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Background/Purpose: Midwife-led continuity of care (MLCC) is an evidence-based care model positively influencing the health and wellbeing of women and their families. Despite the evidence, a sustainable future of the model is uncertain. The aim of this paper is to give an example of a theoretical exercise that enhances the understanding of the trends and developments impacting MLCC's future state. Methods: The industrial complex theory scaffolded the theoretical approach. The intuitive logics scenario development methodology was used to structure the key variables that influence the utility of MLCC. Dimensionally structured scenarios representing the probable, possible and probable MLCC futures were written. Results: Thirteen key variables that greatly impact the future MLCC, with varying degrees of certainty were identified. A theoretical framework representing two underlying meta dimensions of MLCC was constructed: identity system of midwife-led continuity of care (fixed vs fluid) and embodied orientation to the world (reasoning vs meaning making). Within the framework, four different storylines of possible, plausible prospective futures emerged: Sense & sensibility, The birth of mothers, Too many sisters and One-stop-shop. Conclusion: The paper is an example of how to approach the future of MLCC, the method serving as a tool to establish a theoretical truth of how its future state may unfold, the scenarios facilitating a dialogue among stakeholders and informing the public.

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Settlement expansion and commercial agriculture affect landscape sustainability and ecosystem service provision. Integrated landscape approaches are promoted to negotiate trade-offs between competing land uses and their reconciliation. Incorporating local perceptions of landscape dynamics as basis for such negotiations is particularly relevant for sub-Saharan Africa, where most people depend on natural ecosystems for livelihoods and well-being. This study applied participatory scenario building and spatially explicit simulation to unravel perceptions of the potential impact of rubber and settlement expansion on the provision of selected ecosystem services in southwestern Ghana under a business-as-usual scenario. We collected data in workshops and expert surveys on locally relevant ecosystem services, their indicator values, and the probable land-use transitions. The data was translated into an assessment matrix and integrated into a spatially explicit modeling platform, allowing visualization and comparison of the impact on ecosystem service provision of land-use scenarios under rubber plantation and settlement expansion. The results show the capacity of current (2020) and future land-use patterns to provide locally relevant ecosystem services, indicating a decline in capacity of ecosystem service provisioning in the future compared to the 2020 land-use patterns, a threat to the benefits humans derive from ecosystems. This highlights urgent need for policies and measures to control the drivers of land-use/land-cover change. Furthermore, the results emphasize the importance of diversifying land-use/land-cover types for sustainable landscape development. The paper contributes new insights into how spatially explicit and semi-quantitative methods can make stakeholder perceptions of landscape dynamics explicit as a basis for implementing integrated landscape approaches.

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Radiation and radioactive substances result in the production of radioactive wastes which require safe management and disposal to avoid risks to human health and the environment. To ensure permanent safe disposal, the performance of a deep geological repository for radioactive waste is assessed against internationally agreed risk-based standards. Assessing postclosure safety of the future system's evolution includes screening of features, events, and processes (FEPs) relevant to the situation, their subsequent development into scenarios, and finally the development and execution of safety assessment (SA) models. Global FEP catalogs describe important natural and man-made repository system features and identify events and processes that may affect these features into the future. By combining FEPs, many of which are uncertain, different possible future system evolution scenarios are derived. Repository licensing should consider both the reference or "base" evolution as well as alternative futures that may lead to radiation release, pollution, or exposures. Scenarios are used to derive and consider both base and alternative evolutions, often through production of scenario-specific SA models and the recombination of their results into an assessment of the risk of harm. While the FEP-based scenario development process outlined here has evolved somewhat since its development in the 1980s, the fundamental ideas remain unchanged. A spectrum of common approaches is given here (e.g., bottom-up vs. top-down scenario development, probabilistic vs. bounding handling of uncertainty), related to how individual numerical models for possible futures are converted into a determination as to whether the system is safe (i.e., how aleatoric uncertainty and scenarios are integrated through bounding or Monte Carlo approaches).

