The Qualitative Report The Qualitative Report
Volume 20 Number 2 Article 7
2-16-2015
Generic Qualitative Research in Psychology Generic Qualitative Research in Psychology
William H. Percy
Capella University
Kim Kostere
Capella University
Sandra Kostere
Capella University
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Percy, W. H., Kostere, K., & Kostere, S. (2015). Generic Qualitative Research in Psychology.
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Generic Qualitative Research in Psychology Generic Qualitative Research in Psychology
Abstract Abstract
Some topics for qualitative research in psychology are unsuitable for or cannot be adapted to the
traditional qualitative designs such as case study, ethnography, grounded theory, or phenomenology. This
paper explores reasons for this, and proposes that psychological researchers can use a generic
qualitative design in such situations. After discussing the types of topics most suitable for a generic
qualitative design, the paper differentiates generic qualitative designs from the more traditional
qualitative designs, with particular attention to how generic qualitative inquiry differs from
phenomenological psychological research. Finally, appropriate procedures for data collection and for
thematic data analysis in a generic model are discussed and described in detail.
Keywords Keywords
Qualitative Research, Thematic Analysis, Generic Qualitative Research, Basic Qualitative Research, Data
Analysis forQualitative Research.
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The Qualitative Report 2015 Volume 20, Number 2, Article 5, 76-85
http://www.nova.edu/ssss/QR/QR20/2/percy5.pdf
Generic Qualitative Research in Psychology
William H. Percy, Kim Kostere, and Sandra Kostere
Capella University, Minneapolis, Minnesota, USA
Some topics for qualitative research in psychology are unsuitable for or cannot
be adapted to the traditional qualitative designs such as case study,
ethnography, grounded theory, or phenomenology. This paper explores
reasons for this, and proposes that psychological researchers can use a generic
qualitative design in such situations. After discussing the types of topics most
suitable for a generic qualitative design, the paper differentiates generic
qualitative designs from the more traditional qualitative designs, with
particular attention to how generic qualitative inquiry differs from
phenomenological psychological research. Finally, appropriate procedures for
data collection and for thematic data analysis in a generic model are discussed
and described in detail. Keywords: Qualitative Research, Thematic Analysis,
Generic Qualitative Research, Basic Qualitative Research, Data Analysis for
Qualitative Research.
Generic Qualitative Inquiry
Differentiating Generic Qualitative Inquiry
Many studies report people’s subjective opinions, attitudes, beliefs, or experiences of
things in the outer world. Such psychological things cannot be measured in the statistical sense,
and require qualitative methods (cf., Aronson, 1994). Sometimes, the other more focused
approaches (e.g., ethnography, case study, grounded theory, or phenomenology) are not
appropriate for one reason or another. In those cases, researchers should consider a more
generic qualitative inquiry approach. Suppose a researcher were interested in investigating one
of the following:
1. People’s attitudes, opinions, or beliefs about a particular issue or experience;
2. Workers’ feelings about their supervisors’ performance;
3. The reflections of women who left the convent on their “life journey”;
4. Senior managers’ reflections on experiences that have had significant
impacts on them during their careers;
5. Clients’ descriptions of their experiences of psychotherapy;
6. Children’s reports of their experiences being placed in special education
classes.
Each of these topics calls for qualitative inquiry, but several other, more common
approaches would not be suitable. Why not?
• Ethnography (see next section) focuses on the investigation of the network
of social groupings, social customs, beliefs, behaviors, groupings, practices,
etc., that define a “culture.” None of these topics focuses on that unit of
analysis (social-cultural).
• Case studies are in-depth investigations of a “single case,” using multiple
methods and multiple sources of data. A single case is defined by having
William H. Percy, Kim Kostere, and Sandra Kostere 77
clearly recognizable boundaries that differentiate the case from any other
collection of instances. None of the groups of people above constitute a
“case” in that sense.
