one-shot case study | Definition

A one-shot case study is a research design that observes the outcome of a single group after an intervention, without a pretest or control group.

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Introduction to the One-Shot Case Study Design

The one-shot case study design is a simple, exploratory research design used to evaluate the effect of an intervention or treatment on a single group, observing the outcome only after the intervention has been implemented. It is often referred to as a “posttest-only” design because it involves measuring the dependent variable once, following the intervention. Researchers use this approach when there are limited resources or when the focus is on obtaining preliminary data quickly, as it requires only one measurement and no control group for comparison.

In social sciences, this design can provide useful initial insights but has significant limitations, especially regarding internal validity. It is particularly common in educational, behavioral, and medical studies where researchers aim to observe potential effects under real-world conditions.

Structure of the One-Shot Case Study Design

The one-shot case study design involves two primary components:

1. Intervention (X): The researcher administers a treatment, program, or intervention to a single group of participants. This intervention is intended to influence the dependent variable in some measurable way.
2. Posttest Observation (O): After the intervention, the researcher measures the dependent variable to observe any effects that may have resulted from the intervention.

The one-shot case study design is often symbolized as:

• X O

where:

• X represents the intervention, and
• O represents the observation or measurement after the intervention.

Because there is no pretest or control group, this design is only useful for documenting outcomes at a single point in time, without a baseline or comparison condition to confirm that any observed effects are due to the intervention.

Example of a One-Shot Case Study

Suppose a school administrator wants to evaluate the impact of a motivational workshop on students’ study habits. Using a one-shot case study design:

1. The administrator arranges the workshop (X) and all participating students attend.
2. After the workshop, the students complete a survey assessing their attitudes toward studying and self-reported study habits (O).

In this case, the survey results provide information on students’ study habits after the workshop. However, without a pretest or control group, it is unclear if any changes in study habits are attributable solely to the workshop.

Advantages of the One-Shot Case Study Design

Although the one-shot case study design has limited applications, it offers several advantages, particularly for exploratory and preliminary research.

1. Simplicity and Efficiency: The design requires only one group and one measurement, making it easy to administer and analyze. This simplicity is ideal for studies where time, resources, or participant availability are limited.
2. Cost-Effectiveness: Since there is no pretest or control group, the one-shot case study design is inexpensive to implement. It is a good choice for preliminary research or pilot studies where researchers seek quick, cost-effective data collection.
3. Real-World Applicability: The design allows researchers to observe the intervention’s effect in natural settings, which can offer insights into how an intervention might function under real-world conditions.
4. Exploratory Value: One-shot case studies can help identify potential trends or suggest new areas for further research. By observing the outcome post-intervention, researchers can gather initial data that could be useful in designing more robust future studies.

Limitations of the One-Shot Case Study Design

The one-shot case study is highly limited in its ability to establish causal relationships due to the absence of a control group and pretest. Several major limitations include:

1. Lack of Internal Validity: The design cannot control for other factors that may influence the outcome, meaning it is difficult to conclude that the observed results are due solely to the intervention. This raises questions about the reliability of the findings.
2. No Baseline Measurement: Without a pretest, there is no baseline against which to measure the intervention’s effect. This makes it challenging to determine if the intervention changed the outcome or if the observed result was pre-existing.
3. Susceptibility to Confounding Variables: In a one-shot case study, any external events or personal changes (e.g., maturation, environmental factors) that occur between the intervention and observation could affect the outcome. These confounding factors can mislead researchers about the intervention’s true impact.
4. Lack of a Control Group: Without a control group, the study cannot account for changes that might have occurred naturally over time or as a result of other influences. This absence prevents the researcher from ruling out alternative explanations for the observed results.
5. Difficulty in Making Causal Inferences: Since the design only observes outcomes after the intervention, it is impossible to establish a cause-and-effect relationship confidently. The design can suggest associations but not prove causation.

Threats to Validity in One-Shot Case Study Design

The lack of a pretest and control group in one-shot case studies opens them up to various threats to validity, making it difficult to draw strong conclusions from the findings.

1. History Effects

History effects refer to external events that occur between the intervention and observation, which may influence the outcome. For example, if a teacher implements a new teaching method and observes improved student behavior afterward, it is possible that an unrelated school event, like a recent motivational talk, also influenced the students’ behavior.

2. Maturation Effects

Maturation effects are internal changes within participants over time, such as natural development or changes in mood or behavior, which could influence the outcome. For instance, if students appear to study more after an intervention, it may simply reflect their natural adjustment to academic demands over time, rather than the intervention’s effect.

3. Testing Effects

In some cases, the method of measuring outcomes itself can affect results, known as testing effects. For example, if participants know they will be evaluated on their performance after an intervention, they may change their behavior in response to being observed, rather than as a genuine result of the intervention.

4. Instrumentation Effects

Instrumentation effects occur when there are inconsistencies in the way outcomes are measured, such as using different evaluative criteria or tools. For example, if a teacher assesses students’ engagement after implementing a new activity, any changes in how the teacher interprets “engagement” between sessions could affect the results.

Appropriate Applications of the One-Shot Case Study

Given its limitations, the one-shot case study design is best suited for specific scenarios, such as:

1. Pilot Studies: When researchers are testing an intervention or methodology in a preliminary way, this design can provide valuable exploratory data.
2. Initial Observational Studies: If the goal is to observe reactions or results in a real-world setting without strict experimental control, the one-shot case study can offer insights.
3. Program Evaluations: In some cases, evaluators use this design to assess an ongoing program’s impact when pretests or control groups are not feasible. However, they must acknowledge the design’s limitations in attributing outcomes solely to the program.
4. Feasibility Studies: Researchers may use this design to determine if a particular intervention is feasible or suitable for future study.

Example of the One-Shot Case Study in Action

Consider a public health researcher who wants to evaluate the impact of a nutrition workshop on participants’ knowledge of healthy eating. The researcher uses the one-shot case study design:

1. Intervention: Participants attend a one-hour workshop on nutrition.
2. Observation: Immediately after the workshop, participants complete a knowledge assessment on healthy eating.

This assessment provides data on participants’ nutrition knowledge post-workshop, but without a pretest or control group, the researcher cannot conclude whether the workshop alone led to their knowledge level or if participants had this knowledge beforehand.

Alternatives to the One-Shot Case Study Design

Because the one-shot case study design lacks a control group and pretest, researchers may consider alternatives that offer greater validity:

1. One-Group Pretest-Posttest Design: Adding a pretest measurement allows researchers to compare baseline and post-intervention results, providing some insight into changes caused by the intervention.
2. Two-Group Posttest-Only Design: By introducing a control group that does not receive the intervention, researchers can better isolate the intervention’s effect. Although still limited, this design improves the ability to make comparisons.
3. Randomized Controlled Trials (RCTs): RCTs involve both a pretest-posttest structure and random assignment, making them the gold standard for establishing causality.
4. Quasi-Experimental Designs: When randomization isn’t possible, quasi-experimental designs that incorporate a control or comparison group, such as the nonequivalent control group design, provide more reliable results than a one-shot case study.

Conclusion

The one-shot case study design is a simple and convenient tool for obtaining initial observations of an intervention’s effect. While it is useful for pilot studies and preliminary exploration, the design’s lack of a control group and pretest makes it highly vulnerable to validity threats, limiting its ability to provide strong causal evidence. Researchers must interpret findings with caution, recognizing that any observed effects cannot be conclusively attributed to the intervention alone. For studies that demand stronger validity, alternative research designs with additional controls are often more suitable.

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Last Modified: 10/30/2024