METHODS: We collected 3,489,367 tweets data from January 2020 to August 2021. We analyzed factual and fake news using the string comparison method. The difflib library was used to measure similarity. The user's engagement was analyzed by averaging the engagement metrics of tweets, retweets, favorites, replies, and posts shared with sentiments and opinions regarding COVID-19 and COVID-19 vaccination.
RESULT: Positive sentiments on COVID-19 and COVID-19 vaccination dominated, however, the negative sentiments increased during the beginning of the implementation of restrictions on community activities (PPKM). The tweets were dominated by the importance of health protocols (washing hands, keeping distance, and wearing masks). Several types of vaccines were on top of the word count in the vaccine subtopic. Acceptance of the vaccination increased during the studied period, and the fake news was overweighed by the facts. The tweets were dynamic and showed that the engaged topics were changed from the nature of COVID-19 to the vaccination and virus mutation which peaked in the early and middle terms of 2021. The public sentiment and engagement were shifted from hesitancy to anxiety towards the safety and effectiveness of the vaccines, whilst changed again into wariness on an uprising of the delta variant.
CONCLUSION: Understanding public sentiment and opinion can help policymakers to plan the best strategy to cope with the pandemic. Positive sentiments and fact-based opinions on COVID-19, and COVID-19 vaccination had been shown predominantly. However, sufficient health literacy levels could yet be predicted and sought for further study.
CONCLUSIONS: We have provided an overview of current evidence and expert-agreed recommendations for the definition, investigation, and management of OD. As for our original Position Paper, we hope that this updated document will encourage clinicians and researchers to adopt a common language, and in so doing, increase the methodological quality, consistency, and generalisability of work in this field.
OBJECTIVE: This scoping review aims to investigate the impact of artificial intelligence (AI)-based conversational agents (CAs)-including chatbots, voicebots, and anthropomorphic digital avatars-as human-like health caregivers in the remote management of NCDs as well as identify critical areas for future research and provide insights into how these technologies might be used effectively in health care to personalize NCD management strategies.
METHODS: A broad literature search was conducted in July 2023 in 6 electronic databases-Ovid MEDLINE, Embase, PsycINFO, PubMed, CINAHL, and Web of Science-using the search terms "conversational agents," "artificial intelligence," and "noncommunicable diseases," including their associated synonyms. We also manually searched gray literature using sources such as ProQuest Central, ResearchGate, ACM Digital Library, and Google Scholar. We included empirical studies published in English from January 2010 to July 2023 focusing solely on health care-oriented applications of CAs used for remote management of NCDs. The narrative synthesis approach was used to collate and summarize the relevant information extracted from the included studies.
RESULTS: The literature search yielded a total of 43 studies that matched the inclusion criteria. Our review unveiled four significant findings: (1) higher user acceptance and compliance with anthropomorphic and avatar-based CAs for remote care; (2) an existing gap in the development of personalized, empathetic, and contextually aware CAs for effective emotional and social interaction with users, along with limited consideration of ethical concerns such as data privacy and patient safety; (3) inadequate evidence of the efficacy of CAs in NCD self-management despite a moderate to high level of optimism among health care professionals regarding CAs' potential in remote health care; and (4) CAs primarily being used for supporting nonpharmacological interventions such as behavioral or lifestyle modifications and patient education for the self-management of NCDs.
CONCLUSIONS: This review makes a unique contribution to the field by not only providing a quantifiable impact analysis but also identifying the areas requiring imminent scholarly attention for the ethical, empathetic, and efficacious implementation of AI in NCD care. This serves as an academic cornerstone for future research in AI-assisted health care for NCD management.
TRIAL REGISTRATION: Open Science Framework; https://doi.org/10.17605/OSF.IO/GU5PX.
METHODS: A five-tiered workflow of data acquisition; processing; databasing, sharing, version control; visualisation; and monitoring was used. COVID-19 data were initially collated from press releases and then transitioned to official sources.
RESULTS: Key COVID-19 indicators were tabulated and visualised, deployed using open-source hosting in October 2022. The system demonstrated high performance, handling extensive data volumes, with a 92.5% user conversion rate, evidencing its value and adaptability.
CONCLUSION: This cost-effective, scalable solution aids health specialists and authorities in tracking disease burden, particularly in low-resource settings. Such innovations are critical in health crises like COVID-19 and adaptable to diverse health scenarios.
OBJECTIVE: The present study aims to determine the factors associated with malaria infection among forest rangers by systematically reviewing electronic articles from three databases (EBSCOhost, ScienceDirect, and ResearchGate).
METHODS: The current review was prepared based on the updated preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. First, three independent reviewers screened the titles and abstracts of the data collected. The information was then stored in Endnote20 based on the inclusion and exclusion criteria. The articles were critically appraised with the mixed methods appraisal tool (MMAT) to assess their quality.
RESULT: A total of 103, 31, and 51 articles from EBSCOhost, ScienceDirect, and ResearchGate, respectively, were selected, resulting in 185 unique hits. Nevertheless, only 63 full-text publications were assessed following a rigorous selection screening, from which only five were included in the final review. The studies revealed that several factors contribute to malaria infection among forest rangers. The parameters were classified into sociodemographic, individual, and living condition-related.
CONCLUSION: A better understanding of malaria progresses and identifying its potential risk factors is essential to impact worker well-being. The findings might be utilised to improve malaria infection prevention programme implementations, hence maximising their success. Pre-employment and regular health screenings could also aid in evaluating and identifying potential risks for malaria infection among forest rangers.
MATERIALS AND METHODS: Adjust to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020; this study met all the requirements and was up-todate. The search approach was online publications between 2013 and 2023 in Pubmed and SagePub. It was decided not to consider review pieces that had already been published and half done. The STATA 18th version was used for metaanalysis.
RESULTS: Our search results included 370 PubMed and 149 SagePub articles. Since 2013, 134 PubMed and nine SagePub articles have been obtained, and seven studies have met the criteria.
CONCLUSION: Disorders of intestinal motility in the aganglionic segment and accumulation of faeces disrupt the balanced microbiota population, which are factors of preoperative HAEC. Major congenital anomalies and low birth weight worsen pre-operative HAEC. Pre-operative HAEC can continue and affect the post-operative. Constipation and fecal incontinence are still the main challenges after HSCR surgery.