Manuel B. Garcia

Manuel B. Garcia serves as the Senior Director for Educational Technology and Digital Learning at FEU Institute of Technology, Manila, Philippines. Read More

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Should You Decide Which Populations Matter Before Searching?

Define which populations can answer your question before a structured literature search, but do not assume every population characteristic must become a database restriction. Eligibility and retrieval are related but different decisions.

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Define Populations Before Searching Guide 54 of 899
01 · The Question

Do You Need to Define the Population Before You Search?

Population boundaries can look obvious until real studies appear. You may intend to study university students, for example, and then encounter research combining university and secondary-school students. Another paper includes mostly undergraduates but a small number of postgraduate students. A third studies students and instructors together without reporting their results separately.

Suddenly, “university students” is not quite as precise as it seemed.

For a structured review, these decisions are better considered before individual studies begin competing for inclusion. Yet defining the population in advance does not necessarily mean translating every demographic, geographic, diagnostic, or contextual characteristic into a database search restriction.

02 · The Short Answer

Define the Population Early, but Search It Strategically

In Brief

Yes. If your research question concerns a particular population, you should normally define that population before a structured search so you know which studies can legitimately contribute evidence to the question.

Specify only characteristics that are substantively justified. Population eligibility criteria do not all need to become search terms, because some characteristics may be poorly indexed, inconsistently reported, or more reliably assessed during screening.

03 · What You Need to Know

Your Population Should Follow From the Research Question

Population is more than an age group or demographic label

In evidence synthesis, the population describes the people, groups, organizations, communities, or other units to which the question applies. Exactly what needs to be specified depends on the question.

For one review, “undergraduate students” may be sufficient. Another may require students enrolled in nursing programs, first-year students, adults with a particular diagnosis, schools serving a defined age range, or institutions operating within a particular educational setting.

Cochrane guidance treats participant characteristics as an important component of review eligibility criteria and recommends describing restrictions involving characteristics such as age, diagnostic criteria, location, and setting when they matter to the review.

The principle is not to describe every imaginable characteristic. It is to specify characteristics that determine whether evidence actually addresses the question.

Ask which population differences could change the meaning of the evidence

A useful population criterion has a reason for being there.

If your question concerns generative AI use among university students, restricting eligibility to higher education may be justified because educational tasks, institutional expectations, assessment practices, and learner autonomy can differ substantially from primary or secondary education. If your question concerns all students' perceptions of generative AI, an undergraduate-only restriction would need a different justification.

The same logic applies to age, diagnosis, profession, educational level, geographic location, socioeconomic characteristics, or other population features. Do not add a restriction merely because it makes the population look methodologically tidy.

Watch Out

Every additional population restriction can remove evidence. Before adding one, ask whether that characteristic is necessary to answer the research question or merely convenient for narrowing the literature.

Population eligibility and population search terms are different decisions

This distinction is fundamental.

Population eligibility Defines which participants or units must be represented for a study to contribute to the review.
Population retrieval Determines which population concepts should actually be represented in the database search to retrieve potentially eligible records.

Suppose your review concerns university students aged 18 or older. Adult status may matter for eligibility, but adding an age restriction to the database search could be unnecessary if the higher-education concept already retrieves the relevant literature and age can be checked during screening.

The same issue arises with location, diagnostic subgroups, socioeconomic characteristics, and other features that may not be reliably represented in titles, abstracts, or database indexing.

This is why deciding which concepts should actually become search terms requires a separate judgment from deciding which concepts matter to the research question.

Mixed populations require a rule

One of the most predictable complications is a study containing both eligible and ineligible participants.

Imagine that your review concerns adolescents aged 13 to 17, but a study includes participants aged 12 to 19. Or your review concerns university students, while a survey includes both students and faculty members.

There is no single rule that works for every review. You might include a mixed-population study when data for the eligible subgroup are reported separately. In other circumstances, you might establish a threshold for the proportion of eligible participants, seek subgroup data from the authors, or exclude studies from which the relevant population cannot be isolated.

What matters is deciding how these cases will be handled consistently. Cochrane reporting guidance specifically recommends explaining how studies containing only a subset of eligible participants were addressed.

Setting may be part of the population question

Population and setting are conceptually distinct, but in practice they can interact. “Nurses” could mean hospital nurses, community nurses, nursing faculty, school nurses, or nurses working across several settings. “Students” could refer to primary school, secondary school, university, vocational education, or online professional education.

If setting changes whether the evidence answers your question, define it. If it does not, imposing a setting restriction may unnecessarily narrow the evidence base.

This is where defining what counts as relevant before seeing the search results becomes useful. Population and setting boundaries can then be justified by the intended scope rather than improvised around individual papers.

Do not define the population more narrowly than the question requires

Specificity can feel like rigor. It is not automatically rigor.

Suppose your question concerns university students' experiences with online learning. Restricting the review to students aged 18 to 22, enrolled full-time, studying at public universities, and living on campus might produce a beautifully precise eligibility statement. It might also exclude substantial evidence without improving the answer.

Population restrictions should therefore be defensible in substantive terms. An arbitrary restriction can make a review easier to manage while making its conclusions less informative or less applicable.

This is one mechanism through which overly strict criteria can hide important evidence.

Exploratory searching may legitimately precede final population boundaries

If you are entering an unfamiliar literature, you may not yet know how researchers define the population. An exploratory search can reveal common age ranges, diagnostic definitions, educational levels, terminology, and patterns of mixed samples.

That does not contradict the principle of prespecification. It means the exploratory phase is being used to develop a defensible question before the final structured search begins. Systematic review methodology relies on prespecified eligibility criteria, but question development itself can require substantial preliminary work. Cochrane emphasizes that well-formulated questions guide eligibility criteria, searching, data collection, synthesis, and presentation.

