bluuebunny/crossref_metadata_2025_split huggingface dataset:
Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study
Authors: Boon-Itt Sakun , Skunkan Yukolpat 
Published: October 2020

Background
COVID-19 is a scientifically and medically novel disease that is not fully understood because it has yet to be consistently and deeply studied. Among the gaps in research on the COVID-19 outbreak, there is a lack of sufficient infoveillance data.

Objective
The aim of this study was to increase understanding of public awareness of COVID-19 pandemic trends and uncover meaningful themes of concern posted by Twitter users in the English language during the pandemic.

Methods
Data mining was conducted on Twitter to collect a total of 107,990 tweets related to COVID-19 between December 13 and March 9, 2020. The analyses included frequency of keywords, sentiment analysis, and topic modeling to identify and explore discussion topics over time. A natural language processing approach and the latent Dirichlet allocation algorithm were used to identify the most common tweet topics as well as to categorize clusters and identify themes based on the keyword analysis.

Results
The results indicate three main aspects of public awareness and concern regarding the COVID-19 pandemic. First, the trend of the spread and symptoms of COVID-19 can be divided into three stages. Second, the results of the sentiment analysis showed that people have a negative outlook toward COVID-19. Third, based on topic modeling, the themes relating to COVID-19 and the outbreak were divided into three categories: the COVID-19 pandemic emergency, how to control COVID-19, and reports on COVID-19.

Conclusions
Sentiment analysis and topic modeling can produce useful information about the trends in the discussion of the COVID-19 pandemic on social media as well as alternative perspectives to investigate the COVID-19 crisis, which has created considerable public awareness. This study shows that Twitter is a good communication channel for understanding both public concern and public awareness about COVID-19. These findings can help health departments communicate information to alleviate specific public concerns about the disease.
Efficacy of a Transdiagnostic Self-Help Internet Intervention for Reducing Depression, Anxiety, and Suicidal Ideation in Adults: Randomized Controlled Trial
Authors: Batterham Philip J , Calear Alison L , Farrer Louise , Gulliver Amelia , Kurz Ella 
Published: October 2020

Background
Low-intensity self-guided mental health interventions that are delivered on the web may meet the needs and preferences of adults with mild to moderate symptoms. However, few clinical trials have examined the effectiveness of self-guided transdiagnostic interventions within a naturalistic setting.

Objective
This randomized controlled trial (RCT) tests the effectiveness of the video-based transdiagnostic intervention FitMindKit in reducing depression symptoms (primary outcome), anxiety symptoms, disability, and suicidal ideation, relative to an attention-matched control condition called HealthWatch.

Methods
The RCT was conducted with adults living in the Australian Capital Territory, Australia. Participants (n=1986) were recruited through the web using social media advertisements, screened for psychological distress, and then randomized to receive one of two 4-week programs: FitMindKit (12-module psychotherapy intervention) or HealthWatch (12-module program providing general health information). Participants were assessed at baseline and at 4 weeks postbaseline. To maintain the ecological validity of the trial, participants completed brief assessments and interventions without direct researcher contact or incentives.

Results
Mixed model repeated-measures analyses of variance demonstrated that FitMindKit significantly improved depression symptoms (F1,701.7=3.97; P=.047), along with panic symptoms (F1,706.5=5.59; P=.02) and social anxiety symptoms (F1,680.0=12.37; P<.001), relative to the attention control condition. There were no significant effects on other outcomes.

Conclusions
Self-guided transdiagnostic interventions can be beneficial when delivered directly to end users through the internet. Despite low adherence and small effect sizes, the availability of such interventions is likely to fill a critical gap in the accessibility of mental health services for the community.

Trial Registration
Australian New Zealand Clinical Trials Registry ACTRN12618001688279; http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=376113.

International Registered Report Identifier (IRRID)
RR2-10.1016/j.conctc.2019.100341
Where Virtual Care Was Already a Reality: Experiences of a Nationwide Telehealth Service Provider During the COVID-19 Pandemic
Authors: Uscher-Pines Lori , Thompson James , Taylor Prentiss , Dean Kristin , Yuan Tony , Tong Ian , Mehrotra Ateev 
Published: October 2020

Background
The COVID-19 pandemic has led to an increase in the use of and demand for telehealth services.

Objective
Here, we describe the utilization of telehealth services provided by Doctor On Demand, Inc., a well-known telehealth company in the United States, before and during the COVID-19 pandemic. We also explore how the number of virtual visits, reasons for visits, and patients served changed over time.

