This document discusses various topics related to nursing research methods. It describes different types of non-probability sampling including purposive sampling, theoretical sampling, convenience sampling, quota sampling, and network sampling. It also discusses caution areas when working with data, such as biases that can influence data collection and analysis. Finally, it provides an overview of descriptive and inferential statistics that can be used for bivariate and multivariate data analysis in nursing research.

1. NURSING
RESEARCH
Nursing Path
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2. Types of Non-probability
Sampling
 Convenience (Accidental) Sampling
 Quota Sampling
 Purposive Sampling
 Network Sampling
 Theoretical Sampling
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3. Non-Probability Sampling
Purposive Sampling (Non-Randomized)
Theoretical Sampling
Convenience Sampling
Quota
Network
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4. Caution Areas on Data
 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
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5. Dealing With Data (ch. 11)
 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
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6. Data Collection Tasks
 Recruiting Subjects
 Maintaining Consistency
 Maintaining Controls
 Protecting Study Integrity
 Problem-Solving
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7. Physiological Measures:
Reliability and Validity
 Accuracy
 measurement that has the most precise identifiers for the
level of measurement sought
 Selectivity
 the ability to identify that which is really want to
sometimes called specificity
 Precision
 the amount of reproducibility in measurement
 Sensitivity
 The amount of a changed parameter that can be detected
 Sources of Error
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8. Data Collection Problems
 People Problems
 Researcher Problems
 Institutional Problems
 Event Problems
 Measurement Validity
 Measurement Reliability
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9. Computer Support for Data
 Data Input
 Data Storage
 Data Retrieval
 Statistical Analysis
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10. Numbers and Use of Numbers
 Nominal (subjective)
 A Named category given a number for convenience, e.g.
males are 1 and females are 2
 Ordinal (subjective)
 A scale that is subjective but shows a direction, e.g. pain
scale, cancer staging, all Likert scales
 Interval (objective)
 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)
 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.
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11. Bivariate Data Analysis
Independent Groups
 Nominal Data
 Chi squared (Two or more samples)
 Phi (Two samples)
 Cramer’s V (Two samples)
 Contingency Coefficient (Two samples)
 Lambda (Two samples)
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12. Bivariate Data Analysis
Independent Groups
 Ordinal Data
 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)
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13. Bivariate Data Analysis
Independent Groups
 Interval or Ratio Data
 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)
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14. Bivariate Data Analysis
Dependent Groups
 Nominal Data
 McNemar Test
 Cochran Q Test (three or more samples)
 Ordinal Data
 Sign Test
 Wilcoxon Matched-pairs, Signed-Ranks
 Friedman Two-Way Analysis of Variance
by Ranks (for three or more samples)
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15. Bivariate Data Analysis
Dependent Groups
 Interval or Ratio Data
 t Test for Related Samples
 Analysis of Covariance (for three or more
samples) ANCOVA
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16. Multivariate Data Analysis
 Interval or Ratio Data
 Multiple Regression Analysis
 Factorial Analysis of Variance
 Analysis of Covariance
 Factor Analysis
 Discriminate Analysis
 Canonical Correlation
 Structural Equation Modeling
 Time-Series Analysis
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17. Working with Descriptive Data:
A Toolkit for Health Care Professionals
Using Descriptive Statistics
Correlational Descriptive
Predictive Descriptive
Model Testing Descriptive

18. Statistics vs. Tools
 Inferential Statistic Analysis
 Statistics (regression, correlation, t-test, F-
test, Multivariate testing etc.)
 Descriptive Statistic Analysis
 Tools to display information
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19. Critical Path Process (p. 524)
1. Select the process
2. Define the process
3. Form a team
4. Create the critical path
5. Make the path a working document
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20. Critical Pathway for
Complaints of Chest Pain in ED
O2, IV,
Bloods, EKG
No previous
symptoms
Good Health
Min. Risk factors
O2, IV, Bloods, EKG
ASA, Nitroglycern
Previous
symptoms
Has some risk
factors
O2, IV, ASA, Beta,
Blocker, Morphine,
Cardiac Cath Lab
CCU
Previous CAD
many risk
factors
ED Patients
c/o chest pain
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21. Force Field Analysis
Driving Forces
(support efforts)
Comparable to Other Schools
Recent drop in NCLEX rates
Faculty requests

Restraining Forces
(conflict with efforts)
Significant Change in Policy
More students would fail
DSN had 90-94% NCLEX
rates with 72%

