Amsra's Internal Education Exam - February 2016

This study design is best described as cross-sectional because it involves assessing a random sample of residents at a specific point in time through a telephone questionnaire. It aims to gather information about the prevalence of obesity and its association with diagnosed diabetes in the community. A cross-sectional study design allows for the collection of data from different individuals at a single time point, providing a snapshot of the relationship between variables without establishing causality or following individuals over time.

This study design is a cohort study. In a cohort study, a group of individuals who share a common characteristic or exposure (in this case, women who worked in a factory painting radium dials) is followed over time to compare their outcomes (in this case, the incidence of bone cancer) with a control group (in this case, telephone operators). The study compares the incidence of bone cancer in the two groups between 1945 and 1975 to determine if there is a relationship between the exposure (working as a radium dial painter) and the outcome (developing bone cancer).

The purpose of random sampling is to ensure that the sample is representative of the target population. Random sampling involves selecting individuals or items from the population in a way that each member has an equal chance of being included in the sample. This helps to minimize bias and increase the generalizability of the findings from the sample to the larger population. By ensuring representativeness, random sampling allows researchers to make accurate inferences about the population based on the characteristics observed in the sample.

The correct answer explains the key difference between probability and non-probability sampling. Probability sampling involves starting with a defined population and selecting a sample from it, while non-probability sampling begins with a sample and defines the population based on the characteristics of that sample. This means that probability sampling is more representative of the entire population, while non-probability sampling may introduce bias by only including certain characteristics in the population.

The correct answer is that the disease outcome is rare. This suggests that the reason why the initial studies establishing maternal DES intake as a cause of vaginal adenocarcinoma in female offspring were case-control studies is because the disease outcome is rare. Case-control studies are often used when studying rare diseases or outcomes because they allow researchers to efficiently compare cases (individuals with the disease) to controls (individuals without the disease) and identify potential risk factors. In this case, using a case-control design would have been more feasible and practical than conducting a cohort study.

A prospective study is the correct answer because it involves following a group of individuals over a period of time to observe the development of a disease or condition. In this case, the study plans to measure and compare the incidence of silicosis in two populations after 5 and 10 years. This approach allows for the evaluation of cause and effect relationships and can help determine if volcanic dust exposure is indeed a risk factor for silicosis.

Based on the given histogram, the bar representing the range of 6.5 to 7.5 hours per night is taller than the bar representing 7.0 hours per night. This indicates that more students fall within the range of 6.5 to 7.5 hours, making the statement "More than half of the students slept between 6.5 and 7.5 hours per night" true.

The risk ratio (RR) is calculated by dividing the probability of a positive response in the treated group by the probability of a positive response in the placebo group. In this case, the probability of a positive response in the treated group is 40% (0.4) and the probability of a positive response in the placebo group is 10% (0.1). Therefore, RR = 0.4 / 0.1 = 4.0.

The odds ratio (OR) is calculated by dividing the odds of a positive response in the treated group by the odds of a positive response in the placebo group. The odds of a positive response in the treated group is 0.4 / (1 - 0.4) = 0.4 / 0.6 = 0.67 and the odds of a positive response in the placebo group is 0.1 / (1 - 0.1) = 0.1 / 0.9 = 0.11. Therefore, OR = 0.67 / 0.11 = 6.0.

Case-control studies are efficient for studying rare diseases because they allow researchers to identify individuals with the disease and compare them to a control group without the disease. This design is particularly useful when studying rare diseases because it is often difficult to find a sufficient number of cases for a traditional cohort study. By selecting cases and controls from a defined population, researchers can efficiently investigate the potential risk factors associated with the rare disease.

Age at first birth is a continuous quantitative variable because it represents a numerical measurement that can take on any value within a certain range. It is a continuous variable because it can be measured on a continuous scale, such as in years or months, and can have decimal values. In contrast, the other variables listed are categorical or discrete variables, such as favorite fruit, gender, decade of birth, and occupation, which represent distinct categories or groups.

Randomization minimizes confounding in a study. Confounding occurs when an extraneous variable is associated with both the exposure and the outcome, leading to a false association. By randomly assigning participants to different groups, the distribution of confounding variables is expected to be similar between groups, reducing the potential for confounding. This allows researchers to confidently attribute any differences observed in the outcome to the exposure being studied, increasing the internal validity of the study.

