Lecture №18
Nursing Research
PART IІ
Types of Non-probability
Sampling
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Convenience (Accidental) Sampling
Quota Sampling
Purposive Sampling
Network Sampling
Theoretical Sampling
Non-Probability Sampling
Theoretical Sampling
Quota
Purposive Sampling (Non-Randomized)
Convenience Sampling
Network
Caution Areas on Data
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You see what you look for
You look for what you know
Appropriate statistical strategies for
certain types of numbers
If you are a hammer, the world looks
like a nail
Dealing With Data (ch. 11)
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Developing Data Collection Forms
Planning Data Collection Process
Planning he Organization of Data
Planning Data Analysis
Planning Interpretation &
Communication of Findings
Evaluation of the Plan
Data Collection Tasks
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Recruiting Subjects
Maintaining Consistency
Maintaining Controls
Protecting Study Integrity
Problem-Solving
Physiological Measures:
Reliability and Validity
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Accuracy
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Selectivity
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the amount of reproducibility in measurement
Sensitivity
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the ability to identify that which is really want to
sometimes called specificity
Precision
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measurement that has the most precise identifiers for the
level of measurement sought
The amount of a changed parameter that can be detected
Sources of Error
Data Collection Problems
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People Problems
Researcher Problems
Institutional Problems
Event Problems
Measurement Validity
Measurement Reliability
Computer Support for Data
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Data Input
Data Storage
Data Retrieval
Statistical Analysis
Numbers and Use of Numbers
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Nominal (subjective)
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Ordinal (subjective)
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A scale that is subjective but shows a direction, e.g. pain
scale, cancer staging, all Likert scales
Interval (objective)
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A Named category given a number for convenience, e.g.
males are 1 and females are 2
Numbers where the interval between them is meaningful,
and there is no absolute zero but an arbitrary zero, e. g. a
temperature. These numbers can be less than zero.
Ratio (objective)
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Numbers where there is an absolute zero which means it
is absent or there is a denominator that allows for
comparison of meaning and . e. g. number of cases or
infections per 100 hospital days, stage 2 skin breakdown
per 100 patients.
Bivariate Data Analysis
Independent Groups
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Nominal Data
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Chi squared (Two or more samples)
Phi (Two samples)
Cramer’s V (Two samples)
Contingency Coefficient (Two samples)
Lambda (Two samples)
Bivariate Data Analysis
Independent Groups
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Ordinal Data
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Mann-Whitney U
Kolmogorov-Smirnov (two-sample test)
Wald-Wolfowitz Run Test
Spearman Rank-Order Correlation
Kendall’s Tau
Kruskal-Wallis One-Way Analysis of
Variance by Rank (three or > samples)
Bivariate Data Analysis
Independent Groups
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Interval or Ratio Data
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t Test for independent samples
Pearson’s Correlation
Analysis of Variance (Two or more
samples) ANOVA
Simple Regression
Multiple Regression Analysis (two or more
samples)
Bivariate Data Analysis
Dependent Groups
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Nominal Data
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McNemar Test
Cochran Q Test (three or more samples)
Ordinal Data
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Sign Test
Wilcoxon Matched-pairs, Signed-Ranks
Friedman Two-Way Analysis of Variance
by Ranks (for three or more samples)
Bivariate Data Analysis
Dependent Groups
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Interval or Ratio Data
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t Test for Related Samples
Analysis of Covariance (for three or more
samples) ANCOVA
Multivariate Data Analysis
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Interval or Ratio Data
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Multiple Regression Analysis
Factorial Analysis of Variance
Analysis of Covariance
Factor Analysis
Discriminate Analysis
Canonical Correlation
Structural Equation Modeling
Time-Series Analysis
Working with Descriptive Data:
A Toolkit for Health Care Professionals
Using Descriptive Statistics
Correlational Descriptive
Predictive Descriptive
Model Testing Descriptive
Statistics vs. Tools
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Inferential Statistic Analysis
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Statistics (regression, correlation, t-test, Ftest, Multivariate testing etc.)
Descriptive Statistic Analysis
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Tools to display information
Critical Path Process (p. 524)
1.
2.
3.
4.
5.