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Diverse agricultural land uses are a typical feature of multifunctional landscapes. The uncertain change in the drivers of global land use, such as climate, market and policy technology and demography, challenges the long-term management of agricultural diversification. As these global drivers also affect smaller scales, it is important to capture the traits of regionally specific farm activities to facilitate adaptation to change. By downscaling European shared socioeconomic pathways (SSPs) for agricultural and food systems, combined with representative concentration pathways (RCP) to regionally specific, alternative socioeconomic and climate scenarios, the present study explores the major impacts of the drivers of global land use on regional agriculture by simulating farm-level decisions and identifies the socio-ecological implications for promoting diverse agricultural landscapes in 2050. A hilly orchard region in northern Switzerland was chosen as a case study to represent the multifunctional nature of Swiss agriculture. Results show that the different regionalised pathways lead to contrasting impacts on orchard meadows, production levels and biodiversity. Increased financial support for ecological measures, adequate farm labour supplies for more labour-intensive farming and consumer preferences that favour local farm produce can offset the negative impacts of climate change and commodity prices and contribute to agricultural diversification and farmland biodiversity. However, these conditions also caused a significant decline in farm production levels. This study suggests that considering a broader set of land use drivers beyond direct payments, while acknowledging potential trade-offs and diverse impacts across different farm types, is required to effectively manage and sustain diversified agricultural landscapes in the long run. Supplementary information: The online version contains supplementary material available at 10.1007/s10113-023-02092-5.

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This study presents a novel approach to enhance expert panel discussions in a medical conference through the use of ChatGPT-4 (Generative Pre-trained Transformer version 4), a recently launched powerful artificial intelligence (AI) language model. We report on ChatGPT-4's ability to optimize and summarize the medical conference panel recommendations of the first Pan-Arab Pediatric Palliative Critical Care Hybrid Conference, held in Riyadh, Saudi Arabia. ChatGPT-4 was incorporated into the discussions in two sequential phases: first, scenarios were optimized by the AI model to stimulate in-depth conversations; second, the model identified, summarized, and contrasted key themes from the panel and audience discussions. The results suggest that ChatGPT-4 effectively facilitated complex do-not-resuscitate (DNR) conflict resolution by summarizing key themes such as effective communication, collaboration, patient and family-centered care, trust, and ethical considerations. The inclusion of ChatGPT-4 in pediatric palliative care panel discussions demonstrated potential benefits for enhancing critical thinking among medical professionals. Further research is warranted to validate and broaden these insights across various settings and cultures.

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The complexity of waste management (WM) problems resulted in the explosion of scenarios that challenge focused discussion among stakeholders and hinder the integrity of policy responses in developing countries. Hence, drawing similarities is essential to reduce the number of scenarios to simplify the WM efforts. To extract similarities, measuring WM performance is not enough, but the background factors related to this performance should be incorporated. These factors form a unique system characteristic that facilitates or hinders WM functions. Thus, this study applied multivariate statistical analysis to clarify underlying characteristics that facilitate efficient WM scenario developments for developing countries. The study first analysed drivers associated with improved WM system performance using bivariate correlation analysis. As a result, twelve significant drivers associated with controlled solid waste were identified. Then, it mapped the countries based on their WM system characteristics using the combined principal component analysis and hierarchical clustering approach. Thirteen variables were examined to extract similarities between the countries. The results identified three homogenous clusters. The clusters were found considerably parallel to the global classifications based on income and human development index. Hence, the presented approach is efficient in explaining similarities that reduce WM scenarios and favours cooperation among countries.

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This study defines futures myocardial infarction landscapes and proposes a few policy options to reduce the burden of cardiovascular diseases using the scenario development method. We identified the effective drivers of myocardial infarction by reviewing the literature and completed the returned list with "experts" opinions. The results were classified using the STEEP (Social, Technological, Environmental, Economic, and Political) framework. We plotted the critical uncertainties in a two-dimensional ranking of "effect" and "uncertainty" levels. Eleven drivers with uncertainty and high potential impact were selected and categorized into three groups: Political Development, Access to health services, and Self-Care. Scenarios were developed, and 3 scenarios (optimistic, pessimistic, and possible) were selected based on scoring. For each scenario, policy options were formulated. Utilizing the capacity of Non-Governmental Organizations and charities and strengthening restrictive and punitive legislation was chosen as policy options for addressing possible scenarios. Building infrastructure and improving prevention services, designing and regenerating curative infrastructure were selected as optimal strategies for addressing issues related to the optimistic scenario. Strengthening restrictive and punitive legislation related to community health and population empowerment were proposed as critical policy options for health improvement regarding the pessimistic scenario. Increasing people's participation, strengthening infrastructure and punitive policies can be effective in Myocardial infarction mortality prevention policies in Iran.

