HBS 108 ABTC Interpreting and Evaluating Health Evidence Project

HBS108 Assignment Task 2Interpreting and Evaluating Health Evidence
1,200 words, 30% of total assessment
Due Sunday 12 September 2021 by 8.00 PM (AEST)
This assignment draws on Topics 4, 5, 6 and 7. It requires you to access, understand, interpret, and
report on findings from qualitative and quantitative research studies that explore the health of
Aboriginal and Torres Strait Islander Australians with a particular focus on access to health care and
health literacy.
You are required to access and read the following resources and answer questions based on their
content:
Canuto, K., Wittert, G., Harfield, S., Brown, A (2018). “I feel more comfortable speaking to
a male”: Aboriginal and Torres Strait Islander men’s discourse on utilizing primary health
care services. International Journal for Equity in Health, 17(185).
https://doi.org/10.1186/s12939-018-0902-1
Ju, X., Brennan, D., Parker, E., Mills, H., Kapellas, K., & Jamieson, L. (2017). Efficacy of an
oral health literacy intervention among Indigenous Australian adults. Community Dentistry
and Oral Epidemiology, 45(5). 413–426.
Lakhan, P., Askew, D., Harris, M. F., Kirk, C., Hayman, N. (2017). Understanding health talk
in an urban Aboriginal and Torres Strait Islander primary healthcare service: a crosssectional study. Australian Journal of Primary Health, 23(4). 335–341.
Topics 4, 5, 6 and 7 (and especially the online tutorial activities and sessions associated with each
topic) will provide you with the knowledge and skills you need to successfully complete this
assignment.
Important Note
The marks allocated for each question do not necessarily reflect the number of words required to
answer the question. For example, some questions worth 2 or 3 marks can be answered in a few
words, though others might require one or two sentences. If you are struggling to stay within the
word count it is recommended that, if it is possible to answer a question in a few words, you do so in
order to save words for those questions that require more text to answer. For brief answers, the
following format is acceptable: Q. 5 (i): Random sampling.
HBS108 Assignment Task II 202102
Page 1 of 4
Task A—Interpreting study design and approach
Using the skills you developed in Topic 2, locate the journal article by Canuto et al. (2018). Read the
article carefully before answering Questions 1 (i)–(iv).
Question 1
(i)
What was the aim of the study?
(4 marks)
(ii)
What type of sampling was used during data collection? Why is this used in research?
(Please use supporting evidence to justify your response here, e.g., unit material or external
literature)
(6 marks)
(iii)
How was the data analysed? Explain the data analysis process.
(iv)
What is a potential limitation of this research? Why is this potentially problematic? (Please
use supporting evidence to justify your response here using external literature)
(4 marks)
(6 marks)
Task B—Identifying study methods and results A
Using the skills you developed in Topic 2, locate the journal article by Lakhan et al. (2017). Read the
article carefully before answering Questions 2 (i)–(v).
Question 2
(i)
Identify and explain the study design used in this piece of research. In your response you
must identify whether primary or secondary data was used.
(4 marks)
(ii)
What are variables? What variables were assessed in the current study?
(iii)
What was the data collection method used in this study? What are potential limitations of
this approach (in general)?
(8 marks)
(iv)
From the results presented in Table 3, please explain the association between age,
education, and gender in overall health literacy of the sample. What do these findings
suggest about the health literacy of the population?
(4 marks)
HBS108 Assignment Task II 202102
(4 marks)
Page 2 of 4
Task C—Identifying study methods and results B
Using the skills you developed in Topic 2, locate the journal article by Ju et al. (2017). Read the
article carefully before answering Questions 3 (i)–(iv).
Question 3
(i)
Where does a randomised control trial fit in the hierarchy of evidence? Please mention the
key relevant concept/s.
(6 marks)
(ii)
Please comment on the external validity of this study of Aboriginal and Torres Strait Islander
Australians? How could the sampling frame be changed to increase external validity?
(4 marks)
(iii)
How was risk ratio used in this study? What does the risk ratio demonstrate about the study
findings? (Please use supporting evidence to justify your response here)
(8 marks)
(iv)
Observe the data in Table 4 ‘Changes in oral health knowledge under the different
scenarios’. Which scale of measurement (nominal, ordinal, interval, ratio) was used to
present the data?
(2 marks)
Task D: Conclusion—Synthesising results and exploring the literature
In this section, you will need to attempt to synthesise the findings from the three studies.