04 · A Practical Example

How Population Boundaries Affect a Literature Search

Hypothetical Example

Generative AI use among university students

A researcher wants to examine how university students use generative AI for academic writing. Before the formal search, she defines the eligible population as students enrolled in higher-education programs. She does not restrict eligibility by academic discipline because her question concerns university students broadly.

Study A A survey includes undergraduate engineering students. The population meets the planned criteria.
Study B A study combines university students and faculty members but reports student results separately. The eligible subgroup can therefore be assessed independently.
Study C A survey combines secondary-school and university students and reports only pooled findings. The researcher applies her predetermined rule for mixed populations rather than deciding based on whether the results look interesting.
Study D A university study does not report students' exact ages. Because age was never necessary to the research question, the researcher does not exclude it merely for lacking that demographic detail.

The important decision occurred before screening: the population was defined according to the question. Individual papers then had to satisfy that definition rather than quietly redefining it.

05 · What Researchers Often Get Wrong

Common Mistakes When Defining a Study Population

Misconception

“More specific population criteria make a review more rigorous”

Only when the specificity is justified by the question. Unnecessary age, location, institutional, diagnostic, or demographic restrictions can reduce the evidence base without improving the validity of the review.

Misconception

“Every population criterion should appear in the search string”

No. Some population characteristics are better assessed during screening because they are inconsistently reported or indexed. Eligibility criteria and database retrieval criteria perform different functions.

Misconception

“Mixed-population studies must always be excluded”

Not necessarily. Relevant subgroup data may be reported separately, or a review may establish another defensible rule for mixed samples. The important issue is to specify how such cases will be handled rather than improvising a different rule for each study.

Misconception

“Population only means demographic characteristics”

Population can involve clinical status, educational level, occupation, institutional membership, or other characteristics relevant to the question. Setting may also be important when it determines whether evidence applies to the intended population.

Misconception

“If the population is not described perfectly in the abstract, the study is irrelevant”

Abstracts contain limited information. Potentially eligible studies may require full-text assessment before population eligibility can be determined. Searching too narrowly on poorly reported population characteristics can prevent those studies from reaching screening at all.

06 · What This Means for You

Define the Population You Need, Not the Narrowest Population You Can Imagine

Before a structured search, describe the population that must be represented for a study to answer your question. Then examine each proposed restriction and ask what methodological or substantive purpose it serves.

After defining eligibility, make a second decision about retrieval. Which population characteristics need to be represented in the search itself, and which can be assessed during screening?

A simple decision framework

If a population characteristic is fundamental to the research question
Specify it in the eligibility criteria and consider how reliably it can be retrieved from the relevant databases.
If a characteristic is merely convenient
Do not automatically restrict the population. Ask whether excluding other participants would materially improve the answer.
If eligible and ineligible participants commonly appear together
Define in advance how mixed populations and separately reported subgroups will be handled.
If the population terminology is unclear
Use exploratory searching to understand how the field describes participants before finalizing the structured search.

The same logic applies to other boundaries. You should also consider which study designs can answer the question and whether particular outcomes need to be defined before searching.

07 · A Quick Checklist

Before Finalizing Your Population Criteria

Before restricting studies by population, check:
The population follows directly from the research or review question.
Each demographic, diagnostic, geographic, educational, or contextual restriction has a defensible reason.
I have defined how mixed populations and eligible subgroups will be handled.
I have considered whether setting is genuinely relevant to population eligibility.
I have separated population eligibility criteria from population terms used for database retrieval.
I am not excluding potentially useful evidence merely to make the population easier to describe.
For a structured review, the population criteria are documented before substantive study selection begins.
08 · Frequently Asked Questions

Questions About Population Criteria in Literature Searches

Do I need to specify an age range before searching?

Only if age is substantively relevant to the question or eligibility of the evidence. If age is not important, an arbitrary age restriction can unnecessarily exclude studies. If it is important, decide whether age should be searched directly or assessed during screening.

Should country or geographic location be part of the population criteria?

Only when location is relevant to the question, context, or intended applicability of the review. Geographic restrictions should have a substantive rationale rather than being used merely to reduce the number of search results.

Can I include a study with both eligible and ineligible participants?

Potentially. Relevant subgroup data may be available separately, or your review may use a predefined rule for mixed populations. State the rule clearly and apply it consistently.

Should every population characteristic become a keyword?

No. Characteristics that matter for eligibility may be difficult to retrieve reliably through database searching. Some are better assessed during title, abstract, or full-text screening.

What if I discover an important population I had not considered?

During exploratory work, that discovery may legitimately lead you to revise the question. In a formal review already governed by a protocol, consequential changes should be justified and documented rather than introduced simply because a particular study is attractive.

Can my population be too broad?

Yes. If important population differences make the studies answer materially different questions, an overly broad definition can make interpretation difficult. The solution is not necessarily to exclude more studies; subgrouping or separate syntheses may sometimes preserve useful evidence while respecting meaningful differences.

09 · The Bottom Line

Define Who the Evidence Needs to Represent

The Bottom Line

Define the population before a structured literature search when population characteristics determine whether a study can answer your question, but include only restrictions that you can substantively justify.

Then separate eligibility from retrieval. A characteristic can matter when deciding whether a study belongs without necessarily being a safe or useful restriction in the database search itself.

10 · Sources and Further Reading

Sources and Further Reading

11 · Cite this Guide

How to Cite This Guide

This guide is intended to be read, shared, and used in research, teaching, and academic work. If you draw on its ideas, explanations, or other content, please acknowledge the source by citing the guide. Doing so gives appropriate credit and helps your readers locate the original resource.

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