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19,079 Research products, page 1 of 1,908

  • COVID-19
  • Publications
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  • 2013-2022
  • ZENODO

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  • Open Access
    Authors: 
    Caasi, Nelda B.; Pentang, Jupeth T.;
    Publisher: Zenodo

    {"references": ["Arcebuche, J. M. (2022). STUDENTS' AWARENESS AND USAGE OF OPEN EDUCATIONAL RESOURCES (OER) AS LEARNING TOOL IN THEIR COURSE STUDIES AT THE UNIVERSITY OF THE PHILIPPINES OPEN UNIVERSITY (UPOU). Universal Journal of Educational Research, 1(3). Retrieved from http://ejournals.ph/form/cite.php?id=18200", "Agayon, A., Agayon, A. K., & Pentang, J. (2022). Teachers in the new normal: Challenges and coping mechanisms in secondary schools. International Journal of Humanities and Education Development, 4(1), 67-75. https://doi.org/10.22161/jhed.4.1.8", "Bacomo, A., Daculap, L. P., Ocampo, M., Paguia, C., Pentang, J., Bautista, R. M. (2022). Modular learning efficiency: Learner's attitude and performance towards self-learning modules. IOER International Multidisciplinary Research Journal, 4(2), 60-72. https://doi.org/10.54476/s149512", "Bonilla, M., Camo, J., Lanzaderas, R. A., Lanzaderas, R., & Bonilla, A. (2022). Parental involvement on child's education at home during COVID-19 pandemic. International Journal of Humanities and Education Development, 4(3), 6-13. https://doi.org/10.22161/jhed.4.3.2", "Buar, C. L. (2022). A Phenomenological Study on the Lived Experiences of Physics Students in Laboratory Classes. Universal Journal of Educational Research, 1(2), 10-18. DOI: https://doi.org/10.5281/zenodo.6939564", "Carbonilla, M., Kadusale, G. B., Lucero, R., & Pungyan, M. (2022). Parents' coping mechanism in conquering challenges towards distribution and retrieval of modules. International Journal of Multidisciplinary: Applied Business and Education Research, 3(7), 1249-1256. https://doi.org/10.11594/ijmaber.03.07.04", "Chohan, B. I., & Khan, R. M. (2010). Impact of parental support on the academic performance and self concept of the student. Journal of Research and reflections in Education, 4(1), 14-26. https://ue.edu.pk/jrre/articles/41002.pdf", "De Apodaca, F. R., Gentling, D. G., Steinhaus, J. K., & Rosenberg, E. A. (2015). Parental involvement as a mediator of academic performance among special education middle school students. School Community Journal, 25(2), 35-54. http://www.adi.org/journal/2015fw/ApodacaEtAlFall2015.pdf", "Ghazvini, S. (2011). Relationships between academic self-concept and academic performance in high school students. Procedia-Social and Behavioral Sciences, 15, 1034-1039. https://doi.org/10.1016/j.sbspro.2011.03.235", "Gonzalez-Pienda, J., Nunez, J., Gonzalez-Pumariega, S., Alvarez, L., Roces, C., & Garcia, M. (2002). A structural equation model of parental involvement, motivational and aptitudinal characteristics, and academic achievement. The Journal of Experimental Education, 70(3), 257-287. https://www.tandfonline.com/doi/abs/10.1080/00220970209599509", "Guinto, V. M. R. (2022). The Emotional Response of Filipino Teachers-in-Training to Memes. Universal Journal of Educational Research, 1(2), 19-25. https://doi.org/10.5281/zenodo.6934683", "Hamora, L., Rabaya, M., Pentang, J., Piza\u00f1a, A., & Gamozo, M. (2022). Students' evaluation of faculty-prepared instructional modules: Inferences for instructional materials review and revision. Journal of Education, Management and Development Studies, 2(2), 20-29. https://doi.org/10.52631/jemds.v2i2.109", "Kang, X., & Wu, Y. (2022). Academic enjoyment, behavioral engagement, self-concept, organizational strategy and achievement in EFL setting: A multiple mediation analysis. PLoS ONE 17(4), e0267405. https://doi.org/10.1371/journal.pone.0267405", "Laryea, J. E., Saani, A. J., & Dawson-Brew, E. (2014). Influence of students self-concept on their academic performance in the Elmina township. European Journal of Research and Reflection in Educational Sciences, 2(4), 1-10. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.1079.8872&rep=rep1&type=pdf", "Magulod, G. C., Jr., Capulso, L., Delos Reyes, R. J., Luna, A. R., Orte, C. J., Maglente, S., Pentang, J. T., Olitres, B. J., Vidal, C., & Samosa, R. (2021). How to write and publish your thesis. Beyond Books Publication. https://philpapers.org/rec/MAGHTW", "Martinez, A. (2015). Parent involvement and its affects on student academic achievement [Master's thesis, California State University]. https://scholarworks.calstate.edu/downloads/3f4626170", "Neuenschwander, M., Vida, M., Garrett, J., & Eccles, J. (2007). Parents' expectations and students' achievement in two western nations. International Journal of Behavioral Development, 31(6), 594-602. https://doi.org/10.1177%2F0165025407080589", "Pentang, J. (2021). Quantitative data analysis. Holy Angel University Graduate School of Education: Research and Academic Writing. http://dx.doi.org/10.13140/RG.2.2.23906.45764/1", "Sanchez, F. J. P., & Roda, M. D. S. (2003). Relationships between self-concept and academic achievement in primary students. Electronic Journal of Research in Educational Psychology, 1(1), 95-120. https://www.redalyc.org/pdf/2931/293152876003_2.pdf", "Sumayang, K. R., Celendron, K., Declaro, N. P., & Flandez, D. L. (2022). Mainstreaming Learners with Special Needs in a Regular Classroom: A Scoping Review. Universal Journal of Educational Research, 1(3), 106-114. https://www.ujer.org/vol1no3/article132", "Valoroso, M. B., Idulog, M. V. A., & Baslan, C. J. N. (2022). Pandemic era: The role of parents at home in the occurrence of modular distance learning. International Journal of Arts, Sciences and Education, 3(July Special Issue), 99-115. https://ijase.org/index.php/ijase/article/view/167", "Zakaria, W., Turmudi, T., & Pentang, J. (2022). Information and communication technology in elementary schools: A comparison between hybrid and face-to-face learning systems. Profesi Pendidikan Dasar, 9(1), 46-54. http://dx.doi.org/10.23917/ppd.v9i1.17534", "Zhan, Z., & Mei, H. (2013). Academic self-concept and social presence in face-to-face and online learning: Perceptions and effects on students' learning achievement and satisfaction across environments. Computers & Education, 69, 131-138. https://doi.org/10.1016/j.compedu.2013.07.002"]} Parental factors impact students’ self-concept and academic performance during the pandemic. Thus, this study determined the students’ self-concept and academic performance and the parental factors related to it. The research design was descriptive-correlational, and 500 nonrandom college students in West Philippines participated in the study. Researcher-made instruments were used, which were subjected to reliability and validity evaluation. Data were collected online from June 2021 to July 2022 and were analyzed using descriptive (frequency counts and percentage) and inferential statistics (Spearman correlation). Results revealed a positive self-concept and satisfactory academic performance among the students. Besides, parental factors such as educational attainment and school/classroom involvement are significantly related to self-concept and academic performance. Further, self-concept is significantly associated with academic performance. This shows that some parental factors are vital in developing the student’s self-beliefs and supporting their studies and academic endeavors amid the COVID-19 pandemic. Future studies may consider more factors related to academic achievement and self-concept. Other researchers may find the mediation or moderation effect of self-concept between parental factors and students’ scholastic achievement.

