Thematic analysis is a popular six-phased approach to analysing qualitative data; however, very few studies adopting this approach have explicitly demonstrated step-by-step and explained the whole . Is the Subject Area "Qualitative studies" applicable to this article? Methodology, When to use thematic analysis. We tested our method on single-tier codebooks, but qualitative researchers often create hierarchical codebooks. In quantitative research, you'll most likely use some form of statistical analysis. How to Do Thematic Analysis | Step-by-Step Guide & Examples. Fig 1 shows the process, and how base size and run length relate to one another. This renders a quotient of 11%, still not below our 5% threshold. This paper reports on the use of this type of analysis in systematic reviews to bring together and integrate the findings of multiple qualitative studies. Can I use TA? Thematic analysis is a method for analyzing qualitative data that entails searching across a data set to identify, analyze, and report repeated patterns (Braun and Clarke 2006). Here, we return to the data set and compare our themes against it. Researchers often use data-analysis software for analyzing large amounts of qualitative data. If we wanted to be more conservative, and confident in our conclusion of reaching saturation in this example, we could adjust two parameters of our assessment. Our approach involves only simple arithmetic and calculation of percentages. We hope researchers find this method useful, and that others build on our work by empirically testing the method on different types of datasets drawn from diverse study populations and contexts. The same can be said for how a researcher chooses to report and interpret statistical findings. Quantitative content analysis is a research method in which features of textual, visual, or aural material are systematically categorized and recorded so that they can be analyzed. Formal analysis, Navigating the world of qualitative thematic analysis can be challenging. The method we propose is designed for qualitative data collection techniques that aim to generate narrativesi.e., focus groups and one-on-one interviews that use open-ended questioning with inductive probing (though we have only attempted to validate the method on individual interview data). Qualitative variables are nominal and ordinal. should I use TA? Mixed methods dissertations combine qualitative and quantitative approaches to research. Similarly, the method allows for different optionsand greater clarity and transparencyin describing and reporting on saturation. The practical implication of this finding is that researchers can choose a longer run lengthe.g., three interviews (or more)to generate a more conservative assessment of saturation. Yes We test and validate our method using a bootstrapping technique on three distinctly different qualitative datasets. The expression of Theme A is not necessarily to the exclusion of Theme B, nor does the absence of the expression of Theme A necessarily indicate Not-A. Most of the time, youll combine several codes into a single theme. Thus, comparison is an inherent part of the analysis. An important stage in planning a study is determining how large a sample size may be required, however current guidelines for thematic analysis are varied, ranging from around 2 to over 400 and it is unclear how to . We can also draw other lessons to inform application of this process: There are, of course, still limitations to this approach. Cite. How many qualitative interviews are enough? Researchers have options for how they describe saturation and can also use the term with more transparency and precision. Qualitative data do not, however, have a standardised scale. Thematic analysis is one of the most important types of analysis used for qualitative data. The same can be said for . Another potential limitation of this method relates to codebook structure. Interested in What Is A Acoustic Model In Speech Recognition? This reflects similar developments in primary research in mixing methods to examine the relationship between theory and empirical data which . Theres also the distinction between a semantic and a latent approach: Ask yourself: Am I interested in peoples stated opinions (semantic) or in what their statements reveal about their assumptions and social context (latent)? Yes Dataset 3. Data saturation is the most commonly employed concept for estimating sample sizes in qualitative research. Data from all three studies were digitally recorded and transcribed using a transcription protocol [32]; transcripts were translated to English for Dataset 3. https://doi.org/10.1371/journal.pone.0232076.s001. The two main types of quantitative data are discrete data and continuous data. Though there were 14 questions on the guide, only data from three questions were included in the thematic analysis referenced here. Many qualitative data analyses, however, do not use the specific grounded theory method, but rather a more general inductive thematic analysis. The applicability of this approach for qualitative research with a different epistemological or phenomenological perspective is yet untested. You can manage to achieve trustworthiness by . The method we propose facilitates qualitative researchers choice among levels of assessment criteria along with a common description of those criteria that will allow readers to interpret conclusions regarding saturation with more or less confidence, depending on the strictness