13 Worked Example: From Raw Data to Themes

(PSY206) Data Management and Analysis

Author

Md Rasel Biswas

In this example, we demonstrate the complete qualitative analysis process, starting from raw interview data and moving step-by-step toward themes and interpretation.

12.1 Research Context

Suppose we are conducting a study on:

Barriers to accessing healthcare from the Dhaka University Medical Center among university students

We conducted short interviews with students and collected the following responses.


12.2 Raw Data (Interview Excerpts)

Participant 1:
“The medical center is affordable, but there are no specialist doctors. For serious problems, I go outside. \(\cdots\)

Participant 2:
“Many of the machines do not work properly. Last time, they could not even measure my blood pressure. \(\cdots\)

Participant 3:
“It is always crowded. I have to wait for a long time, so I avoid going unless it is urgent. \(\cdots\)

Participant 4:
“I do not trust their treatment much. They usually give the same medicine without proper check-up. \(\cdots\)

Participant 5:
“The medical center is far from my hall. When I am sick, I do not feel like going there. \(\cdots\)

Participant 6:
“There is not enough privacy. It feels uncomfortable to talk about personal health problems. \(\cdots\)

Participant 7:
“I am not sure what services are actually available there. \(\cdots\)

Participant 8:
“The treatment is very basic. If the condition is serious, they refer you outside immediately. \(\cdots\)


12.3 Step 1: Identifying Data Segments

We begin by carefully reading each response and identifying meaningful segments that represent a single idea.

Example:
The medical center is affordable, but there are no specialist doctors.”

Segments:

  • The medical center is affordable
  • There are no specialist doctors

This step ensures that coding is based on meaningful units rather than entire responses.


12.4 Step 2: Initial Coding (Open Coding)

At this stage, we assign codes to each segment. Instead of creating many highly specific codes, we use a small number of broader, conceptually meaningful codes.

Data Segment Initial Code
There are no specialist doctors lack of specialist doctors
Same medicine without proper check-up inadequate treatment
Referred outside immediately external referral
Machines do not work equipment failure
Cannot measure BP lack of basic equipment
Long waiting time long waiting time
Medical center is far distance barrier
Not enough privacy lack of privacy
Not aware of services lack of awareness
Avoid going unless urgent avoid seeking care

Important observations:

  • The same code (e.g., poor service quality) appears across multiple participants
  • This repetition helps reveal patterns in the data
  • Codes are broad enough to capture meaning, but not overly general

12.5 Step 3: Reviewing and Refining Codes

We review the initial codes to ensure clarity, consistency, and conceptual distinctness.

Final refined codes:

Data Segment Code
No specialist doctors / Same medicine without proper check-up / Referred outside immediately poor service quality
Machines do not work / cannot measure BP facility limitation
Long waiting time / Medical center is far access difficulty
Not enough privacy environment concern
Not aware of services awareness issue
Avoid going unless urgent delayed care

12.6 Step 4: Developing Themes (Axial and Selective Coding)

We now group the refined codes into broader themes. Each theme represents a distinct dimension of the problem.

Theme 1: Poor Quality of Medical Service
Includes:

  • poor service quality

This theme reflects students’ perception that the medical center cannot provide reliable or adequate treatment.


Theme 2: Structural and Access Barriers
Includes:

  • facility limitation
  • access difficulty

This theme captures both infrastructural problems and practical difficulties in accessing the service.


Theme 3: Awareness and Environmental Concerns
Includes:

  • awareness issue
  • environment concern

This theme reflects lack of information and discomfort in the service environment.


Theme 4: Consequence: Delayed or Avoided Care
Includes:

  • delayed care

This theme represents how students respond to the barriers.


12.7 Step 5: Interpretation

Based on the analysis, we can interpret the findings as follows:

Students face multiple barriers when accessing healthcare from the Dhaka University Medical Center. The most prominent issue is the perceived poor quality of medical service, including lack of specialist doctors and inadequate treatment practices. Structural and access-related barriers, such as malfunctioning equipment, long waiting times, and distance from residential halls, further discourage utilization. In addition, lack of awareness about available services and concerns about privacy reduce students’ willingness to seek care. As a result, many students delay treatment or rely on external healthcare providers.


12.8 Key Learning Points from the Example

  • Coding should balance detail and simplicity
  • Repetition of codes helps identify patterns
  • Codes can be broad but must remain meaningful
  • Themes should represent distinct dimensions of the problem
  • Interpretation connects analysis back to the research question

This structured approach reflects standard qualitative analysis and can be directly implemented in QualCoder.