These studies have explored the health of Aboriginal and Torres Strait Islander Australians with a
particular focus on access to health care and health literacy. As a research fellow for the Department
of Health and Human Services, you have been asked to report on the evidence drawing on the three
studies available to you.
Question 4
(i)
Please provide a summary of the evidence regarding the factors impacting on Aboriginal and
Torres Strait Islander Australians’ access to health care. In your response you should identify
the key findings from each of the three studies.
(10 marks)
(ii)
Given your understanding of study designs, design a study (qualitative or quantitative) that
further investigates the factors that contribute to Aboriginal and Torres Strait Islanders’
health outcomes. You must:
(10 marks)
a. Identify the study design
b. List the research question
c. Explain the chosen sampling method
d. Outline the data collection methods
e. Identify relevant data analyses
Note: 20 marks will be awarded for writing, grammar, presentation and referencing
HBS108 Assignment Task II 202102
Page 3 of 4
How to structure your assignment
This assignment should take the form of a structured report (i.e., a question/answer format) rather
than an “essay” and should be approached with a formal scientific writing style (i.e., full sentence
structure). Please note you are not expected to re-write the questions in your assignment as this
would be an unwise use of your word count. Please use appropriate section and question numbers
to label your answers clearly.
Assignment Title – Top of the first page (please do not submit a cover sheet)
Student name & ID – Either as a footer OR under the assignment title
COMPULSORY: Label all responses to questions with the appropriate question number
Font – 12 point, Times New Roman
Line Spacing – 2
Margins – Normal
Borders – None
Use of references
Include all references cited in your assignment (including those that you are instructed to locate and
use) in a reference list at the end of the assignment, using the Deakin-Harvard (i.e., author-date)
referencing style. If you refer to any additional data not included in these sources, you must
reference these additional sources of data too. Remember that, as covered in Topic 2, references are
not restricted to academic journals, and can include books and reports from reputable websites.
Information about the Deakin-Harvard referencing style is available here:
https://www.deakin.edu.au/students/studying/study-support/referencing/harvard
Word limit
The word limit for the assignment is 1,200 words (excluding the reference list and pasted abstract
but including in-text citations and headings). You are permitted a 10% margin over and under the
word limit, but words over 1,320 will not be assessed. This is done to ensure equity among
students—it is unfair if students who exceed the word limit get higher grades (due to including extra
material over the word count) than students who comply with the limit. Given the tight word count,
be concise. Do not repeat the questions in your assignment—the words will be included in your
word count.
Using the TurnItIn Originality check and Assignment Submission
Before submitting your assignment you should check the originality of your work (excluding the
abstracts as these will impact on your TurnItIn score) by using TurnItIn. In Week 4 there was a
PowerPoint presentation shown during your HBS108 lecture that covered this process. You should
ensure that your answers to the assignment questions are written in your own words. It is NOT
acceptable in this assignment to answer questions using ‘blocks’ of text taken from the references
provided (though the occasional word or technical term is acceptable). Your lecturer will also show
you how to submit your assignment online via Moodle.
HBS108 Assignment Task II 202102
Page 4 of 4
HBS108 AT2—Grading Form
Criteria
Exemplary
Accomplished
Competent
Developing
Beginning
Task 1
16–20 marks
14–15.5 marks
12–13.5 marks
10–11.5 marks
0–9.5 marks
Interpreting study
design and approach
20 marks
Correctly identifies the study
aim and sampling with
appropriate explanation, data
analysis appropriately
described with the limitations of
the research discussed using
relevant supporting evidence.
Correctly identifies the study
aim and sampling with
explanation, data analysis
described with the limitations of
the research discussed. Some
responses could include more
detail.
Correctly identifies the study
aim AND/OR sampling with
explanation AND/OR data
analysis described AND/OR the
limitations of the research
discussed.
Response is developing with
one (1) or more aspect of the
task missing or lacking
appropriate detail.
Response does not address
each aspect of the task with
two (2) or more responses
missing or lacking appropriate
detail.
Task 2
16–20 marks
14–15.5 marks
12–13.5 marks
10–11.5 marks
0–9.5 marks
Identifying study
methods and results A
Correctly identifies and explains
the study design, variables and
identifies variables assessed in
the current study. Data
collection method identified and
study findings discussed.
Correctly identifies and explains
the study design, variables and
identifies variables assessed in
the current study. Data
collection method identified,
and study findings discussed.
Some responses could include
more detail.
