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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 9000 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/WileyCDA/PressRelease/pressReleaseId-77637.html, retrieved September 25,2016 ) 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 1.4 and 1.5 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?

Step by step solution

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a. Population of interest

The population of interest is women over 50 years old, as the study aims to examine the relationship between teenage physical activity and cognitive impairment in later life for these women.

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b. Sample selection

The sample for this study consisted of more than 9000 women over 50 years old from Maryland, Minnesota, Oregon, and Pennsylvania. The information given does not specify how the sample was selected, so it is difficult to determine if the method was reasonable or not. However, given the large number of participants, it is plausible that the sample could potentially provide meaningful insights on the topic of interest, although the method of selection could influence the representativeness of the sample.

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c. Representativeness of the sample

We know that the sample consists of women over 50 years old from four different states in the United States. While this might seem geographically diverse, it is essential to consider that the sample is only drawn from these specific states due to the study's design. Therefore, the sample may not be fully representative of the population of interest, which should include women aged 50 and above from all across the country, if not also from other countries. Additionally, the ethnicity, socioeconomic background, and other factors are not considered in this description, so there could be variability in the representativeness of this particular sample.

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d. Sources of bias

There can be several sources of bias in this study: 1. Recall bias: As the participants were asked about their physical activity as teenagers, there is a possibility of recall bias. Participants may unintentionally misreport or forget details about their physical activity levels in their teenage years. 2. Selection bias: As mentioned earlier, the method how the sample was selected is unclear, and drawing a sample only from four specific states in the United States could lead to a selection bias, limiting the study's generalizability. 3. Confounding factors: There may be other factors that are not considered in this study, which could influence both physical activity and cognitive impairment (e.g., genetics, socioeconomic status, nutrition, or educational background). If these factors are not accounted for in the study, they could introduce bias in the results. 4. Generalizing to the entire population: The press release generalized the study results to all American women, which might be misleading as the sample for this study may not be fully representative of the entire population.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Population of Interest

In any observational study, the population of interest represents the broader group that the researchers aim to draw conclusions about. In this specific research about teenage physical activity and its impact on cognitive health, the population of interest is women over 50 years old. This group is crucial since the research focuses on examining how physical activity at an earlier age might influence cognitive decline in later years.
Understanding the correct population of interest is essential, as it defines the scope and relevance of the conclusions drawn from the study. It dictates who the findings are applicable to and helps in ensuring the outcomes are significant for a specific demographic, in this case, older women.

Sample Selection

Sample selection is the process used to choose individuals or groups from the broader population to participate in the study. In this case, the study utilized over 9000 women over 50 years old from a few specific states like Maryland, Minnesota, Oregon, and Pennsylvania. The large sample size is a strength, as it can help reduce random errors and provide more reliable results, but the method of selection is not detailed.
Without knowing the exact method of selection, it's challenging to assess how well the sample represents the broader population of interest. Ideally, a sample should be selected randomly and should include participants from various backgrounds to avoid any skewness in the data.

• **Diverse Sampling**: Should have participants from various geographical locations and cultures.
• **Random Selection**: Increases chances of getting a sample that accurately represents the whole population.

Bias in Studies

Bias occurs when there are systematic errors that can lead to conclusions that are not representative of the entire population. In this study, several layers of potential bias could affect the outcome.
**Recall Bias:** Remembering past behaviors, such as teenage physical activity, can be problematic. Memories fade or distort over time, especially when decades have passed.
**Selection Bias:** Drawing the sample only from four states presents a risk. It might result in data that does not generalize well to all women across America. For instance, cultural and lifestyle variances could affect the results.
**Confounding Factors:** These are external factors that might influence both the independent and dependent variables. Such as nutrition, socioeconomic status, or genetics, which if not controlled for, could mislead the study's results.

Representativeness of Sample

The representativeness of a sample refers to how well the sample mirrors the population of interest. The sample should ideally reflect the diversity of the target group in terms of demographics, geography, and other relevant factors.
In the context of this study, the representativeness is questionable due to a few factors. Firstly, involving women from only four states of the U.S. might not capture some significant variables present in the entire country or globally. There could be cultural, economic, or environmental differences that have an impact on the lifestyle and, consequently, the study's outcomes.
Ensuring representativeness generally involves:

• **Multiple Locations**: Drawing samples from different geographic areas increases diversity and representativeness.
• **Diverse Demographics**: Involving individuals from different age groups, ethnicities, and economic backgrounds.
• **Avoiding Overrepresentation**: Ensuring one particular group within the population does not dominate the sample, which can skew results.

Hence, these factors should be considered and addressed to make robust and applicable generalizations from the study's findings.