Search Results (11)

Cyberattacks in education are a serious concern (e.g., breaches and system intrusions) that teachers need to respond to by cultivating cybersecurity awareness, engaging in continuous professional development, and modeling safe digital practices in their daily work, while technical prevention and mitigation are primarily the responsibility of institutional IT services and system-level governance. Strengthening cybersecurity depends on fostering awareness of how information is collected, analyzed, and used, thereby enabling users to take proactive steps to protect data, which are key components of teachers’ professional media literacy, particularly in managing personal and student information across social media, email, and cloud platforms. This quantitative study was conducted in Hong Kong with 120 early childhood, primary, secondary, and tertiary education teachers (88.3% female, age range = 18–54, Mage = 23.76) via an online survey. The study focused on social media, email, and cloud storage, and administered the Perceived Severity, Perceived Vulnerability, and Self-Efficacy Scales; the Data Protection Strategies Scale; and the Data Fabrication Strategies Scale, along with questions assessing awareness of data protection. Results revealed significant positive relationships among data protection awareness, psychological factors, and use of protection strategies. Awareness and protection strategies were also moderately linked to data fabrication behaviors. The findings indicate concerning gaps in teachers’ awareness of cyberattacks and their limited understanding of media literacy concepts, highlighting the need to integrate comprehensive media literacy training into teacher education programs and also provide intensive, mandatory on-site training for in-service early childhood, primary, secondary, and tertiary education teachers. Full article

Background: Appropriate medication management before surgery is essential to minimise perioperative risk. Patient adherence to preoperative medication advice demonstrates considerable variability and is influenced by multiple interacting factors. This study assessed patient understanding and adherence to preoperative medication advice provided in the Pre-Admission Clinic (PAC) and identified factors contributing to non-adherence. Methods: A cross-sectional survey study was conducted over 12 weeks in 2022 at a tertiary hospital. Adult patients scheduled for elective surgery who received preoperative medication advice in PAC were surveyed on the day of surgery. Data collected included demographics, clinical characteristics, adherence, reasons for non-adherence, and communication preferences. Descriptive and inferential statistics were used for analysis. Results: Of 156 participants, 91 (58.3%) adhered to medication advice, while 65 (41.7%) did not. Common reasons for non-adherence included forgotten advice (35.4%), misunderstood advice (33.8%), and intentional deviation due to surgery (18.5%). Non-adherence rates were highest for NSAIDs (50.0%) and P2Y12 inhibitors (45.5%). Two surgeries were cancelled due to the delayed cessation of anticoagulants. Non-adherence was significantly associated with a greater number of medications requiring perioperative management (p = 0.004) and a longer duration between PAC and surgery (p = 0.010). Most non-adherent patients (64.7%) preferred a combination of verbal and written advice. Conclusions: A substantial proportion of patients were non-adherent to preoperative medication advice, often due to unclear communication or a lack of understanding of the clinical rationale for the advice. Multimodal strategies, including written or digital reinforcement of verbal advice, multidisciplinary collaboration, and patient-centred education, may improve adherence and reduce preventable cancellations. Future studies should evaluate the impact of these interventions. Full article

