey. Mixed impacts were identified, with 10 themes related to contributions and 16 to drawbacks. Regarding the contributions, the results highlighted the use of DTs for monitoring and anticipating system performance. Machine learning seems to be the most promising approach for this purpose. A key drawback is the need for developing new skills across the workforce so that they can make sense of the outputs of DTs and are aware of their strengths and weaknesses. The human role is expected to remain crucial for RP, which makes the current coordination difficulties with DTs even more important to address. A research agenda composed of five topics is proposed, encompassing description, prescription, and assessment. The agenda emphasizes the need for mapping the attributes or functionalities of DTs onto resilience concepts, models, and frameworks.

Large Language Models and User Trust: Consequence of Self-Referential Learning Loop and the Deskilling of Health Care Professionals.

As the health care industry increasingly embraces large language models (LLMs), understanding the consequence of this integration becomes crucial for maximizing benefits while mitigating potential pitfalls. This paper explores the evolving relationship among clinician trust in LLMs, the transition of data sources from predominantly human-generated to artificial intelligence (AI)-generated content, and the subsequent impact on the performance of LLMs and clinician competence. One of the primary concerns identified in this paper is the LLMs' self-referential learning loops, where AI-generated content feeds into the learning algorithms, threatening the diversity of the data pool, potentially entrenching biases, and reducing the efficacy of LLMs. While theoretical at this stage, this feedback loop poses a significant challenge as the integration of LLMs in health care deepens, emphasizing the need for proactive dialogue and strategic measures to ensure the safe and effective use of LLM technology. Another key takeaway from our investigation is the role of user expertise and the necessity for a discerning approach to trusting and validating LLM outputs. The paper highlights how expert users, particularly clinicians, can leverage LLMs to enhance productivity by off-loading routine tasks while maintaining a critical oversight to identify and correct potential inaccuracies in AI-generated content. This balance of trust and skepticism is vital for ensuring that LLMs augment rather than undermine the quality of patient care. We also discuss the risks associated with the deskilling of health care professionals. Frequent reliance on LLMs for critical tasks could result in a decline in health care providers' diagnostic and thinking skills, particularly affecting the training and development of future professionals. The legal and ethical considerations surrounding the deployment of LLMs in health care are also examined. We discuss the medicolegal challenges, including liability in cases of erroneous diagnoses or treatment advice generated by LLMs. The paper references recent legislative efforts, such as The Algorithmic Accountability Act of 2023, as crucial steps toward establishing a framework for the ethical and responsible use of AI-based technologies in health care. In conclusion, this paper advocates for a strategic approach to integrating LLMs into health care. By emphasizing the importance of maintaining clinician expertise, fostering critical engagement with LLM outputs, and navigating the legal and ethical landscape, we can ensure that LLMs serve as valuable tools in enhancing patient care and supporting health care professionals. This approach addresses the immediate challenges posed by integrating LLMs and sets a foundation for their maintainable and responsible use in the future.

Unveilling the hidden skillset: exploring non-technical skills in surgical education across spanish medical universities.

BACKGROUND: Non-Technical Skills (NTS) are cognitive, social, and personal resource skills that are crucial in complex and high-risk environments. The aims of our research are to determine the prevalence and content of NTS in the surgical rotation teaching guides of the Medicine Degree programs in Spanish Universities, to identify the most prevalent types and subtypes of NTS, and to analyze factors associated with the prevalence of surgical NTS in Medical Schools in Spain. METHODS: Descriptive observational cross-sectional study involving the identification and collection of competencies outlined in the surgical rotation teaching guides of Spanish Medical Schools. Information regarding university performance was obtained from the Foundation for Knowledge and Development Ranking webpage. The "Non-Technical Skills for Surgeons" (NOTSS) system was used to classify each competency in the teaching guides as NTS (categories and elements) and technical skills. Disagreements were resolved through group consensus. RESULTS: A total of 1,846 competencies were analyzed in surgical rotations of the Medicine Degree programs across 40 Spanish Universities, with 99 competencies identified as surgical NTS, accounting for 5% of the total. The most frequently identified surgical NTS were "Decision Making" (46%), "Communication & Teamwork" (25%), and "Leadership" (19%). Additionally, several NOTSS were not identified in any institution. Public universities and those including a greater number of competencies had a higher rate of surgical NTS competencies, and we did not find a correlation between surgical NTS competencies and quality indices of University Centers. CONCLUSIONS: There is a limited presence of surgical NTS in the educational plans of Spanish Universities.

