What Is Information Power, and When Is It Useful for Qualitative Sample-Size Planning?

Can the Quality and Relevance of Interviews Matter More Than the Number of Participants?

You are planning a qualitative interview study involving university teachers who have developed online courses and experimented with generative artificial intelligence in assessment design. You expect the participants to have substantial firsthand experience of the phenomenon.

Your research adviser asks whether fifteen interviews will be sufficient. You could cite a previous study with a similar participant count or state that recruitment will continue until data saturation occurs. Yet neither response necessarily explains why those interviews would provide enough information for your particular research question.

Information power offers another way to reason about sample adequacy. Instead of assuming that every additional participant contributes an equivalent amount of information, it considers how relevant and analytically useful the accumulated data are for the study's purpose.

Information Power Links Sample Adequacy to the Information Participants Provide

Understanding the Five Dimensions of Information Power

Where Did the Concept of Information Power Originate?

Malterud, Siersma, and Guassora introduced information power in their 2016 article, "Sample Size in Qualitative Interview Studies: Guided by Information Power," published in Qualitative Health Research.

The authors questioned the usefulness of treating qualitative interview sample size as a matter of reaching a predetermined number or applying saturation without sufficient attention to the research design.

Their alternative emphasizes the informational contribution of the sample relative to the study's aim. A sample providing highly relevant and detailed material may support the intended analysis with fewer participants than a sample providing less focused or less informative accounts.

The framework is a methodological argument about adequacy, not a statistical sampling theorem. It does not imply that information can be measured objectively through a universal numerical score.

What Are the Five Dimensions of Information Power?

The framework identifies five considerations that jointly influence the information available for analysis.

These dimensions interact. A narrowly focused aim does not automatically justify a small sample if participants provide limited information or the analysis requires extensive subgroup comparisons.

How Does the Study Aim Affect Information Power?

A narrowly defined research aim concentrates the information needed from participants.

For example, investigating how experienced online instructors decide whether to permit generative AI in one particular assessment type is more focused than investigating teachers' experiences of educational technology generally.

The focused study may require fewer distinct perspectives because its intended analytical scope is narrower.

However, a narrow aim does not guarantee simplicity. The phenomenon may involve conflicting institutional expectations, complicated professional judgments, or substantial contextual variation.

The relationship between research aim and qualitative sample size should therefore be considered alongside participant characteristics and analytical requirements.

What Does Sample Specificity Mean?

Sample specificity concerns how closely the selected participants match the experiences and characteristics relevant to the research question.

Suppose a researcher investigates how teachers negotiate academic integrity when designing AI-assisted assessments.

Teachers who have personally designed, implemented, and reviewed such assessments may provide more directly relevant information than participants who have only attended an introductory AI seminar.

Purposive recruitment of information-rich participants may therefore increase information power.

Nevertheless, specificity should not be confused with selecting only participants who share the same opinions. Meaningful differences in experience may be necessary to understand the phenomenon adequately.

The effect of sample specificity on qualitative sample size depends on what variation the study seeks to examine.

How Does Established Theory Influence Information Power?

An established theoretical perspective can help researchers identify relevant concepts and focus interview questions.

For example, a study investigating teachers' technology-related professional decisions might use an appropriate theoretical framework to clarify which aspects of agency, institutional expectations, or professional practice warrant attention.

Such theoretical direction may increase the relevance of the collected material to the research aim.

However, theory does not automatically increase information power. A poorly matched framework may constrain questioning, overlook unexpected experiences, or impose categories that participants do not find meaningful.

The benefit depends on whether theory genuinely supports the inquiry rather than merely supplying terminology.

Does Using a Theoretical Framework Always Reduce the Required Sample?

No. The relationship is conditional.

A focused theory-informed investigation may require fewer participants than a broad exploratory inquiry because its analytical questions are more clearly defined.

However, a study comparing competing theoretical explanations may require substantial variation across participants and settings.

Likewise, theory development may require iterative sampling to investigate emerging conceptual relationships.

Researchers should explain how the theoretical framework affects the information needed, rather than assume that citing an established theory justifies a smaller sample.

What Is Quality of Dialogue?

Quality of dialogue concerns the informational richness of interactions between researcher and participant.

An effective interview may elicit detailed accounts, concrete examples, reflections on contradictory experiences, and clarification of important meanings.

For instance, asking a teacher whether AI makes assessment design easier may produce a brief affirmative response. Asking the teacher to describe a specific assessment-development decision, the alternatives considered, and the consequences of that decision may produce substantially richer material.

Dialogue quality depends partly on interviewer competence, rapport, question design, participant engagement, and the interview context.

The relationship between interview quality and participant numbers is important because interviews of equal duration or count do not necessarily provide equivalent analytical information.

Can Excellent Interviews Compensate for Missing Perspectives?

Only to a limited extent.

Detailed interviews can deepen understanding of participants' experiences, but they cannot establish perspectives that were never included in the sample.

Suppose a study investigates online assessment design across several disciplines but interviews only teachers from one program.

Even exceptionally rich interviews may not support claims about disciplinary differences that the sample does not adequately represent.

Information power should therefore be evaluated in relation to the scope of the research question. Depth and relevant variation are complementary considerations rather than interchangeable quantities.

How Does the Analysis Strategy Affect Information Power?

Analysis strategy concerns how the researcher intends to interpret the data and the kinds of claims the analysis will produce.

An intensive analysis of individual cases may require a different sample from an investigation designed to compare experiences across several groups.

For example, detailed interpretation of teachers' professional decision-making within one specific institutional setting may be feasible with a focused sample.

A study comparing teachers, students, administrators, and instructional designers across multiple institutions may require broader recruitment because its analytical objectives involve more distinct perspectives.

