Conduct a thematic analysis using qualitative data to address research questions.

Introduction
This assessment has three parts:
A&B: Analyse data in JASP and report the results to address research questions.
C: Conduct a thematic analysis using qualitative data to address research questions.
PART A & B: Quantitative Data Analysis – Comparing groups
Assessment 3A and 3B consist of short-answer questions that are listed in the section below
labelled Directions.
Part A – Misinformation data analysis
Imagine you are working as a researcher at a public health organisation. Concerned about
the spread of misinformation around topics such as vaccine risks, you want to know whether
people are misled when sources of information have “false consensus”. Data has already
been collected, and your job is to begin to analyse the data and report the results.
Part B – Therapies data analysis
Another research project is investigating the effectiveness of a new Exposure-Based Cognitive
Therapy as treatment for depression. Again, your job is to begin to analyse the data and
report the results.
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PART C – Qualitative Data Analysis
Exploring the concept of well-being for drama students and their lecturer
A final research project focuses on interviews with drama students and their lecturer. These
participants were asked about how they understood the concept of well-being in the context
of their drama education and the development of their acting skills. Your job is to conduct a
qualitative analysis of interview data and report your findings.
Purpose
The purpose of this assessment is to demonstrate that you can apply knowledge and skills
from Modules 4 to 6 to address research questions.
Learning Outcomes
This assessment maps to the following course learning outcomes:
• Synthesise quantitative evidence to address psychological research questions and
hypotheses.
• Use statistical software to explore and analyse basic types of quantitative data.
• Apply basic methods of conducting qualitative research in psychology.
• Communicate research findings in a style that is suitable for technical reports.
Grading Criteria
This assessment is worth 40% of your overall grade.
The marks assigned to each question are indicated in square brackets in the instructions for
Parts A, B and C below. Total marks = 40.
For Parts A and B, you will be graded in the MyUni Quiz as per the quiz marking guidelines
provided for this assessment. Part C will be marked as per the assessment rubric provided
for this assessment.
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Resources
Learning materials from Module 4, 5 and 6 will help prepare you for this task. Part A and B
correspond to materials from Modules 4 and 5, and Part C corresponds to materials from
Module 6.
We recommend that you work on the relevant sections of the assessment during the
week of each module.
Requirements
PART A & B: Quantitative Data Analysis – Comparing groups
You must submit your answers to the questions for Parts A and B in the assessment portals
in MyUni. There is a separate portal for Part A and for Part B. There will be a separate textbox
for each question. You should prepare your answers as text in a separate document and
then paste them into the textboxes on MyUni, so that you have easy access to a copy of your
answers.
There is no word limit, but we are interested in quality, not quantity. Do not write for the sake
of writing. Simply write as much as you think is necessary to convince your marker that you
know what you are talking about, referring to the relevant principles or concepts to which you
have been introduced.
Each question will indicate the expected length of your response. As a guide, consider the
examples from the exercises that you have completed during the course modules. You
should refer to the marking guidelines for detailed information about how this part of the
assessment task will be graded. Your tutor will be marking according to this marking
guideline when reviewing your answers in MyUni, so you should review and consider this
before starting this part of the assessment.
PART C: Qualitative Data Analysis
You must submit your thematic analysis online via MyUni as a text document (doc, docx, pdf).
Format your analysis using either Arial, Calibri or Times New Roman, Size 11 or 12 font. You
should refer to the assessment rubric for detailed information about the grading criteria for
this part of the assessment task. Your tutor will be marking according to this rubric, so you
should review and consider this before starting this part of the assessment.
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PART A & B DIRECTIONS: Quantitative Data Analysis [25 marks
total]
Part A – Misinformation data analysis [12 marks]
Analyse data in JASP and report the results from a study that investigated whether people are
misled when sources of information have “false consensus”. You will need to answer the
questions below.