How will technology change people's home care in the next 20 years? A strategic foresight study.

The rapid expansion of home health care has raised many unresolved issues and will have far-reaching consequences that can only be overcome with a holistic approach to help build and use collective intelligence in a structured, systemic way to anticipate developments. In this frame, the set of issues covered by the human factors research field will significantly impact the safety, quality, and effectiveness of home health care. However, only with a gaze of strategic foresight will we be capable of exploring, anticipating, and shaping the future. A group of researchers from the Italian Society of Ergonomics and Human Factors (SIE) has developed a road map to help all the stakeholders involved in this process.

A Strategic Foresight study was conducted to define a preferred scenario of home care in the next 20 years. A hybrid survey method called Human-Centred Foresight was applied. The results achieved in the study show a possible scenario of home care that can define medium- and long-term goals from today until 2041.

Human Factors Contributing to Infection Prevention in Outpatient Hemodialysis Centers: A Mixed Methods Study.

RATIONALE & OBJECTIVE: Infection prevention efforts in dialysis centers can avert patient morbidity and mortality but are challenging to implement. The objective of this study was to better understand how the design of the work system might contribute to infection prevention in outpatient dialysis centers. STUDY DESIGN: Mixed methods, observational study. SETTING & PARTICIPANTS: Six dialysis facilities across the United States visited by a multidisciplinary team over 8 months. ANALYTICAL APPROACH: At each facility, structured macroergonomic observations were undertaken by a multidisciplinary team using the SEIPS 1.0 model. Ethnographic observations were collected about staff encounters with dialysis patients including the content of staff conversations. Selective and axial coding were used for qualitative analysis and quantitative data were reported using descriptive statistics. RESULTS: Organizational and sociotechnical barriers and facilitators to infection prevention in the outpatient dialysis setting were identified. Features related to human performance, (eg, alarms, interruptions, and task stacking), work system design (eg, physical space, scheduling, leadership, and culture), and extrinsic factors (eg, patient-related characteristics) were identified. LIMITATIONS: This was an exploratory evaluation with a small sample size. CONCLUSIONS: This study used a systematic macroergonomic approach in multiple outpatient dialysis facilities to identify infection prevention barriers and facilitators related to human performance. Several features common across facilities were identified that may influence infection prevention in outpatient care and warrant further exploration.

Assessment and application of non-technical skills in robotic-assisted surgery: a systematic review.

BACKGROUND: Undeniably, robotic-assisted surgery (RAS) has become very popular in recent decades, but it has introduced challenges to the workflow of the surgical team. Non-technical skills (NTS) have received less emphasis than technical skills in training and assessment. The systematic review aimed to update the evidence on the role of NTS in robotic surgery, specifically focusing on evaluating assessment tools and their utilisation in training and surgical education in robotic surgery. METHODS: A systematic literature search of PubMed, PsycINFO, MEDLINE, and EMBASE was conducted to identify primary articles on NTS in RAS. Messick's validity framework and the Modified Medical Education Research Study Quality Instrument were utilised to evaluate the quality of the validity evidence of the abstracted articles. RESULTS: Seventeen studies were eligible for the final analysis. Communication, environmental factors, anticipation and teamwork were key NTS for RAS. Team-related factors such as ambient noise and chatter, inconveniences due to repeated requests during the procedure and constraints due to poor design of the operating room may harm patient safety during RAS. Three novel rater-based scoring systems and one sensor-based method for assessing NTS in RAS were identified. Anticipation by the team to predict and execute the next move before an explicit verbal command improved the surgeon's situational awareness. CONCLUSION: This systematic review highlighted the paucity of reporting on non-technical skills in robotic surgery with only three bespoke objective assessment tools being identified. Communication, environmental factors, anticipation, and teamwork are the key non-technical skills reported in robotic surgery, and further research is required to investigate their benefits to improve patient safety during robotic surgery.

