trustworthiness and integrity in qualitative research

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trustworthiness and integrity in qualitative research
2013-12-05 22:23:28
3215 final
3215 final
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  1. debates about rigor and validity
    Controversies about quality

    A major dispute has involved whether “validity” and “rigor” are appropriate.

    Some reject these terms and concepts totally, some think they are appropriate, and others have searched for parallel goals.
  2. terminology proliferation and confusion
    no common vocabulary exists

    • - goodness
    • - truth value
    • - integrity 
    • - trustworthiness 
    • - validity and rigor
  3. controversies in qualitative research
    • - some frameworks and criteria aspire to being generic - to be applicable across qualitative traditions
    • - other frameworks are specific to a tradition or even to a specific analytic approach within a tradition
  4. which criteria is often viewed as the "golden standard" for qualitative research?
    the criteria that were outlined by Lincoln and Guba
  5. is is they key goal for Lincoln and Guba's framework
  6. trustworthiness
    • concerns the "truth value" of a qualitative data, analysis, and interpretation
    • a parallel perspective, with analogs to quantitative criteria
  7. Lincoln and Guba framework encompasses what five criteria?
    • - credibility 
    • - dependability 
    • - confirmability
    • - transferability 
    • - authenticity
  8. credibility
    • refers to confidence in the truth of the data and interpretations of them 
    • the analog of internal validity in quantitative researc
    • arguably the most important criterion for assessing the quality and integrity of a qualitative inquiry
  9. dependability
    • refers to stability of data overtime and over conditions
    • the analog of reliability in quantitative research
  10. confirmability
    • refers to neutrality - the potential for congruence between two or more people about data accuracy, relevance, or meaning
    • the analog of objectivity in quantitative research 
  11. transferability
    • the extent to which findings can be transferred to other settings or groups
    • the analog of generalizability or external validity in quantitative research
  12. authenticity
    • the extent to which the researchers fairly and faithfully show a range of different realities and convey the feeling/tone of participants' lives as they are lived
    • no analog in quantitative research 
    • added to the Lincoln-Guba framework at a later date
  13. strategies to enhance quality in qualitative inquiry
    • researchers can take many steps to enhance the quality of their inquiries 
    • consumers can assess quality-enhancement efforts by looking for these steps and assessing their success in strengthening integrity/validity/trustworthiness
  14. strategies during data collection
    • prolonged engagement 
    • persistent observation 
    • reflexivity strategies
    • data triangulation
    • method triangulation
    • comprehensive and vivid recording of information 
    • member checking
  15. prolonged engagement
    the investment of sufficient time collecting data to have in-depth understanding of the culture, language, or views of the people or group under study, to test for misinformation and distortions, and to ensure saturation of important categories
  16. persistent observation
    concerns the salience of the data being gathered. it refers to the researchers focus on the characteristics or aspects of a situation that are relevant to the phenomena being studied
  17. reflexivity strategies
    involves awareness that the researchers as an individual brings to the inquiry a unique background, set of values, and a social and professional identity that can affect the research process
  18. data triangulation
    the use of multiple data sources to validate conclusions [time, space, and person triangulation]
  19. time triangulation
    • involves collecting data on the same phenomenon or about the same people at different points in time
    • similar to test-retest reliability assessment 
  20. space triangulation
    involves collecting data on the same phenomenon in multiple sites, to test for cross-site consistency
  21. person triangulation
    involves collecting data from different types or levels of people [e.g., individuals, family, communities], with the aim of validating data through multiple perspectives of the phenomenon
  22. method triangulation
    the use of multiple methods of data collection to study the same phenomenon (e.g., self-report, observation)
  23. comprehensive and vivid recording of information
    Maintenance of an audit trail, a systematic collection of documentation and materials, and a decision trail that specifies decision rules
  24. audit trails may include the following types of records
    • the raw data [interview transcripts]
    • methodologic, theoretic, and reflexive notes
    • instrument development information [i.e., pilot topic guides]
    • data reconstruction products [i.e. drafts of the final report]
  25. member checking
    providing feedback to participants about emerging interpretations; obtaining their reactions

    A controversial procedure—considered essential by some but inappropriate by others
  26. strategies related to coding and analysis
    • investigator triangulation 
    • stepwise replication 
    • theory triangulation
    • searching for discomfirming evidence and competing explanations
    • negative case analysis
    • peer review and debriefing 
    • inquiry audit
  27. investigator triangulation
    • use of two or more researchers to make data coding, analytic, and interpretive decision
    • the thought is that through collaboration, investigators can reduce the possibility of biased decisions and idiosyncratic interpretations
  28. stepwise replication
    • dividing the research team into two groups to undertake parallel analyses and interpretations that are then compared
    • associated with Lincoln-Guba dependability criterion
  29. theory triangulation
    use of competing theories, hypothesis, or conceptualizations in the analysis and interpretation of data
  30. searching for discomfirming evidence and competing explanations
    • Search for disconfirming evidence as the analysis proceeds, through purposive/theoretical sampling of cases that can challenge interpretations
    • this strategy depends on concurrent data collection and data analysis; researchers cannot look for discomfirming data unless they have a sense of what they need to know
  31. negative case analysis
    • a specific search for cases that appear to discredit earlier critical feedback
    • this strategy is a process by which researchers review their interpretations by including cases that appear to disconfirm earlier hypotheses
  32. peer review and debriefing
    sessions with peers specifically designed to elict critical feedback
  33. inquiry audit
    • a formal scrutiny of the data and relevant supporting documents and decisions by an external reviewer 
    • can be a good tool for persuading other that qualitative data are worthy of confidence
  34. strategies relating to presentation
    Thick and contextualized description: vivid portrayal of study participants, their context, and the phenomenon under study

    Researcher credibility: enhancing confidence by sharing relevant aspects of the researcher’s experience, credentials, and motivation
  35. Interpretation of Qualitative Findings
    Interpretation in qualitative inquiry—making meaning from the data—relies on adequate incubation.

    Similar interpretive issues as in quantitative research: credibility, meaning, importance, transferability, and implications
  36. incubation
    is the process of living the data, a process in which researchers must try to understand their meanings, find their essential pattern, and draw well-grounded, insightful conclusions.