Ansiedad, sentimientos del odontólogo y medidas adoptadas en la atención clínica durante la pandemia COVID-19

Introducción: la pandemia COVID-19 ha afectado la práctica odontológica por el alto riesgo de contagio durante su ejercicio. El objetivo del estudio fue determinar el nivel de ansiedad, sentimientos manifestados y medidas adoptadas en la atención clínica por el odontólogo durante la pandemia COVID-19 en Lima Metropolitana-Perú. Métodos: estudio descriptivo, prospectivo y transversal realizado en 386 odontólogos de Lima Metropolitana-Perú en los primeros meses del 2021. El nivel de ansiedad se midió a través del: Generalized Anxiety Disorder. Se confeccionó y validó un cuestionario para medir los sentimientos y medidas adoptadas, que fue enviado a través de distintas redes sociales. Resultados: los niveles de ansiedad leve y moderada se presentaron en el 42,5% y 21,2% respectivamente, presentándose mayores niveles de severidad en las mujeres (p<0,001). A mayor edad y número de años de experiencia profesional el nivel de ansiedad fue menor (Rho=-0,132; p=0,009) y (Rho=-0,129, p=0,011). Los sentimientos experimentados aumentaron a medida que el nivel de ansiedad fue mayor p<0,001. El 97,7% manifestó haber modificado el uso de equipos de protección personal como el uso de mascarillas respiratorias tipo N95 y el protector facial, y el 48,7% reveló haber tenido alguna dificultad para obtenerlo. La medida más utilizada en la atención clínica fue el lavado de manos antes y después de cada atención (92,7%) y el uso de luz ultravioleta (42,5%) fue la menos utilizada. Conclusiones: los odontólogos han cambiado el protocolo de atención, manifestando diferentes niveles de ansiedad acompañados de sentimientos negativos durante la pandemia COVID-19.

Introduction: the COVID-19 pandemic has affected dental practice, due to the high risk of contagion during its practice. The objective of the study was to evaluate the level of anxiety; emotions and measures taken by dentists during COVID-19 pandemic in Lima Metropolitana-Peru. Methods: the study was descriptive, prospective, and cross-sectional carried out in 386 dentists practicing in Lima Metropolitan-Peru during the first months of 2021. Level of anxiety was assessed by "Generalized Anxiety Disorder 7-item" (GAD-7) scale. A questionnaire was developed and validated to evaluate emotions and measures taken and was sent through different social networks. Results: mild and moderate anxiety were present in 42.5% and 21.2% respectively, with higher levels of severity in women (p<0.001). The higher the age and number of years of professional experience, the level of anxiety was lower (Rho=-0.132; p=0.009) and (Rho=-0.129, p=0.011). The emotions increased as the level of anxiety was higher p<0.001. 97.7% stated that they had modified the use of personal protective equipment such as the use of N95-type respiratory masks and face shields, and 48.7% revealed that they had some difficulty in obtaining it. The most used measure in clinical practice was hand washing before and after treatment (92.7%), while the use of ultraviolet light (42.5%) was the least used. Conclusions: dentists have changed care protocol, manifesting different levels of anxiety accompanied by negative emotions during COVID-19 pandemic.

UTILIZING AI TECHNOLOGY TO PREVENT SUICIDAL BEHAVIOR BY ANALYSING SENTIMENTS EXPRESSED ON SOCIAL MEDIA PLATFORMS.

This study introduces a technique for leveraging sentiment analysis to detect potential suicide risk among social media users. Our approach utilizes machine learning to scrutinize the textual content of social media posts and identify signicant markers of suicidal behavior. Our methodology comprises data collection, data preprocessing, data labeling, machine learning model training, and model testing. The effectiveness of our approach is assessed using precision, recall, and F1 score metrics. The outcome of our evaluation demonstrates that our method is adept at detecting individuals who may be at risk of suicide on social media, yielding an impressive F1 score of 0.85.

