Class 8 Flashcards
Qualitative Sampling
- uses what form of sampling
- How is the type determined
- What do you focus on with the same size
Non-probability sampling
-All qualitative research uses non-probability sampling because our aim is not to look at the whole population (not interested in generalizaible), its more in-depth therefore a smaller sample size and not seen as a critique
Type determined by methodology
Sample size
-focus on richness of data, rely on smaller numbers of participants
What are the three common types of nonprobability sampling and describe them
Snowball sampling- Participants informing other potential participants based on eligibility criteria
Purposive sampling- hand picked sample based on specific knowledge of the population and its elements
Theoretical sampling- More focused data from new participants, complete information about developing concepts
(grounded theory)
Qualitative Data Collection
-What are 6 different tools/strategies and describe them
Interviews (unstructured or semi-structured)
- Unstructured: unbias data, go in with an idea of what you want to talk about but do not have any specific questions written down
- Semi-structured: have some questions written, but not many; questions you would like to ask
Focus groups (groups of people interviewed together) -Focus groups: type of interviewing, with a group of people at the same time rather than a standard interview which is usually one-on-one
Observations
-Observation: reflections of observing that becomes that data; sits in a research setting an observes
Field notes
-Field notes: on going detailed notes as the research is unfolding and progressing; apart of the data even though they are your own thoughts and observations
Written accounts or documents (i.e. letters, diaries, narratives, policies, newspaper stories)
Visual mediums (photos, artwork)
Interviews
- How do the collector/researchers ask questions
- Which allows for
- Room for what
- express what
Interview guide
- written by who
- adapted as?
- may include
- may be given to
- do they change
Data collector or researcher asks the participant(s) questions verbally (face to face, over the phone, Skype or electronic means)
Allows for rich and complex data to be collected
Room for clarification of misunderstood questions, greater depth of data
-By asking specific or detailed questions as well as open-ended, we can create a greater depth of data
- Express thoughts and feelings
Interview guide
- Written questions to be asked during the interview
- Adapted as study progresses
- May include prompts
- May be given to the participant prior
- planned questions however can change as the study progresses
Observation
- Best for what
- What kind of communication
- Interactions?
- behaviours?
- Best for complex research situations (difficult to measure in parts)
- Verbal and nonverbal communication
- Group/social interaction
- Psychosocial Behaviours
E.g., Parent-infant bonding, group interaction and teamwork, cultural norms, nursing process
Qualitative Data Analysis
- require what 2
- what is object of analysis
- what is the data
- analysis of what
- text can include? 5
- Requires creativity
- A considerable time commitment
Data itself is the object of analysis
Data is also a window through which to view the participants’ world (Denzin & Lincoln, 2000)
It is an analysis of qualitative text (mainly)
Text can include:
- Verbatim Transcripts (from audio-recorded interviews)
- Narratives or personal journals
- Documents
- Media (newspaper, blogs, websites)
- Field notes (observations, ideas etc)
Data Management
- What is fat data
- what can the computer software do
- data must be
Sheer volume of data collected with qualitative inquiry = “Fat data” (Glesne, 2011)
Use of computer software to organize and manage the data (does not perform the analysis, that is the task of the researcher)
E.g., QSR NVIVO 12
- Data must be kept secure to maintain confidentiality*
- Inscription to store data
Overview of Data Analysis
‘When?’ depends on the method 2
-researcher needs to identify what
-the goal is
- In some designs, data collection may be completed before analysis begins
- Others, occurs simultaneously (e.g., GT)
- The researcher needs to identify the process used*
- The goal is to make meaning out of massive amounts of text or data*
Qualitative analysis process
-3 paths
Starts with qualitative researcher
With -experiences, background, intent to engages in coding process by reviewing -data to -identify relevant info using specific coding methods -put them into containers called nodes -label the nodes to -Generate categories and themes -create models and illustrations to -representing the data -addressing the research questions ENDS
Uses -NVivo To analyze -data to -identify relevant info using specific coding methods -put them into containers called nodes -label the nodes to -Generate categories and themes -create models and illustrations to -representing the data -addressing the research questions ENDS
Gains credibility by -being transparent in the coding process to -demonstrating how he/she arrived at the Findings (to) -representing the data -addressing the research questions
Some common features among different approaches to qualitative data analysis: 4
- Affixing codes to a set of interview transcripts, field notes, or documents
- Sorting and sifting through coded materials to ID similar phrases, relationships, patterns, themes etc.
- Gradually elaborating on small set of generalizations that cover the consistencies noted in the data
- Confronting those generalizations with a formalized body of knowledge in the form of constructs or theories
Overview of Data Analysis
- researcher does what
- what are the three distinct stages of qual data analysis
Researcher immerses themselves in the data (reading and re-reading text)
Miles et al., (2014) outlines three distinct stages of qualitative data analysis:
- Data Reduction
- Data Display
- Conclusion drawing/ verification
Data Reduction
- what is coding
- what are themes
- what are thematic analysis
- what are codes
Coding- selecting, focusing, simplifying, abstracting, and transforming the data ->Themes/subthemes
Themes are structured meaning units of data that occur frequently in the text, further categorized via subthemes
Thematic analysis is the process of recognizing and recovering the emergent themes
Codes are simply tags or labels assigned to the themes identified
Data Display
- what is it
- form of what
E.g., MacDonald, Martin-Misener, Steenbeek et al. (2015) identified five themes and 13 subthemes to describe Mi’kmaq women’s experiences with Pap screenings
A visual format that presents information so that the user can draw conclusions take needed action
Form of figures, charts, graphs, matrices, other visual representation, even vignettes (changes throughout the analysis)
Conclusion Drawing/ Verification
- What is conclusion drawing
- what is verification (4 parts of it)
Conclusion drawing is essentially the description of the relationships between the themes
Verification- questioning one’s own conclusions, checking with past participants, verification by colleagues, finding new cases and applying the model to them
- Reflexivity (cause and effect) during interviewing and analysis
- Peer Debriefing
- Member checking
- Verbatim quotes
Quality & Credibility of Qualitative Research
- qual researchers do not reject what
- quality and credibility depends on? 3
Qualitative researchers do not reject rigour
Quality and credibility depends on:
- High-quality data
- Credibility of the researcher
- Philosophical belief in the value of qualitative inquiry
