😶‍🌫️
Psych
  • Preface
  • [4/9/2025] A One-Stop Calculator and Guide for 95 Effect-Size Variants
  • [4/9/2025] the people make the place
  • [4/9/2025] Personality predicts things
  • [3/31/2025] Response surface analysis with multilevel data
  • [3/11/2025] A Complete Guide to Natural Language Processing
  • [3/4/2025] Personality - Self and Identity
  • [3/1/2025] Updating Vocational Interests Information
  • [2/25/2025] Abilities & Skills
  • [2/22/2025] APA table format
  • [2/19/2025] LLM that replace human participants can harmfully misportray and flatt
  • [2/18/2025] Research Methods Knowledge Base
  • [2/17/2025] Personality - Motives/Interests
  • [2/11/2025] Trait structure
  • [2/10/2025] Higher-order construct
  • [2/4/2025] RL for CAT
  • [2/4/2025] DoWhy | An end-to-end library for causal inference
  • [2/4/2025] DAGitty — draw and analyze causal diagrams
  • [2/2/2025] Personality States
  • [2/2/2025] Psychometric Properties of Automated Video Interview Competency Assessments
  • [2/2/2025] How to diagnose abhorrent science
  • [1/28/2025] LLM and personality/interest items
  • [1/28/2025] Personality - Dispositions
  • [1/28/2025] Causal inference in statistics
  • [1/27/2025] Personality differences between birth order categories and across sibship sizes
  • [1/27/2025] nomological network meta-analysis.
  • [1/25/2025] Classic Papers on Scale Development/Validation
  • [1/17/2025] Personality Reading
  • [1/15/2025] Artificial Intelligence: Redefining the Future of Psychology
  • [1/13/2025] R for Psychometics
  • [12/24/2024] Comparison of interest congruence indices
  • [12/24/2024] Most recent article on interest fit measures
  • [12/24/2024] Grammatical Redundancy in Scales: Using the “ConGRe” Process to Create Better Measures
  • [12/24/2024] Confirmatory Factor Analysis with Word Embeddings
  • [12/24/2024] Can ChatGPT Develop a Psychometrically Sound Situational Judgment Test?
  • [12/24/2024] Using NLP to replace human content coders
  • [11/21/2024] AI Incident Database
  • [11/20/2024] Large Language Model-Enhanced Reinforcement Learning
  • [11/05/2024] Self-directed search
  • [11/04/2024] Interview coding and scoring
  • [11/04/2024] What if there were no personality factors?
  • [11/04/2024] BanditCAT and AutoIRT
  • [10/29/2024] LLM for Literature/Survey
  • [10/27/2024] Holland's Theory of Vocational Choice and Adjustment
  • [10/27/2024] Item Response Warehouse
  • [10/26/2024] EstCRM - the Samejima's Continuous IRT Model
  • [10/23/2024] Idiographic Personality Gaussian Process for Psychological Assessment
  • [10/23/2024] The experience sampling method (ESM)
  • [10/21/2024] Ecological Momentary Assessment (EMA)
  • [10/20/2024] Meta-Analytic Structural Equation Modeling
  • [10/20/2024] Structure of vocational interests
  • [10/17/2024] LLMs for psychological assessment
  • [10/16/2024] Can Deep Neural Networks Inform Theory?
  • [10/16/2024] Cognition & Decision Modeling Laboratory
  • [10/14/2024] Time-Invariant Confounders in Cross-Lagged Panel Models
  • [10/13/2024] Polynomial regression
  • [10/13/2024] Bayesian Mixture Modeling
  • [10/10/2024] Response surface analysis (RSA)
  • [10/10/2024] Text-Based Personality Assessment with LLM
  • [10/09/2024] Circular unidimensional scaling: A new look at group differences in interest structure.
  • [10/07/2024] Video Interview
  • [10/07/2024] Relationship between Measurement and ML
  • [10/07/2024] Conscientiousness × Interest Compensation (CONIC) model
  • [10/03/2024] Response modeling methodology
  • [10/02/2024] Conceptual Versus Empirical Distinctions Among Constructs
