Search Results (1,648)

Large Language Models (LLMs) are reshaping recommendation systems through enhanced language understanding, reasoning, and integration with structured data. This systematic review analyzes 88 studies published between 2023 and 2025, categorized into three thematic areas: data processing, technical identification, and LLM-based recommendation architectures. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the review highlights key trends such as the use of knowledge graphs, Retrieval-Augmented Generation (RAG), domain-specific fine-tuning, and robustness improvements. Findings reveal that while LLMs significantly advance semantic reasoning and personalization, challenges remain in hallucination mitigation, fairness, and domain adaptation. Technical innovations, including graph-augmented retrieval methods and human-in-the-loop validation, show promise in addressing these limitations. The review also considers the broader macroeconomic implications associated with the deployment of LLM-based systems, particularly as they relate to scalability, labor dynamics, and resource-intensive implementation in real-world recommendation contexts, emphasizing both productivity gains and potential labor market shifts. This work provides a structured overview of current methods and outlines future directions for developing reliable and efficient LLM-based recommendation systems. Full article

Sjögren’s Disease (SjD) is an autoimmune disorder characterized by sicca symptoms arising from impaired salivary and lacrimal gland function and accompanying extraglandular involvement. SjD is recognized as an illness of female dominance for which the 2002 American–European Consensus Group Classification Criteria and the American College of Rheumatology/European Alliance of Associations for Rheumatology 2016 classification criteria are utilized for inclusion in clinical trials, and treatment recommendations from countries belonging to the American College of Rheumatology or the European Alliance of Associations for Rheumatology are globally recognized. It is presumed that there are geographical differences among female sufferers, and unique diagnostic criteria and recommendations are used in clinical practice in Japan. In addition to the items included in the classification criteria, several methods to measure saliva secretion, serum biomarkers, and artificial intelligence tools have recently been reported to be useful for the assessment of SjD. While symptomatic therapies including tear drops, artificial saliva, and muscarinic agonists are still the mainstay for treating SjD, several kinds of molecular targeted drugs, such as biological drugs and Janus kinase inhibitors, that are expected to improve the prognosis of SjD have been tested in recent clinical trials. Full article

Objectives: In view of a lack of evidence on the subject, we aimed to perform a scoping review to understand the impact of health education among people attending mass gatherings. Methods: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Guidelines. PubMed, EMBASE, Scopus, and Cochrane Library were searched from inception to March 2025 to identify eligible studies. Observational and interventional studies that reported the impact of health education on any health-related outcome among those attending a mass gathering were considered. A narrative synthesis of review results was performed to gather evidence. Recommendations were framed in the context of this evidence. Results: Of the 1731 records, only 17 studies met the inclusion criteria. These included cross-sectional (n = 10), pre-post design (n = 3), quasi-experimental (n = 2), randomized controlled trial (n = 1), and ethnographic (n = 1) studies. These studies involved participants attending hajj, umrah, and basketball events. The current evidence on health education in mass gatherings is highly varied in its objectives, intervention strategy, educational plan, mode of delivery, design, and reported outcomes. Most studies agreed that health education should be initiated by the country of origin and continued throughout the event. It is recommended that this education should be tailored to patient needs based on age, medical condition, and other personal factors, and given in the local language for better acceptability. Such sources can be provided in various forms, either online or offline, as per the participant’s convenience. Conclusions: The current evidence on the effectiveness of health education during mass gatherings, particularly in pilgrimage settings, is varied and inconsistent. Participant-tailored health education should be provided, preferably in the local language, through convenient formats. Full article

