Search Results (2,462)

Metacognitive monitoring plays a crucial role in self-regulated learning, as accurate monitoring enables effective control, which in turn impacts learning outcomes. Most studies on metacognitive monitoring have focused on learners’ monitoring abilities when they are explicitly prompted to monitor. However, in real-world educational settings, learners are more often prompted to control their learning, such as deciding whether to allocate additional time to a learning target. The primary goal of this study was to investigate whether retrieval is engaged when learners are explicitly prompted to control their learning processes by making study decisions. To address this, three experiments were conducted. In Experiment 1, participants (N = 39) studied 70 Swahili–English word pairs in a learning task. Each trial displayed a word pair for 8 s, followed by a distractor task (a two-digit mental addition) and a study decision intervention (choose “Study Again” or “Next”). After learning, participants provided a global judgment of learning (JOL), estimating their overall recall accuracy. Finally, they completed a cued recall test (Swahili cue). Responses were scored for accuracy and analyzed alongside study decisions, study decision reaction time (RT), and metacognitive judgments. Reaction times (RTs) for study decisions correlated positively with test accuracy, global judgments of learning (JOLs), and judgments of confidence (JOCs), suggesting retrieval likely underlies these decisions. Experiment 2 (N = 74, between-subjects) compared memory performance and intervention response time between single-study, restudy, retrieval (explicit recall prompt), and study decision (study decision prompt) groups to have better control over study time and cognitive processes. Although no significant group differences in test accuracy emerged, the retrieval group took longer to respond than the study decision group. Within-subject analyses revealed similar recall accuracy patterns: participants recalled successfully retrieved or “no restudy” items better than failed-retrieval or “restudy” items, implying shared cognitive processes underlying retrieval and study decision interventions. Experiment 3 (N = 74, within-subject, three learning conditions: single-study, retrieval, and study decision) replicated these findings, with no condition effects on test accuracy but longer RT for retrieval than study decisions. The similar recall accuracy patterns between retrieval and study decision interventions further supported shared cognitive processes underlying both tasks. Self-reports across experiments confirmed retrieval engagement in both retrieval and study decision interventions. Collectively, the results suggest that retrieval likely supports study decisions but may occur less frequently or less deeply than under explicit monitoring prompts. Additionally, this study explored objective, online measures to detect retrieval-based metacognitive monitoring. Full article

Background/Objective: The use of artificial intelligence to assist in medical applications is an emerging area of investigation and discussion. The researchers studied whether there was a difference between homeopathy guidance provided by artificial intelligence (AI) (automated) and live professional practitioners (live) for acute illnesses. Additionally, the study explored the practical challenges associated with validating AI tools used for homeopathy and sought to generate insights on the potential value and limitations of these tools in the management of acute health complaints. Method: Randomly selected cases at a homeopathy teaching clinic (n = 100) were entered into a commercially available homeopathic remedy finder to investigate the consistency between automated and live recommendations. Client symptoms, medical disclaimers, remedies, and posology were compared. The findings of this study show that the purpose-built homeopathic remedy finder is not a one-to-one replacement for a live practitioner. Result: In the 100 cases compared, the automated online remedy finder provided between 1 and 20 prioritized remedy recommendations for each complaint, leaving the user to make the final remedy decision based on how well their characteristic symptoms were covered by each potential remedy. The live practitioner-recommended remedy was included somewhere among the auto-mated results in 59% of the cases, appeared in the top three results in 37% of the cases, and was a top remedy match in 17% of the cases. There was no guidance for managing remedy responses found in live clinical settings. Conclusion: This study also highlights the challenge and importance of validating AI remedy recommendations against real cases. The automated remedy finder used covered 74 acute complaints. The live cases from the teaching clinic included 22 of the 74 complaints. Full article

