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Abstract

Qualitative research methods are a robust tool for chaplaincy research questions. Similar to much of chaplaincy clinical care, qualitative research generally works with written texts, often transcriptions of individual interviews or focus group conversations and seeks to understand the meaning of experience in a study sample. This article describes three common methodologies: ethnography, grounded theory, and phenomenology. Issues to consider relating to the study sample, design, and analysis are discussed. Enhancing the validity of the data, as well reliability and ethical issues in qualitative research are described. Qualitative research is an accessible way for chaplains to contribute new knowledge about the sacred dimension of people's lived experience.
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Overview of Qualitative Research
Daniel H. Grossoehme a
a Division of Pulmonary Medicine, Department of Pastoral Care ,
Cincinnati Children's Hospital Medical Center , Cincinnati , Ohio ,
USA
Published online: 13 Jun 2014.
To cite this article: Daniel H. Grossoehme (2014) Overview of Qualitative Research, Journal of Health
Care Chaplaincy, 20:3, 109-122, DOI: 10.1080/08854726.2014.925660
To link to this article: http://dx.doi.org/10.1080/08854726.2014.925660
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Research Methodology
Overview of Qualitative Research
DANIEL H. GROSSOEHME
Division of Pulmonary Medicine, Department of Pastoral Care, Cincinnati Children’s
Hospital Medical Center, Cincinnati, Ohio, USA
Qualitative research methods are a robust tool for chaplaincy
research questions. Similar to much of chaplaincy clinical care,
qualitative research generally works with written texts, often tran-
scriptions of individual interviews or focus group conversations
and seeks to understand the meaning of experience in a study
sample. This article describes three common methodologies: eth-
nography, grounded theory, and phenomenology. Issues to con-
sider relating to the study sample, design, and analysis are
discussed. Enhancing the validity of the data, as well reliability
and ethical issues in qualitative research are described. Qualitat-
ive research is an accessible way for chaplains to contribute new
knowledge about the sacred dimension of people’s lived experience.
KEYWORDS chaplaincy, ethnography, grounded theory,
phenomenology, qualitative research
INTRODUCTION
Qualitative research is, ‘‘the systematic collection, organization, and
interpretation of textual material derived from talk or conversation. It is used
in the exploration of meanings of social phenomena as experienced by indi-
viduals themselves, in their natural context’’ (Malterud, 2001, p. 483). It can
be the most accessible means of entry for chaplains into the world of
research because, like clinical conversations, it focuses on eliciting people’s
stories. The stories can actually be expressed in almost any medium: conver-
sations (interviews or focus groups), written texts (journal, prayers, or
Address correspondence to Daniel H. Grossoehme, Division of Pulmonary Medicine,
Department of Pastoral Care, Cincinnati Children’s Hospital Medical Center, MLC 2021, 3333
Burnet Avenue, Cincinnati, OH 45229, USA. E-mail: daniel.grossoehme@cchmc.org
Journal of Health Care Chaplaincy, 20:109–122, 2014
Copyright #Taylor & Francis Group, LLC
ISSN: 0885-4726 print=1528-6916 online
DOI: 10.1080/08854726.2014.925660
109
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letters), or visual forms (drawings, photographs). Qualitative research may
involve presenting data collected from a single person, as in a case study
(Risk, 2013), or from a group of people, as in one of my studies of parents
of children with cystic fibrosis (CF) (Grossoehme et al., 2013). Whole books
are devoted to qualitative research methodology and, indeed, to the individ-
ual methods themselves. This article is intended to present, in rather broad
brushstrokes, some of the ‘‘methods of choice’’ and to suggest some issues
to consider before embarking on a qualitative research project. Helpful texts
are cited to provide resources for more complete information.
Although virtually anything may be data, spoken mediums are the
most common forms of collecting data in health research, so the focus of
this article will mainly be on interviews and to a lesser extent, focus groups.
