STUDY
Assignment Discuss possible study designs you might employ to research your question: Do physical activities and policies and support programs such as policies and rules improve or lower the risk factors of getting chronic diseases between 5 to 17 years old children in Columbia (Bristish)? The proposed research should not, in itself, be a literature review but a new study on a new group of study participants. Also, the design should be quantitative in nature. Which of the designs described in BELOW would you use to test your research hypothesis? What other designs could you also employ for this purpose? What would be the potential for bias in the study design/s you would use to test your hypothesis? After considering potential designs, state what the most appropriate design is. The following components must fit this particular design: sampling, variables, analysis, and limitations. Assignment Expectations: Identify 2-3 possible study designs that you could employ to address your research question and discuss the potential for bias with each of these. Select the most appropriate design for your study and provide rationale for your decision. Looking ahead...Ensure that sampling, variables, analyses, etc. will be compatible with this design. Develop and submit a 2-3 page paper in which these details are presented. OBJECTIVES: o Identify and discuss basic research designs o Identify potential confounders of relationships between variables and ways of dealing with confounding variables o Discuss reliability, validity, and bias o Identify types of bias Overview of Study Designs The study design is the overall plan for collecting and analyzing data. The PURPOSE OF YOUR RESEARCH DESIGN is to ENSURE that you get the CORRECT answer to your research question. The different types of material indexed in MEDLINE and other data bases are labeled in the pyramid diagram, with the least clinically relevant at the bottom and the most clinically relevant at the top. The four layers above case reports and case series represent actual clinical research. The layers below are least clinically relevant and can be useful as background resources. Observational Study Designs and the Role of Epidemiology Epidemiology studies the various factors influencing the occurrence, distribution, prevention, and control of disease, injury, and other health-related events in human populations. Epidemiologists are most concerned with the validity of research studies (see below) and epidemiologic designs are the basis of public health research. Clinical trials are a particular form of epidemiologic design and are primarily used in medical research Cohort Studies Studies following a group of people in which some are exposed to the factor of interest, to determine the association between that exposure and a specific outcome. Click here for more on cohort studies. Related terms: Incidence and Prevalence Prevalence: quantifies the proportion of individuals in a population who have the disease at a specific instant and provides an estimate of the probability (risk) that an individual will have the disease at a specific point in time. o Incidence: quantifies the number of new cases of disease that develop in a population of individuals at risk during a specific time. Case-Control Studies Studies in which the proportion of cases with a potential risk factor are compared to the proportion of controls (individuals without the disease) in terms of that risk factor. These studies are commonly used for initial, inexpensive evaluation of risk factors and are particularly useful for rare conditions or for risk factors with long induction periods. Due to the potential for many forms of bias, case control studies provide relatively weak empirical evidence even when properly executed. Nested case-control studies (case control studies within a cohort with exposure likely recorded before outcome) are more valid than "true" case-control studies. Click here for more on case-control studies. Cross-Sectional (Prevalence Study) Study A descriptive study of the relationship between diseases and other factors at one point in time in a defined population. Click here for more on cross-sectional studies. Ecologic Studies An observational analytical study based on aggregated secondary data. Aggregate data on risk factors and disease prevalence from different population groups are compared to identify associations. Because all data are aggregate at the group level, relationships at the individual level cannot be empirically determined but are rather inferred from the group level. Thus, because of the likelihood of an ecologic fallacy, this type of study provides WEAK empirical evidence. Related Concept: Confounding Confounding Factors: o An important consideration in epidemiologic research is that an observed association (or lack of one) between an exposure and an outcome may be due to the effects of a third factor that is associated with the exposure and independently affects the risk of developing the disease. o This is referred to as confounding. The extraneous factor is called a confounding factor or a confounder. o Confounding is the main problem with observational studies. Healthy or unhealthy behaviors congregate in the same individuals. For example, people who exercise also eat healthier. Thus, if you merely look at the relationship between exercise and health outcomes without taking diet into consideration, the effect of exercise will falsely appear larger that it actually is. Case Series and Case Reports- Weak Evidence Case Series: A descriptive, observational study of a series of cases, typically describing the manifestations, clinical course, and prognosis of a condition. A case series provides weak empirical evidence because of the lack of comparability unless the findings are dramatically different from expectations. Case series are best used as a source of hypotheses for investigation by stronger study designs, leading some to suggest that the case series should be regarded as clinicians talking to researchers. Case Report: Anecdotal evidence. A description of a single case, typically describing the manifestations, clinical course, and prognosis of that case. Due to the wide range of natural biologic variability in these aspects, a single case report provides little empirical evidence to the clinician. They do describe how others diagnosed and treated the condition and what the clinical outcome was. Experimental Studies In experimental studies, the allocation of participants to a certain intervention is done by the investigator. The main quality of experimental studies is that the