On This Page:ToggleWhat Is Narrative Analysis?AssumptionsKey ConceptsApproachesPratical StepsEthical ConsiderationsStrengthsWeaknesses
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What Is Narrative Analysis?
Narrative analysis is aqualitative research methodused to understand how individuals create stories from their personal experiences.
There is an emphasis on understanding the context in which a narrative is constructed, recognizing the influence of historical, cultural, and social factors on storytelling.
Narrative analysis is not applicable to all research topics; it is best suited when the focus of the analysis is narratives or stories.
Examples of topics that are well-suited to narrative analysis include: various aspects of identity, individual experiences of psychological processes, interpersonal and intimate relationships, and experiences of body, beauty and health
Assumptions of Narrative Analysis
Key Concepts in Narrative Analysis
Narrative analysis is concerned with more than justwhatis said (the content). It also considershowthe story is constructed (the structure) and the context or situation in which the story is told (the performance)
Approaches to Narrative Analysis
There are different models and approaches to narrative analysis, and the type that is used depends on the research problem.
Pratical Steps: Conducting Narrative Analysis
The steps involved in conducting narrative analysis are often iterative and non-linear, rather than following a strict sequential order.
While the steps provide a general framework and guidance for the research process, in practice, researchers may move back and forth between different stages, or engage in multiple steps simultaneously, as new insights and questions emerge from the data.
The iterative nature of narrative analysis reflects the complex and dynamic nature of human experience and meaning-making.
1. Situate the Epistemological Approach
Determine whether to use a naturalist or constructivist approach. The research questions and theoretical framework inform this decision.
Situating the epistemological approach at the outset of the study helps ensure consistency and coherence throughout the research process, guiding methodological choices and the interpretation of findings.
If the research questions focus on understanding the subjective experiences and meaning-making processes of participants, a constructivist approach may be more appropriate.
Conversely, if the research aims to identify common patterns or themes across narratives and assumes a more objective reality, a naturalist approach may be suitable.
2. Select the Analytical Model(s)
Decide which model(s) to use in analyzing narrative data. Different models focus on different features of narratives and raise distinct questions during analysis.
3. Select Narratives to Analyze
In conducting narrative analysis involves selecting specific narratives to analyze within the larger dataset. Even when the aim is to analyze the data holistically, researchers often choose to focus on particular narratives for close scrutiny.
4. Identifying Narrative Blocks
A narrative block refers to a complete, self-contained story or narrative within a larger dataset, such as an interview transcript.
It is a segment of the data that has a clear beginning, middle, and end, and that conveys a specific experience, event, or perspective of the participant.
This involves looking for cues like “entrance and exit talk”, which signal the beginning and end of a distinct narrative within a conversation.
For instance, phrases like, “There was this one time…” or “Let me give you an example…” may signal the beginning of a narrative block.
Similarly, phrases like, “So that’s how that wrapped up…” or “That is a pretty classic example of…” can help researchers pinpoint the end of a narrative block
It is important to note that the selection of narratives and units of analysis is an iterative process, and researchers may revisit and refine their choices as they delve deeper into the data and their analysis progresses.
Researchers should be transparent about their selection criteria and process, and should reflect on how their choices may impact the interpretation and findings of the study.
“I remember when I first started college. I was so nervous and excited at the same time. I didn’t know anyone on campus, and I was worried about fitting in. But during orientation week, I met this group of people who were just as lost and nervous as I was. We bonded over our shared experiences and became fast friends. That group of friends made all the difference in my college experience. We supported each other through the ups and downs, and I don’t think I would have made it through without them.”
This narrative block has a clear beginning (starting college), middle (meeting friends during orientation week), and end (reflecting on the importance of those friendships throughout college).
It conveys a specific experience and perspective of the participant, making it a suitable unit for narrative analysis.
5. Code Narrative Blocks
In conducting narrative analysis involves coding the narrative blocks using one or multiple analytical models.
Codingis the process of assigning labels or categories to segments of data, allowing researchers to organize, retrieve, and interpret the information in a systematic manner.
