Expert Answer:Participant Selection/interviewing Journal/Revisin


Solved by verified expert:Preparing the Qualitative Research Plan: Considerations for Participant Selection and InstrumentationWhile some of the particulars will vary across approaches, the following are fundamental components common to all qualitative methodologies:Participant selectionInstrumentation (choices and development)Procedures for recruitment, participation, and data collectionPlan for data analysisEvaluation of trustworthinessEthical procedures for protecting participantsAnswer the discussion, workshop, journal, and assignment.Specific instructions in word documents and pdf.


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Assignment: Final Project Step I: Revising
the Problem/Purpose Statement and
Choosing the Approach

5, you will complete Step I of the Final Project. To complete Step I, do
the following:
To prepare for this Assignment:
Review your Workshop thread, paying particular attention to feedback
you collected during Weeks 1–5 on your problem statement, purpose,
research question, and approach.
Review the qualitative checklist.
Review the Final Project Rubric.
(Please address the above questions based on the journal
entries below)
The development of my research topic and research problem is too broad, I needed to
narrow it down to US Prisons and Penitentiary studies. I will critique the effectiveness of
Reentry Programs from a criminological and reformative perspective, especially in the
unpalatable truth that re-entry programs had not really reformed released prisoners , but , on the
other hand, have contributed to alarming increases in recidivism, or the return of prisons within
3-5 years after their release thus nullifying the very purpose of such Programs.
I started looking to see the correlations, (if any) between lower effectiveness of Reentry
programs, on the one hand, with increased rates of recidivism within a few years of release, on
the other, I think at this point this remains a dilemma for my research studies, and questions the
very premise of Federal and State investments in these Programs. I certainly need to do more
research to provide both qualitative as well as quantitative studies based on US Prisons and
Penitentiary studies. As I continue to research my topic I decide to change to Social Change: Re-
entry Programs and Recidivism in the United State of America. My new aim of this prospectus is
to identify, qualify, and quantify the major drivers of criminal recidivism in the United State base
on specific characteristic using research study analysis of a Prison and a Penitentiary which I’m
currently researching. I started reviewing and questioning the evidence of prisoner reentry
Next week, I plan to decide how to answer my research questions -whether to use
qualitative or quantitative data or both. I will attempt to answer: what are specific problems and
characteristics of different programs? What are the major benefits/drawbacks /limitations in the
context of the two programs I will be examining? Have these Programs helped reduce
recidivism, increased recidivism within the last decade? I’m working diligently trying to narrow
down and focus on my aim and objectives, plus other things.
Journal : 2
The development of my research topic and research problem is slowly coming together.
Last week, I narrowed it down to US Prisons and Penitentiary studies. I will critique the
effectiveness of Reentry Programs from a criminological and reformative perspective, especially
in the unpalatable truth that re-entry programs had not really reformed released prisoners, but,
on the other hand, have contributed to alarming increases in recidivism, or the return of prisons
within 3-5 years after their release thus nullifying the very purpose of such Programs.
Essentially, the primary task assumed by the study is to provide empirically- built, evidential,
triangulated studies (both qualitative and quantitative studies), based on using a research analysis

San Quentin State Prison in Marin County, Cal

Louisiana State Penitentiary, Louisiana
Problem Statement
By studying these two institutions I will examine the correlation, (if any) between lowered
effectiveness of reentry programs, if increased rates of recidivism within the first few years of
release, the flip side, remain a dilemma for my research studies, and questions the very premise
of Federal and State investments in these Programs. As many states confront substantial budget
shortfalls, it is critical that they invest in proven programs.
Aim and objectives

The main aim of this study is to identify, qualify and quantify the significant players of
criminal recidivism in the United States, vis-à-vis quality, effectiveness and efficient
deployment of result-oriented reentry programs carried out in prisons, corrective centers
and penitentiaries using research study analysis of San Quentin Prison and Louisiana
State Penitentiary.

Other objectives include qualitative studies which consider how ineffective or inadequate
re-entry programs contribute to higher rates of recidivism in general as well as specific
contextual settings.

