Overview of Evidence-basedPractice and the Research Pro.docx

Overview of Evidence-based
Practice and the Research Process
What is EVIDENCE BASED PRACTICE?
A systematic review of critical appraisal and synthesis of the
most relevant research.
Clinical Expertise
Patient Preferences and Values

Initiatives to Advance EBP
To Err is Human: Institute of Medicine (IOM): Building a Safer
Health System
Initiatives driving the movement
IOM’s goal: By 2020, 90% health care will be evidence-based
US Preventive Services Task Force (sponsored by AHRQ):
analyzing evidence and publishing guidelines (Guide to
Preventive Clinical Services)
Magnet Recognition Program (ANA): mandate nursing research
and use of EBP
Goal of EBP
OPTIMUM PATIENT OUTCOMES
Once you begin to look for
evidence-based projects,
you’ll start to see them everywhere!

SOURCES OF EVIDENCE
Research Findings
Agency quality monitoring data
Data from national databases
Expert opinions
Scientific principles
Research prOCESS

Conducting Research:
Steps of the Research Process
1. Identify issue or question
2. Formulate research question
3. Review the literature
If further research is needed:
4. Determine theoretical framework
5. Design the study
6. Select the sample
7. Collect data
8. Analyze data
9. Interpret results
If indicated, change practice!
Step ONE: Identify issue

Step Two: formulate Research Question
Conducting Research: Formulating the research question
Research Questions (quantitative):
Identify the target population
State an intervention or treatment (independent variable)
List the variables to be measured/outcomes (dependent
variables)
Sample Research Question
Do pediatric patients who are given a
reward when they cooperate during
nursing procedures tend to be more
cooperative during those procedures
than unrewarded peers?

12
Sample Research Question
What are the relationships among spiritual well-being, sleep
quality, and health status in HIV-infected men and women?
13
Research Question:
What are the effects of weekly quizzes on the grades of nursing
students?
What is the target audience?
What is the independent variable?
What is the dependent variable?

Research Question:
Do nursing students who participate in study groups earn
higher grades on final exams?
Research Question:
Is there a difference in patient satisfaction scores
between patients who have had nursing students care for them
and patients who have not had nursing students assigned to
them?

Avoid “Yes” or “No” Question Formats
Practice
Identify the Variables
Do nursing home residents who are praised

by nursing personnel for self-feeding
require less assistance in feeding than
those who are not praised?
19
Do pediatric patients who are given a
reward when they cooperate during
nursing procedures tend to be more
cooperative during those procedures
than unrewarded peers?
20

For nurses working in psychiatric wards, does a 5-day training
course in aggression management positively influence nurses’
tolerance towards patient aggression and their feeling toward
aggressive patients?
21
Do students participating in the Crawford Intervention sessions
have higher physical activity and lower dietary fat intake
compared with students not in the intervention group?
22

What are the effects of Behavioral Change
Intervention (BCI) in self-efficacy and
outcome expectations for exercise and
functional activity, physical activity
participation, and physical performance
of older adults in Thailand?
23
Does a telephone therapy intervention for patients with prostate
cancer cause improvements in their psychological distress and
coping skills?

24
What are the effects of animal-assisted therapy on the
nutritional intake of individuals with Alzheimer disease?
25
Conducting Research: Formulating the research hypothesis
Research Hypothesis H1
The results a researcher expects to get about the relationships
among variables
Null Hypothesis H0
The prediction that there will be no relationships among the
variables

Conducting Research: Formulating the research hypothesis
Research Question
What are the effects of weekly quizzes on the grades of
nursing students?
Research Hypothesis H1
Weekly quizzes will improve the grades of nursing
students.
Null Hypothesis H0
Weekly quizzes will not influence the grades of nursing
students.
Research Question
What are the effects of weekly quizzes on the grades of
nursing students?
Research Hypothesis
Weekly quizzes will improve the grades of nursing
students.

28
Research Hypothesis
The results a researcher expects to get about the relationships
among variables
Null Hypothesis
The prediction that there will be no relationships among the
variables
29
Research Question
What are the effects of weekly quizzes on the grades of nursing
students?
Null Hypothesis
Weekly quizzes will not influence the grades of nursing
students.

30
Step three: review the literature
Step Four: Determine Theoretical Framework
Conducting Research: Determine theoretical framework
A theory is an idea or explanation
related to a particular subject.

Every research study is based on theory
Predetermined nursing theory
Researcher’s own theory
Theories from other disciplines
Often times it is not mentioned in report/article
Research is based on theory. Research finds out if the parts of
the theory hold up.
Theory is initial inspiration for research study
Research helps answer the question “Were the predictions based
on my theory correct?”