The relevant question is whether the available accounts provide sufficient information for the intended level and breadth of analysis.

Is Information Power the Same as Data Saturation?

No. Although both concepts can inform qualitative sample adequacy, they emphasize different reasoning.

A study may have high information power without claiming that every possible code or theme has been identified.

Conversely, repeated codes do not necessarily establish that the available interviews are sufficiently rich or relevant.

The choice between information power and data saturation for sample-size planning should reflect the methodological approach rather than a preference for whichever concept produces a smaller sample.

Does Information Power Require Data Saturation?

No. Information power does not require a finding that additional interviews produce no new codes.

Its emphasis is on whether the accumulated material provides sufficient information for the intended analysis.

However, this does not mean that researchers can stop whenever interviews seem interesting or informative. The assessment still requires a reasoned account of relevance, variation, and analytical sufficiency.

Where saturation is methodologically appropriate, the two concepts may inform complementary aspects of recruitment. They should not be treated as interchangeable or mechanically combined.

Can Information Power Produce an Exact Sample-Size Calculation?

No. The five dimensions are not numerical variables in a validated universal formula.

Assigning each dimension a score and adding the scores to obtain a required number of participants would introduce a calculation that the original framework does not establish.

Researchers may use structured notes or a matrix to document their reasoning, but such tools should remain aids to judgment.

The distinction between qualitative sample-size justification and statistical calculation is especially important when institutions request an exact participant number.

Can Information Power Be Used Before Data Collection?

Yes. The framework can inform prospective recruitment planning.

Before interviews begin, researchers can evaluate the specificity of the research aim, the intended participant population, the role of theory, the expected interview format, and the analytical strategy.

These considerations may support an initial recruitment target or range.

However, anticipated dialogue quality and actual information richness cannot be known completely in advance.

Prospective judgments should therefore remain open to revision when the methodology permits iterative recruitment.

How Can Information Power Be Assessed During Data Collection?

Researchers can review transcripts, analytical memos, and recruitment characteristics as interviews accumulate.

They may ask whether participants are providing sufficiently detailed accounts, whether important variation has been explored, and whether the material supports the intended analytical claims.

For example, early interviews may reveal that participants have extensive experience with AI-generated assessment questions but little experience evaluating student-created AI outputs.

If both practices are central to the research question, the researcher may need additional participants with relevant experience.

This is a substantive recruitment decision based on informational needs rather than a mechanical requirement to reach a particular number.

How Should Researchers Document Information Power?

A structured assessment can help make the reasoning transparent.

The matrix does not assign an information-power score. It records the evidence informing the researcher's judgment.

Does Information Power Apply to Every Qualitative Methodology?

Not automatically. The framework was developed specifically in the context of qualitative interview studies.

It may inform reasoning across several interview-based methodologies, but its compatibility should be assessed in relation to the research tradition.

For example, an ethnographic study may depend heavily on observation and sustained field engagement, while a qualitative case study may draw on documents, interviews, and institutional records.

In such studies, interview information power may be relevant without fully establishing the adequacy of the entire evidence base.

Researchers should avoid treating information power as a universal substitute for methodology-specific sampling principles.

Is Information Power Appropriate for Reflexive Thematic Analysis?

Information power may offer useful considerations for sample justification, particularly the relationship between research scope, participant relevance, and analytical richness.

However, researchers should ensure that their use of the framework is consistent with the reflexive and interpretive assumptions of the analysis.

In reflexive thematic analysis, themes are actively developed through analytical engagement rather than simply discovered as a fixed set.

Information power should therefore not be converted into an objective threshold claiming that the dataset contains all possible meanings.

The broader question of methodological compatibility of qualitative adequacy criteria remains important.

What Are the Main Limitations of Information Power?

Information power relies on interpretive judgments that may differ among researchers.

Its dimensions do not independently establish whether a particular sample contains sufficient variation, whether an interpretation is credible, or whether important experiences have been overlooked.

The framework can also be misused retrospectively. A researcher who planned twenty interviews but completed only eight because recruitment was difficult should not automatically describe the achieved sample as having high information power.

A credible justification requires evidence that the material supports the intended analysis, not merely a favorable description of the sample.

When Is Information Power Especially Useful?

The framework is particularly useful for focused qualitative interview studies involving purposively selected participants with direct experience of the phenomenon.

It can also help researchers justify a provisional sample range when a research proposal or ethics application requires a prospective recruitment plan.

Its usefulness is more limited when the central sampling question concerns the number of cases, observational settings, or documents rather than interviews alone.

Ultimately, the value of information power lies in making the relationship between research purpose and sample adequacy explicit.

Using Information Power to Plan Interviews With Online Course Designers

The provisional range is defensible only to the extent that its supporting assumptions are credible and the resulting material is sufficient for the analysis.

Information power does not establish that twelve participants will be adequate or that eighteen must be sufficient. It provides a framework for explaining why the recruitment plan may be reasonable and how it should be reviewed.

Common Misconceptions About Information Power

Use Information Power to Explain Why the Sample Supports the Analysis

Begin by evaluating the five dimensions in relation to the proposed study. Identify which dimensions support a focused sample and which suggest that broader recruitment may be necessary.

Use this reasoning to develop a provisional target or range, then revisit the assessment as interviews and analysis progress.

The final methods section should explain how the five dimensions informed the sampling plan and how the achieved material supported the analysis.

Information power is most useful when it strengthens methodological reasoning, not when it is used to defend a predetermined number without examining the data.

Before Using Information Power to Justify Sample Size

Frequently Asked Questions About Information Power

Information Power Makes Qualitative Sample-Size Reasoning More Explicit

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