Collective Opinion Research Articles

Leveraging uncertainty in collective opinion dynamics with heterogeneity

Natural and artificial collectives exhibit heterogeneities across different dimensions, contributing to the complexity of their behavior. We investigate the effect of two such heterogeneities on collective opinion dynamics: heterogeneity of the quality of agents’ prior information and of degree centrality in the network. To study these heterogeneities, we introduce uncertainty as an additional dimension to the consensus opinion dynamics model, and consider a spectrum of heterogeneous networks with varying centrality. By quantifying and updating the uncertainty using Bayesian inference, we provide a mechanism for each agent to adaptively weigh their individual against social information. We observe that uncertainties develop throughout the interaction between agents, and capture information on heterogeneities. Therefore, we use uncertainty as an additional observable and show the bidirectional relation between centrality and information quality. In extensive simulations on heterogeneous opinion dynamics with Gaussian uncertainties, we demonstrate that uncertainty-driven adaptive weighting leads to increased accuracy and speed of consensus, especially with increasing heterogeneity. We also show the detrimental effect of overconfident central agents on consensus accuracy which can pose challenges in designing such systems. The opportunities for improved performance and observablility suggest the importance of considering uncertainty both for the study of natural and the design of artificial heterogeneous systems.

Expert opinion on use of vagus nerve stimulation therapy in the management of pediatric epilepsy: a Delphi consensus study

Purpose: To provide consensus-based recommendations for use of vagus nerve stimulation (VNS) therapy in the management of pediatric epilepsy. Methods: Delphi methodology with two rounds of online survey was used to build consensus. A steering committee developed 43 statements related to pediatric epilepsy and the use of VNS therapy, which were evaluated by a panel of 12 neurologists/neurosurgeons with expertise in pediatric epilepsy, who graded their agreement with each statement on a scale of 1 (“I do not agree at all”) to 5 (“I strongly agree”). For each statement, consensus was established if ≥70% of the agreement scores were 4 or 5 and <30% were 1 or 2 in the final survey. Results: Twenty-four statements regarding the need for seizure reduction in pediatric epilepsy, the recommended treatment algorithm, the benefits and safety of VNS therapy, management of side effects of VNS therapy, patient selection for VNS therapy, and the use, dosing, and titration of VNS therapy achieved consensus. VNS and other neuromodulation therapies should be considered for pediatric patients with drug-resistant epilepsy who are not candidates for resective surgery, or who do not remain seizure free after resective surgery. When VNS therapy is initiated, the target dose range should be achieved via the fastest and safest titration schedule for each patient. Scheduled programming can be helpful in dose titration. Conclusion: The expert consensus statements represent the panelists’ collective opinion on the best practice use of VNS therapy to optimize outcomes in the management of pediatric epilepsy.

Dynamic multi-dose vaccination with initial immunity on higher-order networks

Vaccination remains crucial during pandemics for combating disease spread. We here propose a two-layer model for multi-dose vaccination policy, considering vaccine hesitancy, initial immunity, as well as media-driven information dissemination concerning vaccine strategy selection. Moreover, we consider collective opinions through social networks with higher-order interactions. We perform numerical simulations to analyse variations in vaccination strategies. We further compare obtained outcomes with the exploration of real data on vaccination behaviours. Our research indicates that information dissemination can regulate vaccination, and that models accounting for individual immunity align more closely with real-world scenarios. Furthermore, we find that considering vaccination decisions from neighbouring agents is crucial under multi-dose policies for the facilitation of faster vaccination diffusion.

