Waiting
Login processing...

Trial ends in Request Full Access Tell Your Colleague About Jove
JoVE Science Education
Experimental Psychology

This content is Free Access.

Subtitles
 

The Simple Experiment: Two-group Design

Overview

Source: Laboratories of Gary Lewandowski, Dave Strohmetz, and Natalie Ciarocco—Monmouth University

A two-group design is the simplest way to establish a cause-effect relationship between two variables. This video demonstrates a simple experiment (two-group design).  In providing an overview of how a researcher conducts a simple experiment (two-group design), this video shows viewers the process of turning ideas into testable ideas and forming hypothesis, the identification and effect of experiment variables, the formation of experimental conditions and controls, the process of conducting the study, the collection of results, and the consideration their implications. This research technique is demonstration in the context of answering the research question: “How does physiological arousal/excitement influence perceived attraction?”

Procedure

1. Introduction of topic/research question

  1. Research question: All research seeks to answer questions. Often those questions start out fairly broad (e.g., What leads to attraction?). The researcher then forms a hypothesis based on educated guesses about potential answers.
  2. Research hypothesis: Those who are experiencing high excitement will see others as more attractive than those who are experiencing low excitement.

2. Key variables

  1. Variable = anything that changes in a study
  2. Independent variable = the cause or what the researcher manipulates/changes in order to detect changes in the participant
    1. Based on the hypothesis, excitement is the independent variable.
  3. Dependent variable = the effect or the outcome that the researcher measures in the participant.
    1. Based on the hypothesis, perceived attractiveness is the dependent variable.

3. Defining the variables

  1. To manipulate the independent variable of excitement, have participants run on a treadmill.
  2. To measure the dependent variable of perceived attractiveness, show participants pictures.

4. Establishing conditions

  1. Experimental condition = The group that receives the key ingredient, or whatever the researcher believes will have the most influence on the outcome.   
    1. Ethical consideration: In using a manipulation that requires physical effort such as this, the researcher must be mindful of the pertinent ethical considerations (i.e., people should be in shape and cannot have them run too hard to too long)
  2. Control condition = The condition that does not have the key ingredient. This group serves as the baseline for comparison.  

5. Experimental control

  1. What it is: Keeping everything exactly identical across conditions except for the key piece that the researcher wants to manipulate/change
  2. It’s importance: This is the only way a researcher can isolate which piece or factor is responsible for the changes in the dependent variable.
  3. Application to study: In the present study the researcher wants to focus on how excitement/arousal influences attraction. As such, excitement/arousal should be the only piece that changes between conditions. Thus, if the experimental group (high arousal) runs on a treadmill at 6mph for 3 minutes in a lab, the control group should be as similar as possible. They should be on a treadmill in lab for 3 minutes, but should walk at 3mph.

6. Measuring the dependent variable (attraction)

  1. Use of pictures
    1. Key measurement considerations: shouldn’t be too attractive or unattractive, shouldn’t have piercings/tattoos; and should just be head shot
    2. 7-point Likert Scale: 1 = extremely unattractive; 7 = extremely attractive

7. Procedure/conducting the study

  1. Informed consent
    1. Tell participants: “Here is the informed consent, which outlines what the study is basically about, any risks/benefits of participation, and lets you know that you are free to quit at any time.” 
  2. Random assignment to condition
    1. Randomly order the packets so that the participant’s condition (running or walking) is not based on anything other than chance. Otherwise, the researcher may subconsciously be more likely to assign certain participants (e.g., those who look physically fit) to certain conditions (e.g., running). 
  3. Running the study: Experimental condition
    1. Set treadmill to 6 mph, explain to the participant what they need to do, and start the timer for 3 min.
    2. Show participants a series of pictures and ask them to rate on provided scale (1 = not at all attractive through 7 = extremely attractive).
  4. Running the study: Control condition
    1. Set treadmill to 3 mph, explain to the participant what they need to do, and start the timer for 3 min.
    2. Show participants a series of pictures and ask them to rate on provided scale (1 = not at all attractive through 7 = extremely attractive).
  5. Debriefing
    1. Explain the purpose of the study to the participant: “Thank you for participating. In this study I was trying to determine if excitement or arousal from exercise would lead participants to find a picture more attractive. To manipulate excitement/arousal there were two conditions; running vs. walking on the treadmill. Do you have any questions?”

Experimental design is the process by which a researcher plans a study. A two-group design is the simplest way to establish a cause-effect relationship between two variables.

Here, a two-group experimental design is used to answer the research question: “How does physiological arousal in the form of exercise influence perceived attraction? In other words, are people more attractive to you after a workout?”

This video demonstrates the process of turning concepts into testable ideas and forming hypotheses, how to design experimental conditions and controls as well as how to identify experimental variables, how to execute the study, and finally, analysis of the data and consideration of their implications.

All research seeks to answer questions. Often those questions start out fairly broad. The researcher then forms a hypothesis based on educated guesses about potential answers.

Here, the researcher forms the research hypothesis that those who are experiencing high excitement through exercise will see others as more attractive than those who are experiencing low excitement.

To test this hypothesis, the researcher organizes two groups of people: an experimental group and a control group. The experimental group is the one that receives the treatment, which in the case of today’s experiment is running on a treadmill. The treatment is the key ingredient that the researcher believes will influence the outcome.

The control group does not have the key ingredient. This group serves as the baseline for comparison. In the control group, everything must be kept exactly identical to the experimental group except for that key ingredient that the researcher wants to manipulate.

