Incorporating stakeholders' preferences into a multi-criteria framework for planning large-scale Nature-Based Solutions.
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ABSTRACT:
SUBMITTER: Ruangpan L
PROVIDER: S-EPMC8249655 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Nature-based solutions (NBS) find increasing attention as actions to address societal challenges through harnessing ecological processes, yet knowledge gaps exist regarding approaches to landscape planning with NBS. This paper aims to provide suggestions of how planning NBS can be conceptualized and applied in practice. We develop a framework for planning NBS by merging insights from literature and a case study in the Lahn river landscape, Germany. Our framework relates to three key criteria that define NBS, and consists of six steps of planning: Co-define setting, Understand challenges, Create visions and scenarios, Assess potential impacts, Develop solution strategies, and Realize and monitor. Its implementation is guided by five principles, namely Place-specificity, Evidence base, Integration, Equity, and Transdisciplinarity. Drawing on the empirical insights from the case study, we suggest suitable methods and a checklist of supportive procedures for applying the framework in practice. Taken together, our framework can facilitate planning NBS and provides further steps towards mainstreaming.
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Project description:Background: Increasingly, multi-criteria decision analysis has gained importance as a method by which to assess the value of orphan drugs. However, very little attention has been given to the weight (relative preferences) of the individual criteria used in a framework. Aims: This study sought to gain an understanding of the preferential weights that should be allocated in a multi-criteria decision analysis framework for orphan drugs, from a multi-stakeholder perspective. Method: Using key MCDA criteria for orphan drugs reported in the literature, we developed an interactive web-based survey tool to capture preferences for different criteria from a general stakeholder sample who were requested to assign weights from a reimbursement perspective. Each criterion could be assigned a weight on a sliding scale from 0 to 100% as long as the sum of all the criteria was 100%. We subsequently used the interactive tool with an expert focus group, followed up with a group discussion regarding each criterion and their perspectives on the weight that each criterion should be allocated when assessing an orphan drug. The expert focus group participants were then able to adjust their weights, if the group discussion had changed their perspectives. Results: The interactive tool was completed by 120 general stakeholder sample from a wide range of countries and professional backgrounds and an expert focus group of ten members. The results showed the differences in perspectives on the importance of criteria. Both groups considered Treatment efficacy to be the most important criterion. The general stakeholder sample weighted Treatment safety at 12.03% compared to the expert focus group's average of 20%. The results also demonstrated the value of the group discussion, which provided additional insights into the perspectives on the importance of criteria in assessing orphan drugs. Conclusion: This study aimed to contribute to the important aspect of preferences for different criteria in MCDA. This study sheds light on the important aspect of the preferences of the different criteria. All respondents agreed on the relative importance of Treatment efficacy and Treatment safety, criteria that are captured in conventional cost-effectiveness studies, but they also expressed the view that in addition to those, several disease-related and drug-related criteria should be included in MCDA frameworks for assessing orphan drugs.
| S-EPMC7225315 | biostudies-literature
Project description:Planning with nature-based solutions (NBS) presents a participatory approach that harnesses actions supported by nature to address societal challenges. Whilst Geodesign may facilitate participatory planning, manage boundaries between participants, and assess impacts of NBS, empirical insights remain scarce. This paper aims to develop and test a Geodesign process for planning with NBS, and to evaluate its contributions to boundary management. In a one-day Geodesign process, eleven stakeholders delineated priority areas, changed land uses, and observed resulting impacts on ecosystem services. Contributions to boundary management were evaluated regarding translation, communication and mediation functions, as well as perceived attributions of credibility, salience, and legitimacy. Results include spatial NBS scenarios and insights into contributions to boundary management: translating scenario stories into maps differed depending on the stakeholders involved; communication can be easily facilitated; yet mediation using an indicator tool led to frustration. Geodesign can indeed facilitate NBS co-design but needs to be integrated into a larger collaborative process.
