Transferability In Qualitative Research

Transferability in qualitative research refers to the extent to which the findings of a study can be applied or transferred to other contexts, settings, or populations beyond the specific study sample.

Unlike the concept of generalizability in quantitative research, which aims to extrapolate findings to a larger population, transferability recognizes the context-dependent nature of qualitative research and acknowledges that findings may not be universally applicable.

Guba (1981) argues that while generalizability is not a primary aim of qualitative research, transferability is achievable through “fittingness.”

This concept refers to the degree of similarity or “goodness of fit” between the research context and other potential settings where the findings might be applied.

Guba (1981) maintains that it is the reader, not solely the researcher, who bears the responsibility of gauging the “fittingness” of the research findings to their specific situation.

This emphasizes the role of the reader or the “knowledge user” in determining the relevance and transferability of the research to their specific circumstances.

To facilitate this process, researchers must equip readers with a thorough understanding of the study context through thick description.

This detailed account encompasses not only the research setting and participant characteristics, but also the intricate processes of data collection and analysis,

Strategies for Enhancing Transferability

Transferability determines the extent to which research findings can be applied to other contexts or with other subjects. It is a core component of trustworthiness, similar to the concept of generalizability in quantitative research.

1. Thick Description: Painting a Vivid Picture of the Context

Transferability in qualitative research refers to how well findings from one study context can be meaningfully applied to other settings or situations.

Unlike generalizability in quantitative research, which aims for universal applicability, transferability hinges on the “fittingness” between the original study context and the context to which the findings are being transferred.

Thick description serves as the primary tool for enabling transferability assessments.

In essence, it provides readers with the detailed contextual information they need to make informed judgments about this “fittingness.”

The aim is to create a compelling narrative that draws readers into the study context, allowing them to connect with the participants’ experiences and grasp the significance of the findings.

Instead of merely presenting bare-bones findings or themes, thick description involves providing a rich and detailed account of:

• Research Setting: This encompasses the physical, social, and cultural environment in which the study took place. It might include details about the community, the organization, or the specific location where data was collected.
• Participant Characteristics: Thick description extends beyond basic demographics to capture the diversity and complexity of the individuals involved in the study. This might include information about their backgrounds, experiences, perspectives, and roles within the research context.
• Data Collection and Analysis Procedures: A transparent and detailed account of the methods used to gather and analyze data is crucial for transferability. This includes describing the specific techniques employed (e.g., interviews, focus groups, observation), the rationale behind their selection, and how they were implemented in practice. Describing the analytic process, including the steps taken to identify themes, develop interpretations, and ensure rigor, allows readers to understand how the findings were generated and assess their potential applicability to other contexts.

When presenting thick description, avoiding jargon and overly abstract language in favor of clear, evocative language can make qualitative research more accessible and transferable to a wider audience.

This approach ensures that the rich contextual details are communicated effectively to readers from diverse backgrounds and disciplines.

2. Data Triangulation:

Relying on a single source makes a study more vulnerable to errors, such as biased questions or researcher influence.

By gathering data from diverse sources, researchers can illuminate different facets of the phenomenon, reducing the risk that their findings reflect only a partial or skewed perspective.

Using multiple data sources and collection methods can enhance the richness and comprehensiveness of the data, providing a more robust basis for considering transferability.

For instance, using a combination of observation field notes and interview transcripts to gain a richer perspective on the phenomenon being studied.

It’s crucial to note that triangulation does not necessarily imply seeking complete agreement across data sources. The goal is not to force a singular, unified interpretation but to acknowledge and explore the complexities and contradictions that may emerge.

By embracing these complexities, researchers can generate more nuanced and transferable insights.

For example, if one data source suggests a particular theme, while another reveals contradictory evidence, researchers should delve into these discrepancies, exploring the reasons behind the differences and considering how they might shape the overall interpretation of the findings.

3. The Reader’s Role: A Collaborative Process:

Transferability is not solely the researcher’s responsibility.

The onus also falls on the reader to evaluate the applicability of the research findings.

Readers must carefully consider the alignment between the study context and their own situation, factoring in aspects like participant demographics, cultural norms, and the specific phenomenon under investigation.

To support readers in this evaluation process, researchers should strive for clarity and transparency in their writing, avoiding jargon, overly abstract language, and technical terms that might hinder readers’ understanding.

