Using Systems Engineering and Implementation Science to Design an Implementation Package for Preoperative Comprehensive Geriatric Assessment Among Older Adults Having Major Abdominal Surgery: Protocol for a 3-Phase Study.

BACKGROUND: Older Americans, a growing segment of the population, have an increasing need for surgical services, and they experience a disproportionate burden of postoperative complications compared to their younger counterparts. A preoperative comprehensive geriatric assessment (pCGA) is recommended to reduce risk and improve surgical care delivery for this population, which has been identified as vulnerable. The pCGA optimizes multiple chronic conditions and factors commonly overlooked in routine preoperative planning, including physical function, polypharmacy, nutrition, cognition, mental health, and social and environmental support. The pCGA has been shown to decrease postoperative morbidity, mortality, and length of stay in a variety of surgical specialties. Although national guidelines recommend the use of the pCGA, a paucity of strategic guidance for implementation limits its uptake to a few academic medical centers. By applying implementation science and human factors engineering methods, this study will provide the necessary evidence to optimize the implementation of the pCGA in a variety of health care settings. OBJECTIVE: The purpose of this paper is to describe the study protocol to design an adaptable, user-centered pCGA implementation package for use among older adults before major abdominal surgery. METHODS: This protocol uses systems engineering methods to develop, tailor, and pilot-test a user-centered pCGA implementation package, which can be adapted to community-based hospitals in preparation for a multisite implementation trial. The protocol is based upon the National Institutes of Health Stage Model for Behavioral Intervention Development and aligns with the goal to develop behavioral interventions with an eye to real-world implementation. In phase 1, we will use observation and interviews to map the pCGA process and identify system-based barriers and facilitators to its use among older adults undergoing major abdominal surgery. In phase 2, we will apply user-centered design methods, engaging health care providers, patients, and caregivers to co-design a pCGA implementation package. This package will be applicable to a diverse population of older patients undergoing major abdominal surgery at a large academic hospital and an affiliate community site. In phase 3, we will pilot-test and refine the pCGA implementation package in preparation for a future randomized controlled implementation-effectiveness trial. We anticipate that this study will take approximately 60 months (April 2023-March 2028). RESULTS: This study protocol will generate (1) a detailed process map of the pCGA; (2) an adaptable, user-centered pCGA implementation package ready for feasibility testing in a pilot trial; and (3) preliminary pilot data on the implementation and effectiveness of the package. We anticipate that these data will serve as the basis for future multisite hybrid implementation-effectiveness clinical trials of the pCGA in older adults undergoing major abdominal surgery. CONCLUSIONS: The expected results of this study will contribute to improving perioperative care processes for older adults before major abdominal surgery. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59428.

Prepared for the polycrisis? The need for complexity science and systems thinking to address global and national evidence gaps.

The Sustainable Development Goals are far off track. The convergence of global threats such as climate change, conflict and the lasting effects of the COVID-19 pandemic-among others-call for better data and research evidence that can account for the complex interactions between these threats. In the time of polycrisis, global and national-level data and research evidence must address complexity. Viewed through the lens of 'systemic risk', there is a need for data and research evidence that is sufficiently representative of the multiple interdependencies of global threats. Instead, current global published literature seems to be dominated by correlational, descriptive studies that are unable to account for complex interactions. The literature is geographically limited and rarely from countries facing severe polycrisis threats. As a result, country guidance fails to treat these threats interdependently. Applied systems thinking can offer more diverse research methods that are able to generate complex evidence. This is achievable through more participatory processes that will assist stakeholders in defining system boundaries and behaviours. Additionally, applied systems thinking can draw on known methods for hypothesising, modelling, visualising and testing complex system properties over time. Application is much needed for generating evidence at the global level and within national-level policy processes and structures.

Building a Systems Map: Applying Systems Thinking to Unhealthy Commodity Industry Influence on Public Health Policy.

