Findings, progress, and lessons learned during the first 3 years of a student-led interprofessional health clinic in regional Australia.

We describe the establishment and operation of a student-led interprofessional chronic disease prevention and management clinic in regional Australia. Our aim was twofold. First, to report on service delivery, student placement, and health outcome data; and second, to discuss key lessons learned during the first 3½ years of clinic operations. Between July 2019 and December 2022, 146 (79.3%) clinic participants completed the 4-month program and participated in an average of 48.4 occasions of service (total 7,060). The clinic supported 1,060 clinical placement weeks across 147 health students. There was a significant improvement across health measures reported at program completion, with the largest changes observed for the 6-min walk test and preference-adjusted quality of life. Nine key challenges and lessons were identified that affected operations and service delivery, which should be of interest to healthcare teams considering establishing an interprofessional student-led clinic.

Testing the reliability of accident analysis methods: a comparison of AcciMap, STAMP-CAST and AcciNet.

Accident analysis methods are used to model the multifactorial cause of adverse incidents. Methods such as AcciMap, STAMP-CAST and recently AcciNet, are systemic approaches that support the identification of safety interventions across sociotechnical system levels. Despite their growing popularity, little is known about how reliable systems-based methods are when used to describe, model and classify contributory factors and relationships. Here, we conducted an intra-rater and inter-rater reliability assessment of AcciMap, STAMP-CAST and AcciNet using the Signal Detection Theory (SDT) paradigm. A total of 180 hours' worth of analyses across 360 comparisons were performed by 30 expert analysts. Findings revealed that all three methods produced a weak to moderate positive correlation coefficient, however the inter-rater reliability of STAMP-CAST was significantly higher compared to AcciMap and AcciNet. No statistically significant or practically meaningful differences were found between methods in the overall intra-rater reliability analyses. Implications and future research directions are discussed.

Practitioners who undertake accident analysis within their organisations should consider the use of STAMP-CAST due to the significantly higher inter-rater reliability findings obtained in this study compared to AcciMap and AcciNet, particularly if they tend to work alone and/or part of relatively small teams.

Towards a unified model of accident causation: refining and validating the systems thinking safety tenets.

The systems thinking tenets were developed based on a synthesis of contemporary accident causation theory, models and approaches and encapsulate 15 features of complex systems that interact to create both safety and adverse events. Whilst initial testing provided supportive evidence, the tenets have not yet been subject to formal validation. This article presents the findings from a three-round Delphi study undertaken to refine and validate the tenets and assess their suitability for inclusion in a unified model of accident causation. Participants with expertise in accident causation and systems thinking provided feedback on the tenets and associated definitions until an acceptable level of consensus was achieved. The results reduced the original 15 tenets to 14 and 10 were identified as important to include in unified model of accident causation. The refined systems thinking tenets are presented along with future research directions designed to facilitate their use in safety practice.Practitioner summary: This article presents a refined and validated set of systems thinking tenets which describe features of complex systems that interact to create adverse events. The tenets can be used by practitioners to proactively identify safety leading indicators and contributory factors during adverse event analysis.

Using systems thinking-based risk assessment methods to assess hazardous manual tasks: a comparison of Net-HARMS, EAST-BL, FRAM and STPA.

Formal risk assessment is a component of safety management relating to hazardous manual tasks (HMT). Systems thinking approaches are currently gaining interest for supporting safety management. Existing HMT risk assessment methods have been found to be limited in their ability to identify risks across the whole work system; however, systems thinking-based risk assessment (STBRA) methods were not designed for the HMT context and have not been tested in this area. The aim of this study was to compare the performance of four state-of-the-art STBRA methods: Net-HARMS, EAST-BL, FRAM and STPA to determine which would be most useful for identifying HMT risks. Each method was independently applied by one of four analysts to assess the risks associated with a hypothetical HMT system. The outcomes were assessed for alignment with a benchmark analysis. Using signal detection theory (SDT), overall STPA was found to be the best performing method having the highest hit rate, second lowest false alarm rate and highest Matthews Correlation Coefficient of the four methods.Practitioner summary: A comparison of four systems thinking risk assessment methods found that STPA had the highest level of agreement with the benchmark analysis and is the most suitable for practitioners to use to identify the risks associated with HMT systems.