  • Open Access English
    Authors: 
    Radke, Josefine; Meinhardt, Jenny; Aschman, Tom; Chua, Robert Lorenz; Farztdinov, Vadim; Lukkassen, Sören; Ten, Foo Wei; Friebel, Ekaterina; Ishaque, Naveed; Franz, Jonas; +34 more
    Publisher: Zenodo

    Data set including image files of histological stainings, immunohistochemistry, MELC, and spatial transcriptomics associated with the study mentioned above.

  • Open Access
    Authors: 
    Patricia Wonch HIll; Judy Diamond; Amy N. Speigel; Elizabeth VanWormer; Meghan Leadabrand; Julia McQuillan;
    Publisher: Zenodo

    Dataset for manuscript: Accuracy of COVID-19 relevant knowledge among youth: Number of information sources matters

  • Open Access English
    Authors: 
    Chacón-Lozsán, Francisco; Tamasi, Peter;
    Publisher: Zenodo

    Abstract Background Most patients admitted to the intensive care unit with coronavirus disease (COVID-19) develop severe respiratory failure. Understanding lung mechanics helps to guide protective mechanical ventilation, improve oxygenation, and reduce the ventilator induce lung injury. This study aims to describe lung mechanics characteristics of patients with COVID -19 related acute respiratory distress syndrome (CARDS) and to compare them with non-COVID-19 associated ARDS. Methods We performed a retrospective observational study of lung mechanics: plateau pressure (Pplat), Driving pressure (DP), Mechanical power (MPw), Elastic (dynamic) power (EdPw), Total ventilatory power (TPw), and oxygenation parameters (ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2), the ratio of arterial oxygen partial pressure to fractional inspired oxygen multiplied by PEEP [PaO2/(FiO2 x PEEP)], arterial and venous carbon dioxide partial pressure (PaCO2, PvCO2), and Ventilation dead space (VD) were measured and compared between the two groups after initiation of mechanical ventilation. Results 30 CARDS and 10 ARDS patients fulfilled the study requirements. We observed a significant higher MPw in the CARDS group (29.17 ± 8.29 J/min vs 15.78 ± 4.45 J/min, P 0.007), similarly observed with EdPw (256.7 ± 84.06 mJ/min vs 138.1 ± 39.15 mJ/min, P 0.01) and TPw (289.1 ± 84.51 mJ/min vs 161.5 ± 45.51, P 0.007). Inside the CARDS group, we found 2 subgroups, a low shunt subgroup and a higher shunt (Qs/Qt (%): 6.61 ± 2.46 for vs 40.3 ± 20.6, P 0.0009), however, between these two subgroups we didn’t find statistical differences on lung mechanic parameters but only in oxygenation parameters (PaO2/FiO2 and PaO2/FiO2*PEEP). When comparing these two subgroups with ARDS patients, we found more similarity between the low shunt CARDS and the ARDS patients on MP (R2 0.99, P 0.001), EdPw (R2 0.89, P 0.05) and TPw (R2 0.99, P 0.0009). Conclusions: Our study suggests important differences between CARDS and ARDS regarding mechanical parameters that could lead to more complicated management of CARDS patients and a higher prevalence of VILI. However due to the study limitations, a bigger study is necessary to corroborate our findings.