• Grounded theory uses data from people to develop an explanation (theory)
for the process in question developed over time. But none of the topics above,
except perhaps the senior managers’ reflections, would lend themselves to
development of theory. They are descriptive, not explanatory. If the
researcher investigating the managers’ experiences in fact wanted to develop
a theory of what experiences contribute to successful leadership style, that
topic might qualify as grounded theory.
• Phenomenology investigates the “lived experience” of various psychological
phenomena. Many of the phenomena this approach tackles include attitudes,
beliefs, opinions, feelings, and the like. However, the phenomenologist’s
interest is in the inner dimensions, textures, qualities, and structures
(“essences”) of those cognitive processes, not in the external content or
referents that may trigger the cognitive processes.
Differentiating Generic Qualitative Inquiry from Phenomenological Inquiry
The most difficult distinction to make here is probably with phenomenology. Let’s take
a moment for a more careful review of the differences.
Phenomenology studies the inner essence of cognitive processing – what structures
(temporality, spatiality, etc.) and textures (what are the felt qualities of the thoughts?) are found
across the reports of many persons’ similar experiences? If a group of people describe how, in
everyday life, they feel when they experience anger at work, the phenomenologist listens to
what they all do similarly when processing their anger without thinking about it. Here is a
common example, taken from an analysis in progress:
All the participants reported that anger feels big, expansive, magically
powerful. They tend to feel themselves puff up, get hot, and start to believe they
can change the problem by shouting or being harsh. They get very present-
centered – nothing else matters when angry. Curiously, most also obsess about
the past and past angers at the same time. “It’s like being in a time warp,” one
said. Another said, “Tunnel vision. Only see one thing, but it feels timeless.”
The phenomenological interest is in the internal subjective structures of the
experiencing itself.
On the other hand, examples 1-6 described above focus on the actual content of their
reports (what do they actually think about the issue? What are the experiences? Etc.). The
attitude/opinion study would not be interested in the subjective psychological experiencing,
but only in its content – what the experience was about. In any of the examples, if someone
reported that anger was part of the experience, we’d be interested in the fact that someone was
angry, not in what that experience of anger (“being angry”) was like.
A second difference is that phenomenology investigates pre-reflective conscious
experiencing, often referred to as “lived experience.” Contrast the term experiencing
(phenomenology’s interest) with experiences (the focus of our topics above). Experiencing
addresses the inward and ongoing act of taking in and making sense of a phenomenon – how
does one do this? What is the structure of one’s cognitive processing? Experiences, on the other
hand, focus our attention outwardly – What was experienced? What happened? To what does
the belief point to in the outer world?
78 The Qualitative Report 2015
Consider this example: Suppose we want to know something about a political
campaign. The phenomenological question we’ll ask our voters might be something like this:
What is it like for you experiencing this campaign? The opinion researcher, on the other hand,
would more likely ask something like: Do you prefer X or Y in this campaign? Which of the
following do you consider the most important issue? Please rank order your preferences in the
race? What stands out as the most interesting thing about this campaign?
The first question to ask yourself, after deciding on your general topic, is what you
really want to know about your topic. If your focus is outward – on the content of opinions, on
the actual-world experiences and happenings, on the thoughtful description and reflection of
historical occurrences in people’s past—you might want to select generic qualitative inquiry as
your methodological approach rather than phenomenology or one of the other approaches.
To sum up, if the researcher is interested more in the actual outer-world content of their
questions (the actual opinions themselves, the life experiences themselves, the participants’
reflections themselves) and less on the inner organization and structure of the participants’
experiencing processes, then phenomenology would not be appropriate, but a more generic
qualitative analysis would be. Let’s turn our attention to what this generic qualitative approach
is.
