Gemma Read

Technology-facilitated intimate partner violence (TFIPV) is increasingly featured in cases of intimate partner violence and intimate partner homicide. There is emerging recognition of the use of technology to abuse and control intimate partners in domestic abuse research and the inherent complexity of TFIPV is evident. As such, a better understanding of the factors that influence TFIPV is necessary. This scoping review aimed to synthesise extant literature on factors known to influence TFIPV. The review included 84 peer-reviewed primary sources that focused on adult intimate relationships (at least 18 years of age), had full-text versions in English, and included individual, situational, environmental, technological, and systemic factors found to increase the likelihood of TFIPV. The influencing factors were extracted and mapped onto a systems-thinking-based framework, Rasmussen's Risk Management Framework. This synthesis identified 28 higher-order themes across the TFIPV system hierarchy. Most of the factors within these themes related to lower levels of the system (e.g. perpetrators, victim-survivors, social environment, device and software capabilities), with limited consideration of broader systemic factors that influence TFIPV. Of the broader systemic factors that were identified, most related to inadequate responses to TFIPV by government, judicial system, technology industry regulators, and police. Future research should consider the use of systems-thinking-based frameworks and methods in understanding and addressing this complex and pervasive problem from a whole-of-system perspective.

Train driving is considered a high‐risk occupation for stress and work‐related mental health disorders. Sources of stress exposure during routine operations can impact a drivers' capacity for safe train operation. From a systems thinking perspective, safety is a responsibility shared by stakeholders across the rail transport system, with risk management relying upon those at the higher levels understanding the system state and the extent to which existing controls are achieving safe system functioning. In relation to driver stress, this requires that rail system stakeholders understand both the stressful events that train drivers are exposed to, and the impacts of this stress on driver performance. This research applied Rasmussen's Risk Management Framework to investigate and compare rail safety stakeholder perceptions on the impacts of acute stress on train driver performance. 119 rail stakeholders (drivers, guards, management, and regulators) were presented with three stressful event scenarios and asked to describe and rate impacts on driver performance. Qualitative analysis provided evidence of alignment of perceptions amongst drivers and other stakeholders, with themes indicating some agreement across rail system levels (e.g., across drivers, guards, supervisors, and management). Results revealed the most frequently reported stress impact related to cognition. Practical implications and future research directions to prevent and manage stressful event exposure are discussed.

Globally, identity theft incidents are increasing. When responding to identity theft incidents, various actors (i.e., individuals/organisations/agencies) interact within a complex response system. However, current literature has not addressed this complexity by using systems analysis methods to understand and potentially enhance the response to identity theft. The aim of this study was to use a systems analysis approach to identify vulnerabilities, flaws, and recommendations for improving the response system. To achieve this, two phases (Work Domain Analysis and Social Organisation and Cooperation Analysis) of the Cognitive Work Analysis framework were applied. The analysis demonstrates that the identity theft response system is complex and has a range of vulnerabilities and flaws, amongst these is the limited support for victim recovery. It is recommended that the system be re‐designed to focus more on restorative support for victims and to ensure that all aspects of victim outcomes are measured, rather than focusing solely on negative financial impacts.

Remotely Piloted Aircraft Systems (RPAS), also known as drones, are a rapidly emerging technology being quickly adopted in civil and military applications. Although there are many potential benefits, several safety challenges also exist. This requires a proactive approach to design the broader sociotechnical safety system required to support the safe and optimal use of this technology. This study provides a novel application of the Systems Theoretic Accident Model and Processes (STAMP) safety control structure model to develop a proposed control structure for safe and effective RPAS operations. Following subject expert review and validation, the proposed STAMP control structure served as the basis for evaluating the current RPAS safety system’s maturity and identifying gaps between the proposed and current structures. The findings revealed several gaps at all levels of the safety control structure model. Based on a review of these gaps, a series of required control actions and feedback mechanisms is presented. A national RPAS strategy was identified as a key control action mechanism that could support safe and effective RPAS operations. Overall, the study represents a novel application of STAMP to a rapidly emerging and disruptive technology; the implications for future applications in other contexts are discussed.