  • Open Access German
    Authors: 
    Becker, Karsten; Brändle, Tobias;
    Publisher: Zenodo

    Online-Anhang

  • Open Access English
    Authors: 
    Franck, Claudio; Franck, Gustavo; Daoud, Ehab;
    Publisher: Zenodo

    Abstract Introduction SARS-CoV-2 may be associated with ARDS and the VILI. However, there are still doubts about the correlations and the interference of tidal energy in the outcomes. The objective of this study was to verify the correlations and interference of mechanical power and its components with age in the outcome in SARS-CoV-2 of subjects undergoing pressure-controlled ventilation (PCV). Method Longitudinal, prospective, observational, analytical, and quantitative study of the information collected on two parameters of the mechanical ventilator, to calculate the mechanical power by Becher formula in 163 subjects with SARS-CoV-2 and moderate ARDS between May 2021 to September 2021. Results Correlations were found between mechanical power and its components, except for compliance (P 0.234), elastance (P 0.515), resistance (P 0.570) and age (P 0.180). There was a significant impact on the outcome in the univariate analysis of age, as well as of mechanical power and its components, except for positive end expiratory pressure (PEEP) (P 0.874), minute ventilation (Ve) (P 0.437), resistive pressure (PResist) (P 0.410) and resistance (P 0.071). The multivariate analysis of mechanical power, plateau pressure (PPlateau), tidal volume (VT), driving pressure (ΔP) and elastance, showed that only mechanical power correlated to death (P 0.04) and for each additional unit in J/minute there is a 6.2% increase in the odds of death (95% IC 0.3%; 12.4%). Conclusion There are correlations between mechanical power and its components, except for compliance, elastance, resistance, and age. There is interference in the outcome in the univariate analysis of age, as well as of mechanical power and its components, except PEEP, Ve, PResist and resistance, but the multivariate analysis showed that only mechanical power correlates with the outcome in SARS-CoV-2 undergoing PCV.

  • Open Access German
    Authors: 
    Robert Koch-Institut;
    Publisher: Zenodo

    Für die Planung von Maßnahmen zur Eindämmung von COVID-19 kommt der genauen Kenntnis der Eigenschaften von SARS-CoV-2 eine zentrale Bedeutung zu. Eine besondere Rolle spielen in diesem Zusammenhang Mutationen des Virus. Für eine erfolgreiche Eindämmung der Pandemie ist es daher entscheidend, einen detaillierten Überblick über die Ausbreitungsmuster spezifischer SARS-CoV-2-Mutationen zu erhalten und auch neue Mutation frühzeitig zu entdecken.Hierfür stellt das Robert Koch-Institut die Systeme zur bundesweiten molekularen Surveillance bereit. Jedes Labor in Deutschland, das SARS-CoV-2 sequenziert, ist laut der Verordnung zur molekulargenetischen Surveillance des Coronavirus SARS-CoV-2 verpflichtet, dem Robert Koch-Institut die Sequenz- und zugehörige Metadaten zu übermitteln. Technisch erfolgt diese Übermittlung über den Deutschen Elektronischen Sequenzdaten-Hub (DESH).Im Projekt "OSEDA - Offene Sequenzdaten" verpflichtet sich das RKI, die aufgearbeiteten und qualitätskontrollierten Sequenzdaten zusammen mit einer Auswahl von klinisch-epidemiologischen Daten über die öffentlich zugängliche Repositorien des European Nucleotide Archive) und GISAID für weitere Forschungsvorhaben bereitzustellen.

  • Open Access German
    Authors: 
    Robert Koch-Institut, Fachgebiet 33;
    Publisher: Zenodo

    Die COVID-19-Impfung kann einen Wendepunkt in der Kontrolle der COVID-19-Pandemie darstellen und erfährt daher hohes Maß an öffentlicher Aufmerksamkeit. Einführung und Umsetzung der COVID-19-Impfung gehen mit besonderen Herausforderungen einher, die bei der Impfdatenerfassung zu berücksichtigen sind. In diesem Kontext ist es Ziel des Projekts 'Digitales Impfquoten-Monitoring' (DIM), tagesaktuell, bundesweit die Impfquote zu erfassen und folgend aufbereitet darzustellen, um zeitnah den Verlauf der COVID-19-Impfkampanne zu analysieren, bei Bedarf nach zusteuern, und logistisch bzw. organisatorische Konsequenzen zu ziehen.Der durch das DIM-Projekt bereitgestellte Datensatz enthält Daten über den Verlauf der COVID-19 Impfungen in Deutschland. Die hier veröffentlichten Impfdaten aggregieren Daten aus drei Datenquellen:Die DIM-Daten enthalten Angaben der Impfzentren, mobilen Impfteams, Krankenhäuser und der Betriebsärzte_innen, die über die DIM-Webanwendung übermittelt werdenDer täglich aggregierte Kerndatensatz der impfenden Ärzt_innen über die Kassenärztliche Bundesvereinigung (KBV)Der täglich aggregierte Kerndatensatz der impfenden Ärzt_innen über die Privatärztliche Bundesvereinigung (PBV)