Driving Issues for Moving Minimum Grade at DSN
From 72% to 74%
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22. Indicators to be Used in Hospitals
 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
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23. Types of Indicators
 Sentinel-event indicators
 Serious injury or death indicator
 Aggregate-data indicators
 Rating for med errors and patient complaints
 Continuous-variable indicators
 Number of new bed sores per day
 Rate-based indicators
 Infections per 1000 patient days
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24. Run Charts
 Probably most
familiar/used tool
 Used to identify
trends/patterns in a
process over time
 Helps track if target
level has been
attained/maintained
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25. Run Chart – Trend Chart
Used for Self Comparison
0
20
40
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
Unit X
Unit X
Quarterly report of new bed sores for Unit X 2008
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26. Comparison Run Charts – Trend
Charts-(Dangerous because these
are not ratio numbers)
0
10
20
30
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
Unit X
Unit A
Unit B
Unit X
Unit A
Unit B
Quarterly report of new bed sores for Units
A, B, & X for 2008
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27. Histograms
 Bar charts that display:
 Patterns of variation
 The way measurement data are distributed
 Snapshot in time
 May be more complex to establish;
consult statistics textbook if needed
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28. Comparison Run Charts – Trend
Charts-(Dangerous because these
are not ratio numbers)
0
5
10
15
20
25
30
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
Unit X
Unit A
Unit B
Quarterly report of new bed sores for Units
A, B, & X for 2008
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29. Comparison Run Charts – Trend
Charts for Delta Hospital (can be
compared equally)
0
2
4
6
8
10
12
14
16
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
Unit X
Unit A
Unit B
Quarterly report of new bed sores per 1000 patient
days for Units A, B, & X for 2008.
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30. Control Chart
Max.
Min.
Std.
0.005 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
x x x
x x x x x
0.003 x x x
x
0.000
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.
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31. Pie Charts
 Descriptive data
 Shows a distribution by category
 Compared to the Whole
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32. Pie Distribution of new bed sores for
hospitalized patients at Delta Hospital
Unit X
Unit A
Unit B
Total of 140 new bed sores reported in 2008
43
37
36
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33. Scatter Diagrams
 Graphs that show statistical correlation
between 2 variables
 Used when group wants to:
 Test a theory
 Analyze raw data
 Monitor an action taken
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34. Scatter Diagram Process
Min. Program Passing rates in %
NCLEX Scores by %
72
74
76
100%
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35. 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
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36. Naturalistic Inquiry— (Ch. 3)
Qualitative Research Methods
 Phenomenology
 Ethnography
 Auto-ethnography
 Grounded Theory
 Descriptive Qualitative
 Historical ?
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37. Non-Probability Sampling
Purposive Sampling (Non-Randomized)
Theoretical Sampling
Convenience Sampling
Quota
Network
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38. Observational Measurement
 Unstructured
 Structured
 Category Systems
 Checklists
 Rating Scales
 Emic (from within)
 Etic (from external view point)
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39. Phenomenology Research:
―The Lived Experience‖
 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
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40. Design Characteristics
 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.
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41. Unique Features of
Phenomenology
 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.
 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.
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42. Five Steps of the Method
 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
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43. Qualitative Research Rigors
The Five Standards (Ch. 13)
 Descriptive Vividness
 Methodological Congruence
 Theoretical Connectedness
 Analytical Preciseness
 Heuristic Relevance
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44. Defining Naturalistic Rigor
Standards 1 and 2
 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?
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45. Defining Naturalistic Rigor
Standards 3, 4 and 5
 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
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46. Other Types of Rigor Using
Trustworthiness
 Trustworthy questions
 Trustworthy approach
 Trustworthy in analysis
 Trustworthy and authenticity of data
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47. Ethnography Research
Defined as:
―Learning from People‖
By Spradley

