Theoretical Sampling in Grounded Theory

Theoretical sampling is a data collection method used in grounded theory research. It involves collecting and analyzing data simultaneously, with the goal of developing a theory as it emerges.

Unlike traditional research where sampling decisions are made upfront, theoretical sampling is an iterative process where the selection of data sources (like participants, documents, or observations) is guided by the emerging analysis.

This means the researcher analyzes data from initial sources before deciding who or what to sample next.

The researcher actively seeks out participants or data sources that are likely to provide rich information about the developing categories and their relationships.

This process continues until theoretical saturation is reached, meaning that no new insights are being gained from the data.

Steps of Theoretical Sampling in Grounded Theory

Theoretical sampling is an iterative process, closely tied to the analysis of the data.

As new data is collected, it is analyzed, and this analysis, in turn, can lead to new theoretical insights, prompting further theoretical sampling decisions.

This cycle continues until the researcher reaches theoretical saturation, indicating that no new information is emerging from the data.

Theoretical sampling is employed once the researcher has begun developing tentative categories through initial coding and analysis.

As the researcher identifies potential relationships between categories, theoretical sampling helps to gather data that can either confirm or refute these hypotheses

1. Initial Purposive Sampling:

• Begin the research with a small, purposefully selected sample of participants or data sources. This initial sample is chosen based on the researcher’s preliminary understanding of the phenomenon under investigation and the research questions.
• The goal of this initial sampling is not to be representative but rather to gain a broad understanding of the phenomenon and identify potential areas for further exploration.
• The size of the initial sample should be manageable, allowing for in-depth analysis of the data.

2. Data Collection and Initial Coding:

• Collect data from the initial sample, using methods such as interviews, observations, or document analysis.
• Begin coding the data immediately, breaking it down into meaningful segments and assigning codes to these segments.
• This initial coding is open and exploratory, focusing on identifying key themes and concepts.

3. Memo Writing and Reflection:

• Simultaneously with coding, write memos to document your analytical thoughts, reflections, questions, and emerging insights.
• Memos serve as a record of your thinking process, allowing you to track the development of your ideas and identify potential areas for further investigation.

4. Identifying Emerging Themes and Concepts:

• Through the process of coding and memo writing, identify patterns in the data and begin to develop tentative categories or concepts.
• These provisional categories may change as you collect and analyze more data.

5. Theoretical Sampling to Refine Categories:

• Based on the emerging categories, make strategic decisions about which participants or data sources to sample next.
• Theoretical sampling is directed by the developing theory and aims to gather data that will help to:
  • Saturate Existing Categories: Collect data to further explore the properties and dimensions of existing categories, ensuring that you have captured their full range and variation.
  • Develop Relationships Between Categories: Sample data to examine how different categories relate to each other, identifying potential connections, overlaps, or contradictions.
  • Explore Emerging Questions: Pursue data that will help answer questions or address gaps that have arisen during analysis.

6. Iterative Process of Data Collection, Analysis, and Sampling:

• Continue the cycle of data collection, coding, memo writing, and theoretical sampling iteratively.
• Each round of data collection and analysis will inform subsequent sampling decisions, leading to a progressively refined and focused theoretical understanding.

7. Achieving Theoretical Saturation:

• Continue theoretical sampling until you reach theoretical saturation, the point at which collecting additional data does not yield new insights or properties within the categories.
• Theoretical saturation indicates that you have sufficiently explored the phenomenon and that your categories are well-developed and conceptually dense.

8. Documentation of Sampling Decisions:

• Throughout the process, meticulously document all sampling decisions, including the rationale for selecting specific participants or data sources.
• This documentation serves as an audit trail, enhancing transparency and allowing you to demonstrate the rigor and systematic nature of your sampling approach.

Practices Related to Theoretical Sampling

Theoretical Sensitivity

Theoretical sensitivity is the researcher’s ability to recognize and extract meaningful patterns and themes from the data that contribute to the developing theory.

When deciding where to sample next, the researcher uses theoretical sensitivity to evaluate which participants or data sources would be most likely to provide rich information about the aspects of the theory that need further development.

The interplay between theoretical sensitivity and theoretical sampling ensures that the emerging theory is constantly refined and grounded in the data, resulting in a richer and more insightful understanding of the phenomenon under study.

Constant Comparison

Constant comparison involves continuously comparing data with data, data with codes, codes with codes, and so on.

Once the researcher has identified these gaps or uncertainties through constant comparison, theoretical sampling provides a roadmap for gathering specific data to address them.

For example, if constant comparison reveals a missing property of a category, the researcher might use theoretical sampling to recruit participants who are likely to possess that property, or to analyze documents that focus on that aspect.

It’s crucial to understand that both constant comparison and theoretical sampling are not one-time activities in GT. They are iterative processes that occur throughout the research.

Theoretical Saturation

Theoretical saturation occurs when collecting additional data about a theoretical category reveals no new properties, dimensions, or insights about the emerging theory.