Select the process
Define the process
Form a team
Create the critical path
Make the path a working document
Critical Pathway for
Complaints of Chest Pain in ED
ED Patients
c/o chest pain
No previous
symptoms
Good Health
Min. Risk factors
Previous
symptoms
Has some risk
factors
Previous CAD
many risk
factors
O2, IV,
Bloods, EKG
O2, IV, Bloods, EKG
ASA, Nitroglycern
O2, IV, ASA, Beta,
Blocker, Morphine,
Cardiac Cath Lab
CCU
Force Field Analysis
Driving Issues for Moving Minimum Grade at DSN
From 72% to 74%
Driving Forces
(support efforts)
Restraining Forces
(conflict with efforts)
Comparable to Other Schools
Recent drop in NCLEX rates
Faculty requests
Significant Change in Policy
More students would fail
DSN had 90-94% NCLEX
rates with 72%
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Indicators to be Used in Hospitals
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Quantitative measures
Related to one or more dimensions of
performance
Help provide data that (when analyzed)
give information about quality
Direct attention to potential problems
Types of Indicators
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Sentinel-event indicators
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Aggregate-data indicators
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Rating for med errors and patient complaints
Continuous-variable indicators
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Serious injury or death indicator
Number of new bed sores per day
Rate-based indicators
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Infections per 1000 patient days
Run Charts
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Probably most
familiar/used tool
Used to identify
trends/patterns in a
process over time
Helps track if target
level has been
attained/maintained
Run Chart – Trend Chart
Used for Self Comparison
Quarterly report of new bed sores for Unit X 2008
40
20
0
1st Qtr
Unit X
2nd Qtr
3rd Qtr
4th Qtr
Unit X
Comparison Run Charts – Trend
Charts-(Dangerous because these
are not ratio numbers)
Quarterly report of new bed sores for Units
A, B, & X for 2008
30
20
Unit B
Unit A
Unit X
10
0
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Unit X
Unit A
Unit B
Histograms
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Bar charts that display:
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Patterns of variation
The way measurement data are distributed
Snapshot in time
May be more complex to establish;
consult statistics textbook if needed
Comparison Run Charts – Trend
Charts-(Dangerous because these
are not ratio numbers)
Quarterly report of new bed sores for Units
A, B, & X for 2008
30
25
20
Unit X
Unit A
Unit B
15
10
5
0
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Comparison Run Charts – Trend
Charts for Delta Hospital (can be
compared equally)
Quarterly report of new bed sores per 1000 patient
days for Units A, B, & X for 2008.
16
14
12
10
Unit X
Unit A
Unit B
8
6
4
2
0
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Control Chart
This is the control chart for infections from I.V.s on Unit X
With 3 case per 1000 patient days as the standard (std)
for 2008.
0.005
Max.
Std.
0.003
0.000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
x
x
x
x
x
x
x
x
x
Min.
x
x
x
Pie Charts
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Descriptive data
Shows a distribution by category
Compared to the Whole
Pie Distribution of new bed sores for
hospitalized patients at Delta Hospital
Total of 140 new bed sores reported in 2008
36
43
37
Unit X
Unit A
Unit B
Scatter Diagrams
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Graphs that show statistical correlation
between 2 variables
Used when group wants to:
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Test a theory
Analyze raw data
Monitor an action taken
Scatter Diagram Process
Min. Program Passing rates in %
76
74
72
NCLEX Scores by %
100%
Surveys
Survey’s can carry a risk to them. Also know what Likert
Scale you are using and why (1-4, 1-5, 1-10 most common).
These are Ordinal Numbers
Naturalistic Inquiry— (Ch. 3)
Qualitative Research Methods
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Phenomenology
Ethnography
Auto-ethnography
Grounded Theory
Descriptive Qualitative
Historical ?
Non-Probability Sampling
Theoretical Sampling
Quota
Purposive Sampling (Non-Randomized)
Convenience Sampling
Network
Observational Measurement
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Unstructured
Structured
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Category Systems
Checklists
Rating Scales
Emic (from within)
Etic (from external view point)
Phenomenology Research:
“The Lived Experience”
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Phenomenology is a science whose purpose
is to describe the appearance of things as a
lived experience.
It allows nursing to interpret the nature of
consciousness in the world.
It can be descriptive or interpretive
(hermeneutic).
It is a philosophy, an method, and an
inductive logic strategy
Design Characteristics
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Purposive samples of 7-20 usually going for
saturation.
Instrument is the researcher
Data collection is by interview of groups or
individual that are verbatim, taped, and
field notes.
Data collection is directly tied to analysis,
that eventually is coded or structured into
themes.
