Qualitative interpretive meta-synthesis in social work research: Uncharted territory

Abstract

The authors present the field of social work with a methodology specifically aimed at the synthesis of qualitative research informed by existing methods and applications yet tailored to the unique values and goals of the profession of social work.

Findings
Though qualitative research in social work is commonplace, currently, the field lacks a methodology to synthesize these qualitative studies. A synthesis of qualitative studies results in generation of a more in-depth understanding of the phenomena studied that can be used to develop theory and inform practice and policy.

Applications
This methodology enables synergistic understanding of phenomena with richness in diversity of settings, participants, and qualitative traditions. This synergistic understanding can be used to develop theory and inform practice and policy.

Full text

Journal of Social Work
2014, Vol. 14(3) 279–294
!The Author(s) 2013
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DOI: 10.1177/1468017313476797
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Article
Qualitative interpretive
meta-synthesis in social
work research:
Uncharted territory
Regina TP Aguirre
The University of Texas at Arlington, Arlington, USA
Kristin Whitehill Bolton
The University of Texas at Arlington, Arlington, USA
Abstract
Summary: The authors present the field of social work with a methodology
specifically aimed at the synthesis of qualitative research informed by existing methods
and applications yet tailored to the unique values and goals of the profession of
social work.
Findings: Though qualitative research in social work is commonplace, currently, the
field lacks a methodology to synthesize these qualitative studies. A synthesis of quali-
tative studies results in generation of a more in-depth understanding of the phenomena
studied that can be used to develop theory and inform practice and policy.
Applications: This methodology enables synergistic understanding of phenomena with
richness in diversity of settings, participants, and qualitative traditions. This synergistic
understanding can be used to develop theory and inform practice and policy.
Keywords
Social work, meta-analysis, meta-synthesis, qualitative methods, qualitative synthesis,
social work research, systematic review
Introduction
Since social work’s inception, the profession has sought to enhance human well-
being from a holistic perspective, acknowledging that humans do not live in vac-
uums – humans are constantly acting and reacting within their social, emotional,
Corresponding author:
Regina TP Aguirre, School of Social Work, The University of Texas at Arlington, 211 S. Cooper, Box 19129,
Arlington, TX 76019, USA.
Email: rtpaguirre@uta.edu
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Appendix D: Recently Published Article

and physical environments (International Federation of Social Workers
[IFSW], 2000). This holistic perspective is prevalent throughout in both social
work practice and social work research. Social work research maintains this atten-
tion to the whole as evidenced by the rise in focus on mixed methods, systematic
reviews, and meta-analyses over the past 30 years (Littell, Corcoran, & Pillai, 2008)
– all of which aim to capture a more holistic view of a phenomenon. Specifically,
mixed methods accomplishes this through combining qualitative and quantitative
methods in primary data collection; systematic reviews ‘‘sum up the best available
research on a specific question’’ (The Campbell Collaboration, n.d.); and meta-
analysis is a ‘‘statistical procedure that integrates the results of several independent
studies considered to be combinable’’ (Egger, Davey, & Phillips, 1997, p. 1533).
Each of these exhibits an effort to bring together multiple sources of evidence,
specific to a particular phenomenon, into a comprehensive whole that offers
insight in terms of social work practice and policy, expanding and deepening the
breadth of evidence-based practice. Mixed methods and systematic reviews
provide a platform for the integration of qualitative and quantitative evidence
on a topic and meta-analysis provides an integration approach for purely
quantitative evidence, but, so far, the discipline of social work has not embraced
a definitive technique or method for cross-study analysis to synthesize qualitative
findings.
An extensive review of the qualitative social work literature revealed that social
work lacks a methodology to synthesize qualitative findings; however, Padgett
(2004) notes a considerable amount of qualitative research is conducted in the
field of social work. Our review unveiled four articles synthesizing qualitative
studies among the scholarly social work literature (Forte, 2009; Hodge,
2011; McCalman et al., 2010; Watkins, Walker, & Griffith, 2010), each has used
different approaches to the task (e.g. Finfgeld, 2003; Noblit & Hare, 1988)
borrowed from nursing, a profession aiming to enhance well-being in terms of
health (American Nursing Association, 2004) similar to our goal of enhancing
overall well-being.