BACKGROUND: Unhealthy commodity industries (UCIs) engage in political practices to influence public health policy, which poses barriers to protecting and promoting public health. Such influence exhibits characteristics of a complex system. Systems thinking would therefore appear to be a useful lens through which to study this phenomenon, potentially deepening our understanding of how UCI influence are interconnected with one another through their underlying political, economic and social structures. As such this study developed a qualitative systems map to depict the complex pathways through which UCIs influence public health policy and how they are interconnected with underlying structures. METHODS: Online participatory systems mapping workshops were conducted between November 2021 and February 2022. As a starting point for the workshops, a preliminary systems map was developed based on recent research. Twenty-three online workshops were conducted with 52 geographically diverse stakeholders representing academia, civil society (CS), public office, and global governance organisations (CGO). Analysis of workshop data in NVivo and feedback from participants resulted in a final systems map. RESULTS: The preliminary systems map consisted of 40 elements across six interdependent themes. The final systems map consisted of 64 elements across five interdependent themes, representing key pathways through which UCIs impact health policy-making: (1) direct access to public sector decision-makers; (2) creation of confusion and doubt about policy decisions; (3) corporate prioritisation of commercial profits and growth; (4) industry leveraging the legal and dispute settlement processes; and (5) industry leveraging policy-making, norms, rules, and processes. CONCLUSION: UCI influence on public health policy is highly complex, involves interlinked practices, and is not reducible to a single point within the system. Instead, pathways to UCI influence emerge from the complex interactions between disparate national and global political, economic and social structures. These pathways provide numerous avenues for UCIs to influence public health policy, which poses challenges to formulating a singular intervention or limited set of interventions capable of effectively countering such influence. Using participatory methods, we made transparent the interconnections that could help identify interventions in future work.

Complex Interventions for a Complex System? Using Systems Thinking to Explore Ways to Address Unhealthy Commodity Industry Influence on Public Health Policy.

BACKGROUND: Interventions are needed to prevent and mitigate unhealthy commodity industry (UCI) influence on public health policy. Whilst literature on interventions is emerging, current conceptualisations remain incomplete as they lack considerations of the wider systemic complexities surrounding UCI influence, which may limit intervention effectiveness. This study applies systems thinking as a theoretical lens to help identify and explore how possible interventions relate to one another in the systems in which they are embedded. Related challenges to addressing UCI influence on policy, and actions to support interventions, were also explored. METHODS: Online participatory workshops were conducted with stakeholders with expertise in UCIs. A systems map, depicting five pathways to UCI influence, and the Action Scales Model were used to help participants identify interventions and guide discussions. Codebook thematic analysis was used to analyse the data. RESULTS: Fifty-two stakeholders participated in 23 workshops. Participants identified 27 diverse, interconnected and interdependent interventions corresponding to the systems map's pathways that reduce the ability of UCIs to influence policy. These include, for example, reform policy financing; regulate public-private partnerships (PPPs); reform science governance and funding; frame and reframe the narrative, challenge neoliberalism and gross domestic product (GDP) growth; leverage human rights; change practices on multistakeholder governance; and reform policy consultation and deliberation processes. Participants also identified four potential key challenges to interventions (ie, difficult to implement or achieve; partially formulated; exploited or misused; requires tailoring for context), and four key actions to help support intervention delivery (ie, coordinate and cooperate with stakeholders; invest in civil society; create a social movement; nurture leadership). CONCLUSION: A systems thinking lens revealed the theoretical interdependence between disparate and heterogenous interventions. This suggests that to be effective, interventions need to align, work collectively, and be applied synchronously to different parts of the system, including multiple levels of governance. Importantly, these interventions need to be supported by intermediary actions to be achieved. Urgent action is now required to strengthen healthy alliances and implement interventions.

Exploring the complexity of the implementation determinants of human papillomavirus vaccination in Africa through a systems thinking lens: A rapid review.

