NSR 338: Research in Nursing Dennis Ondrejka, Ph.D., R.N.

1
NSR 338 Research in NursingDennis Ondrejka,
Ph.D., R.N.

• 303-292-0015, ext. 3625 office
• d.ondrejka_at_denverschoolofnursing.edu
• Fall, 2009

2

• Is nursing a profession?
• Q.1 What are the criteria for a profession?

3
Nursing Profession or Technical Occupation?

• Pavalkos (1971) Continuum Model for a
• Profession
• Theory
• Relevance to social values
• Education
• Motivation
• Autonomy
• Commitment
• Sense of community
• Code of ethics

4
Explore the Meaning of a Professional vs.
Technical Practice

• Describe the similarities or differences between
  the chef at the Brown Palace the cook at the
  Village Inn?

Cook
Chef
5
Professional vs. Technicalfor all practice areas

• Professional Practices
• Have a culture that supports professional
  activities frameworks, CE, research
• Has a defined body of knowledge gained by formal
  education
• Is a discipline with peer review and a code of
  ethics
• Autonomy in practice with legislative and legal
  sanctions
• Is an organized system of practice recognized by
  society

• Technical Occupations
• Are more likely to have more OJT than formal
  education.
• Are skill focused
• Have trade journals or technique trainings
• Do not focus on what advances the practice
• Develop through certifications
• Want less accountability

6
Professional vs. TechnicalThinking and Valuing

• Professional thinking
• More is best
• Specialization in depth and breadth
• Evidence-based education
• Invests energy beyond the work-associations,
  research, reading
• Expects self accountability
• Resilient with change and believes change is
  valuable

• Technical Thinking
• Least is best
• Specialization in depth
• Experience is the primary educator
• Conserves energy beyond the workday
• Prefers others be accountable
• Enjoys consistency and believes change is
  disruptive

7

• Is research important to the profession?
• Yes!! Research is important for
• building a unique, systematic
• body of knowledge about
• a discipline

8
Nursing needs a systematic body of knowledge to
...

• Promote Evidence-based practice
• Give credibility to profession
• Provide accountability for practice
• Help document the cost-effectiveness of care
  (Nieswiadomy, 2008)

9
What is Evidence Based Nursing Practice?

• Knowledge from science research
• Knowledge from experts
• Knowledge from patients
• Knowledge arriving in many forms
• Has levels of power and rigor
• EBP IS NOT JUST FROM RESEARCH

10
Evidence Based Practice Definition

• the integration of current best evidence with
  clinical expertise and patient values (Sackett
  et al., 2000)
• a framework for clinical practice that
  incorporates the best available scientific
  evidence with the expertise of the clinician and
  the patients preferences and values to make
  decisions about health care. (Levin, 2006)

11
What is Research?

• Process of searching for new knowledge about
  phenomena
• Validates and refines existing knowledge (Burns
  Grove, 2007)
• Systematic process of inquiry or study
• Builds new knowledge through the dissemination of
  findings

12
Why Research???

• To Describe
• To identify and understand the nature of nursing
  phenomena
• What is the experience of growing up poor in
  Manhattan?
• To Explain
• Clarifies the relationship among phenomena, and
  why certain events occur
• What are the factors that supported DSN graduates
  to pass NCLEX at 95 in 2009?

13
Why Research???

• To Predict
• This allows us to estimate the probability of a
  specific outcome in a given situation
• There is a statistical difference in baseline
  patient glucose levels when using basilar method
  over sliding scale.
• To Control or Manipulate
• If we can predict, the next goal would be to
  control or manipulate the situation to produce
  the desired outcome.
• We can reduce bed sores at all stages by rotating
  patients every two hours maximum.

