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Background: Contemporary pediatric oncology confronts medical staff with challenges that are not only clinical but also ethical and existential in nature. The aim of this study was to identify the cognitive and affective factors associated with medical professionals' attitudes toward fertility preservation procedures (oncofertility) in pediatric patients. In particular, the association of "existential vacuum" (lack of life goals, sense of meaninglessness), value systems, and religiosity on the level of competence and emotional acceptance of these procedures was examined. Methods: A cross-sectional observational study was conducted between January and September 2024 in pediatric oncology centers in Poland (Gdańsk, Lublin, Łódź, and Poznań). The study group consisted of 62 medical professionals (62.9% physicians and 37.1% nurses) selected using purposive sampling. The research protocol included an Author-Designed Questionnaire, the Scheler Value Scale (SVS), the Life Attitude Profile-Revised (LAP-R), and the Centrality of Religiosity Scale (CRS-15). Statistical analyses comprised Pearson's r correlations, multiple regression analysis, and cluster analysis using the k-means method. Results: Participants demonstrated a moderate level of substantive competence in oncofertility (M = 2.31 on a 5-point scale). Regression analysis revealed that "existential vacuum" was the strongest negative predictor of competence (B = -0.34; p = 0.001), which was found to be a significant negative correlate of professional development in this area. In the affective domain, a pronounced normative conflict was observed: religiosity was negatively correlated with emotional acceptance of the procedures (r = -0.42; p < 0.001), indicating tension between medical imperatives and worldview-based beliefs. At the same time, the regression model showed that internalized religiosity and moral values might theoretically function as an "axiological buffer"; however, due to the severe psychometric limitations of the emotional acceptance measure (α = 0.268), these affective associations are highly tentative and unstable. Alternative measurement strategies are required to validate this hypothesis. Exploratory cluster analysis suggested the potential existence of two professional profiles: "Axiologically Integrated" staff members and a larger group of "Existential Skeptics", who exhibited higher "existential vacuum" and lower psychosocial resources. Conclusions: Viewed through a dual-process interpretative lens, a theoretical phenomenon of cognitive-affective dissociation was explored. The highly tentative data suggest that "existential vacuum" might represent a hypothesized barrier to competence acquisition. Furthermore, findings regarding the affective domain-limited by the low reliability of the emotional measure-suggest religiosity could act as a potential source of normative tension. These exploratory profiles serve as hypotheses for future intervention designs rather than definitive clinical mechanisms.
Gene therapy for Haemophilia B has received FDA approval, offering patients a transformative therapeutic option. However, effective communication about the benefits, risks, long-term efficacy and follow-up of gene therapy remains essential for informed decision-making. This study aimed to explore the diverse expectations, concerns and perspectives of patients with Haemophilia B, their caregivers and healthcare professionals (HCPs) regarding gene therapy and to identify strategies for improving communication. A prospective qualitative study was conducted using semi-structured interviews with male patients aged ≥12 years with moderate or severe Haemophilia B (factor level ≤ 2%), their caregivers and HCPs (physicians, nurses, social workers, advanced practice providers and pharmacists). Interviews were audio-recorded, transcribed and analysed thematically. Thirty participants were interviewed, including 15 patients (mean age, 21.1 years), caregivers and 15 HCPs across the United States. Patients and caregivers emphasised five themes: (1) current challenges; (2) hope and optimism; (3) concerns and skepticism; (4) the complex emotional challenges of decision-making and (5) preferences for transparent, patient-friendly communication. HCPs identified four complementary themes: (1) variable patient knowledge; (2) the need for transparency in discussing 'curative' language; (3) factors influencing treatment decisions (trust, prior experiences and financial concerns) and (4) strategies to improve communication (clear language, visuals and testimonials). Stakeholders view gene therapy as both promising and uncertain. Targeted educational interventions, transparent communication and patient-centred decision discussions are essential to fill knowledge gaps and support informed consent in this transformative era of treatment for Haemophilia B.