A rapid review was conducted to explore the implementation determinants of human papillomavirus (HPV) vaccination in the World Health Organization African Region and describe their dynamic relationship. PubMed and Google Scholar were searched in October 2023 to find relevant literature. A total of 64 published studies that reported factors affecting HPV vaccination were identified. Analysis of identified factors yielded 74 implementation determinants of HPV vaccination across the five domains of the Consolidated Framework for Implementation Research (CFIR): two (2.70%) were in the innovation domain, seven (9.46%) were in the outer setting domain, 14 (18.92%) were in the inner setting domain, 37 (50%) were in the individual domain and 14 (18.92%) were in the implementation process domain. A causal loop diagram of these implementation determinants revealed four balancing and seven reinforcing loops. Applying systems lens promoted a more holistic understanding of the implementation determinants of HPV vaccination, exposing leverage points for interventions.

Systems thinking for local food environments: a participatory approach identifying leverage points and actions for healthy and sustainable transformations.

BACKGROUND: Current local food environments encourage poor diets, posing a significant threat to public and planetary health. Acknowledging and addressing its inherent complexity is vital to making meaningful improvements to the food environment. Using a participatory approach with local stakeholders, this study aims to gain insight into the factors and mechanisms underlying the local food environment and to identify leverage points and system-based actions to foster healthy and sustainable local food environments. METHODS: A systems-thinking approach was used in a Dutch municipality in 2022. Two group model building (GMB) workshops were held with community stakeholders (e.g. local policymakers, retailers and residents). During the first workshop (June 2022), factors and mechanisms influencing the local food environment were identified and visualized through a causal loop diagram (CLD). During the second workshop, leverage points and system-based actions to improve food environments were identified by the stakeholders. Four months after (October 2022), an action-implementation meeting was organized to stimulate the implementation of selected actions. Progress was monitored through brief telephone interviews 6 and 12 months after the second workshop. RESULTS: The CLD visualises the factors and mechanisms influencing the local food environment from the point of view of the community stakeholders. The CLD consists of 46 factors shaping the local food environment, which were categorized into four identified subsystems: societal factors, individual, socio-economic factors, commercial factors and political factors. Eight leverage points were identified within the CLD, for example, 'lobby from food industry', 'governmental food policies' and 'e-commerce and platform economy'. Stakeholders formulated 20 actions targeting the identified leverage points. During the action-implementation meeting, long-term plans were created for five actions. After 1 year, only one participant (policy advisory role) remained actively engaged in three of these actions. CONCLUSIONS: This study yields insight into the numerous factors and mechanisms underlying the local food environment and identified system-based actions as perceived by local stakeholders to improve this food environment locally. The CLD offers stakeholders valuable insights on employing a systems approach when enhancing food environments. More research is necessary, especially into the long-term processes and effects of implementing system-oriented actions to improve local food environments.

Systems thinking in, and for, public health: a call for a broader path.

Systems thinking has been recognized as valuable to public health policy, research and practice. Commentators and reviews have highlighted that there is still much to be done to embrace its potential. Here, we highlight that much of the discourse about systems thinking in, and for, public health supports the pursuit of a narrow path and is limited with respect to the lineages of Systems that are embraced. We invite readers to see the potential of systems thinking in pursuing a broader path which is motivated by a concern for alleviating health inequalities. This does not replace the narrow path but encompasses it. It prompts different considerations with respect to the nature of the transformation, partnership working and legitimacy. It also invites a different way of engaging with systems thinking and different ways of conceptualizing and managing change. The broad path both requires, and helps enhance, new ways of doing, relating, organizing, knowing and framing which are vital for the future of public health as a global concern.

Citizens' perspectives on healthy weight approaches in low SEP neighborhoods: a qualitative study from a systems perspective.