Methods
We reported data as a percentage change from the baseline week during 2 distinct time periods: February-June 2019 and February-June 2020 based on 4 categories of visits: respiratory illness, unscheduled behavioral health, scheduled behavioral health, and chronic illness.

Results
In 2020, the total visit volume increased considerably from March through April 7, 2020 (59% above the baseline) and then declined through the week of June 2 (15% above the baseline). Visits for respiratory illnesses increased through the week of March 24 (30% above the baseline) and then steadily declined through the week of June 2 (65% below the baseline). Higher relative increases were observed for unscheduled behavioral health and chronic illness visits through April (109% and 131% above the baseline, respectively) before a decline through the week of June 2 (69% and 37% above the baseline, respectively). Increases in visit volume among rural residents were slightly higher than those among urban residents (peak at 64% vs 58% above the baseline, respectively).

Conclusions
Although this telehealth service provider observed a substantial increase in the volume of visits during the COVID-19 pandemic, it is interesting to note that this growth was not fueled by COVID-19 concerns but by visits for behavioral health and chronic illness. Telehealth services may play a role as a “safety valve” for patients who have difficulty accessing care during a public health emergency.
Effects of a Mobile App Called Quittr, Which Utilizes Premium Currency and Games Features, on Improving Engagement With Smoking Cessation Intervention: Pilot Randomized Controlled Trial
Authors: Bindoff Ivan , Ling Tristan R , Gee Peter , Geelan Benjamin , Ferguson Stuart G , Peterson Gregory M 
Published: October 2020

Background
Numerous mobile health (mHealth) apps have been developed to support smokers attempting to quit smoking. Although these apps have been reported to be successful, only modest improvements in the quit rate have been measured. It has been proposed that efforts to improve user engagement and retention may improve the quit rate further. Owing to the high cost of smoking-related disease, it is considered worthwhile to pursue even small improvements.

Objective
The aim of this study was to test a novel smartphone app that leverages premium currency strategies developed by the mobile games industry in an attempt to improve engagement and retention with a smoking cessation intervention.

Methods
We designed and developed a smoking cessation app called “Quittr” in line with previously developed smoking cessation mHealth apps. In addition to this established framework, we added a stand-alone fully featured city-building clicker-style game called “Tappy Town,” and a premium virtual currency called “QuitCoins.” The user earns QuitCoins for using the app in a way that contributes positively toward their quit attempt, and they can redeem these coins in Tappy Town for bonuses. To establish whether these features improved engagement and retention, we ran a 5-month randomized controlled trial where the intervention group had the full app with the extra games features, while the control group had the standard app only. Recruitment was performed via web-based advertising. Participants (N=175) had no direct contact with the researchers or other support staff.

Results
No significant differences in terms of engagement, retention, or smoking outcomes were found between the control and intervention groups. However, survey data indicated that the majority of the participants valued Tappy Town (10/17, 59%) and the QuitCoins rewards system (13/17, 77%). Usage data also suggested that Tappy Town was widely played and was generally appealing to users (mean total time spent in app, control group: 797 seconds vs intervention group: 3502 seconds, P<.001). Analysis of the results suggests that users in the intervention group may have been negatively affected by the aspects of the chosen design, and some theories were explored to explain this unexpected outcome.

Conclusions
Although the novel features of the Quittr app failed to improve the key outcomes measured in this study, there were enough positive indications to warrant further exploration of the concept. Additional research will be required to identify and correct any design flaws that may have adversely affected our participants before a follow-up study can be completed.

Trial Registration
Australian and New Zealand Clinical Trials Register ACTRN12617000491369; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372661&isReview=true
An Easy-to-Use Machine Learning Model to Predict the Prognosis of Patients With COVID-19: Retrospective Cohort Study
Authors: Kim Hyung-Jun , Han Deokjae , Kim Jeong-Han , Kim Daehyun , Ha Beomman , Seog Woong , Lee Yeon-Kyeng , Lim Dosang , Hong Sung Ok , Park Mi-Jin , Heo JoonNyung 
Published: October 2020

Background
Prioritizing patients in need of intensive care is necessary to reduce the mortality rate during the COVID-19 pandemic. Although several scoring methods have been introduced, many require laboratory or radiographic findings that are not always easily available.