of the criteria used. The results or findings section usually addresses each theme in turn. Here again, despite a different total number of themes in the overall dataset, the number of new themes evident across 1114 interviews corresponded with a median degree of saturation of 87% to 89%. Height in feet, age in years, and weight in pounds are examples of quantitative data. What can we change to make our themes work better? The interview guide contained 13 main questions, each with scripted sub-questions. The inductive thematic analysis included 11 of the 13 questions and generated 93 unique codes. Conversely, in cases where the numbers are scattered all over the place, the standard deviation will be relatively high. Tutors' Association ID: 55870609, Join Grad Coach On: Facebook | Twitter | YouTube | LinkedIn. . Following a review of the empirical research on data saturation and sample size estimation in qualitative research, we propose an alternative way to evaluate saturation that overcomes the shortcomings and challenges associated with existing methods identified in our review. The first is that the results are within the range of what we would have expected based on previous empirical studies. We propose that furnishing researchers with optionsrather than a prescriptive thresholdis a more realistic, transparent and accurate practice. The number of new themes in this first run is seven. This means that relative to the total number of unique codes identified in the first four, five, or six interviews, the amount of new information contributed by interviews 8, 9, and 10 was less than or equal to 5% of the total. There are various approaches to conducting thematic analysis, but the most common form follows a six-step process: familiarization, coding, generating themes, reviewing themes, defining and naming themes, and writing up. This can help the researcher to better understand the data and draw more meaningful conclusions. In other words, no new information was observed after a median of 11 interviews using a run-length of 2, nor after 14 interviews using a run length of 3. For Dataset 1 (Table 2), at the 5% new information threshold, the median number of interviews needed to reach a drop-off in new information was consistent across all base sizes. Thematic analysis is often quite subjective and relies on the researchers judgement, so you have to reflect carefully on your own choices and interpretations. He found the probability of identifying a concept (theme) among a sample of six individuals is greater than 99% if that concept is shared among 55% of the larger study population. At the 0% new information threshold, saturation was indicated at 12+2 and 16+3, consistent across base sizes. Can thematic analysis be used in literature review? The first is How do we know that were not missing important information by capping our sample at n when saturation is indicated? Put another way, if we had conducted, say, five more interviews would we have gotten additional and important data? This method also enables researchers to select different levels of the constituent elements in the processi.e., Base Size, Run Length and New Information Thresholdbased on how confident they wish to be that their interpretations and conclusions are based on a dataset that reached thematic saturation. Your email address will not be published. Though it is possible an important theme will emerge later in the process/dataset, the empirical studies referenced above demonstrate that the most prevalent, high-level, themes are identified very early on in data collection, within about six interviews. First, it can help researchers to identify relationships between the data and other variables. Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories. Thematic analysis helps you make your qualitative study more accurate. The new information threshold selected affects the point at which saturation is indicated, as one would expect. At this stage, we want to be thorough: we go through the transcript of every interview and highlight everything that jumps out as relevant or potentially interesting. If analyzing data in real time, the results of this initial assessment can then determine whether or not more interviews are needed. here. This type of analysis is often used to uncover the underlying structure of a data set. Finally, our conclusion explains the main takeaways and shows how the analysis has answered our research question. [17, 18] reported similar findings. Even in cases where random sampling is employed, the open-ended nature of qualitative inquiry doesnt lend itself well to probability theory or statistical inference to a larger population because response categories are not structured, so are not mutually exclusive. Coding means highlighting sections of our text usually phrases or sentences and coming up with shorthand labels or codes to describe their content. Search for patterns or themes in your codes across the different interviews. Second, thematic analysis can be used to identify patterns in the data that could not be identified through other methods. However, thematic analysis is a flexible method that can be adapted to many different kinds of research. [26], Fugard & Potts [21], Galvin [20]) ignores the fact that most qualitative research employs non-probabilistic, purposive sampling suited to the nature and objectives of qualitative inquiry [28]. In this paper we present a method to assess and report on saturation that enables qualitative