Study on the strategy of medical security for rare diseases in China from the perspective of public concern and emotion：taking nosinasine as an example / 中国药房

OBJECTIVE To mine the focus and emotional attitude of the public on rare diseases， and to provide decision- making reference for relevant departments to formulate and implement relevant policies， systems and strategies for medical security of rare diseases. METHODS Latent Dirichlet allocation （LDA） topic model and sentiment analysis method were used to analyze the comment text of short videos related to the “nosinasine” medical insurance admission event on the Bilibili video website， mine the theme and sentiment tendency of the text， and put forward relevant strategy suggestions. RESULTS A total of 8 videos with tens of thousands of playback and 7 109 text data were obtained. According to the LDA analysis， online public paid attention to 9 topics related to rare diseases （the price of rare disease drugs， the inclusion of rare disease drugs in medical insurance， the status quo of research and development of rare disease drugs， the scope of medical insurance and the medical security system， the plight of rare disease patients， the prevention and screening of rare diseases， the value of rare disease drugs in medical insurance， the Chinese and western medical methods of rare diseases， and the supply and demand status of rare disease drugs）， which could be summarized into 4 categories according to the objects of concern （rare disease drugs， rare disease medical insurance， rare disease medical and health services and rare disease patient groups）. On the whole， the emotional tendency of the Internet public towards each topic showed a low positive and high negative tendency. CONCLUSIONS The public paid more attention to the price， research and development， supply and demand of rare disease drugs， and was deeply worried about the current medical status of rare diseases in China. To strengthen and improve the medical security for patients with rare diseases， such as actively carrying out public health services for rare diseases， strengthening cooperation in the diagnosis and treatment of rare diseases， and researching rare disease drugs， etc. Chinese medical and health departments can make concerted efforts in medical and health services， drug supply security， medical security and other social security.

Feelings about birth by a group of high-risk pregnant women / Sentimientos sobre el parto de un grupo de gestantes de alto riesgo / Sentimentos a respeito do nascimento por um grupo de gestantes de alto risco

ABSTRACT Objective: to understand feelings about birth among a group of high-risk pregnant women. Method: a descriptive and qualitative study, using Alfred Schütz's social phenomenology as a philosophical theoretical framework. The study included 25 pregnant women undergoing high-risk prenatal care. The interview had the following guiding questions: tell me about your feelings regarding the moment of birth/childbirth; How do you deal with the high-risk diagnosis? What are your expectations for birth/childbirth? Results: five categories emerged: Fear of obstetric care; Fear of complications with the baby; Fear of cesarean section; Resilience in the face of high-risk pregnancy; and Expectations for birth. Considerations: high-risk pregnant women are afraid of the care they will receive, the risks and concern about the baby's vitality at birth. The importance of care is emphasized, with a welcoming environment, bonding and communication between health team and pregnant woman.

RESUMEN Objetivo: comprender los sentimientos sobre el parto de un grupo de gestantes de alto riesgo. Método: estudio descriptivo y cualitativo, utilizando como marco teórico filosófico la fenomenología social de Alfred Schütz. El estudio incluyó a 25 mujeres embarazadas que se sometían a atención prenatal de alto riesgo. La entrevista tuvo las siguientes preguntas orientadoras: cuénteme sobre sus sentimientos con respecto al momento del nacimiento/parto; ¿Cómo lidia con el diagnóstico de alto riesgo? ¿Cuáles son sus expectativas para el nacimiento/parto? Resultados: surgieron cinco categorías: Miedo a la atención obstétrica; Miedo a las complicaciones con el bebé; Miedo a la cesárea; Resiliencia ante el embarazo de alto riesgo; y Expectativas de nacimiento. Consideraciones: las gestantes de alto riesgo tienen miedo de la asistencia que recibirán, de los riesgos y aprensión en cuanto a la vitalidad del bebé al nacer. Se destaca la importancia de la asistencia con ambiente acogedor, vínculo y comunicación entre el equipo de salud y la gestante.

