Chapter017

Copyright © 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins
Chapter 17
Generating Evidence Through
Quantitative Research

Getting Started: From Idea to Reality
• Make note of when questions arise from practice
− Develop a “creative ideas” file
• After developing an idea, conduct a thorough literature
review of relevant studies and systematic reviews
− This informs the process and prevents duplication
• Establish a team of clinicians and research experts
• Prepare a study draft and hold a research design meeting
− Discuss roles and logistics

Overview of Designing a Clinical
Quantitative Study
• Begin by ascertaining the existing state of knowledge
surrounding the clinical question
− Ask what needs to be known
− The answer to this question informs the choice of
design
• Correlational study vs. RCT
• Consider the significance of the problem or research
question
− Will it improve care or patient outcomes?

Overview of Designing a Clinical
Quantitative Study (cont’d)
• Consider
− Feasibility
− Setting
− Research team
− Ethics, benefits, and risks

Question
• Tell whether the following statement is true or false.
• The primary consideration when deciding if a clinical
question merits research is whether the question has
been addressed by earlier research.

Answer
• False
• When deciding whether research is merited, a researcher
should prioritize the question of whether the answer
would improve patient outcomes. The existing knowledge
base must be assessed, but the potential impact on
patients is central.

Specific Steps in Designing a
Quantitative Study
• Step 1: Formulate the study question
− Question should be FINER (feasible, interesting,
novel, ethical, relevant)
− May have to engage a research ethics board at this
early stage
• Step 2: Establish the significance of the problem
− Problem should be one that is clinically important or
that will extend the science in an area

• Step 3: Search and appraise evidence
− Begin searching for systematic reviews on the topic
− Identify and appraise individual studies
• Step 4: Determine a theoretical or conceptual framework
− This is a number of interrelated statements that
attempt to describe, explain, and/or predict a
phenomenon
• Step 5: Generate hypotheses when appropriate
− When there is a theory to guide the formulation of
these predictions or enough evidence from prior work

Question
• A research team has determined the theoretical
framework for their proposed quantitative study. A
theoretical framework is made up of:
a. Statements of belief that guide the understanding of a
phenomenon
b. Proposed relationships between the variables in a study
design
c. Explanations of the factors that have influenced the
choice of study design
d. Speculations about the clinical significance of a research
problem

Answer
• a. Statements of belief that guide the understanding of a
phenomenon
• Rationale: A theoretical or conceptual framework is made
up of a number of interrelated statements that attempt
to describe, explain, or predict a phenomenon. It is
broader than a hypothesis, a rationale for design, or a
statement of clinical significance.

Step 6: Select the Appropriate Research
Design
• The study protocol for testing the study hypotheses or
questions
• Non-experimental designs
− Descriptive studies
• Surveys
• Correlational Studies – descriptive and predictive
− Case-Control Studies
− Cohort Studies

Step 6: Select the Appropriate Research
Design (cont’d)
• Experimental designs – the strongest designs for testing
cause-and-effect relationships
− Randomized controlled trials (RCTs) require
• An experimental group that receives the treatment
or intervention
• A control or comparison group that receives
standard care or a comparison intervention that is
different from the experimental intervention
• Randomization or random assignment

Experimental Designs: Two-group RCT
With Pretest/Posttest Design and
Structurally Equivalent Comparison
Group

With Posttest Design Only

With Long-term Repeated Measures
Follow-up

With True Control Group That Receives
No Intervention

Experimental Designs: Three-group RCT

Experimental Designs: Solomon Four-
group Design

Question
• Tell whether the following statement is true or false.
• In experimental designs, the purpose of a posttest is to
identify similarities or differences between the control
and experimental groups after the intervention has taken
place.

Answer
• True
• Rationale: A posttest allows for comparison of groups in
terms of the study constructs after the application of an
intervention.

Quasi-experimental Designs
• These are designs in which the independent variable is
manipulated, but where there is a lack of random
assignment or a control group

Quasi-experimental Designs: Pretest and
Posttest Design With
Comparison/Control Group but Lacking
Random Assignment

Quasi-experimental Designs: Time Series
Design

Pre-experimental Design

Factors to Consider During Experiments
• Integrity and reproducibility
• Pilot study
• Manipulation checks
• Intervention processes
• Control strategies

Threats to Internal Validity
• Attrition
• Confounding variables/selection
• Nonadherence and failure to complete the intervention
protocol
• Measurement of change in outcome variables
• History
• Maturation
• Testing

Question
• Which of the following measures is most likely to prevent
attrition among study participants during an experiment?
a. Assign participants to groups based on predicted attrition
rates
b. Utilize multiple posttests
c. Account for the effects of history on participant testing
d. Ensure frequent communication with participants

Answer
• d. Ensure frequent communication with participants
• Rationale: Frequent communication between participants
and researchers may prevent attrition over the course of
a study. Multiple posttests do not address this problem
and assignment to groups should be random, not
deliberate. The potential effects of history should be
considered, but doing so does not necessarily minimize
attrition.

Step 7: Identify the Sample
• Consider the population in question, access to this
population, and the needed sample size (power analysis)
• Sampling strategies
− Random sampling
− Stratified sampling
− Cluster (area) random sampling
− Nonprobability or purposive samples
− Modal instance sampling
− Heterogeneity sampling
− Snowball sampling

Step 7: Identify the Sample (cont’d):
Measures to Enhance External Validity
• Determine the necessary sample size carefully
• Consider refusal to participate and study attrition
• Take measures to promote participation
− Frequent contact
− Ease of participation
− Making participation worthwhile

• Step 8: Determine measures
− Consider validity and reliability
− Level of data
• Step 9: Outline the data collection plan
• Step 10: Apply for human subjects approval
− Consider ethical principles
• Step 11: Implement the study

• Step 12: Prepare and analyze data
• Step 13: Interpret the results
• Step 14: Disseminate the findings
• Step 15: Incorporate findings into EBP and evaluate
outcomes

Chapter017

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Chapter017