In the present study, the researcher wants to focus on how physical excitement influences attraction. As such, physical excitement should be the only piece that changes between experimental and control groups. Therefore, the control group will walk on the same treadmill for the same amount of time that the experimental group will run on the treadmill, in order to remove the excited state from the condition.

Now, consider the variables, which are things that change within the experiment. In a cause and effect scenario, the cause, or the condition manipulated to detect changes, is called the independent variable. The effect, or the outcome that the researcher measures, is called the dependent variable.

Based on the hypothesis, excitement is the independent variable and perceived attractiveness is the dependent variable.

As we’ve mentioned, in order to manipulate the independent variable of physical arousal, the experimental group will run on a treadmill.

Including a control group is the only way the researcher can determine if changing the independent variable is responsible for the observed changes in the dependent variable.

To measure the dependent variable of perceived attractiveness, participants in both groups will view pictures. It is important to consider factors that could complicate interpretation of the results. For example, in this case the subject in the picture shouldn’t have piercings or tattoos, and should only include the head.

Here, perceived attraction is quantified through use of the 7-point Likert Scale, where 1 is designated as “Extremely Unattractive” and 7 as “Extremely Attractive.” Now that the experimental design has been established, we can proceed to conducting the experiment.

To begin the experiment, the researcher needs to obtain the subject’s informed consent to participate in the study. The informed consent gives a synopsis of the study—any risks and benefits of participation—and lets the participant know that they are free to quit at any time.

Next, make random assignments to the groups, so that the participant’s group isn’t based on anything other than chance, and any subconscious assumptions on the part of the researcher are avoided.

To perform the experimental condition, bring the participant to the treadmill and explain to the participant what she needs to do. Then, allow the participant to set the treadmill to 6 miles per hour. When the participant begins, immediately start the timer for 3 min.

Afterwards, show the participant a series of pictures and ask her to rate on the provided scale.

For the control study, once again explain to the participant what she needs to do. Allow the participant to set the treadmill to 3 miles per hour, and start the timer for 3 min at the moment the participant begins.

The control subject then rates the attractiveness of the pictures in an identical manner to experimental group.

Following the experiment, give the subject a debriefing where the researcher explains the purpose of the study.

Researcher: Thank you for participating. In this study I was trying to determine if arousal from exercise would lead participants to find a picture of a person more attractive. To manipulate arousal there were two conditions: running vs. walking on the treadmill. Do you have any questions?

After collecting data from 122 people, a t-test was performed for independent means comparing the high arousal condition—achieved through running—to the low arousal condition—achieved through walking—to see how they influenced attraction.

The results reveal that those subjected to the high arousal condition found the pictures more attractive than those subjected to the low arousal condition.

The results of this study are similar to the famous “bridge study” performed by Donald Dutton and Arthur Aron in 1974. In this study, Dutton and Aron found that unaccompanied men who crossed a high shaky bridge were more likely to follow up with a female research assistant than other men who crossed a low sturdy bridge.

Now that you are familiar with setting up a simple experiment using two-group design, you can apply this approach to answer the specific questions of your research.

The two-group experimental design is commonly used in psychological experiments to determine a cause and effect relationship of the intervention in question.

For example, researchers used this type of experiment to determine the effectiveness of combined self-management and relaxation-breathing training for children with moderate-to-severe asthma.

In this study, the independent variable was the type of training provided to the children, and the dependent variables were made up of four physiological variables, including anxiety levels. The results revealed that a combination of self-management and relaxation-breathing training can reduce anxiety in asthmatic children.

In another study, the impact of a feeding log on breastfeeding duration and exclusivity was assessed. The experimental group completed a daily breastfeeding log while the control group did not. The log served to intervene with the participant in the self-regulation process.

The findings suggest that the breastfeeding log may be a valuable tool in self-regulating breastfeeding and promoting a longer duration of full breastfeeding.

You’ve just watched JoVE’s introduction on performing a simple experiment using two-group design. Now, you should have a good understanding of how to form a hypothesis, how to design experimental conditions and controls, as well as how to identify variables. You should also have a comprehension for how to perform a study, and how to assess the results.

And remember, considering the potential effects of arousal on attraction, a first date at the amusement park may be a better choice than a first date at a poetry reading.

Thanks for watching! 

Results

After collecting data from 122 people, a t-test for independent means was performed comparing the high arousal (running) condition to the low arousal (walking) condition to see how they influenced attraction. As shown in Figure 1, those in the running/high arousal condition, depicted with the red bar found the pictures more attractive than those in the walking/low arousal condition.

The results of this study are similar to the famous “bridge study” where researchers found that men who crossed a high shaky bridge were more attracted to a female, than other men who crossed a low sturdy bridge.1

Figure 1
Figure 1. Mean Attraction Ratings by Arousal Condition.

Applications and Summary

Considering the potential effects of arousal on attraction, it may be better to talk to someone you’re interested in while at the gym, instead of the library. It also suggests that a rock concert may be better first date than a poetry reading.

References

  1. Dutton, D. G., & Aron, A. P. Some evidence for heightened sexual attraction under conditions of high anxiety. Journal of Personality and Social Psychology. 30(4), 510-517. doi:10.1037/h0037031 (1974).

Transcript

Tags

Two-group Design Experimental Design Cause-effect Relationship Physiological Arousal Exercise Perceived Attraction Research Question Testable Ideas Hypotheses Experimental Conditions Controls Experimental Variables Data Analysis Research Hypothesis Experimental Group Control Group

Get cutting-edge science videos from JoVE sent straight to your inbox every month.

Waiting X
Simple Hit Counter