The research had been carried out to develop the e-student worksheet (e-SW) based on multiple representational learning models on the material factors which affect the rate of reaction to determine its effectiveness in understanding the concepts and activities of students, as well as the teacher's and the student's responses towards e-worksheet application. The research method and development (R&D) of the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model were used for the development of e-SW. The research samples used were the students of class XI MIPA 1, and the chemistry teachers of class XI of senior high school 3 Banda Aceh, then the determination of the sample for implementation was carried out using random sampling techniques. Based on the results of the study, it can be concluded that an e-worksheet based on the developed multiple representation learning models on the factors which affect the reaction rate fulfilled the very feasible criteria with the acquisition of validity and reliability of 0.85 and 85. Complete understanding of the concepts and activities of students using eworksheet was splendid, namely 84.8 and 85%. The response of students and teachers to the development of e-worksheet based on the multiple representation learning models was also splendid.

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Background: Older adults experience progressive decline in various organs and changes in pharmacokinetics and pharmacodynamics of the drugs in the body which lead to an increased risk of medication-related problems. Potentially inappropriate medications (PIMs) and medication complexity are key factors contributing to adverse drug events in the emergency department (ED). Objective: To estimate the prevalence and investigate the risk factors of PIMs and medication complexity among older adults admitted to the ED. Methods: A retrospective observational study was conducted among patients aged > 60 years admitted to the ED of Universitas Airlangga Teaching Hospital in January -June 2020. PIMs and medication complexity were measured using the 2019 American Geriatrics Society Beers Criteria® and Medication Regimen Complexity Index (MRCI), respectively. Results: A total of 1005 patients were included and 55.0% (95% confidence interval [CI]: 52 -58%) of them received at least one PIM. Whereas, the pharmacological therapy prescribed to older adults had a high complexity index (mean MRCI 17.23 + 11.15). Multivariate analysis showed that those with polypharmacy (OR= 6.954; 95% CI: 4.617 -10.476), diseases of the circulatory system (OR= 2.126; 95% CI: 1.166 -3.876), endocrine, nutritional, and metabolic diseases (OR= 1.924; 95% CI: 1.087 -3.405), and diseases of the digestive system (OR= 1.858; 95% CI: 1.214 -2.842) had an increased risk of receiving PIM prescriptions. Meanwhile, disease of the respiratory system (OR = 7.621; 95% CI: 2.833 -15.150), endocrine, nutritional and metabolic diseases (OR = 6.601; 95% CI: 2.935 -14.847), and polypharmacy (OR = 4.373; 95% CI: 3.540 -5.401) were associated with higher medication complexity. Conclusion: In our study, over one in every two older adults admitted to the ED had PIMs, and a high medication complexity was observed. Endocrine, nutritional and metabolic disease was the leading risk factors for receiving PIMs and high medication complexity.

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COVID-19 cases in Indonesia still remain a concern, particularly for public health. Several factors, such as gender, age, comorbidity, occupation, and vaccination status, might influence COVID-19 infection. Individuals who have many predicting factors have a higher risk of being infected by COVID-19. Other studies have not yet shown the significance of predicting factors for COVID-19 infection in Indonesia. The study explored the association between the predicting factors and COVID-19 infection in Indonesia. The study used a cross-sectional method with a population of all Indonesian communities. It was conducted in August 2021 by distributing a Google Form questionnaire in Indonesia. By a saturated sampling of the population in Jawa, Sumatera, Sulawesi, Kalimantan, and Papua, 776 Indonesians were selected; they were aged > 17 years and voluntarily completed the questionnaires. whereas respondents with incomplete data were excluded from this study. The data were analyzed using a binary logistic regression test in SPSS (version 21.0). The respondents include 134 men (17.3%) and 642 women (82.7%). The binary logistic regression analysis showed that COVID-19 infection was more common among respondents who were non-health-care workers (p  0.001) and less common among those who had been fully vaccinated (p  0.001). The COVID-19 infection was significantly associated with occupation and vaccination status.  Keywords: COVID-19 Infection, Predicting Factors, Public Health, Health-Care Worker, COVID-19 Vaccination, Comorbidity

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