Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study
Mojtaba Vaismoradi, PhD, MScN, BScN,1,3 Hannele Turunen, PhD, RN2 and Terese Bondas, PhD, RN2,3 1College of Human and Health Sciences, Swansea University, Swansea, UK, 2Department of Nursing Science, Kuopio Campus, University of Eastern Finland, Kuopio, Finland and 3Faculty of Professional Studies, University of Nordland, Bodø, Norway
Abstract Qualitative content analysis and thematic analysis are two commonly used approaches in data analysis of nursing research, but boundaries between the two have not been clearly specified. In other words, they are being used interchangeably and it seems difficult for the researcher to choose between them. In this respect, this paper describes and discusses the boundaries between qualitative content analysis and thematic analysis and presents implications to improve the consistency between the purpose of related studies and the method of data analyses.This is a discussion paper, comprising an analytical overview and discussion of the definitions, aims, philosophical background, data gathering, and analysis of content analysis and thematic analysis, and addressing their methodological subtleties. It is concluded that in spite of many similarities between the approaches, including cutting across data and searching for patterns and themes, their main difference lies in the opportunity for quantification of data. It means that measuring the frequency of different categories and themes is possible in content analysis with caution as a proxy for significance.
Key words content analysis, nursing, qualitative descriptive research, thematic analysis.
In health care, qualitative methodologies aim to explore complex phenomena encountered by nurses, other providers, policy makers, and patients (Denzin & Lincoln, 2000; Sandelowski & Barroso, 2003a; Tong et al., 2007). The phi- losophy and the basic principles of methodologies, study aims and questions, and designs and data gathering criteria provide key differences between qualitative and quantitative methodologies (Ayres, 2007a).A belief in multiple realities, a commitment to identifying an approach to in-depth under- standing of the phenomena, a commitment to participants’ viewpoints, conducting inquiries with the minimum disrup- tion to the natural context of the phenomenon, and reporting findings in a literary style rich in participant commentaries are the main characteristics of qualitative methodologies (Streubert Speziale & Carpenter, 2007).
Qualitative methodologies consist of the philosophical perspectives, assumptions, postulates, and approaches that researchers employ to render their work open to analysis, critique, replication, repetition, and/or adaptation and to choose research methods. In this respect, qualitative method- ologies refer to research approaches as the tools with which
researchers design their studies, and collect and analyse their data (Given, 2008). Qualitative methodologies are not a single research approach, but different epistemological per- spectives and pluralism have created a range of “approaches” such as grounded theory, phenomenology, ethnography, action research, narrative analysis, and discourse analysis.
Qualitative research in the field of health has, at times, been undertaken without identification of the specific meth- odology used. The term “approach” is used in this article to differentiate it from the narrower term “methods.” This indi- cates a coherent epistemological viewpoint about the nature of enquiry, the kind of knowledge discovered or produced, and the kind of strategies that are consistent with this (Giorgi, 1970; Holloway & Todres, 2005).
Qualitative approaches share a similar goal in that they seek to arrive at an understanding of a particular phenom- enon from the perspective of those experiencing it. There- fore, the researcher needs to determine which research approach can answer their research questions (Streubert Speziale & Carpenter, 2007). There is a considerable overlap among available qualitative approaches in terms of methods, procedures, and techniques. Such an overlap of epistemologi- cal, aesthetic, ethical, and procedural concerns can encour- age a generic view of qualitative research, considering it a “family” approach in which the similarities are more impor- tant than the differences, and where the notion of flexibility becomes an important value and quest. However, there is another point of view, concerned with how such flexibility can lead to inconsistency and a lack of coherence (Holloway &
Correspondence address: Hannele Turunen, Department of Nursing Science, Kuopio Campus, University of Eastern Finland, Kuopio, Finland. PO Box 1627, 70211 Kuopio. Email: email@example.com Conflict of interest: None. Received 20 March 2012; revision received 30 December 2012; accepted 28 January 2013.
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Todres, 2003). It should not be forgotten that consumers of research assess the quality of evidence offered in a study by evaluating the conceptual and methodological decisions the researchers have made. Therefore, the researcher needs to make good decisions to produce evidence of the highest pos- sible quality (Polit & Beck, 2003; Høye & Severinsson, 2007).