Step five: Design the Study
Conducting Research: Design the study
Differences Between Two Research Methods
Quantitative Research
Qualitative Research
Conducting Research: Design the study
Quantitative Research
“A formal, objective, rigorous, systematic process for
generating information

about the world.”
Conducting Research: Design the study: Quantitative
Research
Truth is absolute.
A single reality can be found by careful research.
Researcher must be objective.
Conducted to test theory, examine relationships among
variables, and determine cause-and-effect relationships.
Conducting Research: Design the study: Qualitative
research
Qualitative Research
“A systematic, subjective approach
used to describe life experiences
and give them meaning.”

research
Truth is relative; there are multiple truths. What is true for one
person may not be true for another.
“Truth” can only be discovered by working to understand a
person’s perspective.
Conducted to promote understanding of human experiences and
situations
research
Qualitative research questions
The population (What are the characteristics of the patients or
clients?)
The situation (What conditions, experiences, or circumstances
are we interested in understanding?)

research
Examples of qualitative research questions
What is the lived experience of being a nursing student?
What is it like to receive a terminal diagnosis?
What is it like to be a graduate nursing student?
Quantitative Designs
Quantitative Design
Important terms:
Rigor: degree of precision of measuring tools,
representativeness of sample, maximum control of variables

Control: researcher control over variables
More important terms:
Bias
Something that distorts the findings of a research study
For example:
Members of this class would bias a study
about the public’s understanding of the
value of nursing care.
Manipulation
Controlling a treatment or intervention
For example:
The researcher controlled the length of time
between administration of pain medication.

Generalizable
The degree to which a study’s findings
are true for the entire target population
For example:
Because the sample was large enough and members of the study
groups were randomly selected, the findings of the study are
assumed to be true for everyone.
Four quantitative research designs:
Descriptive (non-experimental)
Correlational (non-experimental)
Quasi-experimental
Experimental
Types of Studies Described by Time Factors
Cross Sectional Design
Longitudinal (prospective, cohort)

Retrospective (case-control)
Descriptive Designs
Exploration and description
May describe characteristics of people
May determine the frequency of something
May categorize data
Used to examine variables and
characteristics of subjects.
Example of Descriptive Study
A researcher wanted to learn about women’s experiences during
menopause. She measured the frequency of the symptoms, the
average age at menopause, and the percentage of women using
medications to alleviate symptoms.

Measurements used in Descriptive Studies
Frequencies
Averages
Percentages
Proportions
Incidence
Prevalence
Rate
Risk
Types of Descriptive Studies
Case Study Design
Descriptive
Comparative Descriptive
Descriptive Correlational
Descriptive Design
Example
Homeless African-American women
compared to homeless white women for
differences in health promoting behaviors.

Case Study Descriptive Design
The study of one patient, family, or organization.
Example
The family of a blind child was studied
to learn how this family coped with
their child’s blindness through
his growth and development stages.
Cross Sectional Descriptive Design
A study that follows the same subjects at only one point in time
instead of across time.
Example
Surgeons and OR nurses in one hospital were surveyed to
determine degree of compliance with universal precautions.
Descriptive Longitudinal Studies

(Prospective, Cohort)
Conducted on a cohort of people over a period of time going
forward
Usually very long-term projects
Very expensive
Sample must be free of the disease/illness at the start of the
study
Descriptive Longitudinal Design
A study that follows the same subjects over a long period of
time.
Example
Surgeons and OR nurses in one hospital were surveyed every
month for one year to determine changes in the degree of their
compliance with universal precautions.
Descriptive Retrospective Studies
(Case-Control)
Conducted on the past records of a group of people
Less expensive than longitudinal studies
Starts with a group of people with a disease and another group
without the disease
Looks for differences between the two groups in the past

Correlational Designs
Investigate relationships among variables
Measure strength of relationship (-1 to +1)
Measure direction of relationship (positive or negative)
Example of Correlational Study
(a descriptive correlational, retrospective study)
Researchers studied the records of infants who died of SIDS and
a group who didn’t to compare them on birth weight, maternal
characteristics, fetal heart variability, and sleep-wake cycles
Types of Correlational Studies
Descriptive Correlational Design
Predictive Correlational Design

Descriptive Correlation Design
Used to describe variables and examine relationships among
these variables.
Example
Homeless adolescents were studied
to discover the reasons they give for being
homeless, their resilience, and risky behavior.
Predictive Correlation Design
Used to predict the value of one variable based on the values
obtained for other variables
Example
The self-esteem, perceptions of childbearing, race, social status,
and relationships with family members of adolescent girls were
examined to identify those at risk for adolescent motherhood.

