Introduction: The experience of living with a chronic disease is not a simple task, since it requires tools that allow increasing the degree of awareness to face the needs and overcome challenges about the state of health and disease. In recent years, support for self-management has been established, with the aim of enhancing the skills of people with this type of condition. It is important to consider how the nursing discipline can contribute to achieve this. The aim of this paper is to reflect on Meléis' theory of transitions as a paradigm to support self-management in people with chronic conditions. Development: Meléis' theory of transitions establishes that people are in constant change, as occurs in the health-illness transition process. Receiving the diagnosis of a chronic disease involves a series of complex processes for the person, due to the multiplicity of variables involved. Meléis' theory provides guidelines to orient the nursing professional on key and interrelated elements, such as the previous conception of the nature of the transition and its conditions, which will serve for the planning of intervention modalities congruent with the person's experiences and their evaluation in the course of the health and disease process. Conclusion: The paradigm offered by Meléis can be considered a key approach to undertake the nursing care process aimed at supporting people with chronic illness in achieving self-management. Introducción: La experiencia de vivir con una enfermedad crónica no es una tarea sencilla, se requiere de herramientas que permitan aumentar el grado de conciencia para enfrentar las necesidades y superar desafíos sobre el estado de salud y enfermedad. En los últimos años, se ha instaurado el apoyo al automanejo, con la finalidad de potenciar las habilidades en personas con este tipo de afecciones. Resulta trascendental considerar como desde enfermería se puede contribuir al logro de aquello. El objetivo del presente ensayo es reflexionar acerca de la teoría de las transiciones de Meléis como paradigma de apoyo al automanejo en personas con condiciones crónicas. Desarrollo: La teoría de las transiciones de Meléis establece que las personas están en constante cambio, tal como ocurre en el proceso de transición de salud-enfermedad. Recibir el diagnóstico de una enfermedad crónica, conlleva una serie de procesos complejos para la persona, debido a la multiplicidad de variables que ello implica. La teoría de Meléis entrega lineamientos para orientar a la persona profesional de enfermería sobre elementos claves e interrelacionados, como la concepción previa de la naturaleza de la transición y sus condiciones, lo que servirá para la planificación de modalidades de intervención congruentes con las experiencias de la persona y su evaluación en el transcurso del proceso de salud y enfermedad. Conclusión: El paradigma ofrecido por Meléis puede ser considerado un enfoque clave para emprender el proceso de cuidado de enfermería tendiente a apoyar a las personas con enfermedad crónica en el logro del automanejo. Introdução: A experiênca de viver com uma doença crônica não é uma tarefa simple, pois requer ferramentas que permitam aumentar o nível de consciência para enfrentar as necessidades e superar desafios relativos ao estado de saúde e doença. Nos últimos anos, foi estabelecido o apoio à autogestão, com o objetivo de melhorar as habilidades das pessoas com este tipo de condições. É transcendental considerar como a disciplina de Enfermagem pode contribuir para isso. O objetivo deste ensaio é refletir sobre a teoria das transições de Meleis como paradigma de apoio à autogestão em pessoas com condições crônicas. Desenvolvimento: A teoria das transições de Meléis estabelece que as pessoas estão em constante mudança, como acontece no processo de transição saúde-doença. Receber o diagnóstico de uma doença crónica implica uma série de processos complexos para a pessoa, devido à multiplicidade de variáveis envolvidas. A teoria de Meléis fornece directrizes para orientar o profissional de enfermagem sobre elementos-chave e inter-relacionados, como a conceção prévia da natureza da transição e das suas condições, que servirão para o planeamento de modalidades de intervenção congruentes com as experiências da pessoa e a sua avaliação no decurso do processo saúde-doença. Conclusão: O paradigma oferecido por Meleis pode ser considerado uma abordagem chave para empreender o processo de cuidado de enfermagem que visa apoiar as pessoas com doenças crônicas no alcance do autogerenciamento.

The 2019 Coronavirus disease (COVID-19) pandemic is a current challenge for the world’s health systems aiming to control this disease. From an epidemiological point of view, the control of the incidence of this disease requires an understanding of the influence of the variables describing a population. This research aims to predict the COVID-19 incidence in three risk categories using two types of machine learning models, together with an analysis of the relative importance of the available features in predicting the COVID-19 incidence in the Chilean urban commune of Concepción. The classification results indicate that the ConvLSTM (Convolutional Long Short-Term Memory) classifier performed better than the SVM (Support Vector Machine), with results between 93% and 96% in terms of accuracy (ACC) and F-measure (F1) metrics. In addition, when considering each one of the regional and national features as well as the communal features (DEATHS and MOBILITY), it was observed that at the regional level the CRITICAL BED OCCUPANCY and PATIENTS IN ICU features positively contributed to the performance of the classifiers, while at the national level the features that most impacted the performance of the SVM and ConvLSTM were those related to the type of hospitalization of patients and the use of mechanical ventilators.

