16  Explore, apply, reflect

🏢 Lab class

16.1 Lab 2 practice quiz

Here is a short, unmarked practice quiz to help you check your understanding of the key concepts we’ve covered. It’s just a few questions and is designed for your own learning.

Link to Practice Quiz

We’ll go over the answers once you’ve completed it.

16.2 Research basics activity

This activity builds on the psychological questions we generated last week:

You can also view the questions in interactive tables, where you can search by keywords and filter by research categories:

Filter by Category

Filter by Category

Filter by Category

Filter by Category

Filter by Category

Filter by Category

Goal: To practice thinking like a psychologist by taking a general question and outlining a simple research study to investigate it.

Instructions:

  1. If possible, work in a pair or a small group of up to three. Open the whiteboard from last week.

  2. Choose one question to investigate. If your chosen question is very broad (e.g., “What makes us happy?”), your first step is to narrow it down into a more specific, testable research question (e.g., “Does spending 30 minutes outdoors each day increase self-reported happiness levels?”).

  3. Open a Word document and write down your refined research question. Then, answer the following points.

    1. Study Design: Propose a simple design. Would you conduct an experimental study (where you manipulate a variable) or a correlational study (where you just measure existing variables)? Briefly explain why.
    2. Variables: What are the key variables in your design? For each one, state whether it is manipulated or measured.
    3. Operational Definitions: How would you operationally define each variable? That is, how would you turn the abstract concept into a concrete, measurable thing?
    4. Type of Claim: Based on your design, what is the strongest type of claim you could make? An association claim (that two things are related) or a causal claim (that one thing causes another)?

Class Presentation: Time permitting, we will ask some groups to briefly present their answers in class. Be prepared to share your research question and your thinking on a few of the points above.

Tip

Stuck? Ask for Help! You can ask us for guidance, or you can use Copilot. If you use Copilot, try specific prompts like “Help me operationally define ‘social anxiety’ for a survey study.” If you present your answers in class and you used Copilot, please explain how you used it and how helpful you think the answers were.

Here is a worked example to illustrate how the activity could be completed:

  • Original Question: “Does coffee make you smarter?”
  • Refined Research Question: “Does drinking one cup of coffee improve performance on a simple memory test?”
  • Design: An experiment. We manipulate coffee intake to see if it causes a change in memory.
  • Variables:
    • Caffeine Intake (coffee vs. no coffee): Manipulated
    • Memory Performance (score on test): Measured
  • Operational Definitions:
    • “Caffeine Intake” = Participants drink either a cup of standard brewed coffee or a cup of decaf coffee (placebo).
    • “Memory Performance” = The number of words (out of 20) a participant correctly recalls 5 minutes after studying a list.
  • Claim: Because this is an experiment, we could make a causal claim if the coffee group performs significantly better.

If you finish early, here are some optional questions for you to consider:

  • Validity & Reliability: What is one step you would take to improve the validity of your study (i.e., ensure you’re measuring what you intend to)? What is one step you would take to improve the reliability of your study?
  • Sampling: Who would you recruit as participants for your study? Why did you choose this group?
  • Ethics: What is one potential ethical issue you would need to consider?
Random Number Spinner

🏠 Self-study

16.3 Food for thought: Paracetamol and autism

As mentioned earlier, the coffee example was hypothetical. Here, however, is a real case with potentially serious consequences. On 22 September 2025, President Trump advised pregnant women not to take paracetamol, claiming it could increase the likelihood of their child developing autism.

To be clear, the causes of autism are complex and not fully understood. In an article in the New York Times, Alison Singer, the president of the Autism Science Foundation, noted:

Autism doesn’t have a single cause. It is the result of a complex mix of genetics and environmental factors. We know that genetic factors play the biggest role; hundreds of genes have been linked to autism, and inherited or spontaneous changes in these genes can alter brain development. Environmental factors also matter, especially during pregnancy, such as advanced parental age at conception, prematurity or low birth weight, and exposures that affect brain development, like fever or illness during pregnancy.

In fact, there could be an association with paracetamol as Brian Lee, an epidemiologist, explained in the same article:

There are a number of studies, including our 2024 study in JAMA, that showed an apparent statistical association between [paracetamol] use during pregnancy and children’s risk of autism, A.D.H.D. and intellectual disability. But association is not causation.

Note the key phrase “association is not causation”. This raises the question of whether third variables might explain both paracetamol use and increased autism risk. Alison Singer pointed out:

The key question is: Why are these pregnant women taking [paracetamol] in the first place? We know that fever during pregnancy is a risk factor for autism. So if they were taking [paracetamol], was it the fever that caused the autism or the [paracetamol]?

This illustrates how third variables can complicate causal interpretations: infections during pregnancy can cause fever, which leads women to take paracetamol, but those same infections might themselves increase the risk of autism. In other words, the observed association between paracetamol use and autism could be driven by a third variable (the infection) rather than the medication itself.

Further thought: If you were designing a study to test whether paracetamol use during pregnancy causes autism, how would you address the possibility of third variables like infections or fever?

One way to deal with third variables is to collect information about them and take them into account when analysing the data. For example, if fever or infections could be the real reason for the increased autism risk, researchers should record whether the mothers had infections during pregnancy. Then they can compare groups that are similar in terms of infections but differ in paracetamol use.

Another idea is to use a study design that reduces differences between groups, like comparing siblings where one pregnancy involved paracetamol use and the other didn’t. This helps because many other factors (like genetics) stay the same.

However, designing such studies is challenging because it’s hard to measure all possible third variables accurately, and the study would need to follow participants for years - from pregnancy through early childhood - to see whether autism develops.

This is why many studies of this type are retrospective, using data collected after the fact. But that creates another problem: mothers have to remember whether they had an infection and whether they took paracetamol during pregnancy - which is also quite challenging!

If you’re interested in the topic, I would also recommend to read the following articles:

16.4 Confirmation

Important

Please confirm you have worked through this chapter by submitting the corresponding chapter completion form on Moodle.