Full Answer Section

• • • • Credibility: Ensuring findings are a true reflection of participants’ realities (e.g., prolonged engagement, member checking).
      • Transferability: Providing rich descriptions to allow others to determine the applicability of findings to their context.
      • Dependability: Demonstrating the consistency of the findings over time (e.g., audit trail).
      • Confirmability: Establishing the neutrality of the findings (e.g., reflexivity).
    • Example: A qualitative study on patients’ experiences with chronic pain might use member checking, where participants review the researchers’ interpretations to ensure accuracy.
• Generalizability: Qualitative research typically involves small sample sizes, which can raise questions about the generalizability of findings to larger populations.
  • Addressing the issue:
    • Researchers should focus on the transferability of the findings rather than generalizability.
    • Providing thick, rich descriptions of the study context and participants allows clinicians to determine if the findings are applicable to their specific patient population.
    • Example: A qualitative study exploring nurses’ experiences with a new charting system can provide detailed descriptions of the work environment, the nurses’ roles, and the technology. Other nurses can then assess if those descriptions resonate with their own situation.
• Time and Resources: Conducting high-quality qualitative research can be time-consuming and resource-intensive. Data collection (e.g., in-depth interviews, observations) and analysis are often lengthy processes.
  • Addressing the issue:
    • Securing adequate funding and resources for qualitative research projects.
    • Developing efficient data collection and analysis strategies (e.g., using qualitative data analysis software).
    • Collaborating with experienced qualitative researchers.
    • Example: A hospital implementing a new palliative care program might allocate funds for a qualitative study to explore patient and family experiences, recognizing the value of this research in informing program improvement.
• Researcher Bias: Qualitative research involves close interaction between the researcher and participants, which can increase the potential for researcher bias to influence data collection and interpretation.
  • Addressing the issue:
    • Employing reflexivity, where researchers critically examine their own assumptions, beliefs, and experiences and how they might influence the research process.
    • Using triangulation, which involves using multiple data sources or methods to confirm findings.
    • Seeking peer review and expert consultation to enhance the objectivity of the analysis.
    • Example: A nurse researcher studying the impact of a new intervention on patient anxiety might keep a reflexive journal to document their own feelings and reactions during the data collection process, ensuring these are considered during analysis.
• Integration with Quantitative Evidence: EBP has historically favored quantitative research, leading to challenges in integrating qualitative findings, which often explore different types of questions.