BACKGROUND: The physical and the social environment are important predictors of healthy weight, especially in low socioeconomic position (SEP) neighborhoods. Many Dutch municipalities have implemented a healthy weight approach (HWA). Yet, there is room for improvement. This system science study examined what influences the utilization of HWA facilities and activities, and what aspects can help to achieve a desired systems change (also called leverage point themes (LPTs)) in the HWA system as perceived by citizens living in low SEP neighborhoods. METHOD: All research phases were performed with four citizens co-researchers. Forty-seven citizens living in low SEP neighborhoods were semi-structurally interviewed about the neighborhood HWA facilities and municipal HWA activities. A rapid coding qualitative analysis approach was applied per topic. The topics were citizens' healthy living description, personal circumstances, and satisfaction with foot and cycle paths, sports facilities, playgrounds, green spaces, museums and theaters, community centers, churches, healthcare, school, food supplies, contact with neighborhood, unfamiliar and/or unused activities, familiar and used activities, unavailable but desired (lacking) activities, and reaching citizens. RESULTS: The utilization of HWA facilities and activities was influenced by the overarching themes of social cohesion, familiarity, reaching citizens, maintenance, safety, physical accessibility, financial accessibility, social accessibility, fit with personal context, and fit with the neighborhood's specific needs. Different overarching themes stood out across different facilities and activities. LPTs indicated the overarching themes needed in combination with one another for a specific activity or facility to increase utilization. For example, the LPT regarding foot and cycle paths was "accessible, safe, and maintained foot and cycle paths". The LPTs regarding familiar and used activities were "customized activities; information provision (e.g., about possibilities to join without paying); social contact, meeting others, and everyone feels included". CONCLUSION: Conducting inclusive qualitative research from a systems perspective among citizens living in low SEP neighborhoods has contributed valuable insights into their needs. This enables practical implementation of HWAs by providing a deeper understanding of the LPTs within the HWA system. LPTs can help HWA stakeholders to further develop current HWAs toward systems approaches. Future research could study the leverage points that may contribute to LPT implementation.

A novel framework for crash frequency prediction: Geographic support vector regression based on agent-based activity models in Greater Melbourne.

The field of spatial analysis in traffic crash studies can often enhance predictive performance by addressing the inherent spatial dependence and heterogeneity in crash data. This research introduces the Geographical Support Vector Regression (GSVR) framework, which incorporates generated distance matrices, to assess spatial variations and evaluate the influence of a wide range of factors, including traffic, infrastructure, socio-demographic, travel demand, and land use, on the incidence of total and fatal-or-serious injury (FSI) crashes across Greater Melbourne's zones. Utilizing data from the Melbourne Activity-Based Model (MABM), the study examines 50 indicators related to peak hour traffic and various commuting modes, offering a detailed analysis of the multifaceted factors affecting road safety. The study shows that active transportation modes such as walking and cycling emerge as significant indicators, reflecting a disparity in safety that heightens the vulnerability of these road users. In contrast, car commuting, while a consistent factor in crash risks, has a comparatively lower impact, pointing to an inherent imbalance in the road environment. This could be interpreted as an unequal distribution of risk and safety measures among different types of road users, where the infrastructure and policies may not adequately address the needs and vulnerabilities of pedestrians and cyclists compared to those of car drivers. Public transportation generally offers safer travel, yet associated risks near train stations and tram stops in city center areas cannot be overlooked. Tram stops profoundly affect total crashes in these areas, while intersection counts more significantly impact FSI crashes in the broader metropolitan area. The study also uncovers the contrasting roles of land use mix in influencing FSI versus total crashes. The proposed framework presents an approach for dynamically extracting distance matrices of varying sizes tailored to the specific dataset, providing a fresh method to incorporate spatial impacts into the development of machine learning models. Additionally, the framework extends a feature selection technique to enhance machine learning models that typically lack comprehensive feature selection capabilities.

A systems thinking framework for understanding rising childhood obesity in the Caribbean.

OBJECTIVE: The aim of this study is to develop a systems thinking framework to describe the common complexities of childhood obesity in the Caribbean region and identify potential areas of intervention. METHODS: Group model building (GMB) is a form of systems science. Trained GMB facilitators in Puerto Rico, the US Virgin Islands, Barbados, and Trinidad and Tobago convened a group of multi-disciplinary stakeholders in a series of virtual meetings in 2021 to elaborate a hypothesis of the system driving childhood obesity represented by causal loop diagrams (CLD). Commonalities and differences between the CLDs from each island were identified and reconciled to create a synthesized CLD. RESULTS: A single explanatory CLD across the islands was developed and includes nine reinforcing loops. These loops addressed the interconnected role of schools, policy, commercial determinants, community and the personal experience of the child in rising childhood obesity rates. CONCLUSIONS: Despite differences across settings, there is a core system driving childhood obesity in the Caribbean, as described by stakeholders in GMB workshops. Policy solutions to the problem must be multi-faceted and multi-level to address the interlinked reinforcing loops of the complex system and reduce rates of childhood obesity.

