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Basic Research Design:
Published in Lynne M. Bianchi, Research during Medical Residency, 2022
Lynne M. Bianchi, Luke J. Rosielle, Justin Puller, Kristin Juhasz
Note: The key differences between descriptive and analytical cross-sectional studies are: Descriptive cross-sectional studies indicate prevalence of a disease or condition at a given time and do not include a control group.Analytical cross-sectional studies include a control group, provide insight into associations, and may indicate an odds ratio.
Study Design
Published in Marcello Pagano, Kimberlee Gauvreau, Heather Mattie, Principles of Biostatistics, 2022
Marcello Pagano, Kimberlee Gauvreau, Heather Mattie
An advantage of cross-sectional studies is that they can examine more than one exposure and more than one outcome simultaneously. They are relatively quick and inexpensive compared to other study designs. A disadvantage is that while they can be used to investigate associations, cross-sectional studies cannot be used to infer causality. Temporality cannot be established; we typically do not know whether the exposure came before or after the outcome for any particular study subject.
Cancer Epidemiology
Published in Trevor F. Cox, Medical Statistics for Cancer Studies, 2022
Cross-sectional studies collect data at one time point. They are inexpensive to run compared to cohort studies, can collect data on multiple outcomes and exposures and can estimate prevalence. On the downside, incidence cannot be measured and causality cannot be established, only association. You cannot show whether a risk factor caused the cancer, or that having cancer caused individuals to become more exposed to the risk factor. The latter is unlikely in most cases – I am not going to take up smoking because I have been diagnosed with lung cancer! To carry out a cross-sectional study, a sample of individuals needs to be chosen from the population of interest. Data collected can come from questionnaires, interviews and medical examinations. Bias can be a problem because of non-responders, participant recall of past events and selection bias.
Central sensitization syndrome in patients with rotator cuff tear: prevalence and associated factors
Published in Postgraduate Medicine, 2023
Run Peng, Rong Yang, Ning Ning
There were some limitations of this study. First, as our study is cross-sectional in nature, it does not allow for the assessment of disease progression within individual patients over time, consideration of generational differences, or the establishment of causal relationships. This limitation restricts our ability to draw conclusions regarding the temporal aspects and causality of central sensitization in patients with RCT. However, we acknowledge that cross-sectional studies are valuable in estimating prevalence and identifying associated factors. We have taken this into account when interpreting our findings. Second, because the CSI is a self-assessment questionnaire, patients may have a significant impact on the results. In order to evaluate the CSS, additional research needs gather objective criteria such sensory hypersensitivity determined by quantitative sensory testing. Third, given that our center is a surgical department and that the majority of the patients enrolled were candidates for surgical procedures, the severity of RCT might be higher. Those who do not require surgical treatments should be the focus of future research.
The HEX-ACO-18: Developing an Age-Invariant HEXACO Short Scale Using Ant Colony Optimization
Published in Journal of Personality Assessment, 2022
Gabriel Olaru, Kristin Jankowsky
Cross-sectional and longitudinal studies are complementing approaches of studying age-associated differences in personality. Longitudinal approaches allow for the examination of change by studying the same individuals over repeated measurement occasions, whereas cross-sectional studies are focused on age-associated differences between participants. Cross-sectional studies generally cover broader age ranges and item sets, but may be affected by cohort differences. Longitudinal findings may be affected by measurement occasion effects or repeated scale administration (e.g., regression to the mean, practice effects). In this study we optimized MI across age in a cross-sectional context. An optimization of both cross-sectional and longitudinal comparability with longitudinal LSEM would have been preferable. However, longitudinal datasets generally only cover narrow age ranges or use shortened inventories that cannot be used in the context of item selection. In addition, longitudinal administrations of longer personality inventories generally only cover short time spans used to evaluate re-test reliability or a small number of repeated measures, which would not allow us to rule out measurement occasion specific effects.
Prevalence and incidence of hearing impairment among adults: a 13-year follow-up study
Published in International Journal of Audiology, 2021
Venla Lohi, Pasi Ohtonen, Martti Sorri, Elina Mäki-Torkko, Samuli Hannula
While cross-sectional studies provide data at a certain time point, longitudinal studies enable the observation of changes in a certain population or a sample. Hearing deteriorates with ageing, and longitudinal studies, in particular, are expected to provide valuable information. On the other hand, longitudinal studies are time-consuming and resource-intensive. The prevalence of HI has been reported in several population-based, cross-sectional studies. The National Study of Hearing (NHS) is a comprehensive study reporting the prevalence of HI for different ages (18-80 years) in the UK (Davis 1995). In the US, the Framingham cohort study, the Epidemiology of Hearing Loss Study (EHLS) and the National Health and Nutrition Survey (NHANES) provide rich and substantial data on HI among adults (Cruickshanks et al. 1998; Gates, Cooper, Kannel, and Miller 1990; Goman and Lin 2016). The prevalence of HI has also been reported in the Blue Mountains Hearing Study (BMHS) among Australian adults aged 49 years and older (Gopinath et al. 2009) and in a Norwegian study (Borchgrevink, Tambs, and Hoffman 2005). More recently, larger studies examining the prevalence of HI have been conducted in China, the Netherlands and Germany (Homans et al. 2017; von Gablenz, Hoffmann, and Holube 2017; Wang et al. 2019). Furthermore, in an older, Finnish population-based study, the prevalence of HI was analysed for different ages from 5 to 75 years (Uimonen, Huttunen, Jounio-Ervasti, and Sorri 1999).