Background: Cervical artery dissection (CAD) is a leading cause of acute ischemic stroke among young and middle-aged patients. Currently, the growing availability of high-resolution magnetic resonance imaging (MRI), particularly fat-saturated T1-weighted black-blood SPACE sequences, allows the non-invasive, rapid, and reliable diagnosis of multiple arterial dissections. Methods: We reported our experience from two tertiary stroke centers of patients diagnosed with spontaneous multiple cervical artery dissections, detected with high-resolution MRI, during a three-year period (2022–2025). Results: Among 95 consecutive patients with CAD, 11 patients (mean age: 48 ± 9 years, 6 (55%) females) were diagnosed with multiple symptomatic or asymptomatic CADs, whereas in 84 patients (mean age: 49 ± 11 years, 32 (38%) females) a single CAD was detected. In all patients, high-resolution MRI and MR-angiography were performed, whereas digital subtraction angiography (DSA) with simultaneous evaluation of renal arteries was conducted in nine patients. A history of trauma or chiropractic manipulations, intense physical exercise prior to symptom onset, recent influenza-like illness, and recent childbirth in a young female patient were reported as predisposing risk factors. Cervicocranial pain, cerebral infarctions leading to focal neurological signs, and Horner’s syndrome were among the most commonly documented symptoms. Characteristic findings in the high-resolution 3D T1 SPACE sequence were detected in all patients. Fibromuscular dysplasia and Eagle syndrome were detected in four patients and one patient, respectively. Eight patients were treated with antiplatelets, whereas three patients received anticoagulation with low-molecular-weight heparin. There was only one case of stroke recurrence during a mean follow-up period of 9 ± 4 months. Conclusions: This case series highlights the utility of specific high-resolution MRI sequences as a very promising method for detecting multiple CADs in young patients. The systematic use of these sequences could enhance the sensitivity of detecting multiple cervical CADs, affecting also the thorough investigation for underlying connective tissue vasculopathies, stratifying the risk for first-ever or recurrent ischemic stroke, and influencing acute reperfusion and secondary prevention therapeutic strategies. Full article

Background/Objectives: Adolescent idiopathic scoliosis (AIS) often requires prolonged brace use to prevent curve progression. However, adherence is challenging due to discomfort, mobility restrictions, and psychosocial stressors. This study evaluated the feasibility and clinical utility of a mobile health (mHealth) system for real-time tracking of brace adherence and treatment-related experiences in adolescents with AIS. Methods: Thirty adolescents with AIS (mean age = 12.9, SD = 1.8) undergoing brace treatment at a tertiary care center used a custom app for 90 days. The app collected daily self-reports on brace wear duration, discomfort, movement limitations, emotional distress, and social challenges. A clinical alarm system alerted providers when patient input indicated potential concerns. Primary outcomes were feasibility (adherence to daily use and usability ratings) and brace adherence. Secondary outcomes included the app’s capacity to identify treatment-related challenges and its association with changes in stress, quality of life, anxiety, and depression. Results: Participants reported meeting recommended brace wear time (≥16 h/day) on 84.8% of days. The app triggered 186 clinical alarms, with the most frequent related to emotional distress (23.1%) and pain (15.6%). Alarm frequency declined over time. Improvements of ≥20% in psychological outcomes were observed in 20–26.7% of participants, while group-level changes were nonsignificant. Conclusions: mHealth-based monitoring appears feasible and acceptable for digitally engaged adolescents with AIS. The app supported early detection of treatment barriers and prompted timely clinical responses. Despite limitations, it shows promise as a tool to improve treatment engagement and address psychosocial challenges in scoliosis care. Full article

Student attrition at tertiary institutions is a global challenge with significant personal and social consequences. Early identification of students at risk of dropout is crucial for proactive and preventive intervention. This study presents a machine learning framework for predicting and visualizing students at risk of dropping out. While most previous work relies on wide-ranging data from numerous sources such as surveys, enrolment, and learning management systems, making the process complex and time-consuming, the current study uses minimal data that are readily available in any registration system. The use of minimal data simplifies the process and ensures broad applicability. Unlike most similar research, the proposed framework provides a comprehensive system that not only identifies students at risk of dropout but also groups them into meaningful clusters, enabling tailored policy generation for each cluster through digital technologies. The proposed framework comprises two stages where the first stage identifies at-risk students using a machine learning classifier, and the second stage uses interpretable AI techniques to cluster and visualize similar students for policy-making purposes. For the case study, various machine learning algorithms—including Support Vector Classifier, K-Nearest Neighbors, Logistic Regression, Naïve Bayes, Artificial Neural Network, Random Forest, Classification and Regression Trees, and Categorical Boosting—were trained for dropout prediction using data available at the end of the students’ second semester. The experimental results indicated that Categorical Boosting with an F1-score of 82% is the most effective classifier for the dataset. The students identified as at risk of dropout were then clustered and a decision tree was used to visualize each cluster, enabling tailored policy-making. Full article

