The dissertation is often the first empirical research project a doctoral candidate has completed. Although an exciting part of taking on your first research project is the opportunity to examine a research topic that inspires and motivates you, a major aim of any dissertation is learning how to conduct scientific research from start to finish. This is a tall order for most of us, as you have to contend with new challenges like learning the conventions of scholarly writing and editing, finding a research gap related to your topic, setting up an aligned research plan, finding participants and collecting your data, and then analyzing and interpreting your data. That’s a lot to learn in one fell swoop!

On top of all of this, your methods need to be constructed such that your study can truly be considered sufficiently rigorous. If you find the prospect of creating scientific rigor a bit intimidating, you’re not alone. Many of our dissertation consulting clients have shared the feeling of being completely unprepared to take on the challenge of creating a rigorous study for the first time, but we’ve found that breaking the process down into steps can be very helpful.

For those who are conducting studies in the quantitative paradigm, your priorities in this arena are to take measures to promote reliability and validity. But, these quality benchmarks do not apply in qualitative research, so how is it that we create rigor in qualitative studies? If you’re thinking about a qualitative research method for your study, then you will need to understand both the concept of trustworthiness and the associated procedures that should be written into your methods chapter.

What is Trustworthiness?

Trustworthiness is often described as the equivalent of reliability and validity within the naturalistic research arena (Lincoln & Guba, 1986). Naturalistic research is concerned with phenomena as they exist in their natural settings, and qualitative research methods are perfectly suited for exploring such phenomena. These phenomena might be behavioral patterns one can observe or perspectives that a researcher can learn about through interviews. Whatever the topic of interest, though, the naturalistic researcher is always concerned with understanding existing phenomena (e.g., thoughts, feelings, experiences).

In contrast to approaches that use statistical analysis of numbers-based data like survey answers or test scores, qualitative research and analysis is focused around various forms of text, which might be derived through deliberate means such as interviews or observations. Existing documents such as legal proceedings or news articles can also be used as text-based data in qualitative studies. Although we most commonly think of text as language-based content, things like pictures, objects, or symbols can also be considered text.

When you consider the complexities of communication held within such forms of text, you can probably understand why we need standards of rigor when it comes to their analysis in qualitative research. Graneheim and Lundman (2004) expressed a view that “text always involves multiple meanings and there is always some degree of interpretation when approaching a text” (p. 106). If you have ever debated with others about the meanings of, say, a political speech, song lyrics, or even a past conversation, then you understand how different people can bring different meanings to the same text.

Given the emphasis on objectivity in the sciences, you might be wondering how a researcher’s subjective interpretation of text-based data can ever be considered rigorous. Indeed, this is a question that researchers have discussed and debated in great depth, with some suggesting that qualitative research is “soft science” if science at all. Others have argued, however, that subjectivity pervades human perception and cognition, and that although surveys yield numerical results that seem reassuringly objective, the conversion of human perception and experience to quantified variables is an inherently subjective process (Patton, 2014).

The conversion of human perception to quantified variables, however, involves a collection of procedures that contribute in various ways to the quality of quantitative research. You have probably heard of the concepts of reliability and validity in your methods courses, and perhaps you have come across studies that describe the complex process of validating a survey instrument. Maybe you have learned about how specific sampling practices can help to increase confidence in the accuracy and generalizability of a study’s statistical analysis results.

These procedures in combination contribute to the rigor of quantitative research and allow us to feel comfortable viewing quantitative studies’ findings as reliable representations of measurable reality. But, these types of procedures for building reliability and validity simply do not transfer to qualitative research, as qualitative research is not aimed at producing the same types of “knowledge claims” as quantitative studies (Morrow, 2005, p. 252). Given that qualitative research is aimed at understanding subjective experiences that we would not expect to be consistently “measured” from one study to the next, how exactly do we support claims of rigor in qualitative studies?

The answer to this very serious question about the rigor of qualitative research is that we cannot apply the procedures of validation used in quantitative research to qualitative studies because what we’re trying to do with qualitative studies is distinctly different from what we’re trying to do with quantitative studies. However, without a set of procedures for building rigor in qualitative research and analysis, we run the risk of publishing “research findings” that are really just position pieces on various topics.

Answering this real need, qualitative researchers have proposed trustworthiness as the qualitative equivalent to reliability and validity in quantitative research.

