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Schmidt & Brown (2021). Evidence-Based Practice for Nurses:
Chapter 7: Key Concepts and Principles of Quantitative Designs
Chapter 8: Quantitative Designs: Using Numbers to Provide Evidence
Objectives
Objectives
Explain the three essential components of experimental designs
List elements to be considered when appraising quantitative designs
Categorize study designs based on the time dimension of data collection across retrospective, cross-sectional, repeated measures, and longitudinal or prospective designs.
Categorize types of study designs based on their purpose
Identify major experimental designs
Discuss the advantages and disadvantages of various experimental designs
Discuss the key difference between quasi-experimental and experimental designs
Identify major quasi-experimental designs
Discuss the advantages and disadvantages of various quasi-experimental designs
Describe the purpose of nonexperimental designs
Identify major nonexperimental quantitative designs
Discuss the advantages and disadvantages of various nonexperimental designs
Explain how the study purpose, literature review, research questions or hypotheses, and the overall study design are interrelated
Categorizing Designs According to Time
Categorizing Designs According to Time
1. Retrospective Design
= Research designs when researchers look back in time to determine possible causative factors; ex post facto ("after the fact")
Start with the DV and look back in time to determine possible causative factors
The IV cannot be manipulated and the participants cannot be randomly assigned
Retrospective designs are never experimental in nature
Case-Control Study
= A type of retrospective study in which researchers begin with a group of people who have already been diagnosed with the disease ("cases") and compare them with those who do not have the condition
2. Cross-sectional Design
= Nonexperimental design used to gather data from a group of participants at only one point in time; study design to measure cause and outcome variables as each exits in a population or representative sample at one specific point of time
Provide a snapshot by collecting data about both the IV and DV at the same time
Difficult to establish cause and effect
Cohort Comparison Design
= Nonexperimental cross-sectional design in which more than one group is studied at the same time so that conclusions about a variable over time can be drawn without spending as much time
Advantage
Easier to manage
More economical
Threats of mortality, maturation, and testing are minimized because data are collected only one time from each subject
Disadvantage
Difficult for researchers to make claims about cause and effect
3. Longitudinal Design
= Designs used to gather data about participants at more than one point in time
Prospective designs
Studies over time with presumed causes that follow participants to determine whether the hypothesized effects actually occur
Repeated measures designs
= Research designs where researchers measure subjects more than once over a short period of time
Advantage
Provides baseline data so that before and after comparisons can be made on the same subject
Subjects are likely to remain in the study because the time period is short
Panel design
= Longitudinal design where the same participants, drawn from the general population, provide data at multiple points in time over a long period of time and at specified intervals
Trend
= A type of longitudinal design to gather data from different samples across time
Follow-up study
= A longitudinal design used to follow participants, selected for a specific characteristic or condition, into the future
Cohort studies
Can be nonexperimental or experimental follow-up studies
Crossover designs
= Experimental designs that use two or more treatments; participants receive treatments in random order
Advantage
Provide important information about the chronological relationships that exist between the IV and DV by determining changes over time
Can be used to test cause and effect
Disadvantage
Cost in following participants over an extended period of time
Categorizing Designs by Purposes
Categorizing Designs by Purposes
Quantitative designs can be used for 4 key purposes
(1) Examining causality
(2) Predicting relationships and/or differences among variables
(3) Explaining relationships and/or differences among variables
(4) Describing a phenomenon in detail
4 main types of designs
Experimental (to determine causality)
(1) True-Experimental
(2) Quasi-experimental
Nonexperimental (to describe, examine, predict)
(3) Correlational
(4) Descriptive
Experimental vs. Nonexperimental
Experimental
Manipulate the independent variable (IV)
IV = the intervention, or "treatment", that the researcher wants to test in a specific group of people in order to determine the effect that the IV has on the outcome of interest, known as the dependent variable (DV)
5 requirements of a true experimental design
(I) A hypothesis that tests a causal relationship (i.e., testing for the effect that an IV has on a DV)
(II) A treatment group that receives the intervention and a control group that does not get the intervention being tested
(III) Random assignment of participants to treatment/control groups to reduce bias and confounding
(IV) Manipulation of the intervention (IV)
(V) Tight control of the experiment to minimize the influence of confounding variables
Quasi-experimental designs
Involve manipulation of the IV
Lacks either randomization or a control group
Nonexperimental
Lacks manipulation of the IV
Also called observational designs
The researcher "observes" how the variables of interest occur naturally, without the researcher trying to change how the conditions normally exist
Experimental Designs
Experimental Designs
= Designs involving random assignment to groups and manipulation of the independent variable
3 Essential Components of Experimental Designs
1. Randomization
Randomization in experimental designs is used in two ways
(1) Researchers randomly select participants from the target population
(2) Randomly assign participants to groups
2. Control
Related to randomization
Ways to control for extraneous variables
Control group
for comparison to the experimental group
Exert the highest level of control over the selection of participants, the definitions of the variables, and the environment in which the experiment is conducted
3. Manipulation
Manipulate the independent variable for a design to be considered experimental
= Administer the intervention