Experimental Research
Examines causal relationships between independent variable on
dependent variable
Most rigorous research design
Highly controlled
Maximum control of variables
Example of Experimental Study
Researchers compared post-acute intermediate care in an
inpatient nurse-led unit and conventional post-acute care on
general medical wards. They looked at variables such as
patients’ length of stay, functional status, and mortality. All
patients were randomly assigned to the unit or ward.
Experimental Research
3 main characteristics:
Controlled manipulation of independent variable
Treatment or intervention
Random assignment of subjects to control and experimental
groups

Types of Experimental Studies
Pretest-posttest design (could also be quasi-experimental)
Clinical trial
Quasi-Experimental Research
Examines causal relationships OR effects of one variable on
another
Involves a treatment or intervention and measuring the effects
of the treatment or intervention
Experimental design without random assignment of subjects
Example of Quasi-experimental Study
A researcher evaluated the effectiveness of a violence-
prevention intervention for nursing assistants working in long-
term care. The intervention was implemented in three nursing
homes, and three other nursing homes served as the comparison.

Causality
when an independent variable causes
an effect in a dependent variable
For example:
Smoking causes cancer.
Multicausality
when there is more than one independent variable that causes an
effect in a dependent variable
For example:
Smoking and oral contraceptives cause
increased risk of cancer.

Degree of Rigor and Control
DESCRIPTIVE high rigor, low control
CORRELATIONAL high rigor, low control
QUASI-EXPERIMENTAL high rigor, partially controlled
EXPERIMENTAL high rigor, totally controlled
Step six: select the sample
Sample Selection
Population
(Target Population)
The entire set of people
who meet the sampling criteria

Sample Selection
Subjects
People who are being studied
Sample Selection
Sample
the selected group of
people taking part in the study
Sample Selection
Accessible population
The portion of the target population to which the researcher has
access

Sample Selection
Sampling criteria
Eligibility criteria
Inclusion criteria
Exclusion criteria
Sample Selection
Representativeness
The sample, the accessible population,
and the target population must
be as similar as possible
Sample Selection
Sampling Bias
The systematic over-representation or

under-representation of some segment
of the population
Sample Selection
Sampling Bias
For example:
We are conducting a study on nursing students and collected
data from the first 10 students who entered the library. What
bias are we introducing into the sample?
Choosing a Sample from the Sampling Frame
Random sampling methods (for quantitative studies)
Simple random sampling
Stratified random sampling
Cluster sampling
Systematic sampling

84
Table of Random
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46305658205083124006709588811914497585207524200700788
41841037287917610095315411195946495192663747862275997
06416424993000243315604741784210478436022815218528465
00895764314698372261006360245976346845630741770768049
74201515422229402084785970538146343053514133654152708
55142284335173922755
Practice
Which type of sampling is this?

In order to select a sample of patients with asthma, a researcher
first randomly selected a sample of pulmonary clinics and then
a sample of asthma patients from each clinic.
In order to select a sample of nursing students, a researcher
randomly selects 10 nursing schools on the east coast and then 5
nursing schools in one zip code are randomly selected.
In order to select a sample of nursing students, a researcher first
obtained a list of all nursing schools in the US by BSN or RN-
BSN, then randomly selected 10 schools from each type, and
then a sample of students divided by BSN students and RN-BSN
students and randomly selected 100 students from each school.

In order to select a sample of ResU nursing students, a
researcher put each student’s name in a hat and drew names.
In order to select a sample of nursing students at ResU, a
researcher obtained a list of all students, then randomly selected
every 10th student on the list.
Sample Selection
Non-random sampling (for quantitative studies)
Convenience sampling
Quota sampling
Snowball sampling
Consecutive sampling
Purposive sampling

Practice
In order to select a sample of nursing students at WSCN, a
researcher visited a class and asked for volunteers.
In one nursing school 20% of the students were Asian, 33%

were Hispanic, 19% were African American, and 28% were non-
Hispanic white. In order to select a representative sample of
nursing students at WSCN, a researcher accepted the same
proportions of students (by ethnicity) for the study.
Sample Selection
Power analysis
The number of subjects you need for the study.
Sample size is affected by the research design, number of
variables, sensitivity of the measuring tools, effect size and data
analysis techniques.
Step seven: collect the data

Continuous Variables
A variable with an infinite number of possible values falling
along a continuum
Example: age
Discrete Variables
A variable with a finite and small number of possible values
falling along a continuum
Example: grade in elementary school
Collect the Data
The measurement of concrete variables is considered to be
“direct measures.”
Examples

BP, height, weight, EKG, bladder scans, gtts per minute of IV
fluid
Collect the Data
The measurement of abstract variables is called “indirect
measures.”
Generally, multiple indirect measures are needed to measure an
abstract variable for a study.
Collect the Data
Examples of Indirect Measures
IQ tests
Stress scales
Scores on a tool that measures Coping
Patient satisfaction

Collect the Data
Measurement Error
the difference between true measure and what is actually
measured
Collect the Data
A researcher used a blood pressure cuff that was calibrated
1.8mmHg too high. The blood pressures of all subjects of the
study were 1.8mmHg higher than the true measurement.
This is an example of a systematic error.
Collect the Data
Another researcher used a blood pressure cuff that was
calibrated correctly, but didn’t place the stethoscope correctly
for all subjects. The blood pressures of some subjects of the
study were too high or too low.
This is an example of a random error.