  • Open Access German
    Authors: 
    Robert Koch-Institut;

    doi: 10.5281/zenodo.7359335 , 10.5281/zenodo.7384743 , 10.5281/zenodo.7145927 , 10.5281/zenodo.7426097 , 10.5281/zenodo.7170322 , 10.5281/zenodo.7161090 , 10.5281/zenodo.7317583 , 10.5281/zenodo.7131572 , 10.5281/zenodo.7423710 , 10.5281/zenodo.7269399 , 10.5281/zenodo.7259968 , 10.5281/zenodo.7379552 , 10.5281/zenodo.7309329 , 10.5281/zenodo.7218875 , 10.5281/zenodo.7367578 , 10.5281/zenodo.7266070 , 10.5281/zenodo.7294025 , 10.5281/zenodo.7202577 , 10.5281/zenodo.7412676 , 10.5281/zenodo.7223260 , 10.5281/zenodo.7237899 , 10.5281/zenodo.7251145 , 10.5281/zenodo.7213985 , 10.5281/zenodo.7134068 , 10.5281/zenodo.7256017 , 10.5281/zenodo.7325559 , 10.5281/zenodo.7349603 , 10.5281/zenodo.7240739 , 10.5281/zenodo.7407716 , 10.5281/zenodo.7430860 , 10.5281/zenodo.7338775 , 10.5281/zenodo.7420835 , 10.5281/zenodo.7314850 , 10.5281/zenodo.7227153 , 10.5281/zenodo.7196790 , 10.5281/zenodo.7179503 , 10.5281/zenodo.7298404 , 10.5281/zenodo.7272795 , 10.5281/zenodo.7243243 , 10.5281/zenodo.7388648 , 10.5281/zenodo.7312517 , 10.5281/zenodo.7321689 , 10.5281/zenodo.7183919 , 10.5281/zenodo.7316119 , 10.5281/zenodo.7129007 , 10.5281/zenodo.7155333 , 10.5281/zenodo.7306434 , 10.5281/zenodo.7344709 , 10.5281/zenodo.7129008 , 10.5281/zenodo.7329168 , 10.5281/zenodo.7152320 , 10.5281/zenodo.7275479 , 10.5281/zenodo.7246695 , 10.5281/zenodo.7370342 , 10.5281/zenodo.7233018 , 10.5281/zenodo.7392666 , 10.5281/zenodo.7187553 , 10.5281/zenodo.7397219 , 10.5281/zenodo.7262593 , 10.5281/zenodo.7375101 , 10.5281/zenodo.7417007 , 10.5281/zenodo.7279254 , 10.5281/zenodo.7363973 , 10.5281/zenodo.7340306 , 10.5281/zenodo.7353332 , 10.5281/zenodo.7141504 , 10.5281/zenodo.7402844 , 10.5281/zenodo.7264399 , 10.5281/zenodo.7435482 , 10.5281/zenodo.7332830 , 10.5281/zenodo.7136611 , 10.5281/zenodo.7192410 , 10.5281/zenodo.7395363 , 10.5281/zenodo.7212699 , 10.5281/zenodo.7336635 , 10.5281/zenodo.7302468

    Publisher: Zenodo

    Im Datensatz '7-Tage-Inzidenz von COVID-19 in Deutschland' werden die aktuellen 7-Tage-Inzidenzen der nach den Vorgaben des Infektionsschutzgesetzes - IfSG - an das RKI übermittelten COVID-19-Fälle veröffentlicht. Datengrundlage zur Berechnung der 7-Tage-Inzidenzen sind die an das RKI übermittelten COVID-19-Fälle. Eine detaillierte Dokumentation zur Erhebung der Daten zum Infektionsgeschehen ist im Datensatz 'SARS-CoV-2-Infektionen in Deutschland' enthalten. Die für die Berechnung der 7-Tage-Inzidenz notwendigen Bevölkerungsdaten bezieht das RKI durch das Statistisches Bundesamt (Destatis), Referat F24 | Bevölkerungsfortschreibung, Ausländer- und Integrationsstatistiken.

  • Open Access German
    Authors: 
    Robert Koch-Institut;
    Publisher: Zenodo

    Im Datensatz 'COVID-19-Hospitalisierungen' werden die aktuellen Zahlen der nach den Vorgaben des Infektionsschutzgesetzes - IfSG - erfassten hospitalisierten COVID-19-Fälle bereitgestellt. Um den Trend der Anzahl von Hospitalisierungen und der 7-Tage-Hospitalisierungsinzidenz besser bewerten zu können, wird die berichtete Hospitalisierungsinzidenz um eine Schätzung der zu erwartenden Anzahl an verzögert berichteten Hospitalisierungen ergänzt. Neben den Daten der gemeldeten COVID-19-Hospitalisierungen auf Bundes- und Länderebene wird daher ein Nowcasting der Anzahl hospitalisierter Fälle und der 7-Tage-Hospitalisierungsinzidenz auf Bundesebene durchgeführt. Ziel ist die Schätzung der Anzahl von hospitalisierten COVID-19-Fällen mit Meldedatum innerhalb der sieben vorhergehenden Tage - inklusive der noch nicht an das RKI berichteten Hospitalisierungen. Aufbauend auf dem Nowcasting wird eine Schätzung der adjustierten 7-Tage-Hospitalisierungsinzidenz durchgeführt.