RESUMO Objetivo: compreender os sentimentos a respeito do nascimento por um grupo de gestantes de alto risco. Método: estudo descritivo e qualitativo, tendo a fenomenologia social de Alfred Schütz como referencial teórico filosófico. Participaram do estudo 25 gestantes em acompanhamento de pré-natal de alto risco. A entrevista contou com as seguintes questões norteadoras: fale-me sobre seus sentimentos em relação ao momento do nascimento/parto; Como você lida com o diagnóstico de alto risco? Quais suas expectativas para o nascimento/parto? Resultados: emergiram cinco categorias: Medo da assistência obstétrica; Medo das complicações com o bebê; Medo da cesariana; A resiliência diante da gestação de alto risco; e Expectativas para o nascimento. Considerações: as gestantes de alto risco sentem medo da assistência que receberão, dos riscos e apreensividade quanto à vitalidade do bebê no nascimento. Ressalta-se a importância de assistência com ambiente acolhedor, efetivação de vínculo e comunicação entre equipe de saúde e gestante.

Sentimentos de estudantes de mestrado diante a morte da pessoa em situação crítica / Feelings of students in a master's in nursing program facing the death of patients in a critical situation

A morte faz parte do quotidiano da vida dos enfermeiros, principalmente quando lidam com pacientes em situação crítica. A forma como percecionam a morte pode ser relevante para uma prestação de cuidados humanizados. Objetivo: identificar quais os sentimentos de estudantes de um programa de mestrado perante a morte e a sua influência na prestação de cuidados a pacientes críticos. Método: Trata-se de uma pesquisa de abordagem qualitativa, aprovada pela comissão de ética da Universidade (Doc11/CE/2018 de 09/04/2018). Realizaram-se entrevistas a 11 estudantes, processadas por análise de conteúdo. Resultados: os principais sentimentos associados à morte dos pacientes foram: impotência, frustração/revolta, tristeza/angústia, aceitação, alívio e distanciamento. Conclusão: os estudantes criam barreiras emocionais para gerir o sofrimento dos pacientes com que lidam, sendo importante que estas não comprometam a qualidade dos cuidados. Os sentimentos dos estudantes perante a morte influenciam positivamente o cuidado ao paciente crítico, pois as vivências e experiência de vida permitem-lhes prestá-los com mais serenidade

Death is part of nurses' daily lives, especially when they deal with patients in critical situations. The way they perceive death may be relevant for providing humanized care. Objective: to identify the feelings of students of a master's program towards death and its influence on care provided to critical patients. Method: This is a study with a qualitative approach, approved by the ethics committee of the University (Doc11/CE/2018 of 09/04/2018). Interviews were carried out with 11 students, processed by content analysis. Results: the main feelings associated with the death of patients were: impotence, frustration/revolt, sadness/anguish, acceptance, relief, and distancing. Conclusion: students create emotional barriers to manage the suffering of the patients they deal with, and it is important that these do not compromise the quality of care. Students' feelings towards death positively influence critical patient care, as their experiences and life experience allow them to provide care more calmly.

Distanciamento social na pandemia da covid-19: sentimentos vivenciados por pessoas idosas / Distanciamiento social en la pandemia de covid-19: sentimientos experimentados por pesronas mayores / Social distancing in the covid-19 pandemic: feelings experienced by older people

Objetivo: conhecer os sentimentos vivenciados por pessoas idosas diante do distanciamento social na pandemia da Covid-19. Método: estudo qualitativo que adotou como referencial a Teoria das Representações Sociais pelo método do Discurso do Sujeito Coletivo. Participaram do estudo 29 pessoas idosas e a seleção foi do tipo intencional ou teórico, utilizando a técnica de snowball (bola de neve). Os dados foram coletados entre outubro e dezembro de 2020, por meio de um questionário de caracterização sociodemográfica, familiar e de saúde e uma questão aberta norteadora do estudo. Os depoimentos foram gravados, transcritos e analisados. Resultados: as pessoas idosas relataram vivenciar os sentimentos de preocupação, medo, naturalidade, conforto, com maior predomínio dos sentimentos de desconforto, tristeza, solidão e segurança. Considerações finais: sentimentos positivos e negativos foram vivenciados pelas pessoas idosas durante o período de distanciamento social pela pandemia da Covid-19.