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Rainwater harvesting (RWH) has proven to be an efficient method of curtailing water scarcity by substituting it as an alternative water supply which also helps to mitigate the risk of flooding caused due to heavy rainfall. While overcoming the water-related issues, implementation and identifying potential harvesting sites in urban areas on a large scale has always been challenging, necessitating additional research and constraint considerations. The proposed study implements a basin-wide approach and creates a tool using the geographical information system (GIS) to pinpoint site locations to collect rainstorm water. For determining the feasible number of RWH sites, the scenarios were created by considering the minimum basin area. In addition, the volumetric potential of the identified RWH sites was evaluated using the SCS-CN (Soil Conservation Services Curve Number) method by estimating rainfall runoff volume. The proposed methodology is implemented as a case study on the extended area of Jaipur in India, and the analysis shows that all identified locations lie on the outskirts of the study area, ensuring land availability for developing rainwater harvesting structures. As an outcome, the proposed methodology helps to establish the relationship between the basin area, the number of identified RWH sites, and their volumetric potential, creating a benchmark for further conducting similar studies on other areas.

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This paper develops three scenarios for the aviation industry's recovery from COVID-19 until 2030 by utilizing the scenario methodology. Besides the short- and mid-term pandemic development, the study takes into account the industry's adaptation to changes in the market environment, e.g., toward sustainability and hygiene requirements. The resulting scenarios include the expected point in time of full air traffic recovery to pre-crisis levels. Subsequent implications suggest that most COVID-19-related hygiene measures along the travel chain disappear after the pandemic is contained. Some measures might serve as a differentiator between airline business models, while others are expected to become a new standard. Implications for environmental awareness and resulting operational and technical measures include changes in society's attitude toward traveling post-pandemic, especially in light of varying levels of environmental awareness. The presented scenarios help to identify the range of plausible development paths, thus building the basis for future model-based research.

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Fuzzy Cognitive Mapping (FCM) is a participatory modelling tool used to explore complex systems by facilitating interdisciplinary cooperation and integrating a variety of knowledge systems. Here FCM was used to explore marine microfiber pollution. Through individual interviews with representatives from the research, industry, water and environmental sectors, five stakeholder FCMs were developed and used to produce an aggregated community FCM in a stakeholder workshop. Stakeholder FCMs and the revised community FCM were used to compute how the modelled system reacted to changes under two scenarios developed during the stakeholder workshop; (i) Green Shift and (ii) increased textile consumption and production. Significant differences were observed in scenario results from the stakeholder-based models and the community-based model. For societal challenges characterized by unknowns around the problem and potential solutions, inclusion of a variety of knowledge systems through FCM and deliberation processes contribute to a more holistic picture of the system and its uncertainties.

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BACKGROUND: The financing function within a health system is considered inherently complex, so it is of utmost importance to design a suitable future for this system given uncertainties and complexities of the environment. With regard to the current and future complicated conditions, health system financing is also likely to succeed if it can anticipate the impacts of effective factors in the future and further plan appropriate interventions ahead of time. Thus, the purpose of this study was to develop scenarios for the health system financing in Iran. METHODS: This mixed-design research of exploratory future studies type was conducted using the scenario method. In this respect, the key variables were evaluated using a questionnaire from two aspects of importance and uncertainty as well as formation of a future studies group (focus group). Finally, sensitivity analysis was carried out through cross-impact balance (CIB) analysis using the Scenario Wizard (Version 4.31) software. RESULTS: A total of 25 factors were selected based on the type and the position of the variables (driving force, bi-dimensional, risk, secondary leverage or modifiable-to-secondary leverage) over the diameter of the MICMAC chart. Considering the degree of significance and uncertainty, eight variables including all four driving force variables (oil sales and economic blockade, leadership and advocacy, bureaucracy and corruption, and possibility of using information technology in providing services), as well as the variables of resource sustainability, natural disasters, regional security, and specialization culture were chosen. Then, five variables were finalized as the key changes that would create the scenario based on sensitivity analysis and final expert opinions. According to the defined conditions, 270 scenarios were developed, of which fourteen scenarios were identified as poorly adaptable and five cases as highly adaptable. CONCLUSION: The best scenario identified in this study based on the degree of adaptation included the use of massive technology and oil sales, mediocre economic conditions with high probability of occurrence, strong leadership and advocacy, high regional security, as well as bureaucracy and low corruption with medium probability of occurrence.