The rapid growth of live e-commerce, a sector valued at over USD 100 billion worldwide, demonstrates its transformative impact on the retail industry, especially in markets like China, where platforms such as Taobao Live and TikTok Shop have markedly altered consumer interaction. This transition is further expedited by Netflix-like entertainment marketing methods, which have demonstrated the capacity to enhance consumer retention by as much as 40%. As organizations adjust to this evolving landscape, it is essential to optimize supply chain strategies to align with these dynamic, consumer-centric environments. This paper examines the complexity of decision-making in live e-commerce supply chains, specifically regarding Netflix-inspired marketing strategies. The primary aim of this study is to design a game-theoretic framework that examines the interactions between producers and online celebrity retailers (OCRs) across different power dynamics. As live commerce integrates digital retail with immersive experiences, businesses must optimize pricing, quality, and marketing strategies in real-time. We present engagement-driven marketing as a strategic variable and incorporate consumer regret and switching costs into the demand function. To illustrate practical trade-offs in strategy, we incorporate a multi-criteria decision-making (MCDM) layer with AHP-TOPSIS, assessing profit, consumer surplus, engagement score, and channel efficiency. The experiment results indicate that Netflix-style marketing markedly increases demand and profit in retailer-led frameworks, whereas centralized tactics enhance overall channel performance. TOPSIS analysis prioritizes high-effort, high-engagement methods, whereas the Stackelberg experiment underscores the influence of power dynamics on profit distribution. This study presents an innovative integrative decision-making methodology for enhancing live-streaming commerce tactics in data-driven and consumer-focused markets. Full article

This study investigates the effectiveness of contact and online biology teaching by assessing student performance and gathering perceptions from students, teachers, and parents. Conducted in autumn 2021 with 3035 students, 124 biology teachers, and 719 parents, this study combined post-instruction assessments of student performance in knowledge reproduction and conceptual understanding with questionnaires examining perceptions of contact and online biology teaching effectiveness across students, teachers, and parents. To investigate how various teaching-related factors influence perceived understanding of biological content, we applied a CHAID-based decision tree model to questionnaire responses from students, teachers, and parents. Results indicated that students value engaging, flexible instruction, sufficient time to complete tasks and support for independent thinking. Teachers emphasized their satisfaction with teaching and efforts to support student understanding. In contact lessons, students preferred problem-solving, teacher guidance, and a stimulating environment. In online learning, they preferred low-stress, interesting lessons with room for independent work. Parents emphasized satisfaction with their child’s learning and the importance of a focused, stimulating environment. This comparative analysis highlights the need for student-centered, research-based biology teaching in both formats, supported by teachers and delivered in a motivating environment. The results offer practical insights for improving biology instruction in different teaching modalities. Full article

Background: Point-of-care ultrasound (POCUS) is gaining recognition as a valuable diagnostic tool in various fields of medicine, including pediatrics. Its application at the point of care enables real-time clinical decision-making, which is particularly advantageous in pediatric settings. Although global interest in POCUS is growing, many European countries—including Poland—still lack formal training programs for POCUS at both the undergraduate and postgraduate levels. Nevertheless, the number of pediatricians incorporating POCUS into their daily clinical practice in Poland is increasing. However, the extent of its use and perceived value among pediatricians remains largely unknown. This study aimed to evaluate the current level of POCUS utilization in pediatric care in Poland, focusing on pediatricians’ self-assessed competencies, perceptions of its clinical utility, and key barriers to its implementation in daily practice. Methods: This cross-sectional study was conducted between July and August 2024 using an anonymous online survey distributed to pediatricians throughout Poland via national professional networks, with a response rate of 7.3%. Categorical variables were analyzed using the chi-square test of independence to assess the associations between key variables. Quantitative data were analyzed using descriptive statistics, and qualitative data from open-ended responses were subjected to a thematic analysis. Results: A total of 210 pediatricians responded. Among them, 149 (71%) reported access to ultrasound equipment at their workplace, and 89 (42.4%) reported having participated in some form of POCUS training. Only 46 respondents (21.9%) reported frequently using POCUS in their clinical routine. The self-assessed POCUS competence was rated as low or very low by 136 respondents (64.8%). While POCUS was generally perceived as a helpful tool in facilitating and accelerating clinical decisions, the main barriers to implementation were a lack of formal training and limited institutional support. Conclusions: Although POCUS is perceived as clinically valuable by the surveyed pediatricians in Poland, its routine use remains limited due to training and systemic barriers. Future efforts should prioritize the development of a validated, competency-based training framework and the implementation of a larger, representative national study to guide the structured integration of POCUS into pediatric care. Full article

