Reading a research article can be intimidating, especially if it is about an unfamiliar topic, is scientifically complex, and/or contains a lot of numerical values that reveal the findings of the research, but are difficult to make sense of. Consequently, people often find themselves only reading the abstract and/or the conclusion of research papers.

Although a lot of information about research can be gleaned with this approach, some of the most important pieces go unnoticed, such as key findings, pros and cons, and applications of the research. Further, reading an entire research article gives you the opportunity to critically analyze the hypotheses, experimental design, data analyses, and conclusions.

To help make reading research articles less intimidating and a more productive and rich experience, it helps to know what key factors to look for in each section of the paper. It is also crucial to pick research articles that come from credible sources (i.e. peer-reviewed articles and journals that have high impact factors). Papers from credible sources go through rigorous evaluations by experts in a given field before they can be published. It can take years for researchers to get published, which means it can take researchers years of redesigning experiments, rethinking hypotheses, reanalyzing data, collecting more data, and/or building a stronger argument for the research to begin and ultimately be accepted among their peers. As a reader of these types of articles, your job becomes an easier one, thanks to all their hard work beforehand! Not to say that all peer-reviewed articles are perfect, but they most often convey a higher quality of academic research and critical thinking than those articles that have not been peer-reviewed or published in journal with a low impact factor.

You probably have already seen that most research papers contain 5 research-based sections: the Abstract, Introduction, Methods, Results, and Discussion. Again, understanding what each section entails and what it is meant to convey, can help you tackle a paper more quickly and efficiently.

1) The Abstract provides an overall summary of the paper. Basically, an abstract is the summation of the entire research articles sometimes in as little as 250 words. This is another reason, it is important not to rely on the information in the abstract alone. This section is best used to get a taste of the research and to determine whether or not the article is relevant to your needs.

2) The Introduction provides a background review of literature that supports the reason(s) for the research hypotheses. The researcher may use the introduction to reveal a gap in the literature that she/he intends to fill, or to set the stage for disputing past research. A good introduction will tell you why the research is being done and define the specific research hypotheses. Highlighting the hypotheses of the paper is useful and will help you critically analyze the remaining sections of the paper. This section is also very useful for finding other sources to explore!

3) The Methods provides detailed information about how each experiment was designed to test each hypothesis that was presented to you in the Introduction, and what types of statistical analyses were used to test the collected data. Common statistical software used to analyze data are SPSS, PASW, R, NVivo, and Excel. Instruments that were used to test materials, for example a GC-MS or HPLC will also be noted. This section is written in a way that you or I could easily reproduce each experiment and the data analyses, so don't be surprised at the level of detail you will find.

Even with all that detail, there can be a number of experimental designs to test one hypothesis. Peers will very critically review the Methods because ultimately, the experimental designs, the number of replications, how the data were collected, the types of data (quantitative [numbers] or qualitative [text]) collected, and the types of statistics used to analyze the data make up the backbone and validity of all research. General assumptions around the Methods section are that more replications (a minimum of 10) of the experiment produce more accurate results and that parametric statistical tests (require interval or ratio data to run) are more powerful than non-parametric tests (require nominal or ordinal data to run).

Delving into a researchers' methodologies may help you to better appreciate their interpretation of the findings. Methods are also useful models to develop your own experiments if you'd like to conduct similar research.

4) The Results provides you with results of statistical analyses of the collected data, and other results which can come in different forms such as chemical profiles, mass spectra, and graphs. Again, each hypothesis should correspond to each experiment which should correspond to a specific analytic result.

This section can become overwhelming as a result of many numbers, so focus on some key values that are the result of the data collected - bear in mind that each experiment was designed to test a hypothesis presented to you in the Introduction, and Methods sections.

Values to pay closer attention to are the mean, standard deviation, confidence interval, and the p-value. A p-value determines how well the sample data support the argument that a null hypothesis is true. A null hypothesis is that there is no difference between two samples (e.g. 0=0). If there is a difference between two samples (e.g. 0≠0), this is considered the alternative hypothesis, or what you hope to be true!

A p-value of < 0.05 will tell you that the results were significant, or in other words, that there is a difference between two samples (alternative hypothesis accepted). A p-value of > 0.05 indicates that the results were insignificant, or in other words, that there is no difference between the two samples (null hypothesis accepted). Highlighting p-values can be a quick way to analyze whether the researchers hypotheses were accepted (true) or not accepted (not true). And it's important to note that even when a finding doesn't support a hypothesis, it is still a valid and equally important finding.

Graphs are also useful in this section. Typically they represent means, confidence intervals, standard deviations and trends in a way that is much easier to understand. When given a choice to read the results or see a corresponding graph, mass spectra, or chemical profile, save yourself time and review these types of figures first!

5) And not to worry, if some of the results still don't make sense, you might find your answers in the Discussion section, also known as the Conclusion or Summary section. This section links supporting results to the Introduction and will provide further explanation as to why unsupported hypotheses were likely not found to be true. Researchers will also discuss where the research could be improved, how it can be applied, how the findings may differ from other research, and what implications it has on future research.

And if you still are left with many questions, or want to work on future projects with the researcher(s), you'll want to email the corresponding author of the article. Authors, their contact information, and affiliate institutions are identified either numerically or alphabetically. Corresponding authors may also be denoted with an asterisk*.