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Background: Given that students from socio-economically disadvantaged family backgrounds are more likely to suffer from low academic performance, there is an interest in identifying features of academic resilience, which may mitigate the relationship between disadvantaged socio-economic status and academic performance. Aims: This study sought to combine machine learning and explainable artificial intelligence (XAI) technique to identify key features of academic resilience in mathematics learning during COVID-19. Materials and Methods: Based on PISA 2022 data in 79 countries/economies, the random forest model coupled with Shapley additive explanations (SHAP) value technique not only uncovered the key features of academic resilience but also examined the contributions of each key feature. Results: Findings indicated that 35 features were identified in the classification of academically resilient and non-academically resilient students, which largely validated the previous academic resilient framework. Notably, gender differences were shown in the distribution of some key features. Research findings also indicated that resilient students tended to have a stable emotional state, high levels of self-efficacy, low levels of truancy and positive future aspirations. Discussion: This study has established a research paradigm essentially methodological in nature to bridge the gap between psychological theories and big data in the field of educational psychology. Conclusion: To sum up, our study shed light on the issues of education equity and quality from a global perspective in the times of the COVID-19 pandemic.

The era of information and communication technology (ICT) has popularized adolescents' digital reading activities in their daily lives. Most prior studies focused on identifying significant factors that foster digital reading performance. Although educational quality is of great concern, it is crucial to consider the issue of educational equity in the digital world. Our study aims to unfold the mediating roles of ICT-related psychological needs between economic, social, and cultural status (ESCS) and digital reading performance. A multilevel mediation analysis was adopted for 36,490 students from six high-performing Asian regions participating in the Programme for International Student Assessment (PISA). The results indicated that perceived ICT autonomy significantly mediated the relationship in most Asian regions, while perceived ICT competence yielded mixed roles. Interestingly, the suppression effects were detected between ESCS, ICT in social interaction, and digital reading. Our research findings offer fresh insights into narrowing the digital divide in the online reading environment for adolescents.

Although academic resilience is of great concern to contemporary educational practitioners, there is no consensus on its measurement. Furthermore, protective factors characterized by East Asian societal contexts remain ambiguous. This systematic review aims to offer an overview of the operational definitions, statistical methodology, and protective factors of academic resilience identified in East Asian countries/economies. With a focus on large-scale assessment (LSA) research, three databases (i.e., Web of Science, CNKI, and AiritiLibary) were searched and returned 31 peer-reviewed studies over the last decade. Results indicated that the definition-driven method was commonly adopted in international LSA studies (e.g., Programme for the International Student Assessment) to measure academic resilience, and the research conducted in national/regional LSA (e.g., China Education Panel Survey) tended to use the process-driven approach. Logistic regression was the most frequently data analysis technique utilized in the definition-driven approach, while structural equation modeling and mediation/moderation analyses accounted for the largest proportion of the process-driven methods. Our study shed light on the methodological issues of academic resilience in LSA. Additionally, it highlights the aspiration of educational researchers to identify Asian-specific protective factors from the social-ecological perspective to propose appropriate interventions fostering academic resilience.

Collaborative problem-solving competence (CPSC) is a core skill in the twenty-first century. As an innovative literacy, CPSC was assessed for the first time in the Program for International Student Assessment (PISA) 2015. Our study aims to identify the effects of student's perceptions toward interpersonal relationships on CPSC in PISA 2015. Multiple linear regression was used to examine these effects across Hong Kong, Macao, Taiwan, and the four affluent communities in China. After controlling student's gender and socio-economic status, the results indicated that: (a) Student's external perceptions such as teacher unfairness and disciplinary climate, and student's internal perceptions such as valuing relationships and valuing teamwork significantly predicted CPSC; (b) Disciplinary climate was the strongest predictor among all the external perceptions analyzed; (c) Regarding the internal perceptions, valuing relationships positively predicted CPSC, while valuing teamwork negatively predicted CPSC. These findings enlighten educational practitioners to help students develop their CPSC from the perspective of interpersonal relationships.

Several international large-scale assessments were conducted at the turn of the new century, and during the past two decades the Programme for International Student Assessment (PISA) completed seven cycles of assessment to facilitate practitioners' policy debates and governance. This study reviews PISA-related articles published in English and Chinese. Three literature databases were searched, with a focus on SSCI, CSSCI, and TSSCI journal publications. The frequency of publication was analyzed according to the author's country affiliation, type of journal, and research categories/themes. Findings indicate that research on student-, school- and system-level indicators with a focus on students' learning processes and outcomes as well as critiques of technical matters on PISA were frequent topics in the literature during the past two decades. Issues of equality and equity examined in the publications have implications for enhancing practitioners' capabilities in terms of policy making and governance.

