2009-10 Research Project Guidelines

The deadline to register and upload your project is February 1, 2010 at 9 a.m. Eastern Time.

YES National Event, Washington D.C., April, 2010

About Your Research Project

YES research projects should address a health problem in a human population using the methods that are employed by epidemiologists. To accomplish that, your YES research project should:

Clearly state a question or hypothesis about a health problem concerning a clearly defined group of people.
Make certain that the question has a health condition of a health risk factor as the outcome variable.
Select an appropriate study design.
Obtain and analyze data related to your question or hypothesis.
Present results that either answer your original question or contribute to what is known in that area.
Suggest potential ways to improve people's health based on the results of your examination of the data.

These guidelines can help you better understand the types of problems examined by epidemiologists, the methods they use to tackle these problems, and how you can make use of those methods in your project.

The Kinds of Health Problems You Can Look At

While medical doctors are primarily concerned about the health of individual people, epidemiologists are primarily concerned with the health status of groups of people or the public at large.

For example, if you go to your family doctor with a case of food poisoning, your doctor's first priority is to take immediate steps to diagnose the illness, decide on a treatment for you, and assist in your recovery. However, an epidemiologist would be interested in a number of other things, including:

What food made you ill—and might also be a risk for other people?
How and where did you get the food—can you figure out who else might have eaten the contaminated food?
Are there specific groups of people (such as children, the elderly, or those with weakened immune systems) who would be most severely affected by a food-borne illness—and should be targeted for identification and treatment?
How should people who might have been exposed be notified—and treated, if necessary?
How did the food become contaminated in the first place—and how could this be controlled for this outbreak and prevented in the future?

When many people hear the term "epidemic," they immediately think of the rapid spread of infectious diseases such as severe acute respiratory syndrome (SARS), West Nile Virus, or human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS). Epidemiologists are very much involved with tracking, controlling, and preventing such diseases, but they also are concerned with non-infectious illness and health problems, such as:

Chronic, non-infectious diseases, such as cancer, asthma, and diabetes
Disability due to illness or injury
Causes of premature death, such as automobile accidents or youth violence
Factors that put people at higher risk for developing health problems (for example, smoking or exposure to toxic waste)
Factors that make some people healthier than others, keep them from becoming ill, or help them live longer or with greater vitality than others (for example, physical activity or a balanced diet)

Once You've Identified a Problem

Now you need to figure out the question that you want to find the answer to, and design a study that can answer that question. Though not required, a mentor or advisor can be very helpful to you as you select your study design and plan how to obtain the information—the data—that you analyze to answer your question. There are different types of study designs, these include:

1. Descriptive Study

Your first step might be to accurately describe the problem. A descriptive study answers types of questions like who, what, when, where, and how big. An example would be describing the frequency (prevalence) of a specific health problem in a particular group of people, or in one group compared to another. You might choose to determine the rate of cigarette smoking in the population of high school students at your school, and compare the rates between boys and girls. A descriptive study might measure the magnitude of a health problem in a particular group of people, or describe how it differs among people of different age, gender, ethnicity, geographical location, or other factors. In other words, the study describes the patterns of health and disease in people. A descriptive study can be used to identify key areas to investigate as possible causes of illness, injury, or death. It is important for you to understand that a descriptive study is not simply a narrative essay or historical research paper, but must include data about one or more population groups.

2. Analytic Studies

An analytic study investigates the relationships between potential causal factors and health outcomes. Factors (also called independent variables) may be exposures (sunlight, smoky rooms), behaviors (exercise, eating habits), or characteristics (family history of asthma, immigrant status). A factor may be associated with an increase in the frequency of a health condition outcome (making it a possible risk factor for that health outcome) or with a decrease in the frequency of the health outcome (making it a possible protective factor). For example, descriptive studies have found that African American babies are twice as likely to die within the first year of life as white American babies. Knowing this information from a descriptive study, and then using knowledge about possible causal factors that have different likelihoods in the two populations, a researcher could test hypotheses about possible factors that could lead to this difference in death rate. As you think about possible causal factors, think about whether there is a possible mechanism that might explain how the factor could influence whether or not a health problem would occur, or in what form that problem would occur, or at what point in time. Also consider if there are other risk factors that might also contribute to the observed pattern that you might want to check into at the same time as you look at the factor you suspect is the most important determinant.

You may use observational or experimental analytic studies to explore relationships between factors and an outcome.

Observational studies

"Observational" means that the investigator uses or collects data based upon observing actions or exposures of the people in the study without manipulating their environment in any way.

One type of observational study is a cross-sectional study. In this study, the information on the exposure or risk factor is collected at the same time as information about the health outcome. Observational studies are often performed by using a survey. For example, high school athletes might answer questions on risk factors such helmet use, training, and type of sport they play, as well as questions on the outcome, such as what types of injuries and the severity of the injuries they have experienced playing different sports.
Another type of observational analytic study is a cohort study. In this type of study, a group of people—a cohort—is selected and data on baseline characteristics is collected. Later, during a second data collection time, information on whether or not the individuals in the cohort experienced the health outcome of interest is gathered. For example, high school athletes might answer questions on a survey of risk factors at the beginning of a season and then at the end of the season answer questions on a survey of one or more health outcomes, such as whether or not they experienced a head injury during the season.
A third type of observational study is a case-control study. In these studies, people who have already experienced the health outcome—the cases—are identified. A similar group of people who did not experience the health outcome—the controls—are also identified. Then information on risk factors or exposures that the study participants experienced over a period of time prior to the health outcome is collected. The histories of the cases and controls are then compared to see if they differ by suspected risk factors or other exposures. For example, high school athletes who visited an emergency room or doctor's office due to head injury could form the case group, while high school athletes who did not seek health care during the same time period could form the control group.