To identify and elaborate on the correlative relationship (or lack of it) between re-entry
programs and recidivism.
Lastly, I must offer solutions to these vexatious, political, economic, criminological and
sociopathological factors arising out of increased recidivism and their barriers, challenges.
Research questions ( to be answered using both qualitative and quantitative data)

What are the specific problems and characteristics of different types of Offender Reentry
Programs targeting recidivism in the US?

In the context of San Quentin State Prison in Cal, and Louisiana State US Penitentiary,
Louisiana; what are the major benefits, drawbacks, and limitations of different Offender
Reentry Programs?

Within the last decade, have these Programs help reduce recidivism or willfully,
increased recidivism?
At the moment, I am gleaning from Criminological Journal studies, published prison researches
and also inputs from white papers on recidivism statistics and qualitative data from the San
Quentin and Louisiana State Penitentiary. I know more research is needed from various sources.
I am beginning to feel overwhelmed an anxious about this topic. I must slow down and think
about what I am aiming for on this topic.
Volume 11, No. 3, Art. 8
September 2010
Sample Size and Saturation in PhD Studies
Using Qualitative Interviews
Mark Mason
Key words:
Abstract: A number of issues can affect sample size in qualitative research; however, the guiding
saturation; sample
principle should be the concept of saturation. This has been explored in detail by a number of
size; interviews
authors but is still hotly debated, and some say little understood. A sample of PhD studies using
qualitative approaches, and qualitative interviews as the method of data collection was taken from and contents analysed for their sample sizes. Five hundred and sixty studies were
identified that fitted the inclusion criteria. Results showed that the mean sample size was 31;
however, the distribution was non-random, with a statistically significant proportion of studies,
presenting sample sizes that were multiples of ten. These results are discussed in relation to
saturation. They suggest a pre-meditated approach that is not wholly congruent with the principles
of qualitative research.
Table of Contents
1. Introduction
1.1 Factors determining saturation
1.2 Guidelines for sample sizes in qualitative research
1.3 Operationalising the concept of saturation
1.4 The issue of saturation in PhDs
2. Method
3. Results
4. Discussion
5. Conclusion
1. Introduction
Samples for qualitative studies are generally much smaller than those used in
quantitative studies. RITCHIE, LEWIS and ELAM (2003) provide reasons for this.
There is a point of diminishing return to a qualitative sample—as the study goes
on more data does not necessarily lead to more information. This is because one
occurrence of a piece of data, or a code, is all that is necessary to ensure that it
becomes part of the analysis framework. Frequencies are rarely important in
qualitative research, as one occurrence of the data is potentially as useful as
many in understanding the process behind a topic. This is because qualitative
research is concerned with meaning and not making generalised hypothesis
statements (see also CROUCH & McKENZIE, 2006). Finally, because qualitative
research is very labour intensive, analysing a large sample can be time
consuming and often simply impractical. [1]
© 2010 FQS
Forum Qualitative Sozialforschung / Forum: Qualitative Social Research (ISSN 1438-5627)
FQS 11(3), Art. 8, Mark Mason: Sample Size and Saturation in PhD Studies Using Qualitative Interviews
Within any research area, different participants can have diverse opinions.
Qualitative samples must be large enough to assure that most or all of the
perceptions that might be important are uncovered, but at the same time if the
sample is too large data becomes repetitive and, eventually, superfluous. If a
researcher remains faithful to the principles of qualitative research, sample size in
the majority of qualitative studies should generally follow the concept of saturation
(e.g. GLASER & STRAUSS, 1967)—when the collection of new data does not
shed any further light on the issue under investigation. [2]
While there are other factors that affect sample size in qualitative studies,
researchers generally use saturation as a guiding principle during their data
collection. This paper examines the size of the samples from PhD studies that