Since synthesizing qualitative research allows for knowledge gleaned from indi-
vidual qualitative studies of a particular phenomenon to come together in a
broader, in-depth, and more holistic understanding of that phenomenon, having
a method uniquely designed for the social work profession’s mission is deemed
highly desirable. In this paper, we discuss, in generalities, current approaches to
synthesis and present a model for synthesizing qualitative research tailored to the
field of social work that we have developed and implemented.
How is qualitative research synthesized?
Aggregative versus interpretive
Prior to presenting a social work oriented approach to synthesizing qualitative
research, it is important to have a general
1
understanding of existing approaches
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heretofore used to synthesize studies. Two overarching approaches depict the
nature of the methodological procedure. Some researchers operate under the
assumption that a qualitative synthesis is an aggregative process while others
view qualitative synthesis as an interpretive process. Aggregative syntheses take
on a quantitative approach (for example determining an effect size through fre-
quency and intensity) (Sandelowski & Barroso, 2003, 2007). On the other hand,
interpretive syntheses focus on theory development (Dixon-Woods et al., 2006) and
concept development, and follow a traditional qualitative methodological founda-
tion that does not exhibit quantitative features. Multiple differences exist between
these two approaches as well as some similarities; however, we have highlighted
differences relevant to our reasoning for selecting our methodological preference.
Since we want to present a method that focuses on uncovering the whole of a given
phenomenon, we believe the interpretive approach is most congruent with our
primary goals of a holistic understanding and theory development. The choices
of our colleagues (Forte, 2009; Hodge, 2011; McCalman et al., 2010; Watkins et al.,
2010) in conducting their syntheses also reflect a preference for the interpretive
approach.
Nomenclature: Varied approaches to cross study analysis
To enhance further understanding, one must be capable of differentiating qualita-
tive synthesis from quantitative meta-analysis, systematic review, literature review,
and varying approaches to qualitative synthesis.
Quantitative cross study analysis, systematic review and literature review
The synthesis of quantitative studies is most commonly referred to as meta-
analysis, and as stated before can be defined as a ‘‘statistical procedure that inte-
grates the results of several independent studies considered to be combinable’’
(Egger et al., 1997, p. 1533). According to Rubin and Babbie (2008) a ‘‘meta-
analysis simply involves calculating the mean effect size across previously com-
pleted research studies on a particular topic’’ (p. 550). Furthermore, a meta-ana-
lysis increases the external validity of findings through a larger sample size and
minimizes the sampling error. In turn, increasing the external validity of the
research findings adds to the breadth, rigor, and credibility of the results.
Both systematic reviews and literature reviews consist of a detailed overview of
existing literature. The authors of these reviews summarize findings instead of
synthesizing them.
Qualitative cross study analysis
Although use of qualitative cross study analysis in social work research is in its
infancy, it has become a widely discussed, theorized and applied concept in the field
of nursing. Numerous researchers in nursing have developed methods to conduct
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qualitative synthesis (Estabrooks, Field, & Morse, 1994; Finfgeld-Connett, 2010;
Jensen & Allen, 1996; Sandelowski & Barroso, 2007; Sandelowski, Docherty, &
Emden, 1997) and applied these (Barroso & Powell-Cope, 2000; Beck, 2001, 2002;
Britten et al., 2002; Campbell et al., 2003; Dixon-Woods et al., 2006; Finfgeld,
1999, 2000; Jensen & Allen, 1994; Kearney, 2001; McCormick, Rodney, &
Varcoe, 2003; Nelson, 2002; Paterson, 2001; Paterson, Thorne, & Dewis, 1998;
Sandelowski & Barroso, 2003; Thorne & Paterson, 1998). Each of the methods
and subsequent applications in the nursing field has generated a wealth of
understanding of strengths and limitations of various aspects of qualitative cross
study analysis.