The criteria used to test rigor in the convention, scientific paradigm are well known. They include exploring the truth value of the inquiry or evaluation (internal validity), its applicability (external validity or generalizability), its consistency (reliability or replicability), and its neutrality (objectivity). These four criteria, when fulfilled, obviate problems of confounding, atypicality, instability, and bias, respectively…(Lincoln & Guba, 1986, p. 74)

To address these four major dimensions of scientific rigor in the qualitative research paradigm, Lincoln and Guba (1986) proposed a set of qualitative analogs: credibility, transferability, confirmability, and dependability. These four key dimensions of trustworthiness will be covered in the next sections of this article, as well as particular procedures you can build into your methods for each. If you are considering using a qualitative research method for your dissertation—as so many of our dissertation consulting clients are—then it will definitely help to get familiar with the general concept of trustworthiness as well as the specific practices that can be used to build your study’s rigor.

Credibility

The first dimension of trustworthiness we will discuss is credibility. Lincoln and Guba (1986) proposed that the criterion of credibility be approached “as an analog to internal validity” (p. 76). Credibility might be thought of as the correspondence or fit between qualitative research participants’ own perspectives and how these are portrayed or represented by researchers in their findings or results sections (Nowell et al., 2017).

This is an important criterion to consider. Just imagine if the participants you interviewed for your dissertation read your results chapter and said, “This is not at all what I meant!” That would cast serious doubt on the credibility of your findings, making others wonder if your work is really research or maybe just your own particular interpretation of the research topic (otherwise known as an editorial essay). There is definitely a place in the world for opinion pieces, but if you are setting out to conduct research, you need to take measures to faithfully represent the viewpoints you have proposed to explore (i.e., your participants’ viewpoints).

The great news is that specific methods exist for promoting credibility in qualitative research, which you should definitely work to include in your methods planning. These include prolonged engagement, persistent observation, triangulation, peer debriefing, negative case analysis, and member checking (Lincoln & Guba, 1986).

Procedures for Promoting Credibility

Following are suggested procedures for promoting credibility in qualitative research and analysis:

• Prolonged engagement: Spending a good amount of time immersed in the settings of interest, or in contact with the phenomena and/or participants of interest in your study will give you a more thorough familiarity with the meanings and dynamics that are relevant.
• Persistent observation: This refers to “in-depth pursuit of those elements found to be especially salient through prolonged engagement” (Lincoln & Guba, 1986, p. 77). In other words, persistent observation means continuing to observe until one is sure of what was shown.
• Triangulation: This refers to the examination of phenomena of interest from multiple angles. This might mean collecting data from different groups of stakeholders, collecting different forms of data (e.g., interviews, observations, documents), or even bringing in different investigators to collect data in a single study.
• Peer debriefing: This involves running your emerging analysis by an outsider who is not centrally involved in the study, but who is sufficiently knowledgeable to provide an informed review. The purpose of peer debriefing is to ensure that your emerging analyses appear to be true to what is actually reflected in the data. This functions as a great safeguard against undue imposition of your own perspectives (i.e., researcher bias) on the data.
• Negative case analysis: This refers to the “active search for negative instances” in the data, which you use to then adjust your analysis until such negative instances are eliminated (Lincoln & Guba, 1986, p. 77). Essentially what this means is that your analysis fully captures the variety of perspectives held in the data, providing assurance that you did not disregard data that conflicted with your initial interpretations.
• Member checking: This refers to a process of verifying the data and sometimes even your analysis with the original participants. Verifying interview transcripts with participants ensures that you have accurately transcribed what they expressed. Successive interpretations may also be verified with participants to ensure that you interpreted their intended meanings correctly, or that your analysis stayed true to their experiences and perspectives as expressed.

Dependability

The next dimension of trustworthiness is dependability. According to Lincoln and Guba (1986), dependability can be considered the qualitative research analog to the standard of reliability in quantitative methods research. Meeting the standard of reliability in quantitative research means that if another researcher were to attempt to replicate your study using the same methods and context, we would expect the results to come out largely the same (Shenton, 2004).

We can easily see how methods that create consistency of results, regardless of which researcher conducts the study, certainly reflects rigor. However, as Shenton (2004) pointed out, “the changing nature of the phenomena scrutinized by qualitative researchers renders such provisions problematic in their work” (p. 71). Instead of aiming for the benchmark of replicability, then, qualitative researchers aim to provide transparency regarding their research processes as a means of demonstrating that these processes were indeed dependable. Following is a description of how you might go about doing so in your own qualitative research study.

Procedures for Promoting Dependability

External audit is the primary recommendation for bolstering both dependability and confirmability. Lincoln and Guba (1986) specified that the “part of the audit that examines the process results in a dependability audit” (p. 77). This allows other researchers to evaluate the dependability of the processes involved in conducting specific qualitative research studies.

