HLTH 252 wk 9 - qualitative research methods

qualitative research methods

• wide variation in specific designs

• wide variations in specific analysis

• common methods of data collection

  • qualitative observation

  • qualitative interviews

  • qualitative document analysis

    • texts, pictures, media, etc

qualitative observation

• researcher observes and takes field notes on the activities and behaviours of individuals at a research site

  • notes are interpretive and reflexive

  • unstructured or semi structured

• researcher’s role on a continuum:

  • complete observer: uninvolved and unknown

  • observer as participant: ‘un’-involved and known (be as neutral as possible)

  • participant as observer: involved and known

  • complete participant: involved and known

• Strengths

  • researcher is closer to experiences of participant

  • provides context to processes, experiences

  • allows exploration of topics that participants are unaware of or uncomfortable speaking about

• Limitations

  • introducing ‘researcher’ changes dynamic

  • ethics of observing private activities

  • reliant on researcher’s perspective

    • varying skill levels

    • don’t know internal experiences

Qualitative interviews

• researcher speaks with and records a conversation with participants

• variation in question structure

  • structured interview: fully predetermined, set order, often closed-ended for easier comparison

  • semi structured interview: set of open-ended main questions in a flexible order with opportunity for follow up

  • unstructured interview: 1-2 very open-ended questions, followed by open conversation

• variation in interview structure

  • one on one vs dyadic vs focus group

  • in person vs remote

  • inclusion of prompts or activities

• strengths

  • insight on internal experiences/perspectives

  • opportunities for elaboration and nuance

  • may approach challenging topics

• limitations

  • performed out of context

  • current perspectives on past events

  • power dynamics of conversation

  • abilities for verbal communication

realist ontology

• ie. more positivist, quantitative

• one objective reality, independent of me

• reality can be understood through observation

• research methods aim to uncover that reality

• good research is valid and reliable

relativist ontology

• ie. more interpretivist, qualitative

• multiple subjective realities, unique to each person

• reality is constructed through experience, perceptions, and interpretations

• research methods aim to represent others’ realities

• validity and reliability don’t apply, so what does good research look like?

8 big-tent criteria for excellent qualitative research

1. worthy topic

relevant, timely, significant, interesting, evocative

2. rich rigour

3. sincerity

4. credibility

5. resonance

6. significant contribution

theoretical: extends, builds, or critiques disciplinary knowledge

heuristic: moves people to explore, research, or act in that area

practical: produces knowledge that is useful, empowering, or liberating

methodological: engaging methodology in new, creative, or insightful way

7. ethical

care in how the research is conducted, situated in context, positioned, and presented

8. meaningful coherence

achieve stated purpose, use methods in line with paradigms, connect with literature

Richness

• while quantitative research values precision, high quality qualitative research is marked by rich complexity and abundance

Rigour

• face validity in qualitative research: does a study appear to be reasonable and appropriate?

• researchers should evidence their due diligence:

  • are there enough data to support significant claims?

  • did the researcher spend enough time to gather interesting and significant data?

  • is the context or sample appropriate given the goals of the study?

  • did the researcher use appropriate procedures of data collection and analysis?

sincerity

• means that research is marked by honesty and transparency about the researcher’s biases, goals, and foibles as well as how these played a role in the methods, joys, and mistakes of the research

Self Reflexivity

• honesty and authenticity with one’s self, one’s research, and one’s audience

• examination of one’s biases, motivations, knowledge in relation to study design, conduct, and analysis

Transparency

• honesty about the research process

• good researchers leave an “audit trail” of notes on study procedures, decisions, mistakes

credibility

thick description

• good research will show, rather than tell, the participants perspectives

crystallization & triangulation

• alignment between multiple researchers, data sources, methods, or theoretical lenses

multivocality

• lean into conflicting or contrasting opinions by presenting a variety of viewpoints on a topic

member reflections

• seeking input from participants on processes and results of the analysis

resonance

aesthetic merit

• text is presented in an evocative way, which allows the reader to connect with it

transferability and naturalistic generalization

• qualitative research is not statistically generalizable… but that is not a limitation

  • qualitative paradigms do not assume their samples are representative of a population

• transferability is achieved when readers feel as though the story of the research overlaps with their own situation and they intuitively transfer the research to their own actions

• though the process of naturalistic generalizations, readers make choices based on their own intuitive understanding of the scene, rather than feeling as though the research report is instructing them what to do

thematic analysis

common and simple form of qualitative analysis

• applicable across many designs

• contains components of more complex approaches

Braun & Clarke’s (2006) 6-phase model

1. familiarize yourself with the data

2. gererate initial codes

3. develop initial themes

4. review and refine themes

5. define and name themes

6. produce the report

phase 1-2: familiarization & coding

familiarization

• process of immersing yourself in the data

• listening and re-listening; reading and re-reading

  • making general notes about data as information

• if data is in audio, transcribe it to text format

  • check for ‘accuracy,’ use transcription as familiarization

coding

• code = something of interest for research question

  • word, sentence, paragraph

• text can be tagged once, multiple times, or not at all

  • can create new, re-use, combine, or split

phases 3-5: theme construction

theme development

• organize codes into ‘candidate’ themes

  • clustering codes into higher'-level patterns

Theme refinement

• review and revise candidate themes

  • should ‘say something important’ about the data

theme naming & defining

• label and define each theme

  • overarching themes: organizing idea

  • main themes: meaning of central concept

  • sub themes: patterns within themes

Phase 6: writing up

• integral part of the entire analytic process

  • note taking, revisions, definitions, etc

• balance between (a) presenting data extracts and (b) providing analytic commentary

  • aim for 50/50, but depends on space, aim of paper, and research tradition