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All rights are reserved, including those for text and data mining, AI training, and similar technologies. Similar to the OR interpretation, if the RR was equal to 1, exposure did not prevent or harm the exposed and unexposed groups. In other words, being obese did not affect the activity level (sedentary versus not sedentary). If the RR was less than 1, it implies that the exposure had a protective effect in that obese HIV participants were less likely to be sedentary than the unexposed group (not obese). To implement a cross-sectional study, you can rely on data assembled by another source or collect your own. Case-control studies differ from cross-sectional studies in that case-control studies compare groups retrospectively and cannot be used to calculate relative risk.
Analytical Studies
Thus, it suggests that Korean nursing education is moving toward simulation-based instructional design. We can measure the prevalence of disease or calculate the OR as a measure of association. However, due to the nature of study design, in general, it is difficult to derive causal relationships from cross-sectional analysis. The conduct of research requires the selection of the appropriate method to evaluate the research problem or question. Due to some topics’ ethical nature or the need to understand the natural history (i.e., disease or condition), using an observational study design might be the best fit. The primary purposes of observational studies are to describe and examine the distributions of independent (predictor) and dependent (outcome) variables in a population (sample) and analyze the associations between them (Cummings, 2013).
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Defining Characteristics of Cross-Sectional Studies
The results might conclude that obesity among the HIV participants was twice (2.07) as common and occurred almost 12% more often among HIV participants who were sedentary. As briefly discussed earlier, multiple cross-sectional surveys are used to assess the changes in exposures and outcomes in a particular population. A study by Sardana et al. evaluated the antibiotic resistance in isolates of Propionibacterium acnes in a tertiary care hospital in India.
Timeliness
The collected data were analyzed through t-test, ANOVA, Scheffé test, and Pearson’s correlation coefficient using SPSS 25.0. The mediating effect of flow was analyzed through the three-stage mediation effect procedure using hierarchical regression analysis and the Sobel test. A cross-sectional study is a type of observational research design that analyzes data from a population, or a representative subset, at one specific point in time.
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Cross-Sectional vs. Longitudinal Studies
Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research. The cross-sectional study design is the most commonly used design and generally has an analytical component to test the association between the risk factor and the disease. The analytical study designs of case-control, cohort and clinical trial will be discussed in detail in the next article in this series.
Strengths of a Cross-sectional Study
Cross-sectional studies do not provide information from before or after the report was recorded and only offer a single snapshot of a point in time. Cross-sectional studies rely on surveys and questionnaires, which might not result in accurate reporting as there is no way to verify the information presented. Cross-sectional studies are also unique because researchers are able to look at numerous characteristics at once. Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education.
By comparing different subjects without considering the time variable, these studies can provide valuable insights into the prevalence and characteristics of phenomena within a population. The main strength of the cross-sectional design is the ability to obtain results faster. Participants either have the condition or attribute at the time of data collection or not. Furthermore, there are no participant follow-ups; therefore, losing study participants during the study is not an issue.
Cross-sectional studies often draw samples from a large and heterogeneous study population (Wang & Cheng, 2020). Participants with the rare condition of interest might not be identified in the study sample. Confidence intervals (CI) measure the precision of the OR, RR, or the possible “variation in a point estimate (the mean value)” (Alexander, 2015b, p 4).
Challenges of cross-sectional studies
One key difference is that cross-sectional studies measure a specific moment in time, whereas cohort studies follow individuals over extended periods. Both the PPS and the patients’ antibiotic history records from the laboratory registers revealed frequent use of antibiotics classes including cephalosporins, tetracyclines and penicillins. Such findings are in consistent with other studies conducted in South Africa and Uganda [21, 22]. Overall, the resistant pattern of such antibiotics has shown to be considerably high in Malawi based on previous studies and current national AMR reports [10, 11, 15].
Since cross-sectional research data is gathered all at once, multiple variables can be assessed simultaneously. This is especially useful if you’re interested in exploring associations between sets of variables. Although, as we will discuss shortly, cross-sectional market research designs may be explanatory in nature, this methodology is known as descriptive research because it cannot be used to determine the cause of something. In this article, we’ll be focusing on cross-sectional designs, exploring the types of research questions and topics they’re useful for addressing, the characteristics, benefits and weaknesses of the approach, and giving you some handy tips on how to use them.
Shortage of antibiotics as well as unrevised guidelines partly contribute to irrational use of antibiotics in health care facilities in Malawi and sub-Saharan region [10, 20, 22]. Often times, empirical antibiotic prescriptions are made without any microbiological indication as most healthcare facilities do have limited diagnostic capacity. Indiscriminate use of broad spectrum antibiotics leads to extremely high healthcare costs due to an increase in hospital admissions and drug usage [4]. 4) The mediating effect of flow on the relationship between simulation design and simulation educational satisfaction was examined using simple and multiple regression analyses based on the methodology of Baron and Kenny’s three-step procedure. This descriptive survey study investigates factors related to simulation educational satisfaction among nursing students. This highlights the value of the flow experience in enhancing intrinsic motivation in remote learning, which depends on learners’ self-direction, and in producing excellent learning outcomes [19].
Findings for this study will help the hospital AMS team to better understand the burden and relationship between AMR and antibiotics overuse. The goal is for hospital AMS teams to co-design effective interventions including formulation of antibiogram which provide a reference for empirical antibiotic prescriptions. Malawi continues to report rising cases of AMR among both in-patients and out-patients. Several studies have been conducted in the past two decades, signifying the emerging superbugs [7, 8].
However, in this study, 76.9% were satisfied with their major and clinical practice, indicating that simulation educational satisfaction was higher than in the previous study. Furthermore, in this study, the more satisfied students were with their majors and clinical experiences, the higher their simulation educational satisfaction was, supporting this inference. When examining the mean ratings for each of the simulation educational satisfaction subfactors, the emotional response score was the lowest in both this study and the previous study [8]. This may have been because simulation-based education caused nursing students to feel nervous, anxious, or embarrassed [9, 26, 27]. Student feelings assume a fundamental part in comprehension that relates to the securing and moving of information and clinical abilities [28].
The Korean Accreditation Board of Nursing Education also allows simulation-based education to replace four credits of clinical practice credits in the third phase and up to six credits in the fourth phase [3]. The characteristics you want to observe and your research goals dictate the best type of study to use. Cross-sectional studies, for instance, are vital when researching groups of people at a single point in time. Cross-sectional research studies capture multiple types of data at a single point in time.
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