Especially for non-scientists: 4 tips to help understand scientific research papers

By: Camila Almeida, CHAMP staff *

Public interest in evidence-based information has been increasing over the years, and the COVID-19 global pandemic has certainly fueled this growth. Scientific papers aren’t the easiest pieces of information to read. They’re often full of jargon and acronyms, and science writers don’t have a lay audience in mind when writing them. Yet, I want to encourage you to look for science papers of your interest and gather information directly from them. Meanwhile, read on to learn about the structure of a research paper and some helpful tips for non-scientists to find the information they’re looking for.

To help you understand the components of a research paper, a hypothetical study conducted by Dr. Fit and his research team will serve as our example. Their “study” investigated the effect of sleep on physical performance. Let’s say while conducting an online search using the keywords “sleep” and “physical performance,” you come across Dr. Fit’s published article. So, what should you look for when reading his paper?

1.      Find the right info in the right place.

All research papers contain four main sections: introduction, materials and methods, results, and discussion.

The Introduction starts by stating the research topic and what’s known about it. Next, the writer describes the knowledge gap or what’s unknown about the topic. On the last paragraph in this section, you can find the main objective of the research study.

Next comes the Materials & Methods section that provides a detailed overview of what was done. Researchers usually write this section so others can do exactly what they did and (hopefully) find similar results. Since you’re not likely planning to reproduce the study yourself, don’t worry about understanding every single detail in this section.

Results, as the name suggests, is the section that summarizes the main findings of the study and highlights what the data show. We’ll cover more about this later in “big-picture trends.”

Lastly comes the Discussion section where the author describes how the results answer the research question and why it matters.

Now that you know the overall organization of a research paper and where to find each piece of information, let’s go over the important information you should care about.

Research question

When reading a research paper, the first thing you need to determine is whether the study proposes to answer a question that’s of your interest. In our example, Dr. Fit and his team investigated the impact of sleep on the PFT score. A well-written manuscript usually provides this information in the last paragraph of the introduction. Look for the phrase “the objective (goal or aim) of the study was to…” After you find this information, ask yourself if the research question is interesting—and whether you want to find the answer to it.

Study design

The experimental design outlines what Dr. Fit did, out of many possibilities, to answer his research question. For example, one approach would include having Military Service Members complete a survey answering how many hours they slept the previous night and then record their PFT score. In a more complex experimental design, Dr. Fit could randomly assign participants to two different groups: One group sleeps for 4 hours and the other group sleeps for 8 hours. The next day, Dr. Fit would record PFT scores for all participants. Either way, Dr. Fit would have data to assess the relationship between Warfighters’ sleep and physical performance.

Several study designs are available to allow researchers to appropriately answer different research questions. Although explaining them in detail is beyond the scope of this blog, two examples can help you understand the importance of carefully choosing the best study design. Randomized double-blind placebo-controlled trials are the gold standard for studies investigating the effectiveness and safety of interventions.

·    Randomization guarantees that participants are assigned to a treatment group by chance.

·    Placebo-controlled means one group in the study will receive a treatment that’s expected to have no effect.

·    Double-blind means the researchers and the participants are unaware (blind) to the treatment each person will receive.

This way, a study is designed to minimize essential differences between groups and investigators’ biases when analyzing the results. Other study designs are available for studies with different research questions. For example, if a research team wants to investigate the risk factors for musculoskeletal injury (MSKI) throughout a Military Service Member’s career, the best design would be a longitudinal prospective study. Prospective means that participants are selected before any injury occurs, and longitudinal suggests that they’ll be followed periodically through a long period, during which injuries might or might not occur. At the end of the study, researchers investigate the common factors that contributed to MSKI in this population.

Sample size

Sample size is simply the number of participants (or animals) included in the study. In general, we can say the larger the sample size, the more “power” a researcher has to draw conclusions based on the data. In other words, data from studies with a small sample size might not be representative of a larger population. A small number of participants in a given study shouldn’t prevent you from reading a manuscript. Also, don’t assume that studies with few participants lack quality. Just keep in mind that a study with 20 participants can yield completely different results if it included 2,000 participants. The difference in sample size often explains why studies reach different conclusions when trying to answer the same or similar questions.

Big-picture trends

When reading the Results section, don’t try to understand every single detail. It can be quite confusing trying to figure out the meaning of all coefficients and acronyms used in this section. Rather, look for the big picture. Check if the authors described relationships between variables and overall trends in the data. In our example study, Dr. Fit would write a sentence similar to “the number of hours slept positively correlated with the PFT score,” which means that the more the participants slept, the better they performed in the test. If the paper has figures and tables, read them and their legends. “A picture is worth a thousand words” also applies to science.