researchers to speak about--and provide some evidence for--saturation that goes beyond simple declaration. This study included 40 individual interviews with African American men in the Southeast US about their health seeking behaviors [29]. Since we had available the total number of codes identified in each dataset, we carried out one additional calculation as a way to provide another metric to understand how the median number of interviews to reach a new information threshold related to retrospectively-assessed degrees of saturation with the entire dataset. The bootstrap method is a resampling technique that uses the variability within a sample to estimate the sampling distribution of metrics (in this case saturation metrics) empirically [35]. Finally, thematic analysis can provide insight into the data that may not be otherwise apparent. This can then be compared across base sizes, run lengths, and new information thresholds. If you can identify the central organising concept of a theme, you can capture the core of what your theme is about. The method we outline eliminates this problem by using a subset of data items in the denominator instead of the entire dataset, facilitating better prospective assessment of saturation and offering the advantage of allowing researchers to stop before reaching a pre-specified number of interviews. Thematic coding, also called thematic analysis, is a type of qualitative data analysis that finds themes in text by analyzing the meaning of words and sentence structure. What a quantitative researcher accepts, for example, as a large enough effect size or a small enough p-value is a subjective determination and based on convention in a particular field of study. Can I use thematic analysis in case study? Our approach includes three primary elements in its calculation and assessment: Base Size, Run Length, and New Information Threshold. After youve decided thematic analysis is the right method for analyzing your data, and youve thought about the approach youre going to take, you can follow the six steps developed by Braun and Clarke. The fact that IPA is better thought of as a methodology (a theoretically informed framework for how you do research) rather than a method (a technique for collecting/analysing data), whereas TA is just a method. here. Check out the dedicated article the Speak Ai team put together on ChatGPT For Academic Papers to learn more. In practical terms, this implies that saturation should initially be assessed after six interviews (four in the base, and two in the run). It involves breaking down the data into smaller components and analyzing the components to find commonalities and differences. At a run length of 3, the median number of required interviews was 1112 (again higher for base size 4). A central organising concept captures the essence of a theme. We subsequently propose an alternative way of evaluating saturation and offer a relatively easy-to-use method of assessing and reporting on it during or after an inductive thematic analysis. (2010), for example, consider runs of three data collection events each time they (re)assess the number of new themes for the numerator, whereas Coenen et al. We have provided researchers with a method to easily calculate saturation during or after data collection. Using descriptive statistics, you can summarize your sample data in terms of: The distribution of the data (e.g., the frequency of each score . San Francisco, CA: Jossey-Bass. Professional editors proofread and edit your paper by focusing on: The first step is to get to know our data. To validate our method, we use a bootstrapping technique on three existing thematically coded qualitative datasets generated from in-depth interviews. However, it also involves the risk of missing nuances in the data. We would like to thank Betsy Tolley for reviewing an earlier draft of this work and Alissa Bernholc for programming support. We additionally propose a more flexible approach to reporting saturation. Samples and populations can both be represented by a qualitative variable and/or a quantitative variable, because the definition of sample and population does not include anything about the type of variables that can be used within it. . Generate accurate APA, MLA, and Chicago citations for free with Scribbr's Citation Generator. Whilst they are increasingly used and have gained greater legitimacy, much less has been written about their components parts. Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers. At the 0% new information threshold saturation was indicated at the same points as in Dataset 1: 11+2 and 14+3, consistent across all base sizes. All three studies were reviewed and approved by the FHI 360 Protection of Human Subjects Committee; the study which produced Dataset 3 was also reviewed and approved by local IRBs in Kenya and South Africa. Based on these thresholds from 10,000 resamples, for each dataset we computed the median and the 5th and 95th percentiles for number of interviews required to reach each new information threshold across different base sizes and run lengths. Thousand Oaks, CA: Sage. Hence, it could be concluded that evaluation is both quantitative and qualitative. There are several benefits to using thematic analysis in quantitative research. Their tool estimates, for example, that to have 80% power to detect two instances of a theme with a 10% prevalence in a population, 29 participants would be required. The run length is the number of interviews within which we look for, and calculate, new information. Have a human editor polish your writing to ensure your arguments are judged on merit, not grammar errors. Can qualitative and quantitative research be used together? [Note that we include this as a further way to understand and validate the proposed approach for calculating saturation, rather than as part of the proposed process.]