The Statistics Anxiety Rating Scale (STARS) is a 51-item scale commonly used to measure college students’ anxiety regarding statistics. To date, however, limited empirical research exists that examines statistics anxiety among ethnically diverse or first-generation graduate students. We examined the factor structure and reliability of STARS scores in a diverse sample of students enrolled in graduate courses at a Minority-Serving Institution (n = 194). To provide guidance on assessing dimensionality in small college samples, we compared the performance of best-practice factor analysis techniques: confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM). We found modest support for the original six-factor structure using CFA, but ESEM and BSEM analyses suggested that a four-factor model best captures the dimensions of the STARS instrument within the context of graduate-level statistics courses. To enhance scale efficiency and reduce respondent fatigue, we also tested and found support for a reduced 25-item version of the four-factor STARS scale. The four-factor STARS scale produced constructs representing task and process anxiety, social support avoidance, perceived lack of utility, and mathematical self-efficacy. These findings extend the validity and reliability evidence of the STARS inventory to include diverse graduate student populations. Accordingly, our findings contribute to the advancement of data science education and provide recommendations for measuring statistics anxiety at the graduate level and for assessing construct validity of psychometric instruments in small or hard-to-survey populations. Full article

Multi-behavior sequential recommendation (MBSRec) is a form of sequential recommendation. It leverages users’ historical interaction behavior types to better predict their next actions. This approach fits real-world scenarios better than traditional models do. With the rise of the transformer model, attention mechanisms are widely used in recommendation algorithms. However, they suffer from low-pass filtering, and the simple learnable positional encodings in existing models offer limited performance gains. To address these problems, we introduce the context-aware multi-behavior sequential recommendation model (CAMBSRec). It separately encodes items and behavior types, replaces traditional positional encoding with context-similarity positional encoding, and applies the discrete Fourier transform to separate the high and low frequency components and enhance the high frequency components, countering the low-pass filtering effect. Experiments on three public datasets show that CAMBSRec performs better than five baseline models, demonstrating its advantages in terms of recommendation performance. Full article

Microplastics are pervasive environmental pollutants that pose risks to human health through ingestion and inhalation. This review synthesizes current practices to reduce exposure and toxicity by examining major exposure routes and dietary interventions. More than 130 papers were analyzed to achieve this aim. The findings show that microplastics contaminate a wide range of food products, with particular concern over seafood, drinking water, plastic-packaged foods, paper cups, and tea filter bags. Inhalation exposure is mainly linked to indoor air quality and smoking, while dermal contact poses minimal risk, though the release of additives from plastics onto the skin remains an area of concern. Recommended strategies to reduce dietary exposure include consuming only muscle parts of seafood, moderating intake of high-risk items like anchovies and mollusks, limiting canned seafood liquids, and purging mussels in clean water before consumption. Avoiding plastic containers, especially for hot food or microwaving, using wooden cutting boards, paper tea bags, and opting for tap or filtered water over bottled water are also advised. To mitigate inhalation exposure, the use of air filters with HyperHEPA systems, improved ventilation, regular vacuuming, and the reduction of smoking are recommended. While antioxidant supplementation shows potential in reducing microplastic toxicity, further research is needed to confirm its effectiveness. This review provides practical, evidence-based recommendations for minimizing daily microplastic exposure. Full article

Background: Depression that is resistant to two or more adequate treatment trials—treatment-resistant depression (TRD)—is a prevalent clinical challenge. Although psychotherapies have been recommended by clinical guidelines as an alternative or adjunctive treatment strategy, the effectiveness of psychotherapy in individuals with TRD has not yet been evaluated through meta-analytic methods, primarily due to a limited number of trials. This highlights the necessity of personalized research targeting this specific population. This systematic review and meta-analysis aimed to summarize the evidence on psychotherapy in treating TRD. Methods: A systematic search was conducted following the Guidelines from Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Articles were included if they quantitatively examined the efficacy of psychotherapy on depression symptoms in individuals diagnosed with depression who had not responded to at least two prior treatments (i.e., pharmacotherapy and/or psychotherapy). Results: A total of 12 studies were included. The quality of evidence was evaluated as being globally moderate. When pooling all psychotherapies, a small-to-moderate, but significant, effect on depressive symptoms was observed compared to the control group (SMD = −0.49, CI = −0.63; −0.34). The observed effect remained unchanged after removing the outlier (SMD = −0.47, CI = −0.62; −0.32). When examining depressive symptoms by type of psychotherapy, Mindfulness-Based Cognitive Therapy (SMD = −0.51, CI = −0.76; −0.25), Cognitive Behavioral Therapy (SMD = −0.53, CI = −0.92; −0.14), and Cognitive Therapy (SMD = −0.51, CI = −1.01; −0.01) showed a moderately significant effect on depressive symptoms compared to the control group. Conclusions: Although this potentially represents the first meta-analysis in this area, the number of studies specifically addressing this complex population remains limited, and the existing literature is still in its early stages. Research focusing on TRD is notably sparse compared to the broader body of work on depression without treatment resistance. Consequently, it was not possible to conduct meta-analyses by type of psychotherapy across all treatment modalities and by type of control group. Due to several study limitations, there is currently limited evidence available about the effectiveness of psychotherapy for TRD, and further trials are needed. Beyond the treatments usually offered for depression, it is possible that TRD requires a personalized medicine approach. Full article