With the rapid growth of education data in large-scale assessment, machine learning techniques are crucial to the interdisciplinary development of education and information. Although data mining tools are increasingly used to predict overall student performance, resilient students in the digital world remain unstudied. Our study aims to comprehensively identify key features in the classification of academically resilient students (ARS) and non-academically resilient students (NRS) in digital reading. With a sample of 11,496 disadvantaged students from seven high-performing Asian economies, data drawn from the Programme for International Student Assessment (PISA) 2018 were analyzed through Support Vector Machine (SVM). Results indicated that 20 key features were selected from 105 contextual features at the individual, home, and school levels, which demonstrated a high predictive ability of the model. Personal experience, especially the use of metacognitive strategies in digital reading and reading enjoyment were predominant features. Interestingly, information and communication technology (ICT) resources and usage showed mixed effects on resilient students. This study provides significant implications for cultivating resilient students in online learning environments.

This study aimed to identify latent (unobservable) dimensions representing specific physical activity-related behaviors and explore their potential effects on obesity burden and spatial distribution in Colombia. A cross-sectional study (n = 9,658) was conducted based on the Colombian National Survey of Nutritional Status. A generalized structural equations model was proposed, combining exposure and measurement models to define a disease model. Modeling identified latent dimensions of physical activity focused on screen time and means of transportation and estimated their direct and indirect effects on obesity occurrence. Mapping techniques were used to illustrate adherence to these dimensions. The latent dimensions identified were named “Screens use” and “Active transportation”; the latter was inversely associated with obesity occurrence (p = 0.004), with the use of bicycles being the dominant variable, contrasting with the use of motor vehicles. The mapping showed that departments with the highest adherence to the “Active transportation” construct have a lower prevalence of obesity. Bicycle use, as opposed to non-active transportation, represented a dimension of physical activity-related behaviors with a protective effect against obesity. This suggests that active transportation may be a crucial factor in the designing preventive interventions. Moreover, social inequalities may be contributing to the obesity epidemic and physical activity behaviors in Colombia, requiring equitable and multisectoral responses.

Background and purposePsoriasis is a chronic, immune-mediated inflammatory skin disease that significantly impacts patients’ quality of life. The integration of telepharmacy has the potential to enhance patient care by providing flexible and personalized pharmaceutical follow-up. This study (TELEPROM Psoriasis) evaluates a telepharmacy model for evaluating electronic Patient-Reported outcomes (ePROMs) for individuals with moderate to severe plaque psoriasis in Spain with biological treatment.Experimental approachThis multicenter prospective quasi-experimental study included 258 adult patients initiating or switching biological/immunomodulatory therapy for moderate to severe plaque psoriasis. Patients were recruited from public hospitals in Spain and monitored through the NAVETA telepharmacy platform over a six-month period. PROMs assessed were the Psoriasis Symptoms and Signs Diary and the Dermatology Life Quality Index at baseline, 1 month, 3 months, and 6 months. Data were analyzed using ANOVA, Student’s t-test, multiple regression, and machine learning algorithms to evaluate ePROMs evolution and response and satisfaction with Telepharmacy follow up.Key resultsThe analysis revealed significant influences of gender, employment status, educational level, and daily activity, but no effect of age, on responses to Patient-Reported Outcomes questionnaires. Machine learning models, particularly Random Forest (AUC = 0.98) and Support Vector Machine (AUC = 0.96), effectively predicted patient engagement. DLQI scores significantly decreased from 9.33 ± 7.75 at baseline to 4.34 ± 5.86 at 6 months. Similarly, the PSSD - 7 Days questionnaire showed major reductions, with scores dropping from 55.43 ± 29.94 to 30.73 ± 30.66 at 6 months, and 53% of patients reaching a score of 20 or less. Notably, women reported worse scores at all time points compared to men. Regression analysis explained only 13.2% of the variance in PROMs scores, identifying Employment Status and BMI Range as key contributors.ConclusionThis study demonstrates the efficacy of biologic treatments in significantly improving HRQoL for psoriasis patients. Addressing demographic variables, such as gender, is key for optimizing treatment outcomes and improving ePROMs response rates. Tailored strategies and ML techniques can help identify low-engagement patients and mitigate disparities. Integrating sociodemographic factors into clinical decision-making and patient engagement strategies is fundamental for delivering equitable and comprehensive care.

