Qualitative Expert Opinion Research Articles

Treatment decision for recurrences in non-small cell lung cancer during or after adjuvant osimertinib: an international Delphi consensus report.

Osimertinib is recommended by major guidelines for use in the adjuvant setting in patients with EGFR mutation-positive NSCLC following the significant improvement in disease-free survival observed in the Phase III ADAURA trials. Due to limited real-world data in the adjuvant setting, little guidance exists on how to approach potential recurrences either during or after the completion of the treatment. This study aimed to reach a broad consensus on key treatment decision criteria in the events of recurrence. To reach a broad consensus, a modified Delphi panel study was conducted consisting of two rounds of surveys, followed by two consensus meetings and a final offline review of key statements. An international panel of experts in the field of NSCLC (n=12) was used to provide clinical insights regarding patient management at various stages of NSCLC disease including patient monitoring, diagnostics, and treatment approach for specific recurrence scenarios. This study tested recurrences occurring 1) within or outside the central nervous system (CNS), 2) during or after the adjuvant-osimertinib regimen in NSCLC disease which is 3) amenable or not amenable to local consolidative therapy. Panellists agreed on various aspects of patient monitoring and diagnostics including the use of standard techniques (e.g., CT, MRI) and tumour biomarker assessment using tissue and liquid biopsies. Consensus was reached on 6 statements describing treatment considerations for the specific NSCLC recurrence scenarios. Panellists agreed on the value of osimertinib as a monotherapy or as part of the overall treatment strategy within the probed recurrence scenarios and acknowledged that more clinical evidence is required before precise recommendations for specific patient populations can be made. This study provides a qualitative expert opinion framework for clinicians to consider within their treatment decision-making when faced with recurrence during or after adjuvant-osimertinib treatment.

Barriers to inter-municipal cooperation

This article investigates barriers to inter-municipal cooperation in Slovakia, a country that is essentially formed of small municipalities. In a fragmented municipal structure, inter-municipal cooperation could be the way to achieve lower costs for service provision while maintaining or even increasing a quality service, taking into account economies of scale. The study aimed to identify the barriers to inter-municipal cooperation in Slovak conditions. The study uses a questionnaire and a qualitative expert opinions method. The potential of cost saving in local public services was identified as a motivation for inter-municipal cooperation. The main identified barriers are transaction costs (of different types), non-existent benchmarks (no regular comparisons of best solutions), and limited motivation to select the optimal mode of service provision.

Identification of innovative technology enablers and drone technology determinants adoption: a graph theory matrix analysis framework

Two main things ensure technology is integrated into a system: enablers, which help technology get in; and determinants, which act as filters to ensure that the right technology gets in. The study develops a decision framework for ranking determinants of drone technology adoption from the perspective of enablers related to innovative technology integration. This study is based on qualitative expert opinion and quantitative integrated MCDM methods. It provides a valuable graph theory matrix analysis framework for managerial perspectives. Several insights are given into the areas of what makes it possible to use new technologies and what makes people adopt drone technology. The study also points out problems and places where more research is needed.

Decreased muscle mass in type-2 diabetes. A hidden comorbidity to consider

an expert report is presented on the situation of loss of muscle mass in people with type 2 diabetes mellitus (T2DM), with a proposal of what the clinical approach to this comorbidity should be, based on the evidence from the literature and clinical experience. a qualitative expert opinion study was carried out using the nominal approach. A literature search on diabetes and muscle was made and submitted to a multidisciplinary group of 7 experts who through a face-to-face meeting discussed different aspects of the role of muscle mass in T2DM. muscle mass must be taken into account in the clinical context of patients with T2DM. It has an enormous impact on patient function and quality of life, and is as important as adequate metabolic control of T2DM. in addition to drug therapy and diet adjustments, aerobic and strength activities are essential for maintaining muscle mass and function in diabetic patients. In concrete situations, artificial oral supplementation specific for muscle care could improve the situation of malnutrition and low muscle mass. Measures such as the walking speed test, chair test, or the SARC-F questionnaire, together with the Barthel index, constitute a first step to diagnose relevant impairment requiring intervention in patients with T2DM. This document seeks to answer some questions about the importance, assessment, and control of muscle mass in T2DM.