Objective
The purpose of this study was to develop a machine learning model that predicts the need for intensive care for patients with COVID-19 using easily obtainable characteristics—baseline demographics, comorbidities, and symptoms.

Methods
A retrospective study was performed using a nationwide cohort in South Korea. Patients admitted to 100 hospitals from January 25, 2020, to June 3, 2020, were included. Patient information was collected retrospectively by the attending physicians in each hospital and uploaded to an online case report form. Variables that could be easily provided were extracted. The variables were age, sex, smoking history, body temperature, comorbidities, activities of daily living, and symptoms. The primary outcome was the need for intensive care, defined as admission to the intensive care unit, use of extracorporeal life support, mechanical ventilation, vasopressors, or death within 30 days of hospitalization. Patients admitted until March 20, 2020, were included in the derivation group to develop prediction models using an automated machine learning technique. The models were externally validated in patients admitted after March 21, 2020. The machine learning model with the best discrimination performance was selected and compared against the CURB-65 (confusion, urea, respiratory rate, blood pressure, and 65 years of age or older) score using the area under the receiver operating characteristic curve (AUC).

Results
A total of 4787 patients were included in the analysis, of which 3294 were assigned to the derivation group and 1493 to the validation group. Among the 4787 patients, 460 (9.6%) patients needed intensive care. Of the 55 machine learning models developed, the XGBoost model revealed the highest discrimination performance. The AUC of the XGBoost model was 0.897 (95% CI 0.877-0.917) for the derivation group and 0.885 (95% CI 0.855-0.915) for the validation group. Both the AUCs were superior to those of CURB-65, which were 0.836 (95% CI 0.825-0.847) and 0.843 (95% CI 0.829-0.857), respectively.

Conclusions
We developed a machine learning model comprising simple patient-provided characteristics, which can efficiently predict the need for intensive care among patients with COVID-19.
Diagnosing Chronic Obstructive Airway Disease on a Smartphone Using Patient-Reported Symptoms and Cough Analysis: Diagnostic Accuracy Study
Authors: Porter Paul , Claxton Scott , Brisbane Joanna , Bear Natasha , Wood Javan , Peltonen Vesa , Della Phillip , Purdie Fiona , Smith Claire , Abeyratne Udantha 
Published: October 2020

Background
Rapid and accurate diagnosis of chronic obstructive pulmonary disease (COPD) is problematic in acute care settings, particularly in the presence of infective comorbidities.

Objective
The aim of this study was to develop a rapid smartphone-based algorithm for the detection of COPD in the presence or absence of acute respiratory infection and evaluate diagnostic accuracy on an independent validation set.

Methods
Participants aged 40 to 75 years with or without symptoms of respiratory disease who had no chronic respiratory condition apart from COPD, chronic bronchitis, or emphysema were recruited into the study. The algorithm analyzed 5 cough sounds and 4 patient-reported clinical symptoms, providing a diagnosis in less than 1 minute. Clinical diagnoses were determined by a specialist physician using all available case notes, including spirometry where available.

Results
The algorithm demonstrated high positive percent agreement (PPA) and negative percent agreement (NPA) with clinical diagnosis for COPD in the total cohort (N=252; PPA=93.8%, NPA=77.0%, area under the curve [AUC]=0.95), in participants with pneumonia or infective exacerbations of COPD (n=117; PPA=86.7%, NPA=80.5%, AUC=0.93), and in participants without an infective comorbidity (n=135; PPA=100.0%, NPA=74.0%, AUC=0.97). In those who had their COPD confirmed by spirometry (n=229), PPA was 100.0% and NPA was 77.0%, with an AUC of 0.97.

Conclusions
The algorithm demonstrated high agreement with clinical diagnosis and rapidly detected COPD in participants presenting with or without other infective lung illnesses. The algorithm can be installed on a smartphone to provide bedside diagnosis of COPD in acute care settings, inform treatment regimens, and identify those at increased risk of mortality due to seasonal or other respiratory ailments.

