Expanding Frameworks: Conducting Discourse Analysis in Counseling Research

The Qualitative Report The Qualitative Report

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Expanding Frameworks: Conducting Discourse Analysis in Expanding Frameworks: Conducting Discourse Analysis in

Counseling Research Counseling Research

Chloe Lancaster

University of South Florida

, [email protected]

Melissa J. Fickling

Northern Illinois University

, [email protected]

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Recommended APA Citation Recommended APA Citation

Lancaster, C., & Fickling, M. J. (2024). Expanding Frameworks: Conducting Discourse Analysis in

Counseling Research.

The Qualitative Report

(4), 953-967. https://doi.org/10.46743/2160-3715/

2024.6184

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Expanding Frameworks: Conducting Discourse Analysis in Counseling Research Expanding Frameworks: Conducting Discourse Analysis in Counseling Research

Abstract Abstract

Discourse analysis encompasses a variety of disciplinary approaches that broadly aim to understand how

individuals and groups use language to construct and maintain their psychological and social realities. A

central concept in discourse analysis is we all use discourse to accomplish our communication goals

despite being unaware of most discourses we evoke. While discourse studies could help counseling

professionals to better understand how they deploy discourses to maintain identities, inequalities, and

status quo, the method is not well-represented in counseling research in the United States. This

methodological guide presents an introduction to discourse analysis and an overview of the analytic

framework, highlighting discourse studies conducted germane to counseling research and practice.

Keywords Keywords

discourse, discourse analysis, qualitative research, methodological guide

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The Qualitative Report 2024 Volume 29, Number 4, 953-967

https://doi.org/10.46743/2160-3715/2024.6184

Expanding Frameworks:

Conducting Discourse Analysis in Counseling Research

Chloe Lancaster

and Melissa J. Fickling

Department of Leadership, Policy & Lifelong Learning, University of South Florida, USA

Department of Counseling and Higher Education, Northern Illinois University, USA

Discourse analysis encompasses a variety of disciplinary approaches that

broadly aim to understand how individuals and groups use language to construct

and maintain their psychological and social realities. A central concept in

discourse analysis is we all use discourse to accomplish our communication

goals despite being unaware of most discourses we evoke. While discourse

studies could help counseling professionals to better understand how they

deploy discourses to maintain identities, inequalities, and status quo, the method

is not well-represented in counseling research in the United States. This

methodological guide presents an introduction to discourse analysis and an

overview of the analytic framework, highlighting discourse studies conducted

germane to counseling research and practice.

Keywords: discourse, discourse analysis, qualitative research, methodological

guide

Introduction

Discourse analysis (DA) examines how language is used in everyday contexts to

construct social and psychological realities (Willig, 2014). As a profession that utilizes

language in the form of therapeutic dialogue, professional counseling is well-suited to make

use of DA as a method for clinical research (Spong, 2010). DA has been presented as

deconstructive criticism as it entails the identification of discourses, their function, and

exploration of whom they include and exclude (Gee, 2010). Within this tradition, discourse

analysts trace how speakers appeal to culturally and temporally informed discourses to

maintain identities, statuses, and social schisms (Goodman, 2017). Despite this commonality,

DA has been utilized by scholars from a broad range of disciplines for slightly different

purposes, using an array of analytical practices (Stead & Bakker, 2010) and has been discussed

as one of the most complex qualitative methods to learn (Goodman, 2017). Thus, it is

unsurprising that it rarely appears in peer-reviewed counseling journals (Hays et al., 2016) or

in counselor education qualitative methods courses (Borders et al., 2014). This paper aims to

define DA, discuss the method's applicability to Counseling research, and provide a thorough

description of the method with the intent that scholars in the counseling field may consider

how DA could augment their existing research agendas.

What is Discourse Analysis?

DA is a theoretical approach to knowledge production and both a qualitative and

quantitative method for studying discourse. The term discourse is vague, with multiple

overlapping, and competing meanings (van-Dijk, 1997). Researchers have used it to describe

speech at the sub-sentence level, whereas others have emphasized discourse as a broad system

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of rule-bound communication (Coupland & Jaworski, 2001). In this paper, we focus on DA as

a qualitative method and refer to the term “discourse” as talk and language in action (Wood &

Kroger, 2000) sensitive to the interactional context in which it is produced (van-Dijk, 1997).

The origins of DA are rooted in the disciplines of linguistics, linguistic philosophy,

social anthropology, and theoretical sociology (Coupland & Jaworski, 2001), and as an

approach that has evolved in different epistemology traditions, DA is marked by heterogeneity.