Collect the Data
Levels of Measurement
(Types of Variables)
Nominal
Ordinal
Interval
Ratio
Steps Eight and Nine will be discussed
Next week
Review of reliability and validity

Reliability
Reliability is the ability of an instrument to measure a concept
or construct consistently.
Three attributes of reliability:
Stability of the instrument (produces the same results with
repeated testing)
Homogeneity (or internal consistency) of the instrument (all
items measure the same construct)
Equivalence (produces the same results when equivalent
instruments are used)
Reliability
Types of reliability:
Interrater reliability: two or more instructors will give the same
scores
Test-retest reliability: no matter how many times a test is given,
the student will make the same grade
Equivalent forms reliability: different versions of a test produce
the same scores
Internal consistency: all items/questions of a test produce the

same scores
Reliability
Measured with correlation coefficients
(called reliability coefficients)
Validity
Validity is the degree to which an instrument accurately
measures what it is supposed to measure.
Validity

How valid is the use of a yardstick to measure length?
How valid is the use of a thermometer to measure temperature?
How valid is the use of an IQ test to measure intelligence?
How valid is the use of the Kozlarek personality test to measure
personality traits?
Validity
How valid is the use of the Patel test to rate faculty
effectiveness?
Sample question
Rate your instructor’s availability:
a. always available
b. sometimes available
c. rarely available

Types of Validity
Content validity:
measures a representative sample
of the construct and only that construct
(it must measure all parts of the construct and not include parts
of other constructs)
If a research exam contains questions about APA rules, is it a
valid test for knowledge about research?
Types of Validity
Face validity:
the extent to which, on the surface, the tool looks like it is
measuring the construct
Types of Validity
Criterion-related validity
Concurrent validity (correlation of one known test with another)

Predictive validity (correlation between the measure of the
construct and a future measure of the construct-does it
accurately predict an outcome?)
Types of Validity
Construct validity
measures a theoretical construct, attribute, or trait (something
that cannot be directly observed)
by observing behavior or comparing a characteristic to a known
relationship
Examples: racial prejudice, love, creativity
Validity
Measured with correlation coefficients.

Ethical considerations in research
Protection of Human Subjects
3 ethical principles relevant to research
Respect for Persons
Beneficence
Justice
Respect for Persons
Each individual:

Is unique and free
Has the right and capacity to decide
Has value and dignity
Has the right to informed consent
Respect for Persons
People are autonomous agents who have the right to self-
determination
They must be informed about a study.
They can choose whether or not to participate in a study.
They may withdraw from a study at any time without negative
consequences.
Respect for Persons

Right to Privacy:
People have the right to determine the time, extent, and general
circumstances under which their private information will be
shared with or withheld from others.
Anonymity
Confidentiality
Respect for Persons
You must be able to show that potential subjects comprehended
the risks and potential benefits.
Avoid the use of coercion or undue influence.
Informed consent

Respect for Persons
When compensation is provided:
Fully explained and not coercive
Fair payment for time, travel, and inconvenience
Degree of health care to be made available
Respect for Persons
People with diminished autonomy are vulnerable and must have
additional protection.
Legal or mental incompetence
Terminal illness
Confinement to an institution
Pregnant women, fetuses and neonates
Children
Economically or educationally disadvantaged

Respect for Persons
Children provide assent,
their parents provide permission.
Beneficence
Do No Harm!
Maximize possible benefits,
minimize possible harm.

Justice
Treat groups fairly and equitably
Use fair procedures in sample selection
Make sure people aren’t considered for inclusion because of
their availability, compromised position, or vulnerability.
Summary
Respect for Persons
Informed consent
Right to privacy
Additional protection for vulnerable people
Beneficence
Maximize benefits, minimize harm
Justice
Watch for unfair sample selection or treatment

IRB Process
IRB Committee
concerned only with protection of human subjects
must approve research proposal before data can be collected
must monitor the study
USE OF CLINICAL GUIDELINES
Use of Clinical Guidelines
Use existing clinical guidelines to find gaps in empirical
knowledge.

Unit 2: Analyzing Data
Statistical Tests of Significance
Parametric tests meet the assumptions that the dependent
variable (s):
Have an interval or ratio level of measurement
Have a normal distribution in the population
Data can be treated as random samples
Whereas, Nonparametric tests don’t meet any of these
assumptions and are done on nominal or ordinal data only!
137
Testing the Reliability of Measures
If the coefficient is 1.00, each item in the instrument is
consistently measuring the same thing.
A slightly lower coefficient (0.80 to 0.90) indicates that the
instrument is measuring quite well.

A coefficient below 0.70 indicates that there is a problem with
some of the items and the researcher should not analyze the data
collected with the instrument (scale).
A reliability of 0.70 means that 70% of the time you can trust
the score to accurately reflect what is being measured
138
Level of Significance and Probability
Level of Significance

How does a researcher decide how much of a difference is a
significant difference?
An instructor is teaching students about the research process.
She will give you a final exam to determine how much you have
learned.
What score will indicate that students have learned enough to
pass? 50%? 75%? 90%?
Researchers have to decide the “passing scores” for their
studies.
They use probabilities (p) to do so.