  • [10/02/2024] Construct Proliferation
  • [09/23/2024] Psychological Measurement Paradigm through Interactive Fiction Games
  • [09/20/2024] A Computational Method to Reveal Psychological Constructs From Text Data
  • [09/18/2024] H is for Human and How (Not) To Evaluate Qualitative Research in HCI
  • [09/17/2024] Automated Speech Recognition Bias in Personnel Selection
  • [09/16/2024] Congruency Effect
  • [09/11/2024] privacy, security, and trust perceptions
  • [09/10/2024] Measurement, Scale, Survey, Questionnaire
  • [09/09/2024] Reporting Systematic Reviews
  • [09/09/2024] Evolutionary Neuroscience
  • [09/09/2024] On Personality Measures and Their Data
  • [09/09/2024] Two Dimensions of Professor-Student Rapport Differentially Predict Student Success
  • [09/05/2024] The SAPA Personality Inventory
  • [09/05/2024] Moderated mediation
  • [09/03/2024] BiGGen Bench
  • [09/02/2024] LMSYS Chatbot Arena
  • [09/02/2024] Introduction to Measurement Theory Chapters 1, 2 (2.1-2.8) and 3.
  • [09/01/2024] HCI measurememt
  • [08/30/2024] Randomization Test
  • [08/30/2024] Interview Quantative Statistical
  • [08/29/2024] Cascading Model
  • [08/29/2024] Introduction: The White House (IS_202)
  • [08/29/2024] Circular unidimensional scaling
  • [08/28/2024] Sex and Gender Differences (Neur_542_Week2)
  • [08/26/2024] Workplace Assessment and Social Perceptions (WASP) Lab
  • [08/26/2024] Computational Organizational Research Lab
  • [08/26/2024] Reading List (Recommended by Bo)
  • [08/20/2024] Illinois NeuroBehavioral Assessment Laboratory (INBAL)
  • [08/14/2024] Quantitative text analysis
  • [08/14/2024] Measuring complex psychological and sociological constructs in large-scale text
  • [08/14/2024] LLM for Social Science Research
  • [08/14/2024] GPT for multilingual psychological text analysis
  • [08/12/2024] Questionable Measurement Practices and How to Avoid Them
  • [08/12/2024] NLP for Interest (from Dan Putka)
  • [08/12/2024] ONet Interest Profiler (Long and Short Scale)
  • [08/12/2024] ONet Interests Data
  • [08/12/2024] The O*NET-SOC Taxonomy
  • [08/12/2024] ML Ratings for O*Net
  • [08/09/2024] Limited ability of LLMs to simulate human psychological behaviours
  • [08/08/2024] A large-scale, gamified online assessment
  • [08/08/2024] Text-Based Traitand Cue Judgments
  • [08/07/2024] Chuan-Peng Lab
  • [08/07/2024] Modern psychometrics: The science of psychological assessment
  • [08/07/2024] Interactive Survey
  • [08/06/2024] Experimental History
  • [08/06/2024] O*NET Research reports
  • [07/30/2024] Creating a psychological assessment tool based on interactive storytelling
  • [07/24/2024] My Life with a Theory
  • [07/24/2024] NLP for Interest Job Ratings
  • [07/17/2024] Making vocational choices
  • [07/17/2024] Taxonomy of Psychological Situation
  • [07/12/2024] PathChat 2
  • [07/11/2024] Using games to understand the mind
  • [07/10/2024] Gamified Assessments
  • [07/09/2024] Poldracklab Software and Data
  • [07/09/2024] Consensus-based Recommendations for Machine-learning-based Science
  • [07/08/2024] Using AI to assess personal qualities
  • [07/08/2024] AI Psychometrics And Psychometrics Benchmark
  • [07/02/2024] Prompt Engineering Guide
  • [06/28/2024] Observational Methods and Qualitative Data Analysis 5-6
  • [06/28/2024] Observational Methods and Qualitative Data Analysis 3-4
  • [06/28/2024] Interviewing Methods 5-6
  • [06/28/2024] Interviewing Methods 3-4
  • [06/28/2024] What is Qualitative Research 3
  • [06/27/2024] APA Style
  • [06/27/2024] Statistics in Psychological Research 6