Objetivo: conocer los sentimientos vividos por personas ancianas ante el distanciamiento social en la pandemia de Covid-19. Método: estudio cualitativo que adoptó como referencial la Teoría de las Representaciones Sociales por el método del Discurso del Sujeto Colectivo. Participaron del estudio 29 personas mayores y la selección fue del tipo intencional o teórico, utilizando la técnica de snowball (bola de nieve). Los datos fueron recogidos entre octubre y diciembre de 2020, por medio de un cuestionario de caracterización sociodemográfica, familiar y de salud y una cuestión abierta orientadora del estudio. Las declaraciones fueron grabadas, transcritas y analizadas. Resultados: las personas mayores relataron vivenciar los sentimientos de preocupación, miedo, naturalidad, confort, con mayor predominio de los sentimientos de incomodidad, tristeza, soledad y seguridad. Consideraciones finales: sentimientos positivos y negativos fueron vividos por las personas mayores durante el período de distanciamiento social por la pandemia de Covid-19.

Objective: to know the feelings experienced by elderly people in the face of social distancing in the Covid-19 pandemic. Method: qualitative study that adopted as reference the Theory of Social Representations by the method of Collective Subject Discourse. 29 elderly people participated in the study and the selection was intentional or theoretical, using the snowball technique. Data were collected between October and December 2020, through a questionnaire of sociodemographic, family and health characterization and an open question guiding the study. The statements were recorded, transcribed and analyzed. Results: the elderly reported experiencing feelings of worry, fear, naturalness, comfort, with a greater predominance of feelings of discomfort, sadness, loneliness and security. Final considerations: positive and negative feelings were experienced by the elderly during the period of social distancing due to the Covid-19 pandemic.

Análisis de sentimientos y tópicos sobre las vacunas cubanas Soberana 02 y Abdala en Twitter

El análisis de sentimientos o minería de opiniones es una rama de la computación que permite analizar opiniones, sentimientos y emociones en ciertas áreas de interés social como productos, servicios, organizaciones, compañías, eventos y temas de interés actual. En tal sentido se propuso identificar los sentimientos y tópicos presentes en los tweets que hicieron mención a las vacunas cubanas Soberana 02 y Abdala en la red social Twitter. Se optó por los lenguajes de programación Python y R con sus librerías específicas para la ciencia de datos. La primera parte del estudio, que abarcó desde el web scraping hasta la cuantificación de las palabras más usadas, se realizó con Python y las siguientes librerías: tweepy, pandas, re, nltk y matplotlib. Mientras que la segunda, que fue la del análisis de sentimientos y detección de tópicos, se implementó con R y se utilizó: tokenizers, tm, syuzhet, topic modeling, tidyverse, barplot y wordcloud. Se obtuvo que entre los términos con que más se dialoga en Twitter están dosis, vacunas, eficacia, cubanos, candidatos, millones, país, personas, recibido y población. En los tweets las emociones predominantes fueron el miedo y, ligeramente por encima, la confianza; en la polaridad predominó la positiva, como expresión del contexto vivido en el cual se desarrolló la campaña de vacunación. A partir de los tópicos identificados y los términos que se relacionaron con las emociones predominantes, así como por la polaridad, se aprecia consenso en torno a las vacunas Soberana 02 y Abdala.