Theoretically, it is closely aligned with the post-modern approach of social constructionism, as

it emphasizes how language is used to construct reality via social exchanges (Coupland &

Jaworski, 2001). Yet, DA moves beyond social constructionism by asserting that language is

simultaneously shaped and constricted by systems of discourse that reflect temporal structures

of power, knowledge, and ideology (Stead & Bakker, 2010). As we outline considerations for

conducting DA, we highlight the methods outlined by discursive psychology (Potter, 2012;

Willig, 2014) and sociolinguistics (Gee, 2010), respectively. Blending approaches to DA is an

accepted practice in DA, and as Potter (2003) asserts, “DA is neither a self‐contained paradigm

nor a stand‐alone method and can be easily mix‐and‐matched with others” (p. 787). Both

discursive psychology and sociolinguistics focus on talk and the effects of talk on everyday

exchanges, identity, and balance analysis of the interactional process with broader structural

considerations (Gee, 2011), which may offer the greatest utility to practitioners and counseling

outcome researchers.

DA assumes that we are all carriers of discourse and that every social interaction is

discourse laden (Spong, 2010). We inherit discourse from our cultures and subcultures. The

way we receive, reproduce, and create discourse is influenced by a complex set of power

relations comprised of norms, written and unwritten rules, and mental models of acceptable

behavior (Parker, 2005; Willig, 2014). While discourse permeates all our social interactions,

we are largely unaware of the discourses we absorb and, in turn, evoke through our verbal,

non-verbal, and text-based interactions. In this regard, communication is not viewed as a mirror

of reality (Spong, 2010), which has implications for the analytical method, as outlined ahead.

Nonetheless, in DA, communication is seen as performative and intended to accomplish a

specific purpose by a speaker in a specific context (Spong, 2010). While communication is

constructive, the goal of the DA method is deconstructive, as analysts aim to identify the

discourses evident in a social exchange, how the speaker/s construct or position themselves

within a discourse, and the implication of these positions for self and others (Stead & Bakker,

2010). For those of us who operate within a post-modern framework, either as counseling

practitioners, researchers, or educators, DA offers the tools to understand how everyday

interactions become a stage for the reconstruction of social power differentials, which in turn

can help sharpen our multicultural and social justice lenses.

Discourse Analysis for the Counseling Profession

The Multicultural and Social Justice Counseling Competencies (MSJCCs; Ratts et al.,

2015) provide a framework to address issues of oppression impacting clients. Central to the

MSJCC model is counselor self-awareness and valuation of diverse and divergent ideas and

perspectives. DA is aligned to MSJCCs as knowledge of those discourses within which we

operate can help us to trace our biases and interrogate our assumptions, which may contribute

to more competent and empowering counseling practice (Georgaca & Avdi, 2012; Stead &

Bakker, 2010). For example, racist, patriarchal, ableist, and cis-sexist discourses have inflicted

harm upon minoritized communities and individuals. Over the past 20 years, a heightened

awareness of the stigmatizing effect of dehumanizing language has led many counselors across

all levels of practice to adopt the discourses of person-first language, a linguistic practice that

emphasizes the person rather than their diagnosis, disability, or other stigmatized label

Chloe Lancaster and Melissa J. Fickling 955

(Granello & Gorby, 2021). Studying counseling discourses is thus a form of consciousness-

raising (Georgaca & Avdi, 2012) to aid our understanding of what discourses we use across

professional contexts to position ourselves and others, as well as the critical implications of the

discourses we deploy (e.g., who do our discourses privilege or exclude; Parker, 2005). In this

respect, DA can help us to reveal the spoken and unspoken rules inherent in the counseling

profession. Gee (2015) described discourse as an “identity kit” (p. 142), replete with rules for

what to wear, write, and how to appropriately express oneself. For example, how do we come

to be seen as counselors? What language/discourses do we need to engage in? What clothing,

behaviors, mannerisms, or values do we use to perpetuate our being perceived and received as

counselors?

As an approach that examines both the form and function of language, DA yields clues

to how status and power are perpetuated through commonplace social interactions and

established practices (Gee, 2011) and can aid us in thinking critically about the counseling

profession overall. Stead and Bakker (2010) observed that our counseling discourses can

privilege certain groups and exclude others. Highlighting discourses implicit in the practice of

career counseling, Stead and Bakker suggested they “cohere” (p. 75) to values of individualism,

which are more likely to be held by middle-class, predominately White clients. By contrast,

minority groups who operate within a framework of collectivistic discourses may find career

counseling’s focus on individual advancement incompatible with their worldviews (Stead &

Bakker, 2010). As noted by these researchers, understanding the power imbalance inherent in

our own professional discourses can lead to more critical social justice-oriented practices.

Granello and Gibbs (2016) further illustrated the power of language by demonstrating how a

person-first discourse improved counselor empathy. Although not ostensibly a discourse

analysis, their findings revealed that counselors-in-training who completed a tolerance scale

exhibited greater intolerance if instrument items referred to clients as “mentally ill” in

comparison to the sample who completed the same assessment in which items referred to

clients as “individuals with mental illness” (Granello & Gibbs, 2016).

