Qualitative data collection, analysis, and interpretation Flashcards

1
Q

Qualitative data collection

data includes…

A

actions and words

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2
Q

Actions are collected by:

A

observation

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3
Q

Words collected through:

A
questionnaires
interviews
focus groups
case studies
documents
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4
Q

Observation:

A

 Most closely associated with field work
 Structure can vary from unstructured to highly structured
 Participant observation
 Recorded on observation sheets and notes

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5
Q

questionnaires:

A

 Not just demographics
 Not just one or two fill-in-the-blank questions
 Contains open ended questions

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6
Q

interviews:

A

 One-on-one
 Face-to-face or electronically
 Allows probing into answers
 Structured, semi-structured, or unstructured

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7
Q

Focus Groups

A

 Small groups of specially selected individuals(10 or so people)
 To explore attitudes, beliefs, opinions
 Run by a facilitator (Focused goals/objectives/questions, Ground rules)
 Members “bounce” ideas off each other or spark comments
 Observed by the researcher
 Recorded on tape to be transcribed
 Usually about 60-90 minutes with 10 or less questions

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8
Q

Case studies:

A

 Involves one interesting case
 Described from the perspective of the team involved with the case
 Looks at facts and processes
◦ Evolution of the situation / disease
◦ Evolution of needs over time
◦ Evolution of relationships
◦ Evolution of decisions
◦ Situational facilitators / barriers

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9
Q

Critiquing the Data Collection Phase in a qualitative article
Where?

A

◦ Where was the setting, why was it chosen, and when did data collection occur?

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10
Q

Critiquing the Data Collection Phase in a qualitative article
Who(interviewee)?

A

◦ Who did they interview, why were they chosen, and how were they chosen?

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11
Q

Critiquing the Data Collection Phase in a qualitative article
Who(interviewer)?

A

◦ Who were the data collectors, how were they trained, and what did they do?

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12
Q

Critiquing the Data Collection Phase in a qualitative article
What asked?

A

◦ What was asked and how was it recorded?

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13
Q

Critiquing the Data Collection Phase in a qualitative article
When?

A

◦ When did data collected begin and end and why was data collection stopped?

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14
Q

Critiquing the Data Collection Phase in a qualitative article
What biases?

A

◦ What were the biases of the researchers and data collectors and how did they prevent these biases from coloring their perceptions?

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15
Q

Purpose of qualitative analysis?

A

to generate knowledge from the data in order to:

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16
Q

Generate knowledge from the data in order to what?

A
◦	find order
◦	find structure
◦	derive meaning
     	Analysis 
     	Synthesize
◦	communication of findings
17
Q

Difficulties with analysis?

A

 No systematic method or formula for all types of studies
 Enormous amount of data
 Labor intensive
 Hard to keep main points clear
 tend to get lost in verbage…this is why more than one person is needed to analyze.

18
Q

Straight Description

A

derived from the literature

19
Q

analytic description

A

derived from the data

20
Q

Stages of Data Analysis

comprehending

A

what’s going on

21
Q

Stages of Data Analysis

synthesizing

A

sifting and sorting

22
Q

Stages of Data Analysis

theorizing

A

develop an explanation

23
Q

Stages of Data Analysis

recontextualizing

A

could this be appropriate in another setting?

24
Q

Analysis Styles

Quasi-statistical

A

 AKA Manifest content analysis
 Can convert some of the data to numbers.
 Predefine concepts from the literature
 Fit your data into these concepts
 Simple stats
 Important to find “negative cases” or when data shows disagreement

25
Analysis Styles | Template
```  Used in ethnography  Select the template based on words, actions, situations, etc  Code data into the template  Revise template as needed  Determine the resultant pattern ```
26
Analysis Styles | Editing
 Also called constant comparison method  Used in phenomenology and grounded theory  Sort data and identify meaningful segments  Code the data  Look for emerging themes and patterns  Determine structure of how themes and/or patterns relate  Compare with the literature
27
Analysis Styles | Immersion or Crystalization
 Used with case histories  Become totally immersed into the data.  Explore until main point crystallizes.
28
Analysis Styles | Triangulation
 Combined use of two or more theories, methods, data sources, investigators or analysis methods in the study of a single phenomena.  Must use a proper design from each tradition ◦ Descriptive correlational design with phenomenology added  Must all have the same foci.  Use two or more analysis techniques
29
General Procedures for Data Management | Comprehending
◦ Decide on method ◦ Read the data ◦ Re-read the data ◦ Get a “big picture” grasp of the ideas held in the data
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General procedures for data management | Synthesizing
◦ Be alert for themes ◦ Develop initial codes ◦ Code each unit of the data ◦ Reduce the data to manageable pieces
31
General Procedures for Data Management | Theorizing
◦ Identify themes, patterns, etc
32
General Procedures for data management | Recontextualizing
◦ put into a different context
33
Strategies for interpretation (there are lots and lots and lots...)
```  Note patterns/themes  Plausibility  Clustering  Making metaphors  Counting  Making contrasts/comparisions  Partitioning variables  Moving from particular to general  Factoring  Noting relationships  Finding intervening (extraneous) variables  Logical chain of evidence  Conceptual/theoretical coherence ```
34
Trustworthy interpretations | Credible
◦ Authentic and truthful account | ◦ Clean study design
35
Trustworthy interpretations | Confirmable
◦ Clear paper trail | ◦ Accurate process
36
Trustworthy interpretations | Dependable
◦ Consistent findings ◦ Sufficient findings ◦ Logical interpretation of findings
37
Trustworthy interpretations | Transferable
◦ Usefulness in another, similar setting
38
Have a good balance when critiquing...
should be objective, thoughtful, and balanced should be judicious and kind