Suicide is a leading cause of premature mortality worldwide, making suicide prevention a global public health priority. As more Artificial Intelligence (AI)-based suicide prevention interventions are being developed and implemented, it is important to study acceptance of these AI systems. The present study aimed to investigate the factors that predict acceptance of current and future AI systems for suicide prevention and the perceived risks and benefits of these AI systems. Individuals from the Australian public were invited to participate in an online survey, which included six hypothetical scenarios of current AI systems (Artificial Narrow Intelligence [ANI]) and future advanced AI systems (Artificial General Intelligence [AGI]) for suicide prevention. Participants evaluated these scenarios on five technology acceptance factors (performance expectancy, effort expectancy, social influence, facilitating conditions, trust) and elaborated on its perceived risks and benefits. Performance expectancy, social influence, and trust predicted acceptance of ANI systems, but only trust predicted acceptance of AGI systems. Overall, the level of acceptance was higher for ANI systems than for AGI systems. Several perceived risks (e.g., risks to mental healthcare, distrust in AI, threats to humanity) and perceived benefits (e.g., benefits to mental healthcare, trust in AI, human help-seeking) were identified. AI systems represent potential avenues for effective suicide prevention. However, to ensure acceptance, AI systems for suicide prevention must be developed in a way that is safe, reliable, and trustworthy.

Teams play a critical role in society and represent a key area for Human Factors and Ergonomics. Salas et al.'s Big Five model is widely cited; however, the increasing use of Human-Autonomy Teams (HATs) has fuelled debate over its continued relevance. It is important to reflect on how the Big five model has been applied, in what contexts, and whether applications to contemporary teams are emerging. This article presents the findings from a scoping review undertaken to identify and synthesise the peer reviewed literature describing applications of the Big Five model. Articles were deemed eligible for inclusion if they were published in the peer reviewed literature and described an application of the Big Five model to study teamwork. 38 articles were included in the review and no applications of the Big Five model to study HATs were identified. Over half of the studies were undertaken in healthcare and a range of assessment methods have been used (e.g., questionnaires, surveys, interviews, observer-rating scales, communication transcript analysis). Just under a third of included studies evaluated all model components (i.e., the five processes and three coordinating mechanisms) and few considered the relationships between model components or between model components and team effectiveness. Research is required to explore the validity of the Big Five model for HATs, to gather evidence for the relationship between model components and team effectiveness, and to develop more precise Big five-based measures.Teams play a critical role in society and represent a key area for Human Factors and Ergonomics. Salas et al.'s Big Five model is widely cited; however, the increasing use of Human-Autonomy Teams (HATs) has fuelled debate over its continued relevance. It is important to reflect on how the Big five model has been applied, in what contexts, and whether applications to contemporary teams are emerging. This article presents the findings from a scoping review undertaken to identify and synthesise the peer reviewed literature describing applications of the Big Five model. Articles were deemed eligible for inclusion if they were published in the peer reviewed literature and described an application of the Big Five model to study teamwork. 38 articles were included in the review and no applications of the Big Five model to study HATs were identified. Over half of the studies were undertaken in healthcare and a range of assessment methods have been used (e.g., questionnaires, surveys, interviews, observer-rating scales, communication transcript analysis). Just under a third of included studies evaluated all model components (i.e., the five processes and three coordinating mechanisms) and few considered the relationships between model components or between model components and team effectiveness. Research is required to explore the validity of the Big Five model for HATs, to gather evidence for the relationship between model components and team effectiveness, and to develop more precise Big five-based measures.

Signal Passed at Danger (SPAD) incidents, though infrequent, remain a serious threat to rail safety. While often investigated as discrete operational events, SPADs are symptomatic of deeper system conditions. Investigations tend to follow linear logics of human error and focus corrective actions on individual behaviour—especially that of the train driver. However, such approaches may obscure rather than reveal meaningful system-wide learning. This meta-analysis used the AcciMap technique to analyse and aggregate findings from SPAD investigation reports (N = 49), offering a unique holistic perspective. A total of 859 contributory factors were identified (∼17 per SPAD), with most (∼62 %) reported to occur at the level of physical processes and actor activities. The largest aggregate contributory factor being attributed to SPADs was driver cognitive (dis)engagement (63 factors). Thematic aggregation revealed four themes: (1) A signal lost in the noise, relating to information overload in the rail environment and inevitable separation of human attention from signals; (2) Lost in translation, highlighting interchangeable and indistinct use of labels and concepts employed during investigation; (3) Lost in the brake down, reflecting a dominant narrative of driver (in)action and wrong-doing; and (4) Lost in the loop, pointing to surface-level corrective actions that repeated what was expected rather than redesign ineffective controls. Findings are discussed by reflecting on the question: “what might SPADs be trying to teach us?” By shifting the analytical lens from individual to system, this study challenges dominant narratives of driver blame and considers whether current investigations genuinely reflect systems thinking or merely perpetuate an illusion of learning.