Description of Generic Qualitative Inquiry
Generic qualitative inquiry investigates people’s reports of their subjective opinions,
attitudes, beliefs, or reflections on their experiences, of things in the outer world. It can be
selected as the methodological approach when:
1. The research problem and question require a qualitative or mixed-methods
methodology. In fact, the generic qualitative approach is well suited to mixed
methods studies, because its data usually can be re-structured as quantitative to
relate to the statistical side of the study (Creswell, 1995; Tashakkori & Teddlie,
1998)
2. Ethnography, case study, grounded theory, or phenomenology is inappropriate
because the focus of the study, the content of the information desired, or the
kind of data to be obtained do not fit those approaches. These other
approaches—particularly case study and grounded theory—can be used in
mixed methods studies, but often their data cannot be as easily reformulated to
integrate with the quantitative data.
3. The researcher has a body of pre-knowledge/pre-understandings (categories or
sub-categories of information) about the topic that he or she wants to be able to
more fully describe from the participants’ perspective. For instance, suppose
that prior research has shown that employee morale correlates strongly and
positively with their wage bracket, but nothing more is known than that. A
researcher could ask what the employees actually think and feel about being in
various wage brackets (sub-question one) and how those feelings and ideas
influence their morale (sub-question two). Asking these two questions may
expand the previous knowledge—that the two categories are related—with the
qualitative employee-perspective information.
Generic qualitative inquiry is a useful approach when attempting survey research that
includes qualitative elements in a mixed design. Indeed, this approach is appropriate when a
fully qualitative survey approach is desired. Actually, researchers considering any study of
William H. Percy, Kim Kostere, and Sandra Kostere 79
people’s subjective “take” on actual external happenings and events should consider generic
qualitative inquiry as their approach.
Generic Qualitative Data Collection
Data collection in this approach typically uses data collection methods that elicit
people’s reports on their ideas about things that are outside themselves. However, its focus on
real events and issues means it seldom uses unstructured data collection methods (such as open-
ended conversational interviewing from phenomenology, participant and/or non-participant
field observation from ethnography, and the like). Instead, it requires semi- or fully-structured
interviews, questionnaires, surveys, content- or activity-specific participant observation, and
the like. The core focus is external and real-world, as opposed to internal and psychological.
(Even the attitudes and opinions in opinion polling are valued for their reflection on the external
issues.)
By and large, generic qualitative data collection seeks information from representative
samples of people about real-world events and processes, or about their experiences. We want
less to “go deep” and more to get a broad range of opinions, ideas, or reflections. Occasionally,
a small, non-representative, but highly informed sample can provide rich information about the
topic. For instance, a few experienced nurses can often provide rich, accurate, and helpful
information about common patient reactions to certain procedures, because part of a nurse’s
role is to observe patients’ experience and reactions carefully. More often, however, the
sampling in this approach aims for larger representation of the population in mind.
Although this is not hard-and-fast, generic qualitative data collection typically uses
larger samples than other qualitative approaches use, because larger samples tend to be more
widely representative. External generalization (reliability) is not necessary, because the data
are sometimes not quantifiable. However, as with all qualitative inquiry, if the sample is
transparently and fairly representative of the target population or is clearly information-rich
about the topic, readers may be persuaded to apply the findings to similar people or situations
outside the sample itself.
Most generic qualitative studies rely on the following data collection methods:
• Semi- or fully-structured (closed-ended) interviews, either oral (the most
common method) or written (uncommon). In these qualitative interviews,
the questions are pre-structured based on the pre-knowledge of the
researcher, although there may be opportunities for “tell me more” kinds of
questions.
• Questionnaires. Usually these mix scaled or quantitative items (e.g., Likert-
type scales asking preferences or degrees of agreement) with opportunities
for qualitative comments; this approach requires mixed-methods designs.
Again, the researcher will build these questionnaires and their items from
pre-knowledge about the topic.
• Written or oral surveys. The standard opinion or voter poll is a good
example, but survey research has its own rather deep literature and can be
much more sophisticated that simple opinion or voter surveying. Once
again, the items in the survey will be constructed on the basis of pre-
knowledge about the topic.