The experiment
The data you will analyse are based on an experiment by Yousif, Aboody, and Keil (2019). The
researchers investigated one factor that could contribute to the spread of misinformation:
whether people are sensitive to important cues to the degree of consensus—general
agreement about a conclusion—when assessing a set of arguments on a specific topic. In
particular, Yousif et al. (2019) tested whether people are more convinced by a conclusion that
has “true consensus” (the conclusion of each argument is based on independent primary
sources) than when it has “false consensus” (the conclusion of each argument is actually
based on only one primary source).
In the experiment, participants were presented with fictional news articles about the
Japanese economy and were asked to rate their confidence in the conclusion that “Japan’s
economy will continue to improve”. Across three conditions, Yousif et al. (2019) manipulated
the sources that were cited in the news articles. Participants were randomly allocated to each
condition in a between-participants design.
The three conditions were:
• True-consensus condition, in which there were four positive news articles (supporting
the conclusion) and one negative article (rejecting the conclusion), all citing different
primary sources.
• False-consensus condition, in which there were four positive news articles and one
negative article, but the positive articles all citied the same primary source. The negative
article cited a different source.
• No-consensus condition, in which there was only one positive and one negative news
article, each citing a different primary source.
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Yousif et al. (2019) expected that confidence ratings would be higher for the true-consensus
condition than for the no-consensus condition, but the key question was what would happen
in the false-consensus condition. If people care only about the number of primary sources,
then confidence in the false-consensus condition should match that of the no-consensus
condition—there are two primary sources in each condition (one positive and one negative).
However, if instead people focus on just the number of secondary sources, then confidence in
the false-consensus condition should match that of the true-consensus condition—both have
four positive news articles and one negative article.
To check that participants read the news articles properly and attended to the citations in the
first place, at the end of the experiment participants were shown a list of 10 sources and
were asked to indicate which had been cited in the articles.
Reference:
Yousif, S. R., Aboody, R., & Keil, F. C. (2019). The illusion of consensus: a failure to distinguish
between true and false consensus. Psychological Science, 30(8), 1195–1204.
The data
To analyse the (partly fictitious) data, you will need to:
1. Download the Assessment3A.csv dataset from the Assessment 3A page.
2. Open the dataset in JASP.
The variables in the dataset are as follows:
• ParticipantID: Participant ID number.
• Condition: True = True-consensus, False = false-consensus, No = no-consensus
• SourceAccuracy: The participant’s accuracy (% correct) at identifying which sources
had been cited in the articles.
• Confidence: Rating of agreement in the conclusion about Japan’s economy, from 0
(strongly disagree) to 100 (strongly agree).
For the purposes of this assessment, you will perform one assumption check as instructed
below. You can otherwise assume that the assumptions for all statistical tests are met.
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Questions
1. First, as a preliminary analysis you need to check that at the end of the experiment,
participants identified the correct primary sources that had been cited in the articles
(i.e., they read the articles properly and remembered the citations).
Focus on the critical False-consensus condition (i.e., for this question, you need to
select only the people in this group for analysis). For this group, perform the
appropriate statistical test to confirm that mean source-accuracy was significantly
different to the chance level of 50% correct.
In two or three sentences, report the mean and standard deviation for sourceaccuracy,
and the results of the test (in APA style), including a stat block and Cohen’s d.
[2]
2. Now turn to the primary dependent variable of participants’ confidence in the
conclusion about Japan’s economy. Perform the appropriate statistical test to see if
there is a statistically significant difference in mean confidence ratings between the
three consensus conditions. Compare all three groups in a single test.
As the first part of this procedure, check the homogeneity of variance
assumption of the test. Run a Levene test, then report and interpret the results in one
sentence (in APA style), including a stat block. (But for the remaining questions in this
assignment, don’t worry if the assumption is violated.) [1].