Nurse researchers need to delineate and recognize the char- acteristics of the approach they are going to use in their studies to improve validity, and the consistency between the purpose of the study and the method of data analysis. There- fore, this article describes and discusses the boundaries between two commonly used qualitative approaches, content analysis and thematic analysis, and presents implications to improve the consistency between the purpose of studies and the related method of data analysis.
This article continues with a classification of content analysis and thematic analysis as descriptive qualitative approaches to data analysis, and an analytical overview and comparative discussion of the approaches’ definitions, aims, philosophical background, and data analysis process. Figure 1 summarizes the comparison of the main characteristics of thematic analy- sis and content analysis in the continuum of qualitative research.
Content analysis and thematic analysis as qualitative descriptive approaches According to Sandelowski and Barroso (2003b) research findings can be placed on a continuum indicating the degree of transformation of data during the data analysis process from description to interpretation. The use of qualitative descriptive approaches such as descriptive phenomenology, content analysis, and thematic analysis is suitable for researchers who wish to employ a relatively low level of interpretation, in contrast to grounded theory or herme- neutic phenomenology, in which a higher level of interpretive complexity is required. It is noted that there are different views with respect to the meaning of description and interpretation in qualitative research, depending on the methodological approach. Many researchers believe that both descriptive and interpretative approaches entail inter- pretation, even if the interpretive component is downplayed or masked in discussions of its broader narrative and explo- ration (Sandelowski, 2010). The value of qualitative descrip- tion lies not only in the knowledge that can originate from it, but also because it is a vehicle for presenting and treating research methods as living entities that resist simple classifi- cation, and can result in establishing meaning and solid find- ings (Giorgi, 1992; Holloway & Todres, 2005; Sandelowski, 2010).
Nursing researchers frequently use qualitative content analysis and thematic analysis as two analysis approaches in the qualitative descriptive study. However, because the boundaries and the division between the two have not been
Qualifying Qualita ve design Quan fying
Aims and concentra ons
Analyzing narra ve materials of life
and construc onist, fac st perspec ve
Descrip on and interpreta on, both induc ve and deduc ve, emphasizing context, integra on of manifest and latent contents, drawing thema c map, non- linear analysis process, no peer checking
Analyzing nursing sensi ve
phenomena, exploratory work on
the unknown phenomenon
Communica on theory, fac st
Descrip on and more interpreta on, both induc ve and deduc ve, danger of missing context, possibility of finding a theme based on the frequency of its occurrence, division of manifest and latent contents, non- linear analysis process
Thema c analysis Content analysis
Figure 1. Main characteristics of thematic analysis and qualitative content analysis in the continuum of the qualitative methodology.
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clearly specified, they are often used interchangeably and there is confusion about their similarities and differences (Sandelowski & Leeman, 2012), as well as how researchers should choose between them (Braun & Clarke, 2006). For instance, it has not been uncommon to find that qualitative content analysis is classified as a type of narrative analysis (Sandelowski & Barroso, 2003a; Sparker, 2005). Similarly, thematic analysis has sometimes been introduced as one part of phenomenology (Holloway & Todres, 2005) or even simply ignored in textbooks of qualitative methods.Addition- ally, a lack of consistency and the absence of a clear boundary between thematic analysis and qualitative content analysis, and other analytical qualitative approaches, have resulted in the application of titles such as “phenomenological thematic analysis” (Sandelowski & Barroso, 2003a) or “thematic content analysis” (Green & Thorogood, 2004). Interestingly, much of the analysis presented in published papers is essen- tially thematic, but is either described as something else such as content analysis or simply not identified as a particular method. For instance, it has been stated that data were sub- jected to qualitative analysis for commonly recurring themes (Braun & Clarke, 2006), or there is a lack of identification of the explicit methodological orientation (Sandelowski & Barroso, 2003b). Also, some researchers merely describe the use of qualitative data gathering techniques, such as inter- views and focus groups, and not enough effort is made to qualify individual elements of methods other than signaling the data analysis process as either content or thematic analy- sis (Sandelowski & Barroso, 2003b). In this respect, there is a need to clarify and introduce methodological approaches rarely identified as independent methods (Sandelowski, 2010).
Definition of content analysis and thematic analysis
Content analysis is a general term for a number of different strategies used to analyse text (Powers & Knapp, 2006). It is a systematic coding and categorizing approach used for exploring large amounts of textual information unobtrusively to determine trends and patterns of words used, their fre- quency, their relationships, and the structures and discourses of communication (Mayring, 2000; Pope et al., 2006; Gbrich, 2007).