Combating COVID-19 health disparities in Black, Indigenous, and People of Colour Communities-A call for critical systems thinking.

RATIONALE: The Black, Indigenous, and People of Colour populations in the United States are disproportionately affected by the emerging health threat SARS-CoV-2, which causes COVID-19. AIMS AND OBJECTIVES: This paper aims to demonstrate the usefulness of critical systems thinking by using scenario planning based on epidemiological data and tying epidemiology with soft systems methodology to investigate COVID-19 disparities among disproportionately affected Black, Indigenous, and People of Colour populations. METHODS: Using a review of the COVID-19 literature and publicly available US COVID-19 data, critical systems thinking is applied in a scenario planning example and a call to link soft systems methodology with epidemiology. RESULTS: According to the four plausible Endgame scenarios, levels of community transmission as well as the current state transmission are based on the driving forces of the scenarios. In addition, soft systems methodology explores the effect on stakeholders and strengthens the picture of disease burden beyond sole reliance on traditional data sources. CONCLUSION: This analysis underscores employing critical systems thinking to critically assess diverse methods appropriate for the ongoing complexity of global crises. It is argued that critically engaged subjectivity should be given space alongside data-dependent objectivity. COVID-19 disparities are reliant on the social determinants of health's effects as driving forces on disease transmission in Black, Indigenous, and People of Colour populations. It is moreover argued that critical systems thinking is demonstrated by linking epidemiological evidence with scenario planning and soft systems methodology. This in turn supports a critical systems thinking approach to uncover the state of health disparities among minoritized communities under COVID-19.

Interconnectedness of Health and Economy in Post-COVID-19: A Systems Thinking Approach to Synergies, Trade-Offs, and Policy Responses in Nepal.

BACKGROUND: This study addresses the economic challenges posed by the Coronavirus Disease 2019 (COVID-19) pandemic, with a specific focus on Nepal. Employing a Systems Thinking approach, the study develops a comprehensive model that integrates macroeconomic interventions, exploring the trade-offs and synergies among various economic sectors. The interconnectedness of health, economic, and policy domains highlights the need for a holistic understanding of the pandemic's effects. METHODS: An exploratory research design was used. The model introduces three primary subsystems-import, local demand, and local production-illustrating their interdependence. The causal loop diagram depicts the implications of fiscal and monetary policies on the economy, emphasizing the synergy and trade-offs resulting from policy interventions. RESULTS: Findings reveal the significant economic impact of the pandemic on Nepal, leading to its negative growth rate in FY 2020/21, the first time Nepal has experienced this in the last two decades. The results show that both intended and unintended consequences are observed following the adoption of fiscal and monetary policy that aimed at minimizing the spread of virus suggesting a complex nature of relationship among the policy variables. The fiscal policy induced negative consequences on the increasing loan, slow revenue growth, while positive feedbacks are observed on increased investment opportunities, and boosting of local economy. The monetary measures yielded unintended consequences on the rising land prices, surge in share market. CONCLUSIONS: The study concludes by emphasizing the crucial role of informed policymaking in navigating the complex landscape, offering insights for creating a resilient and sustainable post-pandemic future.

Healthcare quality improvement: It's time to update the Donabedian approach with a complex systems perspective.