Background: Screening for cardiovascular disease (CVD) and its associated risk factors in childhood facilitates early detection and timely preventive interventions. However, limited data are available regarding screening tools and their diagnostic yield when applied in unselected pediatric populations. Aims: To evaluate the performance of a CVD screening program, based on history, 12-lead ECG and phonocardiography, applied in primary school children. Methods: The methods used were prospective study, with voluntary participation of third-grade primary school children in the region of Crete/Greece, over 6 years (2018–2024). Personal and family history were collected by using a standardized questionnaire and physical evaluation (including weight, height, blood pressure measurement), and cardiac auscultation (digital phonocardiography (PCG)) and 12-lead electrocardiogram (ECG) were recorded at local health stations (Phase I). Following expert verification of responses and obtained data, assisted by designated electronic health record with incorporated decision support algorithms (phase II), pediatric cardiology evaluation at the tertiary referral center followed (phase III). Results: A total of 944 children participated (boys 49.6%). A total of 790 (83.7%) had Phase I referral indication, confirmed in 311(32.9%) during Phase II evaluation. Adiposity (10.8%) and hypertension (3.2%) as risk factors for CVD were documented in 10.8% and 3.2% of the total population, respectively. During Phase III evaluations (n = 201), the majority (n = 132, 14% of total) of children were considered as having a further indication for evaluation by other pediatric subspecialties for their reported symptoms. Abnormal CVD findings were present in 69 (7.3%) of the study population, including minor/trivial structural heart disease in 23 (2.4%) and 17 (1.8%), respectively, referred due to abnormal cardiac auscultation, and ECG abnormalities in 29 (3%), of which 6 (0.6%) were considered potentially significant (including 1 case of genetically confirmed channelopathy-LQT syndrome). Conclusions: CVD screening programs in school children can be very helpful for the early detection of CVD risk factors and of their general health as well. Expert cardiac auscultation and 12-lead ECG allow for the detection of structural and arrhythmogenic heard disease, respectively. Further study is needed regarding performance of individual components, accuracy of interpretation (including computer assisted diagnosis) and cost-effectiveness, before large-scale application of CVD screening in unselected pediatric populations. Full article

As chronic illness is common among older people, self-care practices for older people are needed to control health status, to prevent possible complications and to ensure optimal quality of life. The literature has demonstrated that integrated care approaches are one key success factor for delivering person-centered and sustainable care for older people, with rehabilitation being a cornerstone in tertiary care prevention for older citizens. The current paper addresses the state of the literature for person-centered geriatric rehabilitation (GR) and the importance of personalized and participatory goal setting. In accordance with the bio–psycho–social model of the International Classification of Functioning, Disability and Health (ICF), social participation and the related goals are of particular importance for the entire rehabilitation process. The social participation of individuals enrolled into GR is therefore one of the milestones to be achieved during GR. Personalized goal setting during the entire rehabilitation process, Comprehensive Geriatric Assessment (CGA) and shared decision making allow a comprehensive care approach separate from solely function-based rehabilitation. The review also focusses on recent developments in digitalization in healthcare and delivers insights into how healthcare professionals’ collaborative practice supports sustainable rehabilitation results in patients of advanced chronological age. Full article

Quality Control (QC) and Quality Assurance (QA) principles are essential for effective cervical cancer prevention. Being a crucial diagnostic step, colposcopy’s sensitivity and specificity improvements are strongly advocated worldwide since inter- and intra-observer differences are the main limiting factors. The objective of the present study was the evaluation of colposcopy accuracy through the results of a QC/QA assessment from a survey in Italian tertiary-level academic and teaching hospitals. A web-based, user-friendly platform based on 100 colposcopic digital images was forwarded to colposcopists with different levels of experience. Seventy-three participants were asked to identify colposcopic patterns, provide personal impressions, and indicate the correct clinical practice. The data were correlated with a panel of experts’ evaluation and with the clinical/pathological data of the cases. Overall sensitivity and specificity with the threshold of CIN2+ accounted for 73.7% and 87.7%, respectively, with minor differences between senior and junior candidates. Identification and interpretation of colposcopic patterns showed full agreement with the experts’ panel, ranging from 50% to 82%, in some instances with better results from junior colposcopists. Colposcopic impressions correlated with a 20% underestimation of CIN2+ lesions, with no differences linked to level of experience. Our results demonstrate the good diagnostic performance of colposcopy and the need for improving accuracy through QC assessments and adhesion to standard requirements and recommendations. Full article

