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The study focused on examining the relationship between well-being and various psychological factors such as loneliness, anxiety, depression, and stress, whilst also considering changes in lifestyle. A total of 108 elderly participants, with an average age of 70.38 years, were enrolled in this quantitative cross-sectional study. The research employed a battery of assessment tools including a Sociodemographic Data Questionnaire, Mini-Mental State Examination, Positive Mental Health Scale, Stress Perception Scale, Geriatric Anxiety Inventory, Geriatric Depression Scale (reduced version), Loneliness Scale, and International Physical Activity Questionnaire. Descriptive analysis was conducted in order to understand the distribution of scores across these variables, followed by the categorization of participants based on the reported alterations in eating and physical activity behaviors. Correlations between variables were assessed using Spearman correlation and an EBIC-LASSO network analysis. The findings indicated a potential detriment to the well-being of elderly individuals practicing social distancing, evidenced by heightened symptoms of loneliness, depression, anxiety, and stress, alongside the reported changes in dietary patterns and physical activity. The study underscores the importance of understanding the pandemic's impact on the well-being of older adults and advocates for longitudinal investigations to delineate the evolving effects of social distancing measures across different phases of the pandemic.

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INTRODUCTION: Delays in prehospital care attributable to the call-taking process can often be traced back to miscommunication, including uncertainty around the call location. Geolocation applications have the potential to streamline the call-taking process by accurately identifying the caller's location. OBJECTIVE: To develop and validate an application to geolocate emergency calls and compare the response time of calls made via the application with those of conventional calls made to the Brazilian Medical Emergency System (Serviço de Atendimento Médico de Urgência-SAMU). METHODS: This study was conducted in two stages. First, a geolocating application for SAMU emergency calls (CHAMU192) was developed using a mixed methods approach based on design thinking and subsequently validated using the System Usability Scale (SUS). In the second stage, sending time of the geolocation information of the app was compared with the time taken to process information through conventional calls. For this, a hypothetical case control study was conducted with SAMU in the Maringá, Paraná, Brazil. A control group of 350 audio recordings of emergency calls from 2019 was compared to a set of test calls made through the CHAMU192 app. The CHAMU192 group consisted of 201 test calls in Maringá. In test calls, the location was obtained by GPS and sent to the SAMU communication system. Comparative analysis between groups was performed using the Mann-Whitney test. RESULTS: CHAMU192 had a SUS score of 90, corresponding to a "best imaginable" usability rating. The control group had a median response time of 35.67 seconds (26.00-48.12). The response time of the CHAMU192 group was 0.20 (0.15-0.24). CONCLUSION: The use of the CHAMU192 app by emergency medical services could significantly reduce response time. The results demonstrate the potential of app improving the quality and patient outcomes related to the prehospital emergency care services.

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Emergency care-sensitive conditions (ECSCs) require rapid identification and treatment and are responsible for over half of all deaths worldwide. Prehospital emergency care (PEC) can provide rapid treatment and access to definitive care for many ECSCs and can reduce mortality in several different settings. The objective of this study is to propose a method for using artificial intelligence (AI) and machine learning (ML) to transcribe audio, extract, and classify unstructured emergency call data in the Serviço de Atendimento Móvel de Urgência (SAMU) system in southern Brazil. The study used all "1-9-2" calls received in 2019 by the SAMU Novo Norte Emergency Regulation Center (ERC) call center in Maringá, in the Brazilian state of Paraná. The calls were processed through a pipeline using machine learning algorithms, including Automatic Speech Recognition (ASR) models for transcription of audio calls in Portuguese, and a Natural Language Understanding (NLU) classification model. The pipeline was trained and validated using a dataset of labeled calls, which were manually classified by medical students using LabelStudio. The results showed that the AI model was able to accurately transcribe the audio with a Word Error Rate of 42.12% using Wav2Vec 2.0 for ASR transcription of audio calls in Portuguese. Additionally, the NLU classification model had an accuracy of 73.9% in classifying the calls into different categories in a validation subset. The study found that using AI to categorize emergency calls in low- and middle-income countries is largely unexplored, and the applicability of conventional open-source ML models trained on English language datasets is unclear for non-English speaking countries. The study concludes that AI can be used to transcribe audio and extract and classify unstructured emergency call data in an emergency system in southern Brazil as an initial step towards developing a decision-making support tool.