This study investigates public perception of the metaverse through a large-scale computational analysis of 52,874 English-language tweets. Leveraging sentiment analysis tools (VADER and RoBERTa) and unsupervised topic modeling (BERTopic), we categorize discourse into four thematic domains: general metaverse discussion, Meta's Horizon Worlds, metaverse-related cryptocurrency tokens, and virtual social events. Our findings reveal that 43.0% of tweets express positive sentiment, driven by enthusiasm for immersive innovation and digital transformation, while 23.6% convey skepticism, primarily concerning platform reliability, corporate dominance, and privacy. Sentiment surrounding Horizon Worlds reflects a paradox: underlying optimism is overshadowed by user frustration, with negative tweets generating disproportionately high engagement. Analysis of metaverse token discourse indicates robust investor interest, tempered by persistent concerns over market volatility and fraudulent schemes. Topic modeling further uncovers a notable narrative shift from speculative price-focused discussions toward utility-driven use cases. Virtual events (e.g., digital weddings, concerts) elicit the most positive sentiment (51.3%), with users frequently expressing emotional resonance and communal belonging, as visually reinforced by word cloud analysis. This research contributes to the literature on digital adoption and emerging technologies by mapping the evolving social discourse of the metaverse. It offers actionable insights for platform developers, investors, and educators seeking to align innovation with user expectations and provides a predictive lens for forecasting public readiness for the next generation of digital interaction.
Fibromyalgia is a chronic pain syndrome traditionally perceived as a predominantly female condition, although growing evidence suggests that this view may partly reflect diagnostic and sociocultural biases rather than true epidemiological differences. This perspective critically examines fibromyalgia in men as an underrecognized and understudied clinical entity. The authors propose an integrative conceptual framework in which the invisibility of men with fibromyalgia emerges from the interaction between sociocultural barriers to healthcare-seeking, clinician-related diagnostic bias, and heterogeneous symptom expression influenced by biological and psychosocial factors. Men may delay seeking medical care due to cultural expectations of masculinity and frequently encounter skepticism regarding symptoms such as diffuse pain, fatigue, and psychological distress. Although core symptoms are shared across sexes, men may differ in coping strategies, illness perception, and healthcare interaction. Emerging evidence also suggests possible neurophysiological and functional alterations, including small fiber pathology, reduced muscular strength, gait impairments, and psychological comorbidities. However, current evidence remains limited by small samples and methodological heterogeneity. The article argues that understanding fibromyalgia in men is essential not to establish rigid sex-specific phenotypes, but to improve diagnostic sensitivity, promote biopsychosocial and gender-sensitive care, and expand the understanding of heterogeneity within chronic pain disorders.
As generative AI (GenAI) is integrated into everyday technologies, it offers new accessibility opportunities and risks for disabled people. However, little is known about how disabled people navigate GenAI in their everyday lives, particularly how trust, privacy, and intersectional identities affect these experiences. We present findings from seven cross-disability focus groups (N=20) that explore how disabled people navigate GenAI. Our findings reveal that while GenAI supports autonomy, efficiency, and communication, it also introduces accessibility taxes and ethical dilemmas. Although participants voiced skepticism, many continued using GenAI out of necessity. Finally, we found identity-based benefits and tensions, in which GenAI preserved and validated intersecting identities, but also misrepresented and erased those identities. We frame these negotiations as a constant balancing act between access and risk, urging research to further examine how "access" is conceptualized. We offer implications for creating GenAI tools that are transparent, trustworthy, and responsive to intersectional identities.
Noise is a ubiquitous environmental pollutant, prevalent in many residential, occupational, and recreational settings, posing an unmet challenge and injustice that can cause auditory and non-auditory health effects. In Europe alone, 112 million people - more than 20% of the population - are exposed to noise levels that exceed thresholds considered unhealthy. Auditory effects of exposure, including declines in hearing function and associated underlying noise-induced injury, have been extensively documented. Affecting many millions worldwide, auditory consequences of noise exposure interfere with communication, isolating individuals from family, friends, and co-workers, and exacerbate functional declines with age. Due to an increasing number of mechanistic and epidemiological cohort studies, the past twenty years have seen a shift from skepticism that noise could affect non-auditory health, to increasing evidence for effects on cardiometabolic disease, annoyance, sleep disturbance, mental health, dementia, and children's learning. Evidence for mechanisms via cortical activation and stress hormones leading to increased vascular and cerebral inflammation and oxidative stress has increased. Efforts to protect public health are expected to intensify over the next 10 years, as evidence informs guidance and policy aimed at protecting and promoting public health.
