Comparison of NEWS2 and PSI as mortality predictors in patients with community acquired pneumonia.

In the West, National Early Warning Score 2 (NEWS2) is commonly applied to predict the severity of illness using only bedside variables unlike the extensive Pneumonia Severity Index (PSI). The objective of this study was to compare these scores as mortality predictors in patients admitted with community acquired pneumonia (CAP). This cross-sectional study was conducted in Jinnah Postgraduate Medical Centre, Karachi, Pakistan, for six months in 2020 on 116 patients presenting with CAP. Cases of aspiration pneumonia, hospital acquired pneumonia, pulmonary tuberculosis, pulmonary embolism, and pulmonary oedema were excluded. In-hospital mortality was taken as the outcome of this study. The mean age of the participants was 46.9±20.5 years. The in-hospital mortalities were 45(38.8%). NEWS2 was 97.8% sensitive but only 15.5% specific in predicting the outcome, whereas PSI was less sensitive (68.9%) but more specific (50.7%), which showed that in comparison with PSI, NEWS2 is a more sensitive mortality predicting score among hospitalised CAP patients.

Dataset: Annotated soybean market news articles.

This dataset involves a collection of soybean market news through web scraping from a Brazilian website. The news articles gathered span from January 2015 to June 2023 and have undergone a labeling process to categorize them as relevant or non-relevant. The news labeling process was conducted under the guidance of an agricultural economics expert, who collaborated with a group of nine individuals. Ten parameters were considered to assist participants in the labeling process. The dataset comprises approximately 11,000 news articles and serves as a valuable resource for researchers interested in exploring trends in the soybean market. Importantly, this dataset can be utilized for tasks such as classification and natural language processing. It provides insights into labeled soybean market news and supports open science initiatives, facilitating further analysis within the research community.

Scientists in the news photos: Photographic portraits of scientists in China (1949-2022).

Photography plays an important role in science communication. This study investigates the photographic portraits of scientists in the news media in China from 1949 to 2022. The data consist of 1,071 photographs published in People's Daily, the most influential newspaper in China. The photographs are analysed according to a framework based on previous studies on the visual representation of scientists. Analysis shows an overall image of scientists that demonstrates distinctive 'Chinese' features, such as the prominence of group photos and governmental honours. Diachronically, the visual image of scientists evolved from the early farmer scientists acclaimed in midst of political struggle to social elites and stars celebrated as China's hope for indigenous innovation. The study enriches our understanding of the visual representation of scientists in China, and sheds light on the influence of culture, politics and social positioning of science and technology on the image of scientists created by the media.

News Media Framing of Suicide Circumstances and Gender: Mixed Methods Analysis.

BACKGROUND: Suicide is a leading cause of death worldwide. Journalistic reporting guidelines were created to curb the impact of unsafe reporting; however, how suicide is framed in news reports may differ by important characteristics such as the circumstances and the decedent's gender. OBJECTIVE: This study aimed to examine the degree to which news media reports of suicides are framed using stigmatized or glorified language and differences in such framing by gender and circumstance of suicide. METHODS: We analyzed 200 news articles regarding suicides and applied the validated Stigma of Suicide Scale to identify stigmatized and glorified language. We assessed linguistic similarity with 2 widely used metrics, cosine similarity and mutual information scores, using a machine learning-based large language model. RESULTS: News reports of male suicides were framed more similarly to stigmatizing (P<.001) and glorifying (P=.005) language than reports of female suicides. Considering the circumstances of suicide, mutual information scores indicated that differences in the use of stigmatizing or glorifying language by gender were most pronounced for articles attributing legal (0.155), relationship (0.268), or mental health problems (0.251) as the cause. CONCLUSIONS: Linguistic differences, by gender, in stigmatizing or glorifying language when reporting suicide may exacerbate suicide disparities.

Sentiment analysis of U.S. News & World Report Best Children's Hospital urology rankings: A difference in positivity between the public and academic worlds.