80 The Qualitative Report 2015
Data Analysis in Generic Qualitative Analysis: Thematic Analysis
…thematic analysis involves the searching across a data set – be that a number
of interviews or focus groups, or a range of texts – to find repeated patterns of
meanings. (Braun & Clark, 2006, p. 86)
Thematic analysis is process that is used to conduct an analysis of qualitative data.
While it does not represent a complete research design, it does offer a process of data analysis
that is flexible and compatible with many approaches to qualitative research and mixed
methodology in particular generic qualitative analysis.
Thematic analysis can be used to analyze data collected through a qualitative survey—
a kind of qualitative survey using interviews (often) that are semi-structured—to investigate
subjective experiences of objective things - like "your experience being a leader," or "your
experience of receiving treatment for X disorder," or "your experience searching for a higher-
paying faculty job." A thematic analysis can also be used to conduct an analysis of the
qualitative data in some types of case study and in mixed methodology studies. Really, thematic
analysis is a generic approach to analyzing people’s reports that may form the basis for many
different kinds of qualitative interpretation.
Three types of thematic analysis will be described here: inductive analysis, theoretical
analysis, and thematic analysis with constant comparison.
Since this is an inductive and intuitive process, there are no simple procedures
or techniques for this kind of analysis. You many find it helpful to ask yourself
questions like: “What do these quotes or observations have in common?”
“What's going on here?” “What does this tell me about how people view their
world?” “How do these themes relate to each other?”. (Taylor & Bogdan, 1998,
p. 156)
Inductive Analysis (IA)
Inductive analysis is data driven and does not attempt to fit the data into any preexisting
categories. The researcher sets aside all pre-understandings. The data collected from each
participant (interviews, observations, open-ended questionnaire, etc.) are analyzed
individually. Once the data from all participants have been analyzed, the repeating patterns and
themes from all participants are synthesized together into a composite synthesis, which
attempts to interpret the meanings and/or implications regarding the question under
investigation.
Step-By-Step Analysis
1. Review and familiarize yourself with the data collected from each
participant (interviews, journals, field notes, records and documents). Read
the documents and highlight intuitively any sentences, phrases, or
paragraphs that appear to be meaningful. During this process the researcher
immerses him/herself in each participant’s data individually.
2. Review the highlighted data and use your research question to decide if the
highlighted data are related to your question. Some information in the
transcript may be interesting, but not relate to your question.
William H. Percy, Kim Kostere, and Sandra Kostere 81
3. Eliminate all highlighted data that are not related to your question. However,
start a separate file to store unrelated data. You may want to come back and
reevaluate these data in the future.
4. Take each piece of data and code it. The code can be very simple, like a
serial number or an address – simply a way to keep track of individual items
of data.
5. Cluster the items of data that are related or connected in some way and start
to develop patterns. For each distinct pattern you discern, describe it in a
phrase or statement that sums it up. If feasible or useful, assign a second
level code to the patterns too. Note that the words describing the patterns
are no longer the words of the participants, but your own. In field-specific
research (e.g., psychology), attempt to make these words meaningful to
specialists in the field (e.g., psychologists).
6. As you start to see patterns, identify items of data that correspond to that
specific pattern. Place them in the previously assembled clusters (see 5) that
manifest that pattern. Direct quotes taken from these data (transcribed
interviews, field notes, documents, etc.) will elucidate the pattern. (The
name or descriptor of your pattern thus is a more abstract phrase, whereas
the data themselves are direct words from participants.)
7. Take all the patterns and look for the emergence of overarching themes.
Themes are “patterns of patterns.” This process involves combining and
clustering the related patterns into themes. As you see meaningful themes
across patterns, assign a yet-more-abstract descriptor to the theme. Use
standard psychological language and terms. This will be a third level of
abstraction, supported by the patterns, in turn illustrated by the direct data.