A probability states the likelihood that scores or groups are the
same.
The most common level of significance for most nursing studies
is 5%, or .05.
(p) = .05
For example:
A researcher conducts a study to see if support hose prevents
muscle pain in people with PVD.
75% of the experimental group (who wore the support hose)
reported less muscle pain, while
38% of the control group experienced less muscle pain.
Was there a difference between the 2 groups?
The researcher finds that the probability of subjects in Group A
being different than the Group B subjects is 80%. (8 out of 10
Group A subjects experienced a different level of muscle pain

than the Group B subjects.)
p = .20
Probability Theory
Probability is the chance that
a certain outcome
will occur from some random process
146
Normal (Bell) Curve
A normal curve is a theoretical frequency distribution of all
possible values in a population…no real distribution of values
from a study will exactly fit the normal curve.
Levels of significance and probability are based on the logic of
the normal curve.
It is a way to look at the distribution of the values obtained
from a sample.
147

Normal Bell Curve
148
“Tailedness” and the Normal Curve
One-tailed test of significance… the hypothesis is directional
with extreme scores in only one tail of the curve
Two-tailed test of significance is used when the researcher does
not know which way the scores will fall…either tail
149
One-Tailed Test
150

Two-Tailed Test of Significance
151
Inference and Generalization
An inference is a conclusion or judgment based on evidence
An inference is made from the statistical findings obtained from
a specific sample and applied to the general population.
Generalization is extending the findings from a sample to a
larger population.
Ex: A researcher may conclude that a significant difference was
found between two samples, one in which the subjects had been
catheterized during hospitalization and another in which the
subjects had not. The findings are generalized from the study
sample to all previously hospitalized patients.
152

Analyzing Quantitative Data
Selecting a statistical test is based on:
Research design
Levels of measurement
Number of groups
Four quantitative research designs:
Descriptive
Correlational
Quasi-experimental
Experimental

Descriptive Analysis
Used to describe samples
Used for data analysis in Descriptive Studies
Types of Descriptive Analyses
Descriptive statistics
Frequency distribution
Percentage distribution
Measures of Central Tendency (mean, median, and mode)
Measures of Dispersion (variability)
Range
Variance
Standard Deviation

Measures of Central Tendency
A measure of central tendency is frequently referred to as an
“average”
Defined: Statistical procedures for determining the center of a
distribution of scores.
Three are commonly used in statistical analyses:
Mode
Median
Mean
159
Mode
The mode is the numerical value or score that occurs with the
greatest frequency
It tells us the most frequently occurring value on a scale item
Data can have more than one mode, and is then called
“bimodal”
Best used with nominal data; but can also be used with ordinal,
interval and ratio data
What is the mode in these two examples?
Example: 2, 2, 2, 4, 4, 4, 6, 8,10
Example: 12, 13, 14, 14, 14, 16, 18

http://www.mathgoodies.com/lessons/vol8/mode.html
160
Median
The median is the score in the exact center of the ungrouped
frequency distribution---the 50th percentile
If the number of scores is uneven then exactly 50% of the
scores are above the median and 50% of the scores are below
the median
If the total number of scores is an even number, i.e. 10, the
median is the average of the two middle scores
For example, what it the median of these scores?
1, 3, 2, 5, 4, 6, 4, 2, 1, 5
Can be used with ordinal data; also interval and ratio data
http://www.mathsisfun.com/median.html
161
Mean
The Mean is the most commonly used measure of central
tendency. It is used for many statistical analyses. (comparing
the group means)
The mean is the sum of the scores divided by the number of

scores being summed.
The mean is the appropriate measure of central tendency for
interval and ratio data. Cannot be used with nominal and ordinal
data.
What is the mean for the following scores?
22, 28, 34, 16, 41, 9
http://www.algebralab.org/lessons/lesson.aspx?file=Algebra_Sta
tMeanMedianMode.xml
162
Types of Descriptive Statistics
Frequency distributions
Ungrouped frequency distributions
Grouped frequency distributions
Percentage distributions
Measures of central tendency
Measures of dispersion
163
163

Example of an Ungrouped Frequency Distribution
164
Data are presented in raw, counted form
1: /
2: /////
3: ///
4: /
5: //
164
Example of a Grouped Frequency Distribution
Data are pre-grouped into categories
Ages 20 to 39: 14
Ages 40 to 59: 43
Ages 60 to 79: 26
Ages 80 to 100: 4
165
165

Example of Percentage Distribution
E.g., Costs of running a business:
Salaries: 41.7%
Maintenance: 8.3%
Equipment: 16.7%
Fixed costs: 8.3%
Supplies: 25%
166
166
167
Commonly Used Graphic Displays of Frequency Distribution
167
Measures of Dispersion