The coding process may involve several rounds or iterations, as researchers refine their codes and categories based on their deepening understanding of the data.
There are two main approaches to coding narrative blocks:
It’s important to note that these classifications are not always clear-cut, and researchers may use a combination of inductive and deductive approaches in their analysis.
For example, a researcher might start with a deductive structural analysis, using a predefined model of narrative structure, but then switch to an inductive thematic analysis to identify emergent themes within each structural element.
This approach, starting with the data and allowing themes and categories to emerge from the narratives aligns with a constructivist approach, where meaning is viewed as co-created between the researcher and the participant.
Researchers using inductive coding might identify emergent themes in the narratives about “life events” and code these narrative blocks accordingly.
For example, stories about deciding to have children could be coded as “Narratives about deciding to have children”.
This approach, using pre-existing frameworks or theories to guide the coding process, aligns with a naturalist approach, where the researcher seeks to objectively identify and categorize elements of the narratives.
When using this framework for deductive coding, researchers would analyze each narrative block, looking for segments that correspond to these six elements. They would then assign the appropriate code to each segment, such as “Abstract,” “Orientation,” “Complicating Action,” and so on.
“I remember my first day at my new job [Orientation]. I was so nervous and excited at the same time [Evaluation]. As soon as I walked in, I realized I had forgotten my employee ID [Complicating Action]. I panicked and thought I would be fired on the spot [Evaluation]. But then my manager came over, laughed, and said, ‘Don’t worry, it happens to everyone. We’ll get you a new one.’ [Resolution] That moment taught me that it’s okay to make mistakes and that my new workplace was actually pretty understanding [Coda].”
By applying Labov’s story structure framework, researchers can systematically analyze the narrative data, identifying patterns in how stories are structured and told.
This can provide insights into the way individuals make sense of their experiences and construct meaning through storytelling.
Step 6: Delve into the Story Structure
This step involves a deep and systematic examination of the coded narrative data, with a focus on understanding how the narrators use story structure elements (e.g., abstract, orientation, complicating action, evaluation, resolution, and coda) to construct meaning and convey their experiences.
By delving into the story structure, researchers can identify patterns, themes, and variations across different narratives, and gain insights into the ways in which individuals make sense of their lives through storytelling.
It allows researchers to move beyond the surface level of the narratives and to gain a deeper understanding of how individuals use storytelling to make sense of their lives and multifaceted nature of human experience.
Throughout this process, researchers need to be aware of the challenges and complexities of interpretation, such as the fact that narrators may not always follow a linear or coherent story structure, or that different individuals may attribute different meanings to similar experiences.
Step 7: Compare Across Story Structure
This step involves a comparative analysis of the narrative data, looking for patterns, similarities, and differences in how story structure elements are used across different narratives.
In the previous step (Step 6: Delve into the Story Structure), researchers examined each story structure element in depth, analyzing its content, function, and meaning within individual narratives.
In Step 7, the focus shifts to a higher-level analysis, where researchers compare and contrast the use of story structure elements across the entire dataset.
The goal is to provide a comprehensive and integrative understanding of the narrative data, one that goes beyond the analysis of individual stories and reveals the broader patterns, meanings, and significance of storytelling in human experience.
Throughout this comparative analysis, researchers should remain attentive to the overarching narrative and the broader themes and meanings that emerge from the data.
While breaking down narratives into specific story structure elements can provide valuable insights, it’s important not to lose sight of the holistic nature of narratives and the way in which different elements work together to create meaning.
Researchers should also be reflexive about their own role in the analysis process, acknowledging how their own backgrounds, assumptions, and interpretive frameworks may shape their understanding of the narratives.
They should strive to provide a balanced and nuanced account of their findings, highlighting both the commonalities and the variations in how story structure elements are used across different narratives.
By comparing story structure elements across the dataset, researchers can generate new insights and theories about the ways in which individuals use storytelling to make sense of their lives and experiences.