Effective vineyard management is essential for maintaining grapevine cultivation in semi-arid regions impacted by climate change. Utilising organic mulches is a viable soil management practice that improves soil properties, such as moisture retention, erosion control and soil structure. However, the effect of organic mulches on plant development and grape composition remains unclear. The present study analysed the effects of three organic mulches and two conventional soil management practices on vine physiology, agronomy and grape composition over three years under semi-arid conditions in northern Spain. Three organic mulches (spent mushroom compost-SMC, straw-STR and grapevine pruning debris-GPD) were compared with two conventional soil management practices (herbicide-HERB and tillage-TILL) in nutrient-poor soil. Physical and chemical soil properties, grapevine physiological response, leaf nutrition, growth development, yield and grape composition were evaluated in the Tempranillo cultivar. The SMC mulch improved soil water content, leaf nitrogen concentrations and vegetative growth, resulting in higher yields without compromising grape composition. Conversely, STR mulch increased soil water content, reduced soil temperature, and improved plant water status and leaf gas exchange variables without affecting vine growth and yield. However, no significant differences in grape carbon isotopic discrimination (δ13C) were observed between soil management treatments. SMC’s nutrient-rich composition, fine granularity and low C/N ratio could thus promote short-term plant development in poor-nutrient soils, and STR and GPD organic mulches may offer long-term benefits for vine development. A strong correlation was obtained between reflectance values and vegetative growth, yield and leaf nutritional content, offering a non-destructive and rapid assessment method. Overall, organic mulches represent a viable soil management alternative that enhances plant development and yield without reducing grape composition. This research provides valuable insights for winegrowers interested in suitable viticultural practices and highlights the importance of analysing soil and mulch properties to select the most appropriate organic mulch.

Background: Low birth weight is a global problem but presents a major burden on the neonatal services in developing countries such as Nigeria, and brings to bear a greater strain on the meagre resources available for health care delivery and family financing. In a resourceconstrained setting as ours, proper weighing of all newborn infants and medical surveillance of low birth weight infants, although highly desirable, are often not achieved due to unavailability of suitable, functional weighing scales. There are serial cut-off points for the various anthropometric indices for the normal birth weight babies below which any baby is termed low birth weight. This study assessed the predictive values of anthropometric measurements in the detection of low birth weight newborn babies and also determined the local specific cut-off points for these measurements in Nnewi, Southeast Nigeria. Methods: This was a crosssectional study in which length, occipitofrontal circumference, mid-arm circumference and maximum thigh circumference of 428 singleton babies were ascertained within 24 hours of delivery. Data were analysed using the Statistical Package for Social Sciences (SPSS) software. Correlation and linear regression analyses were done to examine the linear relationship between the predictors and birth weight. The sensitivity, specificity and predictive values were calculated at serial cut–off points and the points of best discrimination determined. Results: The low birth weight prevalence was 15.2%. Maximum thigh circumference attained the highest correlation with birth weight (r = 0.904), greatest coefficient of detemination (r2=0.817), and least measure of dispersion around the actual birth weight. Thus maximum thigh circumference, which has a cut-off point of 16.75cm, was the best predictor of low birth weight, with 98.5% sensitivity, 92.3% specificity and diagnostic accuracy of 93.2% (P

Although major gains were made in the reduction of childhood health indicators in the previous decade, stagnations or reversals were seen in many countries since the 1990s. Despite presence of primary health centers (PHC) in Nigeria, there are still high levels of morbidity and mortality among children because the quality of child health services falls short of what it could be in the country. Supportive supervision of PHCs should also improve the quality of child health services. This study assessed the level of clients’ satisfaction with care received and the quality of supervision of child health services in selected PHC facilities of Newi, Nigeria. The study design was cross sectional. Four health facilities were selected by simple random sampling technique from a list of 12 public PHC facilities that provide at least three of the range of essential child health services. Using interviewer administered questionnaire, data were collected from 305 caregivers and analyzed accordingly. Also key informant interviews ere used to elicit information facility supervision frequency and adequacy. The mean age of the mainly female caregivers was 31.9 ± 9.4 years. Majority of the caregivers attended health facilities closest to them but 18.5% of the 65 who do not, said they did not like the health workers. Although more than 80% of clients were satisfied with quality of child health services received, yet 1.3% of them felt that the number of service days were inadequate. None of the health facilities had a work plan, supervision schedule or supervision checklist. Increasing the number of service days and providing supervision schedules and checklists at the health facilities can improve caregiver satisfaction and hopefully enhance quality of child health services at the PHCs

Polymer-infiltrated ceramic network (PICN) materials have gained considerable attention as tooth-restorative materials due to their mechanical compatibility with human teeth, especially with computer-aided design and computer-aided manufacturing (CAD/CAM) technologies. However, the designed geometry affects the mechanical properties of PICN materials. This study aims to study the relationship between manufacturing geometry and mechanical properties. In doing so, zirconia-based PICN materials with different geometries were fabricated using a direct ink-writing process, followed by copolymer infiltration. Comprehensive analyses of the microstructure and structural properties of zirconia scaffolds, as well as PICN materials, were performed. The mechanical properties were assessed through compression testing and digital image correlation analysis. The results revealed that the compression strength of PICN pieces was significantly higher than the respective zirconia scaffolds without polymer infiltration. In addition, two geometries (C-grid 0 and C-grid 45) have the highest mechanical performance.