Search Results (39)

Background/Objectives: Childhood vaccine refusal may negatively affect immunization programs in Türkiye, where regional clusters of hesitancy have emerged despite high national coverage. This study aimed to identify sociodemographic, behavioral, and vaccine confidence-related factors independently associated with childhood vaccine refusal in Konya, Türkiye. Methods: An unmatched case–control study was conducted between July and October 2025 in family health centers across Konya. Cases were parents who had refused at least one routine childhood vaccine (n = 406); controls were parents whose children had completed all routine vaccinations (n = 412). Data were collected through face-to-face interviews using a 47-item structured questionnaire and the Turkish version of the Vaccine Hesitancy Scale (VHS). Independent associations were assessed using multivariable logistic regression, with multicollinearity evaluated by variance inflation factors. Results: Maternal employment (aOR = 0.371, 95% CI: 0.218–0.633), parental COVID-19 vaccination (aOR = 0.131, 95% CI: 0.086–0.200), mother’s complete childhood immunization (aOR = 0.418, 95% CI: 0.262–0.667), tetanus vaccination during pregnancy (aOR = 0.259, 95% CI: 0.159–0.421), and neonatal vitamin K administration (aOR = 0.256, 95% CI: 0.132–0.497) were independently associated with lower refusal odds. Higher number of children (aOR = 1.281) and perceived vaccine-related adverse events in the social environment (aOR = 16.982, 95% CI: 9.914–29.089) increased refusal odds. VHS scores were significantly lower in the refusal group (22.2 ± 6.4 vs. 39.8 ± 6.5; p < 0.001), indicating greater hesitancy. Notably, 21.9% of refusing parents reported being advised by a healthcare professional not to vaccinate. Conclusions: Childhood vaccine refusal in Konya was associated with sociodemographic, behavioral, preventive health-related, and vaccine confidence-related factors. The findings suggest relatively reduced engagement with selected preventive health practices, greater reliance on non-professional information sources, and lower vaccine confidence among refusing parents. Interventions should focus on strengthening healthcare-professional communication, trust-building, transparent risk communication, and evidence-based social media strategies. Full article

A central challenge in complex group decision-making is how to integrate heterogeneous types of information. Experts differ in background and experience, which leads to variation in their understanding of assessment attributes and in the forms of information they provide. Such information may include fuzzy semantic information, fuzzy semantic interval information, and uncertain information, increasing the complexity of the decision process. Traditional approaches commonly employ fuzzy set (FS) and intuitionistic fuzzy set (IFS) models to address group decision-making problems involving human cognitive judgments. These models constrain the sum of the membership degree (MD) and the non-membership degree (non-MD) to be equal to 1 and less than or equal to 1, respectively. However, when assessment information is insufficient, the MD and non-membership degree provided by experts may exceed this constraint. In addition, the score function (SF) and accuracy function (AF) used in FS and IFS do not account for indeterminacy, making them unsuitable for handling incomplete and hesitation information. To overcome these limitations, this study proposes a Pythagorean fuzzy stepwise weight assessment ratio analysis-based method and introduces a new score function (NSF) and a new accuracy function (NAF) within the Pythagorean fuzzy set framework for complex group decision-making. An illustrative case on raw material vendor selection for shipbuilding enterprises is used to validate the effectiveness of the proposed method. The results demonstrate that the method produces more reasonable and accurate vendor ranking outcomes. Full article