  • [06/27/2024] Statistics in Psychological Research 5
  • [06/23/2024] Bayesian Belief Network
  • [06/18/2024] Fair Comparisons in Heterogenous Systems Evaluation
  • [06/18/2024] What should we evaluate when we use technology in education?
  • [06/16/2024] Circumplex Model
  • [06/12/2024] Ways of Knowing in HCI
  • [06/09/2024] Statistics in Psychological Research 1-4
  • [06/08/2024] Mathematics for Machine Learning
  • [06/08/2024] Vocational Interests SETPOINT Dimensions
  • [06/07/2024] How's My PI Study
  • [06/06/2024] Best Practices in Supervised Machine Learning
  • [06/06/2024] SIOP
  • [06/06/2024] Measurement, Design, and Analysis: An Integrated Approach (Chu Recommended)
  • [06/06/2024] Classical Test Theory
  • [06/06/2024] Introduction to Measurement Theory (Bo Recommended)
  • [06/03/2024] EDSL: AI-Powered Research
  • [06/03/2024] Perceived Empathy of Technology Scale (PETS)
  • [06/02/2024] HCI area - Quantitative and Qualitative Modeling and Evaluation
  • [05/26/2024] Psychometrics with R
  • [05/26/2024] Programming Grammer Design
  • [05/25/2024] Psychometric Network Analysis
  • [05/23/2024] Item Response Theory
  • [05/22/2024] Nature Human Behaviour (Jan - 20 May, 2024)
  • [05/22/2024] Nature Human Behaviour - Navigating the AI Frontier
  • [05/22/2024] Computer Adaptive Testing
  • [05/22/2024] Personality Scale (Jim Shard)
  • [05/22/2024] Reliability
  • [05/19/2024] Chatbot (Jim Shared)
  • [05/17/2024] GOMS and Keystroke-Level Model
  • [05/17/2024] The Psychology of Human-Computer Interaction
  • [05/14/2024] Computational Narrative (Mark's Group)
  • [05/14/2024] Validity Coding
  • [05/14/2024] LLM as A Evaluator
  • [05/14/2024] Social Skill Training via LLMs (Diyi's Group)
  • [05/14/2024] AI Persona
  • [05/09/2024] Psychological Methods Journal Sample Articles
  • [05/08/2024] Meta-Analysis
  • [05/07/2024] Mturk
  • [05/06/2024] O*NET Reports and Documents
  • [05/04/2024] NLP and Chatbot on Personality Assessment (Tianjun)
  • [05/02/2024] Reads on Construct Validation
  • [04/25/2024] Reads on Validity
  • [04/18/2024] AI for Assessment
  • [04/17/2024] Interest Assessment
  • [04/16/2024] Personality Long Reading List (Jim)
    • Personality Psychology Overview
      • Why Study Personality Assessment
    • Dimensions and Types
    • Reliability
    • Traits: Two Views
    • Validity--Classical Articles and Reflections
    • Validity-Recent Proposals
    • Multimethod Perspective and Social Desirability
    • Paradigm of Personality Assessment: Multivariate
    • Heritability of personality traits
    • Classical Test-Construction
    • IRT
    • Social desirability in scale construction
    • Traits and culture
    • Paradigms of personality assessment: Empirical
    • Comparison of personality test construction strategies
    • Clinical versus Actuarial (AI) Judgement and Diagnostics
    • Decisions: Importance of base rates
    • Paradigms of Personality Assessment: Psychodynamic
    • Paradigms of Assessment: Interpersonal
    • Paradigms of Personality Assessment: Personological
    • Retrospective reports
    • Research Paradigms
    • Personality Continuity and Change
Powered by GitBook
On this page
  • Deep Meaning
  • Phenomenology: Exploring Essence
  • Research Questions
  • Phenomenological Questions
  • Showcasing Phenomenological Practices
  • Interviewing in Practice
  • Unveiling Story
  • Narrative Inquiry: Unveiling Story
  • Narrative Inquiry Questions
  • Self Narratives
  • First Person Artifacts
  • Three-Dimensional Space
  • Characteristics of Research Methods