Interviews explore experiences of individuals, and through a series of
questions and answers, the meaning individuals give to their experiences
(Tong, Sainsbury, & Craig, 2007). They may be ‘‘structured’’ interviews,
in which an interview guide is used with pre-determined questions from
which no deviation is permitted by the interviewer, or semi-structured
interviews, in which an interview guide is used with pre-determined ques-
tions and potential follow-up questions. The latter allows the interviewer to
pursue topics that arise during the interview that seem relevant (Cohen &
Crabtree, 2006). Writing good questions is harder than it appears! In my
first unit of CPE, the supervisor returned verbatims, especially our early
efforts, with ‘‘DCFQ’’ written in the margin, for ‘‘direct, closed, factual ques-
tion.’’ We quickly learned to avoid DCFQs in our clinical conversations
because they did not create the space for reflection on illness and the
sacred the way open-ended questions did. To some extent, writing good
open-ended questions that elicit stories can come more readily to cha-
plains, due perhaps to our training, than to investigators from other disci-
plines. This is not to say writing an interview guide is easy or an aspect of
research that can be taken lightly, as the quality of the data you collect, and
hence the quality of your study, depends on the quality of your interview
questions.
Data may also be collected using focus groups. Focus groups are nor-
mally built around a specific topic. They almost always follow a
semi-structured format and include open discussion of responses among
participants, which may range from four to twelve people (Tong et al.,
2007). They provide an excellent means to gather data on an entire range
of responses to a topic, or on the social interactions between participants,
or to clarify a process. Once the data are collected, the analytic approach
is typically similar to that of interview data.
Qualitative investigators are not disinterested outsiders who merely
observe without interacting with participants, but affect and are affected by
their data. The investigator’s emotions as they read participants’ narratives
are data to be included in the study. Simply asking ‘‘research’’ questions
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can itself be a chaplaincy intervention: what we ask affects the other person
and can lead them to reflect and change (Grossoehme, 2011). It is important
to articulate our biases and understand how they influence us when we col-
lect and analyze data. Qualitative research is often done by a small group of
researchers, especially the data coding. This minimizes the bias of an individ-
ual investigator. Inevitably, two or more people will code passages differ-
ently at times. It is important to establish at the outset how such
discrepancies will be handled.
Ensuring Rigor, Validity, and Reliability
Some people do not think qualitative research is not very robust or signifi-
cant. This attitude is due, in part, to the poor quality of some early efforts.
Increasingly, however, qualitative studies have improved in rigor, and
reviewers of qualitative manuscripts expect investigators to have addressed
problematic issues from the start of the project. Two important areas are
validity and reliability. Validity refers to whether or not the final product
(usually referred to a ‘‘model’’) truly portrays what it claims to portray. If
you think of a scale on which you weigh yourself, you want a valid read-
ing so that you know your correct weight. Reliability refers to the extent to
which the results are repeatable; if someone else repeated this study,
would they obtain the same result? To continue the scale analogy, a
reliable scale gives the same weight every time I step on it. A scale can
be reliable without being valid. The scale could reliably read 72 pounds
every time I step on it, but that value is hardly correct, so the measure
is not valid.
VALIDITY
Swinton and Mowat (2006) discussed ensuring the ‘‘trustworthiness’’ of the
data. N narrative data which are ‘‘rich’’ in their use of metaphor and descrip-
tion, and which express deeper levels of meaning and nuance compared to
everyday language are likely to yield a trustworthy final model because the
investigators have done a credible job of completely describing and under-
standing the topic that is under study. Validity is also enhanced by some
methodologies, such as grounded theory, which use participants’ own
words to name categories and themes, instead of using labels given by
the investigator. The concept of ‘‘member checking’’ also enhances validity.
Once the analyses are complete and a final model has been developed,
these findings are shown to all or some of the participants (the members)
who are invited to check the findings and give feedback. Do they see
themselves in the words or conceptual model that is presented? Do they
offer participants a new insight, or do they nod agreement without really
reengaging the findings?
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RELIABILITY
One means of demonstrating reliability is to document the research decisions
made along the way, as they were made, perhaps in a research diary
(Swinton & Mowat, 2006). Qualitative methodologies accept that the investi-
gator is part of what is being studied and will influence it, and that this does
not devalue a study but, in fact, enhances it. Simply deciding what questions
to ask or not ask, and who you ask them to (and not) reflect certain decisions
that should be consciously made and documented. Another researcher
should be able to understand what was done and why from reading the
research diary.