Predicting preferred motorcycle riding postures to support human factors/ergonomic trade-off analyses within a multi-objective optimisation-based digital human model.

Digital human models (DHM) can predict how users might interact with new vehicle geometry during early-stage design, an important precursor to conducting trade-off analyses. However, predicting human postures requires assumptions about which performance criteria best predict realistic postures. Focusing on the design of motorcycles, we do not know what performance criteria drive preferred riding postures. Addressing this gap, we aimed to identify which performance criteria and corresponding weightings best predicted preferred motorcycle riding postures when using a DHM. To address our aim, we surveyed the literature to find experimental data specifying joint angles that correspond to preferred riding postures. We then deployed a response surface methodology to determine which performance criteria and weightings optimally predicted the preferred riding postures when using a DHM. Weighting the minimisation of the discomfort performance criteria (an aggregate of joint range of motion, displacement from neutral and joint torque) best predicted preferred motorcycle riding postures.

This study describes how we learned what performance criteria and weightings were necessary to best predict riding postures for a cruiser-like motorcycle when using a digital human model. We learned to prioritise the minimise discomfort performance criteria to predict riding postures that best match experimental data.

Quantification of safety improvements and human-machine tradeoffs in the transition to automated driving.

The assumption of reduced human error-related crashes with increasing levels of automation in pursuing Level 5 automation lacks empirical evidence. As automation levels rise, human error-induced safety hazards are anticipated to decrease, while machine error-induced hazards will increase. However, a quantitative index capturing this tradeoff is absent. Additionally, theoretical modeling of safety improvements during the transition to automated driving remains unexplored, particularly concerning reducing human error-related hazards. These limitations impede the understanding of safety from human and machine perspectives for Automated Vehicle (AV) specialists and manufacturers. This research addresses these gaps by investigating safety performance associations between human and machine factors using the "Human-Machine conflict reduction ratio" (H/M ratio), a novel metric. The study aims to establish safety improvements related to human errors under various automation levels. Sixty participants completed driving tasks on a driving simulator at Levels 0, 4, 3, and 2. Safety performance measures, including conflict frequency and severity, were computed. As a result, Level 4 exhibits the largest decrease (93.3%) compared to manual driving, followed by Level 2 (70.7%) and Level 3 (40.5%). The H/M ratio measures the tradeoff between reducing human and machine error-induced hazards, with Level 2 demonstrating the highest ratio, followed by Levels 4 and 3. Safety performance is evaluated by considering all possible types of human errors at each automation level. Theoretical models from a human factor's perspective are employed to estimate safety improvements at each level. This research contributes to a comprehensive understanding of safety in the "human-machine cooperative driving" phase, offering insights to AV industry practitioners and stakeholders.

Applying Human Factors and Systems Simulation Methods to Inform a Multimillion-Dollar Healthcare Decision.

PURPOSE: This article describes a case study of a collaborative human factors (HF) and systems-focused simulation (SFS) project to evaluate potential patient and staff safety risks associated with a multimillion-dollar design and construction decision. BACKGROUND: The combined integration of HF and SFS methods in healthcare related to testing and informing the design of new environments and processes is underutilized. Few realize the effectiveness of this integration in healthcare to reduce risk and improve decision-making, safety, design, efficiency, patient experience, and outcomes. This project showcases how the combined use of HF and SFS methods can provide objective evidence to help inform decisions. METHODS: The project was initiated by a healthcare executive team looking for an objective, user informed analysis of a current connector passageway between two existing buildings. The goal was to understand the implications of keeping the current route for simultaneous use for public and patients service flow versus building and financing a new passageway for separate flow and transport. An interprofessional team of intensive care unit professionals participated in two simulations designed to test the current connector. A failure mode and effects analysis and qualitative debrief feedback was used to evaluate risks and potential failures. RESULTS: The evaluation resulted in data that enabled informed executive decision making for the most effective, efficient, and safest option for public, staff, and patient transport between two buildings. This evaluation resulted in the decision to go forward with building a multimillion-dollar new connector passageway to improve integrated care and transport.