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A orientação profissional aos adolescentes com altas habilidades/superdotação é importante para a compreensão de suas habilidades e competências que irão facilitar a inserção no mercado de trabalho. O estudo teve como objetivo comparar os efeitos da intervenção em orientação profissional para adolescentes com e sem superdotação em relação à maturidade para escolha profissional, indecisão vocacional, autoeficácia e sintomas de depressão, ansiedade e estresse. Utilizou-se um questionário de dados sociodemográficos, critério de Classificação Brasil, Escala de Maturidade para Escolha Profissional, Escala de Indecisão Vocacional, Depression, Anxiety and Stress Scale e a Escala de Autoeficácia Geral Percebida. Participaram 31 adolescentes. Observou-se que a intervenção em orientação profissional reduziu a indecisão vocacional e sintomas de estresse. Os superdotados apresentaram aumento de determinação, autoconhecimento e maturidade para escolha profissional.

The professional guidance for adolescents with high abilities/giftedness is important for understanding their skills and competences that will facilitate their entry into the labor market. Objective to compare the effects of intervention in professional guidance for adolescents with and without giftedness in relation to the maturity for professional choice, vocational indecision, self-efficacy and symptoms of depression, anxiety and stress. We used a questionnaire of sociodemographic data, Brazil Classification criteria, Maturity Scale for Professional Choice, Vocational Indecision Scale, Depression, Anxiety and Stress Scale and the Perceived General Self-efficacy Scale. 31 adolescents participated. It was observed that the intervention in professional guidance reduced vocational indecision and symptoms of stress. The gifted showed an increase in determination, self-knowledge and maturity for professional choice.

La orientación profesional para adolescentes con altas capacidades / superdotación es importante para la comprensión de sus habilidades y competencias que facilitarán su inserción en el mercado laboral. Objetivo de comparar los efectos de la intervención en la orientación profesional para adolescentes con y sin superdotación en relación con la madurez para la elección profesional, la indecisión vocacional, la autoeficacia y los síntomas de depresión, ansiedad y estrés. Utilizamos un cuestionario de datos sociodemográficos, criterios de clasificación de Brasil, escala de madurez para la elección profesional, escala de indecisión vocacional, escala de depresión, ansiedad y estrés y la escala de autoeficacia general percibida. Participaron 31 adolescentes. Se observó que la intervención en orientación profesional redujo la indecisión vocacional y los síntomas de estrés. Los superdotados mostraron un aumento en la determinación, el autoconocimiento y la madurez para la elección profesional.

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OBJECTIVE: The objective of this study was to translate and adapt the National Institute of Mental Health Life Chart Method - Self/Prospective (NIMH-LCM-S/P™) instrument for self-monitoring of mood into Brazilian Portuguese and provide evidence of content validity. Additionally, a user guide was prepared for the instrument and evaluated by mental health professionals. METHODS: The study was divided into two stages - Stage 1: Translation and cross-cultural adaptation and Stage 2: Determination of content validity index (CVI) scores. The translation and cross-cultural adaptation process involved 37 participants between translators, experts, target population, and evaluators. RESULTS: The CVI was evaluated by 15 mental health professionals. 11 (78.57%) of the items evaluated attained the maximum CVI score of 1.00, which constitutes the highest level of content validity, and no changes were suggested by participants. Only one of the items evaluated had a CVI score lower than 0.80. CONCLUSION: The final translated and adapted version of the NIMH-LCM-S/P™ and its user guide were evaluated by the target population and the mental health professionals. Both groups displayed satisfactory comprehension levels, suggesting there is potential for using this instrument in clinical practice to assess therapeutic interventions in Brazilian settings.