INTRODUCTION: Initiated in 2009, the U.S. News & World Report (USNWR) pediatric urology rankings aim to guide patients and families towards high-quality urologic care. Despite this, the pediatric urology community remains divided, with significant debate over the rankings' accuracy, utility, and potential for misleading information. While some professionals argue for a collective opt-out from these rankings, citing these concerns, others highlight their positive impact on patient care, hospital benchmarking, and financial support. OBJECTIVE: Recognizing the lack of formal evaluation on how these rankings are viewed beyond the pediatric urology community, this research endeavors to fill the gap through sentiment analysis of public news articles and academic publications. STUDY DESIGN: We captured news articles from Google News and academic papers from Ovid Medline and Embase, focusing specifically on content related to the USNWR pediatric urology rankings from 2009 to 2023. Sentiment analysis was conducted using the Valence Aware Dictionary and Sentiment Reasoner (VADER) package on both news and academic texts, aiming to capture the overall sentiment through a compound score derived from the presence of sentiment-laden words. Sensitivity analysis was performed using TextBlob Pattern Analyzer tool. RESULTS: The analysis revealed a significant divergence in sentiment between news articles and academic literature. News articles exhibited a predominantly positive sentiment, with an average compound score of 0.681, suggesting a general approval or celebration of the rankings in the public sphere. Conversely, academic literature showed a more moderate sentiment, with an average score of 0.534, indicating a nuanced perspective that includes both positive views and critical reflections on the rankings. Sensitivity analysis confirmed this observation (Figure). DISCUSSION: This difference may reflect the distinct nature of news media and academic discourse. While news outlets may prioritize celebratory narratives that align with public interest and institutional pride, academic discussions tend to offer a balanced view that critically assesses both the merits and limitations of the rankings. This discrepancy underscores the complexity of interpreting and acting upon the rankings within the pediatric urology community. CONCLUSION: While the USNWR pediatric urology rankings are generally received positively by the public, as reflected in news media, the academic community presents a more reserved sentiment. These findings suggest the need for ongoing dialogue and research to understand the implications of these rankings fully. It also calls for a strategic approach to address the concerns and perceptions of healthcare professionals, aiming to leverage the rankings in a way that truly benefits patient care and informed decision-making.

Federated Learning in the Detection of Fake News Using Deep Learning as a Basic Method.

This article explores the possibilities for federated learning with a deep learning method as a basic approach to train detection models for fake news recognition. Federated learning is the key issue in this research because this kind of learning makes machine learning more secure by training models on decentralized data at decentralized places, for example, at different IoT edges. The data are not transformed between decentralized places, which means that personally identifiable data are not shared. This could increase the security of data from sensors in intelligent houses and medical devices or data from various resources in online spaces. Each station edge could train a model separately on data obtained from its sensors and on data extracted from different sources. Consequently, the models trained on local data on local clients are aggregated at the central ending point. We have designed three different architectures for deep learning as a basis for use within federated learning. The detection models were based on embeddings, CNNs (convolutional neural networks), and LSTM (long short-term memory). The best results were achieved using more LSTM layers (F1 = 0.92). On the other hand, all three architectures achieved similar results. We also analyzed results obtained using federated learning and without it. As a result of the analysis, it was found that the use of federated learning, in which data were decomposed and divided into smaller local datasets, does not significantly reduce the accuracy of the models.

Cancer misinformation on social media.

