One of the secrets of science is to understand the language of science, and science’s primary language is the research study. Research studies allow scientists to communicate with one another and share results of their work. There are many different kinds of research and many varying fields of research, including psychology, sociology, biology, genetics, and medicine. Research can contribute findings that are instantly relevant, or inspire new research or approaches.
Scientific Research as an Ongoing Process by ArchonMagnus is licensed under CC BY-SA
These guidelines can help you identify a research study and distinguish an article that presents the findings of a research study from other types of articles.
Research studies are almost always published in peer-reviewed (scholarly) journals. The articles often contain headings similar to these: Introduction, Methods, Results, and Discussion/Conclusion (IMRaD structure).
Articles that are not research studies:
Articles that review other studies without presenting new research results are not research studies. Examples of article types that are NOT research studies include:
Individual research studies are the means of communicating scientific research. This video (1:23 minutes) will describe the purpose and content of a research article.
This video will show an example of a research article, describing its characteristics:
To test your understanding of a research article, scan through each of the articles below and make a list of reasons why each is a research article:
As you read a peer-reviewed (scholarly) article, note the method(s) used by author(s) to plan and conduct their research. There are many different kinds of research methods but they all share two objectives: to assist the researcher to design his or her research in a way that enables the research question to be answered; and to enable the researcher to conduct his or her research in a systematic manner to ensure the findings are scientifically rigorous and have genuine potential for practical application. To achieve these objectives, the researcher follows a step-wise research process.
The research process
Research involves a systematic process that focuses on being objective and gathering a multitude of information for analysis so that the researcher can come to a conclusion. This process is used in all research and evaluation projects, regardless of the research method.
Step 1. Develop the research question
Step 2. Gather information and resources (a literature review)
Step 3. Form hypotheses
Step 4. Select the research approach, also called a research design
Step 4. Select a representative study population and sample size
Step 5. Collect the data
Step 6. Interpret the data and draw conclusions
Step 7. Write and publish the report in a peer-reviewed journal
To be complete the hypothesis must include three components:
A hypothesis should be:
Examples of a hypothesis are:
Types of hypothesis
Simple hypothesis - predicts the relationship between a single independent variable (IV) and a single dependent variable (DV).
For example: Lower levels of exercise postpartum (IV) is associated with greater weight retention (DV).
Complex hypothesis - predicts the relationship between two or more independent variables, and two or more dependent variables.
For example: The implementation of an evidence based protocol for urinary incontinence (IV) will result in (DV):
Used when the researcher believes there is no relationship between two variables, or when there is inadequate theoretical or empirical information to state a research hypothesis.
Research data can be placed into two broad categories: quantitative or qualitative.
|Quantitative data are used when a researcher is trying to quantify a problem, or address the "what" or "how many" aspects of a research question. It is data that can either be counted or compared on a numeric scale. For example, it could be the number of first year students at MCC, or the ratings on a scale of 1-4 of the quality of food served at the Bighorn Cafe. This data are usually gathered using instruments, such as a questionnaire which includes a ratings scale or a thermometer to collect weather data. Statistical analysis software, such as SPSS, is often used to analyze quantitative data.
|Qualitative data describes qualities or characteristics. It is collected using questionnaires, interviews, or observation, and frequently appears in narrative form. For example, it could be notes taken during a focus group on the quality of the food at Bighorn Cafe, or responses from an open-ended questionnaire. Qualitative data may be difficult to precisely measure and analyze. The data may be in the form of descriptive words that can be examined for patterns or meaning, sometimes through the use of coding. Coding allows the researcher to categorize qualitative data to identify themes that correspond with the research questions and to perform quantitative analysis.
In this video (2:35 minutes) a research article that uses qualitative research methods is shown. The video points out how you can determine the methodology used in the article:
In this video (2:16 minutes) a research article that uses quantitative research methods is shown. The video points out how you can determine the methodology used in the article:
This chart summarizes some of the characteristics as well as differences between these two research methodologies:
|Type of Research
qualitative studies (CINAHL)
qualitative research (MEDLINE)
|subjective-involved as a participant observer
|objective - separate, observes, but doesn't participate
This page is designed to give you an understanding of different types of clinical medical studies and how they relate to each other.
