Week 11 Qualitative research 2 Flashcards
What are the NHMRC values in research ethics?
Respect
Research merit and integrity
Justice
benefice
What is ‘respect’
- Each human has intrinsic value
- Respect Autonomy
What is research merit and integrity?
Research involving human participation must have merit and the researchers must have integrity
What is justice?
Distributive justice
Procedural justice
What is benefice?
- Research should do good
- Benefits of the research should justify the risks
How should ‘respect’ be embodied when working with Aboriginal people?
- Respectful engagement with Indigenous peoples
- Value Aboriginal and Torres Strait Islander knowledge and
wisdom
How should research merit and Integrity be embodied when working collaboratively with indigenous Australians?
- Research methods acknowledge cultural distinctiveness of Aboriginal communities
- Identify potential negative consequences and design appropriate processes to minimise them
How should justice be embodied when working collaboratively with Indigenous Australians?
- Indigenous people should be treated as equal research partners
- Provide fair opportunity for indigenous people to be involved in research
How should benefice be embodied when working collaboratively with Indigenous Australians?
- Research benefits should advance the interest of Indigenous people
- Discuss and agree on benefits with Aboriginal people
What AIATISIS Code of Ethics core principles?
Indigenous self-determination
Sustainability and accountability
Indigenous leadership
Impact and value
What comes in Indigenous self-determination? (AIATISIS core principles)
Recognition and Respect
Engagement and collaboration
Informed consent
Cultural capability and learning
What is Indigenous leadership? (AIATISIS core principles)
Indigenous-led research
Indigenous perspectives and participation
Indigenous knowledge and data
What is Indigenous impact and value? (AIATISIS core principles)
Benefits and recipriocracy
Impact and risk
What is Indigenous sustainability and accountability? (AIATISIS core principles)
Indigenous lands and waters
Ongoing Indigenous governance
Reporting and compliance
How do the NHMRC and AIATSIS ethical values
differ?
the AIATSIS values are more cyclical
What is the challenge of qualitative research?
just because qualitative research doesn’t have the same constraints as quantitative research, it does not mean that anything goes it still needs have quality and credability
**quote means there has to be something that differentiates qualitative research to just talking or journalism
qualitative research overview
paradigm - constructionism
Design - Flexible and responds to context
Data - unstructured or semi-structured
analysis - non-numerical, analysis of text
sample - depth not breadth (depth of understanding not generalisability)
What is quality?
Transparency of the research process
An alternative name for quality is reliability
What is credibility?
validation of analysis
An alternative name is validity
Is proving quality and credibility the same in qualitative methods as it is in quantitative?
- ‘Reliability’ and ‘validity’ do not involve the same procedures in qualitative and quantitative approaches
- Different approaches to quality and credibility across different qualitative research methods
In qualitative data, how can we ensure quality and credibility in our study designs and methods?
Consider:
- The phenomenon of interest
- Existing theories about this phenomenon
- The social and cultural context of this phenomenon
- The range of methods that could be used to study the phenomenon
- clear and explicit account of data generalisation methods
- triangulation ( the idea that if you have two or more sources of data and you bring them together then you can get a stronger understanding of the phenomenon than if you just had one source of data)
What is triangulation?
the idea that if you have two or more sources of data and you bring them together then you can get a stronger understanding of the phenomenon than if you just had one source of data)
What does this quote about triangulation mean “ One should not adopt a naively ‘optimistic’ view that the aggregation of data from different sources will unproblematically add up to produce a more complete picture”
Says that different sources of data may not always be commenting on the same phenomenon
What is another critique or qualitative research?
Sample size
says that the sample size of qualitative research is much smaller than quantitative research so that must be a bad thing. From quantitative data we have inherited the idea that larger samples are better and smaller samples are worse.
What are the sampling techniques in in qualitative data
- Representative sample - not ideal
- Purposive sample
- Theoretical sample
Why is representative sampling not ideal for qualitative research
- Large amount of data (hard to analyze this in depth)
- Generally not suitable for rigorous qualitative research
- do not want to generalise to population as qualitative is contextually based
What is purposive sampling?
- An attempt to capture the diversity that you anticipate
might be important - “seek out groups, settings and individuals where … the
processes being studied are most likely to occur”
What is theoretical sampling?