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Abstract Objective The objective of this study was to translate and adapt the National Institute of Mental Health Life Chart Method - Self/Prospective (NIMH-LCM-S/P™) instrument for self-monitoring of mood into Brazilian Portuguese and provide evidence of content validity. Additionally, a user guide was prepared for the instrument and evaluated by mental health professionals. Methods The study was divided into two stages - Stage 1: Translation and cross-cultural adaptation and Stage 2: Determination of content validity index (CVI) scores. The translation and cross-cultural adaptation process involved 37 participants between translators, experts, target population, and evaluators. Results The CVI was evaluated by 15 mental health professionals. 11 (78.57%) of the items evaluated attained the maximum CVI score of 1.00, which constitutes the highest level of content validity, and no changes were suggested by participants. Only one of the items evaluated had a CVI score lower than 0.80. Conclusion The final translated and adapted version of the NIMH-LCM-S/P™ and its user guide were evaluated by the target population and the mental health professionals. Both groups displayed satisfactory comprehension levels, suggesting there is potential for using this instrument in clinical practice to assess therapeutic interventions in Brazilian settings.

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The objective of this study was to determine the association between temporomandibular disorders (TMD) with depression, somatization and sleep disorders in the city of Maringá, Brazil. A total of 1,643 participants were selected from the Brazilian Unified Health System (SUS). Of these, the test group consisted of 84 participants who had moderate or severe limitations due to TMD pain and the control group consisted of 1,048 participants with no pain. There was a highly statistically significant difference (p<0.001) between cases and controls regarding depression (82.1 versus 37.4%), somatization (84.5 versus 31.4%), and sleep disorders (84.6 versus 36.4%), in moderate to severe levels. The levels of moderate to severe depression, somatization and sleep disorders were significantly higher in TMD subjects with high TMD pain disability. The risk of developing TMD increased 4 to 5 times when the individual has moderate to severe levels of depression, somatization, and sleep disorders.

O objetivo deste estudo foi determinar a associação entre disfunções temporomandibulares (DTM) com depressão, somatização e distúrbios do sono na cidade de Maringá, Brasil. Foram selecionados 1.643 participantes atendidos no Sistema Único de Saúde (SUS). Desses, o grupo caso foi formado por 84 participantes que apresentaram limitações moderada ou grave devido à dor na DTM e o grupo controle foi formado por 1.048 participantes com ausência de dor. Verificou-se diferença estatisticamente significativa (p<0,001) entre casos e controles em relação à depressão (82,1 versus 37,4%), somatização (84,5 versus 31,4%) e distúrbios do sono (84,6 versus 36,4%), em níveis moderados a graves. Os níveis de depressão moderada a grave, somatização e distúrbios do sono foram significativamente mais altos em indivíduos com DTM com alta incapacidade devido à dor por DTM. O risco de desenvolver DTM aumentou quatro a cinco vezes quando o indivíduo apresenta níveis moderados a graves de depressão, somatização e distúrbios do sono.

El objetivo de este estudio fue determinar la asociación entre los trastornos temporomandibulares (TMD) con la depresión, la somatización y los trastornos del sueño en la ciudad de Maringá, Brasil. Un total de 1.643 participantes fueron seleccionados del Sistema Único de Salud (SUS) de Brasil. (SUS). De estos, el grupo de casos fue formado por 84 participantes que presentaban limitaciones moderadas o graves debido al dolor TMD y el grupo de control estaba formado por 1.048 participantes sin dolor. Hubo una diferencia estadísticamente significativa (p <0,001) entre casos y controles con respecto a depresión (82,1 frente a 37,4%), somatización (84,5 frente a 31,4%) y trastornos del sueño (84,6 frente a 36,4%), en niveles moderados a severos. Los niveles de depresión moderada a grave, somatización y trastornos del sueño fueron significativamente más altos en personas con TMD con alta discapacidad por dolor en TMD. El riesgo de desarrollar TMD aumenta de 4 a 5 veces cuando el individuo tiene niveles moderados a severos de depresión, somatización y trastornos del sueño.