ETHNOGRAPHIC RESEARCH
Elisa Sobo (2009) defines ethnography as the presentation of, ‘‘...a given
group’s conceptual world, seen and experienced from the inside’’ (p. 297).
Ethnography answers the question, ‘‘what’s it like to be this person?’’ One
example of this kind of study comes from the work of Fore and colleagues
(Fore, Goldenhar, Margolis, & Seid, 2013). In order to design tools that would
enable clinicians and persons with pediatric inflammatory bowel disease
(IDB) to work together more efficiently, an ethnographic study was underta-
ken to learn what it was like for a family when a child had IDB. After 36 inter-
views, the study team was able to create three parent-child dyad personas:
archetypes of parents and children with IDB based directly on the data they
gathered. These personas were used by the design team to think about how
different types of parents and children adapted to the disease and to think
what tools should be developed to help different types of parents and chil-
dren with IDB. An ethnographic study is the method of choice when the goal
is to understand a culture, and to present, or explain, its spoken and unspo-
ken nature to people who are not part of the culture, as in the example above
of IDB. Before ‘‘outsiders’’ could think about the needs of people with IDB, it
was necessary to learn what it is like to live with this disease.
Sampling
Determining the sample in ethnographic studies typically means using what
is called a purposive sample (Newfield, Sells, Smith, Newfield, & Newfield,
1996). Purposive samples are based on criteria that the investigator estab-
lishes at the outset, which describe participant characteristics. In the afore-
mentioned IDB example, the criteria were: (1) being a person with IDB
who was between 12 and 22 years old or the parent of such a child; (2) being
or having a child whose IDB care was provided at one of a particular group
of treatment centers; (3) being a pediatric gastrointestinal nurse at one of the
centers; or (4) a physician=researcher at one of five treatment centers. Having
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a sample that is representative of the larger population, always the goal in
quantitative research, is not the point in ethnographic studies. Here, the goal
is to recruit participants who have the experience to respond to the ques-
tions. Out of their intimate knowledge of their culture, the investigator can
build a theory, or conceptual model, which could later be tested for
generalizability in an entire population.
Design
Ethnographic study designs typically involve a combination of data collection
methods. Whenever possible, observing the participants in the midst of what-
ever experience is the study’s focus is desirable. In the process of an ethno-
graphic project on CF, for instance, two students spent a twelve-hour period
at the home of a family with a child who had CF, taking notes about what
they saw and heard. Interviews with participants are frequently employed
to learn more about the experience of interest. An example of this is the work
of Sobo and colleagues, who interviewed parents of pediatric patients in a
clinic to ask about the barriers they experienced obtaining health care for
their child (Seid, Sobo, Gelhard, & Varni, 2004). Diaries and journals detailing
people’s lived experience may also be used, alone, or in combination with
other methods.
Analysis
Analysis of ethnographic data is variable, depending on the study’s goal. One
common analytic approach is to begin analysis after the first few interviews
have been completed, and to read them to get a sense of their content. The
next step is to name the seemingly important words or phrases. At this point,
one might begin to see how the names relate to each other; this is the begin-
ning of theory development. This process continues until all the data are
collected. At that point, the data are sorted by the names, with data from
multiple participants clustered under each topic name (Boyle, 1994). Similar
names may be grouped together, or placed under a larger label name (i.e.,
category). In a sense, what happens is that each interviewer’s voice is broken
into individual fragments, and everyone’s fragments that have the same name
are put together. From individual voices speaking on multiple topics, there is
now one topic with multiple voices speaking to it.
GROUNDED THEORY RESEARCH
Grounded theory is ‘‘grounded’’ in its data; this inductive approach collects
data while simultaneously analyzing it and using the emerging theory to
inform data collection (Rafuls & Moon, 1996). This cycle continues until
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the categories are said to be ‘‘saturated,’’ which typically means the point
when no new information is being learned (Morse, 1995). This methodology
is generally credited to Glaser and Strauss, who wanted to create a means of
developing theoretical models from empirical data (Charmaz, 2005).