Mapping the connections between language and power has relevance for policy studies

in counseling. Of note, DA analyzes how powerful agencies legitimize discourses of

knowledge by producing and disseminating information and, in turn, citing this material as

evidence of its truth (Georgaca & Avdi, 2012). Given the prominence of intermediatory

organizations in counseling (e.g., counseling associations, accreditation bodies, counseling

boards), it would seem prudent to understand how they promulgate discourses that are

subsequently edified through their standards and licensure rules. One example of how

intermediary organizations dominate their field-specific discourse could be drawn from the

American School Counselor Association (ASCA), the largest school counseling association in

the world, and instrumental in shaping policy and practice contexts both in the US and overseas

(Lambie et al., 2019). Notably, in recent years, the ASCA has emphasized that the primary role

of school counselors is to use data to promote students' academic achievement. This

construction is scaffolded through their professional standards, published research, and practice

models. Within this discourse, school counselors are situated in the roles of prevention,

preliminary intervention, and crisis response specialists, with long-term mental health issues

diverted through referral to other professionals and systems. Scholars have argued that ASCA’s

construction of the school counselor diminishes their role as mental health experts and, in turn,

disenfranchises school counselors from their identity as mental health providers (Lambie et al.,

2019).

To demonstrate variation in DA approaches to studying this type of social phenomenon,

a critically oriented discourse analyst may examine the (powerful) institutional mechanisms at

play in the ascent of ASCA’s construction of the school counselor and who benefits from the

discourse (e.g., Fairclough, 2001; Rodgers, 2011). Conversely, a discursive psychologist may

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consider how ASCA’s discourse restricts both school counselors and students from engaging

in the social roles associated with the therapeutic dyad (e.g., Parker, 2005; Potter 2012, Willig,

2014).

Our Positionalities in Writing this Paper

Understanding our motivation to author a “how-to-guide” for DA in counselor

education can be best explained by our connection to the method. My interest (Chloe’s) in

qualitative inquiry and constructionism is rooted in my undergraduate studies in cultural

anthropology in the UK and my work as a researcher and international counselor educator in

the USA. I was drawn to discourse analysis as I believe the approach offers useful tools for

revealing the hermeneutic assumptions of the counseling field, the social construction of the

therapeutic process, as well as exploring how language shapes successive waves in the

counseling field. I’ve also taught a doctoral-level discourse analysis class, which has furthered

my interest in unpacking complex aspects of the method for the next generation of scholars to

continue and expand the DA tradition.

Melissa’s interest in qualitative inquiry began in her work in women's and gender

studies coursework during her Ph.D. studies in counselor education. Melissa describes herself

as a White, cis-hetero, able-bodied, fat woman centered in many discourses while being

marginalized in others. Discourse analysis allows her to both locate herself and to see the ways

in which she is constrained or included in the discourse by those around her—students, clients,

supervisors, professors, peers, and neighbors. As a practitioner-turned-academic, she continues

to become aware of the ways in which discourses about health, wellness, and healing function

to maintain power structures. Melissa believes professional counselors and clinical supervisors

have an ethical duty to analyze the discourses they use and those in which they operate, hence

her interest in understanding this methodology more deeply. Finally, she appreciates the ways

that discourse analysis encourages mutuality and collaboration between co-investigators,

including in a methodology piece like this.

Overview of the Discourse Analysis Method

In the following section, we will outline the overall DA research methodological

process covering (a) a priori knowledge; (b) research questions; (c) mediums of analysis; (d)

sample/corpus; (e) analyzing data (re-reading, transcribing, coding); (f) representation of

findings; and (g) trustworthiness. Throughout the paper, we connect the DA process to

examples of studies in counseling and related fields. Given the relative dearth of DA

publications in counseling journals in the US, the preponderance of studies highlighted in this

paper were conducted overseas, where DA is better represented in the literature. We do not

intend to propose a formulaic approach to data analysis. DA scholars have historically

eschewed standardization to preserve the flexibility and creativity of the DA method (Gee,

2010; Rodgers, 2011; Willig, 2014). However, by outlining established practices in analytical

traditions associated predominately with discursive psychology and sociolinguistics (Gee,

2010, 2011; Georgaca & Avdi, 2012; Goodman, 2017; Potter, 2012; Willig, 2014), we aim to

build knowledge of DA and, in turn, open new avenues for future scholarship.

A Priori Knowledge

Although it is common in qualitative research for investigators to suspend their

knowledge and a priori assumptions to ensure that findings emerge from the voice of the

participants and not the researcher (Patton, 2015), this is not the case in DA. In brief, the

Chloe Lancaster and Melissa J. Fickling 957

accuracy of one’s analysis, central to a trustworthy study, hinges upon the analyst's knowledge

of prominent discourse registers available to individual actors (Schneider, 2013). Of note, DA

includes not only a description and interpretation of discourses in context but also explanations

for how these discourses connect to historical precedents and contemporary influences (e.g.,

social structure, institutions, group norms, cultural beliefs, practices, paradigms of knowledge),

all of which inform and restrict human communication (Gee, 2010).

