Essential Questions:

1. What attributes do thematic and content analysis have in common?
2. What are the key attributes and steps in content analysis?
3. What are the key attributes and steps in thematic analysis?

Common Attributes in Thematic and Content Analysis

Two main approaches are used for data analysis in descriptive, qualitative research: content analysis, and thematic analysis. However, there are commonalities between the two approaches as pointed out in Module 5. When doing content analysis, the researcher analyzes data qualitatively, but also quantifies the data by counting frequencies of words during the coding process and interpreting the quantitative counts of those codes (Viasmoradi, Turunen, & Bondas, 2013).  Conversely, thematic analysis provides a purely qualitative, detailed, and nuanced account of data (Braun & Clarke, 2013). The key attributes of each type of analysis are presented in Module 6. While these two approaches can be very complex, the following outlines are intended to provide a definition, characteristics of a step-by-step approach to data analysis.

Attributes of and Steps of Content Analysis

In simple terms, content analysis is a strategy a researcher uses to identify the presence of specific words or concepts in a body of text (Colorado State University, 1994-2019). Many researchers categorize content analysis in two basic forms: conceptual and relational.

Conceptual analysis: identify the “existence and frequency of concepts most often represented by words of phrases in a text’ p. 2. The researcher starts with a “hunch,” or purpose. For example, when conducting a study on divorce, the researcher predicts that participants will use emotional words. Therefore, he/she codes text according to the presence of emotional words such as: crying, angry, bitter, jealous, or relieved. The researcher counts how many times these words are used.

Relational analysis: Goes a step further in that after the words are identified and counted, the researcher interprets the meanings that emerge from these words.

According to Viasmoradi, et al., 2013). content analysis is:

• A broad term used to describe several different techniques used to analyze textual data.
• A description of the characteristics of the document’s content addressing the questions of what, to whom, and with what effect (Bloor & Wood, 2006 as cited in Viasmoradi et al., 2013).
• A systematic coding and categorizing process used to analyze large amounts of textual information unobtrusively.
• A process used to identify trends and patterns of words used, along their frequency, and relationships, to the structures and discourses of communication. (Mayring, 2000; Pope et al., 2006; Gbrich, 2007 as cited in Viasmoradi).

 According to Neudorf (2019, content analysis:

• assumes that the messages text is the phenomena to be examined and provides the units of data collection – the data are the recorded occurrences of specified codes as applied to these units.
• Codes are developed a priori (beforehand) in a primarily deductive process and then applied in relatively objective fashion by the researcher
• The codes are most often numeric.
• the a priori coding scheme of a content analysis has often been developed at least in part through a process very much like thematic analysis – an inductive step of deriving salient variables and their codes from the pool of message content to be studied. This is particularly true of investigations

Steps in Content Analysis

Hsieh and Shannon (2005) described three types and steps of content analysis: conventional, directed and summative.  

• Conventional Analysis-
  1. Used when the researcher’s goal is to describe the phenomenon
  2. Data collection is usually open-ended interviews 
  3. Read transcripts several times to become familiar with contents.
  4. Read each word in the transcripts to develop codes; highlight exact words
  5. Record notes of first thoughts and impressions during the first coding cycle.
  6. Label or identify codes that are evidenced by more than one occurrence, or show the same thought came up more than once.
  7. Identify how codes are linked or related and develop 10-15 categories and sub-categories.
  8. Write definitions for each category and sub-category (develop a tree diagram)
  9. Find examples of each code and category.
  10. Discuss links to the theory in the discussion section of the report.
• Directed Analysis-
  1. Deductive process used when a theory or research already exists on the topic, but more research is needed, or is incomplete.
  2. Goal is to add to the existing knowledge on a theory or theoretical framework.
  3. Use the existing theory or framework to identify initial codes or categories.
  4. Write operational definitions of each code or category
  5. Initial coding is two ways:
     • Strategy 1: Initial coding is conducted with a goal or related to the research questions. Read and highlight, for example, emotions.
     • Code all passages or text according to the pre-determined codes; any text that does not fit the existing coding structure are given new codes
     • Strategy 2: Start coding with the initial codes; data that do not fit within the initial codes are saved for later to determine if they fit an existing category or represent a new category.
  6. Findings either support or do not support the theory.
  7. Theory or existing research will guide discussion of findings.
• Summative Analysis-
  1. Goal is to identify words or content in the textual data and to understand the context in which those words are used. Focus is to determining underlying meaning of words through interpretation
  2. Researcher does not infer meaning, but rather explores how the words are used.
  3. Goes “beyond” the words, to determine latent (hidden) meanings beneath those words.
  4. Starts with identifying frequencies of words in the document. Frequency counts for identified terms are recorded according to source or speaker.
  5. Frequencies or word counts are used to find patterns in the data and to understand how the codes are used in context. Look at the range of ways a word is used