Trial Registration
Australian New Zealand Clinical Trials Registry ACTRN12618001521213; http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375939
Tatar Philosophy (General and Special Traits — The Middle Ages)
Authors: Yuzeev A. N. 
Published: October 2020

Tatar philosophy has a long history and dates back to the ancestors of the Tatars, i. e. the Volga Bulgars, who fi rst laid the foundations of philosophical knowledge in the Middle Ages in the X century. Medieval Tatar literature of the X — third quarter of the XVIII centuries is one of the foundations of Tatar social and philosophical thought (A. Yasavi (XII century), Qul- Gali (XIII century), Qutb (XIV century), S. Sarai (XIV century), Muhammadyar (XVI century)). Most of the works of Tatar thinkers of the X–XVIII centuries are syncretic. Works at the same time were both a literary source, and a book on ethics, and an essay that reveals the philosophical views of Tatar thinkers.
Linguagem de Outrora na Poesia de Henriqueta Lisboa
Authors: Câmara Lima Edileide Patrícia 
Published: October 2020

Este trabalho apresenta uma proposta de vocabulário, antigo, nas poesias da autora Henriqueta Lisboa. Pelo léxico utilizado pela autora, podemos constatar as vivências, sentimentos e ideologias da poetisa e assim demonstrar retratos de uma época, a partir de vocábulos não mais usuais no presente. Para desenvolver esse trabalho o procedimento metodológico escolhido foi o da pesquisa bibliográfica. As orientações teórico-metodológicas estão de acordo com os pressupostos da Lexicologia. A organização do vocabulário apresenta os termos em ordem alfabética, seguidos de informações gramaticais, definição, remissiva e nota. Palavras-chave: Henriqueta Lisboa; Léxico; Poesia; Vocabulário.
Vocabulário do escritor Antônio Juraci Siqueira
Authors: Borges Fernandes Francisca Claudia , Pereira Machado Soares Eliane 
Published: October 2020

Este trabalho resulta de uma pesquisa sobre o vocabulário da obra literária do autor Antônio Juraci Siqueira, que reside na cidade de Belém, Estado do Pará, com o objetivo de estabelecer relações entre língua e memória, evidenciando os vocábulos que configuram o imaginário popular e a identidade coletiva da comunidade amazônida (pescadores, ribeirinhos, seringueiros). A criação literária de Siqueira, como representação da língua é, ao mesmo tempo, de caráter inovador e transgressor, seja na poesia ou na prosa, compartilha expressões, vocábulos utilizados pelos falantes de uma comunidade. Conforme Biderman (2001) o leitor, em diálogo com o texto poético, dever-se-á confrontar com a visão de mundo do artista e a significatividade daquela obra. O conjunto lexical empregado por um escritor demonstra a compreensão de sua competência para com a língua. A escolha do falante/escrevente, é a operação da aplicação do léxico de sua língua em escala subjetiva ao discurso. Os verbetes apresentados representam um recorte da pesquisa, fundamentado na Lexicologia, Terminologia, Socioterminologia, evidenciando a relação que a terminologia estabelece com a sociolinguística. Para elaboração do glossário nos pautamos nas orientações de Faulstich (2001), para quem o glossário é um inventário terminológico, de caráter seletivo que tem como escopo registrar e deliberar termos de domínios científicos, técnicos ou culturais, independente do suporte material em que se apresenta. O vocabulário é formatado a partir do uso da ferramenta computacional Lexique Pro e será organizado em ordem alfabética e apresentará os campos semânticos, com as respectivas informações gramaticais, definições e remissivas.
Variação semântico-lexical na fala de Tucuruí e suas contribuições para o ensino de Língua Portuguesa
Authors: Tavares Dias Cecilia Maria , Pereira Machado Soares Eliane 
Published: October 2020

Este artigo apresenta um estudo realizado em uma escola pública da cidade de Tucuruí, município do sudeste paraense, sobre a variação lexical na fala de moradores dessa localidade. Para a realização do trabalho, desenvolveu-se um projeto de pesquisa a partir de um projeto de intervenção pedagógica , utilizando-se a metodologia da pesquisa-ação, em que alunos participaram ativamente da coleta de dados com a aplicação de questões do ALiB, com o objetivo de identificar as variações lexicais existentes na fala de antigos moradores. O embasamento teórico remete aos postulados da Sociolinguística. Os resultados obtidos registram a riqueza semântico-lexical da região, a qual é apresentada num glossário, que é o produto do processo da intervenção. Dessa forma, espera-se contribuir para o o reconhecimento da variação linguística no ensino de língua, bem como para o conhecimento e o fortalecimento da formação da identidade cultural do povo dessa região.
Inflorescência terminal da bananeira em dois Atlas Linguísticos brasileiros: um estudo comparativo
Authors: Dias Marcelo Pires , De Oliveira Marilucia Barros 
Published: October 2020