Perhaps, more than in any other qualitative methodology, the person of
the investigator is the key. The extent to which the investigator notices subtle
nuances in the data and responds to them with new questions for future part-
icipants, or revises an emerging theory, is the extent to which a grounded
theory research truly presents a theory capturing the fullness of the data from
which it was built. It is also the extent to which the theory is capable of being
used to guide future research or alter clinical practice. Grounded theory is the
method of choice when there is no existing hypothesis to test. For instance,
there was no published data on how parents use faith to cope after their
child’s diagnosis with CF. Using grounded theory allowed us to develop a
theory, or a conceptual model, of how parents used faith to cope
(Grossoehme, Ragsdale, Wooldridge, Cotton, & Seid, 2010). An excellent
discussion of this method is provided by Charmaz (2006).
Sampling
The nature of the research question should dictate the sample description,
which should be defined before beginning the data collection. In some cases,
the incidence of the phenomena may set some limits on the sample. For
example, a study of religious coping by adults who were diagnosed with
CF after age 18 years began with a low incidence: this question immediately
limited the number of eligible adults in a four-state area to approximately 25
(Grossoehme et al., 2012). Knowing that between 12 and 20 participants
might be required in order to have sufficient data to convince ourselves that
our categories were indeed saturated, limiting our sample in other ways: for
example, selecting representative individuals spread across the number of
years since diagnosis would not have made sense. In some studies, the goal
is to learn what makes a particular subset of a larger sample special; these
subsets are known as ‘‘positive deviants’’ (Bradley et al., 2009).
Design
Once the sample is defined and data collection begins, the analytic process
begins shortly thereafter. As will be described in the following paragraphs,
interviews and other forms of spoken communication are nearly always tran-
scribed, typically verbatim. Unlike most other qualitative methods, grounded
theory uses an iterative design. Sometime around the third or fourth inter-
view has been completed and transcribed and before proceeding with
further interviews, it is time to begin analyzing the transcripts. There are
two aspects to this. The first is to code the data that you have. Grounded
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theory prefers to use the participants’ own words as the code, rather than
having the investigator name it. For example, in the following transcript
excerpt, we coded part of the following except:
INTERVIEWER: OK. Have your beliefs or perhaps relationship with God
changed at all because of what you’ve gone through the
last nine and 10 months with N.?
INTERVIEWEE: Yeah, I mean, I feel that I’m stronger than I was before
actually.
INTERVIEWER: Hmm-hmm. How so? Can you put that into words? I
know some of these could be hard to talk about but ...
INTERVIEWEE: I don’t know, I feel like I’m putting his life more in God’s
hands than I ever was before.
We labeled, or coded, these data as, ‘‘I’m putting his life more in God’s
hands,’’ whereas in a different methodology we might have simply named it
‘‘Trusting God.’’ Focus on the action in the narrative. Although it can be dif-
ficult, you as a researcher must try very hard to set your own ideas aside.
Remember you are doing this because there is no pre-existing theory about
what you are studying, so you should not be guided by a theory you have in
your mind. You must let the data speak for themselves.
The second point is to reflect on the codes and what they are already
telling you. What questions are eliciting the narrative data you want? Which
ones are not? Questions that are not leading you to the data you want prob-
ably need to be changed. Interesting, novel ideas may emerge from the data,
or topics that you want to know more about that you did not anticipate and
so the interviewer did not’ follow up on them. What are the data not telling
you that you are seeking? All of this information flows back to revising the
semi-structured interview guide (Charmaz, 2006). This issue raised mild con-
cern with the IRB reviewer who had not encountered this methodology
before. This concern was overcome by showing that this is an accepted
method with voluminous literature behind it, and by showing that the types
of item revisions were not expected to significantly alter the study’s effect on
the participants. From this point onward you collect data, code it, and ana-
lyze it simultaneously. As you code a new transcript and come across a state-
ment similar to others, you can begin to put them together. If you are using
qualitative analysis software such as NVivo (‘‘NVivo qualitative data analysis
software,’’ 2012), you can make these new codes ‘‘children’’ of a ‘‘parent’’
node (the first statement you encountered on this topic). The next step is
called ‘‘focused coding’’ and in this phase you combine what seems to you
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to be the most significant codes (Charmaz, 2006). These may also be the most
frequently occurring, or the topic with the most duplicates, but not necessar-
ily. This is not a quantitative approach in which having large amounts of data
is important. You combine codes at this stage in such a way that your new,
larger, categories begin to give shape to aspects of the theory you think is
going to emerge. As you collect and code more data, and revise your
categories, your idea of the theory will change.