Correctly identifies AND/OR
explains the study design
AND/OR variables and
identifies variables assessed in
the current study. Data
collection method identified
AND/OR study findings
discussed.
Response is developing with
one (1) or more aspect of the
task missing or lacking
appropriate detail.
Response does not address
each aspect of the task with
two (2) or more question
missing or lacking appropriate
detail.
Task 3
16–20 marks
14–15.5 marks
12–13.5 marks
10–11.5 marks
0–9.5 marks
Identifying study
methods and results B
Correctly identifies where study
fits on the hierarchy of evidence
and comments on external
validity. Risk ratio discussed
and correct scale of
measurement identified.
Correctly identifies where study
fits on the hierarchy of evidence
and comments on external
validity. Risk ratio discussed
and correct scale of
measurement identified. Some
responses could include more
detail.
Correctly identifies where study
fits on the hierarchy of evidence
AND/OR comments on external
validity. Risk ratio discussed
AND/OR correct scale of
measurement identified.
Responses lacking detail
throughout.
Response is developing with
one (1) or more aspect of the
task missing or lacking
appropriate detail.
Response does not address
each aspect of the task with
two (2) or more question
missing or lacking appropriate
detail.
20 marks
20 marks
HBS108 Assignment Task II Rubric
Page 1 of 3
Criteria
Exemplary
Accomplished
Competent
Developing
Beginning
Task 4
16–20 marks
14–15.5 marks
12–13.5 marks
10–11.5 marks
0–9.5 marks
Conclusion—
Synthesising results
and exploring the
literature
Provides a detailed summary of
the evidence including all three
(3) studies. Designs a relevant
study AND outlines all five (5)
aspects study.
Provides a detailed summary of
the evidence including some of
the studies AND designs a
relevant study and outlines
some aspects study.
Provides a summary of the
evidence including some of the
studies AND designs a relevant
study and outlines some
aspects study.
Response is developing with
one (1) or more aspect of the
task missing or lacking
appropriate detail.
Response does not address
each aspect of the task with
two (2) or more question
missing or lacking appropriate
detail.
8–10 marks
7–7.5 marks
6–6.5 marks
5–5.5 marks
0–4.5 marks
Excellent standard of
presentation; no mistakes in
spelling, punctuation or
grammar; language clearly and
effectively communicates ideas.
As described under ‘Exemplary’
but some occasional, minor
errors or unclear points at
times.
Generally a good standard of
presentation; May include some
errors or communication faults
which leads to lack of clarity in
parts; OR May not meet some
of the presentation
requirements (spacing, font,
page numbers and word count).
As described under
‘Competent’ but
communication may be poor,
leading to lack of clarity; OR
May fail to meet presentation
requirements.
Work contains frequent, serious
errors in spelling, punctuation
and grammar. Presentation
requirements not met.
8–10 marks
7–7.5 marks
6–6.5 marks
5–5.5 marks
0–4.5 marks
Excellent referencing with no
mistakes in the reference list or
in-text citations and consistency
throughout.
As described under ‘Exemplary’
but with minor referencing
errors in text OR in the final
referencing list OR lack of
consistency.
Generally good referencing with
some errors in the reference
list, in-text citations AND/OR
lacking consistency.
As described under
‘Competent’ but with multiple
errors throughout.
Substantial problems with
referencing throughout. Refer
to the Deakin referencing
guides for further assistance:
20 marks
Written clarity &
presentation
Assignment is well
formatted, careful proof
reading and academic
language is used
throughout
10 marks
Referencing (DeakinHarvard)
In-text citations and a
reference list are
required. All sources
appropriately referenced.
Material can include the
unit content, journal
articles, textbooks,
reputable websites
http://www.deakin.edu.au/stude
nts/studysupport/referencing/harvard
10 marks
HBS108 Assignment Task II Rubric
Page 2 of 3
Additional marker comments: This rubric does not include a complete breakdown of marks within each question as it is difficult to do this for some
questions, particularly those worth 2–4 marks. Admittedly, there are some questions which are requiring a simple response that can be marked in
whole digits, while others will require responses that can be graded on a more scaled criterion. Regardless, the questions are very specific about
what is required in the answer, so make sure you include all the information asked for in the question.