Measures of dispersion, or variability, are measures of
individual differences of the members of the sample.
It gives some indication of how scores in a sample are dispersed
around the mean.
It indicates how different the scores are, or the extent to which
individual scores deviate from one another.
If individual scores are similar, the sample is homogenous, and
vice versa….
168
Measures of Dispersion
Examples of Measures of Dispersion:
Range
Value obtained by subtracting the lowest score from the highest
score. Ex: 9 – 1 = 8
Variance – larger the variance the greater the dispersion of
scores
Standard deviation
The square root of the variance
The average difference (deviation) of values
Standardized scores
A common standardized score is the Z-score and it expresses the
deviation from the mean
Scatter-plots
169

Scatterplots
Have two scales: horizontal axis (X) and vertical axis (Y)
Illustrate a relationship between two variables
170
170
Structure of a Plot
171
Example of a Scatterplot
172

172
Nonparametric Statistical Tests
Chi-squared test
Used with nominal data
Tests for differences among frequencies of groups
Mann-Whitney U-test
Median test
Kruskal-Wallis test
Spearman’s rank order correlation
173
Parametric Tests
t-Test
The most common analyses for significant differences between
two samples is the t-Test
Among the most frequently used t tests are:
A test of whether the mean of a normally distributed population
has a value specified in a null hypothesis.
A test of the
null hypothesis that the
means of two
normally distributed populations are equal

Used to test for causality – by testing for significant differences
between groups (to determine the effects of interventions)
174
Parametric Tests
Analysis of Variance (ANOVA)
Tests for differences between means of groups
Also, can be used for two or more groups
Used to examine multiple outcome variables
Results are given as a F score
175
Analysis of Relationships

Correlational Designs
Investigate relationships among variables
Measure strength of relationship (-1 to +1)
Measure direction of relationship (positive or negative)
Relationship Analysis
Measured by correlation coefficients such as
Pearson Product-Moment Correlation (r)
Used when variables are interval or ratio
Relationship Analysis
r = 0.60
r = -0.8
r = 0.0

Differences between
Variables
(nominal and ordinal data)
Chi Squared (x2)
Used for nominal or ordinal data
Variables are described as percentages instead of means
Chi Squared (x2)
To determine how closely observed
frequencies or probabilities match

expected frequencies or probabilities
Expected frequencies = the number of cases
that would be found in each cell of a
contingency table if the H0 were true
Chi Squared (x2)
(actual data)
Complication Incidence72 hours96 hoursTotalHad
complications9
(18.0%)11
(22.0%)20
(20.0%)No Complications41
(82.0%)39
(78.0%)80
(80.0%)Total5050100
Chi Squared (x2)
(expected frequencies)
Complication Incidence72 hours96 hoursTotalHad
complications10
(20.0%)10
(20.0%)20
(20.0%)No Complications40

(80.0%)40
(80.0%)80
(80.0%)Total50
(100%)50
(100%)100
(100%)
Example of Chi Square study
Researchers examined the relationship between the background
characteristics of homeless men and whether or not they were
positive for hepatitis C virus (HCV) infection. They found that,
for example, a significantly higher proportion of men who were
veterans (p<.01), who were white or Latino (p<.001), and who
had been in prison (p<.001) were HCV positive than men not in
these categories.
Differences between
Groups
(nominal and ordinal data)

Mann Whitney U
to test for differences between
groups when the variables are
ordinal data
Mann Whitney U
Example:
A researcher wants to measure differences in happiness of
nursing students at the beginning of their first semester and at
the end of their last semester.
Please highlight the correct answers
1. Your data results are 2, 14, 6, 8, 10, 4, 12, 8.

a) What is the mean?
b) What is the median?
c) What is the mode?
2. A researcher asks hospitalized patients about their comfort in
a new type of gown. This is an example of what type of data? a)
ratio b) independent c) quantitative d) qualitative.
3. If a researcher is examining how exposure to cigarette ads
affects smoking behavior, cigarette ads are what type of
variable? a) qualitative b) quantitative c) dependent
d)independent.
4. A research nurse is coding according to size. BMI is coded
by 1: below average 2: average 3: above average. What level of
measurement is this? a) nominal b) ratio c)ordinal d)interval.
5. A study is completed to examine the relationship between
gender and sports participation. It was conducted randomly
surveying ninth graders.
a) What level of measure is gender?
b) Write a null hypothesis for this study.
c) If the p value is < 0.005, do you accept or reject the null
hypothesis?
Case Study I
Dr. Intellectual conducted a study to measure if a telephone
intervention by nurses (nurses calling patients after discharge)
reduces readmissions within 30 days of discharge. All
discharged patients were called within 48 hours of discharge,
between June 1 and August 1, to discuss compliance with
discharge instructions.
1. What type of research is this?
a. qualitative
b. quantitative
2. Which type of design is this?
a. descriptive

