Content/Thematic/Meta Analysis & Types of Data Flashcards

1
Q

What is the method for conducting content analysis?

A

1~ Secondary QUALITATIVE data collected - if audio recording, it’s TRANSCRIBED.

2~ Researcher reads through / examines S data and FAMILIARISES themselves with it.

3~ Coding units are created / refined - (give EXAMPLES, e.g. no. of times the word ‘woman’ appears)

4~ S data is ANALYSED and coding units are APPLIED.

5~ Frequency table is made from TALLYING or counting the no. of times a coding unit EMERGES / appears.

6~ Conclusions are DRAWN.
(refer to before & after change or how qualitative data is converted into quantitative)

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2
Q

What is the method for conducting thematic analysis?

A

1# Secondary qualitative data is collected OR audio recordings are transcribed.

2# Researcher reads / examines secondary data and becomes FAMILIAR with it.

3# Researcher identifies THEMES - GIVE EXAMPLES of themes.

4# S data analysed by applying themes.

5# Conclusions are DRAWN.

NO SUCH THING AS CODING UNITS - we refer to them as THEMES.

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3
Q

What are the key differences in content and thematic analysis?

A

Content =
Uses coding units
Data converted from qualitative to quantitative.

Thematic =
Uses themes
Data remains qualitative.

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4
Q

What is content analysis?

A

Observational technique studying people indirectly through studying qualitative data in the form of WRITTEN communications.

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5
Q

What are the strengths of using content analysis?

A

= Unethical & Impractical =
Can conduct research that’s unethical / practical in experiments - consent isn’t needed as it’s already published in articles - allows high quality data to be collected even in difficult scenarios.

= Quantitative data collected =
Easier to analyse - can draw firm, concrete & robust conclusions.

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6
Q

How is qualitative data converted into quantitative data in content analysis?

A

Using coding units and then tallying.

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7
Q

What is the success criteria for a 4/5 mark question on content/thematic analysis?

A

1 para

1# Logical > step by step (firstly…)
2# Tentative language (may)
3# Contextualise > refer directly / indirectly in EVERY sentence.
4# Draw conclusions > refer to before & after.

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8
Q

What are the weaknesses of content analysis?

A

= Lacks reliability =
If 1 person analyses - investigator bias threatens reliability & coding units not fully operationalised - interpret data subjectively - need more than 1 person to verify.

= Time consuming =

= Lacks rich detail =
Lacks detail of human experience - no explanations - just identifies trends / patterns.

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9
Q

Suggest a way a researcher can use to improve the validity of content analysis.

A

> Operationalise coding units clearly.

> Double-blind > employ someone who doesn’t know aims - avoids investigator bias.

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10
Q

What are 2 ways of assessing reliability?

A

Test-retest

Inter-rater reliability (DON’T FORGET)

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11
Q

Suggest a way the researcher can use to improve the reliability of content analysis.

A

> Have more than 1 researcher to verify the data - increase inter-rater reliability - can do training beforehand.

> Operationalise coding units.

> Standardisation - same coding units and researcher.

> Use multiple sources of evidence.

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12
Q

What is thematic analysis?

A

Observational technique studying people indirectly through studying qualitative data in the form of WRITTEN communications.

Thematic identify THEMES / patterns in data.

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13
Q

What are the strengths of both content and thematic analysis?

A

= High ecological validity =
Data are observations from real-life behaviour, written & visual communications - shows natural behaviour - can be generalised.

= Can be replicated easily =
Since data/sources remains - replication can be conducted analysing similar scripts.

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14
Q

What is meta analysis?

A

Reviewing existing research on a particular topic.

Uses secondary data.

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15
Q

What are the strengths of meta analysis?

A

= Trends / patterns =
Can observe general trends/patterns in existing literature.

= Large sample =
Analysis uses many studies - conclusions drawn from larger sample - increases statistical power- can be generalised - increases population validity.

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16
Q

What are the weaknesses of meta analysis?

A

= File-draw phenomenon =
Significant research is more likely to be published than non-significant
(so research that rejects the null is published)

= Bias =
res may choose to omit certain findings from their analysis that don’t show significant results - conclusions biased bc isn’t representative of all relevant data in topic.

= Lacks temporal validity =
General trends / patterns may not be generalised to different time intervals.

= Quality of data/research =
Depends on quality of research - no way of knowing.

17
Q

What is quantitative data?

A

Numerical data that can be statistically analysed and converted into graphs.

18
Q

What methods can produce quantitative data?

A

Experiments
Structured observations
Correlations
Closed/rating scale questions (questionnaires)

19
Q

What is qualitative data?

A

Non-numerical, descriptive data collected that provides insight into human behaviours / experiences / opinions.

20
Q

What methods can produce qualitative data?

A

Unstructured / semi-structured interviews
Open questions (questionnaires)

21
Q

What are the strengths of quantitative data?

A

= Easier to analyse =
Easier to conduct statistical/inferential test of significance with numerical data - can be converted into graphs - can draw clear conclusions and establish cause & effect.

22
Q

What are the weaknesses of quantitative data?

A

= Lacks rich detail =
Complex human behaviour is simplified - lacks meaning & context - not representative of real life - lacks ecological validity.

23
Q

What are the strengths of qualitative data?

A

= Rich detail =
Rich detailed insight obtained - pps can develop their responses freely - more detail and meaningful insights to human behaviour - increases ecological validity.

24
Q

What are the weaknesses of qualitative data?

A

= Researcher bias =
May be subjective - researcher may interpret/judge the rich detail differently or in their favour - conclusions may be affected by bias - reduces internal validity.

25
Q

What is primary data? Give examples.

A

Data collected first-hand for a specific reason by the original researcher.

(E.G. sending pps questionnaire/interviews)

26
Q

What is secondary data? Give examples.

A

Data