Confirmability

Next, we will discuss the trustworthiness criterion of confirmability in qualitative research. Confirmability was suggested as the qualitative or naturalistic counterpart to objectivity in quantitative research (Lincoln & Guba, 1986). Although one might argue that even validated quantitative surveys are subject to researcher bias as human-created tools of measurement (Patton, 2014), striving to minimize the imposition of researcher bias on one’s research findings is an aim of qualitative and quantitative researchers alike. As Shenton (2004) proposed, “steps must be taken to help ensure as far as possible that the work’s findings are the result of the experiences and ideas of the informants, rather than the characteristics and preferences of the researcher” (p. 72).

Procedures for Promoting Confirmability

With regard to the external audit mentioned in the previous section, Lincoln and Guba (1986) suggested that the “part concerned with the product (data and reconstructions) results in a confirmability judgment” (p. 77). This means that such an audit, when it focuses on how you gathered the data, confirms that data’s validity; when it focuses on your analysis, it confirms that you properly moved from your raw data to your findings and conclusions.

Transferability

Finally, we will discuss the fourth dimension of trustworthiness in qualitative research and analysis, transferability. Lincoln and Guba (1986) proposed the criterion of transferability as the qualitative research analog to external validity as defined in quantitative research methods. External validity in quantitative research refers to the generalizability of a study’s statistical analysis results to contexts beyond that which was specifically investigated in the study (Morrow, 2005). This is an enormously important standard for research, as we are typically conducting studies to learn not just about the sample we recruited, but also about a broader population or context beyond that sample. This is why sampling strategy is so important in quantitative studies; careful and strategic sampling can ensure that you end up with a sample that truly represents the broader population in which you are interested.

In qualitative research, however, the rationale for sample selection follows a different logic than in quantitative research. Qualitative researchers commonly select participants in a purposive manner, which means that we select only those individuals who have the specific backgrounds or characteristic necessary to provide rich and in-depth insights into the research questions that drive the study (Robinson, 2014). Shenton explained that “since the findings of a qualitative project are specific to a small number of particular environments and individuals, it is impossible to demonstrate that the findings and conclusions are applicable to other situations” (p. 69). However, it is possible to provide information that allows readers to assess the degree to which your findings might transfer to their own settings of interest.

Procedures for Promoting Transferability

To promote transferability, qualitative researchers can provide thick description of the data, setting, and participants (Lincoln & Guba, 1986). As just noted, providing this level of detail allows those who read your study to determine for themselves whether and to what degree your findings are transferable to other related settings. A great description of this process follows:

To facilitate transferability, it is valuable to give a clear and distinct description of culture and context, selection and characteristics of participants, data collection and process of analysis. A rich and vigorous presentation of the findings together with appropriate quotations will also enhance transferability. (Graneheim & Lundman, 2004)

What does this mean for your study? It means that the more your readers know about the participants, the more they will feel that your findings are representative of the whole, i.e., the entire population you will be studying. A major element of the dissertation assistance we offer you serves to help you to present your findings in such a manner. In qualitative research, this involves presenting each participant as a distinct individual, often by carefully choosing quotations from interviews that illustrate your study subjects’ thinking.

What Can We Do to Help You Achieve Trustworthiness?

If you decide to take a qualitative research approach in your research, you need to plan carefully and essentially, have every single step mapped out before you even begin. Many students find that they have a good idea for research and conduct the initial steps, only to find that their study is unfeasible, for any one of a myriad of reasons, resulting in wasted effort and lost time. One very good reason why you might want a dissertation consultant is that you don’t have the time or inclination for a “do-over” if your study turns out to be impractical to conduct.

The other major problem that we help to “head off at the pass” comes for many students at the qualitative analysis stage, wherein the data are “dissected” to tease out themes that can be used to answer the research questions. Novice researchers tend to paint themselves into corners when designing interview questions, making them either too broad (which leads to few discernible, repeated themes in the data) or too narrow (which restricts the scope of the findings). We keep this from happening in the first place by helping you design the way you will be collecting your data.

We can help you achieve trustworthiness in your data by showing you how to ensure its credibility, transferability, confirmability, and dependability, per Lincoln and Guba (1986). In terms of credibility for qualitative research and analysis, we can help you to map out your data collection efforts so that what you record will be a true representation of what you intended to examine. For instance, you want to make sure that your data will be aligned with the questions you ask, and that the questions you ask will be aligned with your study purpose and the study problem you are trying to address with it. It’s far too late to solve a problem with alignment after you start collecting data! That’s why we guide you through every step of the qualitative research design process. This includes designing interview and focus group questions, a skill which very few researchers inherently possess (Goodell et al., 2016).