Over the past few decades, extensive attention has been given by researchers and practitioners to the development and application of multi-criteria decision-making (MCDM) methods within intuitionistic fuzzy environments across a wide range of fields and disciplines. This challenging research area has emerged as one of the most prominent topics, and its importance and popularity are expected to continue growing in the future. The elliptic intuitionistic fuzzy set (EIFS) addresses complex, multidimensional, non-symmetrical vagueness and uncertainty more effectively than other traditional intuitionistic fuzzy sets (IFSs). Sustainable renewable energy source selection is a critical decision-making (DM) process aiming to identify the most suitable energy alternative. The process of selecting sustainable renewable energy sources necessitates a comprehensive assessment of numerous criteria, which encompass environmental ramifications, economic feasibility, and societal acceptance. Contemporary research suggests novel methodologies to enhance this selection process, highlighting the need for an MCDM framework that integrates a variety of factors. This study presents an innovative DM framework for sustainable renewable energy source selection based on EIFS and a newly developed aggregation operator, the Elliptic Intuitionistic Fuzzy Weighted Muirhead Mean Aggregation (EIFWMMA) operator. These mechanisms expand upon conventional intuitionistic fuzzy frameworks by employing an elliptical portrayal of membership and non-membership degrees, facilitating a more accurate and lifelike representation of uncertainty and hesitation in evaluations by experts. To enhance computational efficiency, the framework weaves together machine learning-driven dimensionality reduction and weight optimization strategies of principal component analysis (PCA) for DM. The suggested operators are employed in an MCDM scenario centered around the selection of sustainable renewable energy sources, where the hierarchy of alternatives is established through score values derived from EIFWMMA. A comparative exploration of Circular Intuitionistic Fuzzy Sets (C-IFSs) and Interval-Valued Intuitionistic Fuzzy Sets (IVIFSs) uncovers that the elliptical formulation yields consistently reliable, precise, and geometrically comprehensible results. The findings affirm that EIFS-based operators offer a resilient, adaptable, and broadly applicable strategy for tackling MCDM challenges amidst uncertainty. The Min–Max normalization method is employed to validate our proposed methodology for identifying alternatives within the MCDM paradigm. It also improves accuracy, stability, and scalability in comparison to conventional approaches. Full article

Background: Childhood vaccination remains one of the most effective public health interventions. Despite consistently high national coverage, vaccine hesitancy persists among parents and may undermine herd immunity. The Parent Attitudes about Childhood Vaccines (PACV) questionnaire provides a validated framework for identifying parental concerns and patterns of hesitancy. Methods: A cross-sectional online survey was conducted in May 2025 using the Croatian version of the Parent Attitudes about Childhood Vaccines (PACV) questionnaire. The study included 1087 parents aged 18–65 years. PACV scores were transformed to a 0–100 scale, with values ≥50 indicating vaccine hesitancy. Associations between PACV scores and parental age and educational level were analysed using non-parametric statistical tests. Results: Most respondents were mothers (87.7%) and aged between 30 and 45 years (71.8%). Approximately one fifth of parents reported postponing vaccination (22.7%), and 19.2% indicated having refused at least one vaccine dose. While 63.7% expressed full acceptance of recommended childhood vaccines, a substantial proportion either refused vaccination (20.8%) or remained undecided (15.5%). Higher educational attainment was significantly associated with lower PACV scores, whereas no significant association was observed with parental age. Conclusions: Although overall vaccination acceptance in Croatia remains high, vaccine hesitancy continues to affect a considerable proportion of parents. Strengthening tailored communication strategies and reinforcing trust-based counselling—particularly within pediatric and community nursing services—may support informed decision-making and improve vaccine confidence. Full article

University students are a major target population for infectious disease prevention programmes. Understanding the barriers to implementation of these programmes, and specifically vaccines, among student populations is critical for effective health prevention strategies. To assess changes in COVID-19 vaccine hesitancy and vaccine delivery programmes, we compared questionnaire-based survey data of two cohorts of first year students from two points, July and October 2021, during the COVID-19 vaccine rollout in the United Kingdom. We observed a highly significant increase in vaccine uptake without any alteration in vaccine hesitancy, as measured using a modified VAX score between the two survey dates. The October survey confirmed an association of vaccine hesitancy with the Non-White ethnic group and specifically identified concerns with the plurality of vaccine testing as a potential cause of this hesitancy. University pop-ups for COVID-19 vaccine delivery were not extensively utilised but were deemed as strongly or weakly favourable by 28.3% of students. Survey responses indicated that on-campus pop-ups for delivery of MMR and MenACWY were also supported by a significant minority of students. Full article