14
Ways We Acquire Knowledge

• Tradition
• Authority
• Borrowing
• Trial and error
• Personal experience
• Role-modeling mentoring
• Intuition

• Reasoning
• Inductive-gather
• Deductive-divide
• Rational-logic
• Unstructured
• Research
• Quantitative
• Qualitative
• Mixed / Other

15
Research Defined

• Research is a systematic, diligent inquiry that
  is necessary to address
• What needs to be known-what is the question,
  hypothesis, or interest area
• What research methods are needed to examine this
  question or phenomena
• What meaning can be extracted from the study
  through data analysis to build our knowledge base
  of that subject
• Generate outcomes and disseminate new knowledge

16
Ways to Study Research

• By its components (questions, rigors, sampling
  method, measurement method, etc)
• Divided into two major types
• Qualitative
• Quantitative
• By the name of the method (experimental,
  phenomenology, etc)
• By the philosophy it uses to inquire
  (positivistic, naturalistic, both, neither)

17
Burns Grove method Examine Your Text

• Table of Contents 7 Ch. 1
• Ch. 2 Quantitative Research
• Ch. 3 Qualitative Research (philosophy
  discussed)
• CH. 4 tries to address both qualitative and
  quantitative questions
• Ch. 5, 6 Lit review, Study Frameworks Theory

18
Examine Your Text

• Ch. 7 ethics
• Ch. 8 Clarify Designs (quantitative)
• Ch. 9 Outcomes Research
• Ch. 10 Populations and Sampling for
  quantitative and qualitative methods
• Ch. 11 Measurement of Data quantitative and
  qualitative
• Ch. 12 Understanding Statistics

19
Examine Your Text

• Ch. 13 Critiquing Research for qualitative
  (five Standards) and quantitative.
• Ch. 14 Building an Evidence Based Practice

20
Ch. 14 Evidence Based Practice

• Research Utilization (RU) may have a lag time for
  Practice up to 20 years
• Involves being a Change Agent. (DSN uses the I2E2
  model for change in third quarter)
• Best Evidence by research type
• Integrative Reviews (many types of designs)
• Systematic Reviews (focused on a particular type
  of research designs)
• Meta-Analysis (has statistical evaluation of
  quantitative designs).
• Metasummaries Metasynthesis (qualitative
  research)

21
Hierarchy of EvidenceCompare to Florczak article

• Level I A systematic review or RCTs,
  meta-analysis of many randomized controlled
  trials (RCTs)
• Level II Integrative Reviews of experimental
  designs
• Level III from a well-designed controlled trial
  without randomization
• Level IV From case-control or cohort studies

22
Hierarchy of EvidenceCompare to Florczak article

• Level V From systematic reviews of descriptive
  or qualitative studies, metasummaries,
  metasynthesis,
• Level VI a single descriptive or qualitative
  study
• Level VII It is an opinion from authorities on
  that subject, or expert committee

23
Recent Changes in Nursing

• Page 500, second paragraph, Using ASA 81 mg. in
  at risk adults
• Page 517, I.V. flush using 0.9 NS vs. heparin. P
  P on page 520.
• Algorithms on page 524 for tx HTN.
• I.V. skin prep using chlorhexidine vs. Iodine
  products like providone-iodine
• Strait cath urethra prep

24
Mydsn.org, NRS 338

• Evidence Based Research
• www.cochrane.org/
• www.guideline.gov
• http//www.cebm.utoronto.ca/resources/websites.htm
  
• www.ahcpr.gov/clinic/
• http//www.crd.york.ac.uk/crdweb/

25
Research Philosophy MethodPositivistic versus
Naturalistic Inquiry

• This is a 100 year old debate
• It is often correlated to research methodology
• It is a philosophy on the way we think about
  human phenomenon inquiry (research)
• We can integrate two different inquiry
  methodologies, but philosophically they are very
  different (mixed or blended design)
• Our philosophy is the foundation for how we
  design research

26
Positivistic Inquiry Naturalistic Inquiry
(Constructivism) Quantitative
Triangulated Qualitative
 Solomon Design Blended
Designs Post-modern -four group design
- use quantitative
-pretest-treat-post test Intervention Res
qualitative -research self
-pretest-no treat- post test methods
-novel sounding -no pre- no treat- post test
lacks theory -random group
Quasi-Experimental Grounded Theory
Phenomenology -validated tools
-two of three -theory building
- descriptive
Exp. controls -Basic Social Process
- interpretive
- hermeneutic Descriptive
Experimental Design
- quantitative or Ethnography -random
sample qualitative methods
-living in the experience -control group