Social media is widely used globally by patients, families of patients, health professionals, scientists, and other stakeholders who seek and share information related to cancer. Despite many benefits of social media for cancer care and research, there is also a substantial risk of exposure to misinformation, or inaccurate information about cancer. Types of misinformation vary from inaccurate information about cancer risk factors or unproven treatment options to conspiracy theories and public relations articles or advertisements appearing as reliable medical content. Many characteristics of social media networks-such as their extensive use and the relative ease it allows to share information quickly-facilitate the spread of misinformation. Research shows that inaccurate and misleading health-related posts on social media often get more views and engagement (e.g., likes, shares) from users compared with accurate information. Exposure to misinformation can have downstream implications for health-related attitudes and behaviors. However, combatting misinformation is a complex process that requires engagement from media platforms, scientific and health experts, governmental organizations, and the general public. Cancer experts, for example, should actively combat misinformation in real time and should disseminate evidence-based content on social media. Health professionals should give information prescriptions to patients and families and support health literacy. Patients and families should vet the quality of cancer information before acting upon it (e.g., by using publicly available checklists) and seek recommended resources from health care providers and trusted organizations. Future multidisciplinary research is needed to identify optimal ways of building resilience and combating misinformation across social media.

Oral cancer diagnosis communication: Impact of an educational intervention using the SPIKES protocol.

OBJECTIVE: This study evaluated the influence of a single educational intervention on the perception and knowledge of strategies for communicating oral cancer diagnoses. METHODS: A educational intervention, 72 dentists and 41 dental undergraduates participated in the 'Maio Vermelho Project', a continuing education activity. Participants completed a 14-question online questionnaire concerning their experiences and perceptions of delivering difficult news. The educational intervention featured an interview illustrating the SPIKES protocol, broadcast on YouTube. RESULTS: Participants had a mean age of 40 years. A minority (21.2%) had encountered or experienced communicating an oral cancer diagnosis. Exposure to lectures on this topic during their education was uncommon (22.1%) but more prevalent among students. After the intervention, confidence in communicating a cancer diagnosis (29.2%) and addressing the patient's family (30.1%) in line with the SPIKES protocol increased. CONCLUSION: A training deficit persists in delivering cancer diagnoses, highlighting the need for educational interventions to empower students and professionals in this critical procedure. Integration of this topic into the dental undergraduate curriculum is imperative. CLINICAL RELEVANCE: Effectively communicating a cancer diagnosis poses challenges to healthcare professionals, impacting treatment outcomes. Implementing educational interventions ensures that professionals are well prepared to navigate this complex task, ultimately improving patient care.

A time-robust group recommender for featured comments on news platforms.

Introduction: Recently, content moderators on news platforms face the challenging task to select high-quality comments to feature on the webpage, a manual and time-consuming task exacerbated by platform growth. This paper introduces a group recommender system based on classifiers to aid moderators in this selection process. Methods: Utilizing data from a Dutch news platform, we demonstrate that integrating comment data with user history and contextual relevance yields high ranking scores. To evaluate our models, we created realistic evaluation scenarios based on unseen online discussions from both 2020 and 2023, replicating changing news cycles and platform growth. Results: We demonstrate that our best-performing models maintain their ranking performance even when article topics change, achieving an optimum mean NDCG@5 of 0.89. Discussion: The expert evaluation by platform-employed moderators underscores the subjectivity inherent in moderation practices, emphasizing the value of recommending comments over classification. Our research contributes to the advancement of (semi-)automated content moderation and the understanding of deliberation quality assessment in online discourse.

The kitchen assessment: an interactional analysis of assessment and feedback between an occupational therapist and a patient with aphasia post stroke.