have used interviews as their source of data collection. It does not look at the
data found in those studies, just the numbers of the respondents in each case. [3]
1.1 Factors determining saturation
While saturation determines the majority of qualitative sample size, other factors
that can dictate how quickly or slowly this is achieved in a qualitative study.
CHARMAZ (2006) suggests that the aims of the study are the ultimate driver of
the project design, and therefore the sample size. She suggests that a small
study with “modest claims” (p.114) might achieve saturation quicker than a study
that is aiming to describe a process that spans disciplines (for example describing
drug addiction in a specific group rather than a description of general addiction). [4]
Other researchers have also elucidated further supplementary factors that can
influence a qualitative sample size, and therefore saturation in qualitative studies.
RITCHIE et al. (2003, p.84) outline seven factors that might affect the potential
size of a sample:
“the heterogeneity of the population; the number of selection criteria; the extent to
which ‘nesting’ of criteria is needed; groups of special interest that require intensive
study; multiple samples within one study; types of data collection methods use; and
the budget and resources available”. [5]
To this, MORSE (2000, p.4) adds, “the scope of the study, the nature of the topic,
the quality of the data, the study design and the use of what MORSE calls
“shadowed data”. [6]
JETTE, GROVER and KECK (2003) suggested that expertise in the chosen topic
can reduce the number of participants needed in a study—while LEE, WOO and
MACKENZIE (2002) suggest that studies that use more than one method require
fewer participants, as do studies that use multiple (very in-depth) interviews with
the same participant (e.g. longitudinal or panel studies). [7]
Some researchers have taken this a step further and tried to develop a debate on
the concept of saturation. MORSE (1995) feels that researchers often claim to
have achieved saturation but are not necessarily able to prove it. This is also
© 2010 FQS
FQS 11(3), Art. 8, Mark Mason: Sample Size and Saturation in PhD Studies Using Qualitative Interviews
suggested by BOWEN (2008) who feels that saturation is claimed in any number
of qualitative research reports without any overt description of what it means or
how it was achieved. To this end, CHARMAZ (2006) gives the example of a
researcher studying stigma in obese women. It is entirely possible that a
researcher will claim that the category “experiencing stigma” is saturated very
quickly. However, while an inexperienced researcher might claim saturation, a
more experienced researcher would explore the context of stigma in more detail
and what it means to each of these women (p.114). [8]
According to DEY (1999), the concept of saturation is inappropriate. He suggests
that researchers often close categories early as the data are only partially coded,
and cite others to support this practice, such as and STRAUSS and CORBIN
(1998 [1990]) who suggest that saturation is a “matter of degree” (p.136). They
suggest that the longer researchers examine, familiarise themselves and analyse
their data there will always be the potential for “the new to emerge”. Instead, they
conclude that saturation should be more concerned with reaching the point where
it becomes “counter-productive” and that “the new” is discovered does not
necessarily add anything to the overall story, model, theory or framework (p.136).
They admit that sometimes the problem of developing a conclusion to their work
is not necessarily a lack of data but an excess of it. As the analysis begins to take
shape it is important for the researcher to become more disciplined and cut data
where necessary. [9]
1.2 Guidelines for sample sizes in qualitative research
As a result of the numerous factors that can determine sample sizes in qualitative
studies, many researchers shy away from suggesting what constitutes a sufficient
sample size (in contrast to quantitative studies for example). However, some
clearly find this frustrating. GUEST, BUNCE and JOHNSON (2006, p.59)
suggest, “although the idea of saturation is helpful at the conceptual level, it
provides little practical guidance for estimating sample sizes for robust research
prior to data collection”. During the literature search for the background to their
study they found “only seven sources that provided guidelines for actual sample
sizes” (p.61):