-cultural immersion -a treatment
given Outcome Research
Case Study Epidemiology (humans
Ds) -single-double cases
Analytic Epi -In-depth
analysis
Descriptive Epi - comparative
analysis Action Research Adeq
uate time commitment Collaborative
effort Openness to change Quality of data
collection and analysis Impact on ones
practice
27
Positivistic Inquiry Naturalistic Inquiry
(Constructivism) Quantitative
Triangulated Qualitative  Solomon
Design Blended Designs Post-modern
Quasi-Experimental Grounded Theory
Phenomenology Constant Comparative
Analysis Descriptive
Experimental Design
Ethnography
Case Study Scientific Rigors by
DesignQuantitative Research RigorValidity
Reliability (internal-external)
Qualitative Research Rigor
Conceptual Framework
Developed Descriptive Vividness Statistical
Inference Methodological CongruenceGeneralizabi
lity Analytical PrecisenessTemporality Theor
etical Connectedness Selection and
Bias Heuristic RelevanceMeasurement validity /
reliability Trustworthiness, Credibility,
Controlling confounders and AuditabilityApprop
riate study design for the questions Confirmabili
ty, transferability Stylistic Personal
Relevance, Heuristic
28
Sample Size by DesignPositivistic Inquiry
Naturalistic Inquiry (Constructivism) Quant
itative Triangulated
Qualitative  Solomon Design Blended
Designs Post-modern Power
Analysis
20-40
1
Quasi-Experimental
Grounded Theory
Phenomenology gt40
10-1000 10saturation (10-30)
Descriptive
Experimental Design
1-12
Ethnography Power Analysis
1 Case Study

1-2 Action
Research ?-100
29
Assumptions of Positivistic Thinking

• Reality is singular, tangible, and can be
  dissected
• The researcher and those being studied are
  independent
• Time and context-free generalizations are
  possible
• Inquiry is value-free

singular reality
value free
Positivistic thinking
independent variables
generalizable
30
Assumptions of Positivistic Thinking

• There are real causes or at least high
  probability of a relationship.
• We believe we can have independent and dependent
  variables as separate entities
• Validity of a design is very critical to results

singular reality
value free
Positivistic thinking
cause effect
validity
independent variables
generalizable
31
Assumptions of Positivistic Thinking

• Reliability is based on how the design is
  reproducible
• Generalizability is related to good internal
  validity and reliability with comparable samples
• Hypothesis testing

value-free
reliability
hypothesis testing
singular reality
Positivistic thinking
cause effect
validity
generalizable
independent variable
32
Assumptions of Naturalistic Inquiry

• Realities are multiple, pluralistic, and holistic
• The researcher cannot really be separated from
  those being studied and relation-ships are
  explained
• hypotheses are time and context bound - they are
  only working statements

multiple realities
naturalistic inquiry
hypothesis is a focus area
researcher subject connected
33
Assumptions of Naturalistic Inquiry

• All entities are in a state of mutual
  simultaneous shaping
• Inquiry is value-bound
• Validity is designed into the process
• Reliability general- izable are not concepts of
  value with this thinking

multiple realities inquiry is value bound
Naturalistic inquiry
hypothesis is a focus area
researcher subject connected
thick description
34
Differences in Scientific Rigorpositivistic nat
uralistic

• Validity
• Internal and external reliability
• Hypothesis testing
• Statistical inferences
• Independent and dependent variables
• Variable controls
• Generalizability

• Descriptive Vividness
• Methodological Congruence
• Analytical Preciseness
• Theoretical Connectedness
• Heuristic Relevance
• Others

35
Data Collection Differencepositivistic naturali
stic

• Tools
• surveys, questionnaires
• objective assessment identification
• Measure the dependent variable
• Convert to numeric symbols
• Apply statistical inferences to numbers
• Large sample sizes help with confidence levels