Study designs can be thought of as a pyramid. Case reports are the first articles published on new topics so they make up the base of the pyramid. As we progress up the pyramid, the studies become more evidence-based and less numerous. Meta-Analyses are at the top of the pyramid because they can only be written after much other research has been done on a topic. There are many fewer of them but they offer very strong evidence.
The below links take you to a brief definition of each design along with a real-life example.
An article that describes and interprets an individual case, often written in the form of a detailed story. Case reports often describe:
Case reports are considered the lowest level of evidence, but they are also the first line of evidence, because they are where new issues and ideas emerge. This is why they form the base of our pyramid. A good case report will be clear about the importance of the observation being reported.
If multiple case reports show something similar, the next step might be a case-control study to determine if there is a relationship between the relevant variables.
- Can help in the identification of new trends or diseases
- Can help detect new drug side effects and potential uses (adverse or beneficial)
- Can help experimenters produce novel hypotheses which can be used for later testing
- Identifies rare manifestations of a disease
- Cases may not be generalizable
- Not based on systematic studies
- Causes or associations may have other explanations
- Can be seen as emphasizing the bizarre or focusing on misleading elements
This case report was published by eight physicians in New York city who had unexpectedly seen eight male patients with Kaposiâ€™s sarcoma (KS). Prior to this, KS was very rare in the U.S. and occurred primarily in the lower extremities of older patients. These cases were decades younger, had generalized KS, and a much lower rate of survival. This was before the discovery of HIV or the use of the term AIDS and this case report was one of the first published items about AIDS patients.
A study design where one or more samples (called cohorts) are followed prospectively and subsequent status evaluations with respect to a disease or outcome are conducted to determine which initial participants exposure characteristics (risk factors) are associated with it. As the study is conducted, outcome from participants in each cohort is measured and relationships with specific characteristics determined.
- Subjects in cohorts can be matched, which limits the influence of confounding variables
- Standardization of criteria/outcome is possible
- Easier and cheaper than a randomized controlled trial (RCT)
- Cohorts can be difficult to identify due to confounding variables
- No randomization, which means that imbalances in patient characteristics could exist
- Blinding/masking is difficult
- Outcome of interest could take time to occur
Lao, X., Liu, X., Deng, H., Chan, T., Ho, K., Wang, F., ... Yeoh, E. (2018). Sleep Quality, Sleep Duration, and the Risk of Coronary Heart Disease: A Prospective Cohort Study With 60,586 Adults. Journal Of Clinical Sleep Medicine, 14(1), 109-117. https://doi.org/10.5664/jcsm.6894
This prospective cohort study explored "the joint effects of sleep quality and sleep duration on the development of coronary heart disease." The study included 60,586 participants and an association was shown between increased risk of coronary heart disease and individuals who experienced short sleep duration and poor sleep quality. Long sleep duration did not demonstrate a significant association.
A study design that randomly assigns participants into an experimental group or a control group. As the study is conducted, the only expected difference between the control and experimental groups in a randomized controlled trial (RCT) is the outcome variable being studied.
- Good randomization will "wash out" any population bias
- Easier to blind/mask than observational studies
- Results can be analyzed with well known statistical tools
- Populations of participating individuals are clearly identified
- Expensive in terms of time and money
- Volunteer biases: the population that participates may not be representative of the whole
- Loss to follow-up attributed to treatment
van Der Horst, N., Smits, D., Petersen, J., Goedhart, E., & Backx, F. (2015). The preventive effect of the nordic hamstring exercise on hamstring injuries in amateur soccer players: a randomized controlled trial. The American Journal of Sports Medicine, 43(6), 1316-1323. https://doi.org/10.1177/0363546515574057
This article reports on the research investigating whether the Nordic Hamstring Exercise is effective in preventing both the incidence and severity of hamstring injuries in male amateur soccer players. Over the course of a year, there was a statistically significant reduction in the incidence of hamstring injuries in players performing the NHE, but for those injured, there was no difference in severity of injury. There was also a high level of compliance in performing the NHE in that group of players.
