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1.
Arzu Karakulak; Beyza Tepe; Radosveta Dimitrova; Mohamed Abdelrahman; Plamen Akaliyski; Rana Rana Alaseel; Yousuf Alkamali; Azzam Amin; Andrii Andres; John Aruta; Hrant Avanesyan; Norzihan Ayub; Maria Bacikova-Sleskova; Raushan Baikanova; Batoul Bakkar; Sunčica Bartoluci; David Benitez; Ivanna Bodnar; Aidos Bolatov; Judyta Borchet; Ksenija Bosnar; Yunier Broche-Pérez; Carmen Buzea; Rosalinda Cassibba; Bin-Bin Chen; Dương Công Doanh; Alejandra Domínguez-Espinosa; Nelli Ferenczi; Regina Fernández-Morales; Jorge Gaete; Yiqun Gan; Wassim Gharz Edine; Suely Giolo; Rubia Carla Giordani; Maria-Therese Friehs; Shahar Gindi; Biljana Gjoneska; Juan Godoy; Maria del Pilar Grazioso; Camellia Hancheva; Given Hapunda; Shogo Hihara; Mohd. Husain; Md. Islam; Anna Janovská; Nino Javakhishvili; Veljko Jovanović; Russell Kabir; Nor Ba’yah Abdul Kadir; Johannes Karl; Darko Katović; Zhumaly Kauyzbay; Tinka Kawashima; Maria Kazmierczak; Richa Khanna; Meetu Khosla; Martina Klicperová; Ana Kozina; Steven Krauss; Rodrigo Landabur; Katharina Lefringhausen; Aleksandra Lewandowska-Walter; Yun-Hsia Liang; Danny Lizarzaburu Aguinaga; Ana Makashvili; Sadia Malik; Marta de la C. Martín-Carbonell; Denisse Manrique-Millones; Stefanos Mastrotheodoros; Breeda McGrath; Enkeleint Mechili; Marinés Mejía; Samson Mhizha; Justyna Michalek-Kwiecien; Diana Miconi; Fatema Mohsen; Rodrigo Moreta-Herrera; Camila Muhl; Mriya Muradyan; Pasquale Musso; Andrej Naterer; Arash Nemat; Félix Neto; Joana Neto; Luz Alonso Palacio; Hassan Okati; Carlos Orellana; Ligia Orellana; Sushanta Mishra; Joonha Park; Iuliia Pavlova; Eddy Peralta; Petro Petrytsa; Saša Pišot; Franjo Prot; José Rasia; Gordana Ristevska-Dimitrovska; Rita Rivera; Benedicta Riyanti; Adil Samekin; Telman Seisembekov; Danielius Serapinas; Fabiola Silletti; Prerna Sharma; Shanu Shukla; Katarzyna Skrzypińska; Iva Poláčková Šolcová; Olga Solomontos-Kountouri; Adrian Stanciu; Delia Stefenel; Lorena Cecilia López Steinmetz; Maria Stoginani; Jaimee Stuart; Laura Sudarnoto; Kazumi Sugimura; Mst. Sultana; Angela Suryani; Ergyul Tair; Lucy Tavitian-Elmadjan; Luciana Thome; Fitim Uka; Rasa Pilkauskaitė Valickienė; Brett Walter; Guilherme Wendt; Pei-Jung Yang; Ebrar Yıldırım; Yue Yu; Maria Angela Yunes; Milene Zanoni da Silva.
researchsquare; 2022.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-2412449.v1

ABSTRACT

The current study investigated the motives that underlie support for COVID-19 preventive behaviorsin a large, cross-cultural sample of 12,758 individuals from 34 countries. We hypothesized that the associations of empathic prosocial concern and fear of disease, with support towards preventive COVID-19 behaviors would be moderated by the individual-level and country-level trust in the government. Results suggest that the association between fear of disease and support for COVID-19 preventive behaviors was strongest when trust in the government was weak (both at individual and country-level). Conversely, the association with empathic prosocial concern was strongest when trust was high, but this moderation was only found at individual-level scores of governmental trust. We discuss how both fear and empathy motivations to support preventive COVID-19 behaviors may be shaped by socio-cultural context, and outline how the present findings may contribute to a better understanding of collective action during global crises.