Table 1. Coding Differences in the Three Types of Content Analysis

Adapted from Table 8, p. 1286, Hsieh and Shannon (2005).

 Attributes and Steps of Thematic Analysis

 Braun and Clark (2013) defined and highlighted the main characteristics of thematic analysis:

• Generally defined as a process used to make sense out of large amounts of outwardly unrelated text.
• A spontaneous and reflective technique used to identify patterns in a textual data set.  
• The investigator notes patterns and themes from the coded texts and from this may construct a codebook, a structured compendium of codes that includes a description of how codes interrelate.
• Coding categories often form a hierarchy or layers of related concepts.
• The end result of a thematic analysis will highlight the most striking meanings units contained in the texts.

Saldana (2016) also characterized thematic analysis:

• involves the search for and identification of common threads that extend across an entire interview or set of interviews.
• assumes that the recorded messages themselves (i.e., the texts) are the data, and codes are developed by the investigator during close examination of the texts as salient themes emerge inductively from the texts.
• These codes most often consist of words or short phrases that symbolically assign an “essence-capturing, and/or evocative attribute” (Saldaña, 2016 , p. 4) and are viewed interactively, to be modified throughout the coding process by the investigator.
• While the investigator may begin the thematic analysis process a set of predetermined codes, these are flexible and may be changed or modified during analysis.
• The conclusion of the thematic analysis is the identification of a (hopefully) saturated set of themes (i.e., no additional themes are found from additional data; Ando, Cousins, & Young, 2014 as cited in Saldana, 2016) and a meaningful “codebook” or other compilation of findings that documents the structure of codes and themes, with the validity of the findings paramount. The frequency of occurrence of specific codes or themes is usually not a main goal of the analysis.

Steps of Thematic Analysis 

Braun and Clarke (2013) outlined a recursive set of six steps for thematic analysis:

1. Become familiar with the data; identify text of interest
2. Develop initial codes that outline features in data pertinent to the research questions. Apply the codes to data
3. Search for themes; examine codes and collate to identify broader patterns (categories).
4. Review themes and apply to the data set to determine if the answer the research questions
5. Finalize theme names and write a detailed summary of each theme.
6. Publish the report weaving together narrative with data segments (quotes).

References

Clarke, V. and Braun, V. (2013) Teaching thematic analysis: Over-coming challenges and developing strategies for effective learning. The Psychologist, 26 (2). pp. 120-123. ISSN 0952-8229 

Hsieh, H.F., and Shannon, S. (2005, November). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9). 1277-1288. DOI: 10.1177/1049732305276687

Neuendorf, K. A. (2019). Content analysis and thematic analysis. In P. Brough (Ed.), Research methods for applied psychologists: Design, analysis and reporting (pp. 211-223). New York: Routledge

Viasmoradi, M., Turunen, H. & Bondas, T. (2013). Content analysis and thematic analysis: Implications for conducting a qualitative, descriptive study. Nursing and Health Sciences, 15, 398-405.