Unique Features of
Phenomenology
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Most of the literature review is conducted at
the end of the data collection. It is believed
the CF biases the data collection and
analysis.
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Like Grounded Theory but without a BSP or bias
already in mind.
It is conducted by gathering interview data
from others.
It is never quantitative, but some would
prefer to try and keep it objective.
Five Steps of the Method
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Shared Experience is presented
Transform the lived experience into an
experience the subject would agree with
Code the data
Put it into written form and create
confirmation of the data texts.
Create a complete integration of all of these
for a research document
NOTE: In come cases, researchers need to
have Bracketing to control an over-riding
bias or emotional response
Qualitative Research Rigors
The Five Standards (Ch. 13)
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Descriptive Vividness
Methodological Congruence
Theoretical Connectedness
Analytical Preciseness
Heuristic Relevance
Defining Naturalistic Rigor
Standards 1 and 2
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Descriptive vividness
 narratives are texturized, thick, and full of
details
 the writer shows connections and level of
membership
Methodological congruence
 details of exactly how the data is gathered
with ethical rigor. Does the method match
the design?
Defining Naturalistic Rigor
Standards 3, 4 and 5
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Analytical preciseness
 the data is transformed across several levels of
abstraction
 moving raw data to clusters, interpretations, or
theory
Theoretical connectedness
 ensuring the theoretical schema is clear and
related to the data being collected and a lens for
analysis
Heuristic relevance
 readers must recognize the phenomenon as
applicable, meaningful, & recognizable
Other Types of Rigor Using
Trustworthiness
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Trustworthy questions
Trustworthy approach
Trustworthy in analysis
Trustworthy and authenticity of data
Ethnography Research
Defined as:
“Learning from People”
By Spradley
Four Types of Ethnography
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Classical
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Systematic
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Defines the structure of a culture.
Interpretive (hermeneutic)
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Years in the field, constantly observing and making sense of
actions. Includes description and behavior. Attempts to describe
everything bout the culture.
To study the culture through inference and analysis looking for
“why” behaviors exist.
Critical
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Relies on critical theory. Power differentials, who gains and who
loses, what supports the status quo.
Historical Roots
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Early 1900s had several introductions
Herodotus wrote about travel in Persia
Malinowski’s Study of Trobriand Islanders
Hans Stade wrote about his being in captivity
by the wild tribes of Eastern Brazil
The School of Sociology in Chicago, where
the city was a laboratory from all the
immigrants (dancers, muggers, case studies)
Observation Methods
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Emic
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From within the research itself as a
member or participant of some type.
Etic
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From the outside looking in like a camera.
It can be a peripheral issue or external
observer member.
Fundamental Constructs
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Is usually “etic” on the outside like a
camera
Sometimes they are “emic”, on the inside as
one of the actors (more in sociology)
Researcher is the instrument
Fieldwork is where the work occurs
Focus is on culture
Involves cultural immersion
There is a tension and reflexivity between
the researcher as a member or researcher
as researcher
Stages of Ethnography
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Participant observation (gain access,
rapport, trust)
Descriptive observation (9) (space, actors,
activities, objects, act, event, time, goal,
and feelings)
Ethnographic record (field notes, verbatim,
old records, amalgamate the information)
Domain analysis
Focused observation (what is now critical)
Stages in Ethnography-2
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Taxonomic analyzing (categorize)
Componential analysis (components
of the selected areas)
Discover cultural themes
Take a cultural inventory
Write up the ethnography
Rigors for Ethnography
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Plausibility
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Credibility
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Not exactly self evident, so you look at sources
of evidence
Thick Description
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It is very easy to accept as truth
Writing in such detail as to know exactly what is
going on.
We could also use the Five Standards
Sources of Errors
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Personal reactivity
False inferences
Gaps in writing, remembering, and
interpreting
Going Native
Grounded Theory Research
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Started by Glaser and Strauss in 1967
Used extensively in nursing research
Takes into account the concepts of George
Herbert Mead (1934) regarding symbolic
interaction theory- how we give meaning to
situations, words, objects, symbols
Is very individualistic in meaning
Most often used to study areas which
previous research exists
Steps in Grounded Theory are
conducted simultaneously
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Observation
Collection of data
Organization of data
Review of additional literature
Forming theory from the data
Using Constant Comparative
Analysis
Data Collection Methods Have qualitative
and quantitative properties
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Interviews (one on one, groups)
Observation
Records (retrospective analysis)
Surveys (quantitative)
Questionnaires (could be quantitative)
Demographic data
Constructs of Grounded Theory
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Conceptual framework comes from the data
rather than the literature review
There is always an over-riding social issues
being addressed called the Basic Social
Process (BSP)
Researcher focuses on dominate processes
rather than describing the setting, or unit
You compare all data with all other data
Constructs of Grounded Theory
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You may change data collection methods in
mid stream to be more appropriate to what
has already been discovered
The researcher is to be doing most
sequential tasks all at the same time
Constant Comparative Analysis
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Get data, look at it, look at the
literature, look at previous data, go
get more data, look at more literature,
look at all the data, etc.