• Tool
• is the investigator by interview, focus groups,
  observation
• Data is subjective and objective. It is
  collected not measured
• Themes or clusters are identified and data is
  sorted in a theme analysis
• The themes are supported by participants or
  experts

36
Differences in Results positivistic naturalistic

• The exploration description of a phenomenon
• Identification of linkages, relationships, or
  interpretations based on theory connections
• Results are themes, clusters of ideas, or theory
  constructs

• Statistical significance for pre-post treatment
• Statistical correlations relationships
  identified
• Probability of errors confidence identified
• Causal relationships

37
Positivistic Discussion of Results

• 250 nurses were surveyed with an 80 response
  rate or N200. Questions were rated using the
  Likert 5 scale. Question 1 had a mean of 4.2
  with a S.D. of 0.5 suggesting the nurses had
  favorable opinions about continuing education.
  Compared to a 1994 survey asking the same
  question, there was a statistical difference that
  was less favorable (mean 3.1, S.D. 0.7, plt.05)

38
Naturalistic Description

• I sat in the classroom as a peripheral member
  staying as unobtrusive as possible. The
  instructor came out from behind her desk, sitting
  on the edge as she opened with a question that
  brought all eyes in the room to meet her own
  eyes. She paused - looked at the eyes of the
  students.
• The instructor displayed immediacy from the
  moment she started the class.

39
Ethics and Research (Ch. 7)

• Starts with the study purpose, design, methods of
  measurement, and subjects
• Guidelines for all of these
• It is still a concern today
• More recent ethical issues are
• Fabrication of a study
• Falsification or forging of data
• Dishonest manipulation of the design or methods
• Plagiarism
• 50 of the top 50 research institutions in US
  have been investigated for research fraud

40
Ethical Problems in History

• Nazi medical experiments (1933-1945)
• Tuskegee syphilis study by the USPHS (1932-1972)
• Willowbrook study (1950-1970) Hepatitis study
• Jewish Chronic Disease Hospital study with live
  CA cells in 1960s

41
Ethical Problems in History

• University Atomic Energy Government Exp.
• 18 men and women injected with plutonium to
  determine body distribution (at the time said to
  be terminal) 1945-47
• 20 subjects ages 63-83 given doses of radioactive
  radium and thorium inj. or oral. 1961-65
• 64 male inmates at Washington St. Prison had
  testicular radiation to determine the smallest
  does to makes someone sterile. 1963-70
• 125 retarded residents were fed radioactive ir9n
  and calcium to see if a diet rich in cereal would
  block the digestion of those two minerals.
  1946-56

42
Nuremberg Code-1949

• Voluntary consent
• Must yield fruitful results for society
• Anticipated results justify the type of
  experiment
• Avoids all unnecessary physical-mental injury
• Cannot do studies that have a known injury or
  death unless the exp. Physician is a subject
• Risk does not out weight humanitarian benefit
• Proper precautions to prevent injury, dis., death
• Conducted by qualified persons
• Subjects can always stop the study
• Researcher must always be ready to stop the study
  (risk)

43
Declaration of Helsinki-1964-84

• Differentiated therapeutic vs. non-therapeutic
  research
• Clinical vs. Basic
• Greater care to protect subjects in
  non-therapeutic research
• There must be a strong, independent justification
  for exposing a healthy vol. to substantial risk
• The investigator is to protect the health and
  life of research subjects

44
The Belmont ReportThree Ethical Principles

• Principle of respect for persons
• Right to self determination and freedom to
  participate or not
• Principle of Beneficence
• Do no harm to others
• Principle of Justice
• Treat everyone fairly without discrimination
• Led to USDHHS Code on Ethics
• Title 45, Part 46 (45 CFR 46)
• Office of Human Subjects Research (OHSR) within
  NIH
• http//helix.nih.gov8001/ohsr

45
Institutional Review Board (IRB)

• Provides oversight on all ethical issues related
  to someone doing research
• Consent forms (voluntary subjects)
• Disclosure forms
• Confidentiality
• Compensation disclosure
• Ethics documented in the research
• Accountability to rules, regulations, and legal
  entities
• Protects at risk populations