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The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
19,079 Research products, page 1 of 1,908
  • Open Access
    Authors: 
    Caasi, Nelda B.; Pentang, Jupeth T.;
    Publisher: Zenodo

    {"references": ["Arcebuche, J. M. (2022). STUDENTS' AWARENESS AND USAGE OF OPEN EDUCATIONAL RESOURCES (OER) AS LEARNING TOOL IN THEIR COURSE STUDIES AT THE UNIVERSITY OF THE PHILIPPINES OPEN UNIVERSITY (UPOU). Universal Journal of Educational Research, 1(3). Retrieved from http://ejournals.ph/form/cite.php?id=18200", "Agayon, A., Agayon, A. K., & Pentang, J. (2022). Teachers in the new normal: Challenges and coping mechanisms in secondary schools. International Journal of Humanities and Education Development, 4(1), 67-75. https://doi.org/10.22161/jhed.4.1.8", "Bacomo, A., Daculap, L. P., Ocampo, M., Paguia, C., Pentang, J., Bautista, R. M. (2022). Modular learning efficiency: Learner's attitude and performance towards self-learning modules. IOER International Multidisciplinary Research Journal, 4(2), 60-72. https://doi.org/10.54476/s149512", "Bonilla, M., Camo, J., Lanzaderas, R. A., Lanzaderas, R., & Bonilla, A. (2022). Parental involvement on child's education at home during COVID-19 pandemic. International Journal of Humanities and Education Development, 4(3), 6-13. https://doi.org/10.22161/jhed.4.3.2", "Buar, C. L. (2022). A Phenomenological Study on the Lived Experiences of Physics Students in Laboratory Classes. Universal Journal of Educational Research, 1(2), 10-18. DOI: https://doi.org/10.5281/zenodo.6939564", "Carbonilla, M., Kadusale, G. B., Lucero, R., & Pungyan, M. (2022). Parents' coping mechanism in conquering challenges towards distribution and retrieval of modules. International Journal of Multidisciplinary: Applied Business and Education Research, 3(7), 1249-1256. https://doi.org/10.11594/ijmaber.03.07.04", "Chohan, B. I., & Khan, R. M. (2010). Impact of parental support on the academic performance and self concept of the student. Journal of Research and reflections in Education, 4(1), 14-26. https://ue.edu.pk/jrre/articles/41002.pdf", "De Apodaca, F. R., Gentling, D. G., Steinhaus, J. K., & Rosenberg, E. A. (2015). Parental involvement as a mediator of academic performance among special education middle school students. School Community Journal, 25(2), 35-54. http://www.adi.org/journal/2015fw/ApodacaEtAlFall2015.pdf", "Ghazvini, S. (2011). Relationships between academic self-concept and academic performance in high school students. Procedia-Social and Behavioral Sciences, 15, 1034-1039. https://doi.org/10.1016/j.sbspro.2011.03.235", "Gonzalez-Pienda, J., Nunez, J., Gonzalez-Pumariega, S., Alvarez, L., Roces, C., & Garcia, M. (2002). A structural equation model of parental involvement, motivational and aptitudinal characteristics, and academic achievement. The Journal of Experimental Education, 70(3), 257-287. https://www.tandfonline.com/doi/abs/10.1080/00220970209599509", "Guinto, V. M. R. (2022). The Emotional Response of Filipino Teachers-in-Training to Memes. Universal Journal of Educational Research, 1(2), 19-25. https://doi.org/10.5281/zenodo.6934683", "Hamora, L., Rabaya, M., Pentang, J., Piza\u00f1a, A., & Gamozo, M. (2022). Students' evaluation of faculty-prepared instructional modules: Inferences for instructional materials review and revision. Journal of Education, Management and Development Studies, 2(2), 20-29. https://doi.org/10.52631/jemds.v2i2.109", "Kang, X., & Wu, Y. (2022). Academic enjoyment, behavioral engagement, self-concept, organizational strategy and achievement in EFL setting: A multiple mediation analysis. PLoS ONE 17(4), e0267405. https://doi.org/10.1371/journal.pone.0267405", "Laryea, J. E., Saani, A. J., & Dawson-Brew, E. (2014). Influence of students self-concept on their academic performance in the Elmina township. European Journal of Research and Reflection in Educational Sciences, 2(4), 1-10. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.1079.8872&rep=rep1&type=pdf", "Magulod, G. C., Jr., Capulso, L., Delos Reyes, R. J., Luna, A. R., Orte, C. J., Maglente, S., Pentang, J. T., Olitres, B. J., Vidal, C., & Samosa, R. (2021). How to write and publish your thesis. Beyond Books Publication. https://philpapers.org/rec/MAGHTW", "Martinez, A. (2015). Parent involvement and its affects on student academic achievement [Master's thesis, California State University]. https://scholarworks.calstate.edu/downloads/3f4626170", "Neuenschwander, M., Vida, M., Garrett, J., & Eccles, J. (2007). Parents' expectations and students' achievement in two western nations. International Journal of Behavioral Development, 31(6), 594-602. https://doi.org/10.1177%2F0165025407080589", "Pentang, J. (2021). Quantitative data analysis. Holy Angel University Graduate School of Education: Research and Academic Writing. http://dx.doi.org/10.13140/RG.2.2.23906.45764/1", "Sanchez, F. J. P., & Roda, M. D. S. (2003). Relationships between self-concept and academic achievement in primary students. Electronic Journal of Research in Educational Psychology, 1(1), 95-120. https://www.redalyc.org/pdf/2931/293152876003_2.pdf", "Sumayang, K. R., Celendron, K., Declaro, N. P., & Flandez, D. L. (2022). Mainstreaming Learners with Special Needs in a Regular Classroom: A Scoping Review. Universal Journal of Educational Research, 1(3), 106-114. https://www.ujer.org/vol1no3/article132", "Valoroso, M. B., Idulog, M. V. A., & Baslan, C. J. N. (2022). Pandemic era: The role of parents at home in the occurrence of modular distance learning. International Journal of Arts, Sciences and Education, 3(July Special Issue), 99-115. https://ijase.org/index.php/ijase/article/view/167", "Zakaria, W., Turmudi, T., & Pentang, J. (2022). Information and communication technology in elementary schools: A comparison between hybrid and face-to-face learning systems. Profesi Pendidikan Dasar, 9(1), 46-54. http://dx.doi.org/10.23917/ppd.v9i1.17534", "Zhan, Z., & Mei, H. (2013). Academic self-concept and social presence in face-to-face and online learning: Perceptions and effects on students' learning achievement and satisfaction across environments. Computers & Education, 69, 131-138. https://doi.org/10.1016/j.compedu.2013.07.002"]} Parental factors impact students’ self-concept and academic performance during the pandemic. Thus, this study determined the students’ self-concept and academic performance and the parental factors related to it. The research design was descriptive-correlational, and 500 nonrandom college students in West Philippines participated in the study. Researcher-made instruments were used, which were subjected to reliability and validity evaluation. Data were collected online from June 2021 to July 2022 and were analyzed using descriptive (frequency counts and percentage) and inferential statistics (Spearman correlation). Results revealed a positive self-concept and satisfactory academic performance among the students. Besides, parental factors such as educational attainment and school/classroom involvement are significantly related to self-concept and academic performance. Further, self-concept is significantly associated with academic performance. This shows that some parental factors are vital in developing the student’s self-beliefs and supporting their studies and academic endeavors amid the COVID-19 pandemic. Future studies may consider more factors related to academic achievement and self-concept. Other researchers may find the mediation or moderation effect of self-concept between parental factors and students’ scholastic achievement.