Background: Cochlear implantation (CI) in pediatric patients with cochlear nerve deficiencies (CND) remains controversial due to a highly variable clinical population, lack of evidence-based guidelines, and mixed research findings. This study assessed current clinical perspectives and practices regarding CI candidacy in children with CND among hearing healthcare professionals in the USA. Methods: An anonymous 19-question online survey was distributed to CI clinicians nationwide. The survey assessed professional background, experience with aplasia and hypoplasia, and perspectives on CI versus auditory brainstem implant (ABI) candidacy, including imaging practices and outcome expectations. Both multiple-choice and open-ended responses were analyzed to identify trends and reasoning. Results: Seventy-two responses were analyzed. Most clinicians supported CI for hypoplasia (60.2%) and, to a lesser extent, for aplasia (41.7%), with audiologists more likely than neurotologists to favor CI. Respondents cited lower risk, accessibility, and the potential for benefit as reasons to attempt CI before ABI. However, many emphasized a case-by-case approach, incorporating imaging, electrophysiological testing, and family counseling. Only 22.2% considered structural factors the best predictors of CI success. Conclusions: Overall, hearing health professionals in the USA tend to favor CI as a first-line option, while acknowledging the limitations of current diagnostic tools and the importance of individualized, multidisciplinary decision-making in CI candidacy for children with CND. Findings reveal a high variability in clinical perspectives on CI implantation for pediatric aplasia and hypoplasia and a lack of clinical consensus, highlighting the need for more standardized assessment and imaging protocols to provide greater consistency across centers and enable the development of evidence-based guidelines. Full article

With the popularization of social media, information related to public health events has seen explosive growth online, making it essential to accurately identify informative tweets with decision-making and management value for public health emergency response and risk monitoring. However, existing methods often suffer performance degradation during cross-event transfer due to differences in data distribution, and research specifically targeting public health events remains limited. To address this, we propose the Label Confusion Domain Adversarial Network (LCDAN), which innovatively integrates label confusion with domain adaptation to enhance the detection of informative tweets across different public health events. First, LCDAN employs an adversarial domain adaptation model to learn cross-domain feature representation. Second, it dynamically evaluates the importance of different source domain samples to the target domain through label confusion to optimize the migration effect. Experiments were conducted on datasets related to COVID-19, Ebola disease, and Middle East Respiratory Syndrome public health events. The results demonstrate that LCDAN significantly outperforms existing methods across all tasks. This research provides an effective tool for information detection during public health emergencies, with substantial theoretical and practical implications. Full article

The modified Rankin Scale (mRS) is a widely used outcome measure for assessing disability in stroke care; however, its administration is often affected by subjectivity and variability, leading to poor inter-rater reliability and inconsistent scoring. Originally designed for hospital discharge evaluations, the mRS has evolved into an outcome tool for disability assessment and clinical decision-making. Inconsistencies persist due to a lack of standardization and cognitive biases during its use. This paper presents design principles for creating a standardized clinical assessment tool (CAT) for the mRS, grounded in human–computer interaction (HCI) and cognitive engineering principles. Design principles were informed in part by an anonymous online survey conducted with clinicians across Canada to gain insights into current administration practices, opinions, and challenges of the mRS. The proposed design principles aim to reduce cognitive load, improve inter-rater reliability, and streamline the administration process of the mRS. By focusing on usability and standardization, the design principles seek to enhance scoring consistency and improve the overall reliability of clinical outcomes in stroke care and research. Developing a standardized CAT for the mRS represents a significant step toward improving the accuracy and consistency of stroke disability assessments. Future work will focus on real-world validation with healthcare stakeholders and exploring self-completed mRS assessments to further refine the tool. Full article