As discussed previously, qualitative cross study analysis or synthesis can be
approached aggregatively or interpretively. A qualitative metasummary is defined
as ‘‘a quantitatively oriented aggregation of qualitative findings that are themselves
topical or thematic summaries or surveys of data’’ (Sandelowski & Barroso, 2007,
p. 151). In essence, a metasummary incorporates quantitative research methods to
express correlations and findings, while a qualitative synthesis lacks any trace of
quantitative research methods, maintaining its inherent qualitative identity.
Sandelowski and Barroso (2007) have also used the term ‘meta-synthesis’ to
describe this method.
There are many interpretive methods
2
for qualitative synthesis; those that seem
most commonly used include: meta-ethnography, meta-study, grounded formal
theory, and cross-case analysis. In preparation for this paper, we studied these in
depth and reviewed worked examples of each, identifying what we wanted to keep
from each of these approaches and what we wanted to address in our method in
terms of limitations. Before presenting our method, we define these methods briefly
along with noting limitations of each.
Meta-ethnography seeks to explicate relationships between and within individual
studies through metaphors (Noblit & Hare, 1988; worked examples: Barroso &
Powell-Cope, 2000; Beck, 2001, 2002; Jensen & Allen, 1994; Nelson, 2002;
Paterson et al., 1998). However, this methodology does not suggest a sampling
method or strategies regarding appraisal of individual studies. Grounded Formal
Theory is an extension of grounded theory and utilizes the constant comparative
method for data collection, analysis, and theory development (Strauss & Corbin,
1998; worked examples: Finfgeld, 2000; Kearney, 2001). The limitation to this
method lies in the possibility of theoretical saturation being achieved prior to the
inclusion of all of the relevant studies. Furthermore, this methodology does not offer
an explanation on how to address this issue. Cross-case Analysis was suggested by
Miles and Hubberman (1994), and consists of a technique to identify categories
within individual studies, refine, and cross-reference with other studies (worked
example: McNaughton, 2000). Again, similar to grounded formal theory and
meta-ethnography, this method fails to provide guidance related to sampling or
inclusion criteria. Finally, a meta-study is a highly systematic process involving sev-
eral evaluative phases prior to the actual synthesis: meta-theory, meta-method, and
meta-data analysis (worked example: Watkins et al., 2010). These phases are then
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followed by the actual meta-synthesis. Furthermore, this method provides guidance
regarding sampling and appraisal techniques.
Our proposed method: Qualitative interpretive
meta-synthesis
From our standpoint, in presenting this model, our goal of an interpretive quali-
tative meta-synthesis is not to generate a systematic review, a literature review, or
quantify qualitative data, but to create a synergy of qualitative findings. However,
as in all qualitative research, some aspects of the process will vary as it is emergent
and contextual in nature. Throughout the presentation of the method, we note
these areas for researchers who choose to conduct qualitative interpretive meta-
syntheses. The first step in presenting our model is to define it: considering the three
words in ‘‘interpretive meta-synthesis’’’, ‘‘interpretive’’ meaning that we eschew
aggregating findings quantitatively; ‘‘meta’’ ‘‘denoting a change of position or
condition’’ and ‘‘synthesis’’ being ‘‘the combination of ideas to form a theory or
system’’ (Meta, 2011; Synthesis, 2011). We conceptualize qualitative interpretive
meta-synthesis (QIMS) as a means to synthesize a group of studies on a related
topic into an enhanced understanding of the topic of study wherein the position of
each individual study is changed from an individual pocket of knowledge of a
phenomenon into part of a web of knowledge about the topic where a syn-
ergy among the studies creates a new, deeper and broader understanding. This
can be considered akin to social work’s person-in-environment approach to
practice. Just as each person a social worker interacts with is not a lone island
but rather a part of a system of relationships with other people, organizations,
policies, and environments, so too, each individual qualitative study captures only
a snapshot of the human experience of a phenomenon. Qualitative studies give in-
depth views of a particular phenomenon experienced by a particular group in a
particular situation yet the combination of these studies in QIMS allows us to see
what is the shared human experience of this phenomenon and what aspects may be
divergent.