Therefore, researchers commence DA by identifying influential discourses that have

shaped and sometimes engendered the discourse under study (Schneider, 2013). Not all

discourses are equally relevant or influential; thus, a central concern in DA is how specific

discourses ascend into "master models” (Gee, 2010, p. 69) of discourse and their ensuing

effects on specific populations. Gee (2010) described these as “Big D” discourses, “ways of

behaving, interacting, valuing, thinking, believing, speaking, and often reading and writing,

that are instantiations of identities (or ‘types of people’) by specific groups” (p. 3). Gee

contrasts Big D’s with “little d’s,” seemingly inconsequential, everyday language in use.

Integral to data analysis (addressed below) is a researcher's skill in describing how Big D’s

influence the construction of little d’s, and conversely, how little d’s reveal clues about the

nature of Big D’s (Gee, 2010, p. 6). Establishing the historical context and discourse layers

surrounding the topic under investigation is essential in both design and data analysis

(Schneider, 2013).

Although it is unlikely that analysts can unveil every contextual factor relative to the

discourse under study, to the greatest extent possible, all related and dynamic forces of

discourse should be mapped in advance of the actual data analysis process. Schneider (2013)

recommends brainstorming all sources of influence and asking oneself: By whom were they

produced? For what reason? And to what effect? Professional counselors, for example,

represent a cultural group comprised of multiple subgroups (e.g., clinical, school, addiction,

rehabilitation) with their discourses of implied meanings, values, and standards of practice

(Spong, 2010). Thus, a researcher conducting a DA focused on counseling would need a

multifaceted knowledge of the counseling profession (e.g., history, professional and ethical

standards, accreditation requirements, licensure and credentialing, counseling theory) to

understand how the discourse actors under study (e.g., counselors, supervisors, counselor

educators, counselors-in-training) build discourse to accomplish essential professional tasks

and activities, such as counseling and clinical supervision.

Research Questions

Research questions considered appropriate for DA inquiry both depart and converge

from standards of qualitative research practice. The most notable difference is that DA research

questions investigate how realities are constructed beyond the level of words and not

participants' meaning-making processes, lived experiences, or perceptions of reality (Georgaca

& Avdi, 2012). Yet, like other methods of inquiry, an effective DA begins with a question

sufficiently narrow in scope to be operational (Schneider, 2013). Counseling-related DAs have

typically posed two or more questions related to (a) What discourses are evident in counseling

and supervision? and (b) What are the consequences of the discourses upon the social

relationships? In Reeves et al.'s (2004) analysis of suicide as a discursive object, the researchers

asked, "How do counselors deal with suicide risk? and "What are the implications for clients”

(p. 2)? In their study of discursive strategies deployed in email supervision, Luke and Gordon

(2011) asked, "What are the discursive strategies used within email supervision by master's

level counseling students?” (p. 278) and "How do these discursive strategies function?” (p.

278).

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Mediums of Analysis

A closely related step in the DA process is identifying a medium to study. DA is

demarcated from other forms of qualitative inquiry by the array of mediums suitable for

analysis. Parker contended in DA, "We consider all tissues of meaning as texts, including

speech, writing, non-verbal behaviour, Braille, Morse code, semaphore, runes, advertisements,

fashion systems, stained glass, architecture, tarot cards and bus tickets" (Parker, 1992, p. 7).

With the ascent of digital communication, we could add to this list: emails, social media posts,

blogs, flyers, text messages, and websites, to name a few. In the counseling field, transcripts of

therapy sessions have been a popular medium of analysis as researchers can highlight

discourses deployed by the helper and helpee (therapist and client or supervisor and supervisee)

to construct their respective roles and examine how language use shifts at different stages in

the counseling/supervision process (Asku, 2014; Patrika & Tseliou, 2016). In terms of digital

text, analysts have examined how email supervision between supervisors and supervisees

accomplished the complex tasks of supervisee development and case consultation (Luke &

Gordon, 2011). Given the wide range of text data that can be examined in DA, it is also prudent

to craft research questions that designate or implicate a specific medium for study. Gordon and

Luke (2016) delimited their source material by positing a research question that examined the

discursive use of the pronoun "we" in email correspondence between supervisors and

counselors in training. Similarly, in the study of the discursive negotiation of diagnostic labels

during therapy sessions, Avdi (2005) designated transcripts of therapy sessions as the medium

for analysis in the research questions.

Interview Data

Though there is a history of utilizing interviews in DA, two challenges are associated

with this type of data (Potter & Hepburn, 2005). First, much of the discourse we receive and

reproduce is latent (McGregor, 2004), thus challenging the utility of questions that call upon

participants to articulate the nature of their reality. Second, analysts are interested in capturing

participants' natural language, yet interviews have been discussed as contrived settings (Wood

& Kroger, 2000) in which participants' language markedly differs from their everyday language

in use (Potter, 2012; Potter & Hepburn, 2005). Some authors have suggested that focus group

discussions address some of the limitations of individual interviews, as the researcher can

remain relatively unobtrusive while allowing participants to deliberate on an issue, discover

shared and divergent perspectives, and collectively make sense of their experiences (Hollin &

Larkin, 2011).

