Best Practice

Member Checking: Ensuring Participant Representation

Member checking, among other validation techniques in qualitative research, offers a space for researchers to gather feedback from study participants to bolster the credibility of the data analysis and findings in their study. Read more in this article to learn about the principles of and techniques for member checking.
Roehl Sybing
Content creator and qualitative data expert
  1. Introduction
  2. What is member checking in qualitative research?
  3. Why conduct a member check?
  4. What is an example of member checking?
  5. When should you use member checking?
  6. Different types of member checks
  7. How to conduct member checking
  8. Tips for effective member checking


In more positivist or realist qualitative research paradigms, research findings are almost always solely within the researcher's discretion: they collect qualitative data from research participants through qualitative methods such as interviews, focus groups, and observations, then interpret the data as they see it without the input of others.

However, in more contemporary qualitative research, member checking (sometimes also called respondent validation) is an essential part of the research process as it helps mitigate researcher bias and contextualizes data with the perspectives of research participants. As a qualitative research technique, member checking relies on participants in the generation of knowledge to facilitate a more robust data analysis. In this article, we'll look at why qualitative researchers engage in the process of respondent validation of their data and how it benefits the research process.

The member checking process involves validation techniques to ensure the credibility of qualitative data and enhance trustworthiness.

What is member checking in qualitative research?

In simple terms, the member checking process is the act of sharing research results with participants to gather feedback regarding the extent to which the findings align with their perspectives. In any research context where researcher bias is a concern, particularly if the researcher is an outsider unfamiliar with particular aspects of the research content, member checking holds his or her reports of the data collected up to the scrutiny of research participants. As people tend to look at the same data in different ways, member checking can inform qualitative analysis by providing a richer and more contextualized understanding of the aspects of the social world under study.

Yvonne Lincoln and Egon Guba wrote extensively on the process of member checking. In the concept of member checking from the perspective of Lincoln and Guba, as researchers review the data, members of the research study are part of an iterative process for analyzing the data and establishing credibility within the study. Member checking can help:

Think of member checking as either another layer of data collection or a quality control process to ensure that the original data is valid and accurate. Particularly in fields such as anthropology and sociology, or in qualitative research that deals with critical theory or engages with marginalized or understudied populations, member checking is an outright necessity as it ensures that multiple voices are incorporated in the generation of knowledge. As a result, researchers writing for sociocultural and critical journals will benefit from writing about their member checking practices during data collection.

Why conduct a member check?

It's possible, and often probable, for many researchers to interpret data from interviews or focus groups in a different way than the participant intended. This can be problematic if the goal of your research is to capture the perspectives and knowledge of insiders within your research context.

A researcher's own biases can pose challenges for the interpretive validity of the study without a clear and comprehensive incorporation of participants' perspectives in data analysis and findings. Even in studies where bias does not threaten the credibility of the analysis, the research findings are made richer by a comprehensive contextualization of the data.

What is an example of member checking?

Member checking is often employed in ethnographic research where the goal is to understand a particular research context from the perspectives of those within it and who are familiar with it. Suppose there is a researcher who is conducting observations in a foreign country, where the spoken language is different from their first language. They may be proficient in that language, but what happens if the observed participants use any unfamiliar slang or cultural references?

They could search the Internet for the cultural information they're looking for, but with access to the very people they are observing, member checking becomes a convenient option to gain the insights necessary for understanding. In this case, the researcher can review the transcripts of any audio captured during observations with their participants to get a more complete sense of what was said, what was meant, and what role it played in the observed research context.

When should you use member checking?

Member checking is a key component in any research involving human participants. Particularly if you collect data for research inquiries in which you are an outsider to the context, you can benefit from member checking and gaining access to an insider perspective to the knowledge you are looking to address.

Different types of member checks

In general terms, the member checking process seeks to bolster the accuracy and validity of the study. However, these two concepts can refer to many things. Likewise, researchers employ member checking to incorporate feedback from participants for many reasons.

First, the accuracy of the data collected from participants is important for capturing their perspectives. Narrative accuracy checks can be as simple as ensuring the researcher has accurately documented the times, dates, and people involved in the stories that people tell during interviews or discussions in focus groups. As time-consuming as this may seem, the effort taken in making sure that the elements of a participant's utterances are documented with sufficient accuracy ultimately informs the rest of the research process from analysis of the data to discussion of the findings.