Background: Human papillomavirus (HPV) infection is the most common sexually transmitted infection worldwide and a major cause of several cancers. HPV vaccination is the most effective measure of preventing HPV infection, but knowledge and attitudes towards HPV vaccination are inconsistent. Methods: This study aimed to assess the knowledge, attitudes, and vaccination status related to HPV among university students in both healthcare and non-healthcare fields. A cross-sectional online survey was conducted among 769 full-time students, including 362 healthcare and 407 non-healthcare students. Validated questionnaires assessed HPV knowledge, vaccination attitudes, sociodemographic characteristics, and vaccination status. Results: Healthcare students scored significantly higher on HPV knowledge and had more positive attitudes towards vaccination compared to non-healthcare students. Vaccination rates were similar in both groups. Higher HPV knowledge was significantly correlated with reduced vaccine hesitancy and more positive vaccination attitudes. Binary logistic regression indicated that being younger, having more positive attitudes toward vaccination, and possessing greater knowledge about HPV were each associated with a significantly higher likelihood of HPV vaccination. Conclusions: In conclusion, targeted educational interventions are necessary to enhance HPV vaccination acceptance, especially among non-healthcare students. Universities represent crucial settings for promoting health literacy and increasing HPV vaccination coverage to effectively prevent HPV-related cancers among young adults. Full article

Background: Vaccine hesitancy (VH) remains a pressing global health concern, particularly in low-resource settings, where vaccination remains the primary means of protection against infection. The urgency of this issue became evident during the COVID-19 pandemic. The present study aimed to elucidate the determinants of vaccine hesitancy among university students in medical and non-medical fields in Syria by utilizing the 5C framework (confidence, complacency, constraints, calculation, and collective responsibility). Methods: A structured interview-administered questionnaire collected responses from 4722 students at five universities in Syria. The questionnaire assessed sociodemographic factors, COVID-19 vaccination status, vaccination experience, sources of information, beliefs in vaccine-related conspiracies, attitudes toward vaccine policies and attributes, and the 5C psychological antecedents. Internal consistency and factor analysis of the Arabic 5C scale were performed to ensure construct validity. Statistical analyses included descriptive statistics, logistic regression, and multivariate multiple regression. Results: Our findings revealed that 64% of participants had not received the COVID-19 vaccine, with official sources (e.g., WHO, Ministry of Health) being the most trusted. The highest 5C score was for calculation (5.86, sd = 1.21), followed by confidence (5.29, sd = 1.26). Belief in vaccine conspiracies was common, particularly regarding profit motives and genetic modification. Only three of the 5C—complacency, calculation, and collective responsibility—significantly, predicted vaccination behavior, while all the 5C were influenced by contextual factors. Non-medical students showed significantly higher hesitancy (OR = 1.60, 95% CI [1.39–1.84, p < 0.001]) compared to their medical counterparts. Hesitant respondents displayed significantly, higher complacency, increased calculation, and reduced collective responsibility scores. Conspiracy beliefs eroded confidence and magnified perceived barriers, whereas trust in official sources and favorable views of the vaccine’s attributes strengthened collective responsibility and acceptance. The regression models explained 2.8% to 11.2% of variance across the 5C, with collective responsibility showing the highest explanatory power (adjusted R² = 0.112). Conclusions: Despite high self-reported knowledge, significant VH persisted—a paradox that highlights the limits of information alone. Given the cross-sectional design and the modest explanatory power of the models, these recommendations are tentative. These findings highlight the need for trust-based interventions targeting populations in conflict-affected areas. Full article

