- 1) Data gathering 
- 2) Read data from beginning to the end 
- 3) New codes that represent a theme

- 4) Summarize codes into themes 
- 5) Break 
- 6) Evaluate if the themes were appropriate 
* Steps 4 to 6 need to be repeated


6 Steps for Thematic Analysis 

The goal of analysis is to see how insights gained could create opportunities for change - to reframe how we see the world and our place in it.

The Goal of Thematic Analysis

- Software (CAQDAS)
- Journaling
- Affinity Diagram Techniques 


3 Common Types of Data Analysis Methods

- Labeled chunk of text as a word or a phrase
- Used as a keyword for as body of text 
- Allows researchers to find similarities, differences, and relationships between texts, which can help researchers land major themes 
- Adding the description of a code is suggested if coding requires more than one person or coding is done overtime 


Code in Thematic Analysis

- Interviews
- Focus groups 
- Diary studies 
- Field studies 

Common Thematic Analysis Data Collection Types

- Description of beliefs, practices, and needs
- A content that arises from different participants or sources 


"Theme" in Thematic Analysis


What is the primary purpose of using thematic analysis in qualitative research?

Thematic analysis is a specialized nonstatistical technique used in qualitative research to analyze relatively unfiltered data by focusing on the prominent themes that emerge. Researchers use this method to deeply understand participant experiences rather than relying on numerical statistics.

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University of Michigan - Ann Arbor

Claremont Graduate University

Methods used by UX researchers to analyze and interpret data that is collected.

Data analysis and interpretation methods in UX research

Qualitative research is a methodological approach that originated in anthropology and sociology but is now widely applied in psychology. Rather than using numerical statistics to draw general population conclusions, qualitative researchers begin with a less focused research question to deeply understand the detailed experiences of their participants. They collect large amounts of unfiltered, nonnumerical data from a relatively small number of individuals and analyze it using techniques such as grounded theory, thematic analysis, critical discourse analysis, or interpretative phenomenological analysis.

Qualitative Research

Rosala, M. (2019, September 29). How to Analyze Qualitative Data from UX Research: Thematic Analysis. https://www.nngroup.com/articles/thematic-analysis/

References: Thematic Analysis

https://kpu.pressbooks.pub/psychmethods4e/

KPU Research Methods in Psychology - 4th American Edition

Affinity Diagramming refers to the process of organizing related facts, ideas, or observations into distinct categories.

Affinity Diagramming

- The process where understanding is built out of a collection of data.

- The process is ill defined and complex due to involving data that is incomplete, and can be deceptive or wrong. 

Sensemaking within User Research

While working with a large interdisciplinary team, everyone needs to be on the same page about user needs and behaviors, project goals, and all the different parts involved in a project. This common understanding by the team is commonly built by mapping. Mappings help a team make sense of and describe various parts and processes associated with a product or project.

UX mapping methods

Thematic Analysis

Phenomenological research

Grounded theory research

Ethnographic research

Case study research

Narrative Research

Types of Qualitative Research Approaches

Qualitative research involves non-numerical data and analyses, often using a naturalistic approach to observe and analyze human behavior. Information is often gathered from interviews, naturalistic observation, focus groups, case studies, etc. Qualitative research is not analyzed statistically but rather conclusions are constructed using methods like content analysis and thematic analysis where researchers look for themes and patterns in their observed data and draw conclusions from that.

How to do Qualitative Research

Conversation analysis is a qualitative data analysis technique that examines the specific ways words are spoken during interactions, such as interviews or focus groups. Researchers utilize this specialized tool when their specific research question requires analyzing the nuances of verbal delivery.

Conversation Analysis

Interpretative phenomenological analysis is a nonstatistical method used in qualitative research to deeply describe and understand the lived experiences of research participants. Instead of relying on numerical data to draw general conclusions, it focuses on unfiltered, detailed perspectives.

Interpretative Phenomenological Analysis

In qualitative research, 'thick description' (a term associated with Geertz, 1973) refers to the deep, rich, and highly detailed accounts of human behavior as it naturally occurs within specific real-world contexts. This depth allows researchers to capture the intricacies of an environment or interaction, offering a level of detail that quantitative methods generally cannot achieve.

Thick Description

In the context of qualitative research, 'lived experience' refers to the subjective, first-hand account of what it is actually like to be a member of a particular demographic group or to exist within a specific real-world situation. Capturing this deeply personal perspective is a primary strength of qualitative methodologies, allowing researchers to convey realities that numeric, quantitative data often misses.

Lived Experience

In qualitative research, conducting interviews is one of the most common data collection approaches, particularly in psychological studies. Researchers use interviews to directly question participants and gather detailed information. Interviews can vary widely in format, ranging from flexible, unstructured conversations guided by the participant to highly structured, strictly scripted interactions.