Revise the question, collection
method, and keep collecting data,
look at literature, compare to old data,
etc.
Sampling Methods
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Called Theoretical Sampling
 Based on the current question
 Add new groups to the sample based on
what it is you have learned (may need
more men in the sample, or more people
over the age of 70, etc.)
The sample being used moves as the theory
develops
Coding the data
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Look for positive AND negative cases
related to your social process
Step One: read, describe, and
interpret
Step Two: constant comparison and
clustering
Step Three: reduce it to a BSP
Conducting Grounded Theory
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Be aware of the social life of the participants
Make less assumptions in the beginning
Sensitizing to the literature, Bracket if needed
Layers of reality are explored, assess your own
energy to go further
Spend enough time with participants and data
Be observant to how the participants are doing
Learn the symbols being used to create this
reality
Sample across time
Case Studies
from Stake (2000) and Yin (1994)
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These are OBJECT or METHOD issues
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Object: Has to do with what you want to
study not an approach to how to study it
Method: Can be quantitative or
qualitative method (analytically, vs.
holistically)
Questions are aimed at “How” or
“Why”(rarely “What”)
Single or multiple cases-usually1or 2
Purpose of Case Studies
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Seeks the unique features (particular) while also
describing the common by describing:
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The nature of the case
The case’s history and background
The physical setting
Other contexts (economics, political, legal, aesthetic
issues)
Other cases through which this case is recognized
Through the informants by which the case is known
Examine changes across time (multiple case)
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Same group of different group
Case Study Rigor
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Yin (1994) treats this as a positivistic
activity, therefore:
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Construct, Internal, and external validity
Reliability
This is not just a pilot study for quasi- or full
experimental designs. It is different.
Stake (2000) treats it more naturalistic
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Thick description is key
Auditability (can it be followed by the reader)
Observational Measurement
Could Use all of These
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Unstructured
Structured
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Category Systems
Checklists
Rating Scales
Emic (from within)
Etic (from external view point)
Interview Data Collection
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Unstructured
Structured
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Describing interview questions
Pretesting the interview protocol
Training interviewers
Preparing for an interview
Probing
Recording interview data
Coding methods
Problem Revisions
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I am curious about the standardized
treatment protocols for circumcision of
a new borne.
NEXT REVISION
NEXT REVISION
NEXT REVISION
NEXT REVISION
Problem Statements-Questions
dictates the design
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What is experience of police officers who were
wounded in the line of duty related to their ability to
return to work?
What are the unique features of Hospitals that have
NP conducting all surgical admission assessments?
There is (is no) statistically significant difference in
iatrogenic diseases between nurse to patient ratios of
1:5 vs 1:8 on General Medical Units.
Does the birthing center philosophy show a
relationship to the type of care provided and if so,
what is the relationship.
How did the July 08 BSN cohort at DSN obtain a 99%
NCLEX pass rate?
Special Research Designs
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Triangulated, Mixed, Blended
Historical Research
Action Research
Outcome Research
Intervention Research
Triangulation
Blended Designs
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First used by Campbell and Fiske in 1959.
Denzin in 1989 identified four different
types.
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Data Triangulation
Investigator triangulation
Theoretical triangulation
Methodological Triangulation
Kimchi, Polivka, and Stevenson (1991) have
suggested a fifth type
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Multiple Triangulation
Data Triangulation
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Collection of data from multiple
sources
Intent is to obtain diverse views of the
same phenomenon. (Longitudinal is
different and is looking for change)
Validate data by seeing if it occurs
from different sources
Investigator Triangulation
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Two or more investigators with
different research backgrounds
examining the same phenomenon
Clarifies disciplinary bias
Adds to validity of data
Theoretical Triangulation
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Using all the theoretical
interpretations that could conceivably
be applied to a given area
Each view is critically examined for
utility and power
Increased the confidence of the
hypothesis
Can lead to even greater T. F. beliefs
Methodological Triangulation
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The use of two or more research
methods in a single study
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Design level
Data collection level
Two major types
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Within-method (all are one philosophy)
Across-method (across philosophies)
Pros and Cons of Triangulation
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Very trendy in the 90’s
Can be used with smaller N
Combined methods may just be the
rise of a new method
There are philosophical risks
Complex designs and therefore
complex analysis
Action Research: AKA clinical
research, clinical inquiry,
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A systematic investigation conducted by
practitioners involving the use of
scientific techniques in order to improve
their performance.