This study examined stigma experiences among children and adolescents with Long COVID, a chronic condition marked by persistent symptoms following SARS-CoV-2 infection. We sought to characterize the nature, prevalence, and impacts of stigma on affected youth using a mixed-methods approach. A cross-sectional survey was administered to 58 caregivers of children seen at a pediatric post-COVID clinic, including the PROMIS® Parent Proxy Global Health 7 + 2 measure and nine adapted items from the Internalized Stigma of Mental Illness Inventory. Additionally, 18 parents participated in qualitative interviews analyzed using inductive thematic analysis. Stigma was widespread: over 65% of caregivers reported their child felt out of place, and nearly half reported feelings of inferiority or shame. Lower PROMIS Total T scores, reflecting worse caregiver-perceived child health, were significantly associated with experiences of alienation, discrimination, and stigma resistance. Qualitative findings identified three themes: healthcare discrimination, distrust and skepticism, and alienation and isolation, contributing to social withdrawal, emotional distress, and barriers to care. Stigma is pervasive among children with Long COVID, affecting many aspects of life including healthcare interactions and social relationships. Addressing both enacted and internalized stigma is essential to improving health and psychosocial outcomes in this population. This article shows that stigma is pervasive and multifaceted in pediatric Long COVID, shaping children's health, social participation, and emotional well-being. It adds the first mixed-methods evidence combining quantitative and qualitative data to describe stigma experiences in this population. The study identifies specific stigma domains (alienation, discrimination, social withdrawal) linked to poorer health and functioning, highlighting areas for targeted intervention. The impact is to guide future clinical, educational, and policy efforts aimed at reducing stigma and improving outcomes for affected youth.
To assess informed acceptance and perceptions of the 2025 update of the International League Against Epilepsy (ILAE) seizure classification-after participants had received a focused educational introduction to the updated classification. We analyzed anonymized live poll responses from two educational webinars dedicated to the updated seizure classification: an EpiCARE webinar held on March 26, 2026, and an ILAE e-Forum held on April 15, 2026. At the start of the webinars, participants reported their professional background and prior familiarity with the updated classification. Each webinar then included a 20-min teaching session, after which participants answered a poll question on their opinion of the updated classification. In the EpiCARE webinar, participants additionally classified 16 representative video-EEG cases using the updated classification. For the case exercise, we summarized question-level accuracy, the most frequent incorrect answer, the micro-average accuracy (total number of correct responses across all submitted answers divided by the total number of submitted answers), and the macro-average accuracy (mean of the 16 individual case accuracies). A total of 323 participants actively engaged in the two webinars (185 in the EpiCARE webinar and 138 in the ILAE e-Forum). Most respondents were specialist neurologists or pediatric neurologists/pediatricians. Before the teaching session, most respondents had heard about the updated classification but had not read the full position paper and practical guide. The main post-teaching poll was completed by 295 participants (91.3%). The vast majority of the respondents (242; 82%) rated the updated classification as feasible and useful, 17 (5.8%) as feasible but not useful, and 2 (0.7%) as not feasible, and 34 (11.5%) respondents stated they were unsure / had no opinion. In the case-based exercise on applying the updated classification, the most frequently selected answer was correct in all 16 cases. The micro-average accuracy was 74.3%, the macro-average accuracy 74.5%, and the median question-level accuracy 81.5% (range 30.4%-94.0%). When neurologists and other professionals were surveyed after structured teaching, acceptance of the 2025 ILAE seizure classification was strongly favorable. These findings suggest that education is likely to influence how the update is perceived and may help explain part of the skepticism reported in earlier surveys conducted without a standardized teaching intervention.
Although recent AI algorithms have greatly improved accuracy, there is still skepticism among clinicians about the reliability and trustworthiness of these algorithms when used in real-life situations. To address this, our research proposes a new method for trustworthy medical image segmentation, which aims to produce reliable segmentation results and reliable uncertainty estimations without imposing an excessive computational burden. One key feature of our approach is the extraction of feature maps from each decoder and their fusion based on voxel-level uncertainty to leverage multi-scale semantic information fully. We also model the probability and uncertainty of medical image segmentation problems using subjective logic theory, which quantifies the uncertainty of the backbone by modeling class probabilities as a Dirichlet distribution and calculating the distribution strength. Moreover, our framework learns to gather reliable evidence from features, leading to the final segmentation results. To further improve model performance, an uncertainty-based adaptive threshold strategy is designed based on voxel-level uncertainty. This strategy dynamically adjusts the threshold based on the model's learning state, guiding the model to focus on regions with high uncertainty to optimize segmentation results. Extensive experiments on multiple public datasets have validated the effectiveness of our approach, the code is released at https://github.com/SCUT-Ye/UGML .