[06/28/2024] Interviewing Methods 3-4

Previous[06/28/2024] Interviewing Methods 5-6Next[06/28/2024] What is Qualitative Research 3

Last updated 11 months ago

Deep Meaning

The photograph shows a woman embracing her son in a field. What is the essence of motherhood as she and others experience this phenomenon? Said differently, what is at the heart of the mothering experience?

Phenomenology: Exploring Essence

As a qualitative method, phenomenology evokes the essence, or deep meaning, of individuals’ lived experiences with a phenomenon. Phenomenological researchers value in-depth, iterative interviews and prolonged engagement, often with a small, relatively homogeneous sample of participants. This allows for the elicitation of depth over breadth, which is true to the spirit of phenomenology.

Dr. Laura Curran and colleagues (2017) are among the many social scientists who have studied the phenomenon of mothering. The abstract of their study, which examines maternal identity through a unique lens, is below:

In this study, we examine the phenomenology of maternal identity development among U.S. women hospitalized with medically high risk pregnancies (MHRP). We conducted 16 in-depth interviews with women and found that they drew on culturally normative notions of maternal nurture, worry, and sacrifice to construct maternal identity in the context of MHRP. Based on our findings, we suggest that MHRP shape women’s sense of connection to and distinctive cognitive representations of their fetus. We conclude that hospitalization simultaneously promotes and challenges women’s early maternal identifications.

Throughout this topic area, we will return again and again to the Curran et al. (2017) study, among others, to explore phenomenology. First, we will present a brief history of phenomenology, tracing its evolution. Then, we will examine the kinds of questions phenomenologists seek to answer, while exploring the unique methods utilized.

Phenomenology has roots in 20th century transcendental philosophy. Edmund Husserl and his contemporaries (e.g., Sartre, Merleau-Ponty) aimed to move beyond reductionist, “ready-made” accounts of the world and objects. Let’s take, for instance, a phenomenon like mothering. Objectifying mothering counters its inherently subjective, iterative, and ever-changing nature. To a phenomenologist, mothering, as it is experienced and reflected upon by one who mothers, is worthy of exploration.

Max Van Manen’s (1990) work has been instrumental in advancing phenomenology:

From a phenomenological point of view, to do research is always to question the way we experience the world, to want to know the world in which we live as human beings. And since to know the world is profoundly to be in the world in a certain way, the act of researching is the intentional act of attaching ourselves to the world, to become more fully part of it, or better to become the world. Phenomenology calls this inseparable connection to the world the principle of “intentionality.” In doing research we question the world's very secrets and intimacies which are constitutive of the world, and which bring the world as world into being for us and in us (p. 5).

If this sounds deep and complex, that’s because it is. Phenomena as we experience and reflect upon them are rarely simple. The skilled phenomenologist applies a “systematic attempt to uncover and describe the structures, the internal meaning structures, of lived experience” (Van Manen, 1990, p. 10). Today, psychologists use phenomenology to explore essences of individuals’ lived experiences.

Research Questions

Phenomenologists ask about human beings’ lived experiences. Curran et al. (2017) asked, “How do women in the United States construct and understand their maternal identity in the context of high risk pregnancy?” Said differently, they are asking, “What is the lived experience of maternal identity for women experiencing high-risk pregnancy?”

Phenomenological Questions

Think about a question that you have about a phenomenon that would be tough to measure. Here are some ideas: experiencing stress during exams week, falling in (or out) of love, and navigating jitters when meeting new people.

Let’s consider the first experience through a phenomenological lens:

  • A phenomenologist might ask, “What is the lived experience of stress for first-year college students during exam week?”

  • Specific questions supporting this inquiry might be, “How has this person experienced stress?” “What meaning arises as this person makes meaning of stress?” “In what ways does this person understand their experience?”

On a piece of paper, in a journal, or in another app, write about a phenomenological question of interest to you, then save your response for a later activity.

Showcasing Phenomenological Practices

For those who prefer concrete examples of the phenomenological practices described previously, let us delve into several real-life studies that showcase how these practices come to life.

Epoche: Nieto-Rucian and Furness (2019) explored the lived experiences of 6 individuals who grew up with a parent who had schizophrenia. The epoche process is evident in Nieto-Rucian’s depiction of method; she writes in the article about growing up with a mother with schizophrenia, “an experience that affected her on a deep emotional level, and she believes that this experience has had a high impact in the decisions she has made throughout her life” (p. 255). As part of epoche, Nieto-Rucian, who conducted the interviews, chose to bracket (i.e., not disclose) her life experience during the first three interviews, revealing her history only upon conclusion of the interviews. Intriguingly, early participants persuaded her to share her history earlier, which she did in the latter interviews. As written, “Participants to whom the shared history was revealed beforehand shared more information and appeared more at ease during the interview” (p. 256).