Sentiment analysis or opinion mining is a branch of computing that allows analyzing opinions, feelings and emotions in certain areas of social interest such as products, services, organizations, companies, events and topics of current interest. In this sense, the objective of this paper was to identify the feelings and topics present in the tweets mentioning the Cuban vaccines Soberana 02 and Abdala on Twitter social network. The programming languages Python and R with their specific libraries for data science were chosen. The first part of the study, which ranged from web scraping to the quantification of the most used words, was carried out with Python and the libraries tweepy, pandas, re, nltk and matplotlib. While the second, which was the sentiment analysis and topic detection, was implemented with R and used tokenizers, tm, syuzhet, topic modeling, tidyverse, barplot, and wordcloud. It was obtained that among the terms with which there is more dialogue on Twitter are doses, vaccines, efficacy, Cubans, candidates, millions, country, people, received and population. In the tweets, the predominant emotions were fear and confidence, slightly above it; in the polarity, the positive one predominated, as an expression of the lived context in which the vaccination campaign was developed. A consensus can be perceived around the vaccines Soberana 02 and Abdala, from the identified topics and the terms that were related to the predominant emotions, as well as the polarity.

HPV vaccination in China based on website platform information / 上海预防医学

ObjectiveTo analyze the online public Q&A texts on HPV vaccine， focus on the important issues related to HPV vaccination and cervical cancer prevention in China， and propose strategies and suggestions. MethodsThe latent Dirichlet allocation （LDA） topic model was employed to extract key topics of 15 565 Q&A texts related to HPV vaccines from the social Q&A platform "Zhihu". The Baidu AI sentiment analysis tool was used to analyze the emotional tendencies of the texts corresponding to each topic， and the topics were classified based on the strategic coordinate method. ResultsOnline users focused on eight topics about HPV vaccine information. Among them， vaccination knowledge， HPV vaccination hesitation， and HPV vaccine development and marketing belonged to the low positivity-high negativity emotional topics， HPV infection and high-risk factors belonged to the low positivity-low negativity emotional topics， and HPV vaccine appointment channels， comparison between domestic and imported vaccines， HPV vaccines and cervical cancer prevention， and HPV vaccine types and selection were grouped under high positivity-low negativity emotional topics. ConclusionPublic concerns regarding HPV vaccines can be classified into three major dimensions： health knowledge， health beliefs， and health behaviors. Overall， the public's views and attitudes towards vaccine-related issues are not optimistic. Strengthening science publicity and education， enhancing vaccine supervision， and encouraging enterprises’ innovative research and development capability are effective strategies to improve public awareness of cervical cancer prevention and accelerate the full HPV vaccination coverage.

Análisis de sentimiento de tweets sobre la vacuna contra el COVID-19 en países iberoamericanos hispanohablantes / Sentiment analysis of tweets about the COVID-19 vaccine in Spanish-speaking Ibero-American countries

Resumen Introducción: En este estudio se evalúa la emocionalidad asociada a la vacunación contra el COVID-19 a partir de la técnica de análisis de sentimientos de los tweets en países iberoamericanos hispanohablantes. Método: En enero de 2021 se realizó un estudio mixto observacional transversal de 41023 tweets procedentes de nueve países iberoamericanos hispanohablantes (Chile, El Salvador, Venezuela, Ecuador, Argentina, México, Panamá, Perú y España) con una fase cuantitativa y técnicas de análisis de sentimientos mediante algoritmos de inteligencia artificial y una fase cualitativa donde se realizó un análisis del discurso de los tweets cuya emocionalidad era en extremo positiva y negativa. Resultados: A partir del análisis de sentimiento de los tweets, se observó que los países presentan una emocionalidad negativa asociada a la vacunación contra el COVID-19, que se podría atribuir a la desconfianza hacia las autoridades y a la eficacia o seguridad de las vacunas, según el análisis del discurso en los tweets de emocionalidad en extremo negativa. Conclusiones: Las técnicas de análisis de sentimientos en combinación con el análisis del discurso de la emocionalidad extrema posibilitaron la monitorización de las opiniones negativas y sus posibles factores asociados en la vacunación contra el COVID-19 en los países iberoamericanos estudiados.