Member checking for descriptive validity is the process of confirming the accuracy of the researcher's observations with their participants. In this case, it is not the representation of participants' perspectives being assessed but the representation of what the researcher sees while in the field collecting data. This is especially useful when they are in a context with which they are unfamiliar. Imagine that a researcher observes a cultural ritual conducted in a language that they do not understand or for reasons that they do not know. They can document their observations in field notes and then conduct member checking with participants who are more familiar about the ritual to gain deeper understanding of the culture.

Member checks also extend beyond whether the data itself is accurate or not. When a researcher interviews participants and elicits narratives about their daily lives, what meaning can they draw from such stories? While a researcher can make a guess or inference about such meanings, they can benefit from employing member checking for interpretive validity to give participants the opportunity to contextualize their previous utterances and affirm or challenge the conclusions made about the collected data. This collaborative approach ensures that researchers capture as comprehensive a picture of the participants' worldviews as possible.

How to conduct member checking

Regardless of the rationale for conducting member checking, there are a number of commonly accepted steps to take when engaging with research participants about the data and the resulting analysis.

  1. Review the data. Regardless of whether or not you conduct member checking, reviewing the data that you collect while in the field is an essential component of engaged qualitative research as it allows you to refine your analytical lens to more ably identify critical insights about the research context. In the case of member checking, reviewing the data can help raise questions or identify ambiguities that can be addressed with your participants.
  2. Prepare the data. Data collection can produce large amounts of data that are daunting for researchers, let alone their participants. It's a good idea to transcribe any interviews or observation audio and focus only on the parts that are immediately relevant to the participants from whom you are gathering feedback. It's also important to remove any identifying information to preserve participant confidentiality.
  3. Select the participants. In an ideal world, a researcher can rely on all of the participants they interview or observe. The varied nature of human relationships and the demands on time, however, might make member checking with every participant challenging, if not impossible. Focus your efforts on those participants with whom you have the greatest rapport and, thus, are the most likely to offer you the deepest insights in a collaborative approach.
  4. Share data. Treat the member checking process as another interview, although less formal in nature. The goal of member checking is less about collecting structured data and more about contextualizing the data you already have. In addition to sharing an interview transcript or a set of field notes, it might be helpful to also share the raw audio or video recordings as the playing back process can help stimulate the recall of your participants about events or utterances.
  5. Collect feedback. Once you share what you have collected, invite your participants to speak freely about what they think, what needs to be corrected or clarified, and what information or context is missing. Again, member checking relies on an open dialogue with participants to ensure that the feedback received helps you to better understand the context so that you can produce more robust research findings.
  6. Analyze feedback. The knowledge you elicit from member checking can inform your developing analytical lens. Compare your assumptions about the data with what your participants say during member checking. Do your assumptions need revisiting or have your participants confirmed your thinking about the insights that arose during the initial analysis? The trustworthiness of your data relies on the extent that your assumptions align with those of your participants.
  7. Revise interpretations. While the insights gained during member checking can directly inform your research findings, you can enhance trustworthiness in your study overall if the member checking process has an influence on the analysis of your data in general. The development of your theoretical framework which you apply to the data can be facilitated by the insights that your participants have by making the context more familiar, ultimately affecting your research findings.

Keep in mind that member checking need not be a formal or rigid process. The overall goal is to gain a familiarity of the context so you can analyze it with greater depth and rigor. How you achieve that, given the relationships you have with your participants and the breadth and depth of the data you have collected, is for you to determine.

Tips for effective member checking

Member checking can be a useful process if you keep in mind the following considerations.

  • Make the data comprehensible. An interview transcript or a set of field notes can often be structured to facilitate analysis, but that does not mean the data is easily accessible to the participants. Ensure that your participants can easily understand the data you want to review.
  • Respect your participants. It would be a mistake to simply see your participants as sources of information. Especially in ethnographic or observational research, rapport is built on trust and mutual respect, with the collection of data as a secondary concern.
  • Detail the member checking process. Research papers and presentations are more persuasive if you can comprehensively describe your methods for data collection and analysis, and that includes how you conducted member checking and how participants responded.