In-depth interviewing: Gupta’s (2020) study on the LGBTQ closet was phenomenological; she worked with five adult participants, all of whom experienced being in the closet. Prior to the interview, participants drafted “a descriptive anecdote about a painful experience of being in the closet, including as much detail as possible such as thoughts, feeling, sensations, images and metaphors” (p. 6). This task invited space within the interview for deep, in-depth exploration of the phenomenon under investigation. Consequently, “the interviews produced an outpouring of imagery about participants’ felt senses of the closet” (p. 6).

Curran and colleagues (2017) also used in-depth interviewing, yet with a larger group of individuals (n = 16) who met their study’s inclusion criteria. Of particular intrigue and importance to the idea of prolonged engagement is that the interviews, up to two hours in length, took place while participants were hospitalized for their high-risk pregnancies.

Interviewing in Practice

Consider the following example in which we apply epoche and in-depth interviewing to a phenomenological question.

Question

Response

Restate your phenomenological research question.

What is the lived experience of stress for first-year college students during exam week?

Epoche: What previous knowledge, experiences, theories, or worldviews do you need to set aside, or carefully consider, before you investigate this question? Why?

My own experiences of exam week, especially from my freshman year, were harrowing. In one case, I got very sick because the stress was just so bad. I have always wondered how some students navigate the week with seeming ease. That was never me. I’m less interested in those narratives, though, because I want to bring to the surface a deeper understanding of what people like me have endured. In a way, hearing others’ stories may help me understand my own.

I think I need to set aside my own strong bias that final exams cause more harm than good. I don’t think exams really assess learning in the right ways. Maybe there are people who experience stress who really love the drive, fervor, and more that exam weeks bring. I know I cannot really bury my own opinions, but I can be sure to create a space in the interviews for others’ stories to emerge.

In-depth interviewing: In what ways might deep, prolonged interviews help you address your research question?

Well, stress is a complex phenomenon in and of itself. And I’m looking particularly at stress as experienced by a certain group, freshman, as it may relate to exam week. In-depth interviewing could allow for rapport-building, an opportunity for participants to share their experience as they’re going through it, and perhaps even a second interview (after exam week) when there’s opportunity for even deeper meaning-making.

Mirroring the work we did in the preceding example, on a piece of paper, in a journal, or in another app, write out a reflection on your positioning as it relates to a qualitative research question that interests you. Answer each of the three reflective questions and save your answers for later reference.

  1. Restate your phenomenological research question.

  2. With regard to epoche, what previous knowledge, experiences, theories, or worldviews do you need to set aside, or carefully consider, before you investigate this question? Why?

  3. With regard to in-depth interviewing, in what ways might such deep, prolonged interviews help you address your research question?

Unveiling Story

In the photograph, a happy and cheerful 85-year-old Native American Navajo grandmother poses for a portrait on a dirt yard in Monument Valley Arizona. Consider the powerful, poignant stories shared, exchanged, and retold by this grandmother to her family: not only those of the present, but those that are centuries old, recounted amongst generations.

Narrative Inquiry: Unveiling Story

Narrative inquiry is the methodology of storytelling and uncovering meaning from stories. That is, the human experience is studied through stories. Narrative researchers are interested in the ways that stories help us make meaning of our humanity: past, present, and future. Narrative inquirers explore the stories of one or more participants to unearth thematic elements. In some cases, researchers also study their own stories. Data may come from interviews, letters, autobiographies, diaries, and other artifacts.

Quayle and Sonn (2019) used narrative inquiry to “amplify” the voices of indigenous elders in Australia. Specifically, they aimed to “identify the shared community narratives evident across the [elders’] stories” (p. 51). The abstract of their narrative inquiry is below. As with the section on phenomenology, we will utilize the Quayle and Sonn example, among others, to illuminate the distinctive characteristics of narrative inquiry. We will also present a brief history of narrative inquiry, tracing its evolution. Then, we will examine the kinds of questions narrative researchers seek to answer, while exploring some methodological practices utilized.

Researchers and practitioners in community psychology have an important role to play in supporting decolonial work including promoting opportunities for reclamation, healing, and acknowledgment of history. In this article, we discuss research undertaken alongside a community arts and cultural development project that sought to support Aboriginal people in Western Australia to create an archive of their stories for current and future generations—stories that could serve as resources for healing, reclamation, and for examining a painful and unjust past. Narrative approaches have been promoted in community psychology to advance empowerment research and practice alongside marginalized, excluded, and minoritized groups. We report on findings from a critical narrative inquiry of the stories shared through the project and in conversational interviews with four Noongar Elders to explicate the history and ongoing legacy of racialized oppression in their lives as well as cultural continuity and survival evident in the stories.