As ad-supported subscription models proliferate across over-the-top (OTT) media platforms, understanding the psychological mechanisms and perceptual factors that underlie consumers’ transition decisions becomes increasingly consequential. This study integrates the Uses and Gratifications framework with a contemporary motivation-based perspective to examine how users’ media consumption motivations and advertising attitudes predict intentions to adopt ad-supported OTT plans. Data were collected via a nationally representative online survey in South Korea (N = 813). The sample included both premium subscribers (n = 708) and non-subscribers (n = 105). The findings reveal distinct segmentation in decision-making patterns. Among premium subscribers, switching intentions were predominantly driven by intrinsic motivations—particularly identity alignment with content—and by the perceived informational value of advertisements. These individuals are more likely to consider ad-supported plans when ad content is personally relevant and cognitively enriching. Conversely, non-subscribers exhibited greater sensitivity to extrinsic cues such as the entertainment value of ads and the presence of tangible incentives (e.g., discounts), suggesting a hedonic-reward orientation. By advancing a dual-pathway explanatory model, this study contributes to the theoretical discourse on digital subscription behavior and offers actionable insights for OTT service providers. The results underscore the necessity of segment-specific advertising strategies: premium subscribers may be engaged through informative and identity-consistent advertising, while non-subscribers respond more favorably to enjoyable and benefit-laden ad experiences. These insights inform platform monetization efforts amid the evolving dynamics of consumer attention and subscription fatigue. Full article

In the attention-driven environment of online video platforms, understanding the factors that influence content selection and channel subscriptions is crucial for creators, marketers, and platform managers. This study investigates how thumbnails, view counts, video length, genre, and the number of advertisements affect user decision-making on YouTube. Grounded in random utility theory and reference-dependent preference theory, this study conducted a choice experiment with 525 respondents and employed a combined model of rank-ordered and binary logit methods to analyze viewing and subscription behaviors. The results indicate a significant preference for thumbnails with subtitles and shorter videos. Notably, we found evidence of reference-dependent effects, whereby a higher-than-expected number of ads decreased viewing probability, while a lower-than-expected number significantly increased subscription probability. This study advances our understanding of the factors that influence user behavior on social media, specifically in terms of viewing and subscribing, and empirically supports prospect theory in the online advertising market. Our findings offer both theoretical and practical insights into optimizing video content and monetization strategies in competitive social media markets. Full article

High penetration of photovoltaic (PV) generation presents new challenges for voltage regulation in distribution networks (DNs), primarily due to output intermittency and constrained reactive power capabilities. This paper introduces a distributed voltage control method leveraging reactive power compensation from PV inverters. Instead of relying on centralized computation, the proposed method allows each inverter to make local decisions using real-time voltage measurements and delayed communication with neighboring PV nodes. To account for practical asynchronous communication and feedback delay, a Distributed Online Primal–Dual Push–Sum (DOPP) algorithm that integrates a fixed-step delay model into the push–sum coordination framework is developed. Through extensive case studies on a modified IEEE 123-bus system, it has been demonstrated that the proposed method maintains robust performance under both static and dynamic scenarios, even in the presence of fixed feedback delays. Specifically, in static scenarios, the proposed strategy rapidly eliminates voltage violations within 50–100 iterations, effectively regulating all nodal voltages into the acceptable range of [0.95, 1.05] p.u. even under feedback delays with a delay step of 10. In dynamic scenarios, the proposed strategy ensures 100% voltage compliance across all nodes, demonstrating superior voltage regulation and reactive power coordination performance over conventional droop and incremental control approaches. Full article

