Research study

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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?

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Sample Research Question

What are the relationships among spiritual well-being, sleep quality, and health status in HIV-infected men and women?

13

Conducting Research: Formulating the research question

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?

Conducting Research: Formulating the research question

Research Question:

Do nursing students who participate in study groups earn higher grades on final exams?

What is the target audience?

What is the independent variable?

What is the dependent variable?

Conducting Research: Formulating the research question

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?

What is the target audience?

What is the independent variable?

What is the dependent variable?

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?

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Identify the Variables

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

Identify the Variables

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

Identify the Variables

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

Identify the Variables

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

Identify the Variables

Does a telephone therapy intervention for patients with prostate cancer cause improvements in their psychological distress and coping skills?

24

Identify the Variables

What are the effects of animal-assisted therapy on the nutritional intake of individuals with Alzheimer disease?

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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.

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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

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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.

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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.

Conducting Research: Determine theoretical framework

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

Conducting Research: Determine theoretical framework

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.”

Conducting Research: Design the study: Qualitative 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

Conducting Research: Design the study: Qualitative 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?)

Conducting Research: Design the study: Qualitative 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.

More important terms:

Manipulation

Controlling a treatment or intervention

For example:

The researcher controlled the length of time

between administration of pain medication.

More important terms:

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.

More important terms:

Causality

when an independent variable causes

an effect in a dependent variable

For example:

Smoking causes cancer.

More important terms:

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 Numbers

061501 896939 173249 851495 080678
088722 507157 949463 056582 050831
240067 095888 119144 975852 075242
007007 884184 103728 791761 009531
541119 594649 519266 374786 227599
706416 424993 000243 315604 741784
210478 436022 815218 528465 008957
643146 983722 610063 602459 763468
456307 417707 680497 420151 542222
940208 478597 053814 634305 351413
365415 270855 142284 335173 922755

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.

Which type of sampling is this?

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.

Which type of sampling is this?

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.

Which type of sampling is this?

In order to select a sample of ResU nursing students, a researcher put each student’s name in a hat and drew names.

Which type of sampling is this?

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

Which type of sampling is this?

In order to select a sample of nursing students at WSCN, a researcher visited a class and asked for volunteers.

Which type of sampling is this?

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

Protection of Human Subjects

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

Protection of Human Subjects

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.

Protection of Human Subjects

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.

Protection of Human Subjects

Anonymity

Confidentiality

Protection of Human Subjects

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

Protection of Human Subjects

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

Protection of Human Subjects

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

Protection of Human Subjects

Respect for Persons

Children provide assent,

their parents provide permission.

Protection of Human Subjects

Beneficence

Do No Harm!

Maximize possible benefits,

minimize possible harm.

Protection of Human Subjects

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.

Protection of Human Subjects

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

Protection of Human Subjects

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

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Level of Significance and Probability

Level of Significance

How does a researcher decide how much of a difference is a significant difference?

Level of Significance

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%?

Level of Significance

Researchers have to decide the “passing scores” for their studies.

They use probabilities (p) to do so.

Level of Significance

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

Level of Significance

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?

Level of Significance

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

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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

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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

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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_StatMeanMedianMode.xml

162

Types of Descriptive Statistics

Frequency distributions

Ungrouped frequency distributions

Grouped frequency distributions

Percentage distributions

Measures of central tendency

Measures of dispersion

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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

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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

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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

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Scatterplots

Have two scales: horizontal axis (X) and vertical axis (Y)

Illustrate a relationship between two variables

170

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Structure of a Plot

171

Example of a Scatterplot

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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

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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)

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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

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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 Incidence 72 hours 96 hours Total
Had complications 9
(18.0%)
11
(22.0%)
20
(20.0%)
No Complications 41
(82.0%)
39
(78.0%)
80
(80.0%)
Total 50 50 100

Chi Squared (x2)
(expected frequencies)

Complication Incidence 72 hours 96 hours Total
Had complications 10
(20.0%)
10
(20.0%)
20
(20.0%)
No Complications 40
(80.0%)
40
(80.0%)
80
(80.0%)
Total 50
(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

3. Which type of design is this?

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

c. quasi-experimental

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

c. quasi-experimental

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

31. Which type of design is this?

a. descriptive

b. correlational

c. quasi-experimental

d. experimental

e. phenomenological

f. ethnography

g. historical

h. grounded theory

32. Which type of design is this?

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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