Sustainable education requires addressing the challenges posed by digital transformation, including technostress among university students. This study evaluates technostress levels in higher education through the validation of the TS4US scale and its implications for sustainable learning environments. A cross-sectional study was conducted with 328 university students from four districts in Lima, Peru, using an online survey to measure technostress. Confirmatory factor analysis (CFA) was performed to assess the psychometric properties of the TS4US scale, resulting in a refined model with two latent factors and thirteen validated items. Findings indicate that 28% of students experience high technostress levels, while 5% report very high levels, though no significant associations were found between technostress and sociodemographic variables such as campus location, employment status, gender, and academic level. The TS4US instrument had been previously validated in Chile; this study confirms its structure in a new sociocultural context, reinforcing its cross-cultural applicability. These results highlight the need for sustainable strategies to mitigate technostress in higher education, including institutional support, digital literacy programs, and policies fostering a balanced technological environment. Addressing technostress is essential for promoting sustainable education (SDG4) and enhancing student well-being (SDG3). This study directly contributes to the achievement of Sustainable Development Goals 3 (Good Health and Well-being) and 4 (Quality Education) by providing validated tools and evidence-based recommendations to promote mental health and equitable access to digital education in Latin America. Future research should explore cross-country comparisons and targeted interventions, including digital well-being initiatives and adaptive learning strategies, to ensure a resilient and sustainable academic ecosystem. Full article

Three-dimensional printing is commonly used to fabricate provisional dental restorations. Studies have reported that changes in printing orientation affect the physical and mechanical properties of 3D-printed polymeric provisional restorations; however the findings have been inconsistent. Therefore, this systematic review and meta-analysis aims to analyze the articles evaluating the influence of printing orientation on the physical and mechanical properties of 3D-printed polymeric provisional dental restorations. Recommendations provided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to structure and compose the review. The PICO (Participant, Intervention, Comparison, Outcome) question ordered was: ‘Do 3D-printed provisional dental restorations (P) printed at various orientations (except 0°) (I) exhibit similar physical and mechanical properties (O) when compared to those printed at a 0° orientation (C)?’. An electronic search was conducted on 28 and 29 April 2025, by two independent researchers across four databases (MEDLINE/PubMed, Scopus, Cochrane Library, and Web of Science) to systematically collect relevant articles published up to March 2025. After removing duplicate articles and applying predefined inclusion and exclusion criteria, twenty-one articles were incorporated into this review. Self-designed Performa’s were used to tabulate all relevant information. For the quality analysis, the modified CONSORT scale was utilized. The quantitative analysis was performed on only fifteen out of twenty-one articles. It can be concluded that the printing orientation affects some of the tested properties, which include fracture strength (significantly higher for specimens printed at 0° when compared to 90°), wear resistance (significantly higher for specimens printed at 90° when compared to 0°), microhardness (significantly higher for specimens printed at 90°and 45° when compared to 0°), color stability (high at 0°), and surface roughness (significantly higher for specimens printed at 45° and 90° when compared to 0°). There were varied outcomes in terms of flexural strength and elastic modulus. Full article