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Project description:The solar wind is a magnetized plasma and as such exhibits collective plasma behavior associated with its characteristic spatial and temporal scales. The characteristic length scales include the size of the heliosphere, the collisional mean free paths of all species, their inertial lengths, their gyration radii, and their Debye lengths. The characteristic timescales include the expansion time, the collision times, and the periods associated with gyration, waves, and oscillations. We review the past and present research into the multi-scale nature of the solar wind based on in-situ spacecraft measurements and plasma theory. We emphasize that couplings of processes across scales are important for the global dynamics and thermodynamics of the solar wind. We describe methods to measure in-situ properties of particles and fields. We then discuss the role of expansion effects, non-equilibrium distribution functions, collisions, waves, turbulence, and kinetic microinstabilities for the multi-scale plasma evolution.
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Project description:We aimed to compare the volumetric-modulated arc therapy (VMAT) plans with or without multi-criteria optimization (MCO) on commercial treatment-planning systems (Eclipse, Varian Medical System, Palo Alto, CA, USA) for patients with prostate cancer. We selected 25 plans of patients with prostate cancer who were previously treated on the basis of a VMAT plan. All plans were imported into the Eclipse Treatment Planning System version 15.6, and re-calculation and re-optimization were performed. The MCO plan was then generated. The dosimetric quality of the plans was evaluated using dosimetric parameters and dose indices that account for target coverage and sparing of the organs at risk (OARs). We defined the rectum, bladder, and bilateral femoral heads. The VMAT-MCO plan offers an improvement of gross treatment volume coverage with increased minimal dose and reduced maximal dose. In the planning treatment volume, the Dmean and better gradient, homogeneity, and conformity indexes improved despite the increasing hot and cold spots. When implemented through the MCO plan, a steeper fall off the adjacent OARs in the overlap area was achieved to obtain lower dose parameters. MCO generated better sparing of the rectum and bladder through a tradeoff of the increasing dose to the bilateral femoral heads within the tolerable dose constraints. Compared with re-optimization and re-calculation, respectively, significant dose reductions were observed in the bladder (241 cGy and 254 cGy; p<0.001) and rectum (474 cGy and 604 cGy, p<0.001) with the MCO. Planning evaluation and dosimetric measurements showed that the VMAT-MCO plan using visualized navigation can provide sparing of OAR doses without compromising the target coverage in the same OAR dose constraints.
| S-EPMC8432831 | biostudies-literature
Project description:BackgroundA Multi Criteria Decision Analysis (MCDA) technique was adopted to reveal the preferences of the Appraisal Body of the Polish HTA agency towards orphan drugs (OMPs).ResultsThere were 34 positive and 23 negative HTA recommendations out of 54 distinctive drug-indication pairs. The MCDA matrix consisted of 13 criteria, seven of which made the most impact on the HTA process. Appraisal of clinical evidence, cost of therapy, and safety considerations were the main contributors to the HTA guidance, whilst advancement of technology and manufacturing costs made the least impact.ConclusionsMCDA can be regarded as a valuable tool for revealing decision makers' preferences in the healthcare sector. Given that only roughly half of all criteria included in the MCDA matrix were deemed to make an impact on the HTA process, there is certainly some room for improvement with respect to the adaptation of a new approach towards the value assessment of OMPs in Poland.
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Project description:The need for patient engagement has been recognized by regulatory agencies, but there is no consensus about how to operationalize this. One approach is the formal elicitation and use of patient preferences for weighing clinical outcomes. The aim of this study was to demonstrate how patient preferences can be used to weigh clinical outcomes when both preferences and clinical outcomes are uncertain by applying a probabilistic value-based multi-criteria decision analysis (MCDA) method. Probability distributions were used to model random variation and parameter uncertainty in preferences, and parameter uncertainty in clinical outcomes. The posterior value distributions and rank probabilities for each treatment were obtained using Monte-Carlo simulations. The probability of achieving the first rank is the probability that a treatment represents the highest value to patients. We illustrated our methodology for a simplified case on six HIV treatments. Preferences were modeled with normal distributions and clinical outcomes were modeled with beta distributions. The treatment value distributions showed the rank order of treatments according to patients and illustrate the remaining decision uncertainty. This study demonstrated how patient preference data can be used to weigh clinical evidence using MCDA. The model takes into account uncertainty in preferences and clinical outcomes. The model can support decision makers during the aggregation step of the MCDA process and provides a first step toward preference-based personalized medicine, yet requires further testing regarding its appropriate use in real-world settings.
