Indonesia has distributed the COVID-19 vaccinations to its people starting from January 2021 based on certain priorities to deal with COVID-19 pandemic. News of deaths after the COVID-19 vaccination has made some people hesitate to get vaccinated. This study aims to depict the pattern and determinant of public interest in COVID-19 vaccine information using Google Trends data. The pattern can be used as a suggestion to the government to conduct a campaign on the COVID-19 vaccine. Several topics related to the COVID-19 vaccine were collected from Google Trends and then clustered by the province using K-Means. By total within sum of square, best number of clusters is two. Then, a logistic regression analysis was done with cluster as response variable to find out what factors made people interested in the COVID-19 vaccine topic. As a result, percentage of people who received the first dose of the COVID-19 vaccine and the rate of COVID-19 patients who were treated had influenced public interest in the COVID-19 vaccine. Hence, the campaign must be transparent so that the public can see both the good and bad effects of vaccination. It will help to reduce the number of people dying after receiving vaccinations.
Nutritional-related problems can severely impact the growth and development of children under five. It can trigger low IQ and delays in motor and skill development. Therefore, a good understanding of the factors related to children's nutrition will lead to the successful prevention of malnutrition in children under five. This research aims to analyze and synthesize data on factors related to the nutritional status of children under five. This study used a narrative review method. The literature in English was searched using the indexed databases of Google Scholar, Scopus, and PubMed. There were 9.129 scientific journals, and only 13 met the inclusion criteria. From the 13 journals, information was collected in the form of publication years from 2015 to 2021, journal titles, research designs, research populations, interventions, results, and most importantly, the nutrition issue in children under five. Data processing was done by collecting sentences that were relevant to the coding, reading and marking essential sentences, and compiling a framework for reviewing narratives. Data analysis was carried out qualitatively by presenting data and compiling research reports. The results reveal that variables such as prelacteal feeding history, mother's education, infectious diseases suffered, and antenatal care visits were the most critical factors affecting the nutritional status of children under five. Conclusion: The main factors causing the nutritional status of children under five are that the children have a history of prelacteal feeding, low maternal education, children under five often experience infectious diseases, and low antenatal care visits.
Complaints of musculoskeletal disorders (MSDs) are common in workers with a reasonably heavy workload, such as workers at refill drinking water depots. MSDs can be caused by repetitive activities such as daily bending, lifting and lowering liters of drinking water refills. This study aimed to identify the risk factors of MSDs among workers at refilled drinking water filling depots and analyze the dominant factors that influence MSDs. This study was quantitative research with an analytical survey using a cross-sectional design conducted in Simpang Selayang Village, Medan City, Indonesia. A total of 40 refilled drinking water depot workers were involved in this study with a comprehensive sampling approach. Data was collected directly by distributing questionnaires to workers at refill drinking water filling depots. Data were tested statistically using the Chi-Square test and logistic regression. The analysis showed that work posture, workload, tenure and length of work are associated with MSDs complaints. The results of the logistic regression test showed that the dominant variable influencing MSDs complaints is work posture. Refillable drinking water depot workers with non-ergonomic working postures were likely to experience MSDs complaints 11 times as often as those with ergonomic work postures. The findings highlight the need for local health agencies to educate or empower workers at water refilling stations regarding MSDs complaints. Musculoskeletal disorders associated with work involving heavy loads could be prevented if workers know ergonomic work postures well. In addition, adequate rest is recommended to avoid musculoskeletal injuries.
Background: Pesticides can poison users if they do not follow pesticide use standards. This is because the active substances in these pesticide products can cause acute pain. Objective: The study aimed to identify the factors of safe behavior in using pesticides in farmers. Methods: This study employed a scoping review method. The literature search was carried out on the indexed databases of Google Scholar, Science Direct, Scopus, PubMed, Free Medical Journals, and ProQuest in English. There were 450 research articles, and 15 met the inclusion criteria. From the 15 journals, information was collected from the publication year 2015-2021, article titles, design, population, interventions, and results. Relevant study articles related to the topics were qualitatively analyzed using NVIVO-12 Plus. Results: The analysis showed that knowledge, safe behavior of using pesticides, farmers' education, and personal protective equipment are the dominant factors influencing the safe behavior of using pesticides on farmers. Conclusion: Farmers who do not comply with safe behavior will have a higher health risk because of the toxicity of pesticides that can be directly inhaled and enter through the pores of the farmers’ skin.
Abstract BACKGROUNDS : The COVID-19 pandemic has created a global health emergency that requires a public health response to prevent the spread of the virus. AIM: The purpose of this study was to determine the prediction model for the incidence of COVID-19 based on community behavior. METHODS: This study used a cross-sectional study design. The study population was all people aged >18 years in Medan City and obtained a sample of 395 people with stratified random sampling technique. The research instrument used a questionnaire in google form, then, using Microsoft Office Excel, we transferred the data from the survey to a computer program. Furthermore, the data was analyzed using the neural networks method. Then the features importance will be calculated using the Random Forest with Mean Decrease Impurity (RF-MDI) method. RESULT: The results showed that based on the confusion matrix, the prediction value for those who did not suffer from COVID-19 was correct from negative data = 8, the correct prediction value for COVID-19 from positive data = 8. While the incorrect prediction value for machines that predicted negative results but the actual data was positive = 2, and predicts a positive result but the actual data is negative = 4. Thus, based on the neural net classification method, the accuracy value is 72%. The results of this study indicate that poor preventive behavior by the community greatly affects the spread of COVID-19 cases. CONCLUSION: Poor community behavior, such as not limiting their interaction/contact with other people, not exercising frequently, leaving the house without keeping a safe distance, and not washing hands regularly, can all impact COVID-19 transmission in the community Keywords: Behavior Prediction Model, COVID-19 Incidence, Neural Network
Mental health is an issue that is often discussed during the Covid-19 pandemic. It is critical to understand mental health for realizing its beneficial aspects. Early detection or screening of mental health status is an excellent step to prevent mental health problems. The researchers are interested in screening mental health problems in groups of adults and the elderly. This research design is a descriptive study with a cross-sectional data collection approach. The population in this study were all residents on Jalan Pasar VII Padang Bulan, Medan. The research sample was 139 people who were recruited by non-probability sampling with purposive sampling technique. Data collection was carried out from August to December 2021. The questionnaire used in this study is the Depression Anxiety Stress Scales (DASS 42) questionnaire, which is a tool for measuring stress, anxiety, and depression levels which contains 42 questions. This study shows that from 139 respondents, 54 people (38.85) suffer from mental health problems. Types of mental health problems experienced by respondents were stress as much as 32 people (23%), 54 people (38.85%) experienced anxiety, and 36 people experienced depression (25.9%). It is crucial for the community to educate themselves on how to manage their mental health in a healthier way.
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