They may identify common patterns or structures that underlie different types of narratives, or they may discover how particular social, cultural, or historical factors shape the way stories are told.
Step 8: Tell the Core Narrative
This step involves synthesizing the insights and findings from the previous steps into a coherent and compelling narrative account that captures the essence of the research participants’ experiences and the key themes and meanings that emerged from the analysis.
At this stage, researchers have thoroughly examined the narrative data, coding and analyzing it at various levels, from the specific story structure elements to the broader patterns and comparisons across narratives.
They have gained a deep understanding of how participants use storytelling to make sense of their lives and experiences, and how different factors (such as social, cultural, or historical context) shape the way stories are told.
In Step 8, researchers aim to distill this complex and multifaceted understanding into a clear and concise narrative that conveys the core insights and conclusions of the study.
The goal is to provide a powerful and insightful narrative account that captures the richness and complexity of the research participants’ experiences, and that contributes to a deeper understanding of the ways in which storytelling shapes and reflects human lives and meanings.
By telling the core narrative, researchers can communicate the significance and relevance of their findings to a wider audience, and contribute to ongoing conversations and debates in their field and beyond.
Ethical Considerations in Narrative Analysis
Researchers face the challenge of balancing the need to provide faithful accounts of participant stories with theethical obligationto interpret those stories in a way that respects the participants and avoids misrepresentation.
This requires nuance and sensitivity, acknowledging the ambiguities inherent in narrative data.
Reflexivity and Positionality
Researchers should acknowledge their role in shaping all aspects of the research process, including the interpretation of narratives.
Researchers need to be aware of their own subjectivity and how their experiences, assumptions, and perspectives could influence their interpretations of participants’ narratives.
This awareness, often referred to asreflexivity, involves critically examining one’s own assumptions and being conscious of potential biases throughout every stage of the research process.
Researchers are encouraged to maintain field journals to track their thoughts and experiences, which can provide valuable insights into their influence on the research.
Ethical narrative analysis emphasizes the importance of representing participants’ stories in a way that is true to their experiences.
Ethical narrative analysis prioritizes representing participants’ stories in a manner that accurately reflects their lived experiences, ensuring their voices are heard and their perspectives are not misrepresented.
This can include involving participants in the interpretation of their narratives and giving them a voice in how their stories are shared.
This can involve:
Strengths of Narrative Analysis
Narrative analysis is a powerful tool for qualitative research, offering several strengths.
Let’s illustrate these strengths with a specific research example. Imagine investigating the experiences and beliefs of individuals facing social marginalization.
By identifying recurring patterns, symbols, or motifs within their narratives, researchers could shed light on how these individuals make sense of their experiences, revealing the often-hidden impacts of social marginalization.
Weaknesses of Narrative Analysis
Further Information
FOR NARRATIVE ANALYSIS
LABOVIAN MODEL
Labov identified six key elements that he argued are present in fully-formed oral narratives: abstract, orientation, complicating action, evaluation, resolution, and coda.
POLKINGHORNE MODEL
According to Polkinghorne, narratives are not simply a way of representing or communicating experience, but are the primary means through which we construct and make sense of our lives.
He argued that narratives are a fundamental form of human cognition, and that we use stories to organize and interpret our experiences, to create coherence and continuity in our sense of self, and to navigate the social and cultural worlds we inhabit.
One of the key features of the Polkinghorne Model is its emphasis on theinterpretive and constructivistnature of narrative analysis.
MISHLER MODEL
Elliot Mishler, a social psychologist and professor at Harvard Medical School, developed an influential model for analyzing narratives in the context of medical encounters.
The Mishler Model, also known as the “Narrative Functions Model,” focuses on theinteractiveand collaborative nature of storytelling in medical interviews, and examines how patients and healthcare providers co-construct meaning through their dialogue.
FOR VISUAL NARRATIVE ANALYSIS
Examples
Olivia Guy-Evans, MSc
BSc (Hons) Psychology, MSc Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
Saul McLeod, PhD
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.
