Frequently Asked Questions about Research Research FAQs Contents: Where does the information on this website come from? What do you mean by unbiased, scientific information and well-designed studies? What is meant by uncertainty and why is it important? What is a clinical trial? What is a cohort? What is a longitudinal study? Why is some of the information on this website different from what I have heard on television or from my family members and friends? Where does the information on this website come from? The information provided on this website is based on data from professional scientific, medical and public health journals. We strive to offer unbiased, scientific information to help you make good choices about menopause treatment and disease prevention. We have done our best to summarize and highlight what is currently known based on the results of well-designed research studies and clinical trials. The information provided here represents the best scientific knowledge available to date and may change as new information is obtained. We do our best to update this website as new research results are published. This website is completely funded by the Department of Health and Human Services' (DHHS) Agency for Health Care Research and Quality (R01: HS13329). It is not funded by any pharmaceutical companies. What do you mean by unbiased, scientific information and well-designed studies? The information available about a certain topic is only reliable and trustworthy if the research conducted to collect that information was done properly. Unfortunately, not all published studies are conducted in an ideal manner, and thus we must constantly make judgments about the quality of the information available to us. Several research principles to keep in mind when interpreting data from research studies include: Control Group.  In a controlled research study, there is a group of participants (the control group) who do not receive the treatment or intervention being tested. The group that does receive the intervention (the intervention group) is then compared to the control group to illustrate what would have happened to the intervention group had they not received the intervention. Ideally, the control group should be identical to the treatment group. For example, in a clinical trial of a new drug, a control group is critical because it allows us to infer cause and effect when any changes occur in the intervention group. If, during a clinical trial, participants in both the intervention and the control groups experience headaches equally often, we can infer that the drug is not the cause of the headaches. Without the control group, we would not know whether the headaches were caused by the drug or just a coincidence. The control group is often also called the placebo group. Randomization.  In a randomized research study, the study participants are assigned to groups through an objective random process. By randomly assigning participants to groups, the researcher ensures that the groups are as similar as possible prior to the onset of the intervention being tested. If a non-random method is used to define groups, the research may be biased because the groups may have been different before the experiment began, making it difficult to interpret any difference in the groups after the intervention. Randomization does not guarantee that the groups are exactly alike, but it does minimize the chance that systematic differences exist, and the researcher can compare the groups to see if there were are substantial differences between the groups simply due to chance. Blinded and Double-blinded.  In a blinded study, the participants do not know if they will be assigned to the intervention group or the control group. Blinding is important because participants may react differently with the knowledge that they are in one group or another. For example, if participants know they are receiving an experimental drug, they may convince themselves that they feel better when they really do not. Double-blinded means that neither the participants nor the researchers know who is in the control group and who is in the intervention group. Double blinding is important when the knowledge about who is in what group might affect judgments made during the trial or how subjective outcomes are interpreted. For example, if a doctor knows that a patient is receiving a new drug, that doctor might (consciously or unconsciously) rate that patient’s symptoms as better than those of a patient whom the doctor knows is receiving a placebo. Adequate sample size.  Research studies need to enroll enough participants to be able to show that the reported effects are a result of the intervention, not of chance. The exact sample size needed depends on the question(s) that the researchers are trying to answer, so there is no clear minimum size, but generally the larger the sample size the better. A related concept is attrition or the drop-out rate. It is important to know how many participants did not complete the entire study because those participants may have left for a reason that could bias the results. For example, if everyone with severe side-effects chooses to drop-out of a clinical trial testing a new drug and only the results from the remaining participants are reported, those results will be biased, making the drug appear safer than it actually is. Funding source.  A study funded by a group with a financial or other vested interest in the outcome is not inherently flawed, and, in fact, many companies, pharmaceutical and otherwise, conduct quality research and contribute valuable information to the scientific community. However, one should always be aware of the funding source of a particular study, however, and consider how that funding relationship may have affected the results of the study and influenced the scientists involved, especially if the study was not randomized and double blinded. The list of principles above is not meant to be comprehensive and there are certainly unique issues to consider when interpreting each study. The list is meant to give you an idea of how we evaluated the results of research studies when accumulating information for this website, and also to provide you with some tools for interpreting scientific information for yourself. What is meant by uncertainty and why is it important? Whereas the information provided in this website represents the best scientific knowledge currently available, not all of the available studies were designed or conducted in an ideal manner. When interpreting the results of such studies, it is important to understand why the study design is not considered optimal. This website reports when the effect of a treatment on a specific symptom or condition is uncertain due to the quality or absence of data. Below is a list of reasons commonly used by WISDOM to explain uncertainty in research studies: Not enough data.  Example: Studies are either too few or too small to answer the research question with certainty. Poorly done study.  Example: A study that did not include a control group or did not blind participants as to whether they were in the intervention or control group. Inadequate study design to answer the questions.  Example: A study that recruited too few participants (inadequate sample size) to show a cause-effect relationship between the treatment and the reported outcome, or a study in which the participants were not followed for long enough to accurately show the effect of a treatment on a disease or symptom. Conflicting data.  Example: Studies of similar quality reporting contradictory findings. Uncertainty in generalizing reported findings due to non-standardization of dose and potential contamination.  Example: One study reports that eating 50 mg of dried ginger root reduces hot flashes while another study reports that one cup of ginger tea does not reduce hot flashes. Because of the variation in dosages and the uncertainty about ingredients included in certain mixtures or teas, it is difficult to determine the effect of ginger on hot flashes. What is a clinical trial? A clinical trial is a research study that tests the safety and effectiveness of a treatment or disease prevention method (usually medications or medical devices). Clinical trials are designed to progressively understand the overall benefit/risk relationship of a drug or device. They are conducted in a series of 4 Phases, with FDA-approval being given if the treatment is found to be safe and effective in Phase III. What is a cohort? A cohort is a group of people who are identified by researchers as sharing one or more characteristics that are important for the intended research. For example, in a study examining a new drug to reduce hot flashes, researchers might recruit a cohort of healthy women aged 45-65. What is a longitudinal study? A longitudinal study enrolls participants, then follows them forward through time. This allows researchers to examine the effect of a treatment or prevention method over time. Why is some of the information on this website different from what I have heard on television or from my family members and friends?     This website summarizes information from the scientific, medical and public health literature. Despite what you read here, you may be reluctant to try a particular treatment because someone you know has had a bad experience or, conversely, you may hope to try a new treatment because it worked so well for someone you know. Keep in mind that every person is unique in their experiences, both physical and emotional, as well as in their attitudes and perceptions. Just because a treatment worked well for one person does not mean it will work well for everyone. Scientific studies like those cited in this website use large groups of people to reach their conclusions. Although research studies can not tell us precisely how a treatment will affect every individual or for whom exactly treatment will be most effective, they provide the best indication we have of how a treatment is expected to affect most people.     In addition, keep in mind that words of discontent are often spoken more loudly than those of satisfaction. We are more likely to hear and pay attention when something goes wrong than when it goes right. For example, the media is more likely to interview a woman experiencing severe side-effects from treatment than a woman for whom treatment is working smoothly. Scientific research attempts to objectively report both positive and negative effects, and this website has been designed to allow you to weigh those effects for yourself.