Benefits of Usability Evaluation in the Development Process of Diabetes Technologies Using the Example of a Continuous Glucose Monitoring System Prototype.

BACKGROUND: Usability engineering analyzes the interaction between the intended users and a device. Its implementation is mandatory for manufacturers to obtain regulatory approval for the European market. The aim of this evaluation was assessing the role of usability testing in the development process. For this purpose, a continuous glucose monitoring (CGM) device under development was investigated to determine whether it could be used safely and effectively by the intended users. METHODS: Conduct of the usability testing was based on the international standard IEC 62366-1. Medical device use of CGM-experienced and non-experienced users (n = 15 each) was observed without initial training in use scenarios containing 18 tasks. The success rate of task completion was determined and the System Usability Scale (SUS) score was calculated from a questionnaire. A prototype of the FiberSense CGM System (EyeSense GmbH, Großostheim, Germany), comprising of a single-use sensor and a reusable detector, was investigated. RESULTS: Most use errors made by both user groups were related to ease of handling of the reusable detectors. The SUS scores achieved in this study were below the pre-defined SUS score acceptance criterion of ≥68. The most frequently mentioned reason for use errors was an incomprehensible and non-chronological instructions for use (IFU). CONCLUSIONS: The evaluation provides valuable insights on how to improve usability of the prototype device and demonstrates the value of conducting structured usability testing prior to product finalization. The results reflected areas for improvement of the user interface, mainly by restructuring the IFU, provision of an additional leaflet, and device training prior to use.

Terrain park injuries and risk factors in western Canadian resorts, 2008-2009 to 2017-2018: insights for risk management.

Terrain parks (TP) are popular attractors to snowsport resorts for both skiers and snowboarders, however there is some concern about the risk of severe injury. TP risk management needs to balance the business case against the human cost of injury. To inform effective TP risk management strategies, it essential to understand risk factors, and injury frequency and severity. To this end, a retrospective inductive analysis of Canada West Ski Areas Association's Accident Analyzer database (2008-2009 to 2017-2018). Inclusion criteria., (i) at least 8 seasons of matching injury and participation data, (ii) minimum of 10 TP injuries p.a., (iii) activity either skiing or snowboarding, and (iv) injury location was coded as terrain park/rail. Data was excluded for ticket type N/A. Anonymised and deidentified secondary data was entered into SPSS for analysis. Between group differences were explored via χ2 analysis with Yates' Continuity Correction for 2 × 2 tables and an inductive data driven approach to explore other factors. From this data, 12,602 injuries were in TPs across 28 resorts. 11,940 (94.7%) met the inclusion criteria (14.2% female; 86.5% <25 years; 73.0% snowboarders. 50.8% were male snowboarders <25 years). Higher levels of helmet use were not correlated with a decline in reported head injuries. Day-ticket holders were more likely to be injured on their first two uses of a run than season pass holders. More snowboarders injured in TPs (59.7%) went to hospital than skiers (51.0%). Thus, participants injured in TP are typically younger, male, and snowboarders with either a Season Pass or day ticket, thus potentially a distinct target group for injury mitigation and prevention strategies and communications. The application of other frameworks such as the hierarchy of control and socioecological framework reflects the complex multifactorial systems in which snowsports occur and from which more targeted risk management strategies may emerge to mitigate injury risk while maintaining TP appeal.