46
The Literature Review

• Primary Sources
• Secondary Sources
• Theoretical literature
• Empirical (Research) literature
• Evidence Based Research Sites
• www.cochrane.org/
• www.guideline.gov
• http//www.cebm.utoronto.ca/resources/websites.htm
  
• www.ahcpr.gov/clinic/
• http//www.crd.york.ac.uk/crdweb/

47
Definition of a Literature Review (Ch. 5)

• A systematic and explicit approach to the
  identification, retrieval, and bibliographical
  management of independent studies locating
  information synthesizing developing
  guidelines

48
Purposes of the Lit. Review

• Facilitate development of the Conceptual
  Framework by summarizing knowledge
• Clarify the research topic
• Clarify the research problem
• Verify the significance of the research problem
• Specify the purpose of the study
• Describe relevant studies or theories
• Develop definitions of major variables
• Select a research design, data measurement, data
  collection analysis, interpret findings

49
Literature Searches

• Ebscohost with CINAHL http//search.ebscohost.co
  m
• Log in DSN
• Password evidence
• Mydsn.org
• NRS 338
• Data bases

50
Understanding Research Designs

• Can have confusing terms
• Research Methodology
• The entire process from question to analysis
• Research Design
• Clearly defined structures within which the study
  is implemented
• Is a large blueprint, but must be tailored to the
  study and then mapped out in detail

51
Quantitative Designs (Ch. 2)

• What are the four types of
• Quantitative Designs?

52
Quantitative Designs

• Experimental
• Quasi-experimental
• Descriptive
• Correlational
• Aim to describe, compare, and predict in order to
  understand or control phenomena

53
Quantitative Designs

• What characterizes true Experimental Research
  Designs?

54
True Experimental Research Designs

• Are characterized by
• Random assignment of subjects to groups
• Comparison of treatment group(s) with a
• Control or business as usual group

55
True Experimental Research Designs (cont.)

• Also characterized by
• Strict control of extraneous variables
• to obtain true representation of cause
• and effect
• Note use causality language with caution!!!
  (there is always a P-value)
• Ex Smoking and cancer

56
Randomized Controlled Clinical Trials (RCT)

• True Experimental Design
• Large N ( of subjects)
• Draw subjects from reference population
• Randomly assign subjects to treatment/experimen
  tal or control group
• Examine for baseline equivalence
• Multiple sites used for generalizability

57
Quasi-Experimental Research Designs

• Are characterized by
• Treatment or intervention
• Comparison of treatment group(s) with a
• control or business as usual group
• Non-equivalence of groups--not randomly assigned
  group assignment often evolves naturally?
  convenience sampling)
• Ex Pts. on one unit compared to pts. on another

58
Quasi-Experimental Research Designs (cont.)

• Also are characterized by
• Aiming to represent cause and effect in
  situations where less control over variables
  exists
• Most frequently used design in nursing

59
Correlational Designs

• Descriptive correlational designs
• Used to describe variables and to examine
  relationships between or among variables
• Predictive correlational designs
• Used to predict value of one variable based on
  values obtained for another variable
• Independent variable used to predict Dependent
  variable ? Regression
• Model-testing design
• Looks at relationships among a of variables

60
Correlational Designs

• Descriptive correlational designs
• Used to describe variables and to examine
  relationships between or among variables
• Predictive correlational designs
• Used to predict value of one variable based on
  values obtained for another variable
• Independent variable used to predict Dependent
  variable

61
Quantitative Design Concerns

• Primary purpose (check question)
• Is there a treatment (intervention)
• Will the treatment be controlled
• Is there a control (untreated) group
• Is there a pre or post test (or both)
• Is sample random
• Will sample be a single group or divided into
  several groups

62
Quantitative Design Concerns-2

• How many groups will there be
• What is the size of each group
• Will groups be randomly assigned
• Will there be repeated measurements over time or
  will the data be collected cross-sectionally at
  one or two points in time
• Have extraneous variables been identified and
  controlled for
• What strategies are being used to compare
  variables or groups