PURPOSE: After stroke, patients undergo frequent multidisciplinary assessments. Little is known about patients' experiences of being assessed and the impact of assessment interactions and feedback for ongoing engagement in rehabilitation. This research aims to stimulate reflection on clinical interactions, even during routine clinical assessments, and the provision of assessment feedback. MATERIALS AND METHODS: This study involved a detailed analysis of an authentic kitchen assessment interaction between an occupational therapist and a patient with aphasia following stroke. It used a speech function analysis based on systemic functional linguistics resulting in both dynamic and synoptic data, and a consideration of interactive framing, to explore assessment explanation and feedback. RESULTS: The analysis revealed the clinician's interactive dominance in terms of number and type of moves, and misalignment of interactional framing at different points in the exchange. The session appeared to result in patient disengagement related both to the clinician's misjudged response to the patient's aphasia, and the context of assessment itself, characterised by reliance on question-and-answer exchanges, and a tendency to highlight deficit. CONCLUSIONS: Assessment sessions may be emotionally challenging for patients after stroke and feedback may be interpreted as bad news. Sensitive communication is required to support psychological wellbeing and engagement in rehabilitation.IMPLICATIONS FOR REHABILITATIONAfter stroke, patients are assessed by the multidisciplinary team to inform intervention and discharge planning.Little is known about the feedback patients receive or their views of this feedback, including when it is perceived as bad news.The presence of aphasia can complicate how assessments are conducted and how feedback is delivered and received.Greater awareness is needed of how feedback following assessment might impact patients' psychological wellbeing and engagement in rehabilitation.

Cognitive, affective, and behavioral engagement with science news predicted by the use of accessibility strategies in science-minded and general audiences.

Numerous studies have explored internal factors such as cultural values and acquired knowledge accounting for how people engage with science. However, it remains unclear how external factors embedded in science texts relate to audience engagement. A content analysis of 298 text-based popular science news articles and their following 5852 reader comments was conducted in two Israeli audiences, science-minded and general readers, to explore how the accessibility strategies embedded in these articles relate to cognitive, affective, and behavioral engagement. Findings indicated similar patterns of relationship between accessibility strategies and engagement expressions for both audiences; however, the relationships were more pronounced for general readers compared to science-minded readers. Using jargon and a narrative writing style increased the odds of positive emotions in reader comments, whereas addressing socio-scientific issues increased the odds of cognitive expressions. These results may contribute to a fuller understanding of ways to drive meaningful public engagement.

Covert marketing of quick-service restaurants via news media in Australia: A content analysis.

OBJECTIVE: To determine the extent and nature of news media coverage generated from press releases made by top-selling quick-service restaurants in Australia. METHODS: We conducted a content analysis of press releases made between July 2021 and June 2022 by the five largest quick-service restaurant brands in Australia by brand share, including coding their main subject. We then conducted a content analysis of news media coverage related to the press releases, including coding its slant towards the brand. RESULTS: Among 52 press releases, new food products (27% of press releases; all unhealthy foods) and corporate social responsibility activities (25%) were the most promoted subjects. For 62% of press releases, at least one news media item was identified. Among the 86 identified news media items, most related to press releases promoting new food products (45% of news media items) or corporate social responsibility activities (21%). News media items overwhelmingly had a slant favourable to the relevant brand (93%). CONCLUSIONS: Press releases by top-selling quick-service restaurant brands in Australia commonly generate news media coverage that promotes such brands and their predominantly unhealthy products. IMPLICATIONS FOR PUBLIC HEALTH: Policies restricting unhealthy food marketing should consider brand-generated news media coverage.

Influences on COVID-19 Vaccine Adherence among Pregnant Women: The Role of Internet Access and Pre-Vaccination Emotions.

INTRODUCTION: The onset of the COVID-19 pandemic brought about global uncertainties and fears, escalating the dissemination of fake news. This study aims to analyze the impact of fake news on COVID-19 vaccine adherence among pregnant women, providing crucial insights for effective communication strategies during the pandemic. METHODS: A cross-sectional, exploratory study was conducted with 113 pregnant women under care at a Women's Health Reference Center. Data analysis included relative frequency and odds ratio to assess the relationship between sociodemographic and behavioral variables regarding vaccination. RESULTS: In the behavioral context of vaccination, internet access shows a significant association with decision-making, influencing vaccine refusal due to online information. Nuances in the odds ratios results highlight the complexity of vaccine hesitancy, emphasizing the importance of information quality. Pre-vaccination sentiments include stress (87.61%), fear (50.44%), and anxiety (40.7%), indicating the need for sensitive communication strategies. DISCUSSION: Results revealed that pregnant women with higher education tend to adhere more to vaccination. Exposure to news about vaccine inefficacy had a subtle association with hesitancy, while finding secure sources was negatively associated with hesitancy. The behavioral complexity in the relationship between online information access and vaccination decision underscores the need for effective communication strategies. CONCLUSIONS: In the face of this challenging scenario, proactive strategies, such as developing specific campaigns for pregnant women, are essential. These should provide clear information, debunk myths, and address doubts. A user-centered approach, understanding their needs, is crucial. Furthermore, ensuring information quality and promoting secure sources are fundamental measures to strengthen trust in vaccination and enhance long-term public health.