The purpose of content analysis is to describe the charac- teristics of the document’s content by examining who says what, to whom, and with what effect (Bloor & Wood, 2006). On the other hand, thematic analysis often is seen as a poorly branded method, in that it does not appear to exist as a named method of analysis in the same way that content analysis does. Thematic analysis as an independent qualita- tive descriptive approach is mainly described as “a method for identifying, analysing and reporting patterns (themes) within data” (Braun & Clarke, 2006: 79). It has also been introduced as a qualitative descriptive method that provides core skills to researchers for conducting many other forms of qualitative analysis. In this respect, qualitative researchers should become more familiar with thematic analysis as an independent and a reliable qualitative approach to analysis.
Aim and focus of data analysis
It seems that both content analysis and thematic analysis share the same aim of analytically examining narrative mate- rials from life stories by breaking the text into relatively small units of content and submitting them to descriptive treatment (Sparker, 2005). Both content and thematic analy- sis approaches are suitable for answering questions such as: what are the concerns of people about an event? What reasons do people have for using or not using a service or procedure? (Ayres, 2007b). Content analysis is well-suited to analyse the multifaceted, important, and sensitive phenom- ena of nursing (Elo & Kyngäs, 2008; Vaismoradi et al., 2011). If conducting exploratory work in an area where not much is known, content analysis may be suitable for the simple reporting of common issues mentioned in data (Green & Thorogood, 2004). It has been suggested that thematic analy- sis, as a flexible and useful research tool, provides a rich and detailed, yet complex, account of the data (Braun & Clarke, 2006). Clearly, thematic analysis involves the search for and identification of common threads that extend across an entire interview or set of interviews (DeSantis & Noel Ugarriza, 2000).
It should be noted that both approaches allow for a quali- tative analysis of data. By using content analysis, it is possible to analyse data qualitatively and at the same time quantify the data (Gbrich, 2007). Content analysis uses a descriptive approach in both coding of the data and its interpretation of quantitative counts of the codes (Downe-Wamboldt, 1992; Morgan, 1993). Conversely, thematic analysis provides a purely qualitative, detailed, and nuanced account of data (Braun & Clarke, 2006).
When qualitative approaches are introduced in qualitative research textbooks, each approach is discussed in the context of its historical and philosophical background (Streubert Speziale & Carpenter, 2007). Generally, qualitative approaches share a broad philosophy, such as person- centeredness, and a certain open-ended starting point (Holloway & Todres, 2003).
Communication theory has been introduced as a way to address the issue of interpretation and to clarify the under- lying assumptions of content analysis (Graneheim & Lundman, 2004). Thematic analysis can be conducted within both realist/essentialist and constructionist paradigms, although the outcome and focus will be different for each (Braun & Clarke, 2006). It has also been noted that both approaches are largely based on the “factist” perspective. A factist perspective assumes data to be more or less accurate and truthful indexes of the reality out there (Sandelowski, 2010). In other words, the researcher wants to find out about the actual behaviour, attitudes, or real motives of the people being studied, or to detect what has happened (Ten Have, 2004).
According to Sandelowski (2010), a lot of energy is spent focusing on philosophical details, which often have little or nothing to do with what the researchers actually do.
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However, the philosophical starting points of the study should not be forgotten when seeking differences and simi- larities in the approaches (Bondas & Hall, 2007). The actual implementation of the methods and understanding their sub- tleties in the data analysis process should receive greater attention from nurse educators and qualitative researchers.
Exploration of the data analysis process
Both content analysis and thematic analysis are used in nursing studies. Nevertheless, a scarcity of information about the process of data analysis in nursing literature has resulted in a diversity of perspectives on how the approaches are used in research practice (Braun & Clarke, 2006; Elo & Kyngäs, 2008). A unified and standard data analysis protocol is pre- ferred to be implemented by all researchers, because differ- ent results may be produced if different protocols are followed (Gbrich, 2007).
Regarding the data analysis process, different research approaches can be compared based on aspects such as “description and interpretation,”“modalities of approaches,” “consideration of context of data,” “data analysis process,” and “evaluation of the analysis process.”