investigator can control for confounding. While in an observational study people self-select their category of exposure (e.g. people choose to exercise or not), in an experimental study the researcher assigns the exposure. The symmetry of potential unknown confounders is achieved through randomization. Thus, a randomized controlled clinical trial (RCT) is an experimental study in which individuals are randomly allocated to two or more treatment groups and the outcomes of the groups are compared after a predetermined follow-up time. If properly executed, the RCT is the strongest evidence for a relationship between exposure and outcome. Reliability, Validity and Bias Reliability (Reproducibility): the consistency of your measurement, or the degree to which an instrument measures the same way each time it is used under the same condition with the same subjects. In short, it is the repeatability of your measurement. A measure is considered reliable if a person's score on the same test given twice is similar. Validity: Best Available Approximation to the truth, Accuracy. o Click here for more on reliability and validity. o Internal Validity: Truth within a study. A study is internally valid if the study conclusions represent the truth for the individuals studied because the results were not likely due to the effects of chance, bias, or confounding because the study design, execution, and analysis were correct. The statistical assessment of the effects of chance is meaningless if sufficient bias has occurred to invalidate the study. All studies are flawed to some degree. The crucial question that the reader must answer is whether or not these problems were great enough that the study results are more likely due to the flaws than the hypothesis under investigation. o External Validity (Generalizability): Truth beyond a study. A study is external valid if the study conclusions represent the truth for the population to which the results will be applied because both the study population and the reader's population are similar enough in important characteristics. The important characteristics are those that would be expected to have an impact on a study's results if they were different (e.g., age, previous disease history, disease severity, nutritional status, co-morbidity, ...). Whether or not the study is generalizable to the population of interest to the reader is a question only the reader can answer. External validity can occur only if the study is first internally valid. Bias (Systematic Error): Deviation in one direction of the observed value from the true value of the construct being measured (as opposed to random error). Any process or effect at any stage of a study from its design to its execution to the application of information from the study, that produces results or conclusions that differ systematically from the truth. Almost all studies have bias, but to varying degrees. The critical question is whether or not the results could be due in large part to bias, thus making the conclusions invalid. Observational designs are inherently more susceptible to bias as compared to experimental designs. Here are some examples of bias: o Confounding Bias - results from confounding (described above) o Ecological Bias (Fallacy) - Systematic error that occurs when an association observed between variables representing group averages is mistakenly taken to represent the actual association that exists between these variables for individuals (described above) o Measurement Bias - Measurement error that affects study groups in a systematically different way. Related Concept: Observer Bias o Reader Bias - Systematic errors of interpretation made during inference by the user or reader of clinical information (papers, test results, ...). Such biases are due to clinical experience, tradition, credentials, prejudice and human nature. The human tendency is to accept information that supports pre-conceived opinions and to reject or trivialize that which does not support preconceived opinions or that which one does not understand. o Selection Bias - Systematic error that occurs when, because of design and execution errors in sampling, selection, or allocation methods, the study comparisons are between groups that differ with respect to the outcome of interest for reasons other than those under study. o Recall Bias - Respondents' selective recalling of past experiences and behavior Case-control studies are particularly prone to selection and recall bias (e.g. cancer patients will remember past behavior differently than controls).
Study Designs
Name:
Institution:
In the field of epidemiology, it is crucial that the occurrence of a chronic disease in question be measured within the given population of between five and seventeen years old. Other than that, there is also the idea of assessing the exposure that is associated with the disease. One of the very first steps that one has to take into considerations is that of defining the right hypothesis, for the research on chronic diseases. The next step involves the selection of the study design that will fit the research. The study designs fall into two broad categories, which are experimental and observational. The former relates to varying of certain variables and recording the outcome. Study subjects of the selected population of between five and seventeen may be separated into two groups. One of the groups is treated to a controlled exposure of all the possible causes of the chronic disease, while the second group lives a normal live as the control sample. The results of the prevalence between the two groups are then compared for analysis and recommendation. With the observational study, much of the results about the chronic diseases would be derived from observation (University of Ottawa, 2014).
One of the study designs that would be applicable in this case is the cross-sectional surveys. In this case, a random sample of the population between five and seventeen years would be drawn and all the information about their health status and history is put into the record. After the recording, the sample can then be compared to other groups of people that have the chronic diseases in question and those without, to try and draw a conclusion about the exposure and the factors that may be responsible for the disease. One of the major biases in this case is selection bias, where ideally, getting a representative sample is difficult. Information bias is also common given that information on the disease condition and the risk factors are obtained at the same time (International Agency for Research on Cancer, n.d.), as w...