Nonopioid Drugs for Postoperative Pain: A Selection Governed by Choices of the Authors of Academic Articles

The opioid crisis has profoundly changed the interest in using nonopioid analgesics. This review identified nonopioid drugs receiving the most interest in the treatment of postoperative pain. Publication-based interest, which reflects the authors’ choices of subjects for academic articles, was used to show the shifts in their interest. The authors’ choices of a particular drug for an article’s subject were regarded as reflective of the collective opinion of experts most knowledgeable on the subject. The frequency with which a drug was the topic of an article was measured with the use of specific bibliometric indices. They were employed to select nonopioid drugs for this review. These included acetaminophen, dexmedetomidine, dexamethasone, ketamine, gabapentin, ibuprofen, ketorolac, diclofenac, magnesium sulfate, clonidine, intravenous lidocaine, and meloxicam (in order of most to least bibliometric interest). Individual reviews on these agents described how the bibliometric indices characterized a drug. They also addressed the question of whether a nonopioid analgesic produced a marked opioid-sparing effect. Information relative to this question was presented via the results of meta-analyses with emphasis on the possible reduction of opioid-related side effects. Overall, nonopioid drugs demonstrating the largest popularity among authors and continuous interest growth in 2018-2022 include acetaminophen, dexmedetomidine, dexamethasone, and ibuprofen. The relevant meta-analyses show that nonopioids, administered as components of multimodal analgesia, provided the opioid-sparing effect; they also show that the most common change in the opioid-related side effects was a lower incidence of postoperative nausea and vomiting.

Mentorship for early career academics in a long-term problem- and project-based university academic development program in Denmark: views of subject and pedagogy mentors

ABSTRACT The study explored the viewpoints of two groups of mentors – subject and pedagogy – on their roles in a 12-month problem-based learning (PBL) academic development program at a Danish university. Q methodology analysis from 49 mentors revealed consensus on certain generic characteristics of good mentorship, namely active listening, constructive feedback, and mutual respect. Significantly distinguished collective opinions on good mentorship were identified through three factors: 1) providing advice using one’s own teaching experience, 2) probing mentee self-reflection and responsibility, and 3) co-creating and mediating. While most pedagogy mentors were loaded on Factor 2, emphasizing a social-constructivist approach centred on mentees, subject mentors’ views differed across all three distinct collective opinions. Factor 1 participants consisted mainly of subject mentors who have had no pedagogical background, with some reporting similar views to pedagogy mentors. Factor 3 included five female subject mentors who highlighted the importance of knowledge co-creation, reciprocity, and peer learning – an approach called for in the mentorship literature. The results suggest that structured mentorship preparation programs are needed, in addition to professional learning communities, for pedagogical and subject mentors to work collaboratively.

Raylike Subject Model of Text Deauthorization in Media Genres (in English and Belarusian)

The purpose of the article is to construct a raylike subject model of text deauthorization based on the material of English and Belarusian media texts of information genres with the identification of common and distinctive features. In the result of analysis of the ways in which the subject components of deauthorization structures are located in news articles and interviews using the modeling method, methods of semantic and contextual analysis, the raylike subject model of text deauthorization is constructed, which exhibits similar and distinctive features in the compared English and Belarusian media texts. The characteristics of the analyzed model that are common to the compared media cultures are established: structural and semantic parallelism of deauthorization structures, the presence of similar narrating subject groups, the dichotomy of opinions of specialists and non-specialists. Different features of the analyzed model in the compared media cultures are identified, which relate to the nature of the dominant pragmatic marking and the formal-referential characteristics of the subject components in deauthorization structures. The genre specificity of the studied model in the interview texts is revealed, where a new version of raylike subject model is discovered, in which two collective opinions are contrasted on the principle of «we» vs «strangers», while a number of fortifying discursive signals are used to strengthen the we-position.

A vision to the future: value-based laboratory medicine.

The ultimate goal of value-based laboratory medicine is maximizing the effectiveness of laboratory tests in improving patient outcomes, optimizing resources and minimizing unnecessary costs. This approach abandons the oversimplified notion of test volume and cost, in favor of emphasizing the clinical utility and quality of diagnostic tests in the clinical decision-making. Several key elements characterize value-based laboratory medicine, which can be summarized in some basic concepts, such as organization of invitro diagnostics (including appropriateness, integrated diagnostics, networking, remote patient monitoring, disruptive innovations), translation of laboratory data into clinical information and measurable outcomes, sustainability, reimbursement, ethics (e.g., patient empowerment and safety, data protection, analysis of big data, scientific publishing). Education and training are also crucial, along with considerations for the future of the profession, which will be largely influenced by advances in automation, information technology, artificial intelligence, and regulations concerning invitro diagnostics. This collective opinion paper, composed of summaries from presentations given at the two-day European Federation of Laboratory Medicine (EFLM) Strategic Conference "A vision to the future: value-based laboratory medicine" (Padova, Italy; September 23-24, 2024), aims to provide a comprehensive overview of value-based laboratory medicine, projecting the profession into a more clinically effective and sustainable future.