Description and interpretation
When using content analysis, the primary aim is to describe the phenomenon in a conceptual form (Elo & Kyngäs, 2008). The content analyst views data as representations not of physical events but of texts, images, and expressions created to be seen, read, interpreted, and acted on for their meanings, and must therefore be analyzed with such uses in mind (Krippendorff, 2004). However, it has been claimed that content analysis in nursing research can be applied to various levels of interpretation (Graneheim & Lundman, 2004). In contrast, thematic analysis applies minimal description to data sets, and interprets various aspects of the research topic (Braun & Clarke, 2006).
Modalities of approaches
The current application of both content analysis and the- matic analysis similarly, is associated with two modalities: inductive and deductive. Inductive content analysis and the- matic analysis is used in cases where there are no previous studies dealing with the phenomenon, and therefore the coded categories are derived directly from the text data (Hsieh & Shannon, 2005). A deductive approach is useful if the general aim of thematic analysis and content analysis is to test a previous theory in a different situation, or to compare categories at different periods (Hsieh & Shannon, 2005; Elo & Kyngäs, 2008). This form tends to provide a less rich description of the data overall, and a more detailed analysis of some aspect of the data (Braun & Clarke, 2006). It should be noted that both the approaches may begin with a theory about the target phenomenon or a framework for collecting or analysing data, but that does not mean there is a commit- ment to stay within this theory or framework (Sandelowski, 2010).The question of whether a study needs to use an induc-
tive or directed approach can be answered in both methods by matching the specific research purpose and the state of science in the area of interest to the appropriate analysis technique (Hsieh & Shannon, 2005).
Consideration of context of data
Every analysis requires a context within which the available texts are examined. The researcher must construct a world in which the texts make sense allowing them to answer research questions (Krippendorff, 2004). The researcher, who has a broader understanding of the context influencing the stories of the study participants, may develop a wider understanding of what is going on, in addition to the understanding that she or he may share with those participating in the re- search (Downe-Wamboldt, 1992). Both approaches provide researchers with a framework of analysis within which the context of data is apparent. Certainly, content analysis makes sense of what is mediated between people including textual matter, symbols, messages, information, mass-media content, and technology supported social interactions (Krippendorff, 2004; Hsieh & Shannon, 2005). On the other hand, thematic analysis is able to offer the systematic element characteristic of content analysis, and also permits the researcher to combine analysis of their meaning within their particular context (Loffe & Yardley, 2004).
If in content analysis only the frequency of codes is counted to find significant meanings in the text, there is the danger of missing the context (Morgan, 1993). Therefore, researchers employing content analysis are sometimes accused of removing meaning from its context. The problem is that a word or coding category may occur more frequently in the speech of one person or group of people than another for different reasons. Frequent occurrence could indicate greater importance, but it might simply reflect greater will- ingness or ability to talk at length about the topic (Loffe & Yardley, 2004; Shields & Twycross, 2008).
Data analysis process
Like other qualitative methods, gathering and analysing data are conducted concurrently in descriptive qualitative approaches, thus adding to the depth and quality of data analysis. However, it is also common to collect all the data before examining it to determine what it reveals (Chamberlain et al., 2004).
The process of data analysis in content analysis according to Elo and Kyngäs (2008), and in thematic analysis according to Braun and Clarke (2006) is shown in Table 1.According to the table, the preparation phase in content analysis and the phase of familiarizing with data in thematic analysis are equivalent. In both phases, the researcher is expected to tran- scribe the interview, and obtain the sense of the whole through reading the transcripts several times. While the the- matic analysis researcher is mainly advised to consider both latent and manifest content in data analysis, the content analyst can choose between manifest (developing categories) and latent contents (developing themes) before proceed- ing to the next stage of data analysis. Open coding,
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collecting codes under potential subcategories/subthemes or categories/themes, and comparing the emerged coding’s clus- ters together and in relation to the entire data set conprise the next stage of data analysis, which is named the organizing phase in content analysis.The same set of analytical interven- tions used in content analysis is applied in thematic analysis under the classifications of generating initial codes, defining and naming themes, reviewing themes, and searching for themes.
The final stage of data analysis in both approaches is related to reporting the result of the previous stages. This stage is especially highlighted as the final opportunity of data analysis in thematic analysis. In addition, in both approaches, the creativity of the researcher for presenting the result in terms of a story line, a map, or model is encouraged.