True Experimental Designs
True Experimental Designs
True Experimental Designs
Randomized Controlled Trials (RCTs)
= Clinical experimental studies that typically involve large samples and are sometimes conducted at multiple sites
6 characteristics of RCTs
(1) They involve a large number of participants, often from diverse geographic areas
(2) There are strict guidelines for including participants in a study
(3) Participants are randomly assigned to either the intervention or control group
(4) Participants in each group must be comparable (equivalent) on either the intervention or control group
(5) The intervention is consistently implemented to all participants in the experimental group following a very rigid defined protocol for implementation
(6) All participants in both groups are measured on the dependent variable using the same method of measurement at the same points in time
6 types of true experimental designs
(1) Two-group pretest-post-test
= Participants are randomly assigned to the experimental or control group and are measured before and after the intervention; classic or true experiment
Allows researchers to examine within-subjects results as well as between-subjects results
Potential disadvantage
threats to internal validity
introduced from repeated testing
mortality
Participants are measured more than once and some participants may drop out before the study is completed
(2) Two-group posttest-only
= Experimental designs where participants are randomly assigned to an experimental or control group and measured after the intervention
Used when it is not possible or practical to measure the dependent variable before the intervention is implemented
Advantage
Because participants are measured once, the followings are minimized:
Threats of testing
Mortality
Disadvantage
Threats of selection bias
One cannot assume that the two groups are equivalent because there was no measurement at baseline
(3) Solomon four-group
= An experimental design involving four groups - some receive the intervention, others serve as controls; some are measured before and after the intervention, others are measured only after the intervention
Advantage
Better than the two-group pretest-posttest design to reduce the threat of testing
Better than the two-group posttest-only design to minimize selection bias
Disadvantage
Sample sizes must be large because there are more groups, meaning
Participants must be available
Recruitment of participants will take longer
Costs will be increase
(4) Multiple experimental groups
= Experimental designs using two or more experimental groups with one control group
Advantage
Allows researchers to compare the effects of different interventions on the dependent variable
Disadvantage
A large number of participants is needed to detect differences across multiple groups
(5) Factorial
= Experimental designs allowing researchers to manipulate more than one intervention
Advantage
Time and effort are saved by not having to conduct multiple studies
Disadvantage
Sample size for a minimum of four groups
(6) Crossover designs
= Experimental designs that use two or more treatments; participants receive treatments in a random order
A type of longitudinal design
Advantage
Smaller sample sizes because only one group of participants is required, and participants serve as their own controls
Disadvantage
Participants may continue to engage in the first intervention after moving to the second
Quasi-Experimental Designs
Quasi-Experimental Designs
= Research designs involving the manipulation of the independent variable but lacking random assignment to experimental and comparison groups
4 types of quasi-experimental designs
1. Nonequivalent control group pretest-posttest
= A quasi-experimental design where participants are not randomly assigned to treatment or comparison groups, but are measured before and after an intervention
2. One-group pretest-posttest
= A quasi-experimental design where only one group is measured before and after an intervention
3. One-group time series
= A quasi-experimental design where one group is measured prior to administering the intervention and then multiple times after the intervention
4. Preexperimental designs
= A posttest-only design that involves manipulation of the independent variable but lacks control for extraneous variables
Nonexperimental Designs
Nonexperimental Designs
= Research designs that lack manipulation of the independent variable and random assignment
3 main purposes
(1) describe a phenomenon in detail
(2) explain relationships and differences among variables
(3) predict relationships and differences among variables
2 general categories of nonexperimental designs
- (1) Correlational designs
= Nonexperimental designs used to study relationships between two or more variables
Covary
= When change in one variable is associated with change in another variable
3 types of correlational designs
(I) Descriptive correlational
= Correlational design type used to explain the relationships among the variables or groups using a nondirectional hypothesis
(II) Predictive correlational
= Correlational design where researchers hypothesize which variables are predictors or outcomes
Causality cannot be assumed
2 main aims
(i) Attempt to determine the amount of variance in an outcome variable that can be explained by multiple predictor variables
(ii) Attempt to know how accurately a group of predictor variables can determine group membership
(III) Model testing
= Correlational design to test a hypothesized theoretical model; causal modeling or path analysis
Can only provide a suggestion of causality, not true evidence of causality
- (2) Descriptive designs
= Designs that provide a picture of a situation as it is naturally happening without manipulation of any of the variables
Purposes
To assess current practice
To be used in the early stages of theory development
Conceptual and operational definitions of the variables and possible theoretical relationships among the variables can emerge from descriptive studies
Variations in names
Exploratory designs
Nonexperimental design type used when little is known about a phenomenon
Comparative designs
Descriptive design type that compares two or more groups or variables
Survey designs
Descriptive design type involving data obtained through participants' self-reports
Advantage
Flexibility in the methods that can be used to collect data, often leading to more rapid collection of data and cost savings
Disadvantage
Inability to establish causality
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