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Search Results (763)

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Keywords = qualitative randomized study

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29 pages, 6224 KiB  
Article
Applications of Linear and Ensemble-Based Machine Learning for Predicting Winning Teams in League of Legends
by Supratik Chowdhury, Mominul Ahsan and Phoebe Barraclough
Appl. Sci. 2025, 15(10), 5241; https://doi.org/10.3390/app15105241 - 8 May 2025
Abstract
Over the last decade, advancements in machine learning and easier model deployment have led to increased commercial applications. One such use case is esports, where machine learning (ML) is used to understand predictors of success. League of Legends, one of the most popular [...] Read more.
Over the last decade, advancements in machine learning and easier model deployment have led to increased commercial applications. One such use case is esports, where machine learning (ML) is used to understand predictors of success. League of Legends, one of the most popular esports, has been a particular academic focus. Investigations into League are divided into two areas: qualitative analyses of factors such as perseverance and group dynamics and quantitative research to create models to predict match outcomes via either pre-game player information or in-game match data. Few studies have integrated both pre-game and in-game data to improve modeling, often using datasets that may not represent the broader player community. This study investigates the factors influencing the accuracy of match prediction models in League of Legends. Evaluating the effects of training on data that are representative of the actual player on the basis of accuracy and determining whether models that amalgamate pre-game and in-game features yield superior results. By utilizing a dataset derived from the Riot API, this research work introduces a novel “streak” feature and constructs models using logistic regression, random forest, C5.0 Gradient Boost and XGBoost, evaluating model performance against recent literature. The results indicate that employing a dataset that more accurately reflects the general player population leads to a slight decrease in the efficacy of the models compared with those using professional datasets only; however, the models demonstrate potential for greater generalizability across a wider range of ranks. The models that incorporate both pre-game and in-game data outperformed most existing studies that focus solely on one type of data, achieving a peak accuracy of 76.8% for the best-performing model. These findings guide future work on feature engineering via the Riot API and model application for broader player populations in esports. Additionally, these insights can be applied to build and improve tools that provide real-time predictions of match results. Full article
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26 pages, 860 KiB  
Systematic Review
Can the Pupillary Light Reflex and Pupillary Unrest Be Used as Biomarkers of Parkinson’s Disease? A Systematic Review and Meta-Analysis
by Aleksander Dawidziuk, Emilia Butters, Daniel Josef Lindegger, Campbell Foubister, Hugo Chrost, Michal Wlodarski, John Grogan, Paulina A Rowicka, Fion Bremner and Sanjay G Manohar
Diagnostics 2025, 15(9), 1167; https://doi.org/10.3390/diagnostics15091167 - 3 May 2025
Viewed by 159
Abstract
Background/Objectives: The pathological changes preceding the onset of Parkinson’s disease (PD) commence several decades before motor symptoms manifest, offering a potential window for identifying objective biomarkers for early diagnosis and disease monitoring. Among the primary non-motor features of PD is autonomic dysfunction; however, [...] Read more.
Background/Objectives: The pathological changes preceding the onset of Parkinson’s disease (PD) commence several decades before motor symptoms manifest, offering a potential window for identifying objective biomarkers for early diagnosis and disease monitoring. Among the primary non-motor features of PD is autonomic dysfunction; however, its precise assessment remains challenging, limiting its viability as a reliable biomarker. Both the pupillary light reflex (PLR) and pupillary unrest are regulated by autonomic pathways suggesting their potential as objective non-invasive indicators of the PD prodromal phase. This review systematically evaluates studies that compare PLR and pupillary unrest in individuals with PD and healthy controls to determine their utility as potential biomarkers of the disease. Methods: A systematic search strategy was designed to identify studies reporting PLR and pupillary unrest findings in PD patients. Searches were conducted across three databases (MEDLINE, Embase PsycINFO), supplemented by cross-referencing relevant studies found on Google Scholar. The literature search was last updated on 7 December 2020. Pupillometric parameters that permitted statistical synthesis included maximum constriction velocity (VMax), constriction amplitude (CAmp), and constriction latency (CL). Pooled incidence and effect sizes were determined using a random-effects model with an inverse variance DerSimonian–Laird estimator. The I2 statistic was used to assess study heterogeneity. When meta-analysis was not feasible, a qualitative analysis was undertaken. Results: The initial search yielded 219 references. Following deduplication and exclusion of ineligible studies, 31 papers were selected for review. Pupillometric data from 11 studies were incorporated into the meta-analysis. Effect sizes for PD patients were significant for VMax −0.92, (p < 0.01), CAmp −0.58, (p < 0.05), and CL 0.46, (p < 0.05). Measures of pupillary unrest were elevated in PD patients compared to controls, but evidence was limited to two studies. Conclusions: Pupillary constriction in response to light is characterised by reduced speed and amplitude in PD, with effect sizes suggesting potential clinical applicability. However, evidence regarding baseline pupillary variability remains insufficient, underlining the necessity for further research. Pupillary metrics represent a promising avenue for early PD detection, though their clinical utility is constrained by methodological heterogeneity and variations in disease duration among studies. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
22 pages, 1650 KiB  
Systematic Review
Efficacy and Safety of Antibody-Drug Conjugates for Lung Cancer Therapy: A Systematic Review of Randomized and Non-Randomized Clinical Trials
by Matteo Gallina, Anna Carollo, Anna Gallina, Sofia Cutaia, Sergio Rizzo and Alessio Provenzani
Pharmaceutics 2025, 17(5), 608; https://doi.org/10.3390/pharmaceutics17050608 - 3 May 2025
Viewed by 218
Abstract
Background/Objectives: Lung cancer is the leading cause of cancer-related deaths worldwide. Non-Small-Cell Lung Cancer (NSCLC) accounts for 80–90% of all lung cancers. Antibody-Drug Conjugates (ADCs) represent an expanding targeted therapy option for the treatment of NSCLC. The aim is to perform a [...] Read more.