8. After all the data have been analyzed, arrange the themes in a kind of matrix
with their corresponding supportive patterns. (The patterns are used to
elucidate the themes, just as the word data are used to support and illustrate
the pattern descriptors). In the matrix, include the codes or descriptors for
each of the data clusters. Thus, the supporting layers of words/text can easily
be accessed when discussing an individual theme in your final report.
9. For each theme, write a detailed abstract analysis describing the scope and
substance of each theme.
10. (Complete this process for each participants’ data)
11. Then combine the analysis of data for all participants including patterns and
themes that are consistent across the participants’ data.
12. Finally, the themes are synthesized together to form composite synthesis of
the data collected regarding the question under inquiry.
Theoretical Analysis (ThA)
Theoretical analysis is employed in a situation in which the research has some
predetermined categories (themes) to examine during the data analysis. In this situation, the
research may use his/her pre-understandings when conducting the data analysis. However, in
this case the researcher also remains open to the possibilities of new themes emerging from the
thematic analysis. The theoretical thematic analysis is driven by theory and the themes that are
predetermined are usually located in the research question. Thus, the research question will
have identified concepts from theories on the topic under inquiry. The data collected are
analyzed individually and patterns that emerged from the data will be organized under the
82 The Qualitative Report 2015
appropriate preexisting themes, keeping in mind that new patterns and themes may also emerge
from the data during the data analysis process.
Researchers might approach this analysis in two phases: In the first phase, after
preparing the data (steps 1-4 below), one works on assigning the data units to the pre-
determined themes derived from previous research and theory and carries out the analyses as
described in steps 5 through 13. Then, in phase two, return to the data and work with data units
and patterns that did not seem to fit the pre-determined categories, again following steps 5-13.
The themes derived from this analysis will likely not be found in previous research but may
contribute to it.
Step-By-Step Analysis
1. Read, review, and familiarize yourself with the data collected from each
participant (interviews, journals, field notes, records and documents). Re-read
the documents and highlight intuitively any sentences, phrases, or paragraphs
that appear to be meaningful. Keeping in mind the predetermined categories
(themes) that are related to the theory and research question posed as well as
remaining open to any new patterns and themes that are related to the research
question and have emerged from the data analysis. During this process, the
researcher immerses him/herself in each participant’s data individually.
2. For each participant review the highlighted data and use your research question
to decide if the highlighted data are related to your question. Some information
in the transcript may be interesting, but not relate to your question.
3. Eliminate all highlighted data that are not related to your question, however,
start a separate file to store unrelated data. You may want to come back and
reevaluate these data in the future.
4. Take each item of data and code or give a descriptor for the data. The descriptor
or name will often be a characteristic word from within the data.
5. Cluster the items of data that are related or connected in some way and start to
develop patterns.
6. Patterns that are related to a preexisting theme are placed together with any other
patterns that correspond with the theme along with direct quotes taken from the
data (transcribed interviews, field notes, documents, etc.) to elucidate the
pattern.
7. Any patterns that do not relate to preexisting themes should be kept in a separate
file for future evaluation of the meanings as they relate to the overall topic.
Repeat steps 1-7 for all participants.
8. Take all the patterns and look for the emergence of overarching themes. This
process involves combining and clustering the related patterns into the
preexisting themes.
9. After all the data have been analyzed, arrange the themes to correspond with the
supporting patterns. The patterns are used to elucidate the themes.
10. Now revisit the patterns that did not fit the preexisting categories and remain
open to any new patterns and themes that are related to the research topic and
have emerged from the data analysis.
11. For each theme, the researcher needs to write a detailed analysis describing the
scope and substance of each theme.
12. Each pattern should be described and elucidated by supporting quotes from the
data.
William H. Percy, Kim Kostere, and Sandra Kostere 83
13. Finally, the themes are synthesized together to form composite synthesis of the
question under inquiry.