A document often written by a panel that provides a comprehensive review of all relevant studies on a particular clinical or health-related topic/question. The systematic review is created after reviewing and combining all the information from both published and unpublished studies (focusing on clinical trials of similar treatments) and then summarizing the findings.
- Exhaustive review of the current literature and other sources (unpublished studies, ongoing research)
- Less costly to review prior studies than to create a new study
- Less time required than conducting a new study
- Results can be generalized and extrapolated into the general population more broadly than individual studies
- More reliable and accurate than individual studies
- Considered an evidence-based resource
- Very time-consuming
- May not be easy to combine studies
Parker, H.W. and Vadiveloo, M.K. (2019). Diet quality of vegetarian diets compared with nonvegetarian diets: a systematic review. Nutrition Reviews, https://doi.org/10.1093/nutrit/nuy067
This systematic review was interested in comparing the diet quality of vegetarian and non-vegetarian diets. Twelve studies were included. Vegetarians more closely met recommendations for total fruit, whole grains, seafood and plant protein, and sodium intake. In nine of the twelve studies, vegetarians had higher overall diet quality compared to non-vegetarians. These findings may explain better health outcomes in vegetarians, but additional research is needed to remove any possible confounding variables.
A subset of systematic reviews; a method for systematically combining pertinent qualitative and quantitative study data from several selected studies to develop a single conclusion that has greater statistical power. This conclusion is statistically stronger than the analysis of any single study, due to increased numbers of subjects, greater diversity among subjects, or accumulated effects and results.
Meta-analysis would be used for the following purposes:
If the individual studies utilized randomized controlled trials (RCT), combining several selected RCT results would be the highest-level of evidence on the evidence hierarchy, followed by systematic reviews, which analyze all available studies on a topic.
- Greater statistical power
- Confirmatory data analysis
- Greater ability to extrapolate to general population affected
- Considered an evidence-based resource
- Difficult and time consuming to identify appropriate studies
- Not all studies provide adequate data for inclusion and analysis
- Requires advanced statistical techniques
- Heterogeneity of study populations
Nakamura, A., van Der Waerden, J., Melchior, M., Bolze, C., El-Khoury, F., & Pryor, L. (2019). Physical activity during pregnancy and postpartum depression: Systematic review and meta-analysis. Journal of Affective Disorders, 246, 29-41. https://doi.org/10.1016/j.jad.2018.12.009
This meta-analysis explored whether physical activity during pregnancy prevents postpartum depression. Seventeen studies were included (93,676 women) and analysis showed a "significant reduction in postpartum depression scores in women who were physically active during their pregnancies when compared with inactive women." Possible limitations or moderators of this effect include intensity and frequency of physical activity, type of physical activity, and timepoint in pregnancy (e.g. trimester).
Researchers commonly examine traits or characteristics (parameters) of populations in their studies. A population is a group of individual units with some commonality. For example, a researcher may want to study characteristics of female smokers in the United States. This would be the population being analyzed in the study, but it would be impossible to collect information from all female smokers in the U.S. Therefore, the researcher would select individuals from which to collect the data. This is called sampling. The group from which the data is drawn is a representative sample of the population the results of the study can be generalized to the population as a whole. The image below illustrates process researchers generally go through when conducting sampling.
Stage one is to define and group the population by applicable characteristics, such as demographics, consumer behavior, geographic location etc.
Stage two is to determine a sampling frame, which is a list of the actual cases from which sample will be drawn. The sampling frame must be representative of the population.
Stage three is to pick a sampling technique based on the research objectives, parameters and constraints. The below image shows the various types of sampling techniques.
Stage four is to determine a size that provides relevant data, and avoids sampling errors or biases. Note, too small a sample yields unreliable results, while an overly large sample demands a good deal of time and resources.
Stage five is to execute the sampling process.