Orientação a pais por chamadas de áudio durante a pandemia de covid-19 / Support for parents via audio calls during the covid-19 pandemic / Orientación de los padres mediante llamadas de audio durante la pandemia de covid-19

O distanciamento social ocasionado pela pandemia de Covid-19 levou a profundas mudanças na rotina das famílias com crianças pequenas, aumentando o estresse no ambiente doméstico. Este estudo analisou a experiência de planejamento e implementação de um projeto de extensão universitária que ofereceu orientação a pais com filhos de 0 a 11 anos por meio de chamadas de áudio durante a pandemia. O protocolo de atendimento foi desenvolvido para atender às necessidades de famílias de baixa renda e listava problemas específicos relacionados ao confinamento em casa e ao fechamento das escolas seguidos por uma variedade de estratégias de enfrentamento. A análise de 223 queixas relatadas pelos usuários em 130 ligações revelou que 94% dos problemas referidos pelos pais foram contemplados pelo protocolo de atendimento e estavam relacionados aos problemas externalizantes (39%) ou internalizantes (26%) das crianças ou ao declínio do bem-estar subjetivo dos pais (29%). Serviços de apoio devem orientar os pais quanto ao uso de práticas responsivas e assertivas que promovam o bem-estar emocional da criança e estabeleçam expectativas comportamentais em contextos estressantes. A diminuição dos conflitos entre pais e filhos resultante do uso dessas estratégias tende a reduzir o sofrimento dos pais, aumentando sua sensação de bem-estar subjetivo. Recomenda-se ampla divulgação dessas iniciativas e seguimento dos casos.(AU)

The social distancing the COVID-19 pandemic entailed has led to profound changes in the routine of families with young children, increasing stress in the home environment. This study analyzed the experience of planning and implementing a university extension program that offered support to parents with children from 0 to 11 years old via audio calls during the COVID-19 pandemic. The service protocol was developed to meet the needs of low-income families and listed specific problems related to home confinement and school closure followed by a variety of coping strategies. The analysis of 223 complaints reported by users in 130 calls revealed that 94% of the problems reported by parents were addressed by the protocol and were related to children's externalizing (39%) or internalizing (26%) problems or to the decline in parents' subjective well-being (29%). Support services should guide parents on the use of responsive and assertive practices that promote the child's emotional well-being and set behavioral expectations in stressful contexts. The reduction in conflicts between parents and children resulting from the use of these strategies tends to reduce parents' suffering, increasing their sense of subjective well-being. Wide dissemination of these initiatives and case follow-up are recommended.(AU)

La distancia social causada por la pandemia de COVID-19 condujo a cambios profundos en la rutina de las familias con niños pequeños, aumentando el estrés en el entorno del hogar. Este estudio analizó la experiencia de planificar e implementar un proyecto de extensión universitaria que ofreció orientación a los padres con niños de cero a 11 años a través de llamadas de audio durante la pandemia COVID-19. El protocolo de atención se desarrolló para satisfacer las necesidades de las familias de bajos ingresos y enumeró problemas específicos relacionados con el confinamiento en el hogar y el cierre de la escuela, seguido de una variedad de estrategias de afrontamiento. El análisis de 223 quejas informadas por los usuarios en 130 llamadas reveló que el 94% de los problemas informados por los padres fueron abordados por el protocolo de atención y estaban relacionados con los problemas de externalización (39%) o internalización (26%) de los niños o la disminución del bienestar subjetivo de los padres (29%). Los servicios de apoyo deberían aconsejar a los padres sobre el uso de prácticas receptivas y asertivas que promuevan el bienestar emocional del niño y establezcan expectativas de comportamiento en contextos estresantes. La reducción de los conflictos entre padres e hijos como resultado del uso de estas estrategias tiende a reducir el sufrimiento de los padres, aumentando su sensación de bienestar subjetivo. Se recomienda una amplia difusión de estas iniciativas y seguimiento de casos.(AU)

Tracking discussions of complementary, alternative, and integrative medicine in the context of the COVID-19 pandemic: a month-by-month sentiment analysis of Twitter data.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a novel infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite the paucity of evidence, various complementary, alternative and integrative medicines (CAIMs) have been being touted as both preventative and curative. We conducted sentiment and emotion analysis with the intent of understanding CAIM content related to COVID-19 being generated on Twitter across 9 months. METHODS: Tweets relating to CAIM and COVID-19 were extracted from the George Washington University Libraries Dataverse Coronavirus tweets dataset from March 03 to November 30, 2020. We trained and tested a machine learning classifier using a large, pre-labelled Twitter dataset, which was applied to predict the sentiment of each CAIM-related tweet, and we used a natural language processing package to identify the emotions based on the words contained in the tweets. RESULTS: Our dataset included 28 713 English-language Tweets. The number of CAIM-related tweets during the study period peaked in May 2020, then dropped off sharply over the subsequent three months; the fewest CAIM-related tweets were collected during August 2020 and remained low for the remainder of the collection period. Most tweets (n = 15 612, 54%) were classified as positive, 31% were neutral (n = 8803) and 15% were classified as negative (n = 4298). The most frequent emotions expressed across tweets were trust, followed by fear, while surprise and disgust were the least frequent. Though volume of tweets decreased over the 9 months of the study, the expressed sentiments and emotions remained constant. CONCLUSION: The results of this sentiment analysis enabled us to establish key CAIMs being discussed at the intersection of COVID-19 across a 9-month period on Twitter. Overall, the majority of our subset of tweets were positive, as were the emotions associated with the words found within them. This may be interpreted as public support for CAIM, however, further qualitative investigation is warranted. Such future directions may be used to combat misinformation and improve public health strategies surrounding the use of social media information.

Visual Sentiment Analysis With Social Relations-Guided Multiattention Networks.

These days, social media users tend to express their feelings through sharing images online. Capturing the emotions embedded in these social images involves great research challenges and practical values. Most existing works concentrate on extracting the visual feature from a global view, while ignoring the fact that visual objects are also rich in emotion. How to leverage the multilevel visual features to improve the sentiment analysis performance is important yet challenging. Besides, existing works view each social image as an independent sample while ignoring the rich correlations among social images, which may be helpful in detecting visual emotion. In this article, we propose a novel model called social relations-guided multiattention networks (SRGMANs) to incorporate both the multilevel (region-level and object-level) visual features of a single image and the correlations among multiple social images to conduct visual sentiment analysis. Specifically, we first construct a heterogeneous network consisting of various types of social relations and introduce a heterogeneous network embedding method to learn the network representation for each image. Then, two visual attention branches (region attention network and object attention network) are devised to extract emotional and discriminative visual features. For each branch, we design a self-attention module to capture the emotional dependencies among visual parts. Besides, a network-guided attention module is also designed in each branch to focus on more network-related emotional visual parts with the guidance of the topology information. Finally, the attended visual features from the two attention models, together with network representation features, are combined within a holistic framework to predict the sentiment of social images. Extensive experiments demonstrate the superiority of our model on three benchmark datasets.