Most oncology trials define superiority according to dichotomized P value thresholds, which are frequently misinterpreted. Posterior probability, however, directly estimates the probability of the hypothesis at hand. Here, we reanalyze a large collection of modern phase III trials and benchmark posterior probability versus the standard trial interpretation based on statistical significance. Outcomes from 194,129 patients were manually reconstructed from the primary end points of 230 phase III, superiority-design oncology trials. Posterior probabilities of treatment effect were then calculated across multiple priors and several effect sizes of clinical relevance, including minimum clinically important difference (MCID) defined as hazard ratio (HR) < 0.8 per ASCO criteria or HR < 0.64 per European Society of Medical Oncology (ESMO) criteria. All trials interpreted as superior using P value thresholds had probabilities >90% for achieving at least marginal benefits (HR < 1). However, only 62% of positive trials (74/120) had >90% probabilities of achieving the ASCO MCID (HR < 0.8), even under an enthusiastic prior, including 70% of trials (57/82) leading to regulatory approval. Only 30% of positive trials (36/120) had >90% probability of achieving the ESMO MCID (HR < 0.64). Conversely, 24% of trials (26/110) interpreted as not superior had >90% probability of achieving marginal benefits (HR < 1), even under a skeptical prior. Bayesian models, although often in agreement with statistical significance thresholds, add considerable unique interpretative value for a subset of phase III oncology trials. Posterior probability may provide a solution for overcoming the discrepancies between refuting the null hypothesis and detecting clinically relevant effects.
Ephaptic field research has undergone a remarkable evolution spanning over nine decades, from pioneering observations in the 1930s through a period of severe scientific skepticism in the mid-20th century to a contemporary renaissance driven by advanced computational modeling, measurement techniques, and new consciousness theories. This review traces the complete chronological development of ephaptic coupling research, examining early foundational work by Adrian, Katz and Schmitt, and Arvanitaki, the influential skepticism of Lashley's study that marginalized the field for decades, and the recent resurgence beginning in the 2000s that has led to recognition of ephaptic interactions as providing fast and direct communication throughout the brain. Contemporary research has established that weak electric fields (0.1-5 V/m) can produce measurable physiological effects and that ephaptic coupling contributes significantly to brain network complexity, memory formation, and potentially consciousness itself. Ephaptic communication, together with some form of electromagnetic field (EMF) theory of consciousness, provides a ready solution to the critical 'binding problem' that has perplexed philosophers and neuroscientists for at least the last century. This historical perspective demonstrates how scientific paradigms can shift dramatically as methodological advances allow for more sophisticated investigation of previously dismissed phenomena.
This paper examines how artificial intelligence (AI) is reshaping diagnostic decision-making in academic and clinical head and neck pathology (HNP) and argues for the redefinition of post-doctoral education in the age of AI. While AI promises enhanced diagnostic accuracy, reproducibility, and efficiency, its integration also amplifies human cognitive biases and introduces new forms of error. Here we build on the 2019 Accreditation Council for Graduate Medical Education (ACGME) pathology milestones to provide an educational framework that prepares clinicians to engage critically and responsibly with AI-assisted diagnostics. We emphasize the importance of integration of insights from decision science, cognitive psychology, and medical education with recent applications of AI in HNP, including histopathology, radiology, and multi-omics modeling. By mapping how human reasoning processes interact with algorithmic systems, we identify cognitive, ethical, and institutional vulnerabilities that arise in hybrid human-machine decision environments. Our analysis highlights that AI does not eliminate diagnostic uncertainty but redistributes it. Automation bias, overconfidence, and anchoring may distort reasoning when clinicians fail to question algorithmic outputs. To address these challenges, we outline a model of healthcare-optimization training, centered on three core skills: AI literacy, diagnostic skepticism, and ethical transparency. As such, reframing decision-making education in HNP requires moving beyond technical training toward reflective, ethically grounded practice. Embedding AI literacy and critical reasoning within competency-based curricula and institutional governance can ensure that AI enhances rather than replaces human judgment-fostering safer, more equitable, and patient-centered diagnostic care.
This patient perspective article advances observation as an intentional, rigorous form of clinical care rather than a passive absence of intervention. The recommendations arise from the lived experience of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), informed by clinical training as a mobile equine veterinarian. Over a nine-year diagnostic course, early clinical curiosity gave way to prolonged skepticism in the context of normal examinations and laboratory findings, ultimately shifting responsibility for daily functioning and symptom interpretation onto the patient. Across repeated encounters, subtle but consistent indicators of impaired energy regulation and exertional intolerance were present yet remained clinically unintegrated. When viewed longitudinally, these findings revealed a coherent physiological pattern that was not apparent at any single time point. Modern medical training emphasizes action. However complex, relapsing, and poorly understood conditions often demand sustained clinical attention before diagnostic clarity emerges. In the absence of immediate abnormalities, discomfort with uncertainty may prompt premature intervention or disengagement, eroding trust and obscuring evolving signals. Structured observation offers an alternative. As a clinical strategy, it preserves diagnostic curiosity, strengthens the physician-patient relationship, and allows for the observation of physiology without confounding influences. Such observation can yield meaningful insight and guide precise, compassionate care.