A multi-criteria CCUS screening evaluation of the Gulf of Mexico, USA

Continued research into reservoir characterization along with offshore carbon dioxide (CO2) transportation and infrastructure assets is needed to facilitate development of safe and successful carbon capture, utilization, and storage (CCUS) projects. This paper outlines a multi-criteria evaluation methodology that incorporates disparate sets of quantitative, spatially variable data into a decision-making framework for screening the Gulf of Mexico (GOM) outer continental shelf (OCS) for potentially viable CO2 storage and enhanced oil recovery (EOR) sites. Criteria categories include favorable geologic characteristics, logistics, and potential risks. Data compiled for 14 criteria from several publicly available geographic information system (GIS) layers was aggregated over 2559 spatially balanced points across the study area using the National Energy Technology Laboratory (NETL)-developed Cumulative Spatial Impact Layers™ (CSIL) GIS tool. Criteria are weighted by qualitative expert opinion relative to their perceived importance to given scenarios— the output of combined criteria values and weights enables regional CO2 storage suitability differentiation. The methodology considers both technical and non-technical factors impacting CCUS decision-making. The flexible methodology enables a systematic approach to regional ranking at high spatial resolution over a large study domain. Additionally, the framework enables high-grading of priority sites that warrant further characterization and follow-on analysis. Areas along the Louisiana coast and Mississippi River Delta consistently rank high for all scenarios largely a result of the favorable geology with the potential for stacked storage, as well as the density of existing pipelines and platforms, and proximity to several onshore CO2 sources. High-graded regions for the CO2 EOR-related scenarios are typically located further offshore towards the middle and edge of the OCS compared to higher priority regions for the geologic storage scenarios which fall closer to the Louisiana coastline.

Strategies for sustainable irrigation system management: a socio-technical system approach

PurposeIrrigation System Management (ISM) poses many issues in terms of social and technical aspects. These can be further elaborated as the issues toward the efficiency of infrastructure, equity of water sharing, environmental integrity and economic acceptability. Water losses and the structural changes of the system caused many issues putting the irrigation system into distress. Hence, this urges the need for sustainable ISM to improve social and technical attributes in ISM. This paper aims to apply the Socio-Technical Systems (STSs) theory for sustainable ISM.Design/methodology/approachThe qualitative expert opinion survey method was selected as the research strategy to approach the research aim. Sixteen industry professionals in the ISM sector were selected through the purposive sampling method to conduct semi-structured interviews to collect data in the Sri Lankan context. Code-based content analysis through a directed approach was used to analyse the data.FindingsFour main categories of strategies were emerged from the research findings as “engineering strategies”, “operational strategies”, “management strategies” and “regulatory strategies” through STS approach for sustainable ISM. The STS framework was developed by combining engineering and operational strategies into the technical subsystem and the management and regulatory strategies into the social subsystem to approach the aim of achieving contemporary system management in irrigation in a sustainable manner.Originality/valueThe research revealed the links between the strategies emerged from various disciplines to minimise the issues in ISM from the perspectives of technical and social subsystems. The study contributes to knowledge by providing a framework for sustainable ISM by applying the socio-technical systems theory by integrating the concepts of sustainability.

Multi-stage sound planning methodology for urban redevelopment

Due to its local character, there is a tight link between the environmental noise issue and urban planning. Although the need for sound planning has been advocated since decades, limited information can be found on what this now means in practice. In this work, a methodology to internalize sound in the urban planning process is presented, applied to a major redevelopment project of a city ring road. The specific interest in increasing green infrastructure, and at the same time, tackling environmental noise, makes this project timely and challenging. Noise experts took part in an intense co-creation process with the spatial planning teams, where also dwellers were involved. Interactions ranged from conveying general information on environmental noise, providing solutions tailored to the local setting, qualitative expert opinions on initial plans, and assessing the applicability of uncommon noise abatements with numerical tools. The latter is important as the noise reduction potential of such measures could strongly influence the next round of spatial planning. Each planning phase should be optimized to allow maximum freedom in the next iterations. While evaluating various planning scenarios, separate acoustic goals were set for the sound exposure at dwellings, in the public space and along soft connections.