Thematic Analysis with Constant Comparison (CC)
Thematic analysis with constant comparison can be either inductive analysis or
theoretical analysis. The difference is that the data collected are analyzed as they are collected.
The analysis begins during the collection of data. The first participant’s data are analyzed and
as each subsequent participant’s data are analyzed, they are compared to the previously
analyzed data. The analysis constantly moves back and forth between current data and the data
that have already been coded and clustered into patterns. Patterns and themes will change and
grow as the analysis continues throughout the process.
Step-By-Step Analysis
1. Review and familiarize yourself with the data collected from the first
participant (interviews, journals, field notes, records and documents). Read
the documents and highlight intuitively any sentences, phrases, or
paragraphs that appear to be meaningful.
2. Review the highlighted data and use your research question to decide if the
highlighted data are related to your question. Some information in the
transcript may be interesting, but not relate to your question.
3. Eliminate all highlighted data that are not related to your question, however,
start a separate file to store unrelated data. You may want to come back and
reevaluate this data in the future.
4. Take each set of data and code or name the data.
5. Cluster the sets of data that are related or connected in some way and start
to develop patterns.
6. Complete this process for the first participants’ data. The researcher will
code and cluster the first participant's data and as each subsequent
participant’s data are analyzed, they are compared to the previously
analyzed data. Throughout this process, each participant’s data are reviewed
and analyzed, and the researcher is comparing and contrasting the data being
analyzed with the data that have been previously analyzed in the study.
Thus, a constant comparison emerges.
7. Throughout this process, data that correspond to a specific pattern are
identified and placed with the corresponding pattern and direct quotes are
taken from the data (transcribed interviews, field notes, documents, etc.) to
elucidate the pattern.
8. Throughout the process, take all the patterns and look for the emergence of
overreaching themes. This process involves combining and clustering the
related patterns into themes.
9. Patterns and themes may tend to shift and change throughout the process of
analysis, as previously completed analyses are compared with new data.
10. After all the data have been analyzed, arrange the themes to correspond with
the supporting patterns. The patterns are used to elucidate the themes.
11. For each theme, the researcher writes a detailed analysis describing the
scope and substance of each theme.
12. Each pattern should be described and elucidated by supporting quotes from
the data.
84 The Qualitative Report 2015
13. The data are synthesized together to form composite synthesis of the
question under inquiry.
Thematic Analysis in a Mixed Methodology Study
Thematic analysis is often used in conducting the analysis of the qualitative portion of
the data collected in a mixed methodology study. There are a number ways to develop a
research design using mixed methods, below are a number of mixed methodology designs
common to the field of psychology. An excellent source for more about mixed methods studies
is Creswell (2003, 2008, 2013)
• Sequential studies (or what Creswell, 2003, calls two-phase studies): The
researcher first conducts a qualitative phase of a study and then a
quantitative phase, or vice versa. The two phases are separate.
• Parallel/simultaneous studies: The researcher conducts the qualitative and
quantitative phase at the same time.
• Equivalent status designs: The researcher conducts the study using both the
quantitative and qualitative approaches about equally to understand the
phenomenon under study.
• Dominant-less dominant studies: The researcher conducts the study "within
a single dominant paradigm with a small component of the overall drawn
from an alternative design" (Creswell, 1995, p. 177).
• Designs with multilevel use of approaches: Researchers use different types
of methods at different levels of data aggregation. For example: data could
be analyzed qualitatively at the student level, qualitatively at the class level,
quantitatively at the school level and qualitatively at the district level
(Tashakkori & Teddlie, 1998, p. 18).
References
Aronson, J. (1994). A pragmatic view of thematic analysis. The Qualitative Report, 2(1).
Retrieved from http://www.nova.edu/ssss/QR/index.html
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research
in Psychology, 3, 77-101.
Creswell, J. (1995). Research design: Qualitative and quantitative approaches. Thousand
Oaks, CA: Sage Publications, Inc.