This review addresses the nutritional composition, health benefits, and claim conditions of aquaculture fish, focusing on gilthead sea bream (Sparus aurata) and European sea bass (Dicentrarchus labrax). Both species provide high-quality proteins, essential amino acids, and favorable lipid profiles, particularly long-chain omega-3 fatty acids, alongside minerals such as phosphorus and selenium, which meet EU criteria for several authorized nutrition and health claims. Evidence demonstrates that regular consumption supports cardiovascular, cognitive, and visual health, reduces inflammation, and contributes to better pregnancy and early childhood outcomes. Consumer skepticism toward aquaculture persists, often driven by perceptions of reduced nutritional quality, despite evidence that farmed fish provide nutritionally valuable proteins and beneficial lipids. Nevertheless, both species consistently meet the requirements for multiple nutrition and health claims, particularly those related to protein, omega-3 fatty acids, and selected minerals, allowing their effective use in labeling and consumer communication. Clear, evidence-based labeling of such claims is crucial to enhance acceptance and promote farmed fish as safe, sustainable, and health-promoting dietary choices.
Artificial intelligence-based decision support systems have been suggested as possible aids for decision makers in emergency care. To balance patient safety, cost, efficiency, and professional integrity, we need to understand the views and arguments health professionals have for and against the implementation of such systems. The current study aimed to explore emergency primary care personnel's perspectives on artificial intelligence-based decision support systems in emergencies in the municipality. This study used a qualitative design with online, semistructured interviews with 12 primary emergency health care personnel. A purposive sampling strategy was used, and participants were recruited either from EPC center or municipal healthcare institutions receiving services from the EPCRU. The data were analyzed following thematic analysis. Four main themes were identified, namely, "Human need, clinical evaluations," "Balancing skepticism and confidence," "Digital sparring partner and alternative hypotheses," and "Health personnel's role in procurement and development." The participants emphasized a need for human and clinical assessments to detect illness and initiate appropriate actions. Aspects of skepticism and confidence were also discussed. However, they perceived that AI-based decision support systems could be ideal digital sparring partners. Moreover, all the participants underlined the importance of involving intended users when developing and implementing decision support systems. This study emphasizes the essential role of health personnel in decision-making processes in emergency primary care, as well as in the implementation processes of AI in these services. AI is suggested as a supportive tool that provides safe and trustworthy solutions. These aspects are useful for managers and other decision makers in the transformation of health services for the future.
Diabetes represents a major public health burden in the Middle East and North Africa (MENA) region. However, limited research has explored patients' lived experiences and perspectives on diabetes management, particularly nutrition, within the Arab region. This study examined factors influencing adherence to dietitian-led counseling among adults with diabetes in the United Arab Emirates (UAE), with a focus on social support, outcome expectations, and patient suggestions to enhance motivation for dietary adherence. A qualitative study using semi-structured individual interviews was conducted with 44 adults with diabetes attending a diabetes management clinic in the UAE. Audio-recorded interviews were transcribed and analyzed using NVivo-12. Inductive thematic analysis guided by Social Cognitive Theory (SCT) was used to identify key concepts related to outcome expectations and social support. Participants' suggestions for improving motivation to seek nutrition advice from dietitians were also explored. Four main themes emerged from the analysis: (1) positive expectations, (2) negative expectations, (3) enablers and motivators, and (4) participant suggestions. Positive outcome expectations, including improved health, better glycemic control, and weight management, motivated adherence to dietary advice. Social support from family members, friends, and healthcare professionals facilitated adherence and attendance at dietitian consultations. In contrast, misinformation, low awareness of the role of dietitians in diabetes management, and skepticism toward nutrition advice acted as barriers. Participants encouraged others with diabetes to consult dietitians and adopt healthier lifestyle behaviors. Enhancing culturally appropriate social support and addressing informational barriers may improve dietary adherence, increase engagement in dietitian-led counseling, and improve nutrition-related diabetes outcomes.