Abstract Introduction: This study evaluates the emotionality associated with vaccination against COVID-19 using the sentiment analysis technique of tweets in Spanish-speaking Ibero-American countries. Method: In January 2021 a mixed cross-sectional observational study of 41023 tweets from nine Spanish-speaking Ibero-American countries (Chile, El Salvador, Venezuela, Ecuador, Argentina, Mexico, Panama, Peru and Spain) was carried out with a quantitative phase and analysis techniques of feelings based on artificial intelligence algorithms and a qualitative phase where an analysis of the discourse of the tweets whose emotionality was extremely positive and negative was carried out. Results: From the sentiment analysis of the tweets, it was observed that the countries present a negative emotionality associated with the vaccination against COVID-19, which could be attributed to mistrust towards the authorities and the efficacy or safety of the vaccines, according to the analysis of the discourse in the extremely negative emotionality tweets. Conclusions: Sentiment analysis techniques in combination with extreme emotionality discourse analysis made it possible to monitor negative opinions and their possible associated factors in vaccination against COVID-19 in the Ibero-American countries studied.

Twitter sentiment analysis for COVID-19 associated mucormycosis

Purpose: COVID?19?associated mucormycosis (CAM) was a serious public health problem during the second wave of COVID?19 in India. We planned to analyze public perceptions by sentiment analysis of Twitter data regarding CAM. Methods: In this observational study, the application programming interface (API) provided by the Twitter platform was used for extracting real?time conversations by using keywords related to mucormycosis (colloquially known as “black fungus”), from May 3 to August 29, 2021. Lexicon?based sentiment analysis of the tweets was done using the Vader sentiment analysis tool. To identify the overall sentiment of a user on any given topic, an algorithm to label a user “k” based on their sentiments was used. Results: A total of 4,01,037 tweets were collected between May 3 and August 29, 2021, and the peak frequency of 1,60,000 tweets was observed from May 17 to May 23, 2021. Positive sentiment tweets constituted a larger share as compared to negative sentiment tweets, with weekly variations. A temporal analysis of the demand for utilities showed that the demand was high in the initial period but decreased with time, which was associated with the availability of resources. Conclusion: Sentiment analysis using Twitter data revealed that social media platforms are gaining popularity to express one’s emotions during the ongoing COVID?19 pandemic. In our study, time?based assessment of tweets showed a reduction over time in the frequency of negative sentiment tweets. The polarization in the retweet network of users, based on sentiment polarity, showed that the users were well connected, highlighting the fact that such issues bond our society rather than segregating it.

A aplicação da técnica de análise de sentimento em mídias sociais como instrumento para as práticas da gestão social em nível governamental / La aplicación de la técnica de análisis de sentimiento en medios sociales como instrumento para las prácticas de la gestión social a nivel gubernamental / The application of the sentiment analysis technique in social media as a tool for social management practices at the governmental level

Resumo A análise de sentimento é uma técnica de descoberta de conhecimento por meio da mineração de dados, sua finalidade é revelar a opinião das pessoas sobre temas específicos. Essa é uma técnica apropriada para aplicação em fontes de dados não estruturados, como as mídias sociais, que abarcam informações sobre diversos temas, inclusive política e administração pública. O objetivo deste estudo foi identificar se a análise de sentimento pode refletir a opinião pública e, assim, trazer contribuições para as práticas da gestão social. Para tanto, a técnica foi aplicada para revelar as opiniões dos cidadãos expressas no Twitter sobre alguns dos principais programas sociais em vigor no Brasil durante o governo Dilma Rousseff. O estudo consistiu no confronto entre os resultados da análise de sentimento e os conceitos e aplicações envolvendo quatro estratégias de utilização de mídias sociais pelos governos sob a ótica da gestão social. Os resultados da pesquisa revelaram que a técnica da análise de sentimento pode contribuir para as práticas da gestão social no contexto da estratégia de rede.