Determining the relative importance of titania nanotubes characteristics on bone implant surface performance: A quality by design study with a fuzzy approach.

TiO2 nanotubes (TNTs) are a promising bone/dental implant surface modification strategy with enhanced bioactivity and local therapeutic functions. However, inconsistencies related to the understanding of the influence of various TNTs characteristics on Ti implant functions, and the multi-factorial inter-dependence of such characteristics, requires an in-depth Quality by Design (QbD) analysis towards optimizing TNTs-modified implants. To this end, an extensive systematic literature search was undertaken to identify the various TNTs characteristics that may influence implant performance. Subsequently, in order to facilitate a QbD analysis, an expert questionnaire survey was carried out to determine the perceived contribution of various TNTs characteristics on an implant's biological, physicochemical, and mechanical performance. To achieve this goal, the Quality Function Deployment method was employed using symmetrical triangular fuzzy numbers to translate qualitative expert opinion into meaningful quantitative information. The results show that pore diameter, inter-nanotube distance and wall thickness are the TNTs characteristics with the most influential effects on the overall implant performance. This pioneering study evaluates perceived importance of various parameters contributing to TNTs functionality, and represents a step forward in the implementation of QbD strategies towards optimizing nano-engineered Ti implants.

An Uncertainty Quantification and Aggregation Framework for System Performance Assessment in Industrial Maintenance

The exponential increase in technological complexity of modern engineering systems necessitates rigorous and accurate maintenance planning to determine optimum equipment availability and turnaround time whilst allowing for overruns and unforeseen costs. Quality and availability of quantitative data, as well as qualitative expert opinion and experience expose uncertainties that can result in under or over estimation of the above factors. Uncertainty quantification in complex engineering systems should consider inter-connected components and associated processes from a combination of quantitative and qualitative (compound) perspectives. This paper presents a framework to quantify and aggregate compound uncertainties and to be assessed against a predetermined acceptable level of uncertainty. This will provide maintenance planners with a confident, comprehensive view of parameters surrounding the above factors to improve decision making capabilities. The framework was validated by assessing individual and compound uncertainties in a bespoke heat exchanger test rig comprised of subsystem modules interact in a non-linear manner, as well as subjective opinions and actions of operators. The results demonstrate the framework’s ability to effectively quantify these factors with an indication of their impact on the system. Future work will include further validation with more complex case studies and development of methods to forecast the quantified uncertainty through the in-service phase of an asset’s life cycle.

An innovative decision-making framework for evaluating transportation service providers based on sustainable criteria

Evaluating transportation service providers is an applied and multi-criteria decision-making problem. To ensure supply chain sustainability, it is important to consider all sustainable criteria for assessing and evaluating transport service providers. This paper aims to develop a new decision-making framework to evaluate transport service providers considering sustainable criteria from economic, environmental, social and operational aspects. The decision-making framework integrates both qualitative expert opinion and quantitative best-worst method (BWM) and VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method. The developed framework contributes to the academic literature by expanding the knowledge in supply chain sustainability by considering all possible sustainable criteria and integrating both qualitative and quantitative methods for evaluating transport service providers. This study also contributes to practice by developing a decision support tool, by which decision-makers can make an accurate, systematic and prompt decision to identify and assess sustainable criteria and to evaluate the priority of different transport service providers.

Using the Analytic Hierarchy Process for Prioritizing Imaging Tests in Diagnosis of Suspected Appendicitis

In clinical guideline or criteria development processes, such as those used in developing American College of Radiology Appropriateness Criteria (ACR AC), experts subjectively evaluate benefits and risks associated with imaging tests and make complex decisions about imaging recommendations. The analytic hierarchy process (AHP) decomposes complex decisions into structured smaller decisions, incorporates quantitative evidence and qualitative expert opinion, and promotes structured consensus building. AHP may supplement and/or improve the transparency of expert opinion contributions to developing guidelines or criteria. To conduct an empirical test using health services research tools, we convened a mock ACR AC panel of emergency department radiology and nonradiology physicians to evaluate by multicriteria decision analysis, the relative appropriateness of imaging tests for diagnosing suspected appendicitis. Panel members selected benefit-risk criteria via an online survey and assessed contrast-enhanced computed tomography, magnetic resonance imaging, and ultrasound using an AHP-based software. Participants were asked whether the process was manageable, transparent, and improved shared understanding. Priority scores were converted to rankings and compared to the rank order of ACR AC ratings. When compared to magnetic resonance and ultrasound imaging, participants agreed with the ACR AC that contrast-enhanced computed tomography is the most appropriate test. Contrary to the ACR AC ratings, study results suggest that magnetic resonance is preferable to ultrasound. When compared to nonradiologists, radiologists' priority scores reflect a stronger preference for computed tomography. Study participants addressed decision-making challenges using a relatively efficient data collection mechanism, suggesting that AHP may benefit the ACR AC guideline development process in identifying the relative appropriateness of imaging tests. With additional development, AHP may improve transparency when expert opinion is used in clinical guideline or appropriateness criteria development.