The development of QIMS
In developing this method, we have drawn from multiple approaches to qualitative
cross study analysis in an attempt to operationalize a method specific to the field of
social work. As we describe our proposed method for conducting QIMS in social
work, we wish to emphasize that this is not a linear process but rather an iterative
one as illustrated in Figure 1, depicting the method. Since developing the method,
we have implemented it in 22 different cross study analyses across a wide range of
social work topics, using these implementations to refine the steps.
3
In addition to
describing the proposed methodology, a partial worked example from one of 22
qualitative interpretive meta-syntheses we have conducted (Aguirre & Bolton,
forthcoming) to date will be used to enhance understanding of each step.
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The partial worked example is a QIMS on volunteer motivations in crisis settings
(Aguirre & Bolton, forthcoming).
The steps in QIMS
The first step in beginning a QIMS is to formulate a research question. Once this is
accomplished, a sample is selected, followed by steps in analysis (theme extraction,
theme synthesis, triangulation, etc.), and credibility reporting.
Sampling. Sampling for QIMS is a combination of purposive and theoretical sam-
pling, and is common practice in qualitative research. Purposive sampling is used to
initially select studies followed by theoretical sampling to test, add, and elaborate on
the emerging analysis (Dixon-Woods et al., 2006). Sample selection in a QIMS dif-
fers slightly from traditional sampling techniques used in literature reviews and
systematic reviews. Researchers should cast a broad net including grey literature
(i.e., dissertations or unpublished studies), books, and studies from various discip-
lines. Furthermore, literature searches should be exhaustive in nature to ensure the
inclusion of all relevant studies in the synthesis.
4,5
Limiting searches to internet
databases can limit the overall scope of the synthesis and result in omission of per-
tinent data. Throughout the search process, we recommend that researchers develop
a quorum chart to depict the process of data collection, review, elimination, and
inclusion. Quorum charts are commonly found in systematic reviews or meta-
analyses and offer a precise and rigorous outline of the sampling process.
6
Things to consider: Traditions, context, temporal relevance and fatal flaws. After
exhausting all resources and compiling studies related to the research topic,
Figure 1. Meta-synthesis path to synergistic understanding.
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the next step is to narrow the list of studies which may include consideration of
traditions, context, temporal relevance and fatal flaws. In the existing literature on
qualitative synthesis, there are varying opinions regarding whether or not to
include studies in the sample from varying qualitative traditions. Some researchers
are cautious of synthesizing findings from qualitative studies generated using dif-
ferent qualitative traditions out of concern that there would be a misrepresentation
of the original research (e.g., Jensen & Allen, 1996). We certainly recognize the
differences
7
among traditions and are aware of the concern of comparing ‘‘apples
to oranges’’ (Padgett, 2008). However, we, along with others (e.g. Finfgeld, 2003),
encourage including studies from various traditions for two major reasons. First,
the wide range of philosophical and methodological traditions researchers employ
(Padgett, 2008), each expose a different aspect of a phenomenon. For example,
ethnographies focus on culture and phenomenologies on the lived experience of a
phenomenon – each provides a portion of a richer picture or understanding of the
phenomena under study. Including studies of various traditions such as phenom-
enology and ethnography in a QIMS further advances social work’s goal in
research to understand a given phenomenon across cultures and situations so as
to develop and improve client-centered policy, theory, advocacy, and services.