63
Research Question Considerations

• Ethics
• Significance
• Motivation
• Qualifications
• Feasibility

64
Hypotheses and Research Qs

• Hypotheses Intelligent guesses about predicted
  relationships
• Problem statement ? what the issue/concern/problem
  is and why it should be addressed
• Research Qs Burning question

65
What are Criteria for Hypotheses? (Ch. 4)

• Declarative
• Written in present tense
• Include population
• Identify variables
• Reflect the problem/concern
• Are empirically testable

66
Independent Dependent Variables

• Independent (IV)
• The treatment
• The intervention
• That which is manipulated
• Dependent (DV)
• Outcome
• What is being measured
• The difference

67
Types of Hypotheses Simple Complex

• Simple
• One Independent Variable (IV) and one Dependent
  Variable (DV)
• Complex
• Two or more IVs, two or more DVs, or
• both, being investigated at same time

68
Hypothesis 1

• Average length of gestation is shorter for
  infants of mothers who use cocaine than among
  mothers who use alcohol during the last six
  months of pregnancy.
• Population? IV? DV?
• Simple or complex?

69
Hypothesis 2

• The greater the degree of sleep deprivation, the
  higher the anxiety levels of intensive care unit
  patients.
• Population? IV? DV?
• Simple or complex?

70
Hypothesis 3

• The total wt. loss of overweight elementary
  students who follow a reduced calorie diet and
  exercise 20 minutes four times a week will be
  greater than those students who do not follow a
  reduced calorie diet and do not exercise 20
  minutes four times a week.
• Population? IV? DV?
• Simple or complex?

71
Hypothesis 4

• The degree of stress reported by flight-for-life
  nurses is greater than the degree of stress
  reported by ICU nurses.
• Population? IV? DV?
• Simple or complex?

72
Name that Hypothesis 5

• More domestic violence and levels of anger are
  reported by veterans who served in the military
  in Iraq compared to those in the military who
  served in Afghanistan.
• Population? IV? DV?
• Simple or complex?

73
Sample of Research Topic Questions

• Topic Adolescent sexuality
• Problem statement (e.g., pregnancy rates in US
  are much higher compared to most Western
  countries)
• Research Question
• Will high school adolescent males report higher
  levels of comfort with their own sexuality than
  will females?
• Hypothesis
• Adolescent males in grades 9 12 will report
  statistically higher levels of comfort with their
  own sexuality than will females in the same
  grades.

74
Quantitative Design Concerns

• Primary purpose (check question)
• Is there a treatment (intervention)
• Will the treatment be controlled
• Is there a control group (untreated)
• Is there a pre or post test (or both)
• Is the sample a random sample
• Will the sample be a single group or divided into
  several groups

75
Quantitative Design Concerns-2

• How many groups will there be
• What is the size of each group
• Will groups be randomly assigned
• Will there be repeated measurements
• Will the data be collected cross-sectionally or
  over time
• Have extraneous variables been identified and
  controlled for
• What strategies are being used for comparison of
  variables or groups

76
Components of Study Validity

• Definition It is an examination of the
  approximation of truth or falsity of the
  propositions
• Statistical Validity (right stats used)
• Internal Validity (sample represents the
  population being studied)
• Construct Validity (concept Operational def. of
  variable match, instrument accuratly measures
  theoretical constructs it purports to measure.
• External Validity (methods allow for
  generalizability)
• (Cook and Campbell, 1979)

77
Statistical Validity Errors

• Violate assumptions about the data
• Nominal, ordinal, interval, ratio data
• Type I and Type II errors
• Need for Power Analysis
• Predicts the necessary N value
• Inappropriate use of certain statistics for the
  various types of data
• Random irrelevancies in setting
• Random heterogeneity of respondents

78
Statistical Conclusion ValidityType I and Type
II Errors

• Accept the Null Hypothesis
  Reject the Null Hypothesis
• Reality is Type I Error
• No Desired There is no difference
• difference caused by fishing
• Reality is Type II Error, there is
• There is a difference often caused Desired
  
