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Chapter 10: Non-Experimental Design II: Observational and Archival Methods

Chapter Objectives

• Distinguish between naturalistic and participant observation methods.

• Articulate the problems that can occur in observational research and how researchers address those problems.

• Explain how thematic analysis can be a tool for evaluating qualitative data.

• Define archival research and explain why it is non-experimental.

Observational Research

Key Concepts

• Naturalistic Observation: Involves observing behaviors in natural settings with minimal intrusion on the environment.

• Participant Observation: The researcher becomes part of the group being observed, impacting the data collection process.

Problems with Observational Research

• Lack of control over variables can lead to challenges in drawing conclusions.

• Observer bias can occur, necessitating tools like behavior checklists and techniques for interobserver reliability.

• Reactivity from participants can affect behavior, suggesting the need for unobtrusive methods.

• Ethical considerations include consent and privacy.

Thematic Analysis

• A qualitative analysis method for identifying patterns within data.

• Steps in thematic analysis:

  1. Familiarize with Data: Understand the dataset thoroughly.

  2. Code Data: Mark key segments of data.

  3. Search for Themes: Identify broader themes within the codes.

  4. Review Themes: Refine themes based on relevance and prominence.

  5. Define and Name Themes: Summarize the essence of each theme captured.

  6. Write Report: Compile findings into a coherent narrative.

Archival Research

Characteristics

• Involves using data that was previously collected for other purposes.

• Content Analysis: Often utilized to analyze archival data, allowing researchers to derive insights from existing datasets without reactivity.

• Challenges include missing data and biases inherent to the original data collection methods.

Advantages and Limitations

• Advantages: Enables researchers to study phenomena with existing data, thus saving time and resources.

• Limitations: Potential biases and lack of control over how data was originally collected; data may not fit research needs directly.

Analyzing Observational and Archival Data

Data Analysis Techniques

• Factor Analysis: Helps identify clusters within datasets to form factors.

• Meta-Analysis: Evaluates effect sizes across studies addressing similar hypotheses, assessing the consistency and size of effects.

Examples of Methods

Naturalistic Observation Example

• Study in a science museum where parental engagement was observed. Findings indicated a gender difference in parental interaction, with parents explaining science concepts more to sons than daughters.

Participant Observation Example

• A volunteer at a homeless shelter observed and recorded identity maintenance strategies of homeless individuals, exploring the impact of time spent homeless on self-perception and social interactions.

Summary

• Observational research is a valuable method for examining psychological phenomena in natural or controlled settings.

• Thematic analysis aids in understanding qualitative responses.

• Archival research facilitates analysis of pre-existing data sets for empirical inquiries.

• Factor analysis and meta-analysis serve as important tools in analyzing data from archival sources.