Creswell, J. (2003). Research design: Qualitative, quantitative, and mixed methods approaches
(2nd
ed.). Thousand Oaks, CA: Sage Publications, Inc.
Creswell, J. (2008). Research design: Qualitative, quantitative, and mixed methods approaches
(3rd
ed.). Thousand Oaks, CA: Sage Publications, Inc.
Creswell, J. (2013). Research design: Qualitative, quantitative, and mixed methods approaches
(4th ed.). Thousand Oaks, CA: Sage Publications, Inc.
Taylor, S., & Bogdan, R. (1998). Introduction to qualitative research methods (3rd ed.). New
York, NY: John Wiley & Sons, Inc.
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William H. Percy, Kim Kostere, and Sandra Kostere 85
Author Note
William H. Percy, PhD, was trained in qualitative methodologies at the Union Institute,
where he received his PhD in Family Social Science in 1982. After practicing psychology and
family therapy in Minneapolis for ten years, he joined the faculty of the Capella University,
first in the Human Services department in 1996, and then the Harold Abel School of
Psychology in 1998, where he served in various roles, including Director of Residence, Acting
Director of Field Training, and core faculty. He served on the University Institutional Review
Board for many years, and was instrumental, with Drs. Sandra and Kim Kostere, and Dr.
Malcolm Gray in developing much of the infrastructure of the research programs for the
Department of Psychology. Percy retired in 2012, and now writes novels in Idaho.
Correspondence regarding this article can be addressed directly to: Dr. William H. Percy at E-
mail: bill.percy@capella.edu or Phone: 208-264-1116
Kim Kostere has a Ph.D. in Clinical Psychology. He graduated from The Union
Institute in 1989. He also has a Psy.S. in Humanistic and Clinical Psychology and Education,
from the Center for Humanistic Studies. Dr. Kostere is a Licensed Psychologist and a licensed
Marriage and Family Therapist in the State of Michigan. Dr. Kostere is a Clinical Member in
AAMFT. He has over 20 years of experience in the field of psychotherapy and health care
administration. Dr. Kostere’s research background is in qualitative research. He studied with
both Clark Moustakas and Bruce Douglass. His master’s thesis and dissertation were both
qualitative heuristic in design. He is currently faculty at Capella University and has been faculty
since December, 1999. Dr. Kostere teaches advanced qualitative analysis, has designed
courses, and mentors qualitative dissertations. He is currently serving as an Assistant Editor
at The Qualitative Report. Correspondence regarding this article can also be addressed directly
to: Dr. Kim Kostere at E-mail: kim.kostere@capella.edu
Sandra Kostere has a Ph.D. in Clinical Psychology. She graduated from The Union
Institute in 1989. She also has a Psy.S. in Humanistic and Clinical Psychology and Education,
from the Center for Humanistic Studies. Dr. Kostere is a Licensed Psychologist in the State of
Michigan and has over 20 years of experience in the field of psychotherapy and health care
administration. Dr. Kostere’s research background is in qualitative research. She studied with
both Clark Moustakas and Bruce Douglass. Her master’s thesis and dissertation were both
qualitative heuristic in design. She is currently faculty at Capella University and has been
faculty since December, 1999. Dr. Kostere teaches advanced qualitative analysis, has designed
courses, and mentors qualitative dissertations. She is currently serving on the Editorial Board
of The Qualitative Report. Correspondence regarding this article can also be addressed directly
to: Dr. Sandra Kostere at E-mail: Sandra.kostere@capella.edu or Phone: 239-775-4775
Copyright 2015: William H. Percy, Kim Kostere, Sandra Kostere, and Nova
Southeastern University.
Article Citation
Percy, W. H., Kostere, K., & Kostere, S. (2015). Generic qualitative research in psychology.
The Qualitative Report, 20(2), 76-85. Retrieved from
http://www.nova.edu/ssss/QR/QR20/2/percy5.pdf