As vision and mission statements embody the directions set forth by an organization, their connection to the Sustainable Development Goals (SDGs) must be made explicit to guide overall decision-making in taking strides toward the sustainability agenda. The semantic alignment of these strategic statements with the SDGs is investigated in a previous study, although several limitations need further exploration. Thus, this study aims to advance two contributions: (1) utilizing the capabilities of LLMs (Large Language Models) in text semantic analysis and (2) integrating fuzziness into the problem domain by using a novel intuitionistic fuzzy set extension of the PROBID (Preference Ranking On the Basis of Ideal-average Distance) method. First, a systematic approach evaluates the semantic alignment of organizational strategic statements with the SDGs by leveraging the use of LLMs in semantic similarity and relatedness tasks. Second, viewing it as a multi-criteria decision-making (MCDM) problem and recognizing the limitations of LLMs, the evaluations are represented as intuitionistic fuzzy sets (IFSs), which prompted the development of an IF extension of the PROBID method. The proposed IF-PROBID method was then deployed to evaluate the 47 top Philippine corporations. Utilizing ChatGPT 3.5, 7990 prompts with repetitions generated the membership, non-membership, and hesitance scores for each evaluation. Also, we developed a cohort-dependent SDG–vision–mission matrix that categorizes corporations into four distinct classifications. Findings suggest that “highly-aligned” corporations belong to the private and technology sectors, with some in the industrial and real estate sectors. Meanwhile, “weakly-aligned” corporations come from the manufacturing and private sectors. In addition, case-specific insights are presented in this work. The comparative analysis yields a high agreement between the results and those generated by other IF-MCDM extensions. This paper is the first to demonstrate two methodological advances: (1) the integration of LLMs in MCDM problems and (2) the development of the IF-PROBID method that handles the resulting inherently imprecise evaluations. Full article

Background/Objectives: Vaccine hesitancy among immunocompromised patients is complex and not well understood. This study aimed to determine the rate of COVID-19 vaccine hesitancy among pediatric oncology and bone marrow transplant (BMT) patients and to understand associated factors. Methods: Parents of patients (≤18 years) with cancer or post-BMT completed the Parent Attitudes about Childhood Vaccines Survey. A COVID-19 vaccine hesitancy score (VHS-COVID) was calculated from 0 to 100 (higher scores indicating increasing hesitancy). A small group of patients (patients older than 15 years) were also surveyed directly. Results: Among 113 parent respondents, the majority were female (58%) and at least college/university educated (78%). The majority (73%) of patients had cancer (61% leukemia/lymphoma, 37% solid/CNS tumors), while 27% had received BMT for malignant and non-malignant conditions. Only 48% of patients had been vaccinated against COVID-19, compared to 88% of parents. Ineligibility due to phase of cancer/BMT treatment (27%), vaccine hesitancy (24%), and age (24%) were the top three reasons for not vaccinating against COVID-19. Only 13% of parents said they would “definitely vaccinate” if their child became eligible. VHS-COVID scores were higher for parents of patients in surveillance versus active therapy (mean 61 vs. 48; p = 0.03). Parents who had received fewer COVID-19 vaccine doses (0–1 vs. ≥2) were more hesitant toward all vaccines (p = 0.0002), COVID-19 vaccines (p = 0.0003), and influenza vaccines (p = 0.005). Conclusions: Vaccine hesitancy is common among this population and was demonstrated through beliefs (hesitancy scores) as well as vaccine uptake. Future work should focus on education targeting vaccine eligibility and engaging with vaccine hesitant families in the immunocompromised community. Full article

This paper presents an innovative methodology for the dynamic emergency response scheme selection (ERSS) problem in post-major natural disasters. It employs a combination of subjective and objective composite weights and the integrated ELECTRE-score approach. The study aims to provide a practical approach for continuously determining optimal decision schemes at various time points during the decision period in the aftermath of significant natural disasters while accommodating evolving real-world scenarios. Firstly, the probabilistic T-spherical hesitant fuzzy set (Pt-SHFS) captures decision-makers’ ambivalence and hesitation regarding diverse evaluation attributes of different schemes. Subsequently, Pt-SHFS is integrated with the best–worst method (BWM) to determine subjective weights, followed by the structured CRITIC method to amalgamate subjective weights and derive the final combination weights of criteria. Additionally, this paper proposes applying a penalty-incentive mechanism to establish dynamic attribute weights during scenario evolution. Furthermore, the ELECTRE-score method, which may fully exploit the advantages of non-compensation situations, is adopted to obtain more reliable dynamic optimal decision outcomes. Consequently, based on these foundations, an integrated dynamic ERSS approach is formulated to determine optimal dynamic emergency response schemes. Finally, a case study on the Gansu Jishishan earthquake, sensitivity analysis, comparative analysis, and continuous analysis are conducted to verify the practicality, stability, and effectiveness of the proposed approach. The result shows that the proposed comprehensive approach can depict variances among experts’ information, dynamically adjust attribute weights in response to evolving scenarios, and assign a score range and a representative score to each scheme at each decision state. Sensitivity and comparative analyses show this model has strong stability and dynamics. Furthermore, the proposed approach can effectively deal with the complex dynamic situation in the earthquake rescue process, such as the secondary collapse of buildings after the earthquake, the damage of materials caused by heavy rain, and the occurrence of aftershocks. The model can continuously optimize decision-making and provide scientific and reliable support for emergency decision-making. Full article

