Table Of Content
While this study cannot prove that overeating causes obesity, it can draw attention to a relationship that might be worth investigating. 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.
Examples of Cross-Sectional Data
Longitudinal studies and cross-sectional studies are two different types of research design. In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time. A cohort study is a type of longitudinal study that samples a group of people with a common characteristic. One key difference is that cross-sectional studies measure a specific moment in time, whereas cohort studies follow individuals over extended periods. Findings from this study showed that residents whose family members smoked were more supportive of smoke-free building policies than those whose family members did not smoke.
Publication types
If learners are not immersed in the simulation, their ability to achieve learning outcomes is not only affected but can also lead to anxiety, which can hamper their collaboration with their peers [11]. This suggests that a simulation design that increases physical, conceptual, and psychological fidelity is necessary to induce flow, as flow increases students’ motivation, enjoyment, and satisfaction with the learning process. The design’s inherent nature makes it inexpensive to conduct and can yield multiple independent (predictor) and dependent (outcome) variables (Cummings, 2013).
The stages of a Cross-Sectional study
Each item was scored on a 5-point Likert scale ranging from 1 point (strongly disagree) to 5 points (strongly agree). The total score ranged from 10 to 50, with a higher score indicating a higher level of flow in simulation-based education. Nevertheless, simulation-based education improves nursing students’ problem-solving, clinical judgment, and communication skills [5, 6] and develops the teamwork necessary for clinical nurses [7], leading to its increasing use in nursing education. Simulated education is an integrated process of knowledge, skill, and experiential learning for nursing students and is a teaching and learning strategy to facilitate nursing competencies [1]. The National Council of State Boards of Nursing recommends simulation use in nursing education since it can safely replace up to half of clinical practice training hours [2].
Cross-sectional study
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Note that the original results and data are studied together simultaneously in an analytical cross-sectional study. The Australian Census run by the Australian Bureau of Statistics, is an example of a whole of population cross-sectional study. If the results show that Asian women would not buy the phone because it is bulky, the mobile phone company can tweak the design to make it less bulky.
Participants in longitudinal studies have to commit for an extended period, which significantly increases costs. Cross-sectional studies are at risk of participation bias, or low response rates from participants. If a large number of surveys are sent out and only a quarter are completed and returned then this becomes an issue as those who responded may not be a true representation of the overall population. Please note the Introduction, where there is a table under "Which study type will answer my clinical question?". You may find that there are only one or two question types that your study answers – that’s ok. Cross-sectional studies are not the best choice for studying rare events because of the need for a sufficiently large sample size to obtain meaningful results.
Cross-Sectional Studies: Strengths, Weaknesses, and Recommendations
Do sociodemographic factors influence the levels of health and oral literacy? A cross-sectional study - BMC Public Health - BMC Public Health
Do sociodemographic factors influence the levels of health and oral literacy? A cross-sectional study - BMC Public Health.
Posted: Wed, 20 Dec 2023 08:00:00 GMT [source]
These sponsors had no role in the study design; in the collection, analysis or interpretation of data; in the writing of the report; or in the decision to submit the article for publication. The confidence level (1-α) was 0.95; the proportion of main outcome (depression and anxiety) was 0.1; The confidence interval width (two sided) was 0.03. The confidence interval formula was Exact (Clopper-Pearson); the 2-tailed P value was 0.05. It was calculated by PASS 11.0 (Power Analysis and Sample Size 11.0, NCSS Inc., USA) [8, 10, 18].
Information was gathered through a questionnaire that individuals completed themselves. The mental health of the participants was assessed using the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder Assessment-7. Binary logistic regression was used to calculate adjusted odds ratios (ORs) and their corresponding 95% confidence intervals. 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 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].
He has been published in peer-reviewed journals, including the Journal of Clinical Psychology. Neither patients nor the public were involved in the research design, recruitment, conduct, reporting and dissemination plans of the study. Participants A total of 616 adult individuals living in MUH for at least 2 years participated in the study. The Ethics Committee of Shengjing Hospital Affiliated China Medical University granted ethical permission (2022PS753K). The procedures were carried out in accordance with the ethical guidelines outlined in the 1975 Declaration of Helsinki.
Cross-sectional studies can be useful research tools in many areas of health research. By learning about what is going on in a specific population, researchers can improve their understanding of relationships among certain variables and develop additional studies that explore these conditions in greater depth. For example, researchers might be interested in learning how exercise influences cognitive health as people age. They might collect data from different age groups on how much exercise they get and how well they perform on cognitive tests. Conducting such a study can give researchers clues about the types of exercise that might be most beneficial to the elderly and inspire further experimental research on the subject.
Second, the data were gathered by self-reported questionnaires, specifically pertaining to measurements such as height and weight. In addition, given that the majority of the study sample consists of young women, there is a possibility that they may be tempted to falsely report their height and weight. Third, it is important to note that the GAD-7 and PHQ-9 are screening questionnaires that lack the ability to provide clinical diagnosis. However, this study is the first to examine the connection between BMI and mental health in nurses during the COVID-19 epidemic while accounting for several influential factors. The cross-sectional design is an appropriate method to determine the prevalence of a disease, attribute, or phenomena in a study sample.
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. First, due to the cross-sectional nature of the study, we could not establish a causal relationship between the choice of smoke-free policies and sociodemographic and smoking-related variables. Second, we used self-reported data that are subject to recall and social desirability bias.50 51 These two types of bias may result in underestimation or overestimation of the association between the outcome variable and other variables.
The data collected can lead to additional studies to build upon the knowledge obtained. From the example, the investigators learned that obese HIV participants were more likely to be sedentary; the next study might develop a clinical trial to determine the methods to increase activity level in this population. Cross-sectional designs help determine the prevalence of a disease, phenomena, or opinion in a population, as represented by a study sample. Prevalence is the proportion of people in a population (sample) who have an attribute or condition at a specific time point (Mann, 2012) regardless of when the attribute or condition first developed (Wang & Cheng, 2020). Additionally, each study participant’s evaluation is completed at one time-point with no follow-ups (Cummings, 2013), providing a ‘snapshot’ of the sample. Cross-sectional designs can be implemented as an interview or survey and may also collect physiological data and biological samples.
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