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Successful Research Strategies

There are many components to a successful research study and many questions that researchers must consider in order to develop a relevant and viable project.  This article seeks to identify successful research strategies and to outline the process that researchers undertake.

How does a researcher find a topic?

In order to find a topic, the researcher must first identify the goal of their research.  Is it to improve or advance a program or intervention, to establish basic data on an unknown topic, or instead to test an educational innovation? Answering this broad question will help you to hone the possible topics of your study.

Oftentimes, students as well as professional researchers discover their topics in a variety of conventional and unconventional ways.  Many researchers find that their personal interests and experiences help to narrow their topic.  For students, previous classes and course material are often the source of research ideas.  Furthermore, current events in politics as wells as in academia can inspire topics for research.   Academic journals such as Health Affairs, Health Economics, and the American Journal of Bioethics can provide good material for new studies and E-resources such as Pubmed, Google Scholar and Philosopher’s Index are also good starting places.  Lastly, many research ideas are generated through dialogue—by talking with professors, fellow students and family.

What makes a good research question?

Not all research questions are good ones—in other words, not all questions can be answered through qualitative and quantitative research methodology.  A good research question needs to:

  1. “Make sense”:  In other words, you must clearly define your terms using known definitions outlined in the literature.   For example, a poor research question would be:  How do people’s lives improve after surgery?  Not only does this research question fail to specify the study population, it contains the vague term “improve”.  The researcher must specify what he/she means by this term—does it involve a physical improvement or rather an improvement in mental state?  The more specific your research question, the better.
  2. Address an important and relevant issue:  A good research question will always have relevance to the time, place, and population of the study.  For example, a study of Vitamin A deficiency in Southern India would be a poor choice as this is not a particularly significant problem in the area.  
  3. Not already have been done:  A good research study will be novel.  This means that there will be some new aspect of the study that has never before been examined.  However, this does not mean that you should avoid replicating past research.  In fact, not only is replication a good way to get a research methodology, it is how science is supposed to advance knowledge.  When replicating a pervious study, it is best to add or change one or two things to increase the novelty of the research.
  4. Be “operationalizable”:   Oftentimes, beginning researchers pose questions that cannot be operationalized, or assessed methodologically with research instruments.  From the example above, the idea of life improvement could be operationalized by a Quality of Life survey—a well known and validated research tool. In general, the more abstract the idea, the harder it is to operationalize. 
  5. Be within a reasonable scope: A good research project will be manageable in depth and breadth.  The scope will depend on the amount of time and the availability of resources you have for your study.  In general, the more focused the research question the more likely it will be a successful project.   For example, a study that seeks to identify the prevalence eye disease in a specific village is more likely to succeed than a comparable study that seeks to identify eye disease prevalence in the world population.

How do you identify study objectives and establish a hypothesis?

The objectives of your study should directly follow from the research question(s).  Study objectives should detail the exact goals of your study: what you want to measure, which questions you need answered, and what data should be collected.  These objectives will be constrained by the scope of the research question and will depend upon the stage of the research.  For example, if you are conducting a pilot study, your objectives will be different than research with a full-blown sample size.  If you are conducting a retrospective study, your objectives will revolve around describing the data collected.  In turn, your hypothesis will follow directly from your study objectives.  When formulating your hypothesis, it is important that you do not try to “prove” that your hypothesis is true.  Instead, you should seek to find evidence that it is not true.  In other words, you can never accept your hypothesis; instead you fail to reject the null (posited) hypothesis.  This is especially important when you are using statistics such as t-tests and p-values to determine significance.  

How do you create a research methodology?

When formulating your methodology, you must ask yourself, “what methods will allow me to answer my research questions?”.  For example, if you wish to assess the efficacy of an educational intervention you will need to measure the “change in knowledge”.  This lends itself to a pre-test/post-test methodology in which the research will determine the knowledge of study participants on a topic prior to the intervention and then again after the educational intervention has been implemented. However, in order to determine the actual impact of an intervention, a pre-test/post-test methodology must always be compared with a control group. For more information about this, please see the section on Assessing Behavioral Changes: The Importance of Having a Baseline For Comparison. The four points below—data collection, sampling, interviews and surveys, and analysis—must be considered when formulating methods. 

Data Collection: Several common methods in health policy and public health research are secondary data analysis and primary data collection.  Secondary data analysis involves aggregating already available data on a specific topic and manipulating it in various ways to answer your research question.  On the other hand, primary data collection involves going out into the field to conduct interviews, surveys or observations firsthand. 

Sampling:  In order to ensure the validity of data, it is extremely important that random samples be conducted whenever possible and that an appropriate sized sample is used. For more information on ensuring the validity of research, please see Research Validity.

Interviews and Surveys:  When constructing your interviews and surveys, make sure that the questions directly relate to your research questions. Furthermore, it is important that the surveys and interviews are not extremely time-consuming; try to place a 20-30 minute limit. If you will be using an interpreter, simple questions are always better.  Easily interpreted questions that avoid ambiguity will strengthen your results.  Lastly, before you decide to create your own survey, do some research to find out if a similar study has been conducted.  If so, you should avoid reinventing the wheel, and instead seek to use previous surveys and standardized measures.

Analysis: Your analysis procedure will depend on your specific study.  If you are pursuing quantitative research, you should take a statistics class or online course to learn the basics: t-tests, f-tests, chi-squares, regression analysis (linear, logistic). In qualitative research, content analysis is often used to analyze results and look for themes in data in a systematic unbiased way.  The most important thing to remember when analyzing your results is causation.  In order to assert that “X caused Y”, your study should be experimental, with control groups and random sampling procedures.  Determining causation is a difficult thing to do, and it is a common mistake to assert a cause-and-effect relationship when the study methodology does not support this assertion.

The “Iterative” Process of Research

Ultimately, the key to a successful research project lies in iteration: the process of returning again and again to your research question, methods, and data, which leads to new ideas, revisions and improvements.  It is easy to think of research as a step-by-step “1,2,3” process, but it is important to be fluid and open to change.  Oftentimes, by discussing your research project with advisers and peers you will find that new research questions need to be added, variables need to be omitted, and other changes made.  As you return again and again to your proposed study, it may begin to transform and take a different shape.  The more you examine your study methods and data from different viewpoints, the more complexity you may reveal.  This will undoubtedly lead to a stronger, better-conceptualized study.  In conclusion, there is no formula for developing a successful research study since the research process is cyclical and iterative.