HBS108 Assignment Task II Rubric
Page 3 of 3
25 June 2021
Class schedule and exam revision
Topic 1—Introduction to research
Health Information and
Data (HBS108)
Topic 2—Searching for and evaluating online health information
WEEK 7:
Topic 6—Sampling, data collection & measurement
Topic 3—Evaluating online health information and data
Topic 4—Qualitative research
Topic 5—Introduction to quantitative research
ANALYSIS AND INTERPRETATION IN QUANTITATIVE RESEARCH
[PART I]
1
2
Class schedule and exam revision
Outline for today
▪ Lecture
▪ Descriptive Statistics
▪ Measures of Association
Topic 7 (Part 1)—Analysis and interpretation in quantitative research
Topic 7 (Part 2)—Analysis and interpretation in quantitative research
Revision of Topics 1–7
▪ Seminar
▪ Individual Activity I
▪ Individual Activity II
Topic 8—Measuring health and disease in populations
Topic 9—Evidence based professional practice
Exam Revision
3
4
Topic 7 [Part I]—Learning objectives
By the end of Topic 7 [Part I], you should be able to:
▪ Explain how quantitative data are summarised, analysed and presented using some
basic forms of descriptive and inferential statistics
▪ Interpret methods used to summarise and present data in the form of descriptive
statistics, including:
▪ Commonly encountered frequency distributions, including normal and skewed
▪ Measures of central tendency (mean, median and mode)
▪ Measures of dispersion (range, percentiles, interquartile range [IQR] and standard
deviation [SD])
Descriptive Statistics
▪ Interpret some commonly used measures of association used in inferential
statistics, including:
▪ Relative risk (RR)
▪ Odds ratio (OR)
HBS108 TOPIC 7.1
5
HBS108 Week 07 Lecture Notes
6
1
25 June 2021
Topic 7 [Part II]—Learning objectives
By the end of Topic 7 [Part II], you should be able to:
▪ Interpret some commonly used measures of association used in inferential
statistics, including:
▪ Correlation coefficient (r)
▪ Chi-square (χ2)
▪ Apply the rationale and logic of statistical significance and hypothesis testing
through the use of:
▪ Confidence intervals (CI)
▪ p-values
▪ Apply the rules of generalisability and causality that underpin the interpretation of
results from quantitative research studies
▪ Outline the strengths of mixed methods in health research
Image credit: Wikimedia Commons
7
8
Application of descriptive statistics

Home

9
10
Descriptive statistics
Examples of graphs and tables
that describe data
Mark
Frequency
Percent
90-99
0
0
80-89
2
4
70-79
6
12
60-69
9
18
50-59
12
24
40-49
10
20
30-39
7
14
20-29
3
6
10-19
2
2
0-9
0
0
Total
50
100
▪ Average
▪ Sensitive to extreme values
Mode
Frequency Polygon
14
14
▪ Value that occurs the most often
12
12
▪ Not sensitive to extreme values
10
10
Frequency
Frequency
Frequency Histogram
Measures of central tendency
Mean
8
6
4
2
2
0
0
10-19
20-29
30-39
40-49
50-59
60-69
70-79
80-89
▪ The middle value in a list ranked from highest to lowest
6
4
0-9
Median
8
90-99
Marks
11
HBS108 Week 07 Lecture Notes
▪ Not sensitive to extreme values
0-9
10-19
20-29
30-39
40-49
50-59
60-69
70-79
80-89
90-99
Marks
12
2
25 June 2021
Measures of dispersion
Range
▪ Difference between the highest and the lowest values
Percentile rank
▪ The percentage of scores that are equal to or lower than a particular score
Inter-quartile range (IQR)
▪ Difference between the first quartile and the third quartile
▪ Companion to the median
▪ Middle 50% of observations
Standard deviation (SD)
▪ Indicates the amount that each observation differs from the mean
▪ Companion to the mean
13
Distributions
Negative (left) skew
Positive (right) skew
14
Activity 1
Measures of association
INDIVIDUAL ACTIVITY
HBS108 TOPIC 7.2
15
16
Measures of association
Relative risk or risk ratio (RR)
▪ Next step after descriptive statistics
▪ Used to determine the strength of relationships between exposures and
outcomes
▪ Do not ‘prove’ cause and effect or explain why an association exists
Four measures covered in this unit:
▪ This week:
▪ Relative Risk or Risk Ratio (RR)
▪ Odds Ratio (OR)
▪ Next week:
▪ Correlation Coefficient (r)
▪ Chi-square (χ2)
▪ Measures associations between exposures and outcomes
▪ Derived from data based on RCTs and cohort studies
▪ Estimates the risk of getting the outcome in the exposed group vs. not