Background: Vaccine hesitancy (VH) represents a growing concern among healthcare professionals and students, potentially undermining public health efforts. Nursing, pediatric nursing, and midwifery students are future vaccinators and educators, making it essential to understand their attitudes, knowledge, and confidence toward vaccination. This study aims to assess vaccine-related perceptions and behaviors among these student populations in an Italian university. Methods: A cross-sectional survey was conducted between November 2022 and February 2024 at the University of Rome “Tor Vergata”. A structured, anonymous questionnaire, including the Vaccination Attitudes Examination (VAX) scale, vaccine knowledge items, and sources of information, was administered to students in nursing (n = 205), pediatric nursing (n = 46), and midwifery (n = 21). Statistical analyses included descriptive statistics, ANOVA, post hoc tests, and Mann–Whitney U tests. Results: Among the 272 participants, 20.6% reported refusing at least one recommended vaccine, and 18.4% delayed vaccination for non-medical reasons. Vaccine knowledge and confidence increased significantly with academic progression (p < 0.001). Midwifery students showed both the highest concern for long-term vaccine effects and the greatest confidence in vaccine safety. Institutional and scientific sources were the most trusted, though traditional and non-institutional media also influenced perceptions, particularly among midwifery students. Conclusions: Despite high COVID-19 vaccine uptake, VH persists among health professional students. Discipline-specific patterns highlight the need for early, targeted educational strategies to enhance vaccine literacy and reduce hesitancy. Tailored training may empower future professionals to become informed and credible advocates for vaccination. Full article

Objectives: Artificial intelligence (AI) symptom-checker apps are proliferating, yet their everyday usability and transparency remain under-examined. This study provides a triangulated evaluation of three widely used AI-powered mHealth apps: ADA, Mediktor, and WebMD. Methods: Five usability experts applied a 13-item AI-specific heuristic checklist. In parallel, thirty lay users (18–65 years) completed five health-scenario tasks on each app, while task success, errors, completion time, and System Usability Scale (SUS) ratings were recorded. A repeated-measures ANOVA followed by paired-sample t-tests was conducted to compare SUS scores across the three applications. Results: The analysis revealed statistically significant differences in usability across the apps. ADA achieved a significantly higher mean SUS score than both Mediktor (p = 0.0004) and WebMD (p < 0.001), while Mediktor also outperformed WebMD (p = 0.0009). Common issues across all apps included vague AI outputs, limited feedback for input errors, and inconsistent navigation. Each application also failed key explainability heuristics, offering no confidence scores or interpretable rationales for AI-generated recommendations. Conclusions: Even highly rated AI mHealth apps display critical gaps in explainability and error handling. Embedding explainable AI (XAI) cues such as confidence indicators, input validation, and transparent justifications can enhance user trust, safety, and overall adoption in real-world healthcare contexts. Full article

Background: Perioperative care is an integral part of the procedure of a surgical operation, with strictly defined rules. The need to upgrade and improve some individual long-term processes aims at optimal patient care and the provision of high-level health services. Therefore, preoperative care is drawn up with new data resulting from the evolution of technology to upgrade the procedures that need improvement. According to the international literature, a factor considered to be of major importance is high preoperative anxiety and its effects on the patient’s postoperative course. High preoperative anxiety is postoperatively responsible for prolonged hospital stays, increased postoperative pain, decreased effect of anesthetic agents, increased amounts of analgesics, delayed healing of surgical wounds, and increased risk of infections. The use of Virtual Reality technology appears as a new method of managing preoperative anxiety. Objective: This study investigates the effect and effectiveness of Virtual Reality (VR) technology in managing preoperative anxiety in adult patients. Methods: A literature review was performed on 193 articles, published between 2017 and 2024, sourced from the scientific databases PubMed and Cochrane, as well as the trial registry ClinicalTrials, with a screening and exclusion process to meet the criterion of investigating VR technology’s effectiveness in managing preoperative anxiety in adult patients. This systematic review was conducted under the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. Results: Out of the 193 articles, 29 were selected. All articles examined the efficacy of VR in adult patients (≥18) undergoing various types of surgery. The studies represent a total of 2.354 participants from 15 countries. There are two types of VR applications: distraction therapy and patient education. From the studies, 14 (48%) used the distraction VR intervention, 14 (48%) used the training VR intervention, and 1 (4%) used both VR interventions, using a range of validated anxiety scales such as the STAI, VAS-A, APAIS, and HADS. Among the 29 studies reviewed, 25 (86%) demonstrated statistically significant reductions in preoperative anxiety levels following the implementation of VR interventions. VR technology appears to manage preoperative anxiety effectively. It is a non-invasive and non-pharmacological intervention with minimal side effects. Conclusions: Based on the review, the management of preoperative anxiety with VR technology shows good levels of effectiveness. Further investigation of the efficacy by more studies and randomized controlled trials, with a larger patient population, is recommended to establish and universally apply VR technology in the preoperative care process as an effective method of managing preoperative anxiety. Full article