Furthermore, when analyzing interview data, Gee (2010) cautioned researchers from

assuming participants mean the same thing as the researcher even when they use the same

words in an interaction. Gee recommended that researcher interactions be included in the

analysis to trace how the researcher shaped the co-construction process. Thus, while both

interview and focus group data are permitted in DA, analysts should be prepared to articulate

a rationale for their design decisions and how the discourses generated in the interview milieu

may have affected the data analysis and, hence, the overall results and implications of the study

(Potter & Hepburn, 2005).

Sample/Corpus

Identifying an appropriate sample to study is complicated in DA due to the variety of

communication data suitable for analysis. Given that analysts often use text-based (non-speech)

data, the term corpus is often used in place of the term “sample” (Goodman, 2017). What

Chloe Lancaster and Melissa J. Fickling 959

constitutes an adequate corpus size in DA is ambiguous (Goodman, 2017). The size of a study’s

corpus is not considered a reliable indicator of high-quality analysis, as an extensive data set

can obscure methods through which discourse "actors" appeal to different discourses to

construct an argument or position themselves relative to the topic under study (Schneider,

2013). According to Starks and Trinidad (2007), appropriate corpus size depends on the

analytic objective and the data source. Researchers are encouraged to incorporate a wide range

of data into the analyses, and as discussed by Schneider (2013), a good DA is signified when

researchers explain what texts they used, where they came from, and why they chose them.

Thus, it is reasonable to use a single person's narrative and compare it with written documents;

alternatively, a larger corpus might be required to understand variations in language in use

across discourse actors and settings (Starks & Trinidad, 2007). Hollin and Larkin (2011)

contrasted speech data from a single focus group of social workers with governmental foster

care policy documents to illuminate the emasculating influence of powerful discourse in the

workplace. Conversely, Kennedy-Lewis (2014) amassed policy documents from 50 states to

contrast the competing discourses put forth by policymakers to account for why school

discipline policies disproportionally impacted minority youth.

Variation in sample or corpus size is evident in those DAs conducted within counseling

and related fields (see Davis & Lester, 2016; Evans & Radina, 2014; Gordon & Luke, 2016;

Knight et al., 2012). In general, researchers who have used speech data as the medium of

analysis utilized a smaller corpus. This design decision attests to the meticulous detail involved

in coding and analysis, as we will describe in the transcription section. For example, those

researchers who utilized therapy sessions as their medium of analysis have used a smaller

corpus, ranging from nine (Patrika & Tseliou, 2016) to twelve (Avdi, 2005) transcripts of

counseling sessions. By contrast, written documents require much less annotation, and

researchers using this medium of analysis use a larger corpus. For instance, Gordon and Luke

(2016) gathered 475 emails derived from exchanges between 23 supervisees and two

supervisors over a semester.

Data Analysis

Once data collection is completed, researchers begin to organize and analyze data. In

brief, data analysis aims to (a) identify the discourses evident in communication data, (b)

analyze how discourse actors justify their positions through the purposeful (re)construction of

the discourse, and (c) interpret the function of these discourse positions. This requires analyzing

patterns in data beyond the surface level of meaning conveyed by the participants, a process

often perplexing for researchers new to DA, especially those experienced in qualitative inquiry

based on thematic data analysis (Starks & Trinidad, 2007). Researchers looking for guidance

from literature may be further confounded by the dearth of formal guidelines and the absence

of standardization (Goodman, 2017). In this methodological guide, we highlight data analysis

approaches credited to sociolinguistics (e.g., Gee, 2010) and discursive psychologists (e.g.,

Goodman, 2017; Potter, 2012; Willig, 2014). Both provide well-documented approaches that

balance the analysis of the spoken and written word with the nuances of context and the

backdrop of larger social discourse. Within these traditions, analysts have demonstrated

variability in their methods. Yet, both approaches lend to a two-fold process consisting of (a)

data analysis: repeated readings, transcription, and coding for the discursive strategies and (b)

interpretation of the function of the discourse related to the research question (Potter &

Wetherell, 1987; Willig, 2014).

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Repeated Reading of Text

Willig (2014) described the first stage of analysis in DA as familiarity with one's data.

In DA, repeated reading of one's data is considered a crucial stage of data analysis, particularly

for researchers using digital and print data, which does not require transcription. During re-

reads, Goodman (2017) recommended that analysts focus their attention on the speaker's action

orientation, or as described by Potter, "What is the business being done in talk?" (Potter, 2003,

p. 73). Goodman (2017) further suggested that because a data set will contain numerous "action

orientations" (p. 147) irrelevant to one's research question, analysts should record their initial

thoughts about the data and begin to cull their data set by extracting relevant excerpts into a

separate document.