b. correlational
c. quasi-experimental
d. experimental
e. phenomenological
f. ethnography
g. historical
h. grounded theory
a. cross-sectional
b. longitudinal
c. retrospective
4. What is the target population?
a. all patients at this hospital
b. all discharged patients at this hospital
c. all discharged patients discharged from this hospital
between June 1 and August 1
d. all discharged patients at all hospitals
5. Identify the independent variable
a. telephone calls
b. readmissions
c. 48 hours post discharge
d. compliance with discharge instructions
6. What level of measurement is the independent variable?
a. nominal
b. ordinal
c. interval
d. ratio
7. Identify the dependent variable.
a. telephone calls
b. readmissions

c. 48 hours post discharge
d. compliance with discharge instructions
8. What level of measurement is the dependent variable?
a. nominal
b. ordinal
c. interval
d. ratio
Patients were asked 10 questions: if they knew their discharge
instructions, if they had filled their medication prescriptions, if
they had started taking the medications as ordered, if they were
following orders regarding activity levels, and if they were
eating as instructed. The data collectors talked at length about
each of these issues with each patient.
9. If the patient had filled their medication prescriptions, the
data collector indicated a “yes.”
What level of measurement is this?
a. nominal
b. ordinal
c. interval
d. ratio
10. If the patient was taking all of their medications as ordered,
the data collector gave the patient a “3.” If the patient was
taking most of the medications ordered, the data collector gave
the patient a “2.” If the patient was taking few of the
medications ordered, the patient was rated as “1.” What level of
measurement is this?
a. nominal
b. ordinal
c. interval
d. ratio

11. The patients had a right to refuse to answer the callers’
questions. This is an example of which ethical principle?
a. the principle of respect
b. the principle of beneficence
c. the principle of justice
12. Patients were told that they could decide not to answer
questions, even if they had already answered some of them. This
is an example of which ethical principle?
a. the principle of respect
b. the principle of beneficence
c. the principle of justice
13. Data collectors protected the identity of the patients by
giving each one a code and keeping personal information in a
separate file. This is an example of:
a. anonymity
b. confidentiality
14. Which method of data analysis did Dr. Intellectual use to
analysis the data (as described in Question 10)?
a. frequency distribution
b. Pearson’s
r
c. chi square
d.
t test
15. Dr. Intellectual later decided to compare the responses of
the patients by grouping them by the unit they had been
discharged from. He wanted to know, for example, if the
patients who were discharged from unit 3 South were more
compliant and readmitted fewer times than the patients who
were discharge from unit 4 North. What type of study is Dr.
Intellectual conducting now?

a. descriptive
b. correlational
d. experimental
e. phenomenological
f. ethnography
g. historical
h. grounded theory
16. What statistical analyses will Dr. Intellectual use to analyze
data regarding number of patients readmitted?
a. frequency distribution
b. Pearson’s
r
c. chi square
d.
t test
Case Study 2
17. Nurse Feelgood conducted a study to discover the lived
experience of parents whose unborn children undergo surgery
while in utero. She wanted to obtain in-depth descriptions of
their experiences. Which design did she use?
a. descriptive
b. correlational
d. experimental
e. phenomenological
f. ethnography
g. historical
h. grounded theory
18. She obtained people to participate in the study by asking

patients admitted to the hospital for the surgery. She was able to
find 12 patients over a three-month period. What method of
sample selection did she use?
a. purposive
b. snowball
c. convenience
d. quota
19. What were the members of her sample called?
a. subjects
b. participants
c. target population
d. cohort
20. How did she collect data?
a. survey
b. interview
c. chart review
d. all of the above
21. How did she reduce the likelihood of introducing bias into
the study?
a. power analysis
b. random sampling
c. bracketing
d. control of extraneous variables
22. Was a sample of 12 large enough to find significant
differences?
a. Yes. Sample sizes are small in these types of studies.
b. No. The power of this study would be too low to find
significance.
c. This type of study does not look for significant
differences.
23. What method did she use to analyze the data?

a. coding
b.
t tests
c. chi square
d. Mann Whitney U
24. Are her findings generalizable to the larger population?
a. Yes, if she used rigor in her methods.
b. No, the sample size is too small.
c. Findings are not generalizable in this type of research.
Case Study 3
Nurse Noseinabook wants to find out if the hospital policy at
Mercy General Hospital regarding frequency of Foley catheter
tubing changes is based on evidence. The policy currently states
that Foley catheter tubing should be changed once a month at
the same time as the replacement of the Foley itself. The policy
was created in 1995 and updated in 2005. Only one reference
was indicated as a source of evidence supporting the data:
guidelines from the Urologists Association of America (UAA)
dated 2002.
25. Nurse Noseinabook searches for the 2002 guidelines and
discovers them at the UAA website. They were written in 2002
and were based on 2 correlational studies, 1 descriptive study,
and expert opinion. Is this evidence strong enough to base
nursing practice or hospital policy on?
a. Yes, as long as the power of each study was above 0.80.
b. Yes, although it would have been stronger to have a
clinical trial included.
c. No. These studies do not provide evidence that is strong
enough.

