Humans have a tendency to promote information that they agree with while ignoring data that points to contrary opinions. In research, this is known as publication bias and it has a far-reaching impact on the validity of any systematic investigation.
The first step in limiting publication bias is understanding what it is, and how it manifests in research. In this article, we will do a deep dive into publication bias, how to reduce or avoid it, and other types of biases in research.
A publication bias is a type of bias that affects research. It refers to a situation where studies with positive results are more likely to be published than those with negative or null findings. This means that the results from published studies are systematically different from the results of unpublished research reports.
There are several reasons for publication bias in research. For example, some researchers may not report research findings if they feel that these data sets do not support their hypothesis. They prefer to present research reports that align with their hypothesis, even if they are false. The other reason is research with positive results is more likely to get featured in journals than one with negative findings.
When publication bias becomes prevalent, it leads to an overrepresentation of positive results in scientific literature, affecting our understanding of any systematic investigation.
Find Out: What is Participant Bias? How to Detect & Avoid It
The obvious implication of publication bias is it creates an illusion of positivity in research when this is not the case. The researcher knowingly saturates the public with false information, affecting their understanding and interpretation of the research subject matter.
Here’s a breakdown of other implications of publication bias in research.
The causes of publication bias boil down to several reasons:
The best way to detect publication bias is to compare the results of published and unpublished research findings addressing the same subject matter. By comparing results, you’d know if there’s a bias for positive results in the field of study.
Citation bias is a common type of bias that affects the overall presentation of data in systematic investigations. It happens when a researcher repeatedly references specific materials because of their personal preference.
For example, a researcher may cite their own published work more often than expected because researchers tend to refer to their own work more frequently. Moreover, they often overestimate the number of times their work has been cited.
Here’s the thing: If you were to write an article about your research, you would naturally want to make sure it was well-cited. You may also be tempted to cite some of your previous papers because you feel like they are significant contributions to your field.
Citation bias doesn’t only refer to citing your work. A researcher might refer to articles published in their preferred journals or materials written in his language of competence. Other factors that influence citation bias include:
Dissemination bias occurs when a researcher fails to disseminate new research findings. This can happen for many different reasons, including:
Remember that dissemination bias does not necessarily mean that the researcher didn’t publish any of their studies. Instead, they just failed to share those results with colleagues.
Gray-literature bias is the exclusion of unpublished research findings or research results that have received little or no exposure in an academic field of study. Gray literature refers to information published outside traditional channels, such as government reports. This could be books, articles, websites, and other sources not usually considered part of the scientific record.
Gray literature is sometimes referred to as “hidden knowledge” since its existence is often unknown to most scientists. However, it is still very valuable since it provides insight into topics not covered by traditional academic journals.
Language bias happens when researchers predominantly publish reports written in a particular language, irrespective of the nature and direction of the results. It also means the use of certain words and expressions that connote social biases.
Read: Undercoverage Bias: Definition, Examples in Survey Research
Media attention bias happens when journalists and media houses amplify specific research findings over others based on individual preferences contravening the standards of journalism. When this happens, it taints media neutrality.
Media attention bias happens in several ways. For example, one may communicate a story with undue significance or weight; that is, with greater importance than a neutral journalist or editor would provide.
Outcome reporting bias is a type of bias that happens when the researcher chooses to publish specific outcomes based on the results. In other words, it is the selection of a research paper based on the results of a subset of the actual outcomes.
Related – Reporting Bias: Definition, Types, Examples & Mitigation
Outcome reporting bias affects the validity of your systematic investigation and creates a problem of missing data. Yet, it is challenging to detect in research.
Time-lag bias happens when there’s an obvious disparity between the timeframe for publishing negative and positive research results. In other words, the results of negative trials take substantially longer to publish than positive trials.
While it’s impossible to avoid publication bias, you can reduce its occurrence to the barest minimum.
First, journals and research publications owe it to themselves and the academic community to publish high-quality studies regardless of novelty or unexciting results. In other words, negative research findings shouldn’t be a deal-breaker for a research publication.
More than publishing research results, journals must make it a duty to publish complete data sets and protocols. Omitting research data can affect the study’s validity, irrespective of whether negative or positive findings have been published.
Researchers can also control publication bias through better-powered studies, enhanced research standards, and careful consideration of true and non-true relationships.
Publication bias is common in different research areas, including medical investigations, science, and psychology. Let’s look at some real-life examples.
Source: The Case of Publication Bias in Evidence-Based Medicine
To preserve validity and objectivity in research, investigators and other relevant stakeholders must limit publication bias to its barest minimum. This means committing to reporting true research findings regardless of what they are.
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