Question

Recently, a group of adults who swim regularly for exercise were evaluated for depression. It turned out that these swimmers were less likely to be depressed than the general population. The researchers said the difference was statistically significant. a) What does "statistically significant" mean in this context? b) Is this an experiment or an observational study? Explain. c) News reports claimed this study proved that swimming can prevent depression. Explain why this conclusion is not justified by the study. Include an example of a possible lurking variable.

Short answer

a) It means the results are unlikely due to chance. b) Observational study. c) Cannot prove causation; possible lurking variable: more free time.

Step-by-step solution

Understanding Statistical Significance

In this context, "statistically significant" means that the difference in depression levels between the swimmers and the general population is unlikely to have occurred by random chance alone. This suggests that there is some underlying factor contributing to this difference.

Distinguishing Experiment from Observational Study

This is an observational study because the researchers did not assign individuals randomly to swim or not to swim. They observed existing behaviors and analyzed the results without manipulating any variables.

Evaluating Claims and Lurking Variables

The conclusion that swimming "proves" prevention of depression is not justified because this study is observational and cannot establish causation. For example, a possible lurking variable could be that people who swim regularly may have more free time or resources to engage in healthy activities, which could contribute to lower depression levels.

Key concepts

Observational Study

In research, it's important to distinguish between two main types of studies: experiments and observational studies. An observational study, like the one involving the group of swimmers, is where researchers simply observe and measure outcomes without trying to influence them. They don't assign participants to a treatment or control group or manipulate any variables.

In this case, the researchers observed a naturally occurring group of individuals who swim regularly and analyzed their levels of depression. By doing so, they gathered data without altering or controlling the participants’ behavior. Observational studies are common in cases where random assignment is either unethical or impractical.

One thing to keep in mind is that observational studies are valuable for finding relationships or patterns, but they don't provide direct evidence of causation.

Causation vs. Correlation

A common pitfall in interpreting research findings is confusing correlation with causation. Correlation indicates a relationship between two variables, while causation confirms that one variable directly affects the other.

In the swimming study, there is a correlation: swimmers tend to be less depressed than the general population. However, without further evidence, we can't say that swimming causes this decrease in depression. It could be that people who swim are generally healthier, happier individuals or that another variable influences both swimming habits and mood.

To establish causation, researchers would need to conduct an experiment with random assignment and control groups, ensuring that swimming is the only differing factor. Until then, we can only speak of a correlation between swimming and depression levels.

Lurking Variables

Lurking variables are hidden influences that could affect the outcomes of a study. They can muddy the waters when trying to interpret the results of observational studies.

In the scenario with the swimmers, a lurking variable might be other lifestyle factors that accompany regular swimming. For example, those who have the time and resources to swim regularly might also engage in other healthy behaviors, such as maintaining a balanced diet or having a supportive social network.

This means that the lower levels of depression observed in swimmers could be partly or entirely due to these other positive lifestyle factors. Identifying and accounting for lurking variables is crucial for making accurate interpretations of observational study results.