Background/Objectives: Lung cancer is the leading cause of cancer-related deaths worldwide. Non-Small-Cell Lung Cancer (NSCLC) accounts for 80–90% of all lung cancers. Antibody-Drug Conjugates (ADCs) represent an expanding targeted therapy option for the treatment of NSCLC. The aim is to perform a systematic literature review to evaluate the efficacy and safety profiles of ADCs currently undergoing clinical trials for the treatment of NSCLC. Methods: The study adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Literature searches were conducted in PubMed, ClinicalTrial.gov and Web of Science databases, covering the period from 2014 to 2024. Only randomized and non-randomized phase II-IV clinical trials focusing on ADC-based therapies for adult patients affected by NSCLC were selected. The Revised Cochrane Risk-of-Bias Tool for Randomized Trials (RoB 2.0) and the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) were used to evaluate the overall risk of bias in the included randomized and non-randomized studies, respectively. While GRADE (Grading of Recommendations, Assessment, Development and Evaluations) methodology was used to assess the certainty of the evidence. Efficacy endpoints were categorized based on primary outcomes while safety was assessed through the frequency and severity of Treatment-Emergent Adverse Events (TEAEs), and a qualitative summary of the findings was conducted. Results: A total of seven studies, including three randomized, three non-randomized, and one without specific allocation, were included, comprising 1287 patients, with 693 (54%) men, and an average age of 63 years old. Two studies were deemed to have a low risk of bias, while six had a moderate risk or some concerns. Five ADCs were evaluated: trastuzumab deruxtecan (T-DXd), trastuzumab emtansine (T-DM1), telisotuzumab vedotin, patritumab deruxtecan, and datopotamab deruxtecan (Dato-DXd). T-DXd demonstrated superior efficacy in HER2-overexpressing and HER2-mutant NSCLC, with an ORR of 52.9% and 49.0%, respectively. However, HER2-mutant patients exhibited a longer median DOR (16.8 vs. 6.2 months) but a higher incidence of grade ≥ 3 TEAEs (38.6% vs. 22%). T-DM1 showed modest efficacy, with an ORR of 20% in HER2-overexpressing NSCLC and 6.7% in HER2-mutant patients. Dato-DXd demonstrated improved ORR (26.4% vs. 12.8%) and PFS (4.4 vs. 3.7 months) compared to docetaxel. Patritumab deruxtecan achieved an ORR of 39% in EGFR-mutant NSCLC, while telisotuzumab vedotin exhibited limited activity in c-MET-positive NSCLC (ORR 9%, median DOR 7.5 months). Frequency and severity of TEAEs varied across ADCs, with ILD being a major concern, highlighting the need for strict patient monitoring and early intervention to mitigate severe adverse events. Conclusions: ADCs represent a promising advancement in NSCLC treatment, offering targeted therapeutic options beyond conventional chemotherapy and immunotherapy. T-DXd has emerged as the most effective ADC for HER2-mutant NSCLC with manageable safety profile, whereas Dato-DXd provides a viable alternative for TROP2-expressing tumors. While ADCs offer significant clinical benefits, careful patient selection and proactive management of adverse events remain crucial. Ongoing and future trials will further refine the role of ADCs in personalized NSCLC treatment, potentially expanding their tumor-agnostic use to broader patient populations. Full article
(This article belongs to the Section Clinical Pharmaceutics)
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13 pages, 521 KiB  
Article
Between Anxiety and Adaptation: Children’s and Parents’ Experiences with Botulinum Toxin Treatment in Cerebral Palsy
by Rannei Sæther, Siri Merete Brændvik and Ann-Kristin Gunnes Elvrum
J. Clin. Med. 2025, 14(9), 3164; https://doi.org/10.3390/jcm14093164 - 2 May 2025
Viewed by 352
Abstract
Background/Objectives: This study explores how children with cerebral palsy (CP) and their parents experience botulinum toxin type A (BoNT-A) treatment, focusing on emotional and procedural challenges and communication within the triad of children, parents, and healthcare providers. Methods: This qualitative sub-study [...] Read more.