Transcription

Through transcription, analysts are tasked with illustrating how a speaker constructs

their situated meaning using verbal and nonverbal, referred to as prosodic (e.g., tone, rhythm,

intonation stress, etc.) elements of speech. Gee (2010) contends transcription is integral to data

analysis, as it involves an interpretive process of how to represent data for the analyst's

purposes. The process can be exceptionally time-consuming, requiring up to 20 hours to

transcribe one hour of speech data (Potter & Wetherell, 1987). To begin, Gee (2010)

recommended transcribing interview data to mirror the production of ideas in a sentence to

help reveal the thought processes of the speaker. For instance, although the human ear discerns

speech in one elongated stream of thought, individuals produce speech in short idea units,

consisting of a single clause in a longer sentence. Thus, individual sentences should be broken

up into participants' idea units in transcription. This can be accomplished by recording data

verbatim (using the default line of a text document) and then repeatedly listening to deconstruct

a chunk of data into individual idea units. All lines should be numbered to demonstrate how

one’s findings connect to a single line or section of the data (Goodman, 2017). Gee (2010)

further recommended organizing idea units into stanzas distinguished by a simple theme, so

transcriptions take on the form of a poem or segment of prose. Discerning which idea unit

belongs within a stanza is subjective; however, analysts should pay close attention to how the

speaker uses content (e.g., grammatical words) and function words (words that link grammar)

to connect ideas and make certain information salient.

Analysts using speech data typically employ a coding system to annotate a transcript.

The Jefferson Convention is considered the gold standard for annotation of speech data due to

the meticulous level of detail it affords (Goodman, 2017); however, more user-friendly is

Kogan's (1998) list of symbols for transcript annotation. While there are no rules regarding the

level of detail to which a transcript is coded, Gee (2010) suggested annotating transcripts with

more detail than required. Transcripts coded with a high degree of detail are referred to as

"narrow," whereas those coded with less detail are described as "broad" (Gee, 2010, p. 88). To

assist the reader in decoding a marked-up transcript, analysts should include an annotation key

in their manuscripts. For exemplifiers of broad and narrow transcripts of therapy sessions, see

Patrika and Tseliou (2016) and O'Reilly (2015), respectively.

Preliminary Codes

Prior to formal analysis, some analysts have suggested conducting a preliminary coding

of the data, wherein analysts record their initial thoughts about the data relevant to the research

question (Goodman, 2017). Potter and Wetherell (1987) suggested that researchers refrain from

deploying higher-order analytical techniques, and categories should be fluid, flexible, and

Chloe Lancaster and Melissa J. Fickling 961

inclusive of all data, even vague cases. We propose that a preliminary coding system may be

helpful when researchers use text-based data that has not undergone the rigors of transcription.

Further, preliminary coding may be useful for researchers exploring a theory-driven research

question or one that examines a specific function of speech. For example, if a researcher were

conducting a DA informed by family systems theory, it would be reasonable to focus one’s

preliminary codes on elements of the data that spoke to aspects of the theory, such as evidence

of family triangulation or and homeostasis (see Avdi, 2005; O’Reilly, 2015; Patrika & Tseliou,

2016). Alternatively, researchers investigating the discursive use of the pronoun “we” in a

corpus of emails (see Gordon & Luke, 2016) may direct their coding efforts to where this term

crops up in the data. In this regard, preliminary coding can be used as an organizational tool to

set boundaries around the data as a precursor to analysis.

Coding for Discursive Strategies

A salient approach to data analysis is to code for discursive strategies and involves a

higher level of abstraction than preliminary coding. Discursive strategies consist of any

linguistic and paralinguistic device a speaker utilizes to construct a position. Willig (2014)

recommended that analysts identify discursive strategies by posing a series of questions

focused on the constructive and functional dimensions of the data, such as: What subjects

(topics) and objects are selected? How does the speaker use communicative strategies (e.g.,

nomination, restriction, turn-taking, topic control, silence), and to what effect? In addition to

line-by-line identification of discursive strategies, analysts attend to how a speaker builds

discourse by asking: What knowledge systems are cited/privileged by the speaker to construct

themselves and others? What “statements of truth" are proffered as objective facts? How does

the speaker use emotion and morality? How do they establish a "we/us vs. them/others"

boundary? What was left out and why (Willig, 2014)? Examples of discursive strategies

include Asku's (2014) finding that supervisors utilized “silence” to establish power differentials

in the context of dyadic supervision and Clarke's (2009) finding that English language teachers-

in-training participating in an online forum used “otherization talk” to unite themselves in a

community of practice.