• Difference by a low N value

79
Internal Validity

• Definition
• It is the extent to which the effects detected
  in the study are a true reflection of reality
  rather than the result of extraneous variables
• The independent variable did have an impact
  on the dependent variable and it was not by
  random chance (p value)

80
Threats to Internal Validity

• History Natural events over time impacting the
  subjects
• Maturation A persons growth in any area
  impacting his/her response
• Testing effect caused by subjects remembering
  previous testing
• Instrument reliability of treatment
• Selection process (randomized)
• Mortality threat
• Interaction with subjects
• No equalization of treatment

81
External Validity

• Definition
• To provide development of the design that allows
  it to be generalized beyond the sample used in
  the study.
• Most serious threat is that the results can only
  be said of the group being studied

82
Threats to External Validity

• Small N
• No randomization when it is needed
• Poor sample representation either by type,
  geography, or some other characteristic
• Cannot be replicated for some extraneous variable

83
Factors Influencing Sample Size

• Effect Size
• The degree to which the phenomenon is present in
  the population or to which the null hypothesis is
  false.
• It is hard to detect an effect from an
  intervention if the sample is small
• Type of study conducted
• Case study, phenomenology, experimental,
  Descriptive

84
Factors Influencing Sample Size

• The number of variables
• This requires a power analysis to determine the
  necessary N
• Measurement Sensitivity
• The ability of the measurement to find what it
  thinks it is finding.
• Data Analysis Techniques
• The various statistics can impact the number of
  subjects needed.

85
Types of Probability Sampling

• Simple Random Sampling (select those with
  specific characteristics)
• Stratified Random Sampling (2 or more strata of
  population)
• Cluster Sampling (all states, cities)
• Systematic Sampling (every nth)
• Random Assignment to Groups (Treatment and
  Control)

86
Types of Non-probability Sampling

• Convenience (Accidental) Sampling
• Quota Sampling
• Purposive Sampling
• Network Sampling
• Theoretical Sampling

87
Non-Probability Sampling
Purposive Sampling (Non-Randomized)
Theoretical Sampling
Quota
Convenience Sampling
Network
88
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

89
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

90
Data Collection Tasks

• Recruiting Subjects
• Maintaining Consistency
• Maintaining Controls
• Protecting Study Integrity
• Problem-Solving

91
Physiological MeasuresReliability 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

92
Data Collection Problems

• People Problems
• Researcher Problems
• Institutional Problems
• Event Problems
• Measurement Validity
• Measurement Reliability

93
Computer Support for Data

• Data Input
• Data Storage
• Data Retrieval
• Statistical Analysis

94
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.

95
Bivariate Data AnalysisIndependent Groups

• Nominal Data
• Chi squared (Two or more samples)
• Phi (Two samples)
• Cramers V (Two samples)
• Contingency Coefficient (Two samples)
• Lambda (Two samples)

96
Bivariate Data AnalysisIndependent Groups

• Ordinal Data
• Mann-Whitney U
• Kolmogorov-Smirnov (two-sample test)
• Wald-Wolfowitz Run Test
• Spearman Rank-Order Correlation
• Kendalls Tau
• Kruskal-Wallis One-Way Analysis of Variance by
  Rank (three or gt samples)

97
Bivariate Data AnalysisIndependent Groups

• Interval or Ratio Data
• t Test for independent samples
• Pearsons Correlation
• Analysis of Variance (Two or more samples) ANOVA
• Simple Regression
• Multiple Regression Analysis (two or more samples)

98
Bivariate Data AnalysisDependent 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)

99
Bivariate Data Analysis Dependent Groups

• Interval or Ratio Data
• t Test for Related Samples
• Analysis of Covariance (for three or more
  samples) ANCOVA

100
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

101
Working with Descriptive DataA Toolkit for
Health Care Professionals Using Descriptive
Statistics

• Correlational Descriptive
• Predictive Descriptive
• Model Testing Descriptive

102
Statistics vs. Tools

• Inferential Statistic Analysis
• Statistics (regression, correlation, t-test,
  F-test, Multivariate testing etc.)
• Descriptive Statistic Analysis
• Tools to display information

103
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

104
Critical Pathway for Complaints of Chest Pain in
ED
105
Force Field Analysis
Driving Issues for Moving Minimum Grade at DSN
From 72 to 74

• 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
• ?