Impact of the COVID-19 pandemic on student supervision and education in health care settings: A state-wide survey of health care workers.

OBJECTIVE: To investigate student supervisor experiences of supervising students on clinical placements since the onset of the COVID-19 pandemic. BACKGROUND: Studies on the impact of COVID-19 on student clinical placements have focused largely on student reports and have been specific to individual professions or topic areas. There is a need to investigate student supervisor experiences. This study was conducted in Queensland (Australia) in four regional and rural public health services and four corresponding primary health networks. METHODS: The anonymous, mixed methods online survey, consisting of 35 questions, was administered to student supervisors from allied health, medicine, nursing and midwifery between May and August 2021. Numerical data were analysed descriptively using chi-square tests. Free-text comments were analysed using content analysis. RESULTS: Complete datasets were available for 167 respondents. Overall trends indicated perceived significant disruptions to student learning and support, plus mental health and well-being concerns for both students and supervisors. Extensive mask wearing was noted to be a barrier to building rapport, learning and teaching. Some positive impacts of the pandemic on student learning were also noted. CONCLUSIONS: This study has highlighted the perceived impact of the pandemic on supervisors' mental health, and on the mental health, learning and work readiness of students. This study provides evidence of the pandemic impacts on student clinical placements from a supervisor point of view. Findings can assist in future-proofing clinical education and ensuring that students continue to receive learning experiences of benefit to them, meeting curriculum requirements, in the event of another pandemic.

Testing the reliability and validity of risk assessment methods in Human Factors and Ergonomics.

There is growing interest in the use of systems-based risk assessment methods in Human Factors and Ergonomics (HFE). The purpose of this study was to test the intra-rater reliability and criterion-referenced concurrent validity of three systems-based risk assessment approaches: (i) the Systems-Theoretic Process Analysis (STPA) method; (ii) the Event Analysis of Systemic Teamwork Broken Links (EAST-BL) method; and, (iii) the Network Hazard Analysis and Risk Management System (Net-HARMS) method. Reliability and validity measures were obtained using the Signal Detection Theory (SDT) paradigm. Whilst STPA identified the highest number of risks, the findings indicate a weak to moderate level of reliability and validity for STPA, EAST-BL and Net-HARMS. There were no statistically significant differences between the methods across analyses. The results suggest that there is merit to the continued use of systems-based risk assessment methods following a series of methodological extensions that aim to enhance the reliability and validity of future applications. Practitioner summary The three risk assessment methods produced weak to moderate levels of stability and accuracy regarding their capability to predict risks. There is a pressing need to further test the reliability and validity of safety methods in Human Factors and Ergonomics.

The impact of power on health care team performance and patient safety: a review of the literature.

Communication failure within health care teams is a major cause of patient harm across health care settings. Factors which contribute to communication failure include actual or perceived 'power'. Whilst a great deal of ergonomics research has focussed on teamwork in health care, the role of power in relation to measurable patient safety and performance outcomes remains relatively unknown. This article presents the findings from a review of the literature on power within multidisciplinary health care team settings. Following a systematic literature search, nineteen studies were evaluated in terms of research design, methods and analyses across the included studies. The main impacts resulting from power imbalances include negative effects on team collaboration, decision-making, communication and overall performance. Wider patient safety research, and more specifically the ergonomics discipline, is encouraged to address the complex interplay between power and teamwork in the health care sector.Practitioner Statement: We conducted a review of studies focussed on the influence of power on teamwork in health care. The findings show that power can have negative impacts on collaboration, decision-making, communication, and team performance. We conclude that power represents an important area for ergonomics, both in health care and other settings.Abbreviations: CRM: crew resource management; TEM: threat and error management; SNA: social network analysis; EAST: event analysis of systemic teamwork.

Complexity theory in accident causation: using AcciMap to identify the systems thinking tenets in 11 catastrophes.