  • Open Access English
    Authors: 
    Radke, Josefine; Meinhardt, Jenny; Aschman, Tom; Chua, Robert Lorenz; Farztdinov, Vadim; Lukkassen, Sören; Ten, Foo Wei; Friebel, Ekaterina; Ishaque, Naveed; Franz, Jonas; +34 more
    Publisher: Zenodo

    Data set including image files of histological stainings, immunohistochemistry, MELC, and spatial transcriptomics associated with the study mentioned above.

  • Open Access
    Authors: 
    Patricia Wonch HIll; Judy Diamond; Amy N. Speigel; Elizabeth VanWormer; Meghan Leadabrand; Julia McQuillan;
    Publisher: Zenodo

    Dataset for manuscript: Accuracy of COVID-19 relevant knowledge among youth: Number of information sources matters

  • Open Access English
    Authors: 
    Chacón-Lozsán, Francisco; Tamasi, Peter;
    Publisher: Zenodo

    Abstract Background Most patients admitted to the intensive care unit with coronavirus disease (COVID-19) develop severe respiratory failure. Understanding lung mechanics helps to guide protective mechanical ventilation, improve oxygenation, and reduce the ventilator induce lung injury. This study aims to describe lung mechanics characteristics of patients with COVID -19 related acute respiratory distress syndrome (CARDS) and to compare them with non-COVID-19 associated ARDS. Methods We performed a retrospective observational study of lung mechanics: plateau pressure (Pplat), Driving pressure (DP), Mechanical power (MPw), Elastic (dynamic) power (EdPw), Total ventilatory power (TPw), and oxygenation parameters (ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2), the ratio of arterial oxygen partial pressure to fractional inspired oxygen multiplied by PEEP [PaO2/(FiO2 x PEEP)], arterial and venous carbon dioxide partial pressure (PaCO2, PvCO2), and Ventilation dead space (VD) were measured and compared between the two groups after initiation of mechanical ventilation. Results 30 CARDS and 10 ARDS patients fulfilled the study requirements. We observed a significant higher MPw in the CARDS group (29.17 ± 8.29 J/min vs 15.78 ± 4.45 J/min, P 0.007), similarly observed with EdPw (256.7 ± 84.06 mJ/min vs 138.1 ± 39.15 mJ/min, P 0.01) and TPw (289.1 ± 84.51 mJ/min vs 161.5 ± 45.51, P 0.007). Inside the CARDS group, we found 2 subgroups, a low shunt subgroup and a higher shunt (Qs/Qt (%): 6.61 ± 2.46 for vs 40.3 ± 20.6, P 0.0009), however, between these two subgroups we didn’t find statistical differences on lung mechanic parameters but only in oxygenation parameters (PaO2/FiO2 and PaO2/FiO2*PEEP). When comparing these two subgroups with ARDS patients, we found more similarity between the low shunt CARDS and the ARDS patients on MP (R2 0.99, P 0.001), EdPw (R2 0.89, P 0.05) and TPw (R2 0.99, P 0.0009). Conclusions: Our study suggests important differences between CARDS and ARDS regarding mechanical parameters that could lead to more complicated management of CARDS patients and a higher prevalence of VILI. However due to the study limitations, a bigger study is necessary to corroborate our findings.