Recent reports indicate a concerning decline in routine childhood vaccination rates globally. Parental engagement with health information is critical in shaping vaccine acceptance amid rising skepticism and shifting sociopolitical dynamics. In this study, we investigated how Canadian parents engaged with information to decide on COVID-19 vaccination for their children. Using an exploratory qualitative design, we conducted semi-structured interviews with 48 parents between April and August 2022. Data were analyzed thematically and organized around McKenzie's model of information practices. Our findings revealed that parental engagement is a dynamic process shaped by emotional, social, and informational factors. While parents sought evidence-based information, they also employed sophisticated strategies to navigate uncertainty. Novel insights include the use of source triangulation to build epistemic authority, the strategic use of information avoidance to mitigate social stigma, and a transition toward cognitive closure once decisions were finalized. Notably, most parents reached a "case closed" state before pediatric vaccines were authorized, relying on trusted sources (i.e. schools and pediatricians) as proxies and their experiential lived evidence for decision-making. To improve communication about childhood vaccination, including in future health crises, we recommend a proactive approach that recognizes the finite life cycle of information engagement. Public health strategies can prioritize early messaging before cognitive closure occurs and leverage distributed trust by using health-care providers and schools as primary information proxies. These findings offer a blueprint for navigating the psycho-social complexities of health communication.
Despite not achieving statistical significance, the JAVELIN Renal 101 trial indicated a potentially clinically relevant effect size (hazard ratio [HR], 0.88; 95% confidence interval, 0.75 to 1.04) on overall survival (OS) favoring avelumab plus axitinib over sunitinib for advanced renal cell carcinoma (aRCC). To better interpret these findings, we performed a Bayesian evaluation. We reanalyzed individual participant data from the JAVELIN Renal 101 trial using a Bayesian framework. Prior distributions were specified for varying levels of enthusiasm and skepticism for avelumab plus axitinib, and a prior from a meta-analysis of similar trials. The posterior probability of any OS benefit with avelumab plus axitinib, Pr(HR < 1.0), and of benefit exceeding the minimal clinically important difference (MCID; HR = 0.75), Pr(HR < MCID), were estimated using Bayesian Cox models. Bayesian hierarchical models evaluated treatment effect heterogeneity across International Metastatic Renal Cell Carcinoma Database Consortium risk groups and programmed death-ligand 1 (PD-L1) status. Regardless of the prior assumptions used, Pr(HR < 1.0) was consistently high (93.0% to 95.5%). However, Pr(HR < MCID) was low (1.0% to 3.8%). Results were similar when the prior was informed by pooled data from similar trials. In subgroup analyses, Pr(HR < MCID) varied by risk group: 63.4% for poor-risk, 34.9% for favorable-risk, and 0.9% for intermediate-risk aRCC. This probability was low regardless of PD-L1 status. This exploratory Bayesian reanalysis complements the interpretation of the JAVELIN Renal 101 trial and offers a probabilistic perspective beyond a dichotomous (i.e., significant/nonsignificant) interpretation.
Over the past decade, the management of papillary thyroid carcinoma (PTC) has become increasingly individualized, with less aggressive approaches recommended for low-risk diseases. However, the real-world implementation of these recommendations remains limited. This study aims to assess real-world management patterns and therapeutic preferences regarding surgical extent, radioactive iodine (RAI) use, and thyrotropin (TSH) levels in low- and low-to-intermediate-risk PTC through a nationwide survey. A nationwide web-based survey was conducted among members of the Greek Endocrine Society (25% response rate) between November 2023 and April 2024. The questionnaire comprised demographic items, 12 clinical scenarios, and a final section exploring general reasons for nonadherence to clinical guidelines; this report focuses on eight scenarios related to low- and low-to-intermediate-risk papillary thyroid carcinoma. For an 18 mm intrathyroidal low-risk PTC, 67.7% of respondents recommended total thyroidectomy, while 51.8% favored adjuvant RAI. When reclassified as low-to-intermediate risk, 92.5% endorsed RAI, often at higher doses (70 mCi), particularly among more experienced and those practicing in large cities. TSH suppression targets in case of excellent response varied: nearly half selected 0.5-2.0 μU/mL for low-risk PTC, but most favored tighter suppression (0.1-0.5 μU/mL) in low-to-intermediate-risk scenarios. Senior endocrinologists prefer traditional approaches. Barriers to guideline adherence included limited access to molecular and ultrasonography testing, a shortage of experienced surgeons outside major centers, and skepticism regarding guideline safety. Our findings underscore persistent practice variation driven by professional experience and local healthcare infrastructure, underscoring the need for targeted local implementation strategies, particularly outside major urban centers.