Introducing Thematic Content Analysis (TCA) as a research Method in Qualitative Psychological Research. The Process of TCA is explained

1. Thematic Content Analysis
in Psychology
A Primer to the process
Chinchu C
Psychologist, Trainer & Research Consultant
Association for Social Change, Evolution and
Transformation(ASCENT)
Courtesy: Barbara A. Sommer, University of California, Davis

2. Thematic Content Analysis
• A Descriptive presentation of qualitative data
• Data for TCA can come from interviews, FGDs,
narrations, internet, print media etc.
• A foundational procedure in qualitative data analysis
• Interpretations are usually kept to a minimum
• The purpose is to describe, rather than explain
• Thematic Content Analysis is not necessarily a
method, but mostly a tool.

3. Ten steps of content analysis
1) Copy and read through the transcript - make
brief notes in the margin when interesting or
relevant information is found
2) Go through the notes made in the margins
and list the different types of information found
3) Read through the list and categorise each
item in a way that offers a description of what it
is about

4. Ten steps of content analysis
4) Identify whether or not the categories can be linked any
way and list them as major categories (or themes) and / or
minor categories (or themes)
5) Compare and contrast the various major and minor
categories
6) If there is more than one transcript, repeat the first five
stages again for each transcript
7) When you have done the above with all of the transcripts,
collect all of the categories or themes and examine each in
detail and consider if it fits and its relevance

5. Ten steps of content analysis
8) Once all the transcript data is categorised into minor and
major categories/themes, review in order to ensure that the
information is categorised as it should be.
9) Review all of the categories and ascertain whether some
categories can be merged or if some need to them be sub-
categorised
10) Return to the original transcripts and ensure that all the
information that needs to be categorised has been so.
The process of content analysis is lengthy and may require the
researcher to go over and over the data to ensure they have
done a thorough job of analysis

6. Strengths
• Content analysis is a readily-understood, inexpensive
research method. It is unobtrusive, and it doesn't
require contact with people.
• Content analysis becomes a more powerful tool when
combined with other research methods such as
interviews, observation, and use of archival records. It is
very useful for analyzing historical material, especially
for documenting trends over time.
• Establishing reliability is easy and straightforward.
Content analysis scores highest with regard to ease of
replication. Usually the materials can be made available
for others to use

7. Limitations
• Content analysis is a purely descriptive
method. It describes what is there, but may
not reveal the underlying motives for the
observed pattern ('what' but not 'why')
• The analysis is limited by availability of
material. In case of media content, observed
trends may not be an accurate reflection of
reality; for example, catastrophic events
receive more coverage than less dramatic
occurrences

8. Dealing with
Newspaper/Magazine/Text Content
• Scan the material first
• What are you going to
study(News/Ads/Fun/Educational Material….?)
• Is your question well-defined?
• Is the content latent(hidden) or manifest?
• Decide on the categories – Not too many and
Not too few
• Once you have decided the above…
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9. • Review your position
• Prepare a form for the analysis with checklists
• Start with counting and numbering
• Make notes
• See if you can identify patterns/similarities.
• They are the points for categorizing/Theme
identification
• Make sure you record metadata
• Once you have recorded enough data, start
analysis

10. • Record your initial reflections about the
collected data
• How can you make sense of the
patterns/similarities/structures identified?
• How would you interpret your findings?
• Is there a story to be told?
• What about Reflexivity?
• What would be the opinion of others?
• ….

11. A Quick Summary
1. State your research question or hypothesis(If any).
2.Develop coding categories that are
A. clearly defined
B. comprehensive
C. mutually-exclusive (i.e., non-overlapping)
D. appropriate for non-instances (information contrary
to your hypothesis). Use an "other" or "Misc." category for
unusual items (keep it small)
3. Decide on the unit or measurement for each category. You
can use different units for different categories.
4. Develop a systematic sampling plan for data collection.
5. Collect data and code into the categories.
6. Reliability check: Have someone independently code the
data into categories. If level of agreement is low, redefine the
problematic categories and redo the coding.
• 7. Tabulate the results