The 2024 British Society for Rheumatology guideline for management of systemic sclerosis-executive summary.

This guideline was developed according to the British Society for Rheumatology Guidelines Protocol by a Guideline Development Group comprising healthcare professionals with expertise in SSc and people with lived experience, as well as patient organization representatives. It is an update of the previous 2015 SSc guideline. The recommendations were developed and agreed by the group and are underpinned by published evidence, assessed by systematic literature review and reinforced by collective expert opinion of the group. It considers all aspects of SSc including general management, treatment of organ-based complications, including cardiopulmonary, renal and gastrointestinal tract manifestations, as well as broader impact of disease. Whilst it is focused on adults with SSc we expect that the guideline will be relevant to people of all ages and expert input and review by paediatric rheumatologists and other relevant specialists considered where the guideline was, or may not be, applicable to young people with SSc and juvenile-onset disease. In addition to providing guidance on disease assessment and management the full guideline also considers service organization within the National Health Service and future approaches to audit of the guideline. The lay summary that accompanies this abstract can be found in Supplemental information 1.

The 2024 British Society for Rheumatology guideline for management of systemic sclerosis.

This guideline was developed according to the British Society for Rheumatology Guidelines Protocol by a Guideline Development Group comprising healthcare professionals with expertise in SSc and people with lived experience, as well as patient organization representatives. It is an update of the previous 2015 SSc guideline. The recommendations were developed and agreed by the group and are underpinned by published evidence, assessed by systematic literature review and reinforced by collective expert opinion of the group. It considers all aspects of SSc including general management, treatment of organ-based complications, including cardiopulmonary, renal and gastrointestinal tract manifestations, as well as broader impact of disease. Whilst it is focused on adults with SSc we expect that the guideline will be relevant to people of all ages and expert input and review by paediatric rheumatologists and other relevant specialists considered where the guideline was, or may not be, applicable to young people with SSc and juvenile-onset disease. In addition to providing guidance on disease assessment and management the full guideline also considers service organization within the National Health Service and future approaches to audit of the guideline. The lay summary that accompanies this abstract can be found in Supplemental information 1.

Human immunodeficiency virus‐associated Lymphomas: EHA–ESMO Clinical Practice Guideline for diagnosis, treatment and follow‐up

Highlights This EHA–ESMO Clinical Practice Guideline provides key recommendations for managing HIV‐associated lymphomas. The guideline covers clinical, imaging and pathological diagnosis; staging and risk assessment; treatment and follow‐up. The author group encompasses a multidisciplinary group of experts from different institutions and countries in Europe. Recommendations are based on available scientific data and the authors’ collective expert opinion.

Hidden emotional trends on social media regarding the Thailand–China high-speed railway project: a deep learning approach with ChatGPT integration