Background/Objectives: This study explores how children with cerebral palsy (CP) and their parents experience botulinum toxin type A (BoNT-A) treatment, focusing on emotional and procedural challenges and communication within the triad of children, parents, and healthcare providers. Methods: This qualitative sub-study was conducted within the WE-study, a randomized controlled trial on BoNT-A effects in children with CP. Semi-structured interviews with 20 parents and 18 children (aged 4–15 years, GMFCS I–II) were thematically analyzed. Results: Three themes were identified: Preparing for the treatment, Being in the moment, and Adapting after treatment. Pre-procedural anxiety was common, with children describing nervousness or physical discomfort in the days before the treatment. During the procedure, pain management and sedation choices influenced children’s experiences, with healthcare providers being the primary source of information. After treatment, some children experienced temporary walking instability, but most quickly resumed daily activities. Communication primarily occurred between healthcare providers and each party individually, rather than through a triadic interaction. Conclusions: BoNT-A treatment involves both emotional distress and adaptation. Strengthening child-inclusive communication, structured preparation, and collaboration within the triad may improve treatment experiences and better align care with child-centered principles. Future research should explore strategies to enhance child involvement in repeated treatments. Full article
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13 pages, 1104 KiB  
Review
Temporary Mechanical Support in Cardiogenic Shock Secondary to Heart Failure: An Evolving Paradigm
by Nandini Nair, Dongping Du and Balakrishnan Mahesh
J. Pers. Med. 2025, 15(5), 184; https://doi.org/10.3390/jpm15050184 - 2 May 2025
Viewed by 214
Abstract
Cardiogenic shock can be defined as a state of circulatory collapse resulting in hypoperfusion and end-organ dysfunction. It carries a large burden of mortality, but management strategies are driven by expert consensus rather than adequately powered randomized clinical trials. The goal of this [...] Read more.
Cardiogenic shock can be defined as a state of circulatory collapse resulting in hypoperfusion and end-organ dysfunction. It carries a large burden of mortality, but management strategies are driven by expert consensus rather than adequately powered randomized clinical trials. The goal of this review is to highlight the differences in presentation and outcomes in cardiogenic shock depending on the etiology, such as acute myocardial infarction (AMI) versus acute-on-chronic heart failure (HF), gender-based differences in treatment strategies and outcomes and the need for more precise risk stratification and modeling to improve the efficiency of treatment delivery in a personalized fashion. PubMed and Google Scholar were used to search the literature for this qualitative review. The differences in gender and etiology of cardiogenic shock are not consistent in all studies in the exiting literature. There is a need for identification of novel risk factors that define the different phenotypes that present with similar hemodynamic and biomarker profiles. There is an urgent need to devise a methodology to understand and differentiate the different cardiogenic shock phenotypes and their trajectories. Better risk prediction models should be generated to help deliver well-tailored treatment, paving the way to the efficient delivery of personalized medicine. Full article
(This article belongs to the Special Issue New Perspectives of Critical Care Medicine)
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38 pages, 3509 KiB  
Systematic Review
Mixed Reality in Undergraduate Nursing Education: A Systematic Review and Meta-Analysis of Benefits and Challenges
by Laura Guillen-Aguinaga, Esperanza Rayón-Valpuesta, Sara Guillen-Aguinaga, Blanca Rodriguez-Diaz, Rocio Montejo, Rosa Alas-Brun, Enrique Aguinaga-Ontoso, Luc Onambele, Miriam Guillen-Aguinaga, Francisco Guillen-Grima and Ines Aguinaga-Ontoso
Nurs. Rep. 2025, 15(5), 137; https://doi.org/10.3390/nursrep15050137 - 22 Apr 2025
Viewed by 339
Abstract
Background: Nursing Schools are incorporating Mixed Reality (MR) into student training to enable them to confront challenging or infrequently encountered scenarios in their practice and ensure their preparedness. This systematic review evaluates the benefits and challenges of implementing MR in nursing curricula. Materials [...] Read more.