. When to use thematic analysis. Given that both qualitative and quantitative market research provide vital ingredients of the understanding you are looking for (the Why and the What), combining them should deliver significant benefits, enabling you to compare and contrast results and gain much deeper insights. In cases where most of the numbers are quite close to the average, the standard deviation will be relatively low. All interviews were conducted in a local language. Qualitative data of mixed method requires thematic analysis in one way or another. We might decide that a better name for the theme is distrust of authority or conspiracy thinking. Theres the distinction between inductive and deductive approaches: Ask yourself: Does my theoretical framework give me a strong idea of what kind of themes I expect to find in the data (deductive), or am I planning to develop my own framework based on what I find (inductive)? The researcher could look for relationships between the responses and other variables, such as age, gender, or education level. The honest answer to this is that we dont know, and we can never know unless we conduct those five extra interviews, and then five more after that and so on. Their definition was specifically intended for the practice of building and testing theoretical models using qualitative data and refers to the point at which the theoretical model being developed stabilizes. When to use thematic analysis. Dataset 2. Thematic analysis is not particular to any one research method but is used by scholars across many fields and disciplines. The metrics are flexible. Some types of research questions you might use theme-oriented analysis to answer: Whats the difference between thematic analysis and IPA? Interestingly, empirical research on saturation began with efforts to determine when one might expect it to be reached. We start by looking at the first four interviews conducted and summing the number of unique themes identified within this group. Mixed methods reviews. Over time, the broader term data saturation has become increasingly adopted, to reflect a wider application of the term and concept. Although the datasets were all generated from individual interviews analyzed using an inductive thematic analysis approach, the studies from which they were drawn differed with respect to study population, topics of inquiry, sample heterogeneity, interviewer, and structure of data collection instrument, as described below. It is present in all qualitative research but, unfortunately, it is evident mainly by declaration [1]. I am looking for an 'approved' approach for undertaking a thematic analysis, and presenting this, of studies within a systematic review. As one reason for the growth in qualitative synthesis is what they can add to quantitative reviews, it is not surprising that there is also growing interest in mixed methods reviews. There's no one way to do a thematic analysis. The results from the bootstrapping analyses are presented by dataset, in Tables 2, 3 and 4. Themes are generally broader than codes. This is indicated by a superscript +2 or +3. The two "branches" of quantitative analysis. Abstract. Published on For Datasets 1 & 2, two analysts coded each transcript independently and compared code application after each transcript. 17). Themes are identified with any form of qualitative research method, be it phenomenology, narrative analysis, grounded theory, thematic analysis or any other form. These bootstrap findings give us information on how saturation may be reached at different stopping points as new themes are discovered in new interviews and when the interviews are ordered randomly in different replications of the sample of interviews. Conceptualization, The study sample was highly homogenous. The number of new themes evident across 1216 interviews corresponded with a median degree of saturation of 69% to 76%. For this reason, we have chosen to test 4, 5, and 6 interviews as base sizes from which to calculate the total number of unique themes to be used in the denominator of the saturation ratio. Finally, well write up our analysis of the data. For example, we might look at distrust of experts and determine exactly who we mean by experts in this theme. That said, a researcher could, with this approach, run and report on saturation analyses of two or more codebooks that contain differing levels of coding granularity. PLOS ONE promises fair, rigorous peer review, https://doi.org/10.1371/journal.pone.0232076.t005. What are the 2 types of thematic analysis? A semantic approach involves analyzing the explicit content of the data. (2022, November 25). What is the difference between thematic analysis and framework analysis? The purpose of this article is to guide researchers using thematic analysis as a research method. Would the theme identification pattern in a dataset of 20 interviews look the same if interviews #10 through #20 were conducted first? Each time they find a word, they make a copy of it and its immediate context. For this example, we have selected a new information threshold of 5% to indicate