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The oceans face a range of complex challenges for which the impacts on society are highly uncertain but mostly negative. Tackling these challenges is testing society's capacity to mobilise transformative action, engendering a sense of powerlessness. Envisaging positive but realistic visions of the future, and considering how current knowledge, resources, and technology could be used to achieve these futures, may lead to greater action to achieve sustainable transformations. Future Seas (www.FutureSeas2030.org) brought together researchers across career stages, Indigenous Peoples and environmental managers to develop scenarios for 12 challenges facing the oceans, leveraging interdisciplinary knowledge to improve society's capacity to purposefully shape the direction of marine social-ecological systems over the UN Decade of Ocean Science for Sustainable Development (2021-2030). We describe and reflect on Future Seas, providing guidance for co-developing scenarios in interdisciplinary teams tasked with exploring ocean futures. We detail the narrative development for two futures: our current trajectory based on published evidence, and a more sustainable future, consistent with the UN's Sustainable Development Goals, which is technically achievable using existing and emerging knowledge. Presentation of Business-as-usual and More Sustainable futures-together-allows communication of both trajectories, whilst also highlighting achievable, sustainable versions of the future. The advantages of the interdisciplinary approach taken include: (1) integrating different perspectives on solutions, (2) capacity to explore interactions between Life Under Water (Goal 14) and other SDGs, and (3) cross-disciplinary learning. This approach allowed participants to conceptualise shared visions of the future and co-design transformative pathways to achieving those futures. Supplementary Information SI: The online version contains supplementary material available at (10.1007/s11160-020-09629-5) contains supplementary material, which is available to authorized users.

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The old paradigm of horizontal expansion of agricultural land and built-up areas over highland and lowland ecosystems remains highly prevalent in Cameroon, causing significant changes in LULC and undermining the resilience and sustainability of social-ecological systems. We analysed satellite imagery of 1986 and 2018 to examine the extent and spatial patterns of LULCC in Fako sub-region of Cameroon. In addition, we explored the likelihood of LULCC and magnitude of impact of the drivers and predictors of LULCC in the sub-region by engaging 25 stakeholders in a focus group survey. Other cultivated areas of cropland, built-up, oil palm, and banana plantation covers increased by 21,360 ha (10.5%), 3152 ha (1.6%), 5721 ha (2.8%), and 1823 ha (0.9%), while dense forest, rubber and tea plantation covers decreased by - 44,945 ha (- 22.1%), - 15,557 ha (- 7.7%), and - 110 ha (- 0.1%), respectively, from 1986 to 2018. Most of the deforestation and LULCC was caused by expansion of other cultivated areas of cropland by smallholders, contrary to the widely publicised narrative of agro-industrial and built-up areas expansion. The spatial pattern of LULCC showed that expansion of other cultivated areas of cropland and agro-industrial plantations were highest in the north and east zones, respectively, while expansion of built-up areas and decrease in agro-industrial plantation covers were highest in the central, south and western coastal zones of Fako division. The variations in the spatial patterns of LULCC between the sub-divisions are attributed to differences in rates of population growth and urbanisation, topography, size of farming population, proportion of cultivable land, socio-economic opportunities, and strength and resilience of local economy. The presence of the Mount Cameroon (4095 m), with high value forests, endemism, and conservation attractiveness restricted increased LULCC with elevation, while LULCC increased with nearness to the sea and national road networks. The likelihood of change from one LULC to oil palm plantation, banana plantation, and other cultivated areas and from rubber plantation, dense forest, lowland grassland to other land uses was 95% and 90%, respectively. Population growth, agricultural and farmland expansion, and infrastructural development were ranked as the three most important drivers of degradation under the business as usual scenario, while sustainable land management, good governance, and reforestation were ranked as the three most important predictors of LULCC reduction under the green economy scenario. In general, production and living space functions significantly increased at the expense of ecological land cover. Prioritising and increasing the legal protection of the mountain and coastal land-boundary ecosystems while providing for production and living land are invaluable for the sustainability of the social-ecological systems in the western highlands of Cameroon.