It is noted that in both approaches, high quality data analy- sis depends on gathering high quality data. It is the respon- sibility of researchers to conduct data gathering in such a way that any complex data would be suitable to present interest- ing findings.After data gathering and transcribing and paying particular attention to respondents’ emotions besides their behaviours, it is recommended that the data analyst immerses himself/herself in data in order to obtain the sense of the whole through reading and rereading (Polit & Beck, 2003).
As mentioned previously, there are many similarities between the processes of data analysis presented at the dif- ferent stages. The terminology used during the data analysis process in the approaches is comparable and equivalent to each other (Table 1). Data corpus, data item, data extract, code, and theme in thematic analysis are equivalent in
content analysis to the unit of analysis, meaning unit, con- densed meaning unit, code, and category/theme, respectively (Graneheim & Lundman, 2004; Braun & Clarke, 2006; Elo & Kyngäs, 2008).
The final product of analysis, namely the tool for present- ing findings, is much debated in both content and thematic analyses. At the most abstract level, emergence of the theme/ themes can be considered to be the result or final product of data analysis. The term theme has been associated with many definitions and is used interchangeably with a vast number of other terms such as category, domain, unit of analysis, phase, process, consequence, and strategy (DeSantis & Noel Ugarriza, 2000). In this respect, there is considerable diver- sity in nursing and qualitative research literature associated with the identification of themes, the interpretation of the concept, and its function in data analysis (DeSantis & Noel Ugarriza, 2000). A theme is defined as a coherent integration of the disparate pieces of data that constitute the findings (Sandelowski & Leeman, 2012). It captures something important about data in relation to the research question, and represents some level of response pattern or meaning within the data set (Braun & Clarke, 2006).A pragmatic way to state the difference between a theme and a category is that the latter refers mainly to a descriptive level of content and can thus be seen as an expression of the manifest content of the text, whilst the former is the expression of the latent content (Graneheim & Lundman, 2004). Especially in thematic analysis, themes are usually quite abstract, and therefore difficult to identify (DeSantis & Noel Ugarriza, 2000; Spencer et al., 2003). Furthermore, in thematic analysis the
Table 1. Processes of data analysis in thematic analysis and qualitative content analysis
Analysis phases and their descriptions
Thematic analysis (Braun & Clarke, 2006: 87) Content analysis (Elo & Kyngäs, 2008: 110)
Familiarising with data Transcribing data, reading and rereading the data, noting down
Preparation Being immersed in the data and obtaining the sense of whole,
selecting the unit of analysis, deciding on the analysis of manifest content or latent content.
Generating initial codes Coding interesting features of the data systematically across the
entire data set, collating data relevant to each code. Searching for themes Collating codes into potential themes, gathering all data relevant to
each potential theme. Reviewing themes Checking if the themes work in relation to the coded extracts and
the entire data set, generating a thematic map. Defining and naming themes Ongoing analysis for refining the specifics of each theme and the
overall story that the analysis tells, generating clear definitions and names for each theme.
Organising Open coding and creating categories, grouping codes under higher
order headings, formulating a general description of the research topic through generating categories and subcategories as abstracting.
Producing the report The final opportunity for analysis. Selection of vivid, compelling
extract examples, final analysis of selected extracts, relating back of the analysis to the research question and literature, producing a report of the analysis.
Reporting Reporting the analysing process and the results through models,
conceptual systems, conceptual map or categories, and a story line.
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importance of a theme is not necessarily dependent on quan- tifiable measures, but rather on whether it captures some- thing important in relation to the overall research question (Spencer et al., 2003; Braun & Clarke, 2006). The latter per- spective is different from the current idea in content analysis, where it is possible to reach a theme based on the frequency of its occurrence in the text. This approach is objective, sys- tematic, and concerned with the surface meaning of the docu- ment rather than hidden agenda (Bloor & Wood, 2006).
One of the first decisions that should be taken when con- ducting content analysis is whether to concentrate analysis on the manifest or latent content of data. It is said that both manifest and latent content deal with interpretation, but the interpretation varies in depth and level of abstraction (Graneheim & Lundman, 2004; Powers & Knapp, 2006). In contrast, thematic analysis incorporates both manifest and latent aspects. It means that the analysis of latent content of data is an inseparable part of the manifest analysis approach (Braun & Clarke, 2006).