We aimed to examine vaccine hesitancy and knowledge towards influenza vaccines among Jordanian parents. Data were collected via an online questionnaire distributed between October 2023 and March 2024. They included sections on demographics, parental attitudes towards childhood vaccines (PACVs), and knowledge and practices towards influenza vaccines. Associations were examined using the chi-squared test. A binary logistic regression model was utilized to determine predictors of vaccine usage. A total of 3208 participants were included, of which 9.3% were vaccine hesitant per the PACV categorization. Fathers were more likely to be vaccine hesitant (OR: 1.40; 95CI: 1.07–1.85). Similarly, divorced parents (OR: 1.80; 95CI: 1.05–3.12) were significantly more vaccine hesitant compared to their married counterparts. Conversely, higher monthly income (OR: 0.66; 95CI: 0.48–0.92), working in healthcare settings (OR: 0.71; 95CI: 0.51–0.98), and adherence to national vaccination policies (OR: 0.07; 95CI: 0.04–0.13) were significantly associated with a lower likelihood of vaccine hesitancy. Multivariate analysis shows that a healthcare-related occupation (OR: 0.62; 95CI: 0.44–0.87), semi-compliance (OR: 0.37; 95CI: 0.22–0.64), full compliance (OR: 0.08; 95CI: 0.05–0.13) with national vaccine guidelines, and knowledge scores of influenza and vaccines (OR: 0.79; 95CI: 0.75–0.84) were the only independent factors influencing vaccine hesitancy. Finally, non-hesitant participants were significantly more likely to give the influenza vaccine to their children at the present or future time (OR: 2.07; 95CI: 1.53–2.80). Our findings highlight the complexity of vaccine hesitancy and underscore the importance of tailored interventions. Cultural, socioeconomic, and individual factors play significant roles in shaping attitudes toward vaccination. An understanding of the aforementioned among Jordanian parents provides insights for public health initiatives. Compliance with national vaccination guidelines and addressing concerns about vaccine safety are essential for improving childhood vaccination rates in Jordan. Full article

The informational domain related to COVID-19 reflects the degree of uncertainty and pace of evolution of the pandemic. This places a burden on peoples’ searches for information to guide their choices, importantly including for COVID-19 vaccines. Thus, it is important for health communications that support vaccination campaigns to attenuate vaccine hesitancy to be accessible, including in terms of readability, and adapted to the evolving pandemic. This paper aims to understand internet searches on COVID-19 vaccination, specifically the mix of sources and readability of the sources over a two-year period (2021–2023) in Singapore, Hong Kong, and the Philippines, for search results in English, as English is a main language for each of these locations. The sources accessed through online searches in June 2021 and May 2023 were categorized by type of source and whether they were from one of the focal locations or elsewhere. The readability of information from web-search results was assessed using a set of readability tests (Flesch–Kincaid Reading Ease, Flesch–Kincaid Grade Level, Gunning Fog Index, Coleman–Liau Index, and Simple Measure of Gobbledygook Grade level). Over the two-year period there was an increase in government sources and reduction in mass media sources with distinct local patterns. Local government sources increased in Singapore whereas foreign government and multi-lateral organization sources increased in Hong Kong, with the Philippines being an intermediate pattern. In contrast to the changing mix of sources, the readability tests indicate a low proportion of URLs scoring within recommended readability thresholds across locations and types of sources over the two years. Information on COVID-19 vaccine development and deployment is an important part of health communications that includes internet search. The paper contributes to understanding health communications during a pandemic, including mix of local and non-local sources and contingency on local social and health context. Full article