3. Next, present a graph with a 95% confidence interval for the mean confidence rating of
each group. Give the figure an appropriate brief caption above the figure, beginning
with a label of “Figure 1”. [2]
4. Next, report the results of the key statistical test (comparing the three group means) in
one or two sentences, including a stat block, in APA style. (You don’t need to include
descriptive statistics or effect sizes here.) [2]
5. What is the overall effect size for the above test, and how do you interpret it (one
sentence)? [1]
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6. Now consider an appropriate kind of follow-up test (i.e., that adjusts for multiple
comparisons using the Holm correction) to compare mean confidence ratings in each
pair of conditions: true-consensus vs. no-consensus, true-consensus vs. falseconsensus,
and false-consensus vs. no-consensus.
Report the results of each test in one or two sentences, including the p-value for each
comparison. You don’t need to include descriptive statistics or effect sizes here: pvalues
and their interpretation are sufficient. You may wish to refer to Figure
1 above when discussing which group is higher/lower. [3]
7. What conclusion do you draw from your results for questions 3–6 above and why? That
is, do people seem to care about the number of primary sources that support a
conclusion, or just the number of secondary sources? Around two or three
sentences. [1]
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Part B – Therapies data analysis [13 marks]
Analyse data in JASP and report the results from a study that investigated the effectiveness of
a new Exposure-Based Cognitive Therapy as treatment for depression. You will need to
answer the questions below.
The experiment
The data you will analyse are based loosely on research by Grosse Holtforth et al. (2019) on
psychotherapy techniques for depression. The researchers tested whether a new ExposureBased
Cognitive Therapy (EBCT) would enhance treatment gains compared to standard
cognitive-behavioural therapy (CBT). Grosse Holtforth et al. (2019) performed a randomisedcontrolled
trial with adults experiencing Major Depressive Disorder—participants were
randomly assigned to receive either CBT or EBCT.
Participants’ level of depression was assessed using various tests at pre-treatment, posttreatment,
and at a 12-month follow-up stage. You will consider two different depression
measures as dependent variables—scores from the Beck Depression Inventory-II (BDI-II), and
scores from the WHO-Five Well-Being Index (WHO-5).
Note that a mixed experiment design was used, with treatment type as a betweenparticipants
factor, and the three depression-assessment timepoints (pre-treatment, posttreatment
and follow-up) as a within-participants factor. In real life, all six conditions would
be compared in more complex factorial analyses, but you will use the tests from this course
to separately consider different aspects of the data.
Reference: Grosse Holtforth, M., Krieger, T., Zimmermann, J., Altenstein-Yamanaka, D., Dörig,
N., Meisch, L., & Hayes, A. M. (2019). A randomized-controlled trial of cognitive-behavioral
therapy for depression with integrated techniques from emotion-focused and exposure
therapies. Psychotherapy Research, 29(1), 30-44.
The data
To analyse the (fictitious) data you will need to:
1. Download the Assessment3B.csv dataset from the Assessment 3B page.
2. Open the dataset in JASP.
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The variables in the dataset are as follows:
• ParticipantID: Participant ID number.
• Condition: CBT vs. EBCT treatment
• DepressionPre: Baseline score on the BDI-II, prior to any treatment. Higher scores
indicate more severe depression.
• DepressionPost: Score on the BDI-II at the end of treatment.
• Depression12: Score on the BDI-II, 12 months later.
• WellbeingPre: Baseline wellbeing score on the WHO-5. Note that higher scores
indicate reduced depression.
• WellbeingPost: WHO-5 score after treatment.
For the purposes of this assignment, you will perform one assumption check as instructed
below. You can otherwise assume that the assumptions for all statistical tests are met.
Questions
1. First, consider depression levels as measured by the WHO-5. Focusing only on the
EBCT group for this question (i.e., you need to select only the people in this group for
analysis), perform the appropriate statistical test to see if there is a significant
difference in the WHO-5 score, before versus after treatment. Did depression decrease
(i.e., wellbeing increase) after treatment?