There is broad consensus that healthcare systems are complex systems, which as a result, face complex problems. From this perspective, quality of care can be conceptualised as an emergent outcome of the healthcare system, that is more than the sum of individual components of care (in terms of inputs and processes), and quality improvement as a complex systems problem. However, traditional approaches, such as Donabedian's structure/process/outcome framework, are rooted in a linear, reductionist perspective, that fails to recognise that quality of care is created in the context of complex healthcare systems, and the many interactions and uncertainties at play that shape quality of care and health outcomes. A paradigm shift is needed from a reductionist to a systems thinking approach if we are to better understand and improve quality of care. Such a shift begins with asking different research questions, situated within the system context, that focus on identifying how interventions may contribute to system improvement, as opposed to seeking to directly link interventions with quality of care outcomes. In contrast to traditional healthcare quality measures focusing on single components of the system in isolation, research needs to explicitly consider quality of care as an emergent system outcome and identify new indicators and methods of assessment that provide insight into how the healthcare system functions as an interconnected whole. It is an opportune moment to harness the energy of the international healthcare quality movement to drive the innovation needed in research and practice to adopt a systems thinking approach.

Role of heterogeneity: National scale data-driven agent-based modeling for the US COVID-19 Scenario Modeling Hub.

UVA-EpiHiper is a national scale agent-based model to support the US COVID-19 Scenario Modeling Hub (SMH). UVA-EpiHiper uses a detailed representation of the underlying social contact network along with data measured during the course of the pandemic to initialize and calibrate the model. In this paper, we study the role of heterogeneity on model complexity and resulting epidemic dynamics using UVA-EpiHiper. We discuss various sources of heterogeneity that we encounter in the use of UVA-EpiHiper to support modeling and analysis of epidemic dynamics under various scenarios. We also discuss how this affects model complexity and computational complexity of the corresponding simulations. Using round 13 of the SMH as an example, we discuss how UVA-EpiHiper was initialized and calibrated. We then discuss how the detailed output produced by UVA-EpiHiper can be analyzed to obtain interesting insights. We find that despite the complexity in the model, the software, and the computation incurred to an agent-based model in scenario modeling, it is capable of capturing various heterogeneities of real-world systems, especially those in networks and behaviors, and enables analyzing heterogeneities in epidemiological outcomes between different demographic, geographic, and social cohorts. In applying UVA-EpiHiper to round 13 scenario modeling, we find that disease outcomes are different between and within states, and between demographic groups, which can be attributed to heterogeneities in population demographics, network structures, and initial immunity.

Analysis of Iranian health workforce emigration based on a system dynamics approach: a study protocol.

BACKGROUND: Emigration of health workers has emerged as a significant obstacle in Iran, compelling policymakers to implement a diverse range of interventions and reforms to enhance healthcare services. It is imperative to comprehend the efficacy of emigration control interventions. To explore the intricate dynamics of elite emigration, this study employs a system dynamics modeling approach. The objective is to scrutinize Iranian health workers' emigration, examine the relationships, and evaluate the impact of various factors involved. OBJECTIVES: The general purpose of this study is to analyze the policy interventions affecting the emigration of human resources in the field of health in Iran based on the system's dynamic approach. METHOD: The research consists of four phases including analyzing the emigration status of health workers in developing countries, studying health personnel emigration in Iran, developing a System Dynamics (SD) model, and determining evidence-based policy interventions to address health worker emigration. These phases involve realist review, document analysis, qualitative interviews, data integration, and policy scenario planning. The primary objective is to gain a profound understanding of the underlying causes, mechanisms, and consequences of migration, as well as assess the impact of policies, in order to prioritize effective interventions. RESULTS: It seems that the SD model developed in this study can highlight the interconnectedness of various factors that influence health worker emigration, including demographic changes, economic conditions, and characteristics of healthcare systems. CONCLUSION: This study uses a systems dynamics approach to analyze health worker emigration from Iran, focusing on policies that promote retention and explore the implications of emigration on the healthcare system. By examining interrelationships and feedback loops within the healthcare system and socioeconomic factors, the study aims to identify effective policy interventions that can mitigate the negative effects of emigration.

Main findings: The study reveals a complex web of factors driving the emigration of Iranian health workers, and along with the Investigating the effectiveness of different interventions, the aim of this research is to develop sustainable solutions to deal with the emigration of health workers.Added knowledge: This research adds to the existing literature by employing a system dynamics approach to model the multifaceted nature of health workforce emigration in Iran, offering a novel perspective on policy intervention analysis.Global health impact for policy and action: The findings underscore the necessity for comprehensive policy strategies that address the root causes of health worker emigration and can inform global efforts to retain healthcare professionals and ensure sustainable healthcare systems.