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INTRODUCTION: Most patients with COVID-19 have mild or moderate manifestations; however, there is a wide spectrum of clinical presentations and even more severe repercussions that require high diagnostic suspicion. Vital sign acquisition and monitoring are crucial for detecting and responding to patients with COVID-19. OBJECTIVE: Thus, we conducted this study to demonstrate the impact of using a tool called Smart Check on the triage time of patients with suspected COVID-19 and to identify the main initial clinical manifestations in these patients. METHODOLOGY: We assessed triage times before and after the use of Smart Check in 11 466 patients at Hospital Nossa Senhora da Conceição in Porto Alegre, Brazil, from 1 June to 31 July 2020. In this group, we identified 220 patients for the identification of COVID-19 clinical manifestations in a case-control analysis. RESULTS: Smart Check was able to decrease the triage time by 33 seconds on average (P < .001), with 75% of the exams being performed within 5 minutes, whereas with the usual protocol these steps were performed within 6 minutes. A range of clinical presentations made up the COVID-19 initial manifestations. Those with the highest frequency were dry cough (46.4%), fever (41.3%), dyspnoea (35.8%), and headache (31.8%). Loss of appetite was the manifestation that had a statistically significant association with the SARS-CoV-2 presence (univariate analysis). When analysed together, loss of appetite associated with dyspnoea and/or ageusia and/or fever was related to the diagnosis of COVID-19. CONCLUSIONS: Smart Check, a simple clinical evaluation tool, along with the targeted use of rapid PCR testing, can optimise triage time for patients with and without COVID-19. In triage centres, a number of initial signs and symptoms should be cause for SARS-CoV-2 infection suspicion, in particular the association of respiratory, neurological, and gastrointestinal manifestations.

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Background: The benefits of treatment for many conditions are time dependent. The burden of these emergency care sensitive conditions (ECSCs) is especially high in low- and middle-income countries. Our objective was to analyze geospatial trends in ECSCs and characterize regional disparities in access to emergency care in Brazil. Methods: From publicly available datasets, we extracted data on patients assigned an ECSC-related ICD-10 code and on the country's emergency facilities from 2015-2019. Using ArcGIS, OpenStreetMap, and WorldPop, we created catchment areas corresponding to 180 minutes of driving distance from each hospital. We then used ArcGIS to characterize space-time trends in ECSC admissions and to complete an Origin-Destination analysis to determine the path from household to closest hospital. Findings: There were 1362 municipalities flagged as "hot spots," areas with a high volume of ECSCs. Of those, 69.7% were more than 180 minutes (171 km) from the closest emergency facility. These municipalities were primarily located in the states of Minas Gerais, Bahia, Espiríto Santo, Tocantins, and Amapá. In the North region, only 69.1% of the population resided within 180 minutes of an emergency hospital. Interpretations: Significant geographical barriers to accessing emergency care exist in certain areas of Brazil, especially in peri-urban areas and the North region. One limitation of this approach is that geolocation was not possible in some areas and thus we are likely underestimating the burden of inadequate access. Subsequent work should evaluate ECSC mortality data. Funding: This study was funded by the Duke Global Health Institute Artificial Intelligence Pilot Project.

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Background: Preterm birth (PTB) is a growing health issue worldwide, currently considered the leading cause of newborn deaths. To address this challenge, the present work aims to develop an algorithm capable of accurately predicting the week of delivery supporting the identification of a PTB in Brazil. Methods: This a population-based study analyzing data from 3,876,666 mothers with live births distributed across the 3,929 Brazilian municipalities. Using indicators comprising delivery characteristics, primary care work processes, and physical infrastructure, and sociodemographic data we applied a machine learning-based approach to estimate the week of delivery at the point of care level. We tested six algorithms: eXtreme Gradient Boosting, Elastic Net, Quantile Ordinal Regression - LASSO, Linear Regression, Ridge Regression and Decision Tree. We used the root-mean-square error (RMSE) as a precision. Findings: All models obtained RMSE indexes close to each other. The lower levels of RMSE were obtained using the eXtreme Gradient Boosting approach which was able to estimate the week of delivery within a 2.09 window 95%IC (2.090-2.097). The five most important variables to predict the week of delivery were: number of previous deliveries through Cesarean-Section, number of prenatal consultations, age of the mother, existence of ultrasound exam available in the care network, and proportion of primary care teams in the municipality registering the oral care consultation. Interpretation: Using simple data describing the prenatal care offered, as well as minimal characteristics of the pregnant, our approach was capable of achieving a relevant predictive performance regarding the week of delivery. Funding: Bill and Melinda Gates Foundation, and National Council for Scientific and Technological Development - Brazil, (Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPQ acronym in portuguese) Support of the research project named: Data-Driven Risk Stratification for Preterm Birth in Brazil: Development of a Machine Learning-Based Innovation for Health Care- Grant: OPP1202186.