Leveraging sentiment analysis on social media reveals hidden emotional trends by providing deep insights into the public’s collective opinions and feelings because social media can reflect most opinions based on true feelings. However, there is no time-series analysis of Thai opinions on social media regarding government projects in Thailand. Therefore, the focus of this research is to survey and dynamically analyze sentiment on social media platforms, particularly YouTube, regarding the Thailand–China High-Speed Rail Project (Thai–China HSR Project). This is a major project involving an investment of over 500 billion baht, a collaborative effort between the Thai and Chinese governments aimed at developing transportation infrastructure. It leads the public concerns of Thai people about the potential economic and social impacts. The deep learning (DL) technique was used for this analysis by the Bidirectional Encoder Representations from Transformers (BERT) model, together with WangchanBERTa, a Thai language model specifically designed to analyze opinions from Thai comments received from YouTube from July 2015 to January 2024. The analysis reveals that citizens’ sentiments are primarily neutral, with more negative than positive sentiments with the passing years. Results also indicate that the data volume has increased since 2019 and peaked in 2022. Negative comments peaked in January 2022, and based on our analysis, such negative comments followed news covering the opening of the China–Laos Railway on December 1, 2021. Video contents were related to the Thai–China HSR Project, which provides comparative reviews and analysis of government operations. Additionally, we explore the possibility of integrating AI technology based on the ChatGPT 4 model to support data interpretation. Although the AI model can interpret data quickly and efficiently serve as a convenient method for users, the results lack the in-depth analysis that should be done by experts in the field. The proposed framework could be useful to government agencies and can be used to quickly and efficiently survey and track public opinion. The results can be used for policy planning, strategic decision-making, and improving communications to better inform citizens about projects and operations, leading to the country’s sustainable economic and social development.

Suburbanization in Multi-ethnic Area – Conflicts and Local Strategies

The effects of suburbanization can be examined from several aspects, but beyond the individual decisions that initiated it, the real estate market aspects, or the transformation of land use, the effects on local communities and their reactions are rarely highlighted in professional circles. In our work within the agglomeration of Bratislava, the Slovak capital, we researched individual and collective opinions on suburbanization, as well as the questions and potential conflict situations arising among members of the “host community.” A striking element of the study area is that migration also means a change in the linguistic environment, as the newcomers often arrive from a predominantly Slovakspeaking city to an area mostly inhabited by the Hungarian minority. This adds additional dimensions to suburbanization and the responses it generates. Experiences show that the municipalities affected by the process use independent, yet in certain respects similar, strategies to manage it, and as part of these strategies, the ethnic factor also appears prominently in some topics.

Social network group decision-making method based on stochastic multi-criteria acceptability analysis for probabilistic linguistic term sets

In social network group decision-making (SNGDM) problems, decision-makers (DMs) often express their opinions or preferences using probabilistic linguistic term sets (PLTSs). In this paper, a novel SNGDM method for probabilistic linguistic information is proposed. Firstly, to obtain the prioritization of DMs in the clustering process, a DM clustering method for SNGDM is developed considering the influence of trust relationships and opinions similarity among DMs. Then, to satisfy the requirements of the consensus reaching process in SNGDM, a dynamic consensus threshold calculation method based on an optimization model is introduced. Furthermore, in the consensus measure stage, a novel consensus measure method for both DMs and subgroups is proposed, using a stochastic multi-criteria acceptability analysis (SMAA) method. Based on the consensus measure method, a novel SNGDM method based on SMAA for PLTSs is proposed. Finally, a case study of service quality evaluation in institutional pensions is used to illustrate the effectiveness of the proposed method. The results of case show that the proposed method can adjust consensus thresholds dynamically based on each round of collective opinions, and can solve the SNGDM problems when DMs can not provide their preferences for criteria weights.

An Online Review Data-Driven Fuzzy Large-Scale Group Decision-Making Method Based on Dual Fine-Tuning

Large-scale group decision-making (LSGDM) involves aggregating the opinions of participating decision-makers into collective opinions and selecting optimal solutions, addressing challenges such as a large number of participants, significant scale, and a low consensus. In real-world scenarios of LSGDM, various challenges are often encountered due to factors such as fuzzy uncertainties in decision information, the large size of decision groups, and the diverse backgrounds of participants. This paper introduces a dual fine-tuning-based LSGDM method using an online review. Initially, the sentiment analysis is conducted on online review data, and the identified sentiment words are graded and quantified into a fuzzy data set to understand the emotional tendencies of the text. Then, the Louvain algorithm is used to cluster the decision-makers. Meanwhile, a method combining Euclidean distances with Wasserstein distances is introduced to accurately measure data similarities and improve clustering performances. During the consensus-reaching process (CRP), a two-stage approach is employed to adjust the scores: to begin with, by refining the scores of the decision representatives via minor-scale group adjustments to generate a score matrix. Then, by identifying the scores corresponding to the minimum consensus level in the matrix for adjustment. Subsequently, the final adjusted score matrix is integrated with the prospect–regret theory to derive the comprehensive brand scores and rankings. Ultimately, the practicality and efficiency of the proposed model are demonstrated using a case study focused on the purchase of solar lamps. In summary, not only does the model effectively extract the online review data and enhance decision efficiency via clustering, but the dual fine-tuning mechanism in the model to improve consensus attainment also reduces the number of adjustment rounds and avoids multiple cycles without achieving the consensus.