The quest to explain and understand the cause of accidents is both ever-present and ongoing amongst the safety science community. In an attempt to advance the theory and science of accident causation, researchers have recently formalised a set of '15 systems thinking tenets' that cover the conditions and characteristics of work systems that are believed to contribute to the cause of accidents. The purpose of this study was to attempt to identify the systems thinking tenets across a range of different systems and accidents using the Accident Mapping (AcciMap) method. The findings suggest that the tenets can be attributed to play a role in accident causation, however as a result of this process, the capability of AcciMap has been brought into question. Implications and directions for future research are described. Practitioner Summary: This study is an extension of previous work that suggested there was a need to test for the 'systems thinking tenets of accident causation' in a multi-incident dataset. We used AcciMap to evaluate whether it has the capability to support ongoing accident analysis activities in ergonomics research.

Methods matter: exploring the 'too much, too soon' theory, part 1: causal questions in sports injury research.

BACKGROUND: It is widely accepted that athletes sustain sports injury if they train 'too much, too soon'. However, not all athletes are built the same; some can tolerate more training than others. It is for this reason that prescribing the same training programme to all athletes to reduce injury risk is not optimal from a coaching perspective. Rather, athletes require individualised training plans. In acknowledgement of athlete diversity, it is therefore essential to ask the right causal research question in studies examining sports injury aetiology. PURPOSE: In this first part of a British Journal of Sports Medicine educational series, we present four different causal research questions related to the 'too much, too soon' theory and critically discuss their relevance to sports injury prevention. CONTENT: If it is true that there is no 'one size fits all' training programme, then we need to consider by how much training can vary depending on individual athlete characteristics. To provide an evidence-base for subgroup-specific recommendations, a stronger emphasis on the following questions is needed: (1) How much training is 'too much' before athletes with different characteristics sustain sports-related injury? and (2) Does the risk of sports injury differ among athletes with a certain characteristic (eg, high experience) compared with athletes with other characteristics (eg, low experience) depending on how much training they perform? CONCLUSION: We recommend that sports injury researchers aiming to examine the 'too much, too soon' theory should carefully consider how they, assisted by coaches, athletes and clinicians, pose their causal research question. In the light of the limitations of population-based prevention that intends to provide all athletes with the same advice, we argue that a stronger emphasis on research questions targeting subgroups of athletes is needed. In doing so, researchers may assist athletes, clinicians and coaches to understand what training advice/programme works best, for whom and under what circumstances.

Radical systems thinking and the future role of computational modelling in ergonomics: an exploration of agent-based modelling.

We are teetering on the precipice of the imminent Fourth Industrial Revolution. In this new age, systems are set to become more densely intraconnected and interconnected, and massive sociotechnical systems exhibiting unprecedented levels of complexity will increasingly take hold. At the dawning of this new age, the Ergonomics discipline must reflect on its preparedness for tackling problems in these novel systems. This paper engages in this reflection by putting forth a critical commentary on the implication of these changes on the discipline and discusses the utility of our current methods in this new paradigm. A resulting Radical Systems Thinking in Ergonomics Manifesto is put forward - a set of mandates to guide practitioners and researchers in the development of new methods capable of coping with these imminent challenges. From the manifesto are derived a series of capability requirements for future computational modelling approaches in Ergonomics. Practitioner summary: The goal of this paper was to inspire the Ergonomics community to pursue further applications involving computational modelling approaches such as Agent-Based Modelling. It presents a manifesto for the future of the discipline, and from this the capabilities that future computational modelling approaches need to possess. Abbreviations: 1IR: first industrial revolution; 2IR: second industrial revolution; 3IR: third industrial revolution; 4IR: fourth industrial revolution; ABM: agent based model; AI: artificial intelligence; AoF: allocation of function; CPA: cyber physical attack; CPS: cyber-physical system; CWA: cognitive work analysis; DDoS: distributed denial of service; EAST: event analysis of systemic teamwork; FRAM; functional resonance analysis method; HCI: human-computer interaction; HERA: human error and recovery assessment; HET: human error template; HMC: human-machine cooperation; IoT: internet of things; RSTEM: radical systems thinking in ergonomics manifesto; SAI: situated artificial intelligence; STAMP: systems theoretic accident model and processes; TRACEr: technique for the retrospective and predictive analysis of cognitive errors in air traffic control.