Unveiling the power of unity: A novel examination of regional cooperation in mitigating air pollution.

Amidst escalating environmental concerns, regional cooperation has emerged as a potent strategy for environmental preservation. Yet, the potency of such cooperation in curbing air pollution remains largely unexplored and nebulous. Drawing upon a decade-long (2010-2019) new data from the dynamic Guangdong-Hong Kong-Macao Greater Bay Area (GBA), this study seeks to fill these knowledge gaps. Our findings underscore the transformative potential of regional cooperation in mitigating air pollution. By catalyzing technological advancements, fostering structural shifts in businesses, and reshaping land-use patterns, regional cooperation paves the way for a cleaner, healthier environment. A deeper dive into the heterogeneity reveals that "top to bottom" city agreements within regional cooperation frameworks significantly enhance air quality. While institutional and economic collaborations prove instrumental in reducing air pollution, social cooperation appears to have a lesser impact. Research findings indicate that the future will necessitate strengthening formal, institutionalized regional cooperation to address potential challenges posed by environmental pollution.

Associations between valenced news and affect in daily life: Experimental and ecological momentary assessment approaches.

In 203 (mean age = 38.04 years, SD=12.05) participants, we tested the association between valenced news and affect using a 14-day, smartphone-based ecological momentary assessment protocol consisting of two components: 1) a once-per-day experimental protocol in which participants were exposed to good news and bad news stories and 2) a four-times-per-day protocol capturing ecological fluctuations in news consumption. Across both protocols, we replicate findings that consumption of positively valenced news is associated with increased positive affect and decreased negative affect while consumption of negatively valenced news is associated with increased negative affect and decreased positive affect. By integrating the ecological momentary assessment data with network science methodologies, news selection and news effects were modeled simultaneously, uncovering selection processes whereby current positive affect, but not negative affect, predicted future valenced news consumption. Altogether, findings indicate that everyday news consumption influences positive and negative affect and may serve mood management functions for positive but not negative affect.

Social Media News Headlines and Their Influence on Well-Being: Emotional States, Emotion Regulation, and Resilience.

Today, many individuals read the daily news from social media platforms. Research has shown that news with negative valence might influence the well-being of individuals. Existing research that examined the impact of headlines on individuals' well-being has primarily focused on examining the positive or negative polarity of words used in the headlines. In the present study, we adopt a different approach and ask participants to categorize the headlines themselves based on the emotions they experienced while reading them and how their choice impacts their well-being. A total of 306 participants were presented with 40 headlines from main news sites that were considered popular based on the number of public reactions. Participants had to rate their emotional experience of the headlines following five emotional states (i.e., happiness, anger, sadness, fear, and interest). Emotion regulation strategies and resilience were also measured. In line with our hypotheses, we found that participants reported experiencing negative emotions more intensively while reading the headlines. Emotion regulation was not found to influence the emotional states of individuals, whereas resilience did. These findings highlight that individuals can experience heightened emotions without reading the entire news story. This effect was observed regardless of the headline's emotional valence (i.e., positive, negative, or neutral). Furthermore, our study highlights the critical role of interest as a factor in news consumption. Interest significantly affects individuals' engagement and reactions to headlines, regardless of valence. The findings underscore the complex interplay between headline content and reader engagement and stress the need for further research into how headlines are presented to protect individuals from potential emotional costs.