48. Four Types of Ethnography
 Classical
 Years in the field, constantly observing and making sense of
actions. Includes description and behavior. Attempts to describe
everything bout the culture.
 Systematic
 Defines the structure of a culture.
 Interpretive (hermeneutic)
 To study the culture through inference and analysis looking for
“why” behaviors exist.
 Critical
 Relies on critical theory. Power differentials, who gains and who
loses, what supports the status quo.
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49. Historical Roots
 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)
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50. Observation Methods
 Emic
 From within the research itself as a
member or participant of some type.
 Etic
 From the outside looking in like a camera.
It can be a peripheral issue or external
observer member.
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51. Fundamental Constructs
 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
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52. Stages of Ethnography
 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)
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53. Stages in Ethnography-2
 Taxonomic analyzing (categorize)
 Componential analysis (components
of the selected areas)
 Discover cultural themes
 Take a cultural inventory
 Write up the ethnography
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54. Rigors for Ethnography
 Plausibility
 It is very easy to accept as truth
 Credibility
 Not exactly self evident, so you look at sources
of evidence
 Thick Description
 Writing in such detail as to know exactly what is
going on.
 We could also use the Five Standards
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55. Sources of Errors
 Personal reactivity
 False inferences
 Gaps in writing, remembering, and
interpreting
 Going Native
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56. Grounded Theory Research
 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
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57. Steps in Grounded Theory are
conducted simultaneously
 Observation
 Collection of data
 Organization of data
 Review of additional literature
 Forming theory from the data
 Using Constant Comparative
Analysis
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58. Data Collection Methods Have qualitative
and quantitative properties
 Interviews (one on one, groups)
 Observation
 Records (retrospective analysis)
 Surveys (quantitative)
 Questionnaires (could be quantitative)
 Demographic data
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59. Constructs of Grounded Theory
 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
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60. Constructs of Grounded Theory
 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
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61. Constant Comparative Analysis
 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.
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62. Sampling Methods
 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
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63. Coding the data
 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
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64. Conducting Grounded Theory
 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
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65. Case Studies
from Stake (2000) and Yin (1994)
 These are OBJECT or METHOD issues
 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
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66. Purpose of Case Studies
 Seeks the unique features (particular) while also
describing the common by describing:
 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)
 Same group of different group
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67. Case Study Rigor
 Yin (1994) treats this as a positivistic
activity, therefore:
 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
 Thick description is key
 Auditability (can it be followed by the reader)
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68. Observational Measurement
Could Use all of These
 Unstructured
 Structured
 Category Systems
 Checklists
 Rating Scales
 Emic (from within)
 Etic (from external view point)
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69. Interview Data Collection
 Unstructured
 Structured
 Describing interview questions
 Pretesting the interview protocol
 Training interviewers
 Preparing for an interview
 Probing
 Recording interview data
 Coding methods
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70. Problem Revisions
 I am curious about the standardized
treatment protocols for circumcision of
a new borne.
 NEXT REVISION
 NEXT REVISION
 NEXT REVISION
 NEXT REVISION
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71. Problem Statements-Questions
dictates the design
 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?
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72. Special Research Designs
 Triangulated, Mixed, Blended
 Historical Research
 Action Research
 Outcome Research
 Intervention Research
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73. Triangulation
Blended Designs
 First used by Campbell and Fiske in 1959.
 Denzin in 1989 identified four different
types.
 Data Triangulation
 Investigator triangulation
 Theoretical triangulation
 Methodological Triangulation
 Kimchi, Polivka, and Stevenson (1991) have
suggested a fifth type
 Multiple Triangulation
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74. Data Triangulation
 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
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75. Investigator Triangulation
 Two or more investigators with
different research backgrounds
examining the same phenomenon
 Clarifies disciplinary bias
 Adds to validity of data
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76. Theoretical Triangulation
 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
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77. Methodological Triangulation
 The use of two or more research
methods in a single study
 Design level
 Data collection level
 Two major types
 Within-method (all are one philosophy)
 Across-method (across philosophies)
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78. Pros and Cons of Triangulation
 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
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79. Action Research: AKA clinical
research, clinical inquiry,
 A systematic investigation conducted by
practitioners involving the use of
scientific techniques in order to improve
their performance.
 Kurt Lewin (1946).
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80. Advantages of Action Research:
The reflective practitioner
 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
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81. Examples of Action Research
 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
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82. What Makes it Action Research
 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.
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83. Outcome Research p.272-317
Came from evaluation research of the 70’s and 80’s
 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
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84. Evaluation of Outcome Research
 Process Evaluation
 Involves Standards of Care
 Involves Practice Styles
 Involves Cost of Care
 Structure Evaluation
 Elements of the Structure
 Philosophies of Management & Decision Making
Process
 Evaluate Structure Issues and their impact on the
care provided
 Lacks a set methodology
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85. Indicators of Outcome Research
 Many Descriptive Indicators for Nursing
Care: NDNQI, Picker,
 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,
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86. Sampling in Outcome Research
 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.
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87. Intervention Research
 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
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88. Intervention Research Process
 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
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89. Intervention Research Methods
 Integrative lit. reviews
 Consumer publications
 Standards/ guidelines
 Meta-analysis
 Health policy analysis
 Personal exp. Reflections
 Consensus conferences
 Retrospective chart
reviews
 Descriptive-Correlational
studies
 Observation
 Case study
 Focus groups
 Qual. Studies
 Concept analysis
 New media
 Position Papers
 Delphi studies
 Outcome studies
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90. Risk for Use of Intervention
Research
 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.
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91. Criteria for Intervention Research
Design: The intervention is---
 Effective
 Replicable
 Simple to use
 Practical
 Generalizability
 Compatible with local customs and
values
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92. Historical Research
 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)
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93. Process of Historical Research
No Visible Rigor from Qualitative or Quantitative
 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
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94. Thank You
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