Search Results (17)

Background: Diabetic Foot Ulcers (DFU) are a common complication of diabetes, often leading to infections, amputations and even death if left untreated. Effective management of the Diabetic Foot (DF) requires timely detection and frequent monitoring. Current DF assessment methods, by healthcare professionals, are largely based on visual inspection of feet, together with touch, temperature, and vibration sensitivity, and pedal pulse. Methods: The paper describes a machine-learning approach for the assessment of DF from feet images, combining pre-trained convolutional neural networks (CNN) with Generative AI for dataset annotation. Specifically, the GPT-4o-mini model was used to assign risk labels (Low, Medium or High Risk) to individual foot images, following a structured designed prompt for this task. The labeled dataset was used to train and evaluate two pre-trained CNN architectures, namely, ResNet50 and VGG16. Output predictions are obtained by aggregating the prediction for each of the images of a patient. Results: The results obtained show that both ResNet50 and VGG16 achieved good overall performance, with ResNet50 showing superior results. The High Risk class achieved the highest performance. The Low and Medium Risk classes also showed good performance but were prone to confusion due to the similar features of the images belonging to those classes. Conclusions: The technical contribution of the paper is a Streamlit App, available online for public use, showcases the work. The primary scientific contribution is the demonstration of how Generative AI can be used to train common CNN and automate a highly relevant healthcare process. Full article

The increasing use of digital technologies (DT) among university students has raised concerns about their associations with mental health (MH) and academic performance. Grounded in the Diversity in Learning (DinL) framework, this cross-sectional study examines how age and sex moderate the relationships between DT use, MH indicators, learning-related psychological difficulties, and academic outcomes. Data were collected through an online questionnaire administered to 4519 university students in Chile. The survey included self-reported measures of MH indicators and learning-related psychological difficulties (bad mood/irritability, anxiety, lack of motivation, attentional difficulties, and low achievement expectations), as well as academic performance and frequency of use of digital tools (social media, smartphones, gamification and collaboration applications, and asynchronous classes). Descriptive analyses, ANOVAs, and multiple regression models were employed. Results showed that younger students reported more frequent use of gamification apps, social media, and smartphones, as well as higher levels across all mental health issues and learning-related psychological difficulties. Social media use and particularly smartphone use emerged among the DT variables as the strongest predictors of MH problems and learning difficulties, with age significantly moderating these relationships. These predictors were significant for both young female and male students, although stronger associations were observed among females. Female students reported higher levels of MH problems (especially anxiety), as well as greater use of social media and smartphones. However, neither social media use nor smartphone use showed a consistent negative relationship with academic performance. Overall, these findings highlight the importance of considering age and sex differences when examining the links between digital engagement and student well-being. They also underscore the need for targeted interventions to promote healthier digital habits and emotional regulation strategies, particularly among higher-risk groups. Full article

An influx of new mobility trends such as fare-free bus transportation, ride hail, and e-scooter services to improve access and affordability of transportation on campus may be shifting the travel behavior of campus patrons such that it affects their long-term health outcomes. The main research questions explored in this study are as follows: (1) why university patrons choose new modes of travel?; (2) what existing mode did the new modes of travel replace for the riders?; and (3) is the average body mass index (BMI) of users primarily using non-motorized transit options lower than those using motorized or both (referred to as hybrid) for on-campus travel needs? An online survey was administered to a campus community (n = 3309) including students (48%), faculty (15%), and staff (37%) in fall of 2018 when fare-free bus transportation and e-scooters became available on campus, and a gradual increase in ridership of ride-hail services was simultaneously observed. This study found that campus patrons were more inclined to replace active modes of travel with affordable and accessible modes of transportation, thereby substituting their walking or biking routine with app-based transportation services. The mean BMI among travelers who chose motorized transportation modes was more than active travelers, and the BMI was statistically significantly associated with age, gender, race, class standing (undergraduate/graduate), and residence on/off campus. This study concludes with suggestions to prevent substitution of active with non-active transport choices and provides policy guidelines to increase awareness on achieving physical activity levels through active modes of travel for university patrons. Full article