Ethnography and ethnoscience: MORSE (1994, p.225) 30-50 interviews for
both; BERNARD (2000, p.178) states that most studies are based on
samples between 30-60 interviews for ethnoscience;

grounded theory methodology: CRESWELL (1998, p.64) 20-30; MORSE
(1994, p.225) 30-50 interviews.

phenomenology: CRESWELL (1998, p.64) five to 25; MORSE (1994, p.225)
at least six;

all qualitative research: BERTAUX (1981, p.35) fifteen is the smallest
acceptable sample (adapted from GUEST et al., 2006). [10]
While these numbers are offered as guidance the authors do not tend to present
empirical arguments as to why these numbers and not others for example. Also
© 2010 FQS
FQS 11(3), Art. 8, Mark Mason: Sample Size and Saturation in PhD Studies Using Qualitative Interviews
the issue of why some authors feel that certain methodological approaches call
for more participants compared to others, is also not explored in any detail. [11]
Further to this, other researchers have tried to suggest some kind of guidelines
for qualitative sample sizes. CHARMAZ (2006, p.114) for example suggests that
“25 (participants are) adequate for smaller projects”; according to RITCHIE et al.
(2003, p.84) qualitative samples often “lie under 50”; while GREEN and
THOROGOOD (2009 [2004], p.120) state that “the experience of most qualitative
researchers (emphasis added) is that in interview studies little that is ‘new’ comes
out of transcripts after you have interviewed 20 or so people”. [12]
While some researchers offer guidelines for qualitative samples, there is
evidence that suggests others do not strictly adhere to them. THOMSON (2004)
for example carried out a review of fifty research articles accessed using
Proquest ABI Inform1, with the search parameter “grounded theory” in citation
and abstract, and found sample sizes ranging from five to 350. Just over a third
(34%) used samples between CRESWELL’s suggested range of 20 and 30
(1998, p.128)—while only 11 studies (or 22%) used samples in MORSE’s range
of over 30 (1994, p.225). [13]
1.3 Operationalising the concept of saturation
There is an obvious tension between those who adhere to qualitative research
principles, by not quantifying their samples—and those who feel that providing
guidance on sample sizes is useful. Some researchers have gone further than
providing guidelines and have tried to operationalise the concept of saturation,
based on their own empirical analysis. [14]
Possibly the first to attempt this were ROMNEY, BATCHELDER and WELLER
(1986) who developed an analysis tool called the “Cultural Consensus Model”
(CCM ) for their ethnographic work. This sought to identify common
characteristics between communities and cultural groups. The model suggests
that each culture has a shared view of the world, which results in a “cultural
consensus”—the level of consensus of different topics does vary but there are
considered to be a finite set of characteristics or views. ROMNEY et al. suggest
these views can then be factor analysed to produce a rigorous model of the
cultures views on that topic. The subsequent analysis tool has also been used by
some to estimate a minimum sample size—recently for example by ATRAN,
MEDIN and ROSS (2005, p.753) who suggested that in some of their studies “as
few as 10 informants were needed to reliably establish a consensus”. [15]
GRIFFIN and HAUSER (1993) reanalysed data from their own study into
customers of portable food containers. Using a model developed by VORBERG
and ULRICH (1987) they examined the number of customer needs uncovered by
various numbers of in-depth interviews and focus groups. Their work was
1 [Accessed:
May 24, 2010]. Proquest AB Inform is an electronic/online database which provides access to
publications principally in the areas of: Industry, Business, Finance and Management.
© 2010 FQS
FQS 11(3), Art. 8, Mark Mason: Sample Size and Saturation in PhD Studies Using Qualitative Interviews
undertaken from a market research perspective to assist in the development of
robust bids and campaigns. Because of their analysis, they hypothesized that
twenty to thirty in-depth interviews would be needed to uncover ninety to nine-five
per cent of all customer needs. [16]
Most recently, GUEST et al. (2006) carried out a systematic analysis of their own
data from a study of sixty women, involving reproductive health care in Africa.
They examined the codes developed from their sixty interviews, in an attempt to
assess at which point their data were returning no new codes, and were therefore
saturated. Their findings suggested that data saturation had occurred at a very
early stage. Of the thirty six codes developed for their study, thirty four were
developed from their first six interviews, and thirty five were developed after
twelve. Their conclusion was that for studies with a high level of homogeneity
among the population “a sample of six interviews may [be] sufficient to enable
development of meaningful themes and useful interpretations” (p.78). [17]
1.4 The issue of saturation in PhDs
GREEN and THOROGOOD (2009 [2004]) agree with GUEST et al., and feel that
while saturation is a convincing concept, it has a number of practical
weaknesses. This is particularly apparent in what they call “funded work” (or that
limited by time). They suggest that researchers do not have the luxury of
continuing the sort of open-ended research that saturation requires. This is also
true when the point of saturation (particularly in relation to an approach like
grounded theory methodology, which requires that all of the properties and the
dimensions are saturated) they consider to be “potentially limitless” (p.120). They
go on to add that sponsors of research often require a thorough proposal that
includes a description of who, and how many people, will be interviewed at the
outset of the research (see also SIBLEY, 2003). They further suggest that this
also applies to ethics committees, who will want to know who will be interviewed,
where, and when, with a clearly detailed rationale an …
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