A multi-period intuitionistic fuzzy consensus reaching model for group decision making problem in social network

A new intuitionistic fuzzy consensus reaching model is developed with multi-period public opinions and expert evaluation values in social network environment. First, the public opinions are obtained by using the crawler software and sentiment analysis technology is used to transform public opinions into intuitionistic fuzzy decision matrix in each period. Attribute weights are calculated by using the time attenuation factor and changes in public opinion. Second, the social trust relationship is modeled and incomplete social trust relationships are completed by using Archimedean t-norm. The expert weights are calculated by using the dynamic trust degree and similarity degree. Third, a consensus framework is proposed for multiple-period decision making problem, which coordinates conflicts between experts through dual feedback paths. The collective opinion scores are calculated by using weights of periods and attribute weights obtained from the word frequency of public opinions. The tourism attraction recommendation method is used to illustrate the proposed method.

Opinion consensus incorporating higher-order interactions in individual-collective networks

Abstract In the current information society, the dissemination mechanisms and evolution laws of individual or collective opinions and their behaviors are the research hot topics in the field of opinion dynamics. First, in this paper, a two-layer network consisting of an individual-opinion layer and a collective-opinion layer is constructed, and a dissemination model of opinions incorporating higher-order interactions (i.e. OIHOI dissemination model) is proposed. Furthermore, the dynamic equations of opinion dissemination for both individuals and groups are presented. Using Lyapunov’s first method, two equilibrium points, including the negative consensus point and positive consensus point, and the dynamic equations obtained for opinion dissemination, are analyzed theoretically. In addition, for individual opinions and collective opinions, some conditions for reaching negative consensus and positive consensus as well as the theoretical expression for the dissemination threshold are put forward. Numerical simulations are carried to verify the feasibility and effectiveness of the proposed theoretical results, as well as the influence of the intra-structure, inter-connections, and higher-order interactions on the dissemination and evolution of individual opinions. The main results are as follows. (i) When the intra-structure of the collective-opinion layer meets certain characteristics, then a negative or positive consensus is easier to reach for individuals. (ii) Both negative consensus and positive consensus perform best in mixed type of inter-connections in the two-layer network. (iii) Higher-order interactions can quickly eliminate differences in individual opinions, thereby enabling individuals to reach consensus faster.

Consensus reaching in LSGDM: Overlapping community detection and bounded confidence-driven feedback mechanism

The surge of social media has made large-scale group decision-making (LSGDM) crucial in real-world decision-making. The intricacies of trust relationships within social networks that emerged from relations in social media affect both the clustering and the consensus of large groups. However, existing research often neglects the impact of overlapping social trust networks on group consensus. To fill this gap, this study introduces a novel consensus-reaching process (CRP) that integrates overlapping community detection and ELICIT-based optimization models under bounded confidence. Initially, the Lancichinetti-Fortunato method (LFM) is employed to identify overlapping community structures within social trust networks, delineating several subgroups and identifying corresponding non-overlapping and overlapping decision-makers (DMs). Subsequently, the PageRank (PR) algorithm is utilized to compute both global and local weights for individuals, facilitating a rational aggregation of collective and subgroup opinions. Next, two-stage Extended Comparative Linguistic Expressions With Symbolic Translation (ELICIT)-based optimization consensus models under bounded confidence are designed, aiming to provide optimal feedback for guiding DMs' preference adjustments. Since overlapping DMs may belong to multiple subgroups, a weighted influence feedback mechanism is introduced to mitigate conflicting guidance from these multiple affiliations. Finally, we demonstrate the effectiveness and superiority of our proposed method through numerical validation and comparative analysis against existing approaches.