To illustrate our second reason, we consider the point at which these various
traditions and philosophies impact a study. These are employed at every stage of
the study to arrive at the essence of the experience under study. However, the
resulting essence is reported in units that are easily compared across these trad-
itions and philosophies. As illustrated later in this paper, data gathered from the
articles for a QIMS are not to be rewritten, reworked, or analyzed. In fact, it is our
goal to maintain the original themes from the articles included in the sample, so as
to decrease the opportunity for researcher bias and increase reliability across find-
ings. We conceptualize this similarly to the argument for including studies in a
meta-analysis that employ various statistical techniques. In a meta-analysis, the
results are compared on the basis of an effect size, a result that each study produces
regardless of whether using analysis of variance, multiple regression, etc. This is
similar to our procedure in the sense that we take the themes demonstrated in the
qualitative studies and synthesize these across the sample selected. We are not by
any means altering the methodological approaches nor the impact these had on the
processes in the original studies; we are simply focused on the end results presented
by the original researchers.
In addition to considering traditions when narrowing the sample, contextual
relevance is of concern as well. Studies related to the research topic may differ
from the context of the research question and should be discarded accordingly.
For example, if conducting a QIMS on motivations to volunteer in crisis situations,
articles on volunteer motivation related to non-crisis situations would need to be
discarded even though these are related to volunteer motivation. During the pro-
cess of discarding studies, it is important that the researcher not eliminate a study
because it is a ‘‘negative case’’ (or disconfirming case). Patton (2002) emphasizes
the importance of the ‘‘negative case’’ because ‘‘our understanding of those
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patterns and trends is increased by considering the instances and cases that do not
fit within the pattern’’ (p. 554). For example, one study may have findings or
conclusions different from all other studies in the sample. This ‘‘negative case’’
needs to be acknowledged and incorporated similarly to the way a ‘‘negative
case’’ would be in a qualitative study. Including and maintaining the integrity of
this ‘‘negative case’’ is imperative to the quality and trustworthiness of the QIMS as
a whole.
Similar to the contextual relevance is the temporal relevance. Determining the
temporal relevance of each study helps maintain the relevance of the synthesis and
increases its transferability (Sandelowski, Barroso, & Voils, 2007). For example, a
qualitative interpretive meta-synthesis on the use of new technologies in counseling
done in the 21st century would not include previous research on use of the tele-
phone in counseling since the telephone is not a ‘‘new’’ technology.
A final aspect to consider in narrowing the sample is ‘‘fatal flaws’’ (Dixon-
Woods et al., 2006) and these should be eliminated from the sample at the research-
er’s discretion. Fatal flaws can include, but are not limited to, researcher bias, lack
of triangulation, or questionable trustworthiness. Furthermore, researchers must
differentiate between fatal flaws and poor data presentation. If the text presenting a
study is sub-par, it may be included because data within the paper could remain a
vital piece to the sample itself. Sub-par studies would include manuscripts that are
poorly organized, difficult to read, or fail to present writing at a scholarly level.
Even if the presentation of a study is sub-par, the content may be rich with data
pertinent to the topic of inquiry. The process of differentiating between fatal flaws
and sub-par text is subjective in nature and elimination is at the discretion of the
researcher conducting the QIMS. The lack of specific criteria for elimination may
be viewed as a limitation but the process of determining whether a study contains a
fatal flaw is commonly done in systematic reviews, literature reviews, and meta-
analyses as well with the individual researchers’’ deciding the criteria.
Theme extraction. Following the selection and identification of the sample, a table
should be created to list and identify characteristics of the participants and studies
including demographics, methods, and major findings (see Table 1 for a partial
example from Aguirre and Bolton (forthcoming). Once this is completed each
study should be read repeatedly while identifying metaphors, concepts, terms,
and phrases (Noblit & Hare, 1988). Terms used by researchers may differ but
common themes may present themselves across studies. The outcome of repeatedly
reading while identifying metaphors, concepts, terms and phrases should generate a
collage of comparable themes resulting in the emergence of a synergistic picture of
the phenomenon. For example, we conducted a QIMS including 5 research reports
focusing on motivations for crisis volunteers. We developed a table comprising the
phrases and components of the process associated with the themes found among
the research studies included in the QIMS (see Table 2 for a partial example from
Aguirre & Bolton [forthcoming]). This table was accompanied by direct quotes
from the research studies divided into categorical subheadings in the findings
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Table 1. Example table of studies included in a QIMS.