Analysis of temporal change in delivery of ecosystem services over 20 years at long term monitoring sites of the UK Environmental Change Network

The drivers and pressures experienced by farmland, forestry and upland sites in the UK Environmental Change Network (ECN) over the last 20 years are reported through the lens of recognised approaches to the assessment of ecosystem service delivery. Temporal trends in ecosystem service delivery were examined using two methods: qualitative narratives and quantitative scoring of ecosystem service delivery according to land cover. While all sites included in this study are within the same national governance unit (i.e. UK), individual local management decisions were the main agents driving change, influenced by EU and national policies. Gradual change in focus from provisioning to cultural ecosystem services was a persistent trend across most sites, and apparent in both methods. There was generally no net loss in regulating services at the sites. The two methods were subjective but as data were not available for the breadth of ecosystem services present at the sites between 1993 and 2012, it was concluded that it is more informative for holistic assessments to draw on qualitative expert opinion than to ignore less quantifiable services such as many of the cultural services.

Methodology for computing white matter nerve fiber orientation in human histological slices

BackgroundThe gold standard for mapping nerve fiber orientation in white matter of the human brain is histological analysis through biopsy. Such mappings are a crucial step in validating non-invasive techniques for assessing nerve fiber orientation in the human brain by using diffusion MRI. However, the manual extraction of nerve fiber directions of histological slices is tedious, time consuming, and prone to human error. New methodThe presented semi-automated algorithm first creates a binary-segmented mask of the nerve fibers in the histological image, and then extracts an estimate of average directionality of nerve fibers through a Fourier-domain analysis of the masked image. It also generates an uncertainty level for its estimate of average directionality. Results and comparison with existing methodsThe average orientations of the semi-automatic method were first compared to a qualitative expert opinion based on visual inspection of nerve fibers. A weighted RMS difference between the expert estimate and the algorithmically determined angle (weighted by expert's confidence in his estimate) was 15.4°, dropping to 9.9° when only cases with an expert confidence level of greater than 50% were included. The algorithmically determined angles were then compared with angles extracted using a manual segmentation technique, yielding an RMS difference of 11.2°. ConclusionThe presented semi-automated method is in good agreement with both qualitative and quantitative manual expert-based approaches for estimating directionality of nerve fibers in white matter from images of stained histological slices of the human brain.

Assessing species’ habitat associations from occurrence records, standardised monitoring data and expert opinion: A test with British butterflies

Accurate knowledge of species’ habitat associations is important for conservation planning and policy. Assessing habitat associations is a vital precursor to selecting appropriate indicator species for prioritising sites for conservation or assessing trends in habitat quality. However, much existing knowledge is based on qualitative expert opinion or local scale studies, and may not remain accurate across different spatial scales or geographic locations. Data from biological recording schemes have the potential to provide objective measures of habitat association, with the ability to account for spatial variation. We used data on 50 British butterfly species as a test case to investigate the correspondence of data-derived measures of habitat association with expert opinion, from two different butterfly recording schemes. One scheme collected large quantities of occurrence data (c. 3 million records) and the other, lower quantities of standardised monitoring data (c. 1400 sites). We used general linear mixed effects models to derive scores of association with broad-leaf woodland for both datasets and compared them with scores canvassed from experts.Scores derived from occurrence and abundance data both showed strongly positive correlations with expert opinion. However, only for occurrence data did these fell within the range of correlations between experts. Data-derived scores showed regional spatial variation in the strength of butterfly associations with broad-leaf woodland, with a significant latitudinal trend in 26% of species. Sub-sampling of the data suggested a mean sample size of 5000 occurrence records per species to gain an accurate estimation of habitat association, although habitat specialists are likely to be readily detected using several hundred records. Occurrence data from recording schemes can thus provide easily obtained, objective, quantitative measures of habitat association.