Level crossings, where road and rail intersect, pose significant safety risks to train drivers, road users, pedestrians, and cyclists (Edquist et al., 2009; Read et al., 2021). From 2014 to 2022, 322 collisions at Australian level crossings resulted in 39 fatalities and 49 serious injuries (National Level Crossing Safety Committee, 2023; Read et al., 2021). Beyond the significant human and social costs, collisions at level crossings impose a considerable economic burden, with the annual financial cost estimated to exceed AUD $116 million in 2010 (Tooth & Balmford, 2010).
Human Factors issues play a critical role in level crossing collisions (Beanland et al., 2018; Salmon, Read, et al., 2013). Collisions can occur because road users misjudge the speed or distance of an approaching train, rely on past experience to anticipate train movements, or fail to perceive warnings or even trains due to low expectancy (Caird, 2002; Office of the National Rail Safety Regulator, 2024; Salmon, Lenné, et al., 2013; Salmon, 2013; Young, 2015). Studies show that both active crossings (e.g., boom gates, flashing lights) and passive crossings (e.g., stop signs, no warning systems) present risks, with user behaviour shaped by the physical and informational environment (Lenné et al., 2011; Read et al., 2021). Despite substantial research, Human Factors knowledge has not been systematically integrated into level crossing design and evaluation, particularly in rural and regional areas where passive controls dominate (Bearman, 2013).
Given the costs associated with installing traditional active controls, there is growing interest in innovative, low-cost safety solutions (Silla, 2019; Wullems, 2011). However, developers, engineers, and project managers often lack practical guidance on applying Human Factors principles during the design, implementation, and operation of these solutions. This gap can reduce the effectiveness of interventions. This project addresses the gap through the development of a publicly accessible, evidence-based toolkit to help embed Human Factors principles into the design, implementation, and operation of innovative level crossing safety solutions.

Young driver safety remains a road safety priority due to the over-representation of this cohort in crashes, fatalities and injuries. Speeding is recognised as a key contributor to traffic crashes, particularly within this population. Traffic safety culture is a growing area of research that considers the shared attitudes, values and beliefs of communities relating to road safety behaviours. However, the traffic safety culture of young drivers is under-researched and has not been conceptualised for speeding behaviour specifically. The current study applied an exploratory approach paired with systems thinking to discern the traffic safety culture of young drivers in Queensland, and in sub-groups of young drivers (general population females, general population males and car enthusiasts). Further, factors across the road transport system were investigated for their impact on traffic safety culture and speeding behaviour. A sample of 27 young drivers from Queensland participated in semi-structured interviews. Thematic analysis revealed key factors of a general traffic safety culture that exist across the young driver groups. Further, the findings showed that factors across the whole road transport system impact young drivers’ traffic safety culture to varying degrees. The findings provide insight into how the system could be adapted to encourage safer behaviour in young drivers. It is suggested that a holistic approach spanning the road transport system be applied to integrate strategies which promote a positive traffic safety culture around speeding within the young driver cohort.

Substantial evidence suggests that university students experience poor mental health. However, the majority of previous studies focus on undergraduate student populations and common mental disorders (e.g. depression and anxiety). Less is known about the mental health of PhD students, specifically, their experiences of suicidality. The present study aimed to explore the experiences of suicidality among PhD students in Australia. PhD students across Australian universities were invited to complete an online survey. A sample of 299 participants completed the suicidality measure administered (Suicide Behavior Questionnaire-Revised), and results indicate that approximately 37% of participants were at risk of suicide. A subsample of 79 participants (58% at risk of suicide) provided textual response to elaborate on their suicidality experiences, and qualitative content analysis indicated that there were experiences of suicidality that were unrelated to the PhD but also experiences of suicidality that were related to the PhD. Several risk factors for suicidality were mentioned by participants, including PhD pressures and stress, and anxiety about the future. Protective factors that were mentioned included the PhD providing a sense of purpose and the presence of social and psychological support. These results call for action in higher education systems, with the findings suggesting opportunities for universities to implement strategies that better safeguard the mental health of PhD students.