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In order to assess the effectiveness of taking large doses of vitamin \(\mathrm{C}\) in reducing the duration of the common cold, researchers recruited 400 healthy volunteers from staff and students at a university. A quarter of the patients were assigned a placebo, and the rest were evenly divided between \(1 \mathrm{~g}\) Vitamin \(\mathrm{C}, 3 \mathrm{~g}\) Vitamin \(\mathrm{C},\) or \(3 \mathrm{~g}\) Vitamin \(\mathrm{C}\) plus additives to be taken at onset of a cold for the following two days. All tablets had identical appearance and packaging. The nurses who handed the prescribed pills to the patients knew which patient received which treatment, but the researchers assessing the patients when they were sick did not. No significant differences were observed in any measure of cold duration or severity between the four medication groups, and the placebo group had the shortest duration of symptoms. \(^{60}\) (a) Was this an experiment or an observational study? Why? (b) What are the explanatory and response variables in this study? (c) Were the patients blinded to their treatment? (d) Was this study double-blind? (e) Participants are ultimately able to choose whether or not to use the pills prescribed to them. We might expect that not all of them will adhere and take their pills. Does this introduce a confounding variable to the study? Explain your reasoning.

Step by step solution

01

Determine Study Type

This is an experiment because the study involves the manipulation of variables (types and doses of Vitamin C) by the researchers to observe their effect on the outcome (duration of cold symptoms).

02

Identify Variables

The explanatory variable is the type of treatment (placebo, 1g Vitamin C, 3g Vitamin C, 3g Vitamin C with additives), and the response variable is the duration or severity of the cold symptoms.

03

Assess Blinding of Participants

Yes, the patients were blinded to their treatment since all the tablets had identical appearance and packaging, preventing them from knowing which treatment they received.

04

Assess if Study was Double-Blind

Yes, this was a double-blind study because the researchers assessing the patients did not know which treatment each patient received.

05

Analyze Potential Confounding Variables

The choice of participants to not adhere to taking their prescribed pills does introduce a confounding variable, as the actual dose received could differ from the one assigned, affecting the results.

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Key Concepts

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

Blinding in Experiments

Blinding is a crucial technique used in experimental design to prevent bias. In this study, blinding was used by ensuring that the tablets for all treatments looked the same. This means neither the appearance nor the packaging gave away which treatment a participant was receiving.
The primary reason for blinding participants in an experiment is to prevent their expectations from influencing the results. If participants know what they are receiving, it might affect their behavior or perception of the treatment's effectiveness.
Here are the main types of blinding in experiments:

• Single-blind: Only the participants are unaware of which group they belong to.
• Double-blind: Both the participants and the researchers assessing the outcomes are unaware of the assignments.

In the given study, the researchers who were assessing the outcomes were also unaware of the participants' treatment groups. This setup makes the experiment double-blind, adding another layer of protection against bias.

Confounding Variables

Confounding variables are extraneous factors that can affect the results of an experiment. They make it difficult to establish a clear cause-and-effect relationship between the explanatory and response variables.
In the vitamin C study, one potential confounding variable is the adherence to pill-taking. If some participants chose not to take their assigned pills, this behavior could impact the results. Even though participants were randomly assigned treatments, their individual choices about following the prescribed regimen can introduce variability.

• For example, if those who felt less sick decided not to take the pills, it might appear that the treatment was ineffective.
• Conversely, if sicker individuals adhered strictly, it might seem more effective than it is.

To mitigate confounding variables, experiments often include randomized assignment, controls, and sometimes statistical methods to adjust for variables that cannot be controlled directly.

Explanatory and Response Variables

In an experiment, identifying the explanatory and response variables is key to understanding the relationship that the study seeks to evaluate. An explanatory variable is what researchers manipulate or vary to observe its effect. In this experiment, the explanatory variable is the type of treatment assigned — whether it was a placebo, 1g Vitamin C, 3g Vitamin C, or 3g Vitamin C with additives.
The response variable is the outcome that is measured to see how it is affected by changes in the explanatory variable. Here, it refers to the duration or severity of cold symptoms experienced by the participants.
Correctly determining these variables helps in the design of a study and the analysis of the results. Changing the explanatory variable should, ideally, lead to change in the response variable if there is a strong causal relationship. However, in the vitamin C study, no significant difference was found among treatment groups in terms of cold duration and severity.