The aim is to present the research in a way that is accessible and engaging for a wider audience, facilitating meaningful connections between the research context and potential applications.

One innovative approach to enhancing research accessibility and transferability is ethnodrama – a performance-based method that draws upon research data to create a dramatic script.

This approach goes beyond simply presenting research findings; it aims to capture the lived experiences of participants and convey them through dialogue, action, and storytelling.

By witnessing the experiences of others brought to life on stage, audiences can develop a deeper understanding of the research topic and potentially see connections to their own lives or situations.

Ethnodrama can be particularly impactful for communicating sensitive or complex issues, allowing audiences to connect with the research on an emotional level.

This method makes research more accessible to audiences beyond the academic community, bridging the gap between research and the public.

For example, when research findings are presented through dramatic performance, they often become more engaging and memorable for audiences, increasing the likelihood that the insights will be retained and potentially applied in other contexts.

Threats to Transferability in Qualitative Research

1. Insufficient Thick Description:

Thick description aims to create a rich and comprehensive picture of the research context, allowing readers to assess the similarities and differences between the study setting and their own situations.

A key threat to transferability is inadequate thick description of the research context, participant characteristics, and methodological procedures.

Without sufficient detail, readers lack the necessary information to judge the “fittingness” of the findings to their own situations.

This echoes Guba’s (1981) argument, as discussed in our previous conversation, that the reader bears the responsibility for evaluating transferability based on the researcher’s provision of rich contextual information.

2. Overemphasis on Thematic Emergence:

The over-reliance on thematic emergence as a marker of rigor in qualitative research.

While the identification of novel themes is valuable, an exclusive focus on emergence may neglect the importance of connecting findings to existing literature and theoretical frameworks.

This can hinder transferability by limiting the integration of findings into broader bodies of knowledge.

3. Inadequate Attention to Power Dynamics and Positionality:

Qualitative research is inherently influenced by the power dynamics and positionality of both the researcher and the participants.

Failure to acknowledge and account for these factors can limit transferability by obscuring the ways in which social contexts and individual perspectives shape the research process and its outcomes.

4. Lack of Reflexivity in Transcription:

Transcription, a critical stage in qualitative research, can also introduce threats to transferability.

The choices made during transcription, such as the level of detail included or the interpretation of non-verbal cues, are inherently subjective and can influence the analysis.

A lack of reflexivity in the transcription process can obscure these choices, making it difficult for readers to assess the potential influence on the findings and their applicability to other contexts.

5. Misuse of Member Checking:

While member checking can enhance credibility, its misuse can threaten transferability.

If member checking is treated as a validation tool aimed at achieving complete agreement with participants, it can stifle critical analysis and limit the potential for generating transferable insights.

6. Ignoring Negative Cases:

Failing to account for negative cases, those that do not fit the emerging patterns or themes, can lead to an overly simplistic representation of the phenomenon.

Ignoring negative cases can threaten transferability by obscuring the complexity and variability that might exist in other contexts.

7. Lack of Transparency in Data Analysis:

Transparency is important in qualitative data analysis for demonstrating rigor.

A lack of detail regarding the specific moves or strategies used in the analysis can hinder readers’ ability to assess the trustworthiness of the findings and their potential applicability to different settings.

How do I report transferability in my research?

Method section

• Thorough Explanation of Sampling Strategies: Clearly articulate the rationale for your sampling choices, including inclusion and exclusion criteria.
  
  Describe the characteristics of your participant sample in detail (demographics, experiences, roles, etc.).
  
  This transparency enables readers to evaluate whether the sample is representative of the population of interest and to consider the potential generalizability of the findings.
• Detailed Documentation of Data Collection and Analysis: Describe the specific methods used to collect data (e.g., interviews, focus groups, observations), as well as the steps taken to ensure data quality.
  
  Provide a thorough account of your data analysis process, explaining how you coded, categorized, and interpreted the data.
  
  This level of detail enables readers to understand the rigor of your methods and to assess the potential for replication.

Results section

• Provide Rich, Descriptive Accounts of the Findings: Go beyond simply reporting themes or categories; instead, offer vivid and detailed descriptions of the patterns you observed.
  
  Use evocative language and illustrative quotes from participants to bring the findings to life, allowing readers to immerse themselves in the data and consider its potential relevance to other settings.
  