Objective: The largest pandemic in history, the COVID-19 pandemic, has been declared a doomsday globally. The second wave spreading worldwide has devastating consequences in every sector of life. Several measures to contain and curb its infection have forged significant challenges for the education community. With an estimated 1.6 billion learners, the closure of schools and other educational institutions has impacted more than 90% of students worldwide from the elementary to tertiary level. Methods: In a view to studying impacts on student’s fraternity, this article aims at addressing alternative ways of educating—more specifically, online education—through the analysis of Google trends for the past year. The study analyzed the platforms of online teaching and learning systems that have been enabling remote learning, thereby limiting the impact on the education system. Thorough text analysis is performed on an existing dataset from Kaggle to retrieve insight on the clustering of words that are more often looked at during this pandemic to find the general patterns of their occurrence. Findings: The results show that the coronavirus patients are the most trending patterns in word search clustering, with the education system being at the control and preventive measures to bring equilibrium in the system of education. There has been significant growth in online platforms in the last year. Existing assets of educational establishments have effectively converted conventional education into new-age online education with the help of virtual classes and other key online tools in this continually fluctuating scholastic setting. The effective usage of teaching tools such as Microsoft Teams, Zoom, Google Meet, and WebEx are the most used online platforms for the conduction of classes, and whiteboard software tools and learning apps such as Vedantu, Udemy, Byju’s, and Whitehat Junior have been big market players in the education system over the pandemic year, especially in India. Conclusions: The article helps to draw a holistic approach of ongoing online teaching-learning methods during the lockdown and also highlights changes that took place in the conventional education system amid the COVID pandemic to overcome the persisting disruption in academic activities and to ensure correct perception towards the online procedure as a normal course of action in the new educational system. To fill in the void of classroom learning and to minimize the virus spread over the last year, digital learning in various schools and colleges has been emphasized, leading to a significant increase in the usage of whiteboard software platforms. Full article

Physical rehabilitation of stroke patients is based on the daily execution of exercises with face-to-face supervision by therapists. This model cannot be sustained in the long term, due to the involved economic costs, the growing number of patients, and the aging population. Remote rehabilitation tools have emerged to address this unmet clinical need, but they face the double challenge of motivating patients and ensuring an effective remote rehabilitation. In this context, exergames allow patients to play while performing repetitive therapeutic tasks in a safe and ecological environment. This work proposes the design of Personalized Exergames Language (PEL), a language whose sentences can be processed via software in order to automatically generate exergames. The definition of exergames through PEL, guided by an effective methodology of the design and generation of personalized exergames, will include both game mechanics and the necessary metrics to monitor, guide, and adapt the rehabilitation of each patient. The integration of authoring tools are considered to visually guide the therapist when designing exergames. A study has been carried out with stroke patients and therapists from a hospital and two community centers, in order to evaluate several exergames, automatically generated using PEL, in terms of usability, understanding, and suitability. Full article

Physical rehabilitation of patients affected by neurological diseases is currently an unmet clinical need due to the high cost of health systems and the impact that rehabilitation has on patients and their families. This paper introduces an approach based on the idea of precision rehabilitation, where personalization of the physical rehabilitation for each patient and accessibility to technological tools that support it are pursued. A general architecture that contemplates functional modules related to multiple work areas and different roles is proposed. One of these modules is related to gamification and delves into the design and development of exergames, defined from a general data model, in order to increase the level of patient motivation when exercising. The paper discusses the creation and evaluation of an exergame designed for the rehabilitation of lower limbs. Full article