Axial coding follows, as you look at your emerging themes or
categories, and begin to associate coded data that explains that category.
Axial coding refers to coding the words or quotations that are around the
category’s ‘‘axis,’’ or core. For example, in a study of parental faith and cop-
ing in the first year after their child’s diagnosis with CF (Grossoehme et al.,
2010), one of the categories which emerged was, ‘‘Our beliefs have chan-
ged.’’ There were five axial codes which explain aspects of this category.
The axial codes were, ‘‘Unchanged,’’ ‘‘We’ve learned how fragile life is,’’
‘‘Our faith has been strengthened,’’ ‘‘We’ve gotten away from our parents’
viewpoints,’’ and ‘‘I’m better in tune with who I am.’’ Each of these axial
codes had multiple explanatory phrases or sentences under them; together
they explain the breadth and dimensions of the category, ‘‘Our beliefs have
changed.’’
The next step is theoretical coding, and here the categories generated
during focused coding are synthesized into a theory. Some grounded theor-
ists, notably one of the two most associated with it (Glaser), do not use axial
coding but proceed directly to this step as the means of creating coherence
out of the data (Charmaz, 2006). As your emerging theory crystallizes, you
may pause to see if it has similarities with other theoretical constructs you
encountered in your literature search. Does your emerging theory remind
you of anything? It would be appropriate to engage in member-checking
at this point. In this phase, you show your theoretical model and its sup-
porting categories to participants and ask for their feedback. Does your
model make sense to them? Does it help them see this aspect of their
experience differently (Charmaz, 2005). Use their feedback to revise your
theory and put it in its final form. At this point, you have generated new
knowledge: a theory no one has put forth previously, and one that is ready
to be tested.
PHENOMENOLOGY RESEARCH
Perhaps the most chaplain-friendly qualitative research approach is phenom-
enology, because it is all about the search for meaning. Its roots are in the
philosophical work of Husserl, Heidegger and Ricoeur (Boss, Dahl, &
Kaplan, 1996; Swinton & Mowat, 2006). This approach is based on several
assumptions: (1) meaning and knowing are social constructions, always
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incomplete and developing; (2) the investigator is a part of the experience
being studied and the investigator’s values play a role in the investigation;
(3) bias is inherent in all research and should be articulated at the beginning;
(4) participants and investigators share knowledge and are partners; (5) com-
mon forms of expression (e.g., words or art) are important; and (6) meanings
may not be shared by everyone (Boss et al.). John Swinton and Harriet
Mowat (2006) described the process of carrying out a phenomenological
study of depression and spirituality in adults and reading their book is an
excellent way to gain a sense of the whole process. Phenomenology may
be the method of choice when you want to study what an experience means
to a particular group of people. May not be the best choice when you want
to be able to generalize your findings. An accurate presentation of the experi-
ence under study is more important in this approach than the ability to
claim that the findings apply to across situations or people (Boss et al.). A
study of the devil among predominately Hispanic horse track workers is
unlikely to be generalizable to experiences of the devil among persons of
Scandinavian descent living in Minnesota. Care must be taken not to over-
state the findings from a study and extend the conclusions beyond what
the data support.