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Project description:While high-throughput technology, advanced techniques in biochemistry and molecular biology have become increasingly powerful, the coherent interpretation of experimental results in an integrative context is still a challenge. BioModelKit (BMK) approaches this challenge by offering an integrative and versatile framework for biomodel-engineering based on a modular modelling concept with the purpose: (i) to represent knowledge about molecular mechanisms by consistent executable sub-models (modules) given as Petri nets equipped with defined interfaces facilitating their reuse and recombination; (ii) to compose complex and integrative models from an ad hoc chosen set of modules including different omic and abstraction levels with the option to integrate spatial aspects; (iii) to promote the construction of alternative models by either the exchange of competing module versions or the algorithmic mutation of the composed model; and (iv) to offer concepts for (omic) data integration and integration of existing resources, and thus facilitate their reuse. BMK is accessible through a public web interface (www.biomodelkit.org), where users can interact with the modules stored in a database, and make use of the model composition features. BMK facilitates and encourages multi-scale model-driven predictions and hypotheses supporting experimental research in a multilateral exchange.
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Project description:We compare the use of multi-criteria decision analysis (MCDA)-or more precisely, models used in multi-attribute value theory (MAVT)-to integrated assessment (IA) models for supporting long-term water supply planning in a small town case study in Switzerland. They are used to evaluate thirteen system scale water supply alternatives in four future scenarios regarding forty-four objectives, covering technical, social, environmental, and economic aspects. The alternatives encompass both conventional and unconventional solutions and differ regarding technical, spatial and organizational characteristics. This paper focuses on the impact assessment and final evaluation step of the structured MCDA decision support process. We analyze the performance of the alternatives for ten stakeholders. We demonstrate the implications of model assumptions by comparing two IA and three MAVT evaluation model layouts of different complexity. For this comparison, we focus on the validity (ranking stability), desirability (value), and distinguishability (value range) of the alternatives given the five model layouts. These layouts exclude or include stakeholder preferences and uncertainties. Even though all five led us to identify the same best alternatives, they did not produce identical rankings. We found that the MAVT-type models provide higher distinguishability and a more robust basis for discussion than the IA-type models. The needed complexity of the model, however, should be determined based on the intended use of the model within the decision support process. The best-performing alternatives had consistently strong performance for all stakeholders and future scenarios, whereas the current water supply system was outperformed in all evaluation layouts. The best-performing alternatives comprise proactive pipe rehabilitation, adapted firefighting provisions, and decentralized water storage and/or treatment. We present recommendations for possible ways of improving water supply planning in the case study and beyond.
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Project description:Genome-scale datasets have been used extensively in model organisms to screen for specific candidates or to predict functions for uncharacterized genes. However, despite the availability of extensive knowledge in model organisms, the planning of genome-scale experiments in poorly studied species is still based on the intuition of experts or heuristic trials. We propose that computational and systematic approaches can be applied to drive the experiment planning process in poorly studied species based on available data and knowledge in closely related model organisms. In this paper, we suggest a computational strategy for recommending genome-scale experiments based on their capability to interrogate diverse biological processes to enable protein function assignment. To this end, we use the data-rich functional genomics compendium of the model organism to quantify the accuracy of each dataset in predicting each specific biological process and the overlap in such coverage between different datasets. Our approach uses an optimized combination of these quantifications to recommend an ordered list of experiments for accurately annotating most proteins in the poorly studied related organisms to most biological processes, as well as a set of experiments that target each specific biological process. The effectiveness of this experiment- planning system is demonstrated for two related yeast species: the model organism Saccharomyces cerevisiae and the comparatively poorly studied Saccharomyces bayanus. Our system recommended a set of S. bayanus experiments based on an S. cerevisiae microarray data compendium. In silico evaluations estimate that less than 10% of the experiments could achieve similar functional coverage to the whole microarray compendium. This estimation was confirmed by performing the recommended experiments in S. bayanus, therefore significantly reducing the labor devoted to characterize the poorly studied genome. This experiment-planning framework could readily be adapted to the design of other types of large-scale experiments as well as other groups of organisms.
2010-01-24 | GSE16544 | GEO