  • Open Access German
    Authors: 
    Becker, Karsten; Brändle, Tobias;
    Publisher: Zenodo

    Online-Anhang

  • Open Access English
    Authors: 
    Franck, Claudio; Franck, Gustavo; Daoud, Ehab;
    Publisher: Zenodo

    Abstract Introduction SARS-CoV-2 may be associated with ARDS and the VILI. However, there are still doubts about the correlations and the interference of tidal energy in the outcomes. The objective of this study was to verify the correlations and interference of mechanical power and its components with age in the outcome in SARS-CoV-2 of subjects undergoing pressure-controlled ventilation (PCV). Method Longitudinal, prospective, observational, analytical, and quantitative study of the information collected on two parameters of the mechanical ventilator, to calculate the mechanical power by Becher formula in 163 subjects with SARS-CoV-2 and moderate ARDS between May 2021 to September 2021. Results Correlations were found between mechanical power and its components, except for compliance (P 0.234), elastance (P 0.515), resistance (P 0.570) and age (P 0.180). There was a significant impact on the outcome in the univariate analysis of age, as well as of mechanical power and its components, except for positive end expiratory pressure (PEEP) (P 0.874), minute ventilation (Ve) (P 0.437), resistive pressure (PResist) (P 0.410) and resistance (P 0.071). The multivariate analysis of mechanical power, plateau pressure (PPlateau), tidal volume (VT), driving pressure (ΔP) and elastance, showed that only mechanical power correlated to death (P 0.04) and for each additional unit in J/minute there is a 6.2% increase in the odds of death (95% IC 0.3%; 12.4%). Conclusion There are correlations between mechanical power and its components, except for compliance, elastance, resistance, and age. There is interference in the outcome in the univariate analysis of age, as well as of mechanical power and its components, except PEEP, Ve, PResist and resistance, but the multivariate analysis showed that only mechanical power correlates with the outcome in SARS-CoV-2 undergoing PCV.

  • Open Access German
    Authors: 
    Robert Koch-Institut;
    Publisher: Zenodo

    Für die Planung von Maßnahmen zur Eindämmung von COVID-19 kommt der genauen Kenntnis der Eigenschaften von SARS-CoV-2 eine zentrale Bedeutung zu. Eine besondere Rolle spielen in diesem Zusammenhang Mutationen des Virus. Für eine erfolgreiche Eindämmung der Pandemie ist es daher entscheidend, einen detaillierten Überblick über die Ausbreitungsmuster spezifischer SARS-CoV-2-Mutationen zu erhalten und auch neue Mutation frühzeitig zu entdecken.Hierfür stellt das Robert Koch-Institut die Systeme zur bundesweiten molekularen Surveillance bereit. Jedes Labor in Deutschland, das SARS-CoV-2 sequenziert, ist laut der Verordnung zur molekulargenetischen Surveillance des Coronavirus SARS-CoV-2 verpflichtet, dem Robert Koch-Institut die Sequenz- und zugehörige Metadaten zu übermitteln. Technisch erfolgt diese Übermittlung über den Deutschen Elektronischen Sequenzdaten-Hub (DESH).Im Projekt "OSEDA - Offene Sequenzdaten" verpflichtet sich das RKI, die aufgearbeiteten und qualitätskontrollierten Sequenzdaten zusammen mit einer Auswahl von klinisch-epidemiologischen Daten über die öffentlich zugängliche Repositorien des European Nucleotide Archive) und GISAID für weitere Forschungsvorhaben bereitzustellen.

  • Open Access German
    Authors: 
    Robert Koch-Institut, Fachgebiet 33;
    Publisher: Zenodo

    Die COVID-19-Impfung kann einen Wendepunkt in der Kontrolle der COVID-19-Pandemie darstellen und erfährt daher hohes Maß an öffentlicher Aufmerksamkeit. Einführung und Umsetzung der COVID-19-Impfung gehen mit besonderen Herausforderungen einher, die bei der Impfdatenerfassung zu berücksichtigen sind. In diesem Kontext ist es Ziel des Projekts 'Digitales Impfquoten-Monitoring' (DIM), tagesaktuell, bundesweit die Impfquote zu erfassen und folgend aufbereitet darzustellen, um zeitnah den Verlauf der COVID-19-Impfkampanne zu analysieren, bei Bedarf nach zusteuern, und logistisch bzw. organisatorische Konsequenzen zu ziehen.Der durch das DIM-Projekt bereitgestellte Datensatz enthält Daten über den Verlauf der COVID-19 Impfungen in Deutschland. Die hier veröffentlichten Impfdaten aggregieren Daten aus drei Datenquellen:Die DIM-Daten enthalten Angaben der Impfzentren, mobilen Impfteams, Krankenhäuser und der Betriebsärzte_innen, die über die DIM-Webanwendung übermittelt werdenDer täglich aggregierte Kerndatensatz der impfenden Ärzt_innen über die Kassenärztliche Bundesvereinigung (KBV)Der täglich aggregierte Kerndatensatz der impfenden Ärzt_innen über die Privatärztliche Bundesvereinigung (PBV)