When reading the Results section, keep in mind that correlation doesn’t imply causation. This is probably the most important advice contained in this blog. Back to our example: The sentence “the number of hours slept positively correlated with the PFT score” doesn’t convey the message that sleeping long hours always leads to high PFT scores. The opposite is also not true; a few hours of sleep doesn’t guarantee a low PFT score. Correlation is simply a relationship between sleep and PFT score. Causation establishes that sleeping longer causes a high PFT score.

Take-home message

We finally get to the most exciting part of a manuscript: the Discussion section and the take-home message it conveys. This section is worth reading in its entirety. Right at the beginning of the discussion you should find a sentence that clearly summarizes the study findings and answers the research question. “We found that lack of sleep negatively affects performance in the PFT” would likely be found in the first paragraph of the discussion in Dr. Fit’s manuscript.

The development of the discussion doesn’t follow a rigid structure, but you can expect that the authors will explain their finding. For example, Dr. Fit would use data from other studies to try to explain why participants who slept few hours performed poorly on their PFT. He would also compare his findings to those from other studies that also investigate the relationship between sleep and physical performance. The discussion is also the place to wonder why similar studies resulted in opposing findings. Authors also anticipate questions that the readers might have and discuss the limitations of the study, which can include small sample size, high drop-out rate, unexpected results, and technical difficulties, among others.

The last paragraph of the discussion provides the concluding outlines and restates why it’s important to care about the data generated by the study. For example, “Because findings from this and other studies support the conclusion that sleep deprivation has a negative effect on physical performance, people should seek to implement healthy behaviors that promote adequate sleep in their daily lives” would likely be in Dr. Fit’s paper. If you don’t have much time or are just trying to get the take-home message of a study, the first and last paragraphs of the discussion will give you that information.

2.      Understand “peer review.”

Another area to pay attention to is where Dr. Fit published his results. Scientific data are usually published in peer-reviewed journals. As the name implies, studies published in these journals are reviewed by at least two other experts in the field before publication. During the peer-review process, referees judge the study and provide recommendation for publication: accept, reject, or revise. The peer-review process always results in better and more reliable papers. At the end, the authors aren’t the only ones judging the appropriateness of the study design, methods, results, and conclusions. A typical comment to receive from a referee is “your results do not support your conclusions,” and then the authors need to tone down their excitement about the data.

Self-publishing is another way a researcher has to share their data, and this practice has been growing even in academia. Since no one else judges a self-published study, the chances of inappropriate data analysis and conclusions are higher. This happens not because scientists lack ethic in their work, but because they’re usually excited about their data and might draw conclusions beyond what the data really show. Self-published articles are often found on platforms such as, ResearchGate, and Mendeley. You’re always welcome to read self-published manuscripts, but be aware of their limitations.

A quick way to check whether a journal employs the peer-review process is by going to the journal website and looking for the “About” section—this information should be in there.

3.      Is this consistent with other studies?

Before you assume that the conclusion of a study represents the general truth about the topic, you’ll want to find additional studies supporting the same conclusions; the more papers you find, the better. If Dr. Fit’s study was the only one showing that sleep affects physical performance, no one would be able to state that as a fact. We know that this is true because the relationship between sleep and physical performance has been confirmed for Military Service Members, civilians, men, women, different ethnicities and age groups, and using different physical performance tests.

4.      Use the citation index.

Finally, check if other scientists are using this study as a source of information. Some analytical tools count every time a study is cited by another publication. Both Google Scholar and PubMed provide this information for every article indexed in their database. There’s no cutoff for what would be a good number of citations, but a paper that was published 10 years ago and has only been cited 5 times, for example, didn’t spark much interest within the scientific community.

I hope you feel more confident about reading and gathering information directly from science papers. As always, feel free to reach out to HPRC’s team of experts to ask questions and get answers. We’re here to help and serve you. Happy reading!

Camila Almeida is a Staff Scientist for the Consortium for Health and Military Performance (CHAMP) at the Uniformed Services University of the Health Sciences (USU). She has a PhD in neuroscience and is particularly interested in understanding the brain mechanisms responsible for cognitive and mental performance.

* The opinions and assertions expressed herein are those of the author and do not necessarily reflect the official policy or position of USU or DoD. The contents of this publication are the sole responsibility of the author and do not necessarily reflect the views, opinions, or policies of The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. Government. The author has no financial interests or relationships to disclose.