In essence, theoretical saturation signifies that the researcher has reached a point of “theoretical completeness” where the categories are richly developed and the relationships between them are well-established.

The goal of GT is not to collect a massive amount of data but to strategically gather data that is most relevant for building and refining the theory.

When theoretical saturation is reached for a particular category or set of categories, it indicates that further data collection on those aspects is unlikely to contribute any new understanding.

Therefore, the researcher can confidently cease theoretical sampling in those areas

Ethical Issues

The flexible nature of theoretical sampling makes it challenging to specify the exact population and sampling criteria in advance, a common requirement in traditional research ethics applications.

As the research progresses and new theoretical insights emerge, researchers might need to modify their sampling strategy, requiring amendments to their initial ethics applications.

This can lead to delays, require justification, and pose challenges when dealing with ethics committees unfamiliar with GT methodology.

Researchers need to ensure that participants are continually informed about the study’s direction and have opportunities to reconsider their participation.

As theoretical sampling leads to collecting data from new sources, researchers must adapt their data management and security protocols to ensure the confidentiality of all participants. This involves:

• De-identifying data promptly and effectively to protect participant anonymity.
• Securely storing data, both physical copies and electronic files, to prevent unauthorized access.
• Developing clear procedures for data sharing and disposal that comply with ethical guidelines and data protection regulations.

Documentation of Decisions

Meticulously documenting theoretical sampling choices creates an audit trail that enhances the transparency of the research process.

This documentation should outline the rationale for selecting specific participants or data sources at each stage of the research, demonstrating how these decisions were grounded in the emerging theory and not driven by arbitrary choices or researcher bias.

This transparency allows others to understand how the theory evolved and strengthens the study’s credibility.

Clear documentation of theoretical sampling decisions is particularly important when seeking ethical approval or responding to queries from ethics committees.

Researchers need to provide a clear explanation of the principles and procedures of theoretical sampling, demonstrating its systematic and rigorous nature.

Providing examples of how sampling decisions might evolve based on emerging data can help ethics committees understand the rationale behind this flexible approach.

Analytical memos serve as a primary tool for documenting the researcher’s thinking process, including reflections on theoretical sampling decisions.

A dedicated sampling log can be used to systematically record details of each sampling decision, including:

• Date of the decision.
• Rationale for the decision, explicitly linking it to the emerging theory.
• Specific characteristics of the chosen participant or data source.
• Reflections on the potential contribution of this data to the theory development.

Example

To illustrate how theoretical sampling works in practice, let’s consider a hypothetical grounded theory study examining the experiences of nurses transitioning from hospital settings to community care roles.

Initial Purposive Sampling:

• The researcher might begin by purposefully sampling a small group of nurses who have recently made this transition.
• The initial sample could include nurses with varying levels of experience, different specialties, and from diverse geographical locations to ensure maximum variation in the early data.

Initial Data Collection and Analysis:

• The researcher could conduct in-depth interviews with these nurses, exploring their motivations for the transition, challenges they faced, coping mechanisms they employed, and their perceptions of their new roles.
• Initial coding and analysis of these interviews might reveal several emerging themes:
  • Role Adjustment: Nurses describe difficulties adjusting to the increased autonomy, different skill sets, and changing patient dynamics in community care.
  • Professional Identity: Nurses express feelings of uncertainty or a sense of loss related to their professional identity as they navigate their new role.
  • Support Systems: Nurses highlight the importance of support from colleagues, supervisors, and family during the transition.

Theoretical Sampling Based on Emerging Themes:

• Based on these emerging themes, the researcher could then theoretically sample additional participants to refine and expand the developing categories.
  • To further explore “Role Adjustment,” the researcher could seek out nurses who have experienced particularly challenging transitions, perhaps those working in specialized areas of community care or in remote locations with limited resources.
  • To understand the nuances of “Professional Identity,” the researcher could interview nurses who have transitioned back to hospital settings after working in community care, examining the factors that influenced their decisions.
  • To gain a deeper understanding of “Support Systems,” the researcher could interview supervisors and family members of nurses who have made the transition, exploring their perspectives on the challenges and support needs.

Iterative Process and Saturation:

• This process of data collection, coding, analysis, and theoretical sampling would continue iteratively, with each round informing the next.
• As the researcher collects more data and refines the categories, they would write memos documenting their analytical thoughts, the rationale behind their sampling decisions, and any adjustments made to the research process.
• The researcher would continue this cycle until they reach theoretical saturation, the point at which no new properties are emerging within the categories, and the relationships between categories are well-established.

Sources

Birks, M., & Mills, J. (2015). Grounded theory: A practical guide. Sage.

Chenitz, W. C., & Swanson, J. M. (1986). From practice to grounded theory: Qualitative research in nursing. (No Title).

Corbin, J., & Strauss, A. (1990). Grounded theory research: Procedures, canons, and evaluative criteria. Qualitative Sociology, 13, 3-21.

Glaser, B. G. (2005). The grounded theory perspective III: Theoretical coding. Sociology Press.