What is quality research? A guide to identifying the key features and achieving success

George Denison



April 2023

What is quality research? A guide to identifying the key features and achieving success

George Denison



April 2023

Every researcher worth their salt strives for quality. But in research, what does quality mean?

Simply put, quality research is thorough, accurate, original and relevant. And to achieve this, you need to follow specific standards. You need to make sure your findings are reliable and valid. And when you know they're quality assured, you can share them with absolute confidence.

You’ll be able to draw accurate conclusions from your investigations and contribute to the wider body of knowledge in your field.

Importance of quality research

Quality research helps us better understand complex problems. It enables us to make decisions based on facts and evidence. And it empowers us to solve real-world issues. Without quality research, we can't advance knowledge or identify trends and patterns. We also can’t develop new theories and approaches to solving problems.

With rigorous and transparent research methods, you’ll produce reliable findings that other researchers can replicate. This leads to the development of new theories and interventions. On the other hand, low-quality research can hinder progress by producing unreliable findings that can’t be replicated, wasting resources and impeding advancements in the field.

In all cases, quality control is critical. It ensures that decisions are based on evidence rather than gut feeling or bias.

Standards for quality research

Over the years, researchers, scientists and authors have come to a consensus about the standards used to check the quality of research. Determined through empirical observation, theoretical underpinnings and philosophy of science, these include:

1. Having a well-defined research topic and a clear hypothesis

This is essential to verify that the research is focused and the results are relevant and meaningful. The research topic should be well-scoped and the hypothesis should be clearly stated and falsifiable.

For example, in a quantitative study about the effects of social media on behavior, a well-defined research topic could be, "Does the use of TikTok reduce attention span in American adolescents?"

This is good because:

  • The research topic focuses on a particular platform of social media (TikTok). And it also focuses on a specific group of people (American adolescents).
  • The research question is clear and straightforward, making it easier to design the study and collect relevant data.
  • You can test the hypothesis and a research team can evaluate it easily. This can be done through the use of various research methods, such as survey research, experiments or observational studies.
  • The hypothesis is focused on a specific outcome (the attention span). Then, this can be measured and compared to control groups or previous research studies.

2. Ensuring transparency

Transparency is crucial when conducting research. You need to be upfront about the methods you used, such as:

  • Describing how you recruited the participants.
  • How you communicated with them.
  • How they were incentivized.

You also need to explain how you analyzed the data, so other researchers can replicate your results if necessary. re-registering your study is a great way to be as transparent in your research as possible. This  involves publicly documenting your study design, methods and analysis plan before conducting the research. This reduces the risk of selective reporting and increases the credibility of your findings.

3. Using appropriate research methods

Depending on the topic, some research methods are better suited than others for collecting data. To use our TikTok example, a quantitative research approach, such as a behavioral test that measures the participants' ability to focus on tasks, might be the most appropriate.

On the other hand, for topics that require a more in-depth understanding of individuals' experiences or perspectives, a qualitative research approach, such as interviews or focus groups, might be more suitable. These methods can provide rich and detailed information that you can’t capture through quantitative data alone.

4. Assessing limitations and the possible impact of systematic bias

When you present your research, it’s important to consider how the limitations of your study could affect the result. This could be systematic bias in the sampling procedure or data analysis, for instance. Let’s say you only study a small sample of participants from one school district. This would limit the generalizability and content validity of your findings.

5. Conducting accurate reporting

This is an essential aspect of any research project. You need to be able to clearly communicate the findings and implications of your study. Also, provide citations for any claims made in your report. When you present your work, it’s vital that you describe the variables involved in your study accurately and how you measured them.

Curious to learn more? Read our Data Quality eBook.

How to identify credible research findings

To determine whether a published study is trustworthy, consider the following:

  • Peer review: If a study has been peer-reviewed by recognized experts, rest assured that it’s a reliable source of information. Peer review means that other scholars have read and verified the study before publication.
  • Researcher's qualifications: If they're an expert in the field, that’s a good sign that you can trust their findings. However, if they aren't, it doesn’t necessarily mean that the study's information is unreliable. It simply means that you should be extra cautious about accepting its conclusions as fact.
  • Study design: The design of a study can make or break its reliability. Consider factors like sample size and methodology.
  • Funding source: Studies funded by organizations with a vested interest in a particular outcome may be less credible than those funded by independent sources.
  • Statistical significance: You've heard the phrase "numbers don't lie," right? That's what statistical significance is all about. It refers to the likelihood that the results of a study occurred by chance. Results that are statistically significant are more credible.

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