The aims of the present study are: (1) to determine classes of adolescents with homogeneous patterns of smartphone or social media use; and (2) to examine the level of distress across the empirically derived profiles. Three hundred and forty adolescents (M_age = 15.61, SD = 1.19; 38.2% females) participated in a cross-sectional survey. Participants provided objective trace data on time spent on smartphones and applications, as well as self-reported social media addiction, social media use intensity, online social comparison, emotion dysregulation, and psychological distress. Latent class analysis (LCA) with total smartphone use categorized participants into three classes. Participants in Class 3 (19%) showed a more impaired functioning profile, with a tendency towards social media addiction and greater levels of distress. LCAs with the amount of time devoted to specific applications are more heterogeneous, and results showed that heavy use of social media apps was not consistently connected to the most impaired psychosocial profiles. Although the amount of mobile screen time can be a characteristic of problematic users, the link between social media usage and an adolescent’s psychological characteristics is mixed. More research is needed to explore the interplay between mobile screen time and social media usage among adolescents. Full article

Background: At-risk alcohol use, particularly binge drinking, is widespread among adolescents and young adults in most Western countries. MobileCoach Alcohol is a mobile app-based program for alcohol prevention that provides individualized coaching using a conversational agent. The current study tested the acceptance, use, and evaluation of this newly developed program and explored its potential effectiveness. Methods: Longitudinal pre–post study among upper secondary and vocational school students in Switzerland. Within the MobileCoach Alcohol prevention program, a virtual coach motivated participants to deal with alcohol sensitively, and provided feedback on alcohol use and strategies to resist alcohol for a period of 10 weeks. Information was provided in weekly dialogs, within contests with other participants, and interactive challenges. By means of a follow-up survey after the end of the 10-week program, indicators of the use, acceptance, and effectiveness of the program were examined. Results: Between October 2020 and July 2022, the program was advertised in upper secondary and vocational schools. Recruiting schools and school classes was difficult due to the COVID-19 containment measures in place during this period. Nevertheless, the program could be implemented in 61 upper secondary and vocational school classes with a total of 954 participating students. Three out of four students who were present in the school classes participated in the MobileCoach Alcohol program and the associated study. Online follow up assessment at week 10 was completed by 272 program participants (28.4%). Based on program use and evaluations by the participants, the overall acceptance of the intervention was good. The proportion of students who engaged in binge drinking was significantly reduced from 32.7% at baseline to 24.3% at follow up. Furthermore, the longitudinal analyses revealed decreases in the maximum number of alcoholic drinks consumed on an occasion and the mean number of standard drinks per month, whereas self-efficacy to resist alcohol increased between baseline and follow up. Conclusions: The mobile app-based MobileCoach Alcohol program proved to be an attractive intervention, in which the majority of students were interested when proactively recruited at school classes. It allows for individualized coaching in large groups of adolescents and young adults and is promising for reducing at-risk alcohol use. Full article

The pharmacy education and its educators have to expose the student pharmacists to a plethora of activities regarding health disparities. It is essential for student pharmacists to be introduced to the key elements that comprise the Social Determinants of Health (SDOH) during their didactic curriculum. However, while there have been efforts made in the United States to incorporate the SDOH in the pharmacy curricula, there is limited research on student pharmacists’ perspectives of how content in the didactic curriculum prepared them to provide patient care. A quantitative approach was used for this study. For the Class of 2023, activities were added to a skills-based course series and a professional development course series to introduce, apply, and illustrate how SDOH can impact pharmacist-provided care and patient health experiences. As part of the College’s assessment plan, a survey is sent to the third-year student pharmacists in January prior to beginning Advanced Pharmacy Practice Experiences (APPEs). The online survey consists of 24 Likert Scale questions with five choices ranging from Strongly Agree to Strongly Disagree and not applicable. Four of the 24 questions pertained to health disparities and SDOH and were evaluated in this study. The responses were analyzed using SPSS for Windows, version 25.0 (IBM Corporation, Armonk, NY, USA). Descriptive statistics were calculated for all variables. Chi-square tests were used for all nominal data and Mann–Whitney test was used for all nonparametric numeric data. A total of 530 student pharmacists completed the survey. The mean age was 26 years and majority of the respondents identified as female (64%). More students strongly agreed that they had the ability to identify and address SDOH to improve access to or the delivery of healthcare in the class of 2023 (51.4%) compared to the class of 2022 (37.8%) and class of 2021 (35.8%). In addition, the mean survey score for the question between the class of 2023 improved significantly compared to the class of 2022 (p = 0.015) and 2021 (p = 0.004). Overall, this study suggests that longitudinal activities involving SDOH can improve student pharmacists’ assessment of their abilities to interact with and care for a diverse patient population. The results suggest that the curriculum activities implemented to address a plethora of patients improve student assessment of their abilities to identify and incorporate SDOH in providing patient-centered care. Full article