Like phenomenology, narrative inquiry is complex and multi-faceted. At the graduate level, one can take an entire course devoted solely to the study and practice of narrative research. We will focus on how narrative techniques have been developed and are used presently by psychologists.

Narrative inquiry has vast grounding in both the humanities and the social sciences. Within psychology, Wertz and colleagues (2011) note, “there is no single figure to whom one could attribute the narrative research tradition” (p. 63), though various influencers abound (e.g., psychologists Don Polkinghorne, Jerome Bruner, Ruthellen Josselson, James Christopher Head, and Mark Freeman).

Today, narrative inquiry “takes as a premise that people live and/or understand their lives in storied forms . . . . These stories are played out in the context of other stories that may include societies, cultures, families, or other intersecting plotlines in a person’s life” (Josselson, 2011, p. 224). Such stories have beginnings, middles, and ends about the past, present, and future; stories, individually and on the whole, become meaning-making endeavors for participants.

Narrative research focuses not on “facts” or “objective truths” but on stories as they are lived by those sharing their experiences. In this way, narrative inquiry is inherently constructivist. Narrative inquiry draws from a variety of methodological traditions, often overlapping with other qualitative research traditions. Further, narrative inquiry can be transformative, providing platforms for people who have been marginalized, oppressed, and sidelined to tell their stories.

Narrative Inquiry Questions

Clandinin and Connelly (2000) suggest that those who understand the world narratively might also be those drawn to research the world using this approach. Like phenomenologists, narrative researchers inquire into lived experiences. In lieu of seeking to study the unchanging essence of a phenomenon, narrative inquirers bring to the surface nuances of the lived experience as told through open-ended storytelling. Stories formulate the sources that narrative inquirers analyze.

Consider a project that investigates the lived experiences of college students who have ADHD. Whereas the phenomenologist explores ADHD as a phenomenon to be explicated, the narrative inquirer seeks to generate meaning by eliciting detailed stories that reveal how participants understand their ADHD. Further, the narrative inquirer looks not just as what is told, but also to how it is told.

Quayle and Sonn (2019) collected narratives from some of the Noongar people, an Aboriginal culture in southwestern Australia. Older Noongar people remember a time when they were not allowed to enter towns or cities, a time when many Noongar babies, sometimes known as bush babies, were born outdoors with limited or no shelter. A project called Bush Babies was undertaken to honor these people along with the midwives who helped in their births. Quayle and Sonn used this research question to guide their study: “What are the narratives through which Noongar people involved in the Bush Babies project give meaning to their past, present, and future and what are the key themes in these stories?” This question makes it clear that the locus of data collection is the narrative, situated in past, present, and future contexts.

Here’s another example. Dayal, Buck, and Clandinin (2021) conducted a study of counselor trainees’ experiences of working with trauma. Two questions were posed: “How have counselor trainees’ past experiences shaped the ways they approach trauma survivors? How have counselor trainees been shaped by their experiences of working with trauma survivors?” To explore these queries, the research team posed guiding questions during their conversational interviews, like: “Looking back over your experiences prior to, and during, your training to be a psychologist, what stories can you recall of your work with clients who experienced trauma” (p. 476)?

Going back to the earlier example that involves investigating students’ lived experience of stress, let’s see how this might be recast as narrative inquiry:

  • Phenomenology: What is the lived experience of stress, for first-year college students, during exam week? The researcher may invite open-ended reflections, perhaps through a series of interviews, regarding experiences of stress, the meanings that arise from stress, and participants’ understanding of stress during exam week.

  • Narrative inquiry: What stories, either those told to oneself or those conveyed externally, shape first-year students’ experiences of stress during exam week? The researcher invites the telling of stories, through interviews and other methods, focusing both on what is told and on how the stories are conveyed.

Narrative Inquiry Practices and Psychological Scenarios

Given the vast, multidisciplinary nature of narrative research, even within the field of psychology, no one particular practice straddles every narrative study. However, there are some practices that will help novice inquirers understand some of the methodological processes involved, including self-narratives, first person artifacts, and three-dimensional space.