In around two sentences, report the mean difference in WHO-5 score between before
versus after treatment (including whether there was an increase/decrease), and the
results of the test (in APA style), including a stat block and effect size. [2]
2. Now turn to depression levels as measured by the BDI-II. Focusing only on the EBCT
group (i.e., you need to select only the people in this group for analysis), perform the
appropriate statistical test to see if there is a significant difference in BDI-II score
between assessments at pre-treatment, post-treatment, and 12 months
later. Compare all three conditions in a single test.
As the first part of this procedure, check the sphericity assumption for this test. Run
a Mauchly test, then report and interpret the results in one sentence (in APA style),
including the p-value (no other statistics are required). (For the remaining questions in
this assignment, don’t worry if the assumption is violated.) [1]
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3. Next, present a graph with a 95% confidence interval for the mean BDI-II score of
each timepoint condition, for the EBCT group. Give the figure an appropriate brief
caption above the figure, beginning with a label of “Figure 2”. [2]
4. Next, report the results of the key statistical test (comparing the three timepointcondition
means for the EBCT group) in one or two sentences, including a stat
block and the overall effect size, in APA style. (You don’t need to include descriptive
statistics or pairwise effect sizes). [2]
5. Now consider an appropriate follow-up test for the EBCT group (i.e., that adjusts for
multiple comparisons using the Holm correction) to compare mean BDI-II scores for
pre-treatment vs. post-treatment, post-treatment vs. 12 months later, and pretreatment
vs. 12 months later.
Report the results in two or three sentences, including the p-value for each
comparison. You don’t need to include descriptive statistics or effect sizes here: pvalues
and their interpretation are sufficient. You may wish to refer to Figure 2 above
when discussing which condition is higher/lower. [2]
6. Lastly, perform a new test to compare the post-treatment BDI-II scores of
the EBCT group against the CBT control group. You can assume the two groups
had similar scores at the pre-treatment stage; however, is there a significant difference
in BDI-II score at the post-treatment stage?
In around two sentences, report the mean difference in BDI-II
score between the groups (noting which group is higher/lower), and the results of the
test (in APA style), including a stat block and effect size. [2]
7. What conclusion do you draw from your results for questions 3–6 above (around three
sentences):
a. Considering the results for the EBCT group, has the therapy led to lower
depression levels both post-treatment and 12 months later?
b. Was EBCT more effective than the standard CBT? [2]
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PART C DIRECTIONS: Qualitative Data Analysis [15 marks]
Exploring the concept of well-being for drama students and their lecturer
Perform a thematic analysis of interview data, and report your findings, as instructed below.
Your participants are two drama students and their lecturer. Your research question is:
How do drama students and their lecturer define well-being?
The data
Download the Assessment3C.docx dataset from the Assessment 3C page.
These data come from interviews with drama students and their lecturer. These participants
were asked about how they understood the concept of well-being in the context of their
drama education and the development of their acting skills.
Instructions
Using the technique outlined by Braun and Clarke (2006), conduct a thematic analysis data
provided.
Braun and Clarke (2006) describe six steps in thematic analysis. You are required to complete
the first five steps:
1. Familiarising yourself with the data
2. Generating initial codes
3. Searching for themes
4. Reviewing themes
5. Defining and naming themes
(NOTE: you are not required to complete Step 6—producing a report).
You do not need to report these steps. You are only required to produce an analysis.
Use the research question above to guide your analysis. This means that your coding and
analysis will need to focus on how the drama students and their lecturer define well-being.
Write 750 words (+/- 10%). You must provide a general overview of your themes, followed by
a more detailed analysis of each theme with example quote from the data. As a guide, it is
recommended you produce and report on three to five discrete themes. Refer to the
assessment rubric for detailed information about the grading criteria for this assessment.
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Your analysis should aim to describe and interpret the themes you develop. You should
attempt to link the themes in some way in your analysis, and your summary should tie your
themes together into an overarching narrative that helps provide an answer to your research
question. You must not infer meaning from the data, but you should attempt to interpret and
‘make sense’ of the data in the context of the research question. You should also identify [ID]
the participant in your example quotes (e.g., Student k, Student J, Lecturer M).