This study examines fitness app use patterns and their correlates among Chinese users from the perspectives of uses and gratification theory and self-determination theory. Our sample comprised 632 users of WeRun, the fitness plugin of WeChat, the largest Chinese mobile social networking app; participants completed an online survey and provided self-tracked physical activity data, which were subjected to latent class analysis. Based on the four-class latent class model (which yielded the best model fit and the most interpretable results), 30.5%, 27.5%, 24.7%, and 17.3% of the users were categorized as light users, reward-oriented users, lifestyle-oriented users, and interaction-oriented users, respectively. Moreover, class membership was associated with gender, age, education, income, life satisfaction, autonomy, and platform-based motivations. There is a significant heterogeneity in fitness app use and exercise behaviors. Platform-based motivations and autonomy are important classification factors, as users are looking for specific kinds of gratification from their use of fitness apps. Demographics and individual characteristics are also explanatory factors for class membership. The study findings suggest that fitness app designers should segment users based on motivation and gratification. Full article

Online learning has emerged as a fresh method to successfully prevent teacher and student gatherings as well as the propagation of viruses in the context of the ongoing influence of the COVID-19. A problem deserving of consideration is how to increase users’ desire to participate in online learning through online class APPs, identify the variables that affect users’ use of them, and create a useful assessment scale. In this study, user ratings from 68 students who had used an online class APP were collected using the combination of qualitative and quantitative research, and 200 online questionnaires were sent out to complement the interview findings, based on which 328 assessment questionnaires were gathered and 23 valid items were obtained. The influencing elements that had an impact on users’ online learning experiences were identified using factor analysis, and the relationships among the components were investigated using structural equation modeling. Perceived benefits are the main influencing factors, subjective norms and functional quality are the direct factors influencing users’ perceived benefits, and self-efficacy is influenced by subjective norms while promoting the perception of functional quality. The factors influencing users’ use of online class APPs are ultimately identified as perceived benefits, functional quality and self-efficacy. In order to facilitate users’ online learning, user psychological traits, social ties and software functions should be integrated into a cohesive system while designing online class APPs. Full article

Internet traffic classification is a beneficial technique in the direction of intrusion detection and network monitoring. After several years of searching, there are still many open problems in Internet traffic classification. The hybrid classifier combines more than one classification method to identify Internet traffic. Using only one method to classify Internet traffic poses many risks. In addition, an online classifier is very important in order to manage threats on traffic such as denial of service, flooding attack and other similar threats. Therefore, this paper provides some information to differentiate between real and live internet traffic. In addition, this paper proposes a hybrid online classifier (HOC) system. HOC is based on two common classification methods, port-base and ML-base. HOC is able to perform an online classification since it can identify live Internet traffic at the same time as it is generated. HOC was used to classify three common Internet application classes, namely web, WhatsApp and Twitter. HOC produces more than 90% accuracy, which is higher than any individual classifiers. Full article

Many scholarly articles on remittance have focused on its positive or negative impact on the macro- or microeconomy. Given that trend, remittance is usually analysed without its sociological elements embedded within the migration process. Therefore, this paper employs a bird’s eye view to advance our understanding of the dynamics of remittance within the Ghanaian migration framework. By this, the paper uses a mixed-method approach to shed light on the Ghana case. First, through multiple linear regression, the paper shows that remittance inflow to Ghana is positively related to GDP per capita. Specifically, the evidence indicates that a 1% increase in remittance leads to an approximately 4% increase in the GDP per capita. Second, with the aid of household survey data from Ghana Statistical Service and Ghana’s poverty dimension, the paper shows that while the empirical finding suggests an improvement of the populace’s standard of living, the evidence on the grounds, however, conflicts with such findings. This is because remittance is primarily a private resource and is likely to reach only a few well-off homes in Ghana; hence, it does not consider an effective redistributive dimension. Third, to further elucidate why remittance reaches these few groups, the paper analyses within the Marxist political framework how legal migration to the developed countries has always been an option only for the well-off and middle-class Ghanaians who could afford the cost. With this clear establishment of the remittance dynamics in Ghana, the study proposes plausible suggestions to enhance the redistributive effect of remittance in Ghana. In particular, the study recommends a state-led online app for migrants to send money to Ghana. Notably, the state should champion this agenda because subsidising the transaction fees would make it relatively cheaper for migrants. While this would encourage migrants to use the official means, which undoubtedly is significant for the macroeconomy, the app’s returns could be used in addressing the country’s social inequality gap at the micro-level. Full article