that we have reached adequate saturation. Which type you choose depends on, among other things, whether . These new information thresholds can be used as benchmarks similar to how a p-value of <0.05 or <0.01 is used to determine whether enough evidence exists to reject a null hypothesis in statistical analysis. The size of run length effect is smallestvery minimalif employing the 5% new information threshold. Abstract. We offer personal insights and practical examples, while exploring issues of rigor and trustworthiness. This means that relative to the total number of unique codes identified in the first four, five, or six interviews, the amount of new information contributed by interviews 7 and 8 was less than or equal to 5% of the total. To approximate population-level statistics and broaden our validation exercise, we drew empirical bootstrap samples from each of the datasets described above. Retrieved May 1, 2023, Thematic analysis is one of the most frequently used qualitative analysis approaches. What is the difference and similarity between qualitative and quantitative research? [22]). From an applied standpoint this finding is important in that researchers can feel confident that choosing a more stringent new information thresholde.g., 0%will result in a more conservative assessment of saturation, if so desired. While these three studies offer diverse and analytically rigorous case studies, they provide limited generalizability. Check out the dedicated article the Speak Ai team put together on ChatGPT For Academic Textbooks to learn more. Thematic analysis is a good approach to research where you're trying to find out something about people's views, opinions, knowledge, experiences, or values from a set of qualitative data - for example, interview transcripts, social media profiles, or survey responses. It is increasingly being used by researchers to analyze quantitative data as well. . https://doi.org/10.1371/journal.pone.0232076.t003. Widely employed in the field of communication, it also has utility in a range of other fields. What qualitative and quantitative data have in common with one and another? This is compounded by the fact that detailed descriptions of methods are often omitted from qualitative discussions. Funding: The authors received no specific funding for this work. Using the principle of saturation as a foundation, we describe and validate a simple-to-apply method for assessing and reporting on saturation in the context of inductive thematic analyses. Once units of analysis for the numerator and denominator are determined the proportional calculation is simple. Again, what we decide will vary according to what were trying to find out. Search for patterns or themes in your codes across the different interviews. Here again the unit of analysis is the data collection event; the items of analysis are unique codes. Revised on November 24, 2022. Just to be clear, thematic analysis (TA), like many qualitative research methods, is based on the "constant comparative method". Interested in ChatGPT For Academic Textbooks? For more information about PLOS Subject Areas, click Interested in What Is A Normal Speech Recognition Threshold? As well as highlighting all the phrases and sentences that match these codes, we can keep adding new codes as we go through the text. The median number of interviews required were 11+2 and 14+3. In addition, we randomly ordered the selected transcripts in each resample to offset any order effect on how/when new codes are discovered. Why Do Cross Country Runners Have Skinny Legs? Though a study may be powered to certain parameters (quantitative) or have a sample size based on empirical guidance (qualitative), after data collection is completed the resulting data may not conform to either. Writing original draft, At a run length of two interviews, the median number of interviews required before a drop in new information was observed was six. How do you do thematic analysis of qualitative data? Designing and conducting mixed methods research (3rd ed.). The number of themes evident across 68 interviews corresponded with a median degree of saturation of 79% to 82%. One advantage of this analysis is that it is a versatile technique that can be utilized for both exploratory research (where you don't know what patterns to look for) and more deductive studies (where you see what you're searching for). Following this process can also help you avoid confirmation bias when formulating your analysis. We follow this with an overview of the few empirically-based methods that have been put forward to operationalize and measure saturation and identify challenges of applying these approaches to real-life research contexts, particularly those that use inductive thematic analyses. For each qualitative dataset, we generated 10,000 resamples from the original sample. For the purposes of our assessment, saturation refers to the point during data analysis at which incoming data points (interviews) produce little or no new useful information relative to the study objectives. EMMY NOMINATIONS 2022: Outstanding Limited Or Anthology Series, EMMY NOMINATIONS 2022: Outstanding Lead Actress In A Comedy Series, EMMY NOMINATIONS 2022: Outstanding Supporting Actor In A Comedy Series, EMMY NOMINATIONS 2022: Outstanding Lead Actress In A Limited Or Anthology Series Or Movie, EMMY NOMINATIONS 2022: Outstanding Lead Actor In A Limited Or Anthology Series Or Movie.
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