Authors Date
Tradition and data
collection method
Sample
size
Ages, race/ethnicity,
gender Education level
Volunteer
setting
Rath 2007 Grounded Theory;
Interviews
8 22–58, White, female Not specified Rape Crisis
Center
Steffen
& Fothergill
2009 Did not specify;
Data gathered
through 2 waves
of interviews
34 Not reported; Majority
White, other races/
ethnicities represented:
Vietnamese,
Native American,
Iranian, Moroccan,
African American,
Korean, and Mexican
American; 17 male, 17
female
Most have college
degrees
Multiple
locations
Yanay
& Yanay
2008 Did not specify;
Data gathered
through inter-
views and
observations
20 20–50, not reported,
female
Varied from High
School to
Masters degrees
Rape Crisis
hotline
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section. Once the researcher is satisfied all of the key concepts and themes have
been extracted from the research studies as well as categorized and organized, it is
time to synthesize the results.
Synthesis of themes. The identification of themes in each study is followed by the
actual data synthesis. Once themes are recorded, the studies are translated into one
another. This process of translation must maintain the integrity of each individual
study while allowing for the synthesis of similar themes. Noblit and Hare state:
an adequate translation maintains the central metaphors and/or concept of
each account in their relation to other key metaphors or concepts in that account.
It also compares both the metaphors and concepts and their interactions in one
account with the metaphors or concepts and their interactions in other accounts.
(1988, p. 28)
Jensen and Allen (1996) state that a meta-synthesis ‘‘is credible when it re-pre-
sents such faithful descriptions or interpretations of human experience that the
people having that experience would immediately recognize it from those descrip-
tions or interpretations as their own’’ (p. 556). In other words, failure to maintain
the integrity of the original studies results in decreasing the trustworthiness of the
meta-synthesis. One way to limit the loss of original integrity is to utilize
participant quotes from the original research reports included in the interpretive
meta-synthesis.
For example, in our QIMS on volunteers, we maintained the integrity of each
individual research study yet grouped the themes presented in the individual
research studies into five overarching themes (See Table 3 for a partial example
from Aguirre & Bolton [forthcoming]). We then incorporated quotes from the
Table 2. Example table of theme extraction in a QIMS.
Authors Original Themes
Rath (2008) 1. Motivation to train
2. Complexity of change
3. Changes in personal relationships
4. Personal change
5. Feminism
Steffen & Fothergill (2009) 1. Personal healing
2. Self-concept
Community sentiment and involvement
Yanay & Yanay (2008) 1. Motivation saturation
2. Completion
3. Lack of support
4.Lack of direction
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original text to further develop the relationship between the themes from the ori-
ginal articles and the newly developed overarching themes.
Triangulation: Synergistic understanding or entropy. Familiarity with triangulation
is imperative before engaging in a QIMS.
8
The purpose of triangulation in QIMS is
similar to that of triangulation in a qualitative study. Triangulation is a method
used to regulate the trustworthiness of qualitative research; specific to QIMS, this is
a means of verifying that translation across studies has provided a synergistic
understanding rather than a disordered and biased misunderstanding – entropy.
There are four types of triangulation: data collection methods, tradition, sources,
and analysts (Patton, 2002). All four types of triangulation can and should be
utilized in a QIMS. Triangulation of data collection methods, tradition, and
sources are inherent in the process with various studies providing diversity in the
three areas. For example, 1) a synthesis may include studies where data collection
methods included interviews, focus groups, and observation; 2) synthesizing across
traditions provides triangulation of traditions; and 3) multiple qualitative studies
bring multiple sources of data (e.g., multiple participants’ perspectives).
Triangulation of analysts is the key in any type of qualitative analysis, with
QIMS being no different. This is especially the case for researchers who include
their own studies to conduct a qualitative synthesis, as they will need an objective
analyst in the triangulation process. This will help prevent the inclusion of infor-
mation from the original data not included in the final report used in the synthesis.