Achieving optimal agricultural yields and promoting sustainable farming relies on accurate crop recommendations. However, the applicability of many current systems is limited by their considerable computational requirements and dependence on comprehensive datasets, especially in resource-limited contexts. This paper presents HOLISTIQ RS, a novel crop recommendation system explicitly designed for operation on low-specification hardware and in data-scarce regions. HOLISTIQ RS combines collaborative filtering with a Markov model to predict appropriate crop choices, drawing upon user profiles, regional agricultural data, and past crop performance. Results indicate that HOLISTIQ RS provides a significant increase in recommendation accuracy, achieving a MAP@5 of 0.31 and nDCG@5 of 0.41, outperforming standard collaborative filtering methods (the KNN achieved MAP@5 of 0.28 and nDCG@5 of 0.38, and the ANN achieved MAP@5 of 0.25 and nDCG@5 of 0.35). Significantly, the system also demonstrates enhanced recommendation diversity, achieving an Item Variety (IV@5) of 23%, which is absent in deterministic baselines. Significantly, the system is engineered for reduced energy consumption and can be deployed on low-cost hardware. This provides a feasible and adaptable method for encouraging informed decision-making and promoting sustainable agricultural practices in areas where resources are constrained, with an emphasis on lower energy usage. Full article

In the recommendation system (RS) literature, a distinction exists between studies dedicated to fully operational (known users/items) and cold-start (new users/items) RSs. The warm-up phase—the transition between the two—is not widely researched, despite evidence that attrition rates are the highest for users and content providers during such periods. RS formulations, particularly deep learning models, do not easily allow for a warm-up phase. Herein, we propose two independent and complementary models to increase RS performance during the warm-up phase. The models apply to any cold-start RS expressible as a function of all user features, item features, and existing users’ preferences for existing items. We demonstrate substantial improvements: Accuracy-oriented metrics improved by up to 14% compared with not handling warm-up explicitly. Non-accuracy-oriented metrics, including serendipity and fairness, improved by up to 12% compared with not handling warm-up explicitly. The improvements were independent of the cold-start RS algorithm. Additionally, this paper introduces a method of examining the performance metrics of an RS during the warm-up phase as a function of the number of user–item interactions. We discuss problems such as data leakage and temporal consistencies of training/testing—often neglected during the offline evaluation of RSs. Full article

Background/Objectives: Dental fear affects about one in four general dentistry patients in the U.S. and other high-income countries. However, the prevalence of fear in orthodontic practice has received scant attention, with no studies in the U.S. The aim of this study was to investigate the prevalence of orthodontic and general dentistry fear and the relationship between the two among patients at a large, U.S. urban university orthodontic clinic serving a culturally and ethnically diverse population. Methods: Patients (N = 186) rated their general dentistry and orthodontic fear using a validated single-item scale. Results: A substantial proportion of patients experienced clinically significant fear of dentists (22.1% [95% CI 16.31–28.69%]) and orthodontists (17.2% [95% CI 11.61–22.82%]). There was a strong effect size (r = 0.67) between ratings of fear of dentists and orthodontists. Our prevalences were nearly identical to the weighted prevalences in the literature for general dentistry and orthodontic fear (22.90% [95% CI: 20.73–25.22%] and 17.65% [95% CI: 15.09–20.53%], respectively) among orthodontic patients. Conclusions: Despite orthodontic procedures being generally less fear-inducing than general dentistry, orthodontists should assume that over one in six patients will be fearful. Further research is needed to create an assessment of the most feared orthodontic stimuli and to broaden the application of evidence-based dental fear treatments. We recommend screening all orthodontic patients using a single, validated question; if patients are fearful, providers should use empathic communication and accommodate patient needs in treatment sessions. Full article