Descriptive Research

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Descriptive Research

Jeremy Kees, Ph.D.

Descriptive Research

• Describe what is going on or exists

• Estimate how groups of consumers might behave

• Examine relationships between two or more variables

• Predict

Descriptive Research

• Two Basic Types

1. Longitudinal

2. Cross-Sectional

Descriptive Research

(Longitudinal) Example

Bates, Kenny, Kyle Huggins, Scot Burton, and Jeremy Kees (2005), “A

Supersized Diary: Weighing in on Fast Food Consumption,” In Jeff

Langenderfer, Don Lloyd Cook, and Jerome D. Williams (Eds.),

Marketing and Public Policy Proceedings , Washington, D.C., 149-50.

Background

• In a press release by the U.S. DHHS in 2001, former Surgeon

General David Satcher projected that obesity will soon overtake tobacco as the leading cause of preventable deaths.

• Over the last two decades, food dollars spent on meals prepared outside-the-home has risen from 26% to 46%, which today accounts over $400 billion annually (National Restaurant

Association 2004).

Descriptive Research

(Longitudinal) Example

Bates, Kenny, Kyle Huggins, Scot Burton, and Jeremy Kees (2005), “A

Supersized Diary: Weighing in on Fast Food Consumption,” In Jeff

Langenderfer, Don Lloyd Cook, and Jerome D. Williams (Eds.),

Marketing and Public Policy Proceedings , Washington, D.C., 149-50.

Research Questions

• How accurate are consumers’ estimates of nutrition levels (e.g., calories, fat, sodium) of the meals purchased when compared to the actual levels?

• Does obtaining the objective nutrition information about the meal change the respondents’ evaluations of healthiness, evaluations of nutrition levels, and likelihood to repurchase?

• Is there a specific segment of consumers that appear to be more at risk of long-term problems due to high dining frequency combined with large underestimation of the calories and nutrient levels that are being consumed?

Descriptive Research

(Longitudinal) Example

Bates, Kenny, Kyle Huggins, Scot Burton, and Jeremy Kees (2005), “A

Supersized Diary: Weighing in on Fast Food Consumption,” In Jeff

Langenderfer, Don Lloyd Cook, and Jerome D. Williams (Eds.),

Marketing and Public Policy Proceedings , Washington, D.C., 149-50.

Four Primary Stages of Data Collection:

1.

Seven-day diary of fast food restaurant visits (including food and drinks purchased, amount spent, and meal satisfaction).

2.

Provided estimates of calories, fat, saturated fat, and sodium levels of purchased meals, along with ratings of each meal on taste, value, overall nutritiousness, perceptions of nutrition levels, attitude toward the restaurant, and likelihood of repurchasing the same meal.

3.

Accessed restaurant website to obtain objective levels of the nutrient levels for the meals.

4.

Repeated their ratings of the meals (as in stage 2).

Descriptive Research

(Longitudinal) Example

Bates, Kenny, Kyle Huggins, Scot Burton, and Jeremy Kees (2005), “A

Supersized Diary: Weighing in on Fast Food Consumption,” In Jeff

Langenderfer, Don Lloyd Cook, and Jerome D. Williams (Eds.),

Marketing and Public Policy Proceedings , Washington, D.C., 149-50.

Sample Statistics:

• N = 155 College Students, who received course credit for participating in the study.

• 96% reported eating at least one fast food meal during the seven day period.

• Average number of meals: 3.8 (sd=2.2)

• A total of 580 dining experiences were reported.

• Males averaged 4.3 meals, females 3.3 (F=7.8, p<.01)

Descriptive Research

(Longitudinal) Example

Bates, Kenny, Kyle Huggins, Scot Burton, and Jeremy Kees (2005), “A

Supersized Diary: Weighing in on Fast Food Consumption,” In Jeff

Langenderfer, Don Lloyd Cook, and Jerome D. Williams (Eds.),

Marketing and Public Policy Proceedings , Washington, D.C., 149-50.

Results:

Descriptive Research

(Longitudinal) Example

Bates, Kenny, Kyle Huggins, Scot Burton, and Jeremy Kees (2005), “A

Supersized Diary: Weighing in on Fast Food Consumption,” In Jeff

Langenderfer, Don Lloyd Cook, and Jerome D. Williams (Eds.),

Marketing and Public Policy Proceedings , Washington, D.C., 149-50.

Results:

Differences between Estimated and Actual Calories

Actual Calories Consumed

Difference

Between

Estimate and

Actual

Calories

2000.00

1000.00

0.00

-1000.00

-2000.00

0.00

500.00

1000.00

1500.00

2000.00

2500.00

3000.00

Descriptive Research

(Longitudinal) Example

Bates, Kenny, Kyle Huggins, Scot Burton, and Jeremy Kees (2005), “A

Supersized Diary: Weighing in on Fast Food Consumption,” In Jeff

Langenderfer, Don Lloyd Cook, and Jerome D. Williams (Eds.),

Marketing and Public Policy Proceedings , Washington, D.C., 149-50.

Results:

RELATIONSHIP BETWEEN ACTUAL FAT AND DIFFERENCE BETWEEN

ESTIMATED AND ACTUAL FAT CONSUMED

150.00

100.00

50.00

Difference

Between

Estimate and

Actual Fat

0.00

-50.00

-100.00

-150.00

0 50 100

FatAct

Actual Fat of Meal

150 200

Descriptive Research

(Longitudinal) Example

Bates, Kenny, Kyle Huggins, Scot Burton, and Jeremy Kees (2005), “A

Supersized Diary: Weighing in on Fast Food Consumption,” In Jeff

Langenderfer, Don Lloyd Cook, and Jerome D. Williams (Eds.),

Marketing and Public Policy Proceedings , Washington, D.C., 149-50.

Results:

5

Calorie Level

1.00

2.00

4.5

4

3.5

3

1 2

Pre Post

Descriptive Research

(Longitudinal) Example

Bates, Kenny, Kyle Huggins, Scot Burton, and Jeremy Kees (2005), “A

Supersized Diary: Weighing in on Fast Food Consumption,” In Jeff

Langenderfer, Don Lloyd Cook, and Jerome D. Williams (Eds.),

Marketing and Public Policy Proceedings , Washington, D.C., 149-50.

Results:

Descriptive Research (Cross-

Sectional) Example

“Consideration of Future Consequences as a Moderator of Temporal Framing and Regulatory Focus in a Health Domain,” Unpublished Manuscript .

Problem

What types of appeals are effective at encouraging individuals to take a “longterm” perspective on their health behaviors (i.e., eating and exercising)?

– Initial examination of how different health-related variables differ by gender and BMI

Research Questions

• What proportion of undergraduates are under/over weight?

• What is the relationship between BMI and gender? Other variables?

• What key factors predict BMI?

• Others…

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