Self Narratives

Definition

There are many types of narratives that researchers analyze, among them the self-narrative. This narrative may take the form of an autoethnography or an autobiography. The autoethnography, in particular, explores one’s personal story as it exists within a broader framework. Even “storied poems” written as autobiographical accounts can be thought of as self-narratives (Clandinin & Connelly, 2000).

Scenario

Evans (2020) wrote an autobiographical narrative inquiry of birth trauma; she had delivered twins through an unplanned cesarean section, with an ineffective epidural procedure, and sought to explore her story through the lens of Adlerian psychology. As noted, “The narrative analyzed for this study tells the story of the resulting experience” (p. 363).

First Person Artifacts

Definition

First person artifacts augment individuals’ story-sharing experiences. These can be diaries, letters, and even memory boxes: “These are collections of items that trigger memories of important times, people, and events” (Clandinin & Connelly, 2000, p. 114). Even a place wherein a story took place (e.g., a classroom) can serve as a memory box of sorts.

Scenarios

Dayal et al. (2021) used more than interviews; they also analyzed annals (timelines), memory box items, and field notes. “Participants shared memory box items as triggers for memories of important times… For example, when Jennifer’s elementary school emerged as a significant place within her stories, Author 1 proposed visiting her school together to further explore this memory box item.” (p. 477).

Quayle and Sonn (2019) describe the importance of artifacts in documenting lived experiences. They detail intergenerational storytelling workshops, wherein elders were “sharing stories about their lives with young Aboriginal media studies students, who were then supported to create short videos using photographs…” (p. 49). Elders’ stories were later showcased in a museum.

Three-Dimensional Space

Definition

The three-dimensional inquiry space is a framework that represents and helps us analyze facets of the stories shared. As Clandinin and Connelly (2000) wrote, the three-dimensions are:

  • interactions within stories (personal and social);

  • temporality (i.e., stories are past, present, and future); and

  • situation (i.e., stories take place within a context).

Skilled narrative inquirers take the time to locate, and also analyze, these dimensions, seeking to explicate the storylines and themes that they represent.

Scenarios

Evans (2020) explored her experience of trauma through stories that focused on temporality (e.g., past and present), social interaction (e.g., with medical professionals), and context (e.g., hospital).

To add, Dayal et al. (2021) highlighted the dimensions during their analysis: “As participants told stories…it was possible to see how their understandings of trauma were woven into their lives as they were shaped over time, across multiple experiences, places, and encounters with people” (p. 482).

Finally, Quayle and Sonn (2019) conveyed narratives that bring temporality to life: “to understand the historical and contemporary experiences of racialized oppression, and how people resist and survive oppression” (p. 52). The authors identify “narrating circuits'' of how dispossession affects lives, historically and presently.

Narrative Inquiry Revisited

As a qualitative method, narrative inquiry uncovers the meaning of lived experiences from narratives through storytelling. Narrative researchers elicit stories from small groups of participants (through interviews and various artifacts, like memory boxes). In the table that follows, you can contrast narrative inquiry with phenomenology.

Characteristics of Research Methods

Research Method

Purpose:

Focus?

Researcher’s Role?

Unique Practices?

Form:

Outcome?

Narrative Inquiry

To tell and study human experiences through story.

The researcher positions oneself, and may be co-located as both the primary instrument and a participant.

- Self-narratives (e.g., autoethnography)

- First person artifacts

- Three-dimensional inquiry space

Varies widely. Stories can be published intact, or may be analyzed for “storylines” (thematic elements) across participants. Stories may also be analyzed for their resonance with existing theories (e.g., feminist theory).

Phenomenology

To understand the essence (meaning) of lived experiences with phenomena.

The researcher attempts to suspend judgment, through epoche, and serves as the primary instrument.

- Epoche

In-depth interviewing

- Phenomenological reduction*

- Imaginative variation*

* Indicates topics that will be explored later in the section on data analysis.

Experiences, as data, are reduced to essential themes. The outcome describes the “essence” of the phenomenon being investigated.

End block quotation
End block quotation
African-American mother hugging her son
Block quotation
Block quotation
Block quotation
End block quotation
This is an image of a woman looking at herself in a mirror.
This is an image of a memory box containing photographs.
an image of an individual standing in an abstract red, curved architectural space.
This is an image of a woman interviewing a man.
A  young pregnant woman in consultation with her female doctor.
A cheerful 85-year-old Native American Navajo grandmother posing for a portrait in Monument Valley Arizona.