Resumen El análisis de sentimiento es una técnica de descubrimiento de conocimiento a partir de la minería de datos que tiene la finalidad de revelar la opinión de las personas sobre temas específicos. Esta es una técnica apropiada para aplicación en fuentes de datos no estructurados, como los medios sociales, que abarcan información sobre diversos temas, inclusive política y administración pública. En este ámbito, el objetivo de este estudio fue identificar si el análisis de sentimiento puede reflejar la opinión pública y, así, traer contribuciones a las prácticas de la gestión social. Para ello, la técnica se aplicó para revelar la opinión de los ciudadanos expresada en Twitter sobre algunos de los principales programas sociales vigentes en Brasil durante el gobierno de Dilma Rousseff. El estudio consistió en la confrontación de los resultados del análisis de sentimiento con los conceptos y aplicaciones que involucran cuatro estrategias de utilización de medios sociales por parte de los gobiernos bajo la óptica de la gestión social. Los resultados de la investigación revelaron que la técnica de análisis de sentimiento puede contribuir a las prácticas de la gestión social en el contexto de la estrategia de red.

Abstract Sentiment analysis is a knowledge discovery technique developed from data mining; its purpose is to reveal people's opinions on specific topics. This is an appropriate technique to apply to unstructured data sources, such as social media, that cover information on a variety of topics (such as politics and public administration). In this context, the objective of this study was to identify whether sentiment analysis can reflect public opinion and, thus, contribute to practices of social management. Therefore, the sentiment analysis technique was applied to reveal citizens' opinions, which were expressed on Twitter and concerned some of the main social programs in force during Brazil's Rousseff government. The study consisted of a comparison between the results of the sentiment analysis and the concepts and applications involving four strategies of social media used by governments from the point of view of social management. The results revealed that the sentiment analysis technique could contribute to social management practices in the context of the network strategy.

Enfoques big data para la comunicación en salud: análisis de redes y análisis de sentimientos a gran escala / Big data approaches in health communication: Network analysis and large-scale supervised sentiment analysis

Resumen Se exponen los dos principales enfoques metodológicos para la investigación con big data en comunicación en salud: el análisis de redes y el análisis de sentimientos. Primeramente, se explica el cambio de paradigma que está sufriendo el campo de la comunicación en salud gracias a los métodos computacionales para el análisis de datos masivos y se dan ejemplos de su uso en estudios y experiencias previas. Seguidamente, se exponen los conceptos (nodo/arista) y las principales variables de centralidad que se estudian en el análisis de red en procesos de difusión de innovaciones en salud; y, finalmente, se explica cómo ejecutar el procedimiento de análisis de sentimientos supervisado para estudiar contenidos de salud a gran escala.

Abstract The two main methodological approaches for research with big data in health communication are presented: network analysis and the analysis of feelings. Firstly, the paradigm change that the communication field in health is experiencing, thanks to the computational methods for the analysis of massive data, and examples of its use in previous studies and experiences are explained. Next, the concepts (node / edge) and the main centrality variables that are studied in the network analysis in health innovation dissemination processes are exposed; and, finally, it is explained how to execute the supervised feelings analysis procedure to study large-scale health content

Advanced Daily Prediction Model for National Suicide Numbers with Social Media Data

OBJECTIVE: Suicide is a significant public health concern worldwide. Social media data have a potential role in identifying high suicide risk individuals and also in predicting suicide rate at the population level. In this study, we report an advanced daily suicide prediction model using social media data combined with economic/meteorological variables along with observed suicide data lagged by 1 week. METHODS: The social media data were drawn from weblog posts. We examined a total of 10,035 social media keywords for suicide prediction. We made predictions of national suicide numbers 7 days in advance daily for 2 years, based on a daily moving 5-year prediction modeling period. RESULTS: Our model predicted the likely range of daily national suicide numbers with 82.9% accuracy. Among the social media variables, words denoting economic issues and mood status showed high predictive strength. Observed number of suicides one week previously, recent celebrity suicide, and day of week followed by stock index, consumer price index, and sunlight duration 7 days before the target date were notable predictors along with the social media variables. CONCLUSION: These results strengthen the case for social media data to supplement classical social/economic/climatic data in forecasting national suicide events.

