Research Methods in Psychology: Case Study to Meta-Analysis
This paper surveys five foundational research methods used in psychological investigation: case studies, traditional literature reviews, meta-analysis, questionnaire design, and experimental design. Using concrete examples—including a case study on anger behavior in elderly hospital patients, Staunton's 2003 meta-analysis of adventure therapy outcomes, and a controlled experiment testing the effects of a learning drug—the paper explains how each method works, identifies its strengths and limitations, and discusses strategies for improving validity and reducing bias. The paper provides an accessible overview suitable for students learning to evaluate and apply diverse research methodologies.
- Introduction to Case Study Methods: How case studies examine small groups in depth
- Literature Reviews and Their Limitations: Subjectivity problems in traditional literature reviews
- Meta-Analysis as a Research Tool: Statistical integration of multiple study findings
- Questionnaire Design: Common Flaws and Solutions: Avoiding bias and ambiguity in survey items
- Experimental Design: Testing a Learning Drug: Step-by-step controlled experiment on drug and learning
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What makes this paper effective
- Each research method is introduced conceptually and then immediately illustrated with a concrete, specific example, making abstract methodology tangible for the reader.
- The paper clearly identifies the limitations of each method alongside its strengths, demonstrating balanced critical thinking rather than advocacy for any single approach.
- The experimental design section walks through every procedural step in logical sequence, modeling how a well-structured methods section should be written.
Key academic technique demonstrated
The paper demonstrates method-then-critique structuring: each section first explains what a research method is and how it works, then identifies its weaknesses, and finally proposes remedies or best practices. This pattern—explanation, critique, solution—is a hallmark of strong methodology writing and shows the author's ability to move beyond description toward evaluative analysis.
Structure breakdown
The paper is organized into five discrete, parallel sections, each devoted to one research method. The sections move from qualitative approaches (case study, literature review) to quantitative ones (meta-analysis, questionnaire, experiment), creating a natural progression in scope and rigor. Each section is self-contained, making the paper useful as a reference survey of core research methods. The concluding experimental design section is the most detailed, functioning almost as a standalone methods proposal.
Introduction to Case Study Methods
Case studies, a method used by psychologists to study behavior, are unique in that they examine small groups of individuals rather than large samples. Through in-depth, longitudinal examination of a single instance or event, this method can lead to a deep understanding of why a certain event occurred. Further, the researcher can identify issues that may require more extensive examination in future, larger studies (Miles et al., 1984).
For example, a researcher could use case study examinations to determine possible reasons for increased anger behavior in elderly women recently admitted to hospitals. The process would begin with careful selection of a small group of individuals who fit the above criteria. Generally, these small groups would include ten or fewer subjects (Miles et al., 1984).
The researcher would then fully review the patients' histories. This would include conversations with hospital staff, interviews with family members, written histories from previous physicians or mental health representatives, and interviews with the patients themselves. Additionally, the researcher would examine all previous medication schedules, dietary plans, living conditions, and health conditions.
Following this in-depth analysis of all applicable data, the researcher would then attempt to find similarities between cases that could represent reasons for increased anger behaviors. If, for example, the research found that the medication needs of many patients were not followed by hospital staff, this might suggest a possible correlation between medication changes and anger behavior. Conversely, if the researcher noted changes in dietary behavior that altered the patients' routine, he or she might infer that these changes correlate with the behavioral changes observed. By examining a small group of subjects in depth, the researcher will have a better understanding of the full range of possible factors relating to these behavioral changes.
Literature Reviews and Their Limitations
Traditionally, researchers have used a literature review to discuss the findings of other studies on the topic they are investigating. These literature reviews begin with the gathering of all available studies pertaining to the topic. Once all viable information has been gathered, the researcher chooses which studies to include in their own work. These studies are then reviewed, summarized in narrative style, and discussed in terms of their key points as they relate to the topic at hand (Light et al., 1984).
The problem, however, is that these reviews are very subjective in nature. While the strengths and weaknesses of some previous research on the topic are clearly identified, this identification is limited to the perspective of the researcher writing the review. Further, since not all research on a topic can be included in a given literature review, the writer must also rely on their own subjectivity when choosing which studies to include. Without clear and precise procedures for minimizing this subjectivity, the literature review can lose merit (Light et al., 1984).
Meta-Analysis as a Research Tool
The meta-analysis, by contrast, provides a method of using "statistical analysis of a large collection of results from individual studies for the purpose of integrating the findings" (Glass, 1976, p. 5). Since the results from various studies investigate different dependent variables and measure on different scales, the meta-analysis compares the results of each study using a standard measure of effect size. This can be done with any study that reports findings using correlation coefficients. Since standard literature reviews do not account for sample-related issues, the meta-analysis often measures how much difference exists in any given study between the trial group and the control group. This analysis is performed on each study included in the review, allowing researchers to effectively use only those studies that truly show a correlation (Glass, 1976).
A prime example of an effective meta-analysis is the 2003 study by Norman Staunton, "A Meta-Analysis of Adventure Therapy Outcomes." The goal of this analysis was to determine whether adventure therapy was effective, and if so, which types of adventure therapy were most effective. Staunton searched electronic databases, bibliographies, and adventure therapy websites, and also used general research, listserv requests, and existing data. Only empirically based studies that used descriptive statistics were included. Additionally, only studies examining adventure therapy with diagnosed populations were considered. Using these criteria, the selection was limited to 17 studies (Staunton, 2003).
Staunton then calculated the effect sizes for each study and correlated them based on the relationship between effect size and primary and secondary variables. He used regression analysis to ensure all returned significant correlates. Additionally, the study used the file drawer effect to estimate the number of non-significant effects that would be needed to negate the findings (Staunton, 2003).
The final meta-analysis included 17 studies and calculations of 95 effect sizes, with no identification of negative effects. Significant effects were found with dissertations, medium- and high-quality studies, ABC programs, continuous programs, intermittent programs, residential programs, single-sex and co-ed groups, adolescent and adult groups, and self-construct groups. Only outpatient programs were found to have non-significant effect sizes. The highest significance was found with ABC programs and mixed-diagnosis programs (Staunton, 2003). Staunton thus concluded, using meta-analysis, that the above adventure therapy programs were effective.
References
Glass, G. V. (1976). Primary, secondary and meta-analysis of research. Educational Researcher, 5(10), 3–8.
Light, R. J., & Pillemer, D. B. (1984). Summing up: The science of review in research. Harvard University Press.
Miles, M., & Huberman, A. M. (1984). Qualitative data analysis: A sourcebook of new methods. Sage.
Staunton, N. (2003). Thesis defense: A meta-analysis of adventure therapy program outcomes. Retrieved July 14, 2005, from Wilderdom.
Urdang, L., Ryle, A., & Lee, T. (1991). Dictionary of uncommon words. Wynwood Press.
Whitney, D. R. (1972, April). The questionnaire as a data source (Technical Bulletin No. 13). Prepared for the American Educational Research Association training session on Data Collection in Educational Research and Evaluation.
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