Thinking skills are essential to achieve sustainable social development. Nonetheless, there is no specific instrument that assesses all of these skills as a whole. The present study aimed to design and validate a scale to assess complex thinking skills in adult people. A scale of 22 items assessing the following aspects: analysis and problem solving, critical analysis, metacognition, systemic analysis, and creativity, in five levels, was created. This scale was validated in 626 university students from Peru. In total, 16 experts in the field helped to determine the content validity of the scale (Aiken’s V value higher than 0.8). The confirmatory factor analysis allowed the evaluation of the structure of the five factors theoretically proposed and the goodness of fit indexes was satisfactory. An item was eliminated during the process and the scale resulted in 21 items. The composite reliability for the different factors was ranged between 0.794 and 0.867. The invariance between genders was also checked and the concurrent validity was proved. The study concludes that the content validity, construct validity, concurrent validity, and composite reliability levels of the COMPLEX-21 scale are appropriate.

Background: Antimicrobial resistance (AMR) poses a worldwide health threat; quick and accurate identification of AMR enhances patient outcomes and reduces inappropriate antibiotic usage. The objective of this systematic review is to evaluate the efficacy of machine learning (ML) approaches in predicting AMR in critical and high-priority pathogens (CHPP), considering antimicrobial susceptibility tests in real-world healthcare settings. Methods: The search methodology encompassed the examination of several databases, such as PubMed/MEDLINE, EMBASE, Web of Science, SCOPUS, and SCIELO. An extensive electronic database search was conducted from the inception of these databases until November 2024. Results: After completing the final step of the eligibility assessment, the systematic review ultimately included 21 papers. All included studies were cohort observational studies assessing 688,107 patients and 1,710,867 antimicrobial susceptibility tests. GBDT, Random Forest, and XGBoost were the top-performing ML models for predicting antibiotic resistance in CHPP infections. GBDT exhibited the highest AuROC values compared to Logistic Regression (LR), with a mean value of 0.80 (range 0.77–0.90) and 0.68 (range 0.50–0.83), respectively. Similarly, Random Forest generally showed better AuROC values compared to LR (mean value 0.75, range 0.58–0.98 versus mean value 0.71, range 0.61–0.83). However, some predictors selected by these algorithms align with those suggested by LR. Conclusions: ML displays potential as a technology for predicting AMR, incorporating antimicrobial susceptibility tests in CHPP in real-world healthcare settings. However, limitations such as retrospective methodology for model development, nonstandard data processing, and lack of validation in randomized controlled trials must be considered before applying these models in clinical practice.

Although human talent is essential to achieve social and organizational development with a sustainable focus, its definition and features remain unclear considering humanity’s current challenges and the transformation towards the knowledge society. The purpose of this conceptual analysis is to propose a new definition of talent using socioformation as its basis. The methodology used was a hermeneutical analysis due to the lack of previous published works on the subject. The main results were: 1) the proposal of a new definition of talent as a complex process which focuses on solving contextual problems with relevant results for improvement of living conditions, based on competencies, laboriousness, complex thought, opportunities for inclusion, the ethical project of life, collaboration, and continuous improvement; and 2) the new approach is characterized by emphasizing collaboration, being inclusive, and having a systematic and procedural approach. We concluded that it is necessary to approach a new perspective of talent, which contributes to the formation of citizens committed to human development with an emphasis on environmental care, against which the proposal presented in this conceptual analysis, arriving from socioformation, is only an option for discussion.

This study investigates the development of transversal skills and their association with academic performance in university students enrolled in on-campus programs with online activities. A cross-sectional, descriptive, and quantitative research was conducted with 252 students from a public university in Mexico. Transversal skills, socioformative project-based practices, learning strategies, and the relevance of online activities were assessed using validated rubrics. The results indicated a low level of development in three transversal skills: research, entrepreneurship, and English, with the latter being the poorest rated. Critical and creative thinking exhibited the highest level of development. In the didactic component, socioformative project-based pedagogical practices and learning strategies showed acceptable levels. Students expressed satisfaction with complementary online activities, showing a preference for interactive videos and short videos under 4 min. Regression analysis and structural equations were used to examine the relationships between various factors. Results demonstrated that socioformative project-based pedagogical practices, learning strategies, and online education positively correlated with the development of transversal skills. Furthermore, a higher level of transversal skills was associated with better academic averages among students. Socioformative project-based pedagogical practices also correlated with academic performance through transversal skills. The study concludes that integrating online activities into on-campus programs, based on the socioformative pedagogical model, can enhance the development of transversal skills and improve academic performance. Further research into the implementation of this educational model and its long-term impact on university education and professional success is recommended.

The COVID-19 pandemic changed the way education was conducted, not only at the time when the face-to-face model was replaced by virtuality but also in the period of return to normality because the digital skills of teachers are not the same as before. Digital competency frameworks allow for assessment and comparisons between individuals and over time, so they can be used to understand the transformation that may have occurred in teachers’ digital competencies following the pandemic. This systematic literature review analyzes the competency frameworks that have been used in Ibero-America up to the year 2022, with the purpose of defining a concept foundation as an input on which to build a tool to assess digital competencies. The review was done following the pathway proposed by the PRISMA methodology between 2018 and 2022. Results show that there is no consensus or unification of the frameworks, and that there are five purposes in the research being conducted on digital competencies with publications concentrated on two of them. Interest on digital competence frameworks increased substantially in 2020.