Background: Nursing Schools are incorporating Mixed Reality (MR) into student training to enable them to confront challenging or infrequently encountered scenarios in their practice and ensure their preparedness. This systematic review evaluates the benefits and challenges of implementing MR in nursing curricula. Materials and Methods: A search was conducted in PubMed, WOS, Scopus, Embase, and CINAHL for studies published between 2011 and 2023. The search strategy used was “(nurses OR nurse OR nursing) AND mixed reality AND simulation”. Inclusion criteria required that studies focus on undergraduate nursing students and be written in English or Spanish. Exclusion criteria included reviews, bibliometric studies, and articles that did not separately report undergraduate nursing student results. Quality was evaluated with the JBI Critical Appraisal Checklist for Qualitative Research and the Newcastle-Ottawa Scale. A meta-analysis was conducted on studies with control groups to compare MR’s effectiveness against traditional teaching methods. Results: Thirty-three studies met the inclusion criteria. MR was widely used to improve clinical judgment, patient safety, technical skill acquisition, and student confidence. The meta-analysis found that MR reduced anxiety (Cohen’s d = −0.73, p < 0.001). However, its impact on knowledge acquisition and skill development was inconsistent. There was no improvement over traditional methods (p = 0.466 and p = 0.840). Despite positive qualitative findings, methodological variability, small sample sizes, and publication bias contributed to mixed quantitative results. The main challenges were cybersickness, usability, high costs, and limited institutional access to MR technology. Conclusions: Although MR can help nursing education by decreasing students’ anxiety, its efficacy remains inconclusive. Future research should use larger, randomized controlled trials to validate MR’s role in nursing education. Full article
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44 pages, 2395 KiB  
Systematic Review
Artificial Intelligence in Thoracic Surgery: A Review Bridging Innovation and Clinical Practice for the Next Generation of Surgical Care
by Vasileios Leivaditis, Andreas Antonios Maniatopoulos, Henning Lausberg, Francesk Mulita, Athanasios Papatriantafyllou, Elias Liolis, Eleftherios Beltsios, Antonis Adamou, Nikolaos Kontodimopoulos and Manfred Dahm
J. Clin. Med. 2025, 14(8), 2729; https://doi.org/10.3390/jcm14082729 - 16 Apr 2025
Viewed by 636
Abstract
Background: Artificial intelligence (AI) is rapidly transforming thoracic surgery by enhancing diagnostic accuracy, surgical precision, intraoperative guidance, and postoperative management. AI-driven technologies, including machine learning (ML), deep learning, computer vision, and robotic-assisted surgery, have the potential to optimize clinical workflows and improve patient [...] Read more.
Background: Artificial intelligence (AI) is rapidly transforming thoracic surgery by enhancing diagnostic accuracy, surgical precision, intraoperative guidance, and postoperative management. AI-driven technologies, including machine learning (ML), deep learning, computer vision, and robotic-assisted surgery, have the potential to optimize clinical workflows and improve patient outcomes. However, challenges such as data integration, ethical concerns, and regulatory barriers must be addressed to ensure AI’s safe and effective implementation. This review aims to analyze the current applications, benefits, limitations, and future directions of AI in thoracic surgery. Methods: This review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was performed using PubMed, Scopus, Web of Science, and Cochrane Library for studies published up to January 2025. Relevant articles were selected based on predefined inclusion and exclusion criteria, focusing on AI applications in thoracic surgery, including diagnostics, robotic-assisted surgery, intraoperative guidance, and postoperative care. A risk of bias assessment was conducted using the Cochrane Risk of Bias Tool and ROBINS-I for non-randomized studies. Results: Out of 279 identified studies, 36 met the inclusion criteria for qualitative synthesis, highlighting AI’s growing role in diagnostic accuracy, surgical precision, intraoperative guidance, and postoperative care in thoracic surgery. AI-driven imaging analysis and radiomics have improved pulmonary nodule detection, lung cancer classification, and lymph node metastasis prediction, while robotic-assisted thoracic surgery (RATS) has enhanced surgical accuracy, reduced operative times, and improved recovery rates. Intraoperatively, AI-powered image-guided navigation, augmented reality (AR), and real-time decision-support systems have optimized surgical planning and safety. Postoperatively, AI-driven predictive models and wearable monitoring devices have enabled early complication detection and improved patient follow-up. However, challenges remain, including algorithmic biases, a lack of multicenter validation, high implementation costs, and ethical concerns regarding data security and clinical accountability. Despite these limitations, AI has shown significant potential to enhance surgical outcomes, requiring further research and standardized validation for widespread adoption. Conclusions: AI is poised to revolutionize thoracic surgery by enhancing decision-making, improving patient outcomes, and optimizing surgical workflows. However, widespread adoption requires addressing key limitations through multicenter validation studies, standardized AI frameworks, and ethical AI governance. Future research should focus on digital twin technology, federated learning, and explainable AI (XAI) to improve AI interpretability, reliability, and accessibility. With continued advancements and responsible integration, AI will play a pivotal role in shaping the next generation of precision thoracic surgery. Full article
(This article belongs to the Special Issue New Trends in Minimally Invasive Thoracic Surgery)
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17 pages, 3420 KiB  
Article
Learning Infant Development and Surveillance Through a Series of Board Games Designed for Psychology Students
by Boonroungrut Chinun
Educ. Sci. 2025, 15(4), 457; https://doi.org/10.3390/educsci15040457 - 7 Apr 2025
Viewed by 385
Abstract
Human development education often relies on traditional, lecture-based teaching methods, thus limiting opportunities for active engagement. The lack of diverse creative and active teaching approaches hinders psychology students’ ability to fully understand and apply complex concepts. This study examined the effectiveness of a [...] Read more.