Multiple chronic conditions are an important factor influencing mortality in older adults. At the same time, cardiovascular events in older adult patients are one of the leading causes of mortality worldwide. This study aimed to design a machine learning model capable of predicting mortality risk in older adult patients with cardiovascular pathologies and multiple chronic diseases using the Cardiovascular Health Study database. The methodology for algorithm design included (i) database analysis, (ii) variable selection, (iii) feature matrix creation and data preprocessing, (iv) model training, and (v) performance analysis. The analysis and variable selection were performed through previous knowledge, correlation, and histograms to visualize the data distribution. The machine learning models selected were random forest, support vector machine, and logistic regression. The models were trained using two sets of variables. First, eight years of the data were summarized as the mode of all years per patient for each variable (123 variables). The second set of variables was obtained from the mode every three years (369 variables). The results show that the random forest trained with the second set of variables has the best performance (89% accuracy), which is better than other reported results in the literature.

Asthma is a chronic non-communicable disease considered a serious health problem worldwide. The Chronic Care Model promotes the self-management of patients' chronic conditions. This process requires an active engagement of health professionals to provide education for patients to manage their disease better. Aim: this study sought to explore the education process carried out by primary health care providers for asthma patients in two regions of Chile. Methods: Nine group interviews with 35 health providers in nine primary health care centers were conducted in two of the country's major urban areas, the Valparaiso and Biobio Regions. Data were analyzed using an inductive approach, with coding followed by category construction and interpretation. Results: Based mainly on age and educational level, health professionals construct a patient profile to adjust the information provided and the strategies employed to educate patients. The education is focused on pharmacological treatment and inhalation techniques. Educational strategies are primarily direct instruction through individual one-on-one sessions. Fewer actions were described to help patients choose, control, and correct their daily routines and lifestyle and involve patients in self-awareness and self-regulating their behavior. Conclusions: The health care education process for asthma patients focuses on delivering information about the disease and medical treatment. Some issues of the Chronic Care Model, which promotes self-management, are still not addressed.

Background: Low comprehension and adherence to medical treatment among the elderly directly and negatively affect their health. Many elderly patients forget medical instructions immediately after their appointments, misunderstand them, or fail to recall them altogether. Some identified causes include the short time slots allocated for appointments in the public health system in Chile, the complex terminology used by healthcare professionals, and the stress experienced by patients during appointments. One approach to improving patients’ adherence to medical treatment is to combine written and oral instructions with graphical elements such as pictograms. However, several challenges arise due to the ambiguity of natural language and the need for pictograms to accurately represent various medication combinations, doses, and frequencies. Objective: This study introduces SIMAP (System for Integrating Medical Instructions with Pictograms), a technological framework aimed at enhancing adherence among asthma patients through the delivery of pictograms via a computational system. SIMAP utilizes a collaborative and user-centered methodology, involving health professionals and patients in the construction and validation of its components. Methods: The technological framework presented in this study is composed of three parts. The first two are medical indications and pictograms related to the treatment of the disease. Both components were developed through a comprehensive and iterative methodology that incorporates both qualitative and quantitative approaches. This methodology includes the utilization of focus groups, interviews, paper and online surveys, as well as expert validation, ensuring a robust and thorough development. The core of SIMAP is the technological component that leveraged artificial intelligence methods for natural language processing to analyze, tokenize, and associate words and their context to a set of one or more pictograms, addressing issues such as the ambiguity in the text, the cultural factor that involves many ways of expressing the same indication, and typographical errors in the indications. Results: Firstly, we successfully validated 18 clinical indications along with their respective pictograms. Some of the pictograms were redesigned based on the validation results. However, in the final validation, the comprehension percentages of the pictograms exceeded 70%. Furthermore, we developed a software called SIMAP, which translates medical indications into previously validated pictograms. Our proposed software, SIMAP, achieves a correct mapping rate of 96.69%. Conclusions: SIMAP demonstrates great potential as a technological component for supplementing medical instructions with pictograms when tested in a laboratory setting. The use of artificial intelligence for natural language processing can successfully map medical instructions, both structured and unstructured, into pictograms. This integration of textual instructions and pictograms holds promise for enhancing the comprehension and adherence of elderly patients to their medical indications, thereby improving their long-term health.

INTRODUCCIÓN. A nivel mundial, millones de personas padecen un trastorno mental. Este diagnóstico afecta directamente la dinámica y la calidad de vida de las familias. En este contexto, el sentido de coherencia es un recurso esencial para la salud mental de los padres, ya que facilita el afrontamiento de los estresores y la adaptación a las demandas del cuidado. OBJETIVO. Examinar y sintetizar la evidencia descriptiva y sobre intervenciones dirigidas a mejorar el sentido de coherencia en padres de personas con trastornos mentales. MÉTODOS. Se realizó una revisión de alcance siguiendo las pautas del Instituto Joanna Briggs. La búsqueda se realizó en PubMed, Web of Science, Scopus y CINAHL. Se consideraron elegibles estudios primarios y secundarios publicados hasta noviembre de 2024 que evaluaron el sentido de coherencia de los padres de personas con trastornos mentales en contextos familiares, educativos o clínicos. RESULTADOS. Se incluyeron 12 estudios primarios cuantitativos, publicados entre 2002 y 2024, desarrollados en países europeos y asiáticos. Los hallazgos indican que el sentido de coherencia predice niveles más bajos de estrés y que este se ve influido por diversos factores psicológicos, familiares y sociodemográficos. Asimismo, las intervenciones educativas implementadas mostraron cambios en indicadores de salud mental y de adaptación parental. CONCLUSIONES. El sentido de coherencia es un factor determinante para la salud de los padres y puede modificarse mediante estrategias educativas específicas. Sin embargo, se requieren estudios más representativos y que exploren intervenciones asociadas a este constructo.