The Role of Meta-Analysis in Psychology Research

Key Takeaways

• A meta-analysis combines results from many studies to understand the big picture.
• It helps find statistical significance that might be missed in smaller studies.
• Meta-analysis is efficient because it uses data from previous research.

A meta-analysis is a type of statistical analysis in which the results of multiple studies are combined and then analyzed. Researchers can perform this type of study when there have been previous studies looking at the same question.

A meta-analysis is a type of statistical analysis where researchers review, combine, and analyze the results of multiple studies (integrated results). Meta-analysis is useful when there have been many previous studies on the same topic or asking the same question.

This article discusses when meta-analysis might be used and why it’s important. It also covers some advantages and disadvantages of using meta-analysis in psychology research.

What Is Meta-Analysis?

A simple definition of meta-analysis in psychology is that it’s a study of past studies on a subject that can give researchers a “big picture” view of the topic. To do a meta-analysis, a researcher reviews the published studies on a topic and then analyzes all the results to look for trends. Meta-analysis is used in psychology, medicine, and other fields.

New studies from around the world are constantly being published, so the amount of research that’s out there on any given topic can be overwhelming. A meta-analysis is helpful because it’s designed to summarize all the research information on a subject. There are a few general principles that a meta-analysis follows:

• It is done systematically.
• It uses certain criteria.
• It contains a pool of results.
• It is based on quantitative analysis (mathematical and statistical techniques to measure, model, and understand aspects of human behavior).

Why Is Meta-Analysis Important?

The data provided by a meta-analysis is bigger-picture than a single study, so it gives psychology researchers a better sense of the magnitude of the effect of whatever it is that is being studied—for example, a treatment. A meta-analysis also makes important conclusions clear and can identify trends that can inform future studies, policy decisions, and patient care.

Reasons Researchers Do Meta-Analysis

In addition to summarizing and analyzing integrated results, a meta-analysis also has other uses. For example, psychology researchers can use a meta-analysis to:

• Evaluate effects in different subsets of participants.
• Create new hypotheses to be studied in future research.
• Overcome the limitations of small sample sizes.
• Establish statistical significance.

Increasing Sample Size

One of the reasons why meta-analyses are used is to overcome a very common problem in research: small sample sizes.

Even though researchers would often prefer to have a large sample size for a study, it requires more resources, such as funds and personnel, than a small sample size does. When individual studies do not use a large number of subjects, it can be harder to draw reliable and valid conclusions from the findings. 

A meta-analysis helps overcome the issue of small sample sizes because it reviews multiple studies from the same subject area, essentially creating a larger sample size.

Establishing Statistical Significance

Meta-analyses can also help establish statistical significance across studies that might otherwise seem to have conflicting results. Statistical significance refers to the probability of the study’s results being due to random chance rather than an important difference. 

When you consider multiple studies at the same time, the statistical significance that is established is much greater than it would be in one study on its own. This is important because statistical significance increases the validity of any observed differences in a study, which, in turn, increases the reliability of the information researchers may glean from the findings.

Benefits of a Meta-Analysis

Meta-analyses offer many advantages over individual studies. Here are just a few benefits of meta-analysis:

• It has greater statistical power and the ability to extrapolate to the broader population.
• It is evidence-based.
• It is more likely to show an effect because smaller studies are combined into one larger study.
• It has better accuracy (because smaller studies are pooled and analyzed).
• It is more efficient (because researchers can collect a large amount of data without spending a lot of time, money, and resources since the bulk of the data collection work has already been completed).

Meta-analysis provides a view of the research that has been done in a particular field, summarizes and integrates the different findings, and provides possible directions for future research.

A meta-analysis also reduces the amount of work required to research a topic for other researchers and policymakers. For example, instead of having to look at the results of many smaller studies, people can get a more accurate view of what might be happening in a population by looking at the results of one meta-analysis.

Disadvantages

Although it can be a powerful research tool, meta-analysis does have disadvantages:

• It can be difficult and time-consuming to find all of the appropriate studies to look at.
• It requires complex statistical skills and techniques (which can be intimidating and challenging for researchers who may lack experience with this type of research).
• It may have the effect of halting research on a particular topic (for example, rather than giving directions for future research, a meta-analysis may imply that a specific question has been answered sufficiently and no more research is needed).

Types of Bias in Meta-Analysis

The way researchers do a meta-analysis (procedure) can affect the results. Following certain principles is crucial to making sure they draw valid and reliable conclusions from their work.

Even straying slightly from the protocol can produce biased and misleading results. The three main types of bias that can be a problem in meta-analysis are:

1. Publication bias: When “positive” studies are more likely to be accepted and printed.
2. Search bias: When the search for studies produces unintentionally biased results. This includes using an incomplete set of keywords or varying strategies to search databases. Also, the search engine used can be a factor.
3. Selection bias: When researchers do not clearly define criteria for choosing from the long list of potential studies to be included in the meta-analysis to make sure they get unbiased results.

Examples of Meta-Analysis in Psychology

It can be helpful to look at how a meta-analysis might be used in psychology to research specific topics. For example, imagine that a small study showed that consuming sugar before an exam was correlated to decreased test performance. Taken alone, such results would imply that students should avoid sugar consumption before taking an exam. However, a meta-analysis that pools data looking at eating behavior and subsequent test results might demonstrate that this previous study was an outlier.

Here are a few examples of meta-analysis that have been published on topics in psychology:

• Massoud Sokouti, Ali Reza Shafiee-Kandjani, Mohsen Sokouti, Babak Sokouti. A meta-analysis of systematic reviews and meta-analyses to evaluate the psychological consequences of COVID-19. BMC Psychology. 2023;11(1). doi:10.1186/s40359-023-01313-0
• Pim Cuijpers, Franco P, Markéta Čihařová, et al. Psychological treatment of perinatal depression: a meta-analysis. Psychological Medicine. 2021;53(6):2596-2608. doi: 10.1017/s0033291721004529
• Xu C, Lucille Lucy Miao, Turner DA, DeRubeis RJ. Urbanicity and depression: A global meta-analysis. Journal of Affective Disorders. 2023;340:299-311. doi:10.1016/j.jad.2023.08.030
• Pauley D, Pim Cuijpers, Papola D, Miguel C, Eirini Karyotaki. Two decades of digital interventions for anxiety disorders: a systematic review and meta-analysis of treatment effectiveness. Psychological Medicine. Published online May 28, 2021:1-13. doi:10.1017/s0033291721001999
• Bhattacharya S, Goicoechea C, Heshmati S, Carpenter JK, Hofmann S. Efficacy of cognitive behavioral therapy for anxiety-related disorders: A meta-analysis of recent literature. Current Psychiatry Reports. 2022;25(1):19-30. doi:10.1007/s11920-022-01402-8

Verywell Mind uses only high-quality sources, including peer-reviewed studies, to support the facts within our articles. Read our editorial process to learn more about how we fact-check and keep our content accurate, reliable, and trustworthy.

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Additional Reading

• Walker E, Hernandez AV, Kattan MW. Meta-analysis: Its strengths and limitations. Cleve Clin J Med. 2008;75(6):431-439. doi:10.3949/ccjm.75.6.431

By Kristalyn Salters-Pedneault, PhD

 Kristalyn Salters-Pedneault, PhD, is a clinical psychologist and associate professor of psychology at Eastern Connecticut State University.

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