Human development education often relies on traditional, lecture-based teaching methods, thus limiting opportunities for active engagement. The lack of diverse creative and active teaching approaches hinders psychology students’ ability to fully understand and apply complex concepts. This study examined the effectiveness of a designed series of board games to enhance understanding of infant development and surveillance among psychology students. A mixed-method approach using a randomized matched control group design and qualitative exploration was applied. In the experiment, there were two groups, intervention and conventional learning, in three data collection phases. A design involving 60 students (30 in each group) was employed. The qualitative exploration involved the completion of a weekly journal to explore the students’ learning experiences when playing board games. A 2 × 3 mixed-design Analysis of Variance (ANOVA) with content analysis of the journal texts was performed. The results revealed that the created board games significantly enhanced students’ understanding, with them achieving significantly higher understanding scores in the posttest and follow-up phases in learning development progress. An interaction effect for the treatments and test phases was also noted. Meanwhile, the qualitative findings complemented and reinforced the quantitative results, offering deeper insights into the learning experiences and valuable suggestions for improving the design and rules of the games. In conclusion, by tailoring the board games to learning objectives associated with infant developmental psychology, educators can enhance student engagement, knowledge retention, and real-classroom application. Full article
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33 pages, 666 KiB  
Review
The Impact of Dietary Interventions on Metabolic Outcomes in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and Comorbid Conditions, Including Obesity and Type 2 Diabetes
by Joanna Michalina Jurek, Katarzyna Zablocka-Sowinska, Helena Clavero Mestres, Leyre Reyes Gutiérrez, Javier Camaron and Teresa Auguet
Nutrients 2025, 17(7), 1257; https://doi.org/10.3390/nu17071257 - 3 Apr 2025
Viewed by 1086
Abstract
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a public health concern, linked with immune-metabolic dysfunction. While lifestyle and dietary modifications remain the cornerstone of MASLD management, the optimal dietary approach remains uncertain. Objectives: This systematic review aims to investigate the impact of [...] Read more.
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a public health concern, linked with immune-metabolic dysfunction. While lifestyle and dietary modifications remain the cornerstone of MASLD management, the optimal dietary approach remains uncertain. Objectives: This systematic review aims to investigate the impact of model dietary patterns on metabolic outcomes in patients with MASLD and evaluate their effects in individuals with coexisting metabolic conditions, such as obesity, metabolic syndrome, and type 2 diabetes mellitus (T2DM). Methods: To conduct the review, PubMed, Scopus, Google Scholar, Cochrane CENTRAL, and ClinicalTrials.gov databases were searched for Randomized Controlled Trials (RCTs) on the adult population, published between January 2019 and September 2024, following PRISMA principles. The quality of the included RCTs was assessed qualitatively based on study characteristics. Results: The main findings of this review demonstrated that the use of interventions with dietary model based on Mediterranean diet (MED) and intermittent fasting (IF) approaches, such as alternative-day fasting (ADF) and time-restricted feeding regimens (TRF) may have potential in reducing body weight, BMI, and waist circumference, with additional benefits of improving glycemic control and reducing inflammation. The effects on hepatic functions, although limited, may be linked with reduced enzyme activity and liver stiffness. Additionally, the use of lacto-ovo-vegetarian diet (LOV-D) and the Dietary Approaches to Stop Hypertension (DASH) diet may offer additional health benefits, including blood pressure management. Conclusions: This review suggests that MED and IF-based strategies may reduce BW, improve glycemic control, and lower inflammation, with potential benefits for hepatic function. Further long-term studies are needed to confirm these effects and underlying mechanisms, which will allow for the optimization of protocols and ensure their safety in MASLD. Full article
(This article belongs to the Special Issue Dietary Advice and Guidance on Liver Metabolism)
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20 pages, 960 KiB  
Article
The Impact of Integrated Project-Based Learning and Flipped Classroom on Students’ Computational Thinking Skills: Embedded Mixed Methods
by Muh Fitrah, Anastasia Sofroniou, Caly Setiawan, Widihastuti Widihastuti, Novi Yarmanetti, Melinda Puspita Sari Jaya, Jontas Gayuh Panuntun, Arfaton Arfaton, Septrisno Beteno and Ika Susianti
Educ. Sci. 2025, 15(4), 448; https://doi.org/10.3390/educsci15040448 - 2 Apr 2025
Viewed by 1088
Abstract
Computational thinking skills among high school students have become a global concern, especially in the context of the ever-evolving digital education era. However, the attention given by teachers to this skill during mathematics instruction has not been a priority. This study aims to [...] Read more.
