5 Main Factors Affecting Reproducibility in Research

Reproducibility in research

How can science go wrong? This thought often comes to researchers’ minds. When you talk to your PI about designing an experiment, your PI reminds you that it’s important to replicate the experiments and their results. You manage to plan the experiment, complete it successfully, and get the results. After analyzing these results from repeated tests, you realize that you cannot get the same results that you received the first time you did the experiment! Do you think you made a scientific mistake? Do you think there’s something wrong with your science? Great, read on to find out how reproducibility in research affects your research and how you can improve at replicating and reproducing your results!

If you want to understand trends in validating research data, click here.

What is Research Reproducibility?

Reproducibility in research is the main factor that determines the uniqueness of a research study. Research reproducibility means obtaining consistent results using the same data and protocol as the original study. For example, researchers confirm the validity of research results by repeating the experiments that produced the original results. In addition, other researchers in this field are also able to replicate those experiments and produce results similar to the original ones.

This exercise of producing valid experiments and results creates valid scientific discoveries that are more reliable in the scientific fraternity and helps to advance future research studies in the same field. Although many research studies provide significant results, their findings are not reproducible. This issue disappoints researchers and raises the question of whether the research question or the hypothesis of the research study is valid and if the researcher needs to plan a different methodology to approach the research question.

Scientific reproducibility is a challenging and often debated topic that institutions and funding agencies are trying to resolve. The American Society for Cell Biology (ASCB) identifies methods and best practices that increase reproducibility in basic research. In addition, the ASCB has provided various terms to describe reproducibility as follows:

Direct replication: Wherein the original experimental conditions and design are used to reproduce results that have been previously observed.

Analytic replication: A set of scientific findings that are reproduced by reanalyzing the original data set.

Systematic replication: Published findings are reproduced under different experimental conditions.

Conceptual replication: A phenomenon is verified by evaluating a different set of experimental conditions.

Reproducibility Issues

Lack of reproducibility in research cannot be attributed to a single cause because there are various reasons why research results cannot be reproduced. The lack of research reproducibility has a negative effect on scientific output efficiency, scientific progress, and utilization of resources. In addition, the lack of reproducibility of research affects the trust of ordinary people in scientific research. Quantifying these problems is difficult, but estimates of financial expenditures wasted due to inappropriate research designs have been made. Furthermore, participation in non-reproducible research gives false results, leading to non-publication of the studies.

5 Factors Affecting Reproducibility in Scientific Research

Lack of Access to Raw Data and Methodologies

Researchers must have access to original data, protocols, and original research materials to reproduce original results. Lack of access to raw data and scientific methodology is considered an obstacle to reproducibility in research. Systems such as data repositories and biorepositories should be available to alleviate the problem of data sharing.

Invalid Biological Material

The reproducibility of research can be complicated if they cannot trace the original source of the biological material. In addition, if contaminated biological materials are unknowingly used, research results are significantly affected and the reproducibility of the results of such experiments is reduced.

Lack of Knowledge to Analyze Data

Scientific research has led to the creation of complex data sets. These data sets are useful for research only when they are analyzed and presented in the best statistical formats. However, many researchers cannot properly analyze or interpret data due to the lack of knowledge, scientific resources, or tools. This limitation causes misinterpretation of the results and hinders the reproducibility of the research.

Incorrect Laboratory Practices

Poor laboratory practices can result in poor experimental designs. Designing laboratory experiments is an important step in producing a valid research study. Improper research studies or experimental methods can significantly affect research results. These designs without clear test parameters and procedures may reduce reproducibility. Improper laboratory procedures may also lead to contamination of biological materials.

Undervaluing Negative Results

Scientific research is not only about obtaining positive results or proving the correctness of a hypothesis but also about justifying negative results. Researchers are rewarded for publishing new findings, but not encouraged to publish negative results. In fact, there is limited knowledge among primary researchers regarding the context of the publication of negative results. Awareness of the importance of disseminating negative results can increase researchers’ efforts and prevent them from repeating the work that is difficult to reproduce and replicate results.

Best Ways to Improve Reproducibility in Research

Open Science Approach

The Open Science Approach provides access to scientific articles, published data, and collaborative research. It is an umbrella term that includes events aimed at providing open-source information, open collaboration, open peer review, open educational resources, research funding, etc. Access to scientific literature and raw data helps researchers generate reliable and reproducible results. Thus, reproducibility in research is improved.

Use of Validated Biomaterials

Data reproducibility can be improved by using validated biological materials. The use of cells and microorganisms that confirm phenotypic and genotypic traits improves the outputs and results of researchers’ research. Moreover, the absence of contaminants leads to reliable and valid results and data that are more likely to be reproducible.

Train Researchers on Statistical Methods and Study Design

Researchers should be aware of statistical methods and use best practices in their statistical analyses. In addition, they must be properly trained to plan and structure experiments. This can increase the validity and accuracy of their statistical data and increase the chance of scientific reproducibility in research.

Practice Giving Thorough Descriptions of Methods and Methodology

It is a good thing to provide other researchers with detailed methods and methodologies to refer to and reproduce the results. Researchers should also report their objectives regarding experimental parameters, such as the use of equipment, instruments, standards, number of replicates, interpretation of results, statistical analysis, etc.

Promote and Publish Negative Data

Among many research institutions, harmful data that do not support a hypothesis are not supported or encouraged to be published. In addition, researchers are advised to design experiments and continue to conduct research until they achieve results consistent with the hypothesis. However, the publication of harmful data helps to interpret positive results from related studies and does not waste researchers’ efforts and harmful data.

Reproducibility is a sign of valid research. The scientific community tends to achieve reproducibility in research and expects researchers to take responsibility for the accuracy of results. In addition, funders, publishers, and ethical bodies should raise researchers’ awareness about the lack of reproducibility and promote better research practices among primary researchers.

Have you encountered any issues in reproducibility or replicating data during your research project? How did you overcome or manage it? Write to us or email us to discuss how we can deal with the problems related to reproducibility in research.

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