Sampling
The emphasis on accurately portraying the phenomenon means that large
numbers of participants are not required. In fact, relatively small sample sizes
are required compared to most quantitative, clinical studies. The goal is to
gather descriptions of their lived experience which are rich in detail and ima-
gery, as well as reflection on its theological or psychological meaning. The
likelihood of achieving this goal can be enhanced by using a purposeful sam-
ple. That is, decide in the beginning approximately how large and how
diverse your sample needs to be. For example, CF can be caused by over
1,000 different genetic mutations; some cause more pulmonary symptoms
while others cause more gastrointestinal problems. Some people with CF
have diabetes and others do not; some have a functioning pancreas and
others need to take replacement enzymes before eating or drinking anything
other than water. Some CF adolescents may have lung function that is over
100%of what is expected for healthy adolescents of their age and gender,
whereas others, with severe pulmonary disease, may have lung function that
is just 30%of what is expected for their age and gender. A study of what it is
like for an adolescent to live with a life-shortening genetic disease using this
approach might benefit from purposive sampling. For example, lung disease
severity in CF is broadly described as mild, moderate or severe. A purposeful
sample might call for 18 participants divided into 3 age groups (11–13 years;
14–16 years; and 17–19 years old) and disease severity (mild, moderate, and
severe). In each of those nine groups there would be one male and one
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female. In actual practice, one might want to have more than 18 to allow for
attrition, but this breakdown gives the basic idea of defining a purposive
sample. One could reasonably expect that having the experience of both
genders across the spectrum of disease severity and the developmental range
of adolescence would permit an accurate, multi-dimensional understanding
to emerge of what living with this life-shortening disease means to adoles-
cents. In fact, such an accurate description is more likely to emerge with this
purposeful sample of 18 adolescents than with a convenience sample of the
first 18 adolescents who might agree to participate in the study during their
outpatient clinic appointment. Defining the sample to be studied requires
some forethought about what is likely to be needed to gain the fullest under-
standing of the topic.
Design
Any research design may be used. The design will be dictated by what data
are required to understand the phenomena and its meaning. Interviews are
by far the most common means of gathering data, although one might also
use written texts, such as prayers written in open prayer books in hospital
chapels, for example (ap Sion, 2013; Grossoehme, 1996), or drawings
(Pendleton, Cavalli, Pargament, & Nasr, 2002), or photographs=videos
(Olausson, Ekebergh, & Lindahl, 2012). Although the word ‘‘text’’ appears,
it should be with the understanding that any form of data is implied.
Analysis
The theoretical underpinnings of phenomenology, which are beyond the
scope of this article, suggest to users that ‘‘a method’’ is unnecessary or
indeed, contrary, to phenomenology. However, one phenomenological
researcher did articulate a method (Giorgi, 1985), which consists of the fol-
lowing steps. First, the research team immerses themselves in the data. They
do this by reading and re-reading the transcribed interviews and listening to
the recorded interviews so that they can hear the tone and timbre of the
voices. The goal at this stage is to get a sense of the whole. Second, the
texts are coded, in which the words, phrases or sentences that stand out
as describing the experience or phenomena under study, or which express
outright its meaning for the participant are extracted or highlighted. Each
coded bit of data is sometimes referred to as a ‘‘meaning unit.’’ Third, similar
meaning units are placed into categories. Fourth, for each meaning unit the
meaning of the participants’ own words is spelled out. For chaplains, this
may mean articulating what the experience means in theological language.
Other disciplines might transform the participants’ words into psychological,
sociological or anthropological language. Here the investigators infer the
meaning behind the participants’ words and articulate it. Finally, each of
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the transformed statements of meaning are combined into a few thematic
statements that describe the experience (Bassett, 2004; Boss et al., 1996).
After this, it would be appropriate to do member-checking and a
subsequent revision of the final model based on participants’ responses
and feedback.