Identifying Interpretive Repertoires

One notable type of discursive strategy to consider in the data analysis process is

identifying the interpretive repertoires or interpretive frames referenced by the speakers (Potter,

2003). According to Goodman (2017), interpretive repertoires consist of how a speaker draws

from commonly held beliefs and widely known concepts to persuade the audience/listener.

Interpretive repertoires serve as an individual cognitive filter, informed by macro-level

discourses, such as the speaker’s culture, professional norms, and social status, analogous to

Gee's (2010) Big D’s In this regard, coding for interpretive repertoires helps the analysts to see

broader patterns in the data (Willig, 2014), in addition to how a speaker leverages multiple

spheres of discourse to create situated meaning.

Accurate identification of the Big D’s that provide the building blocks of interpretive

repertoires is aided by analyst knowledge of the discourse layers that encircle the topic. In

terms of analytical tools, Gee's (2010) "seven building tasks and building tools" (p. 87) –

significance, activities, identities, relationships, politics, connections, and sign systems – are

useful for identifying what is being accomplished with language and explaining the relationship

between little d’s and Big D’s. Examples of interpretive repertoires and Big D’s in data analysis

include Avdi's (2005) finding that parents' conception of disability (interpretive repertoire)

informed by a medical model, diagnosis-laden discourse (Big D) resulted in a stigmatizing self-

962 The Qualitative Report 2024

narrative about being a parent of a disabled child (little d). Analysts also contrast interpretive

repertoires to demonstrate how varied, contradictory, and marginal discourses contribute to the

complexity of social realities. For instance, Teräsahjo and Salmivalli (2003) studied the

discursive construction of bullying among elementary children and found that children held

contradictory discourses that simultaneously disavowed bullying while blaming the victim.

Interpreting the Function of the Discourse

The second phase of data analysis involves interpreting the function of the discourse.

Less has been written about this stage, as this task is completed somewhat organically, through

the analytical process, which entails drawing inferences about the functions of discourse

strategies deployed by the speaker (Potter & Wetherell, 1987). Potter and Wetherell (1987)

suggested that analysts consider how and why discourse actors pull from various discourses in

a flexible or contradictory manner to meet their communication goals relevant to the specific

interactional context. Examples of how speakers flex to the context by creatively drawing from

their discourse repertoires are evident in counseling-related literature. Avdi (2005) noted in her

study that after several family therapy sessions, the therapist began to address the (non-verbal)

child with autism directly to dislodge the parents’ construction of their child as an involuntary

being. Addressing the child directly rather than referring to the child as an object created space

for a humanized discourse to emerge that attributed socially situated meaning to his behavior.

Other researchers have noted the manifold function of pronouns in everyday settings to build

identity, solidarity, and maintain hierarchy (Clarke, 2009). Gordon and Luke (2016) noted that

the term “we” was used in a multifunctional manner “to normalize interns’ experiences, give

guidance, and promote institutionally appropriate understandings” (p. 64).

Findings

Organizing the Data

As in any qualitative research, moving from data analysis to findings is punctuated by

a great deal of cognitive incubation on the part of the researchers (Moustakas, 1994) and

requires the meticulous organization of data (Goodman, 2017). To organize the findings, Gee

(2010) recommends creating an Excel spreadsheet to cross-tabulate segments of transcribed

data with discourse-building strategies. Another option proposed by Goodman (2017) is to

reduce data by cutting and pasting the most illustrative segments of a transcript into a new

document and using separate headings for each discursive strategy identified.

Representation of Findings

Parker (2005) cautioned researchers from labeling one's findings as themes, as the goal

of DA is not to report upon participants' meaning-making experiences. Across the literature,

findings have been referred to as “constructive dimensions of discourse” (Moore & Radtke,

2015), “discursive patterns” (Davis & Lester, 2016), “dominant constructions/themes”

(Macleod, 2003), and “thematic sections” (Knight et al., 2012), to cite a few. Despite

differences in nomenclature, the products of discourse analysis use evidence from participants'

narratives and other texts to uncover how people use language to accomplish their goals. Thus,

to construct findings, researchers select extracts from data to highlight a discursive strategy

and describe how the strategy performs a particular task (Gee, 2011; Rodgers, 2011). Further,

because analysts are interested in the interactional dynamic and how speaker/s position

themselves to accomplish their communication goals, excerpts are often lengthy (see Asku,

Chloe Lancaster and Melissa J. Fickling 963

2014; Patrika & Tseliou, 2016). While there is no rule governing the number of findings, each

finding should be distinct yet unified (Gee, 2010) and relate to the research question. Further,

in DA, minority discourses are equally relevant as they help illustrate what knowledge is

privileged, by whom, and at what cost (Willig, 2014). For this reason, analysts often juxtapose

dominant and marginal discourses in the organization of findings (Gee, 2010).