Subject(s)
COVID-19 , Cognition Disorders
2.
preprints.org; 2021.
Preprint in English | PREPRINT-PREPRINTS.ORG | ID: ppzbmed-10.20944.preprints202110.0435.v1

ABSTRACT

Hand hygiene is among the most important factors of infection control in healthcare settings. Healthcare workers are considered the primary source of hospital acquired infection. We assessed the current state of hand hygiene knowledge, perception and practice among the healthcare workers in Qassim, Saudi Arabia. In this cross-sectional study we used the hand hygiene knowledge and perception questionnaire developed by the World Health Organization. Knowledge and perceptions were classified into good (80 – 100%), moderate (60 – 79%) and poor (<60% score). Majority of the healthcare workers had moderate knowledge (57.8%) and perception (73.4%) of hand hygiene. Males were less likely to have moderate/good knowledge compared to females (OR: 0.52, p<.05). Private healthcare workers were less likely (OR: 0.33, p<0.01) to have moderate/good perception compared to the government healthcare workers. Healthcare workers who received training on hand hygiene were 3.2 times likely (p<.05) to have good/moderate perception and 3.8 times likely (p<0.05) to routinely use alcohol-based hand-rub than the ones without such training. Physicians were 4.9 times likely (p<0.05) to routinely use alcohol-based hand-rub than the technicians. Our research highlighted gaps on hand hygiene knowledge and perception and practice among healthcare workers in Qassim and importance of training in this regard.


Subject(s)
COVID-19
3.
researchsquare; 2021.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-266255.v1

ABSTRACT

Aim: This article reports the intent to receive a COVID-19 vaccine, its predictors and willingness to pay in Bangladesh. Subject and Methods: We did a cross-sectional survey of 697 adults in January 2021. A structured questionnaire was used to assess vaccination intent. Questionnaire included potential socio-demographic variables and health belief model constructs which may predict vaccination intent. Results: : Among the participants, 25.5% demonstrated a definite intent, 43% probable intent, 24% probable negative, and 7.5% a definite negative intention. Multivariable logistic regression analyses suggest association between definite intent and previous COVID-19 infection (OR: 2.86; 95% CI: 1.71 – 4.78), perceiving COVID-19 as serious (OR: 1.93; 1.04 – 3.59), the belief that vaccination would make them feel less worried about COVID-19 (OR: 4.42; 2.25 – 8.68), and concerns about vaccine affordability (OR: 1.51; 1.01 – 2.25). Individuals afraid of the side effects (OR: 0.34; 0.21 – 0.53) and would take the vaccine if the vaccine were taken by many in public (OR: 0.44; 0.29 – 0.67) are less likely to have a definite intent. A definite negative intent is associated with the concern that the vaccine may not be halal (OR: 2.03; 1.04 – 3.96). 68.4% are willing to pay for vaccine. The median amount they are willing to pay is $7.08. Conclusion: Adequate monitoring to stop the spreading of misinformation, and further research work to understand challenges in making a new vaccine acceptable by the population are needed.


Subject(s)
COVID-19
4.
researchsquare; 2020.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-60301.v2