A system dynamics approach to modelling multiple drivers of the African penguin population on Robben Island, South Africa

The African penguin (Spheniscus demersus) population in southern Africa has experienced rapid decline in the 20th century and as of 2010 is listed as “endangered” on the IUCN Red List. There is an urgent need for decision support tools to enable effective management of colonies. We present a system dynamics model of the penguin population on Robben Island, South Africa, that combines a demographic simulation with the modelling of multiple pressures including food availability and food competition by commercial fisheries, oil spills, predation by terrestrial and marine predators, and extreme climate events. The model is stochastic, stage-specific and resource-driven, and incorporates both well-defined, quantitative field data and qualitative expert opinion. Survival rates for eggs, chicks, immatures and adults were adapted from field data and an earlier model of this population to create a simulation of a stable population used in a variety of scenarios and sensitivity tests. The modelled population was found to be strongly driven by food availability and to a lesser degree by oiling and marine predation, while climate events and terrestrial predation had low impacts. Food biomass levels (small pelagic fish) in the penguins’ foraging area around the island (used during nesting) and further afield (used during the rest of the year) had an equal influence in driving population development in the short and long run. The impact of short-term (three years) fishing restrictions currently being trialled around the island was found to be generally beneficial to the modelled population, but easily masked by food-driven variability in population growth. The model produced population dynamics similar to those observed in 1988–2009 when immigration and a plausible change in predation pressure during this period were simulated. The model is being extended to other colonies to provide tools for specific management decisions and to enable the study of meta-populations by modelling migration between colonies. Our results suggest that improving food availability and mitigating the impact of oiling would have the highest beneficial impact on this penguin population.

Partially Bayesian variable selection in classification trees

Tree-structured models for classification may be split into two broad categories: those that are completely datadriven and those that allow some direct user interaction during model construction. Classifiers such as CART [3 ]a nd QUEST [11] are members of the first category. In those datadriven algorithms, all predictor variables compete equally for a particular classification task. However, in many cases a subject-area expert is likely to have some qualitative notion about their relative importance. Interactive algorithms such as RTREE [17] address this issue by allowing users to select variables at various stages of tree construction. In this paper, we introduce a more formal partially Bayesian procedure for dynamically incorporating qualitative expert opinions in the construction of classification trees. An algorithm that dynamically incorporates expert opinion in this way has two potential advantages, each improving with the quality of the expert. First, by de-emphasizing certain subsets of variables during the estimation process, machine-based computational activity can be reduced. Second, by giving an expert’s preferred variables priority, we reduce the chance that a spurious variable will appear in the model. Hence, our resulting models are potentially more interpretable and less unstable than those generated by purely data-driven algorithms.

Unravelling the cognitive and interorganisational structure of public/private R&D networks: A case study of catalysis research in the Netherlands

This paper presents findings of a study that discloses key features of the Dutch R&D network in the area of catalysis, a sub-domain of industrial-relevant chemistry. The input comprises empirical data on collaborative research publications, informal network ties, and formal R&D linkages. The study aimed at identifying all public and private sector research organisations involved in the network, characterising their R&D output in terms of international scientific papers and patents, and describing and analysing relational and positional dimensions of their interorganisational network. The results provide an overview of Dutch activity within the worldwide cognitive landscape of catalysis R&D — from both a scientific and technological perspective. The interorganisational relationships reveal a strong and integrated network comprising many universities, public research labs, and private enterprises. The results of a mail survey held among academic and industrial researchers who are active within the network not only corroborate these empirical findings, but also elicited relevant criticisms concerning the efficiency and effectiveness of the network, and provided useful suggestions for its improvement. The paper concludes by looking at the benefits of this methodology, which links external quantitative information and qualitative expert opinions, as an analytical tool for government S&T policy and R&D management purposes.