Influence of an interview location on opinions about the ecosystem services provided by trees

Collecting opinions regarding environmental management is essential, particularly in urban areas where space is limited, and interests often collide. However, the impact of the conditions in which the research is conducted on opinions and preferences elicited via surveys and interviews about the environment is usually taken for granted. The recent development of computer-aided survey methods allows a simulation of an environment, which can create an artificial environment for interviews. Therefore, examining whether direct access to the environment impacts opinions and preferences becomes a significant issue when considering environmental policies and management design and execution. This study examines whether the location of an interview, indoors or outdoors (in the vicinity of trees), influences the opinion on the ecosystem services (ES) trees provide. A quasi-experimental method with a map-aided computer-assisted personal interview (CAPI) survey in two Polish cities, indoors and outdoors, in the vicinity of trees, shows that respondents’ location did not significantly affect the opinion on the ES provided by trees. However, on average, respondents answering the survey inside buildings marked more trees on a map than those answering outside. We argue that although an interview location does not have a significant impact on the results, from the perspective of various stakeholder groups in participatory processes, the convenience of place is more important than the character of the place (i.e., in the vicinity of trees) as long as the survey method is mediated by a virtual representation of the subject of the study.

Point-of-care testing: state-of-the art and perspectives.

Point-of-care testing (POCT) is becoming an increasingly popular way to perform laboratory tests closer to the patient. This option has several recognized advantages, such as accessibility, portability, speed, convenience, ease of use, ever-growing test panels, lower cumulative healthcare costs when used within appropriate clinical pathways, better patient empowerment and engagement, and reduction of certain pre-analytical errors, especially those related to specimen transportation. On the other hand, POCT also poses some limitations and risks, namely the risk of lower accuracy and reliability compared to traditional laboratory tests, quality control and connectivity issues, high dependence on operators (with varying levels of expertise or training), challenges related to patient data management, higher costs per individual test, regulatory and compliance issues such as the need for appropriate validation prior to clinical use (especially for rapid diagnostic tests; RDTs), as well as additional preanalytical sources of error that may remain undetected in this type of testing, which is usually based on whole blood samples (i.e.,presence of interfering substances, clotting, hemolysis, etc.). There is no doubt that POCT is a breakthrough innovation in laboratory medicine, but the discussion on its appropriate use requires further debate and initiatives. This collective opinion paper, composed of abstracts of the lectures presented at the two-day expert meeting "Point-Of-Care-Testing: State of the Art and Perspective" (Venice, April 4-5, 2024), aims to provide a thoughtful overview of the state-of-the-art in POCT, its current applications, advantages and potential limitations, as well as some interesting reflections on the future perspectives of this particular field of laboratory medicine.

Expert consensus statements and summary of proceedings from the International Safety and Quality of Parenteral Nutrition Summit.

The International Safety and Quality of Parenteral Nutrition (PN) Summit consisted of presentations, discussions, and formulation of consensus statements. The purpose here is to briefly summarize the summit and to present the consensus statements. There was a high degree of consensus, with all statements approved by all authors/summit experts. These consensus statements should be regarded not as formal guidelines but rather as best-practice guidance intended to complement national and international nutrition society evidence-based guidelines and position statements. This article also summarizes key discussion topics from the summit, encompassing up-to-date knowledge and practical guidance concerning PN safety and quality in various countries and clinical settings, focusing on adult patients. Clear geographical differences exist between practices in Europe and the United States, and different approaches to improve the safety, quality, and cost-effectiveness of PN vary, particularly with regard to the delivery systems used. Discussion between experts allowed for an exchange of practical experience in optimizing PN use processes, opportunities for standardization, use of electronic systems, potential improvements in PN formulations, better management during PN component shortages, and practical guidance to address patients' needs, particularly during long-term/home PN. The consensus statements are the collective opinion of the panel members and form best-practice guidance. The authors intend that this guidance may help to improve the safety and quality of PN in a variety of settings by bridging the gap between published guideline recommendations and common practical issues.