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Land-use planning is an important policy instrument for governing landscapes to achieve multifunctionality in rural areas. This paper presents a case study conducted in Na Nhan commune in the northwest montane region of Vietnam to assess land-use strategies toward multiple ecosystem services, through integrated land-use planning. The assessment employed the Land-Use Planning for Multiple Ecosystem Services (LUMENS) framework and a number of methods and tools, including land-use mapping, GIS-based land-use change analysis, survey questionnaire, rapid carbon-stock appraisal for different land uses, qualitative ecosystem services assessment, and a backcasting technique. Our findings suggest that a lack of participation and acknowledgement of customary land-use practices inhibit successful implementation of current land-use planning and relevant policies such as payment for forest environmental services and the nationally determined contributions. The study also confirmed the contributions of forests and the land-use sector in achieving national emission reduction targets, especially when local stakeholders are involved early in the planning process. Other findings with important policy implications are: (i) tree-based land uses such as agroforestry are key to securing multiple ecosystem services and are highly relevant to local stakeholders, yet their potentials were not made explicit in current debates at the local level; (ii) local stakeholders are highly aware of the co-benefits of ecosystem services to climate-change mitigation and this should be considered in nationally determined contributions; and (iii) an approach for integrated, participatory land-use planning can help catalyze stakeholder engagement, and hence improve governance in rural landscapes.

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Several studies have often cited crash occurrences as a motivation to perform a driving simulator experiment and test driver behavior to understand their causal relations. However, decisions regarding the simulated scenario and participants' requirements do not often rely directly on traffic crash data. To fill the gap between simulation and real data, we have proposed a new framework based on Clustering Analysis (K-medoids) to support the definition of driving simulator experiments when the purpose is to investigate the driver behavior under real risky road conditions to improve road safety. The suggested approach was tested with data of three years of police records regarding loss-of-control crashes and information on three Brazilian rural highways' geometry and traffic volume. The results showed the good suitability of the method to compile the data's diversity into four clusters, representing and summarizing the crashes' main characteristics in the region of study. Drivers' attributes (age and gender) were initially intended to integrate the clustering analysis; however, due to the sample's homogeneity of these characteristics, they did not contribute to the cluster definition. Hence, they were used simply to identify the target population for all scenarios. Therefore, we concluded that driving simulator experiments could benefit from the new approach since it identifies scenarios characterized by many variables connected to real risky situations and orients participants' recruitment leading to efficient safety analysis.

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The Delphi technique is a suitable methodology for structuring group communication to answer current and prospective research questions within several rounds. The method is used in many disciplines and characterized by anonymity, iteration, controlled feedback, and statistical "group response" (Rowe & Wright, 2001). This technical paper presents practical details and lessons learned from a two-round Delphi-based scenario study in which projections (Delphi statements, questions or hypotheses) were developed with findings from expert interviews and an expert workshop. This Delphi study provides answers to future-related questions for which other research methods are inappropriate. This is depicted as a five-step process, making it easy to follow and replicable, for example to help first-time Delphi-method researchers. In doing so, the authors aim to provide the community with valuable technical insights and guidance for studies applying the Delphi technique both to prospective questions and in other research settings.•Conducting a Delphi study can be a slow process with respect to receiving feedback from the panelists. Planning an appropriate period for distributing the questionnaire may produce a higher return rate. A sufficient time buffer should be incorporated into project planning.•Projections that create dissent among the panelists may provide valuable results.•Data analytics, software programs and online social networks can support researchers, save time and resources, and provide further insights in the process of conducting a Delphi study.