Kurt Lewin (1946).
Advantages of Action Research:
The reflective practitioner
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Contributes to the knowledge base of
teaching practice-self awareness
Supports the professional development of
practitioners –more competent in research
issues
Builds a collegial network
Identifies problems and seeks solutions in a
systematic fashion
It can be used at all levels and in all areas of
education
Examples of Action Research
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Pick a topic
Define the problem
Select a design
Select subjects
Collect the data
Analyze the data
Application of results
WHAT MAKES IT ACTION RESEARCH
What Makes it Action Research
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Invested in rigorously empirical
(positivistic), and reflective and
interpretive (naturalistic)
Engages people who have traditionally
been called “subjects” who are active in
the research process.
Results have a practical outcome
related to lives or work of participants.
Outcome Research
p.272-317
Came from evaluation research of the 70’s and 80’s
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Focuses on the end result of patient care and
linked to the process that caused the
outcome
Momentum is from policy makers, insurers,
and the public
Level of concern: 1. Care by clinician, 2.
Amenities, 3. Care by the patient, 4. Care
received by community
More complex that it may appear
Evaluation of Outcome Research

Process Evaluation
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Structure Evaluation
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Involves Standards of Care
Involves Practice Styles
Involves Cost of Care
Elements of the Structure
Philosophies of Management & Decision Making
Process
Evaluate Structure Issues and their impact on the
care provided
Lacks a set methodology
Indicators of Outcome Research

Many Descriptive Indicators for Nursing
Care: NDNQI, Picker,
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Stage all bed sores on patients at
admission vs. during stay and at discharge.
There must be a clear link between
outcome and process
We see practice based web sites:
AHRQ, APRNet, PBRN group,
Sampling in Outcome Research

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Large heterogeneous samples, but not
randomized. They want a full spectrum of the
population.
However, they want samples who were
treated and those who were not treated to
compare differences in outcomes.
Risks, no random sample, small sample sizes
are often used putting all their inferential
statistics at risk for error.
Intervention Research

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It is used to give “Causal Explanations”
for what is being seen
Uses quantitative and qualitative
methods
It is more than a single research event,
but it deals with multiple issues over
time
Intervention Research Process
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Extensive search of what information is
available
Heavy emphasis on the intervention and
refining its use
Field tested to see if it will work
It will involve a host of studies over time
Has a host of informants who explain the
local culture and what it will take to get data
Intervention Research Methods
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Integrative lit. reviews
Consumer publications
Standards/ guidelines
Meta-analysis
Health policy analysis
Personal exp. Reflections
Consensus conferences
Retrospective chart
reviews
Descriptive-Correlational
studies
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Observation
Case study
Focus groups
Qual. Studies
Concept analysis
New media
Position Papers
Delphi studies
Outcome studies
Risk for Use of Intervention
Research
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Risk is asking the wrong question
Inadequately trained interveners
Poorly defined intervention
Many confounding variables that can show up
Too complex to manage and integrate
Long time can change many factors: i.e. who
is doing it, where can you still collect data,
level of commitment by locations, etc.
Criteria for Intervention Research
Design: The intervention is--
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Effective
Replicable
Simple to use
Practical
Generalizability
Compatible with local customs and
values
Historical Research
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Thought of as qualitative because it lacks
sampling, treating, and controls.
Uses Quantitative language, i.e. validity and
reliability of data—best primary sources of
data.
Looks at external criticism of data (where,
when, by whom), and internal criticism of
data (reliability, authentic, biased lens of
writer)
Process of Historical Research
No Visible Rigor from Qualitative or Quantitative
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Research Outline
Watch for cross-referencing
Be prepared to spend months to years
collecting the data
Careful attention to note taking for all data
collection
A synthesis of all the data collected and may
need an interpretive strategy
Develop a writing outline
Write your Historiography