Understanding COVID-19 Impacts on the Health Workforce: AI-Assisted Open-Source Media Content Analysis.

BACKGROUND: To investigate the impacts of the COVID-19 pandemic on the health workforce, we aimed to develop a framework that synergizes natural language processing (NLP) techniques and human-generated analysis to reduce, organize, classify, and analyze a vast volume of publicly available news articles to complement scientific literature and support strategic policy dialogue, advocacy, and decision-making. OBJECTIVE: This study aimed to explore the possibility of systematically scanning intelligence from media that are usually not captured or best gathered through structured academic channels and inform on the impacts of the COVID-19 pandemic on the health workforce, contributing factors to the pervasiveness of the impacts, and policy responses, as depicted in publicly available news articles. Our focus was to investigate the impacts of the COVID-19 pandemic and, concurrently, assess the feasibility of gathering health workforce insights from open sources rapidly. METHODS: We conducted an NLP-assisted media content analysis of open-source news coverage on the COVID-19 pandemic published between January 2020 and June 2022. A data set of 3,299,158 English news articles on the COVID-19 pandemic was extracted from the World Health Organization Epidemic Intelligence through Open Sources (EIOS) system. The data preparation phase included developing rules-based classification, fine-tuning an NLP summarization model, and further data processing. Following relevancy evaluation, a deductive-inductive approach was used for the analysis of the summarizations. This included data extraction, inductive coding, and theme grouping. RESULTS: After processing and classifying the initial data set comprising 3,299,158 news articles and reports, a data set of 5131 articles with 3,007,693 words was devised. The NLP summarization model allowed for a reduction in the length of each article resulting in 496,209 words that facilitated agile analysis performed by humans. Media content analysis yielded results in 3 sections: areas of COVID-19 impacts and their pervasiveness, contributing factors to COVID-19-related impacts, and responses to the impacts. The results suggest that insufficient remuneration and compensation packages have been key disruptors for the health workforce during the COVID-19 pandemic, leading to industrial actions and mental health burdens. Shortages of personal protective equipment and occupational risks have increased infection and death risks, particularly at the pandemic's onset. Workload and staff shortages became a growing disruption as the pandemic progressed. CONCLUSIONS: This study demonstrates the capacity of artificial intelligence-assisted media content analysis applied to open-source news articles and reports concerning the health workforce. Adequate remuneration packages and personal protective equipment supplies should be prioritized as preventive measures to reduce the initial impact of future pandemics on the health workforce. Interventions aimed at lessening the emotional toll and workload need to be formulated as a part of reactive measures, enhancing the efficiency and maintainability of health delivery during a pandemic.

News media consumption and support for counter-terrorism measures: the role of hatred and fear.

Media are a key social agent shaping society's responses to measures implemented in the fight against terrorism. We argue that emotions elicited by media narratives on terrorist attacks are decisive to understand the link between the news media consumption and citizens' support for military intervention in the Middle East, as well as for security measures in the home country. In two studies conducted after the Brussels attacks (N = 250) and the Barcelona attacks (N = 633), we tested the explanatory role of emotions - specifically fear and hatred - in the association between media narratives and these two outcomes. The results of both studies show that hatred explained the positive relationship between news media consumption and support for military intervention, and to a lesser degree, agreement with security measures. In contrast, the positive relationship between news media consumption and agreement with security measures was explained by fear. This research underscores the need to consider how emotions are utilized in media discourse. We discuss practical implications of our findings for promoting ethical journalism.

ONS Past President Johnson's Legacy Leaves Impact on Global Cancer Community.

Oncology Nursing Society (ONS) Past President Judi L. Johnson, PhD, RN, FAAN, dedicated her career to guiding cancer education, patient- centered care, and oncology nursing excellence. On Saturday, April 20, 2024, Johnson pas.