Computational thinking skills among high school students have become a global concern, especially in the context of the ever-evolving digital education era. However, the attention given by teachers to this skill during mathematics instruction has not been a priority. This study aims to evaluate and explore the impact of project-based learning (PBL) integrated with flipped classroom on high school students’ computational thinking skills in mathematics. The research design employed a mixed-method approach with a quasi-experimental, nonequivalent pre-test post-test control group design. The experimental group (46 students) and control group (45 students) were selected through simple random sampling from 12th-grade science students. Data were collected through tests, questionnaires, and in-depth interviews, using instruments such as computational thinking skills assessment questions, questionnaires, and interview protocols. Quantitative data analysis was performed using SPSS Version 26 for t-tests and ANOVA, while qualitative analysis was conducted using ATLAS.ti with an abductive-inductive and thematic approach. The findings indicate that PBL integrated with flipped classrooms significantly improved students’ decomposition, pattern recognition, and abstraction skills. The implementation of PBL, integrated with a flipped classroom, created an interactive learning environment, fostering active engagement and enhancing students’ understanding and skills in solving mathematical concepts. Although there was an improvement in algorithmic thinking skills, some students still faced difficulties in developing systematic solutions. The results of this study suggest that further research could explore other methodologies, such as grounded theory and case studies integrated with e-learning, and emphasize visual analysis methods, such as using photo elicitation to explore thinking skills. Full article
(This article belongs to the Special Issue Project-Based Learning in Integrated STEM Education)
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28 pages, 1104 KiB  
Systematic Review
Orthodontic Ceramic Bracket Removal Using Lasers: A Systematic Review
by Mateusz Michalak, Sylwia Kiryk, Agnieszka Kotela, Kamila Wiśniewska, Jan Kiryk, Jacek Zbigniew Zborowski, Jacek Matys and Maciej Dobrzyński
J. Funct. Biomater. 2025, 16(4), 123; https://doi.org/10.3390/jfb16040123 - 1 Apr 2025
Viewed by 471
Abstract
Objective: The aim of this systematic review was to evaluate the effectiveness and safety of various laser systems for debonding ceramic orthodontic brackets compared to conventional mechanical removal methods. The primary outcomes assessed included enamel damage, pulp temperature changes, adhesive remnant index (ARI), [...] Read more.
Objective: The aim of this systematic review was to evaluate the effectiveness and safety of various laser systems for debonding ceramic orthodontic brackets compared to conventional mechanical removal methods. The primary outcomes assessed included enamel damage, pulp temperature changes, adhesive remnant index (ARI), and shear bond strength (SBS). Materials and Methods: A systematic search was conducted in November 2024 across the PubMed, Scopus, and Web of Science (WoS) databases following PRISMA guidelines. The initial search yielded 453 records, of which 41 studies met the inclusion criteria for qualitative and quantitative analysis. The risk of bias was assessed using a standardized scoring system, and only studies with accessible full texts were included. Results: The review highlighted significant heterogeneity in laser parameters, measurement protocols, and study methodologies. Among the evaluated lasers, CO2 and Er:YAG were the most frequently studied and demonstrated high efficacy in debonding ceramic brackets while maintaining enamel integrity. Sixteen studies assessing SBS reported a reduction from baseline values of 13–23 MPa to clinically acceptable ranges of 7–12 MPa following laser application. ARI was analyzed in 25 studies, with laser-treated groups exhibiting higher scores (2–3), indicating safer debonding with more adhesive remaining on the tooth surface, thereby reducing enamel damage. Pulpal temperature increases were examined in 23 studies, revealing that most laser types, when used within optimal parameters, did not exceed the 5.5 °C threshold considered safe for pulpal health. However, diode and Tm:YAP lasers showed potential risks of overheating in some studies. Conclusions: Laser-assisted debonding of ceramic orthodontic brackets is an effective and safe technique when applied with appropriate laser parameters. CO2 and Er:YAG lasers were the most effective in reducing SBS while preserving enamel integrity. However, variations in laser settings, study methodologies, and the predominance of in vitro studies limit the ability to establish standardized clinical guidelines. Further randomized controlled trials (RCTs) are necessary to develop evidence-based protocols for safe and efficient laser-assisted bracket removal in orthodontic practice. Full article
(This article belongs to the Special Issue New Trends in Biomaterials and Implants for Dentistry (2nd Edition))
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27 pages, 4371 KiB  
Systematic Review
Diagnostic Accuracy of Deep Learning for Intracranial Hemorrhage Detection in Non-Contrast Brain CT Scans: A Systematic Review and Meta-Analysis
by Armin Karamian and Ali Seifi
J. Clin. Med. 2025, 14(7), 2377; https://doi.org/10.3390/jcm14072377 - 30 Mar 2025
Viewed by 698
Abstract
Background: Intracranial hemorrhage (ICH) is a life-threatening medical condition that needs early detection and treatment. In this systematic review and meta-analysis, we aimed to update our knowledge of the performance of deep learning (DL) models in detecting ICH on non-contrast computed tomography [...] Read more.