In terms of formally writing results, we found Fairclough's (2001) suggestion useful to

(a) describe the nature of the discourse constructed by the spearker/s, (b) interpret how the

speaker/s justified their positions through discursive strategies, and (c) discuss the implications

of the speaker/s discourse as it relates to the research question. Findings from DAs grounded

in family systems theory illustrate this presentational structure. Of note, Patrika and Tseliou’s

(2016) findings consist of two interpretive frames, comprised of the contrasting discourses

evinced by the family and the therapist. In their write-up of the family’s interpretive fame, “Do

you consider this as being normal? The Family’s Side” (p. 107), the analysts outline how:

(1) Parents construct a discourse focused on the child as deviant and responsible

for the preponderance of their family troubles (description of discourse).

(2) Morality, developmental theory, and agreed-upon facts (e.g., child’s deviant

behavior) are some examples of the discursive strategies employed by the

couple to persuade the therapist that their child was their main family

problem.

(3) The implication or function of the discourse is to absolve themselves

(parents) of blame for their child’s dysfunction.

Trustworthiness

Credibility in qualitative research is connected to a researcher's competence as the

primary instrument of inquiry (Patton, 2015). In DA, researcher neutrality is never assumed.

As carriers of discourse, it is incumbent on researchers to understand their discursive influences

and how they project upon every facet of the research process (e.g., choice of topic, theoretical

orientation, design, interpretation, representation of results). To develop greater awareness of

discourses constitutive of oneself, Gee recommended that analysts have ongoing conversations

and maintain reflexive journals to ponder what they know and why they know it (Gee, 2010).

In addition to the researcher’s awareness and acknowledgment of their positionality in

the discourse under inquiry, trustworthiness in DA pertains to the accuracy and rigor of one's

analysis (Gee, 2010). Regarding speech data, trustworthiness relates to a researcher's skill in

conceptually linking details of speech to contextual dynamics and relevant discourses that

encircle a social exchange. Gee (2010) suggested that a robust analysis has four salient

characteristics: convergence, agreement, coverage, and linguistic details. Convergence means

how the findings converge around a consistent set of findings that answer the research question.

Agreement refers to the extent to which the discourses identified in the data perform a

consistent set of functions for the speaker/s. Coverage is analogous to the concept of data

triangulation and refers to the applicability of findings to related data sources and

complementary studies. Linguistic details are concerned with fidelity and refer to the extent an

analyst drew upon the linguistic features of the text to support their conclusions. Finally, Gee

(2010) recommended having colleagues familiar with DA evaluate the data and findings

reached. Because speech and text data are open to multiple interpretations, outside analysts can

highlight alternative discourses that may merit inclusion in the analysis.

964 The Qualitative Report 2024

Conclusion

As a profession that utilizes “talk therapy” as a major domain for promoting wellness,

counselors should study “talk” in all its manifestations and implications. Further, as a

profession that values social justice research, scholars should consider “talk” as a domain to

apply critical analysis to promote individual and systemic change. Nonetheless, while DA has

intrinsic value to the counseling profession, the principles and processes of DA are complex

and may create initial barriers to conducting this kind of research. Although an exhaustive

review of the DA literature was not possible in a single manuscript, nor can we claim that our

DA guide provides a blueprint for all DA efforts, we hope our recommendations encourage

practitioners and researchers to engage in this method of analysis. Ultimately, discourse

analysts will choose a method and methodology in keeping with their research question and

knowledge paradigm. Professional counseling has a rich history of conducting qualitative

research to examine the power of language for dividing, uniting, and healing. We believe that

DAs could expand upon this work by shedding light on how our professional discourses

function to bind us, legitimize our expertise, create exclusion, and better understand the

consequences of our discourse agendas upon others.

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Chloe Lancaster and Melissa J. Fickling 967

Author Note

Dr. Chloe Lancaster, Ph.D., CSC, is an Associate Professor in the Department of

Leadership, Policy, and Lifelong Learning. Her research interests include school counselor

accountability, college adjustment for underrepresented populations, qualitative methodology,

and adoption and foster care issues. She is receiving specialized, advanced training in discourse

analysis and teaches a DA doctoral class. Both co-presenters have presented discourse analysis

for counselor educators at the national level.

Melissa Fickling completed her Ph.D. in Counseling and Counselor Education at The

University of North Carolina at Greensboro in 2015 and her Master of Arts degree in

Community Counseling from Roosevelt University in 2009. She has published numerous

studies in counseling journals, chaired or co-chaired doctoral dissertations of various

methodologies, teaches doctoral research courses, and presented on research methodologies.

Correspondence concerning this article should be addressed to Chloe Lancaster,

University of South Florida, 422 E. Fowler Ave, EDU 105, Tampa, FL 33620, United States.

Email: [email protected]

Acknowledgement: We have no conflicts of interest to disclose.

University.

Article Citation

Lancaster, C., & Fickling, M. J. (2024). Expanding frameworks: Conducting discourse analysis

in counseling research. The Qualitative Report, 29(4), 953-967.

https://doi.org/10.46743/2160-3715/2024.6184