I should also mention here the importance of conducting your study in a manner and location that is feasible for you. Many students don’t consider the practical aspects of gathering data. This is one potential stumbling block we can help you avoid; you don’t want to see the clock running out on you because it’s taking too much time to collect your data. We have extensive experience in this and all other aspects of research design.

In terms of dependability, the best safeguard is, as mentioned above, external audit. This is not part of the dissertation itself but is an important aspect of qualitative research. We can help you to plan for and conduct such an audit and tell you where it should be mentioned in your dissertation. Such an audit lends confirmability to your data as well.

Final Thoughts on Subjectivity and Bias

Much of the seminal work on qualitative research, as well as just about every textbook dealing with the subject, discusses researcher bias, often in great detail. Much of what you read, including elements of this post(!) might convince you that all researcher bias is a terrible thing and should be hunted down and stamped out by any ethical and competent researcher. Well, not really.

You are going to be talking to people, asking them questions that you designed, then interpreting their answers using your own subjective perceptions and opinions. Furthermore, you are the one who designed the study in the first place; discerned and researched the study problem; stated the study purpose; and before this whole process even started, decided to embark on your present course of study. Of course you’re biased! If you weren’t, you’d be a terrible researcher! At best, you’d be gathering data regarding something you don’t care about. Research cannot and should not be performed dispassionately.

Rather, you should accept the fact that you are a unique individual, with a unique set of perceptions, beliefs, knowledge, and yes, biases—those biases come from the unique set of experiences that defines you as a person. What you must do is learn to filter your data through your biases—not try to avoid them altogether. For instance, in your data analysis, are you assigning too much or too little importance to something? Are you truly representing what was said to you? Did the questions you asked truly serve your study purpose (and by the way, qualitative researchers find out that their questions did not do that all the time)?

One very informative source on this topic is Chenail (2011). In his article, he discusses how a researcher who conducts qualitative interviews should be self-aware and self-reflective, being aware of bias and compensating for it rather than trying to eliminate it. Chenail also discusses how instruments, such as interview question lists, can be subject to researcher bias in the course of their construction and use (for example, a researcher could spend too much time on one question and not enough on another). Directing you to such helpful sources is, if you wish, part of the dissertation help services we offer.

Finally, I’d like to mention that in the final chapter of many dissertations, the researcher acknowledges their bias and how it may have affected the findings. One critical element of reporting findings is that of “humility,” and part of that humility is admitting that a limitation of the study is that another researcher, using the exact same data, could and probably would have reached different conclusions. So, embrace your bias, while also compensating for it and acknowledging how it will (not may) affect your findings. This will help to strengthen your study substantially, resulting in a quality dissertation you can show off with pride!

References

• Chenail, R. J. (2011). Interviewing the investigator: Strategies for addressing instrumentation and researcher bias concerns in qualitative research. Qualitative Report, 16(1), 255-262. http://www.nova.edu/ssss/QR/QR16-1/interviewing.pdf
• Elo, S., Kääriäinen, M., Kanste, O., Pölkki, T., Utriainen, K., & Kyngäs, H. (2014). Qualitative content analysis: A focus on trustworthiness. SAGE Open, 4(1), 1-10. https://doi.org/10.1177/2158244014522633
• Goodell, L. S., Stage, V. C., & Cooke, N. K. (2016). Practical qualitative research strategies: Training interviewers and coders. Journal of Nutrition Education and Behavior, 48(8), 578-585. https://doi.org/10.1016/j.jneb.2016.06.001
• Graneheim, U. H., & Lundman, B. (2004). Qualitative content analysis in nursing research: Concepts, procedures and measures to achieve trustworthiness. Nurse Education Today, 24(2), 105-112. https://doi.org/10.1016/j.nedt.2003.10.001
• Lincoln, Y. S., & Guba, E. G. (1986). But is it rigorous? Trustworthiness and authenticity in naturalistic evaluation. New Directions for Program Evaluation, 1986(30), 73-84. https://doi.org/10.1002/ev.1427
• Morrow, S. L. (2005). Quality and trustworthiness in qualitative research in counseling psychology. Journal of Counseling Psychology, 52(2), 250-260. https://doi.org/10.1037/0022-0167.52.2.250
• Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16(1), 1-13.
• Patton, M. Q. (2014). Qualitative research and evaluation methods (4th edition). Sage.
• Robinson, O. C. (2014). Sampling in interview-based qualitative research: A theoretical and practical guide. Qualitative Research in Psychology, 11(1), 25-41. https://doi.org/10.1080/14780887.2013.801543
• Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research projects. Education for Information, 22(2), 63-75. https://doi.org/10.3233/EFI-2004-22201