106
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

107
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

108
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

109
Run Chart Trend ChartUsed for Self Comparison
Quarterly report of new bed sores for Unit X 2008
110
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
111
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

112
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
113
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.
114
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 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
Max.
Std.
Min.
115
Pie Charts

• Descriptive data
• Shows a distribution by category
• Compared to the Whole

116
Pie Distribution of new bed sores for
hospitalized patients at Delta Hospital
Total of 140 new bed sores reported in 2008
36
43
37
117
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

118
Scatter Diagram Process

• Min. Program Passing rates in

76

74
72
NCLEX Scores by
100
119
Surveys
Surveys 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
120
Naturalistic Inquiry (Ch. 3) Qualitative
Research Methods

• Phenomenology
• Ethnography
• Auto-ethnography
• Grounded Theory
• Descriptive Qualitative
• Historical ?

121
Non-Probability Sampling
Purposive Sampling (Non-Randomized)
Theoretical Sampling
Quota
Convenience Sampling
Network
122
Observational Measurement

• Unstructured
• Structured
• Category Systems
• Checklists
• Rating Scales
• Emic (from within)
• Etic (from external view point)

123
Phenomenology ResearchThe 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

124
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.

125
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.

126
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

127
Qualitative Research RigorsThe Five Standards
(Ch. 13)

• Descriptive Vividness
• Methodological Congruence
• Theoretical Connectedness
• Analytical Preciseness
• Heuristic Relevance

128
Defining Naturalistic RigorStandards 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?

129
Defining Naturalistic RigorStandards 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

130
Other Types of Rigor Using Trustworthiness

• Trustworthy questions
• Trustworthy approach
• Trustworthy in analysis
• Trustworthy and authenticity of data

131
Ethnography Research

• Defined as
• Learning from People
• By Spradley

132
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.

133
Historical Roots

• Early 1900s had several introductions
• Herodotus wrote about travel in Persia
• Malinowskis 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)

134
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.

135
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 as researcher

136
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)

137
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

138
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

139
Sources of Errors

• Personal reactivity
• False inferences
• Gaps in writing, remembering, and interpreting
• Going Native

140
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

141
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

142
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

143
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

144
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

145
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.

146
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

147
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

148
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

149
Case Studiesfrom 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

150
Purpose of Case Studies

• Seeks the unique features (particular) while also
  describing the common by describing
• The nature of the case
• The cases 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

151
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)

152
Observational Measurement Could Use all of These

• Unstructured
• Structured
• Category Systems
• Checklists
• Rating Scales
• Emic (from within)
• Etic (from external view point)

153
Interview Data Collection

• Unstructured
• Structured
• Describing interview questions
• Pretesting the interview protocol
• Training interviewers
• Preparing for an interview
• Probing
• Recording interview data
• Coding methods

154
Problem Revisions

• I am curious about the standardized treatment
  protocols for circumcision of a new borne.
• NEXT REVISION
• NEXT REVISION
• NEXT REVISION
• NEXT REVISION

155
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 15 vs 18 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?

156
Special Research Designs

• Triangulated, Mixed, Blended
• Historical Research
• Action Research
• Outcome Research
• Intervention Research

157
TriangulationBlended 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

158
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

159
Investigator Triangulation

• Two or more investigators with different research
  backgrounds examining the same phenomenon
• Clarifies disciplinary bias
• Adds to validity of data

160
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

161
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)

162
Pros and Cons of Triangulation

• Very trendy in the 90s
• 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

163
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).

164
Advantages of Action ResearchThe 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

165
Examples of Action Research

• Pick a topic
• Define the problem
• Select a design
• Select subjects
• Collect the data
• Analyze the data
• Application of results