Trata o presente artigo da diversidade lexical a partir de dados do Atlas Geossociolinguístico Quilombola do Nordeste do Pará (AGQUINPA) e do Atlas Linguístico do Brasil (ALiB). Trata-se de um estudo comparativo que tomou como base as respostas mapeadas nos dois atlas referidos para a questão 44 do Questionário Semântico-lexical do ALiB. O ALiB registrou respostas obtidas nas capitais brasileiras e considerou dois níveis de ensino: fundamental e superior. Já o AGQUINPA registrou a diversidade lexical em seis comunidades quilombolas localizadas no Nordeste Paraense e considerou apenas o ensino fundamental. Os resultados apresentados nos dois atlas mostram número alto de variantes para a referida questão a depender da região e apresentam diferenças e semelhanças entre a variedade usada nas capitais brasileiras e nas comunidades quilombolas paraenses.
Narrativas gaúchas: como o centauro dos pampas se transmutou em quimera
Authors: Machado Silas Rodrigues , De Farias Lais Dias 
Published: October 2020

O presente estudo tem por objetivo investigar a constituição da identidade cultural no discurso das narrativas gauchescas, levando em conta as representações do mito e não-mito presentes nos contos de Simões Lopes Neto e Cyro Martins, que habitam o imaginário do Rio Grande do Sul. Como corpus de análise, elegemos duas canções de bandas contemporâneas, Amigo Punk (1988) – Graforréia Xilarmônica – e Torpor Partes 2 e 3 (2014) – Cachorro Grande –, em que, busca-se compreender como este sujeito que agora habita um momento de fragmentação identitária é representado. Para tanto, elegemos como aporte teórico, os estudos de Stuart Hall acerca do sujeito contemporâneo.
Escola Pública e Projeto Social: o cotidiano das aulas de capoeira
Authors: Gorito Alex Dos Santos , Alves Marcelo Paraiso 
Published: October 2020

O presente trabalho tem como centralidade a prática da Capoeira no Programa Arte, Educação e Cidadania que está localizado na Cidade de Barra do Piraí-RJ. Considerando o impacto desta prática corporal no cotidiano dos estudantes que participam do projeto investigado, cabe refletir: Quais as contribuições da Capoeira para os sujeitos participantes? O objetivo do estudo foi investigar as possíveis contribuições das práticas socioculturais desenvolvidas pela Capoeira no referido programa, desenvolvido junto à comunidade da Chacrinha, município de Valença-RJ. Metodologicamente, optamos pelos Estudos do Cotidiano, pelo fato de mergulharmos nas práticas dos estudantes que participam do referido projeto. Utilizamos como instrumentos para produção de dados a roda de conversa e o diário de bordo, no intuito de apreender os registros, acontecimentos e modos comportamentais por meio de observações, que só se tornam possíveis mediante a participação cotidiana nas aulas de capoeira. Considerando ser está, uma pesquisa com estudantes, este trabalho foi aprovado com o parecer 2.168.033 e o CAAE 69443417.4.0000.5237 pelo comitê de ética de pesquisa do Centro Universitário de Volta Redonda. Os resultados revelam que o Projeto Capoeira resgata as raízes históricas, facilita o acesso à cultura corporal, fortalece as relações em grupo, mostra que os estudantes, ao adotarem valores na roda de capoeira, modificaram seus comportamentos em outros espaços de sociabilidade.
A ocorrência da conjunção aditiva “e” no texto de divulgação sobre o Programa Ciência sem Fronteiras na Revista Tecnológica da UTFPR
Authors: Lingnau Carina Merkle , Antonio Juliano Desiderato , Barbosa Pedro Luis Navarro 
Published: October 2020

Na Universidade Tecnológica Federal do Paraná (UTFPR) mais de 1600 alunos participaram do Programa Ciência sem Fronteiras (CsF), sendo que esta participação está divulgada em revista de edição comemorativa da UTFPR. O objetivo deste trabalho é discutir em linhas gerais a ocorrência da conjunção aditiva E em texto de divulgação sobre o Programa Ciência sem Fronteiras na UTFPR. Como metodologia utilizamos levantamento bibliográfico e pesquisa documental. Nossas discussões têm suporte teórico em Neves (1985), Castilho (2010), Pezatti (2005), entre outros. Com base nos trechos retirados como recorte percebemos que a maior parte das ocorrências da conjunção aditiva E estão entre os sintagmas nominais e são utilizados para diferentes situações semânticas.