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Due to the increase in future uncertainty caused by rapid environmental, societal, and technological change, exploring multiple scenarios has become increasingly important in urban planning. Land Change Modeling (LCM) enables planners to have the ability to mold uncertain future land changes into more determined conditions via scenarios. This paper reviews the literature on urban LCM and identifies driving factors, scenario themes/types, and topics. The results show that: (1) in total, 113 driving factors have been used in previous LCM studies including natural, built environment, and socio-economic factors, and this number ranges from three to twenty-one variables per model; (2) typical scenario themes include "environmental protection" and "compact development"; and (3) LCM topics are primarily growth prediction and prediction tools, and the rest are growth-related impact studies. The nature and number of driving factors vary across models and sites, and drivers are heavily determined by both urban context and theoretical framework.

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Mountain regions cover one quarter of the Earth's terrestrial surface, and are both valuable and vulnerable areas with complex human-environmental interrelationships. In this coupled system, land-use changes induced by political or socio-economic transformations generate consequences for ecological landscape functions like soil productivity and species richness, and integrative land-use concepts provide the potential of a sustainable land development. In the Kazbegi region in the central Greater Caucasus of Georgia, these transformations further lead to landscape-structure change and population marginalization. Hence, we developed three agricultural land-use scenarios that meet Agenda 2030 Sustainable Development Goals to ensure a sustainable rural land development and the conservation of mountain ecosystems. Our normative scenario approach integrates quantitative and qualitative findings of empirical research in landscape ecology, soil science, vegetation ecology as well as agronomics and socio-economics. According to the examined environmental and socio-economic resources, we defined various scenario logics and normative assumptions that combine optimized livestock production (in dairy cow keeping and cattle fattening) with ecological limitations to maintain the functioning of mountain ecosystems. The rule-based scenarios achieved measurably increased outputs in biomass yields, livestock production and related revenues at the regional scale. Further, GIS generated scenario maps demonstrate the related land-use patterns spatially explicit and in high resolution, and visualize the alternative future from local to the regional scale. In conclusion, scenario development helps to determine region-specific and integrated land-use options to provide a sound base for land users and decision makers. Based on research on multiple landscape functions, this approach can assist sustainable land development in a mountain region.

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A deliberate expert-based scenario approach is applied to better understand the likely determinants of the evolution of the market for nanoparticles use in remediation in Europe until 2025. An initial set of factors had been obtained from a literature review and was complemented by a workshop and key-informant interviews. In further expert engaging formats - focus groups, workshops, conferences, surveys - this initial set of factors was condensed and engaged experts scored the factors regarding their importance for being likely to influence the market development. An interaction matrix was obtained identifying the factors being most active in shaping the market development in Europe by 2025, namely "Science-Policy-Interface" and "Validated information on nanoparticle application potential". Based on these, potential scenarios were determined and development of factors discussed. Conclusions are offered on achievable interventions to enhance nanoremediation deployment.

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To develop meaningful land use scenarios, drivers that affect changes in the landscape are required. In this study, driving factors that influence farmers to change crops on their farm were determined. A questionnaire was administered to four independent groups of farmers who identified and ranked influencing factors pertaining to their choices of crops. The farmers were located in two mid-latitude agricultural watersheds (in Germany and Canada). The ranked influencing factors were used to develop a "farmer driven" scenario to 2040 in both watersheds. Results showed that the most important influencing factors for farmers to change crops were the "economic return of the crop" and "market factors". Yet, when the drivers of crop land use change were grouped into two categories of "financial" and "indirectly-related financial" factors, the "financial" factors made up approximately half of the influencing factors. For some responses, the "indirectly-related financial" factors (i.e. "access to farm equipment", the "farm experience", and "climate") ranked higher than or just as high as the financial factors. Overall, in the four farmer groups the differences between the rankings of the influencing factors were minor, indicating that drivers may be transferable between farms if the farmers are full-time and the farming regions have comparable growing seasons, access to markets, similar technology, and government programs for farm income. In addition to the "farmer driven" scenario, a "policy driven" scenario was derived for each watershed based only on available information on the financial incentives provided to farmers (i.e. agricultural subsidies, income support, crop insurance). The influencing factors ranked by the farmers provided in-depth information that was not captured by the "policy driven" scenario and contributed to improving predictions for crop land use development. This straight-forward method to rank qualitative data provided by farmers can easily be replicated in other watersheds to improve environmental impact modelling.

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