Similarity measures on trapezoidal-valued intuitionistic fuzzy numbers (TrVIFNs) are functions that measure the closeness between two TrVIFNs, which has a lot of applications in the area of pattern recognition, clustering, decision-making, etc. Researchers around the world are proposing various similarity measures on the generalizations of fuzzy sets. However, many such measures do not satisfy the condition that “the similarity between two fuzzy numbers is equal to 1 implies that both the fuzzy numbers are equal” and this gives a pathway for the researchers to introduce different similarity measures on various classes of fuzzy sets. Also, all of them try to find out the similarity by using a single function, and in the present study, we try to propose a combined similarity measure principle by using four functions (four similarity measures). Thus, the main aim of this work is to introduce a few sets of similarity measures on the class of TrVIFNs and propose a combined similarity measure principle on TrVIFNs based on the proposed similarity measures. To do this, in this paper, firstly, we propose four distance-based similarity measures on TrVIFNs using score functions on TrVIFNs and study their mathematical properties by establishing various propositions, theorems, and illustrations, which is achieved by using numerical examples. Secondly, we propose the idea of a combined similarity measure principle by using the four proposed similarity measures sequentially, which is a first in the literature. Thirdly, we compare our combined similarity measure principle with a few important similarity measures introduced on various classes of fuzzy numbers, which shows the need for and efficacy of the proposed similarity measures over the existing methods. Fourthly, we discuss the trapezoidal-valued intuitionistic fuzzy TOPSIS (TrVIF-TOPSIS) method, which uses the proposed combined similarity measure principle for solving a multi-criteria decision-making (MCDM) problem. Then, we discuss the applicability of the proposed modified TrVIF-TOPSIS method by solving a model problem. Finally, we discuss the sensitivity analysis of the proposed approaches by using various cases. Full article

Addressing the complex issue of multi-attribute decision-making within a probabilistic dual hesitant fuzzy context, where attribute weights are unknown, a novel decision-making method based on cumulative prospect theory is proposed, named the probabilistic dual hesitant fuzzy multi-attribute decision-making method based on cumulative prospect theory. Firstly, a decision matrix is formulated, representing probabilistic dual hesitant fuzzy information. Secondly, according to the decision maker’s authentic preference and non-membership information sensitivity, a comprehensive score function suitable for probabilistic dual hesitant fuzzy elements is proposed. The attribute weights are then determined using the entropy method. Next, the value function and decision weight function from the cumulative prospect theory are employed to compute the cumulative prospect value attributed to each available scheme. In addition, a cumulative prospect matrix is constructed, enabling the establishment of scheme rankings based on the comprehensive cumulative prospect value. Finally, the analysis of specific cases and a comparative assessment of methods pertaining to the selection of emergency response schemes collectively demonstrate the rationality and efficacy of the decision-making method presented in this study. Full article

The communication practices of general practitioners in relation with vaccines have not been a topic of wide scientific interest. In this article, we outline them in the context of Bulgaria. A representative, cross-sectional, quantitative, face-to-face survey was conducted among 358 Bulgarian general practitioners in 2022 using simple random sampling. We conducted an exploratory factor analysis using questions about the role of the GPs, which measure models of communication. Based on the factor analysis, we distinguished four communication styles. They were called: active communicator, restrictive communicator, informing communicator, and strained communicator. One-way ANOVA and the T-test were carried out to explore the connections between factor scores (communication styles) and other variables. One of the most important results in the study was that the informing physician (emphasizing the choice of the parents) was the most common model in Bulgaria. This is somewhat contradictory, because of the mandatory status of most vaccines. We found connections between the communication styles and other variables—such as the type of settlement, having a hesitant parent in the practice, recommendations of non-mandatory vaccines, and experience with vaccine-preventable diseases. On the basis of the factor analysis and analysis of relationships with other variables, we reached the conclusion that in Bulgaria, hesitant parents are not sufficiently involved in active, effective communication about vaccines by GPs. Full article