Background: Intracranial hemorrhage (ICH) is a life-threatening medical condition that needs early detection and treatment. In this systematic review and meta-analysis, we aimed to update our knowledge of the performance of deep learning (DL) models in detecting ICH on non-contrast computed tomography (NCCT). Methods: The study protocol was registered with PROSPERO (CRD420250654071). PubMed/MEDLINE and Google Scholar databases and the reference section of included studies were searched for eligible studies. The risk of bias in the included studies was assessed using the QUADAS-2 tool. Required data was collected to calculate pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with the corresponding 95% CI using the random effects model. Results: Seventy-three studies were included in our qualitative synthesis, and fifty-eight studies were selected for our meta-analysis. A pooled sensitivity of 0.92 (95% CI 0.90–0.94) and a pooled specificity of 0.94 (95% CI 0.92–0.95) were achieved. Pooled PPV was 0.84 (95% CI 0.78–0.89) and pooled NPV was 0.97 (95% CI 0.96–0.98). A bivariate model showed a pooled AUC of 0.96 (95% CI 0.95–0.97). Conclusions: This meta-analysis demonstrates that DL performs well in detecting ICH from NCCTs, highlighting a promising potential for the use of AI tools in various practice settings. More prospective studies are needed to confirm the potential clinical benefit of implementing DL-based tools and reveal the limitations of such tools for automated ICH detection and their impact on clinical workflow and outcomes of patients. Full article
(This article belongs to the Special Issue Neurocritical Care: Clinical Advances and Practice Updates)
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15 pages, 1212 KiB  
Article
Plant-Based Culinary Medicine Intervention Improves Cooking Behaviors, Diet Quality, and Skin Carotenoid Status in Adults at Risk of Heart Disease Participating in a Randomized Crossover Trial
by Andrea M. Krenek, Monica Aggarwal, Stephanie T. Chung, Amber B. Courville, Juen Guo and Anne Mathews
Nutrients 2025, 17(7), 1132; https://doi.org/10.3390/nu17071132 - 25 Mar 2025
Cited by 1 | Viewed by 670
Abstract
Background: Culinary medicine (CM) interventions in teaching kitchens have emerged as novel approaches for influencing dietary behaviors, but their efficacy, content, and delivery vary. Objective: The effects of a virtual vegan CM intervention on behavioral determinants, cooking competencies, diet quality, and [...] Read more.
Background: Culinary medicine (CM) interventions in teaching kitchens have emerged as novel approaches for influencing dietary behaviors, but their efficacy, content, and delivery vary. Objective: The effects of a virtual vegan CM intervention on behavioral determinants, cooking competencies, diet quality, and skin carotenoid status were assessed. Methods: This analysis from a 9-week randomized crossover study evaluated behavioral survey assessments, Whole Plant Food Density (WPFD) as a diet quality indicator utilizing Automated Self-Administered 24 h Dietary Recall data, and skin carotenoid status (SCS) via pressure-mediated reflection spectroscopy at multiple timepoints. Adults at ≥5% atherosclerotic cardiovascular disease (ASCVD) risk followed a vegan diet pattern that was high or low in extra virgin olive oil (EVOO) for 4 weeks each with weekly virtual cooking classes, separated by a 1-week washout period. Qualitative feedback was collected for thematic analysis. Results: In 40 participants (75% female; body mass index, 32 ± 7 kg/m2; age, 64 ± 9 years mean ± SD), perceived control over trajectory of heart disease, knowledge of lifestyle behaviors for heart health, and confidence in cooking skills and preparing a variety of plant-based foods improved post intervention (all p ≤ 0.001). WPFD increased by 69–118% from baseline. Greater SCS changes occurred after high-EVOO (+51.4 ± 13.9 mean ± SEM, p < 0.001) compared to low-EVOO (+6.0 ± 16.4, p = 0.718) diets. Conclusions: A virtual vegan CM intervention improved dietary behaviors and quality, which was associated with reductions in CVD risk factors. SCS is influenced by EVOO intake, warranting consideration when used to estimate fruit and vegetable intake. The potential impacts of CM on behaviors and health outcomes warrant continued research efforts in medical and public health settings. Full article
(This article belongs to the Section Phytochemicals and Human Health)
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18 pages, 1005 KiB  
Systematic Review
Harnessing Generative Artificial Intelligence for Exercise and Training Prescription: Applications and Implications in Sports and Physical Activity—A Systematic Literature Review
by Luca Puce, Nicola Luigi Bragazzi, Antonio Currà and Carlo Trompetto
Appl. Sci. 2025, 15(7), 3497; https://doi.org/10.3390/app15073497 - 22 Mar 2025
Viewed by 1443
Abstract
Regular physical activity plays a critical role in health promotion and athletic performance, necessitating personalized exercise and training prescriptions. While traditional methods rely on expert assessments, artificial intelligence (AI), particularly generative AI models such as ChatGPT and Google Gemini, has emerged as a [...] Read more.