26. Nurse Noseinabook decides to find more recent studies on
this topic. Which source would be the most credible for her
search?
a. Science reviews in
Newsweek magazine
b. a column about causes of urinary tract infections in the
Wall Street Journal
c. a meta-analysis of the causes of urinary tract infections
d. data from a secondary source
27. If Nurse Noseinabook had decided to look for credible
sources written by nurses only, which one of the following
would be most appropriate?
a. Pubmed
b. Cochran Collaboration
c. Ebsco/Cinahl
d. American Academy of Pediatrics
28. Nurse Noseinabook finds a more recent guideline written by
the Internal Medicine Association (IMA). Much of the
recommendations they made are in agreement with the Mercy
General Hospital policy, but the IMA’s are more complete.
What should Nurse Noseinabook recommend?
a. Keep the original policy and add a few additions to it.
b. Update the policy and use the new source as evidence.
c. Make no changes.
Case Study 4
A researcher conducted an experimental study where one group
of patients was given a new drug for hypertension and another
group was given a commonly used diuretic. The blood pressures
of both groups were measured at the same times each day for a
week.

29. What was the researcher’s
intervention in this study?
a. the timing of blood pressure measurements
b. the type of drug given
c. having 2 groups of subjects
d. all of the above
30. To assign patients to a study group, a number was pulled
from a hat by the nurse admitting the patient. An odd number
meant that the patient was assigned to the group that received
the new drug; an even number assigned the patient to the group
that received the commonly used diuretic. This method of
sample selection is:
a. simple random selection
b. stratified random selection
c. cluster sampling
d. systematic sampling
a. descriptive
b. correlational
d. experimental
e. phenomenological
f. ethnography
g. historical
h. grounded theory
a. cross-sectional
b. longitudinal
c. retrospective
33. Identify the independent variable

a. blood pressure
b. type of drug
c. timing of blood pressure
34. What level of measurement is the independent variable?
a. nominal
b. ordinal
c. interval
d. ratio
35. Identify the dependent variable.
a. blood pressure
b. type of drug
c. timing of blood pressure
36. What level of measurement is the dependent variable?
a. nominal
b. ordinal
c. interval
d. ratio
37. What method of analysis did this researcher use?
a.
t test
b. chi square
c. Man Whitney U
d. ANOVA
38. The groups were found to be different with a
p value of 0.03. If the level of significance had been set
at 0.05, was the difference statistically different?

a. yes
b. no
39. The power of the study was found to be 0.85. Was the
sample size large enough?
a. yes
b. no
40. If the researcher accepted the research hypothesis and
rejected the null, what Type of error could the researcher be
making?
a. Type 1
b. Type 2
41. What could the researcher have done to prevent making a
Type I error? (answer all that apply)
a. Make the level of significance 0.01
b. Make the level of significance 0.10
c. Increase the sample size
d. Increase the power
42. What could the researcher have done to prevent making a
Type 2 error? (answer all that apply)
a. Make the level of significance 0.01
b. Make the level of significance 0.10
c. Increase the sample size
d. Increase the power
43. The researcher did not tell the subjects that they had a right
to refuse to participate in the study. Which right was violated?
a. self-determination
b. protection from harm
c. fair treatment
d. no human right was violated

44. Who is legally responsible for enforcing the rights of human
subjects in this study?
a. the researcher and the hospital’s IRB
b. the medical director and the hospital’s IRB
c. the IRB and the hospital administrator
d. all of the above
45. If the dependent variable of this study had had a smaller
effect size, what would have been indicated?
a. a larger sample size
b. a smaller sample size
Case Study 5
Two classes take the same research final examination. The mean
of one class is 80(8) and the mean of the other is 85(13).
46. What is true about these scores?
a. The highest grades between the 2 groups were most
likely in the class with a mean of
85.
b. The lowest score of either class is 75.
c. All students in the class with the higher average did
better on the exam.
d. The class with the mean of 80 had more A’s.
47. What type of measure is the final examination?
a. direct
b. indirect
48. The instructor wants to know if the mean scores from the
two classes are statistically different and set a level of
significance of 0.05 (p = 0.05) to compare them. Findings
indicated a p value of 0.10. How would you interpret this
finding?
a. There was less difference that the researcher was

looking for.
b. There was a lower degree of sameness among the
subjects than the researcher was looking for.
c. This level of significance indicated that the two classes
were different.
49. The test had 150 questions on it. What is true about sample
sizes when there are more variables being tested?
a. The more variables a study has the fewer the subjects
needed.
b. The more variables a study has the more subjects that
are needed.
50. What level of measurement is the dependent variable of this
study?
a. nominal
b. ordinal
c. interval
d. ratio
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