“When conducting theoretical sampling, you are much more selective than before about whom you obtain data from and what you seek from those individuals. You may focus on certain experiences, events or issues, not on individuals per se, because you want to develop your theoretical categories
and need to define how and when they vary”
Data analysis in qualitative research
- Not all explanations are of equal value –> Sometimes people don’t provide an analysis
- Not all explanations are of equal value –> sometimes people wont provide a clear account of the steps they have used to analyse that data
How do you analyse/ show credibility in qualitative data
There is no one way to analyse qualitative data. Here are a few things to be on the lookout for when critiquing qualitative research:
- Comprehensive data analysis
- Reporting (a representation) of data (e.g., transcription)
- Providing ‘thick’ descriptions
- Demonstrating saturation
- Developing analysis with others
- Respondent or communicative validation (‘member checking’)
What is comprehensive data analysis
A way of showing data credibility
trying to combat the problem of anecdotal evidence (the reader needs to know you have analysed data in a particular way and not just cherry-picking evidence that supports your argument )
How do you ensure comprehensive data analysis and ensure the reader knows you aren’t just using anecdotes/cherry picking
- Constant comparative method –> comparing across and within cases (have people said what they said on multiple occasions, have other people said what this person said)
- Deviant/ negative case analysis –> an outlier in qualitative data
What is Reporting (a representation) of data (e.g., transcription)
A way of showing data credibility
when you make the data available for readers. You could transcribe interviews or somehow show the data in an ethical way.
What does ‘Providing ‘thick’ descriptions’ mean?
a way of showing data credibility
provide contexts to claims –> A thin description is no context of claims
What is saturation
A way of showing credibility
Saturation is when you sample until you reach that point of information redundancy (no new information is coming up anymore).
If you can demonstrate saturation to the reader you can demonstrate credibility
What is Developing analysis with others
A way of showing credibility
- Peer debriefing/ data sessions –> Working with people when looking at data
- Inter-rater agreement –> when different researchers agree on how the data should be coded
What is respondent or communicative validation (‘member checking’
a way of showing credibility
Where you do an analysis and then take it back to the participants. The idea is that if the analysis is credible then it must be credible to the people its about
- “There is no reason to assume that members have privileged status as commentators
on their actions
What is REFLEXIVITY
essentially means critical thinking
“Reflexivity is a form of critical thinking which aims to articulate the contexts that shape the processes of doing research and subsequently the knowledge produced”
What is reflexivity underpinned by?
“What is the research process and how am I influencing it?”
Recognises that pure neutrality is not possible and we will always approach research or a topic or a phenomenon with some sort of unconscious biases –> about being open to these and understanding how it effects the work
What should reflexivity include?
Personal reflexivity- what aspects of you influence the research process
Epistemological reflexivity - reflect on the social, political and historical contexts to the research you are conducting
How can we actually practice reflexivity?
- Reflective Journal
- Multiple research/analyse
- Stepping In - insiders perspective
- Stepping out - outsiders perspective
- Stepping sideways - alternative parspective
How can you use reflective journals to practice reflexivity
- Self-dialogue about researcher (personal reflexivity)
- Private record of methodological decisions, preliminary reflections on data generation or analysis
How can you use multiple researchers/analysts to practice reflexivity?
- Dialogue with others to develop complementary and deeper, or divergent and alternative perspectives
- Continuous questioning, multiple answers
How can you use ‘stepping in’ to practice reflexivity?
insider’s perspective
- What do you already know?
- How does your current position, perspective allow you to engage with your topic and participants?
How can you use ‘stepping out’ to practice reflexivity?
outsider’s perspective
- How can you distance yourself from this position?
- Who can help you see it as an outsider?
How can you use ‘stepping sideways’ to practice reflexivity?
alternative perspective
* What other possible explanations are there?
- What other theoretical frames can you use?
How is qualitative data reported?
Different structure to quantitative
* Less formulaic
* More theoretical/ conceptual
* Often results and discussion presented together
* Procedure of data generations and analysis need to be
explained carefully
How is data presented/reported in qualitative research?
Data is usually presented:
* According to themes, concepts, practices etc.
* Active analysis/ interpretation rather than mere
description
* Quotations in their context (social, interactional
etc)
* Enables readers to critically appraise the reported analysis
What are critical appraisal tools?
critical appraisal tools are essentially just some tools that can help you think critically when you’re evaluating the quality of qualitative and Indigenous research
What are some critical appraisal tools?
Consolidated criteria for reporting qualitative studies(COREQ)
Aboriginal and Torres Strait Islander quality appraisal tool
What is Consolidated criteria for reporting qualitative studies(COREQ)
Invites you to reflect on three different parts of the research
Domain 1: research team and research reflexivity (invites you to reflect on the experience of the researcher and their relationship with their participants
Doman 2: about the study design. It encourages you to reflect on the sampling technique that was used, the sample size, weather the setting of the study has been described appropriately
Domain 3: On analysis and findings. Tool encourages you to think about how researchers have coded the data, weather they engaged in participant checking or member checking and weather the evidence have provided match the claims they are making.
What is Aboriginal and Torres Strait Islander quality appraisal tool
Encourages you to reflect on both methodological qualities and ethical practices.
Did the study have Indigenous leadership?
Were local community protocols followed and respected?
Did the research benefit the community is some way?