Towards a complex systems approach in sports injury research: simulating running-related injury development with agent-based modelling.

OBJECTIVES: There have been recent calls for the application of the complex systems approach in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. Therefore, our objective was to use a computational modelling method and develop a dynamic simulation in sports injury research. METHODS: Agent-based modelling (ABM) was used to model the occurrence of sports injury in a synthetic athlete population. The ABM was developed based on sports injury causal frameworks and was applied in the context of distance running-related injury (RRI). Using the acute:chronic workload ratio (ACWR), we simulated the dynamic relationship between changes in weekly running distance and RRI through the manipulation of various 'athlete management tools'. RESULTS: The findings confirmed that building weekly running distances over time, even within the reported ACWR 'sweet spot', will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a 'hard ceiling' dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads. CONCLUSIONS: The presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM and other simulation-based techniques could be considered as a complementary and alternative methodological approach in sports injury research.

Time-to-event analysis for sports injury research part 1: time-varying exposures.

BACKGROUND: 'How much change in training load is too much before injury is sustained, among different athletes?' is a key question in sports medicine and sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous injury, biomechanics, sleep/stress) when studying sports injury aetiology. AIM: To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and injury-related outcomes. CONTENT: Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills. CONCLUSION: To increase knowledge about the association between changes in training load and injury, we encourage sports injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective sports injury data. This will ensure appropriate interpretation of time-to-event data.

Time-to-event analysis for sports injury research part 2: time-varying outcomes.

BACKGROUND: Time-to-event modelling is underutilised in sports injury research. Still, sports injury researchers have been encouraged to consider time-to-event analyses as a powerful alternative to other statistical methods. Therefore, it is important to shed light on statistical approaches suitable for analysing training load related key-questions within the sports injury domain. CONTENT: In the present article, we illuminate: (i) the possibilities of including time-varying outcomes in time-to-event analyses, (ii) how to deal with a situation where different types of sports injuries are included in the analyses (ie, competing risks), and (iii) how to deal with the situation where multiple subsequent injuries occur in the same athlete. CONCLUSION: Time-to-event analyses can handle time-varying outcomes, competing risk and multiple subsequent injuries. Although powerful, time-to-event has important requirements: researchers are encouraged to carefully consider prior to any data collection that five injuries per exposure state or transition is needed to avoid conducting statistical analyses on time-to-event data leading to biased results. This requirement becomes particularly difficult to accommodate when a stratified analysis is required as the number of variables increases exponentially for each additional strata included. In future sports injury research, we need stratified analyses if the target of our research is to respond to the question: 'how much change in training load is too much before injury is sustained, among athletes with different characteristics?' Responding to this question using multiple time-varying exposures (and outcomes) requires millions of injuries. This should not be a barrier for future research, but collaborations across borders to collecting the amount of data needed seems to be an important step forward.

Understanding complexity in a safety critical setting: A systems approach to medication administration.

'Medication errors' are a significant concern and are associated with a higher incidence of adverse events and unintentional patient harm than any other aspect of healthcare. While much research has focused on adverse medication errors, limited studies have specifically examined 'normal' medication delivery performance and the interactions between tasks, agents, and information within the medication administration system. This article describes a study that applied the Event Analysis of Systemic Teamwork (EAST) model to study the hospital medication administration system to identify opportunities to optimise performance and patient safety. Key findings of this study demonstrate that this is a highly complex system, comprising many social agents and a relatively closely linked series of tasks and information. However, most of the workload relies on a small proportion of healthcare professionals. Significantly, the patient has a minimal role in the medication administration system during their hospital stay. The research has shown that this approach enables mapping networks and their interdependencies to optimise the system as a whole rather than its parts in isolation.