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Does alerting shoppers at a grocery store regarding the healthiness (or lack thereof) of energydense snack foods change the shopping habits of overweight individuals? To answer this question, researchers randomly gave 42 overweight shoppers a recipe flyer that either contained health information or did not contain the health information. This type of intervention is referred to as priming. To determine purchases. the receipts of the participants were reviewed. Results of the study found that shoppers primed with the health- and diet-related words on the recipe bought significantly (almost \(75 \%\) ) fewer unhealthy snacks than those without the primes. (a) What is the research objective? (b) Who are the subjects? (c) Explain why blinding is not possible in this study. (d) What is the explanatory variable in the study. (e) The response variable was number of unhealthy snacks purchased. Is this quantitative or qualitative? (f) Another factor in the study was weight status (normal weight vs overweight). Suppose all the normal weight subjects were given the flyer with the prime and overweight subjects were given the flyer without the prime. Explain how confounding would play a role in the study.

Step by step solution

01

Identify the research objective

The main goal of the study is to determine if alerting shoppers about the healthiness of energy-dense snack foods can change the shopping habits of overweight individuals.

02

Determine the subjects

The subjects of the study are the 42 overweight shoppers who were given recipe flyers either with or without health information.

03

Discuss blinding in the study

Blinding is not possible in this study because the participants are aware if their flyer contains health information or not. Since they can see the flyer themselves, they are not blind to the intervention.

04

Identify the explanatory variable

The explanatory variable in the study is the presence or absence of health information in the recipe flyer given to the shoppers.

05

Determine if the response variable is quantitative or qualitative

The response variable, which is the number of unhealthy snacks purchased, is quantitative because it is a numerical measure that can be counted.

06

Explain the role of confounding

Confounding would occur if all the normal weight individuals received the flyer with the prime and the overweight individuals received the flyer without the prime. This would mix up the effect of the flyer with the effect of weight status, making it impossible to tell whether changes in shopping habits are due to the flyer or the individuals' weight status.

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Key Concepts

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

research objective

The main goal of any research is to answer a specific question or investigate an idea.
In this study, the research objective is clear: researchers want to find out if giving health information to overweight shoppers will influence their shopping habits.

This means they are looking to see whether shoppers buy fewer unhealthy snacks after being made aware of how unhealthy those snacks are.
The importance of setting a well-defined research objective can't be overstated.
It helps to guide the entire study and ensures that every step taken is laser-focused on answering that primary question.

subjects in study

Subjects in a study are the individuals or items being examined.
In this case, the subjects are the 42 overweight shoppers who received either a recipe flyer with health information or one without it.

Identifying the subjects is crucial because it helps to understand who the research applies to and can often affect how the outcomes are interpreted.
It's important to note the number of subjects as well, which in this study is a relatively small group.
Having a small group can sometimes limit the generalizability of the study findings to a broader population.

blinding in experiments

Blinding is a method used in experiments to prevent bias.
Typically, neither the participants nor the experimenters know who is receiving the treatment and who is not.

In this study, blinding isn't possible because the participants can see the flyer they receive and know if it contains health information.
When participants know if they are receiving the intervention, it changes how they may behave.
This could introduce bias, as participants might buy fewer unhealthy snacks simply because they feel they should, not necessarily because of the information on the flyer.

explanatory variable

The explanatory variable, also known as the independent variable, is what the researchers manipulate to observe its effects.
In this study, the explanatory variable is whether the recipe flyer given to shoppers contains health information or not.

This variable is important because it is the focus of the intervention. It is what the researchers want to test to see its impact on the shopping habits of overweight individuals.
By changing the content of the flyer, researchers can examine how the inclusion of health information might influence the number of unhealthy snacks purchased.

quantitative vs qualitative data

Data can be either quantitative or qualitative.
Quantitative data is numerical and can be measured or counted.
Qualitative data is descriptive and often involves characteristics or qualities.

In this exercise, the response variable is the number of unhealthy snacks purchased, which is quantitative data.
This is because the data represent counts of snacks.
Quantitative data allows for statistical analysis, which can help determine the significance of the results.
In this case, finding that shoppers bought 75% fewer unhealthy snacks indicates a strong quantitative outcome tied to the intervention.

confounding variables

A confounding variable is an outside influence that can affect the results of an experiment.
This makes it hard to determine if the observed effect is due to the explanatory variable or the confounding variable.

In the provided study, a confounding variable could be the weight status of participants if not properly randomized.
For example, if all normal weight subjects receive the flyer with health information, and all overweight subjects do not, any observed differences could be attributed to weight status rather than the flyer content.
This muddies the waters and makes it difficult to isolate the true effect of the health information. Proper randomization and careful experimental design are crucial to avoid such confounding effects.