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Increasing the variability of the outcome would increase the width of a confidence interval. A confidence interval is a range of values within which the true population parameter is estimated to lie. The width of the confidence interval is affected by the level of confidence chosen, the variability of the outcome, the sample size, and the presence of outliers. Increasing the variability of the outcome means that the data points will be more spread out, resulting in a wider range of possible values for the population parameter, thus increasing the width of the confidence interval.

Case-control studies are observational studies that compare individuals with a specific disease (cases) to individuals without the disease (controls). These studies are primarily used to examine the association between exposures and diseases, rather than calculating disease frequency. Disease frequency measures such as incidence rate, cumulative risk, and prevalence are typically calculated using cohort or cross-sectional study designs, where individuals are followed over time or at a specific point in time, respectively. Therefore, it is not possible to calculate disease frequency directly from case-control studies.

The standard deviation is a measure of how spread out the data points are from the mean. To calculate it, we need to find the mean of the data points first. Adding up all the data points and dividing by the total number of data points, we get a mean of -18. Then, we subtract the mean from each data point and square the result. Next, we find the average of these squared differences. Taking the square root of this average gives us the standard deviation, which in this case is 7.

The method of assignment described in the question is called randomization. Randomization involves using a computer program to allocate participants into different groups purely by chance. This helps to eliminate any bias or potential confounding factors that could influence the results. By randomly assigning participants to either receive the new drug or a beta-blocker, researchers can compare the effectiveness of the two treatments in lowering systolic blood pressure in a more unbiased manner.

Using non-random sampling is a logical reason when students have already been assigned to classes. In this situation, random sampling may not be feasible or practical, as the researcher cannot randomly assign students to different classes. Therefore, non-random sampling allows the researcher to study the specific groups that have already been formed, providing insights into the characteristics and behaviors of those particular classes.

Statistical power refers to the probability of obtaining a statistically significant result when the null hypothesis is false. In other words, it measures the likelihood of correctly rejecting the null hypothesis when there is actually a true effect or relationship in the population. A high statistical power indicates a greater ability to detect true effects, while a low power increases the chances of missing important findings.

The best PICO question for this case is "In patients with allergic asthma, does the addition of omalizumab to ICS (inhaled corticosteroid) compared to ICS alone, result in improvement in asthma control and reduction of exacerbation?" This question specifically addresses the patient's concern about adding omalizumab to their current treatment and whether it would lead to improved asthma control and fewer exacerbations.

Yes, this is likely to represent a bias because the interviewers' beliefs about alcohol intake and bladder cancer could influence the way they ask questions or interpret the responses. This could lead to a higher likelihood of finding a significant association between alcohol intake and bladder cancer, predisposing to a rejection of the null hypothesis.

The likelihood ratio is the most useful ratio in terms of helping in evidence-based diagnosis. It provides information about how much a particular diagnostic test result changes the odds of a disease being present. It takes into account both the sensitivity (the ability of the test to correctly identify those with the disease) and the specificity (the ability of the test to correctly identify those without the disease). Therefore, the likelihood ratio helps in determining the probability of a disease based on the test results, making it a valuable tool in evidence-based diagnosis.

When screening for lupus erythematosus in a young patient with painful joints, the ideal test should be highly sensitive. A highly sensitive test will correctly identify a high proportion of patients who have the condition, minimizing the chances of false negatives. This is important in the initial screening stage to ensure that patients who may have lupus erythematosus are not missed and can receive further diagnostic evaluation and appropriate treatment if necessary.

The incidence rate for breast cancer is calculated by dividing the number of new cases (10 women) by the total person-time at risk (100 women-years). In this case, the incidence rate is 10/100 = 0.1 or 10%. To convert this to events per 100 women-years, we multiply by 100, resulting in 10 events per 100 women-years. Therefore, the answer "2 events per 100 women-years" is incorrect.

The correct answer is "Insomniacs with short sleep duration have a 5-fold higher odds of having hypertension, which corresponds to a 2.5-fold higher risk." This answer accurately reflects the information provided in the study. The odds ratio of 5.12 indicates that insomniacs with short sleep duration have 5 times higher odds of having hypertension compared to normal sleepers. However, the corresponding risk is 2.5 times higher, as odds ratios overestimate the risk ratio in this case.

The correct answer is to stop sampling. Ms. Landry has already started hearing the same things from each additional participant she interviews, which indicates that she has reached saturation point in her data collection. Continuing to sample more participants would not provide any new or additional information, as the same patterns and themes are being repeated. Therefore, it is advisable for Ms. Landry to stop sampling and proceed with the data analysis phase.