Description of synergistic understanding. The final steps of a QIMS are descrip-
tion of the phenomena and synergistic understanding. Description of the
Table 3. Example table synthesis of themes in a QIMS.
New, overarching theme Extracted, original themes with authors and publication year
Lived experience Personal healing (Steffen & Fothergill, 2009)
Self-concept (Steffen & Fothergill, 2009)
Motivation to train – experience with sexual
violence (Rath, 2008)
Changed personal experiences (Rath, 2008)
Personal change (e.g. self-awareness) (Rath, 2008)
Internal/Personal fulfillment Motivation to train (Rath, 2008)
Desire to volunteer
Career exploration
Major life changes (Rath, 2008)
Changed personal experiences (Rath, 2008)
Motivational saturation (Yanay & Yanay, 2008)
Negative cases Lack of support (Yanay & Yanay, 2008)
Lack of direction (Yanay & Yanay, 2008)
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phenomena is when the researchers begin to develop their written report. In some
cases, the researchers may realize their findings are inadequate and further research
is required in order to strengthen the breadth of the study. This may involve
alteration of the research question to widen the sampling pool through theoretical
sampling or adjusting the parameters of the search terms. Regardless, it is import-
ant for the researcher to complete the process in the same order (see Figure 2) to
maintain the systematic process of the QIMS. This phase is relatively subjective
and may vary from researcher to researcher. The result will be synergistic under-
standing where the researcher is able to generate conclusions, theory, and implica-
tions based on the description generated from the synthesis of the included studies.
Limitations
All methods of research encompass limitations associated with data collection, data
analysis, and researcher bias – and QIMS is no exception. The main criticism of
qualitative research is the subjectivity of the data analysis and the uncontested ques-
tion of potential researcher bias. All research, both qualitative and quantitative, is
subject to possible researcher bias and the role of the researcher is to be aware and
address limitations in every research initiative and all levels of research inquiry.
Fortunately, qualitative research has established specific procedures for limiting and
minimizing researcher bias, especially through the four levels of triangulation previ-
ously discussed. A primary criticism of qualitative cross study analysis in other fields is
the recommendation we have presented here to synthesize across traditions. As noted
Figure 2. Cycles to synergy: Data extraction for synergistic understanding.
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previously, this allows for the different traditions to shed light on the different aspects
of a synergistic understanding demonstrated in QIMS. Without inclusion of all rele-
vant available studies, regardless of tradition, the understanding would be partial.
Implications for social work
QIMS provides a structured methodology for further, synergistic, understanding of
phenomena with richness in diversity of settings, participants, and qualitative trad-
itions. These synergistic understandings would be grounded in studies generated
across different qualitative traditions yet focusing on clients who share some simi-
larity depending upon the research question. Synthesis of qualitative studies and
the emergence of synergistic understanding increases efficacy in integrating quali-
tative research into evidence-based practice. It is our hope that the social work
community will embrace the technique of QIMS not only to increase the under-
standing of phenomena but to strengthen the perception of qualitative research as a
rigorous component in evidence-based practice.
Notes
1. A more detailed description of approaches is not offered here due to space limitations. For
more, please refer to Dixon-Woods, Agarwal, Jones, Young, & Sutton (2005) and Finfgeld
(2003).
2. For an in-depth discussion of interpretive synthesis, see Jensen and Allen (1996).
3. These 22 meta-syntheses were conducted under the supervision of the first author by
social work doctoral students in classes on qualitative research. These are in various
stages of the publication process with one published and one in press (Aguirre &
Bolton, forthcoming; Smith & Aguirre, 2012).
4. See Barroso et al. (2003) for information regarding retrieval of qualitative studies.
5. Researchers should refrain from looking at original data even if it is available. This
reduces the possibility of researcher bias in the analysis process.
6. A useful resource for quorum charts is Liberati et al. (2009).
7. See Zimmer (2006) for an extensive discussion.
8. This is extensively discussed in Patton (2002).
Funding
This research received no specific grant from any funding agency in the public, commercial,
or not-for-profit sectors.
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