ABSTRACT

Public health-related misinformation spread rapidly in online networks, particularly, in social media during any disease outbreak. Misinformation of coronavirus disease 2019 (COVID-19) drug protocol or presentation of its treatment from untrusted sources have shown dramatic consequences on public health. Authorities are utilizing several surveillance tools to detect, and slow down the rapid misinformation spread online, still millions of misinformation are found online. However, there is no currently available tool for receiving real-time misinformation notification during online health or COVID-19 related inquiries. Our proposed novel combinational approach, where we have integrated machine learning techniques with novel search engine misinformation notifier extension (SEMiNExt), helps to understand which news or information is from unreliable sources in real-time. The extension filters the search results and shows notification beforehand; it is a new and unexplored approach to prevent the spread of misinformation. To validate the user query, SEMiNExt transfers the data to a machine learning algorithm or classifier which predicts the authenticity of the search inquiry and sends a binary decision as either true or false. The results show that the supervised learning algorithm works best when 80% of the data set have been used for training purpose. Also, 10-fold cross-validation demonstrate a maximum accuracy and F1-score of 84.3% and 84.1% respectively for the Decision Tree classifier while the K-nearest-neighbor (KNN) algorithm shows the least performance. The SEMiNExt approach has introduced the possibility to improve online health communication system by showing misinformation notifications in real-time which enables safer web-based searching while inquiring on health-related issues.


Subject(s)
COVID-19 , Learning Disabilities
5.
ssrn; 2020.
Preprint in English | PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.3667950

ABSTRACT

Approximately a million Rohingya refugees from the Rakhine State, Myanmar is residing at refugee camps in Cox’s Bazar district of Bangladesh. Whereas maintaining the general health and hygiene of these refugees residing in the densely-crowded camps are highly challenging, maintaining their oral health is often neglected. Angiotensin-converting enzyme II (ACE-2) receptors play an essential role in spreading the COVID-19. Hence, it is present in the oral cavity, predominantly in the tongue, and oral mucosa may predispose to infection with 2019-nCoV. Here, we have highlighted the importance of regular monitoring and improving the oral health of the Rohingya refugees in Bangladesh and how it may contribute to preventive measures in spreading this highly contagious disease.


Subject(s)
COVID-19
6.
researchsquare; 2020.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-56753.v1

ABSTRACT

Aim: This study aims to assess the knowledge, awareness, and practices of registered dentists regarding COVID-19 epidemiology and transmission during the rapid outbreak of this highly contagious virus in Bangladesh. Subjects and Methods: A cross-sectional web-based survey was conducted among the dentists who were enrolled with their valid unique Bangladesh Medical and Dental Council (BMDC) registration number. A validated questionnaire was developed and distributed among the dentists by using different social media platforms. A total of 184 dentists participated in the survey between March and April 2020.   Both descriptive analysis logistic regression analysis was performed.Results: The mean age of the dentists is 31.75 years, with a standard deviation of 6.5 years. About 29.3% of dentists completed their postgraduate qualification, and 76% of them are engaged in private practice. The dentists who completed postgraduate education are three times more likely to know (OR=3.1, 95%CI 1.2-7.9) about COVID-19 compared to the dentists who completed an undergraduate degree. It is also observed that the dentists who are employed in private and independent settings are four times (OR=4, 95%CI 0.7-24) more likely to follow safe practice compared to the dentists who are engaged in the government hospitals or clinics.Conclusion: The dentists from Bangladesh have shown good knowledge, awareness, and practice regarding COVID-19. We recommend that the healthcare authorities, professional organizations, and hospitals coordinate, and conduct mandatory advanced infectious disease training for all the practicing dentists in the country.


Subject(s)
COVID-19 , Communicable Diseases
7.
arxiv; 2020.
Preprint in English | PREPRINT-ARXIV | ID: ppzbmed-2007.13633v1

ABSTRACT

Without proper medication and vaccination for the COVID-19, many governments are using automated digital healthcare surveillance system to prevent and control the spread. There is not enough literature explaining the concerns and privacy issues; hence, we have briefly explained the topics in this paper. We focused on digital healthcare surveillance system's privacy concerns and different segments. Further research studies should be conducted in different sectors. This paper provides an overview based on the published articles, which are not focusing on the privacy issues that much. Artificial intelligence and 5G networks combine the advanced digital healthcare surveillance system; whereas Bluetooth-based contact tracing systems have fewer privacy concerns. More studies are required to find the appropriate digital healthcare surveillance system, which would be ideal for monitoring, controlling, and predicting the COVID-19 trajectory.


Subject(s)
COVID-19
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