  This aligns with the concept of “thick descriptions” which are crucial for enhancing transferability.
• Highlight Similarities and Differences within the Sample: If your findings reveal variations in experiences or perspectives among participants, explore and discuss these differences.
  
  This exploration of nuances within the data can provide insights into the potential boundaries of transferability, helping readers to discern contexts where the findings might be more or less applicable.
• Relate Findings to Relevant Characteristics of the Sample: Connect the findings back to the specific characteristics of your sample (demographics, experiences, roles).
  
  For example, if you observe a particular pattern among participants with a certain level of experience, highlight this connection.
  
  This explicit linkage helps readers to assess the potential applicability of the findings to other groups with similar characteristics.
  
  This detailed reporting of the sample’s characteristics also strengthens transferability.
• Offer Tentative Insights about Potential Transferability: While avoiding definitive claims of generalizability, you can offer cautious insights about the potential relevance of your findings to other contexts.
  
  Use phrases like “These findings suggest that…” or “It is possible that…” to signal the tentative nature of these insights.
  
  For instance, you could write: “The strong emphasis on mentorship in this study suggests that similar programs in other healthcare settings might benefit from incorporating robust mentorship components.”

By thoughtfully presenting your results in a way that considers potential transferability, you invite readers to engage with the findings on a deeper level and to contemplate their broader implications.

Discussion section

The discussion section provides a prime opportunity to explicitly address the transferability of your findings and guide readers in considering their broader implications.

• Reiterate the Contextual Boundaries of the Study: Begin by reminding readers of the specific context in which your research was conducted, including any limitations or unique characteristics of the setting or sample.
  
  This transparency helps readers to assess the potential generalizability of the findings from the outset.
  
  As stated in, “Research meets this criterion when the findings fit into contexts outside the study situation that are determined by the degree of similarity or goodness of fit between the two contexts.”
• Compare and Contrast Findings with Existing Literature: Connect your findings to relevant theories and research from your field. Highlight areas of agreement or divergence, discussing how your findings support, challenge, or extend existing knowledge.
  
  This comparative analysis helps readers to situate your findings within a broader scholarly context and to consider their transferability in light of previous work.
• Discuss the Potential Implications for Other Contexts: Based on the insights gleaned from your data and its relationship to the existing literature, offer tentative suggestions about how your findings might apply to other settings, populations, or situations.
  
  Use cautious language and acknowledge the limitations of generalizability.
  
  For example, “While this study focused on a particular type of organization, the findings regarding the importance of clear communication channels may be relevant to other organizations facing similar challenges.”
• Identify Factors That Might Influence Transferability: Explicitly discuss factors that could either enhance or limit the transferability of your findings.
  
  For instance, cultural norms, organizational policies, or specific demographic characteristics of the sample might influence the applicability of the results to other contexts.
  
  Highlighting these factors guides readers in making informed judgments about transferability.
• Suggest Avenues for Future Research: Conclude by proposing directions for future research that could further explore the transferability of your findings.
  
  Encourage replication studies in different contexts or with different populations to test the boundaries of generalizability.
  
  This open invitation for further inquiry acknowledges the limitations of a single study and highlights the ongoing nature of knowledge construction.

By thoughtfully and critically addressing transferability in your discussion section, you empower readers to assess the relevance and applicability of your research beyond the immediate study context.

Reading List

• Anney, V. N. (2014). Ensuring the quality of the findings of qualitative research: Looking at trustworthiness criteria.
• Guba, E. G. (1981). Criteria for assessing the trustworthiness of naturalistic inquiries. Ectj, 29(2), 75-91.
• Krefting, L. (1991). Rigor in qualitative research: The assessment of trustworthiness. The American journal of occupational therapy, 45(3), 214-222.
• Lincoln, Y. S., & Guba, E. G. (1982). Establishing dependability and confirmability in naturalistic inquiry through an audit.
• Lincoln, Y. S., & Guba, E. G. (1986). But is it rigorous? Trustworthiness and authenticity in naturalistic evaluation. New directions for program evaluation, 1986(30), 73-84.
• Schwandt, T. A., Lincoln, Y. S., & Guba, E. G. (2007). Judging interpretations: But is it rigorous? trustworthiness and authenticity in naturalistic evaluation. New directions for evaluation, 2007(114).
• Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research projects. Education for information, 22(2), 63-75.