PRACTICAL CONCERNS
Just as questionnaires or blood samples contain data, in qualitative research it
is the recording of people’s words, whether in an audio, video, or paper for-
mat which hold the data. Interviews, either in-person or by telephone should
be recorded using audio, video or both. It is important to have a device with
suitable audio quality and fresh batteries. Experience has shown me the
benefit of using two audio recorders so that you do not lose data if one of
them fails. There are several small recorders available that have USB connec-
tions that allow the audio file to be uploaded to a computer easily. To protect
participants’ privacy, all data should be anonymized by removing any infor-
mation that could identify individuals. The Standard Operating Procedure in
my research group is to replace all participants’ names with an ‘‘N.’’ During
the transcription process, all other individuals are identified by their role in
square brackets, ‘‘[parent].’’ Depending on the study’s goal and the analytic
method you have selected, you may want to include symbols for pauses
before participants respond, or non-fluencies (e.g., ‘‘ummm. ...’’, ‘‘well
...uh ...’’) or non-verbal gestures (if you are video recording). Decide before
beginning whether it is important to capture these as data or not. There are
conventional symbols which are inserted into transcriptions which capture
these data for you. After the initial transcription, these need to be verified
by comparing the written copy against the original recording. Verification
should be done by someone other than the transcriptionist. There are several
tasks at this stage. Depending on the quality of your recording, the clarity of
participants’ speech and other factors, some words or phrases may have been
unintelligible to the transcriptionist, and this is the time to address them. In
my research group our Standard Operating Procedure is to highlight unintel-
ligible text during the transcription phase, and a ‘‘verifier’’ attempts three
times to clarify the words on the original recording before leaving them
marked ‘‘unintelligible’’ in the transcript. No transcriptionist is perfect and
if they are unfamiliar with the topic, they may transcribe the recording inac-
curately. I recently verified a transcript where a commercial medical tran-
scriptionist changed the participant’s gender from ‘‘he’’ to ‘‘she’’ when the
word prior to the pronoun ended with an ‘‘s.’’ If this pattern had not been
caught during the verification process, it would have been very difficult dur-
ing the coding to know whether the pronoun referred to the participant or to
their daughter.
Overview of Qualitative Research 119
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ETHICAL ISSUES IN QUALITATIVE RESEARCH
Study Design
The issue of power and the possibility of subtle coercion is the concern here.
There is an inherent power differential between a research participant and
the investigator, which is exacerbated when the investigator is a chaplain.
Despite our attempts to be non-threatening, the very words, ‘‘chaplain,’’ or
‘‘clergy’’ connote power. For this reason, the chaplain-investigator should
not approach potential participants regarding a study. Potential participants
may be informed regarding their eligibility to participate by their physician
or a chaplain, but the recruitment and informed consent process should
be handled by someone else, perhaps a clinical research coordinator. How-
ever, as the chaplain-investigator, you will need to teach them how to talk
with potential participants about your study and answer their questions.
Choose a data collection method that is best-suited to the level of sensitivity
of your research topic. Focus groups can provide data with multiple perspec-
tives, and they are a poor choice when there may be pressure to
provide socially correct responses, or when disclosures may be stigmatizing.
In such cases, it is better to collect data using individual semi-structured
interviews.
Risk
Develop a plan for assessing participants’ discomfort, anxiety, or even more
severe reactions during the study. For instance, what will you do when some-
one discloses his=her current thoughts of self-harm, or experiences a flash-
back to a prior traumatic event that was triggered during an interview?
How will you handle this if you are collecting data in person? By telephone?
You will need to be specific who must be informed and who will make deci-
sions about responding to the risk.
Privacy and Confidentiality
In addition to maintaining privacy and confidentiality of your actual data and
other study documents, consider how you will protect participants’ privacy
when you write the study up for publication. Make sure that people cannot
be identified by their quotations that you include as you publish data. The
smaller the population you are working with, the more diligently you need
to work on this. If the transcriptionist is not an employee of your institution
and under the same privacy and confidentiality policies, it is up to you to
ensure that an external transcriptionist takes steps to protect and maintain
the privacy of participants’ data.
120 D. H. Grossoehme
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CONCLUSION
Qualitative research is an accessible way for chaplains to contribute new
knowledge regarding the sacred dimension of people’s lived experience.
Chaplains are already sensitive to and familiar with many aspects of qualitat-
ive research methodologies. Studies need to be designed to be valid and
meaningful, and are best done collaboratively. They provide an excellent
opportunity to develop working relationships with physicians, medical
anthropologists, nurses, psychologists, and sociologists, all of whom have
rich traditions of qualitative research. This article can only provide an over-
view of some of the issues related to qualitative research and some of its
methods. The texts cited, as well as others, provide additional information
needed before designing and carrying out a qualitative study. Qualitative
research is a tool that chaplains can use to develop new knowledge and con-
tribute to professional chaplaincy’s ability to facilitate the healing of broken-
ness and disease.
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