2007-08 Competition Information

The deadline for the 2007-08 YES Competition has passed!

Deadline to register and submit your project for the 2008-09 YES Competition is February 2, 2009, 9 a.m. ET.

YES National Event, Washington D.C., April 17-20, 2009

About Your Research Project

YES research projects should shed light on a health problem, using the methods that are employed by epidemiologists. To accomplish that, your YES research project should do the following things:

1. Clearly state a question or hypothesis about a health problem concerning a clearly defined group of people
2. Select an appropriate study design
3. Obtain and analyze data related to your question or hypothesis
4. Present results that either answer your original question or contribute to what is known in that area
5. Suggest potential ways to improve people's health, based on the results of your examination of the data

The following guidelines will 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.

What Kinds of Health Problems Should I 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?
• How and where you obtained the food?
• Who else might have eaten the food?
• What groups of people (such as children, the elderly or people with weakened immune systems) are most severely threatened by the illness?
• How should people at risk could be notified and treated if necessary?
• How did the food became tainted in the first place?
• What steps could be taken to prevent other people from eating tainted food?

When many people hear the term "epidemic," they immediately think of the rapid spread of infectious diseases like SARS, West Nile Virus, or HIV/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)

I've Identified a Problem — Now What?

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 you will obtain the information — the data — that you will analyze to answer your question. There are different types of study designs — several are described below.

I. Descriptive Study

Your first step might be to accurately describe the problem. A descriptive study answers the question, "Is a health problem important in a particular group of people?" You might choose for example to focus on the population of high school students at your school - that would be your population of interest. 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 ages, genders, 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.

II. Analytic Studies

Analytic studies answer the question: "What is the relationship between a potential causal factor and a health problem?" Factors may be exposures (sunlight, smoky rooms), behaviors (exercise, eating habits), or characteristics (obesity, immigrant status). An analytic study investigates the relationships between potential causal factors and health outcomes. A causal factor may increase the health outcome (a risk factor) or decrease the health outcome (a 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 common sense plus other knowledge about differences in the two populations, a researcher could hypothesize about possible factors that might affect the infant death rate, and design an analytic study. 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.

II. a) 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 a cross-sectional 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, or a cohort, is gathered and their baseline characteristics are collected. Later, during a second data collection time, information on whether or not the individuals in the cohort experienced the outcome is gathered. For example, high school athletes might answer questions on risk factors at the beginning of a season, and would answer questions on the outcome, such as whether or not they experienced head injuries, at the end of the season. Finally, a third type of observational study is a case-control study. In case control studies, people who have already experienced the outcome, the "cases", are identified. A similar group of people who did NOT experience the outcome, the "controls", are also identified. Then information on risk factors or exposures that the study participants experienced over some period of time prior to the 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 vs. a group that did not have that factor. You also want to know the direction of that relationship, that is, does the factor increase or decrease the likelihood of the outcome? Finally, you want to know the strength of the relationship between the factor and the 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 on your data. It is very helpful to graph your basic data first, and 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.

II. b) Experimental Exposures and Interventions

Another way to investigate a possible cause or possible preventive or therapeutic methods for a health problem is to test interventions to see if they affect the frequency of an 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 "controls" the conditions that subjects are exposed to. 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 the other lunch period, and determine whether students receiving nutritional information made better food choices. You also might study how the effect of the exposure is modified by other factors.

Other times epidemiologists study the effects of what are called "natural experiments". In these situations, the researcher does "control" the exposure that happens to one group of subjects but not the others. 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 the following time period. In natural experiments, however, the researcher cannot control the assignment of the intervention to the subjects, and also cannot control other factors that may influence the outcome.

Data Collection

The data you collect and analyze for your YES research project may be obtained from primary and/or secondary data sources. Your decision to use primary or secondary data will depend 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. Also included are a number of links to other resources to help you with your research project. See links to epi resources.

Primary data means information collected directly by the researcher (i.e., you) by interacting with the people being studied (your study subjects). This information could 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 the guidelines for this with your mentor, because there are certain confidentiality and safety requirements that must be followed by all researchers.

Secondary data is information collected by researchers and made available for use by other researchers such as yourself. 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 links to epi 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 will involve you administering questionnaires, interviews, examinations, or surveys of people, it is important that you become familiar with the processes set up to protect human subjects in research known as Institutional Review Boards.

An Institutional Review Board (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 administration, or with your mentor to review the process and check on requirements before you begin your research.

The following websites will better assist you with the IRB guidelines and process. Please review these resources; the United States Department of Health and Human Services, the National Institute of Health, or Bucknell University for additional information.

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

Plagiarism

Participants must be the author of their own submissions; co-authored reports will not be considered eligible. All projects must be your original work.

Plagiarism is defined as the use of another person's words or ideas as if they were your own. Plagiarism or the fabrication or falsification of data will not be tolerated and will lead to immediate disqualification from the competition.

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