Due to increasing algae bloom occurrence and water degradation on a global scale, there is a demand for water quality monitoring systems based on remote sensing imagery. This paper describes the scientific, theoretical, and methodological background for creating a cloud-computing interface on Google Earth Engine (GEE) which allows end-users to access algae bloom related products with high spatial (30 m) and temporal (~5 day) resolution. The proposed methodology uses Sentinel-2 images corrected for atmospheric and sun-glint effects to generate an image collection of the Normalized Difference Chlorophyll-a Index (NDCI) for the entire time-series. NDCI is used to estimate both Chl-a concentration, based on a non-linear fitting model, and Trophic State Index (TSI), based on a tree-decision model classification into five classes. Once the Chl-a and TSI algorithms had been calibrated and validated they were implemented in GEE as an Earth Engine App, entitled Algae Bloom Monitoring Application (AlgaeMAp). AlgaeMAp is the first online platform built within the GEE platform that offers high spatial resolution of water quality parameters. The App benefits from the huge processing capability of GEE that allows any user with internet access to easily extract detailed spatial (30 m) and long temporal Chl-a and TSI information (from August 2015 and with images every 5 days) throughout the most important reservoirs in the State of São Paulo/Brazil. The application will be adapted to extend to other relevant areas in Latin America. Full article

Contemporary mobile technologies offer tablets and smartphones that elicit young children’s active participation in various educational apps, dramatically transforming playing, learning, and communication. Even the most knowledgeable users face difficulties in deciding about the value and appropriateness of the so-called educational apps because of many factors that should be considered. Their importance for children’s attitudes is affected by the perceived positive and negative aspects, which vary across a multiplicity of criteria. Filling the gap in the relevant literature, a new instrument, named PEAU-p (Perceptions about Educational Apps Use–parents), was developed and validated in the present study designed to measure parents’ perception of educational apps for kindergarten pupils. Data (N = 435) were collected via online procedures, and the psychometric properties of PEAU-p were studied via exploratory and confirmatory methods. Principal Components Analysis extracted six factors, namely Usability, Enjoyment, Involvement, Learning, Worries, and Values, which explained 72.42% of the total variance. Subsequently, by implementing Latent Class Analysis based on the above factors, four Clusters (i.e., parents’ Profiles) were extracted corresponding to their perceptions and attitudes towards the educational apps used for kindergarten pupils. Those were named as ‘mild attitude’, ‘negative attitude’, ‘positive attitude’, and ‘indifferent attitude’. This categorization, besides the statistical support, is fully interpretable, and the profiles were associated with certain covariates, such as age, the number of children, knowledge on new technologies, or distal outcomes, e.g., the frequency of using apps, the general position towards apps or their intention to recommend apps use. The findings are discussed within the current research field, investigating the influential role parents play in young children’s media selection and use. 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

In the present educational context, active methodologies and new technologies are aspects that should be included when teaching and learning a subject area. For the education to be successful, classroom management must be considered, since problems may arise and handicap this process. In order to promote learning and reduce negative behaviors and increase positive ones, intervention on students of 1st year of ESO (compulsory secondary education) was implemented. The intervention used gamification as the educational approach and ClassDojo as the online tool to track behavior to determine the effectiveness of both elements to achieve the goal. Taking advantage of the game design principles and mechanics in the learning environment to create motivation and interest, in addition to the information and communication technologies (ICT) represented by ClassDojo, the experimental study showed the benefit of this method and app regarding the improvement of desired behaviors as well as the decrease of the disruptive ones. The implementation engaged the students and activated their behavioral development in order to display a better performance. Full article

This research is based on empirical surveys conducted in two Chinese cities, Beijing and Chengdu, which examine employment relationships, labor protection and social protection in the new digital economy. Through these theoretically informed surveys on various forms of employment via online platforms, we have found that the organizational principles and functional patterns of employment have profoundly transformed in the epoch of digitalization. The traditional employment relationship characterized by written contracts with clearly defined entitlements and obligations for employers and employees have been increasingly substituted by new volatile, fluid and fragile employment forms, softening the labor rights and social rights of “digital employees” and strengthening social control over them through online evaluation systems supported by smart phones and apps. The employees engaged in the online sharing economy have become more individualized and atomized than ever before, resulting in the emergence of an unorganized and disenfranchised “digital working class”. Full article