  • Open Access German
    Authors: 
    Robert Koch-Institut;

    doi: 10.5281/zenodo.7359335 , 10.5281/zenodo.7384743 , 10.5281/zenodo.7145927 , 10.5281/zenodo.7426097 , 10.5281/zenodo.7170322 , 10.5281/zenodo.7161090 , 10.5281/zenodo.7317583 , 10.5281/zenodo.7131572 , 10.5281/zenodo.7423710 , 10.5281/zenodo.7269399 , 10.5281/zenodo.7259968 , 10.5281/zenodo.7379552 , 10.5281/zenodo.7309329 , 10.5281/zenodo.7218875 , 10.5281/zenodo.7367578 , 10.5281/zenodo.7266070 , 10.5281/zenodo.7294025 , 10.5281/zenodo.7202577 , 10.5281/zenodo.7412676 , 10.5281/zenodo.7223260 , 10.5281/zenodo.7237899 , 10.5281/zenodo.7251145 , 10.5281/zenodo.7213985 , 10.5281/zenodo.7134068 , 10.5281/zenodo.7256017 , 10.5281/zenodo.7325559 , 10.5281/zenodo.7349603 , 10.5281/zenodo.7240739 , 10.5281/zenodo.7407716 , 10.5281/zenodo.7430860 , 10.5281/zenodo.7338775 , 10.5281/zenodo.7420835 , 10.5281/zenodo.7314850 , 10.5281/zenodo.7227153 , 10.5281/zenodo.7196790 , 10.5281/zenodo.7179503 , 10.5281/zenodo.7298404 , 10.5281/zenodo.7272795 , 10.5281/zenodo.7243243 , 10.5281/zenodo.7388648 , 10.5281/zenodo.7312517 , 10.5281/zenodo.7321689 , 10.5281/zenodo.7183919 , 10.5281/zenodo.7316119 , 10.5281/zenodo.7129007 , 10.5281/zenodo.7155333 , 10.5281/zenodo.7306434 , 10.5281/zenodo.7344709 , 10.5281/zenodo.7129008 , 10.5281/zenodo.7329168 , 10.5281/zenodo.7152320 , 10.5281/zenodo.7275479 , 10.5281/zenodo.7246695 , 10.5281/zenodo.7370342 , 10.5281/zenodo.7233018 , 10.5281/zenodo.7392666 , 10.5281/zenodo.7187553 , 10.5281/zenodo.7397219 , 10.5281/zenodo.7262593 , 10.5281/zenodo.7375101 , 10.5281/zenodo.7417007 , 10.5281/zenodo.7279254 , 10.5281/zenodo.7363973 , 10.5281/zenodo.7340306 , 10.5281/zenodo.7353332 , 10.5281/zenodo.7141504 , 10.5281/zenodo.7402844 , 10.5281/zenodo.7264399 , 10.5281/zenodo.7435482 , 10.5281/zenodo.7332830 , 10.5281/zenodo.7136611 , 10.5281/zenodo.7192410 , 10.5281/zenodo.7395363 , 10.5281/zenodo.7212699 , 10.5281/zenodo.7336635 , 10.5281/zenodo.7302468

    Publisher: Zenodo

    Im Datensatz '7-Tage-Inzidenz von COVID-19 in Deutschland' werden die aktuellen 7-Tage-Inzidenzen der nach den Vorgaben des Infektionsschutzgesetzes - IfSG - an das RKI übermittelten COVID-19-Fälle veröffentlicht. Datengrundlage zur Berechnung der 7-Tage-Inzidenzen sind die an das RKI übermittelten COVID-19-Fälle. Eine detaillierte Dokumentation zur Erhebung der Daten zum Infektionsgeschehen ist im Datensatz 'SARS-CoV-2-Infektionen in Deutschland' enthalten. Die für die Berechnung der 7-Tage-Inzidenz notwendigen Bevölkerungsdaten bezieht das RKI durch das Statistisches Bundesamt (Destatis), Referat F24 | Bevölkerungsfortschreibung, Ausländer- und Integrationsstatistiken.

  • Open Access German
    Authors: 
    Robert Koch-Institut;
    Publisher: Zenodo

    Im Datensatz 'COVID-19-Hospitalisierungen' werden die aktuellen Zahlen der nach den Vorgaben des Infektionsschutzgesetzes - IfSG - erfassten hospitalisierten COVID-19-Fälle bereitgestellt. Um den Trend der Anzahl von Hospitalisierungen und der 7-Tage-Hospitalisierungsinzidenz besser bewerten zu können, wird die berichtete Hospitalisierungsinzidenz um eine Schätzung der zu erwartenden Anzahl an verzögert berichteten Hospitalisierungen ergänzt. Neben den Daten der gemeldeten COVID-19-Hospitalisierungen auf Bundes- und Länderebene wird daher ein Nowcasting der Anzahl hospitalisierter Fälle und der 7-Tage-Hospitalisierungsinzidenz auf Bundesebene durchgeführt. Ziel ist die Schätzung der Anzahl von hospitalisierten COVID-19-Fällen mit Meldedatum innerhalb der sieben vorhergehenden Tage - inklusive der noch nicht an das RKI berichteten Hospitalisierungen. Aufbauend auf dem Nowcasting wird eine Schätzung der adjustierten 7-Tage-Hospitalisierungsinzidenz durchgeführt.