This study proposed an online early lameness detection method for dairy cow health management to overcome the inability of wearable sensor-based methods for online detection and low sensitivity to early lameness. Wearable IMU sensors collected acceleration data in stationary and moving states; a threshold discrimination module using variance of motion-direction acceleration was designed to distinguish states within 2 s, enabling rapid data screening. For moving-state windowed data, the InceptionTime network was modified with YOLOConv1D and SeparableConv1D modules plus Dropout, which significantly reduced model parameters and helped mitigate overfitting risk, enhancing generalization on the test set. Typical gait features were fused with deep features automatically learned by the network, enabling accurate discrimination among healthy, mild (early) lameness, and severe lameness. Results showed that the online detection model achieved 80.6% dairy cow health status detection accuracy with 0.8 ms single-decision latency. The recall and F1 score for lameness, including early and severe cases, reached 89.11% and 88.93%, demonstrating potential for early and progressive lameness detection. This study improves lameness detection efficiency and validates the feasibility and practical value of wearable sensor-based gait analysis for dairy cow health management, providing new approaches and technical support for monitoring and early intervention on large-scale farms. Full article

Seafood processing byproducts (SB) such as bones and skin can be safely used as food ingredients to increase profitability for the seafood sector and provide nutritional value. An online survey of 716 US adult seafood consumers was conducted to explore SB trial intent, responsiveness to health and safety information, and associated elicited emotions (nine-point Likert scale). Consumers’ SB-elicited emotions were defined as those changing in reported intensity (from a baseline condition) after the delivery of SB-related information (dependent t-tests). As criteria for practical significance, a raw mean difference of >0.2 units was used, and Cohen’s d values were used to classify effect sizes as small, medium, or large. Differences in willingness-to-try, responsiveness to safety and health information, and SB-elicited emotions were found based on self-reported gender and race, with males and Hispanics expressing more openness to SB consumption. SB-elicited emotions were then used to model consumers’ willingness-to-try foods containing SB via logistic regression modeling. Traditional stepwise variable selection was compared to variable selection using raw mean difference > 0.2 units and Cohen’s d > 0.50 constraints for SB-elicited emotions. Resulting models indicated that extrinsic information considered at the point of decision-making determined which emotions were relevant to the response. These new approaches yielded models with increased Akaike Information Criterion (AIC) values (lower values indicate better model fit) but could provide simpler and more practically meaningful models for understanding which emotions drive consumption decisions. Full article

Background/Objectives: Patients with an ileoanal pouch change their diet to manage their symptoms and will often resort to the internet for nutrition advice. Currently, no evidence-based dietary guidelines exist to inform online resources. Hence, this study aims to assess the quality of online nutrition information directed towards patients with an ileoanal pouch. Methods: A systematic Google search was conducted to identify consumer websites including information on nutrition for those with ileoanal pouches. Quality was assessed using the DISCERN instrument, and the readability of written content was assessed using the Flesch–Kincaid score. A summative content analysis was used to identify the frequency of particular topics. Websites were also assessed against standards from the National Institute for Health and Care Excellence (NICE) framework for shared decision-making support tools. Results: A total of 12 websites met the inclusion criteria. Mean total DISCERN scores across all websites are 33 out of 75, indicating that overall, the websites were of poor quality. The mean Flesch–Kincaid score was 57 out of 100, or “fairly difficult” in terms of readability. The main themes according to the content analysis were “general dietary advice for pouch”, “dietary strategies for symptom management”, “addressing risks associated with having a pouch”, and “optimisation of nutritional intake”. Overall, websites did not meet the standards for shared decision-making. Conclusions: Online nutrition information for patients with an ileoanal pouch is of poor quality and difficult to understand. There is a need for higher quality online resources for these patients, ideally co-produced with a multidisciplinary team and patient, to provide patients with good quality, understandable, and accessible nutrition information. Full article

Online reviews increasingly shape experiential travel decisions. This study investigates how structural and linguistic features of user-generated content influence peer endorsement in wine tourism. While prior research has explored review valence and credibility, limited attention has been paid to how micro-level textual and identity cues affect social approval metrics such as likes. Grounded in the Elaboration Likelihood Model, the analysis draws on 7942 TripAdvisor reviews using automated web scraping, readability metrics, and multivariate regression. Results indicate that location disclosure significantly increases likes, while higher textual complexity reduces endorsement. Title length and reviewer contributions function as peripheral cues, with an interaction between complexity and title length compounding cognitive effort. Findings refine dual-process persuasion theory and offer practical insights for content optimization in post-pandemic tourism engagement. Full article