Interviews

Quantitative researchers often criticize qualitative methods for lacking objectivity and being difficult to systematically evaluate for reliability and validity. Furthermore, qualitative studies are frequently critiqued for not allowing findings to be generalized to broader populations or contexts beyond the specific individuals investigated. Despite these criticisms, qualitative researchers are well aware of these issues and have developed specific frameworks to address them.

Criticisms of Qualitative Research

A case study is an observational research method involving an in-depth, and often longitudinal, examination of an individual, social unit, or event. In psychology, case studies typically provide a detailed qualitative description and analysis of a single individual, frequently one who has a rare condition, unusual disorder, or specific brain damage. While they primarily rely on qualitative tools like interviews and naturalistic observation, case studies can also incorporate quantitative data such as psychological testing or physiological measurements.

Case Study

Rosenhan's study on the experiences of people in psychiatric wards is a classic example of qualitative observational research. The researchers (acting as pseudopatients) collected nonnumerical data in the form of written notes about their experiences and hospital records. The analysis relied on written descriptions supported by concrete examples, such as observing staff depersonalizing patients, rather than statistical evaluation.

Example of Qualitative Observational Research: Psychiatric Ward Study

In a qualitative study by Per Lindqvist and colleagues (2008), researchers investigated how families of teenage suicide victims cope with their loss. Instead of starting with a specific numerical hypothesis, they conducted relatively unstructured interviews with $$10$$ families to understand the variety of reactions from their perspectives. The study revealed that even as life normalized, families unexpectedly struggled with the unresolved question of why the suicide occurred, demonstrating how qualitative research focuses on understanding detailed human experiences rather than drawing broad statistical conclusions.

Teenage Suicide Coping Study

Critical discourse analysis is a nonstatistical technique utilized by qualitative researchers to interpret and describe large amounts of relatively unfiltered data. It allows researchers to gain a detailed understanding of participant experiences without drawing broader statistical conclusions.

Critical Discourse Analysis

Qualitative and quantitative research differ significantly in their methodology and goals. Quantitative research generally starts with a focused hypothesis, gathering numerical data from large samples to draw general population conclusions using statistical techniques. In contrast, qualitative research begins with a broader, less focused research question and collects large amounts of unfiltered, nonnumerical data from a small number of individuals. Qualitative analysis relies on nonstatistical techniques to deeply understand the detailed experiences of participants rather than generating broad statistical generalizations.

Comparison of Qualitative and Quantitative Research

David Rosenhan's 1973 investigation into psychiatric wards serves as a classic example of disguised participant observation. Rosenhan and a group of 'pseudopatients' faked symptoms to be admitted to psychiatric hospitals, allowing them to covertly observe how staff interacted with and treated patients. Because the researchers concealed their true identities, the staff and actual patients behaved naturally around them.

Example of Disguised Participant Observation: Rosenhan's Pseudopatient Study

Per Lindqvist and colleagues' study on how families cope with the suicide of a teenager serves as a prime example of the strengths of qualitative research. By conducting unstructured interviews and listening to families discuss their lived experiences, the researchers were able to generate novel hypotheses—such as a potential relationship between the unexpectedness of the suicide and the family's need to understand why it occurred. Additionally, the qualitative approach revealed rich, unexpected details, such as families spontaneously showing interviewers the victim's bedroom, highlighting the importance of physical locations in the grieving process—a nuance that a structured quantitative study would likely have missed.

Example of Qualitative Research: Coping with Teenage Suicide

The relative weaknesses of quantitative methodology are often the primary strengths of qualitative research. Qualitative approaches excel at generating novel and interesting research questions and formulating new hypotheses that might otherwise be overlooked. Furthermore, qualitative research is particularly strong in providing thick, detailed descriptions of human behavior as it occurs in real-world contexts and successfully capturing the subjective, lived experiences of specific individuals and groups.

Strengths of Qualitative Research

Grounded theory is a qualitative data analysis approach where researchers develop a theory or interpretation that is fundamentally 'grounded in' the collected data. Unlike quantitative research—which typically starts with a predefined theory to derive and test a specific hypothesis—grounded theory begins with the data itself. The analysis progresses through systematic stages: researchers first identify repeating ideas within the data, organize these ideas into a smaller number of broader themes, and ultimately construct a theoretical narrative to interpret their findings.

Grounded Theory

Survey research is a flexible methodology that incorporates both quantitative and qualitative approaches, defined by two primary characteristics. First, it relies on self-report measures, where researchers ask participants to directly report on their thoughts, feelings, and behaviors using tools like questionnaires or interviews. Second, it emphasizes rigorous sampling techniques, typically favoring large random samples to acquire accurate estimates of population characteristics. This makes survey research one of the few approaches in psychology that routinely relies on random sampling.

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