Once you have collected your data, how do you determine whether or not there is a relationship between a potential factor and the health outcome of interest? You want to know if the frequency or severity of a particular health outcome was different in a group that had the possible causal factor versus a group that did not have that factor. You also want to know the direction of that relationship. Does the factor increase or decrease the likelihood of the health outcome? Finally, you want to know the strength of the relationship between the factor and the health outcome. Is the relationship greater than what would be expected if the information you collected was determined by chance? In other words, is it statistically significant? The type of statistical test that you should perform on your data depends upon the question you are asking, the study design, and the kinds of data you collected. It is important to understand the basis for a statistical test to decide if it is the appropriate one to use for your study. It is very helpful to graph your basic data first, inspect the patterns you see, and start with simple statistical tests rather than moving immediately to multivariate tests. The actual calculations performed for the statistical analyses can be performed using statistical software programs such as Excel, Access, STATA, Epi Info, SPSS, and SAS.

Experimental exposures and interventions

Another way to investigate a possible cause, preventive, or therapeutic methods for a health problem is to test interventions to see if they affect the frequency of a health outcome. Testing for the effects of an intervention is similar to the classic scientific experiment in which there is a baseline state, exposure to an intervention, and then an end state, or outcome. In the case of a controlled experiment, the researchers control the conditions to which subjects are exposed. Then they compare the health status of people who received the exposure or intervention to those who did not. For example, you might post nutritional information on school lunches during one lunch period but not during another lunch period, and determine whether students receiving nutritional information made healthier food choices. You also might study how the effect of the exposure is modified by other factors.

Other times epidemiologists study the effects of natural experiments. In these situations, the researcher does not control who receives the exposure. An example might be that one state passes laws to prevent smoking in public places, but a neighboring and similar state does not. Epidemiologists can compare the rate of smoking-related diseases in the two states over a subsequent time period. In natural experiments, the researcher cannot control the assignment of the exposure or intervention to the subjects or exposure to other factors that may also influence the health outcome.

Data Collection

The data you collect and analyze for your YES research project may be obtained from both primary and secondary data sources. Your decision to use primary or secondary data depends upon your research questions and what you can realistically accomplish. No preference is given to projects using one type of data over another.

The YES website contains a number of links to data sets should you decide to explore possible secondary data sources. There are also epidemiological resources to help you.

Primary data means information collected directly by the researcher (i.e., you) by interacting with the people being studied (your study subjects). This information can be obtained through interviews, questionnaires, measurements (like weight), or by direct observation. Primary data comes straight from the source; in the case of surveys, that means straight from the participants' replies. If you choose to collect primary data, it is important that you discuss human subject protection guidelines with your mentor or school officials, because there are certain confidentiality and safety requirements that must be followed by all researchers (see below).

Secondary data is information collected by researchers and made available for use by other researchers, such as you. Many governmental agencies, academic researchers, and other organizations offer secondary data that you can analyze free of charge. Many of these same organizations also provide online interactive query functions to facilitate analysis by other researchers. Examples of secondary data include data sets available through the Centers for Disease Control and Prevention (CDC), Data2010, and the National Center for Health Statistics (NCHS). See epidemiological resources for descriptions and links to many secondary data sets that are available for your use. Many state and local public health agencies and departments of health collect health-related data and make them available to researchers and community members. If you are interested in learning more about these sources, we recommend that you contact your state or local department of health, in particular the public health surveillance office or the state epidemiologist. You also could contact one of the Prevention Research Centers in your region.

Research Involving Human Subjects

If your research project plan involves you administering questionnaires, interviews, examinations, or surveys of people, it is important that you protect the identity and personal data of the participants in your study. In your Research Report, explain how you received permission to access this personal data. Also identify who approved the use of the data in your project, for example a school administrator, human rights committee member, or other official.

When researchers use human subjects in their study that poses potential risks to subjects, they must receive approval from an Institutional Review Board (IRB). An IRB is a committee that protects the rights and welfare of human subjects, assists the researcher on ethical and procedural issues related to the use of human subjects in research, and facilitates compliance with federal regulations. Although the YES Competition does not require that you obtain IRB approval, your school or mentor's institution may require formal approval through an IRB or other process. We encourage you to work with your high school teachers and administrators, or with your mentor, to review the process and check on requirements before you begin your research.

You can find additional information about IRB guidelines and processes at:

If your research project utilizes publicly available secondary data sources, then you do not need to get IRB or other formal approval.

Academic Integrity

Academic integrity is a fundamental value of the YES Competition and scientific research. Your Research Report and presentation slides must be your original work; coauthored reports are not eligible. If you use ideas, techniques, facts, words, images, or information from other sources (including the Internet) you must ensure that these sources are properly cited. It is not sufficient to simply modify the words of an original source and claim it as your own. If you have used the essential idea, you must cite the source.

Violations of academic integrity will result in disqualification.

The YES Competition uses specific procedures as part of the judging process to detect plagiarized materials. If your Research Report is found to have improper citations or if citations are omitted, intentionally or unintentionally, you will be disqualified from the YES Competition.

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