A systems-based analysis to rethink the European environmental risk assessment of regulated chemicals using pesticides as a pilot case.

A growing body of scientific literature stresses the need to advance current environmental risk assessment (ERA) methodologies and associated regulatory frameworks to better address the landscape-scale and long-term impact of pesticide use on biodiversity and the ecosystem. Moreover, more collaborative and integrative approaches are needed to meet sustainability goals. The One Health approach is increasingly applied by the European Food Safety Authority (EFSA) to support the transition towards safer, healthier and more sustainable food. To this end, EFSA commissioned the development of a roadmap for action to establish a European Partnership for next-generation, systems-based Environmental Risk Assessment (PERA). Here, we summarise the main conclusions and recommendations reported in the 2022 PERA Roadmap. This roadmap highlights that fragmentation of data, knowledge and expertise across regulatory sectors results in suboptimal processes and hinders the implementation of integrative ERA approaches needed to better protect the environment. To advance ERA, we revisited the underlying assumptions of the current ERA paradigm; that chemical risks are generally assessed and managed in isolation with a substance-by-substance, realistic worst-case and tiered approach. We suggest optimising the use of the vast amount of information and expertise available with pesticides as a pilot area. It is recommended to as soon as possible adopt a systems-based approach, i.e. within the current regulatory framework, to spark a step-wise transition towards an ERA framed at a system level of ecological and societal relevance. Tangible systems-based and integrative steps are available. For instance, the rich sources of existing data for prospective and retrospective ERA of pesticides could be used to reality-benchmark existing and new ERA methods. To achieve these goals, collaboration among stakeholders across scientific disciplines and regulatory sectors must be strengthened.

Over a decade of UAV incidents: A human factors analysis of causal factors.

This analysis examined systemic causes of Uncrewed Air Vehicle (UAV) accidents identifying operator, environmental, supervisory, and organisational factors through the use of the Human Factors Analysis and Classification System (HFACS). HFACS is a system-based analysis method for investigating the causal factors associated with accidents and incidents and has previously been used to reliably and systematically identify active and latent failures associated with both military and general aviation accidents. Whilst HFACS has previously been applied to UAV accidents, the last known application was conducted in 2014. Using reports retrieved from nine accident investigation organisations' databases, causal factors were coded against unsafe acts, preconditions, and failures at the supervisory, organisational, and environmental levels. Causal factors were assessed on 77 medium or large UAV mishaps/accidents that occurred over a 12-year period up to 2024. 42 mishap reports were deemed to involve a human factor as a causal factor. A large proportion of the mishaps contained factors attributed to Decision Errors at level 1 (Unsafe Acts) which was found to be associated with both the Technological Environment and Adverse Mental State at level 2 (Pre-conditions). Causal factors were identified at each of the other 3 levels (Supervisory, Organisational and External) with a number of emergent associations between causal factors. These data provide support for the identification and development of interventions aimed at improving the safety of organisations and advice of regulators for Uncrewed Air Systems.

A Systems Map of the Challenges of Climate Communication.

Over the past sixty years, scientists have been warning about climate change and its impacts on human health, but evidence suggests that many may not be heeding these concerns. This raises the question of whether new communication approaches are needed to overcome the unique challenges of communicating what people can do to slow or reverse climate change. To better elucidate the challenges of communicating about the links between human activity, climate change and its effects, and identify potential solutions, we developed a systems map of the factors and processes involved based on systems mapping sessions with climate change and communication experts. The systems map revealed 27 communication challenges such as "Limited information on how individual actions contribute to collective human activity," "Limited information on how present activity leads to long-term effects," and "Difficult to represent and communicate complex relationships." The systems map also revealed several themes among the identified challenges that exist in communicating about climate change, including a lack of available data and integrated databases, climate change disciplines working in silos, a need for a lexicon that is easily understood by the public, and the need for new communication strategies to describe processes that take time to manifest.