Question

The article "Teenage Physical Activity Reduces Risk of Cognitive Impairment in Later Life" (Journal of the American Geriatrics Society [2010]) describes a study of more than 9,000 women over 50 years old from Maryland, Minnesota, Oregon, and Pennsylvania. The women were asked about their physical activity as teenagers and at ages 30 and \(50 .\) A press release about this study (www.wiley.com) generalized the study results to all American women. In the press release, the researcher who conducted the study is quoted as saying Our study shows that women who are regularly physically active at any age have lower risk of cognitive impairment than those who are inactive, but that being physically active at teenage is most important in preventing cognitive impairment. Answer the following four questions for this observational study. (Hint: Reviewing Examples 1.3 and 1.4 might be helpful.) a. What is the population of interest? b. Was the sample selected in a reasonable way? c. Is the sample likely to be representative of the population of interest? d. Are there any obvious sources of bias?

Short answer

a. The population of interest is 'all American women'. b. It's unclear whether the sample was selected in a reasonable way due to lack of specific details. c. It's not explicitly informed if the sample is likely to be representative of the population of interest 'all American women'. d. Without more information, it's hard to pinpoint any obvious sources of bias.

Step-by-step solution

Identification of population of interest

The population of interest is often the larger group to which we wish to generalise the results of our study. For this specific exercise, the population of interest is 'all American women' as inferred from the press release that generalized the study results.

Assessing the sample selection

The sample selection refers to how the participants in the study were chosen. In this study, women over 50 years old from Maryland, Minnesota, Oregon, and Pennsylvania were included. It's not explicitly detailed how they were selected, so one cannot definitively say if the sample was selected in a reasonable way.

Evaluating the representativeness of the sample

The representativeness of the sample refers to how closely it mirrors the overall population of interest. Given the provided information, it's not clear if the sample is likely to be representative of 'All American women'. Again, this would depend on whether the selection process was unbiased and the composition of the selected sample.

Determining possible sources of bias

Bias can be introduced in a study due to many factors, such as improper selection of participants, data collection methods, or respondents' behavior. Here, it's not clear whether there are any obvious sources of bias as insufficient information is provided in the question.

Key concepts

Population of Interest

Understanding the population of interest is crucial in any study, as it defines the group whose characteristics researchers wish to understand. In the provided example, the population of interest is 'all American women.' This is an expansive group characterized by a high degree of variability in terms of age, race, geography, socio-economic status, and health behaviors, among other factors.

When researchers focus on a population of this scale, it's important to define specific characteristics that relate to the study. Since the study is examining the impact of physical activity in teenage years on cognitive impairment later in life, defining the population of interest with more precision—such as age range or health status—could enhance the relevance and applicability of the findings to target groups.

Sample Selection

Sample selection refers to how researchers choose individuals from the population of interest to participate in a study. Ideally, this process is systematic and follows specific criteria to ensure that the sample represents the broader population. However, the exercise indicates that the study included women over 50 from only four states (Maryland, Minnesota, Oregon, and Pennsylvania), and it's unclear how these women were selected.

It would be essential to use a selection method that does not exclude certain groups or introduce bias, such as random sampling or stratified sampling. This ensures that the sample is varied enough to support generalizations about the entire population. The lack of detail on the selection mechanism in the study is a concern for the validity of its conclusions.

Representativeness of Sample

The representativeness of a sample is a measure of how well it reflects the characteristics of the population of interest. If the sample contains a proportional mix of the population's characteristics, the findings can be more confidently generalized.

In this study, without explicit detail on the demography or the selection mechanics of the sample, one cannot ascertain representativeness with confidence. Factors such as geographical diversity, age distribution, and socio-economic backgrounds play a significant role in ensuring that the selected sample is a small, yet accurate picture of the whole population. To improve representativeness, researchers might have considered including women from a wider range of states or ensuring that the sample mirrored the demographic makeup of all American women.

Sources of Bias

Sources of bias can significantly skew research results and conclusions. Bias can arise at different stages of a study, from the way the sample is selected, how data is collected, to the way respondents interpret and answer questions.

In the study regarding physical activity and cognitive impairment, potential sources of bias could include the self-reporting nature of the women's physical activity, recollection bias concerning past physical activity levels, or selection bias if the women participating in the study were more health-conscious or motivated to partake in such studies. An improvement to the study might involve corroborating self-reported activity levels with historical records or using objective measurements of cognitive impairment to ensure that the findings are as accurate as possible.