Assessment of public sentiment on medical and health reform at grass-root level based on 2015-2017 public sentiment monitoring data / 中华医学图书情报杂志

The medical and health reform at grass-root level was monitored during the NPC and CPPCC from 2015-2017 . The public sentiment on medical and health reform at grass-root level in recent years was thus as-sessed according to the text mining and data analysis using the R language and Python method from the aspects ofnow rural cooperative medical care,comprehensive health reform at grass-root level,health service develop-ment at grass-root level and Internet + medical care in order to provide reference for the effective feedback of achievements and development in policies of medical and health reform at grass-root level.

Terapia de exposición con realidad virtual evaluada mediante minería de textos

El artículo presenta un estudio acerca de la aplicación de Minería de Textos en la evaluación de la psicoterapia. Nuestros voluntarios fueron sujetos diagnosticados con fobia social y tratados con terapia de exposición en Realidad Virtual. El cálculo de la polaridad emocional, desde el enfoque del análisis sintáctico, fue aplicado al material narrativo producido por los propios voluntarios. Para su valoración cuantitativa se utilizó el lexicón de sentimientos LIWC (Linguistic Inquiry and Word Count). Los resultados obtenidos muestran una relación proporcional entre el nivel emocional global de los textos y el avance de la práctica psicológica, lo que sugiere su consideración como evidencia para medir la efectividad de la terapia.

This article presents a study about the application of text mining in psychotherapeutic evaluations. Our volunteers are subjects diagnosed with social phobia and treated with virtual reality exposure therapy. Evaluación de psicoterapia Sentiment analysis, through syntactic analysis, was applied over narrative material the volunteers produced themselves; forthe quantitative assessment, we used the sentiment lexicon LIWC (Linguistics Inquiry and Word Count). The results show a proportional relation between the emotional level of the narrative material and the advancement of therapy, which suggests the consideration of text mining as an effectiveness indicator for psychotherapies.

O artigo apresenta um estudo sobre a aplicação do mineração de texto na avaliação da psicoterapia. Nossos voluntários foram pacientes com diagnóstico de fobia social e tratada com terapia de exposição em Realidade Virtual. O cálculo da polaridade emocional, a partir da abordagem de análise, foi aplicada no material narrativa produzida pelos próprios voluntários. Foi utilizada para a avaliação quantitativa o léxico de sentimentos LIWC (Linguistic Inquiry e Word Count). Os resultados mostram uma relação proporcional entre o nível emocional general de textos e o avanço da prática psicológica, sugerindo-sea sua consideração como prova para medir a eficacia da terapia.

Sentiment analysis to assess the patient´s adherence: a systematic review / Análise de sentimento para avaliar a aderência: uma revisão sistemática / El análisis de sentimientos para evaluar la adherencia del paciente: una revisión sistemática

OBJECTIVE: To conduct a systematic review of the use in sentiment analysis on social media to identify or assess patient's treatment adherence, and evaluate its application, benefits and future research. METHODS: A systematic review of the literature was carried out by identifying published articles on the main databases of computing and healthcare. Search strings were built by combining keywords related to adherence, social media, data analysis and sentiment analysis. RESULTS: From a total of 709 articles screened, it wasn't possible to identify any study related to the objective. However, we could select 15 which presented some similarity degree and yet very heterogeneous, they were analyzed accordingto six dimensions: Adherence, Data Source, Psychology, Methods, Tools and Sentiment Analysis. CONCLUSIONS: A strong agreement and trend can be observed on the potential use and importance of automatic techniques to collectand analyzed online patient data, especially related to assessment of adherence with sentiment analysis.