Regular physical activity plays a critical role in health promotion and athletic performance, necessitating personalized exercise and training prescriptions. While traditional methods rely on expert assessments, artificial intelligence (AI), particularly generative AI models such as ChatGPT and Google Gemini, has emerged as a potential tool for enhancing personalization and scalability in training recommendations. However, the applicability, reliability, and adaptability of AI-generated exercise prescriptions remain underexplored. A comprehensive search was performed using the UnoPerTutto metadatabase, identifying 2891 records. After duplicate removal (1619 records) and screening, 61 full-text reports were assessed for eligibility, resulting in the inclusion of 10 studies. The studies varied in methodology, including qualitative assessments, mixed-methods approaches, quasi-experimental designs, and a randomized controlled trial (RCT). AI models such as ChatGPT-4, ChatGPT-3.5, and Google Gemini were evaluated across different contexts, including strength training, rehabilitation, cardiovascular exercise, and general fitness programs. Findings indicate that generative AI-generated training programs generally adhere to established exercise guidelines but often lack specificity, progression, and adaptability to real-time physiological feedback. AI-generated recommendations were found to emphasize safety and broad applicability, making them useful for general fitness guidance but less effective for high-performance training. GPT-4 demonstrated superior performance in generating structured resistance training programs compared to older AI models, yet limitations in individualization and contextual adaptation persisted. A critical appraisal using the METRICS checklist revealed inconsistencies in study quality, particularly regarding prompt specificity, model transparency, and evaluation frameworks. While generative AI holds promise for democratizing access to structured exercise prescriptions, its role remains complementary rather than substitutive to expert guidance. Future research should prioritize real-time adaptability, integration with physiological monitoring, and improved AI-human collaboration to enhance the precision and effectiveness of AI-driven exercise recommendations. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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15 pages, 1306 KiB  
Systematic Review
Periodontal Disease in Saudi Arabia: A Systematic Review of Prevalence and Associated Risk Factors
by Thani Alsharari, Mohammed Fareed Felemban, Osama Khattak, Fahad Saeed Algahtani and Abdulrahman Alzahrani
Diagnostics 2025, 15(7), 812; https://doi.org/10.3390/diagnostics15070812 - 22 Mar 2025
Viewed by 617
Abstract
Background/Objectives: The oral health disorder periodontal disease is widespread around the world and has a public health dimension. This study aimed to perform a systematic review and an appraised analysis that looks at both the prevalence and diversity of risk factors associated [...] Read more.
Background/Objectives: The oral health disorder periodontal disease is widespread around the world and has a public health dimension. This study aimed to perform a systematic review and an appraised analysis that looks at both the prevalence and diversity of risk factors associated with periodontal disease in Saudi Arabia. It places a particular focus on subgroup analyses and pooled prevalence estimates to identify certain populations that could be described as high risk. Methods: Several databases, including PubMed, Scopus, and Google Scholar, were used to conduct the present systematic review. The search was designed to identify relevant studies published from 1980 to 2023. Both quantitative and qualitative studies were included. Subgroup analyses and meta-analyses were performed using a random-effects model to calculate pooled prevalence rates. The studies were evaluated using three criteria that focused on bias. Finally, the authors created a narrative synthesis of the review findings for ease of understanding. Results: The pooled overall prevalence of periodontal disease was 46.2% (95% CI: 40.5–51.8), with high heterogeneity (I2 = 85%). Subgroup analyses identified obese adults as having the highest prevalence of this condition (71.3%), and individuals diagnosed with diabetes also displayed a significantly high prevalence (52.1%). Adolescents aged 15–19 years had an age-specific prevalence of 8.6%, which was significantly lower than that of the other age groups analyzed. Poor oral hygiene, tobacco use, diabetes, and obesity have been recognized as risk factors for periodontal disease. Conclusions: The substantial burden of periodontal disease in Saudi Arabia, especially among high-risk groups, such as obese and diabetic adults, cannot be overstated. Our public health initiatives need to focus on these high-risk individuals, who are likely to be both periodontally and systemically compromised, to provide lifestyle modification counseling and oral hygiene education for them, as well as to routinize their dental care in a way that minimizes the chances of becoming periodontally compromised. Full article
(This article belongs to the Special Issue Periodontal Disease: Diagnosis and Management)
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