exposed
▪ There is an RR value for each possible relationship
No association
1
0
Protective
17
HBS108 Week 07 Lecture Notes
2
3
4
Increased risk
18
3
25 June 2021
Relative risk or risk ratio (RR)
Odds ratio (OR)
▪ RR ranges from zero to infinity [rarely more than 5]
▪ Measures associations between outcomes and exposures
▪ RR = 1 indicates no association
▪ Used ONLY for case-control studies
▪ RR < 1 means a decreased risk [or exposure protects from outcome] ▪ Estimates the odds of past exposure in cases vs. controls ▪ RR > 1 means that exposure is linked to an increased risk of the
outcome
▪ There is an OR value for each possible relationship
No association
1
0
No association
2
Protective
3
4
1
0
Increased risk
Decreased odds
19
2
3
4
Increased odds
20
Odds ratio (OR)
▪ OR ranges from zero to infinity [rarely more than 5]
▪ OR = 1 indicates no association
▪ OR < 1 means decreased odds, or less likely to have been exposed in the past Activity 2 ▪ OR > 1 means increased odds of having been exposed in the past
No association
INDIVIDUAL ACTIVITY
1
0
2
Decreased odds
21
3
4
Increased odds
22
Reminders
Assignment II (30% of your final grade)
▪ This is an individual assessment task (1,200 words maximum)
▪ Based on the learning materials and concepts covered in Weeks 1–8
▪ Due Sunday 12 September 2021 at 8.00 PM (AEST)
Questions?
23
HBS108 Week 07 Lecture Notes
24
4
25 June 2021
Class schedule and exam revision
Topic 1—Introduction to research
Health Information and
Data (HBS108)
Topic 2—Searching for and evaluating online health information
WEEK 8:
Topic 6—Sampling, data collection & measurement
Topic 3—Evaluating online health information and data
Topic 4—Qualitative research
Topic 5—Introduction to quantitative research
ANALYSIS AND INTERPRETATION IN QUANTITATIVE RESEARCH
[PART II]
1
2
Class schedule and exam revision
Outline for today
▪ Lecture
▪ Revision of Descriptive Statistics
▪ Measures of Association
▪ Null Hypothesis Significance Testing
▪ Confidence Intervals
Topic 7 (Part 1)—Analysis and interpretation in quantitative research
Topic 7 (Part 2)—Analysis and interpretation in quantitative research
Revision of Topics 1–7
Topic 8—Measuring health and disease in populations
Topic 9—Evidence based professional practice
▪ Seminar
▪ Individual Activity I
▪ Individual Activity II
Exam Revision
3
4
Topic 7 [Part I]—Learning objectives
By the end of Topic 7 [Part I], you should be able to:
▪ Explain how quantitative data are summarised, analysed and presented using some
basic forms of descriptive and inferential statistics
▪ Interpret methods used to summarise and present data in the form of descriptive
statistics, including:
▪ Commonly encountered frequency distributions, including normal and skewed
▪ Measures of central tendency (mean, median and mode)
▪ Measures of dispersion (range, percentiles, interquartile range [IQR] and standard
deviation [SD])
Revision of descriptive
statistics
▪ Interpret some commonly used measures of association used in inferential
statistics, including:
▪ Relative risk (RR)
▪ Odds ratio (OR)
HBS108 TOPIC 7B.1
5
HBS108 Week 08 Lecture Notes
6
1
25 June 2021
Topic 7 [Part II]—Learning objectives
Descriptive statistics revision
By the end of Topic 7 [Part II], you should be able to:
▪ Interpret some commonly used measures of association used in inferential
statistics, including:
▪ Correlation coefficient (r)
▪ Chi-square (χ2)
▪ Frequency distributions/patterns
▪ What are frequency distributions?
▪ Apply the rationale and logic of statistical significance and hypothesis testing
through the use of:
▪ Confidence intervals (CI)
▪ p-values
▪ Dispersion (range, percentiles, IQR, SD)
▪ What is the difference between the range and IQR?
▪ Which of these measures is used with the median? Mean?
▪ If I said your assignment mark was in the 80th percentile, what would this mean?
▪ Central tendency (mean, mode, median)
▪ Which of these is most affected by extreme values? Least?
▪ Apply the rules of generalisability and causality that underpin the interpretation of
results from quantitative research studies
▪ Outline the strengths of mixed methods in health research
7
▪ OR and RR
▪ What does it mean if RR = 1? OR = 0.35? RR = 5.26?
▪ What is the difference between OR and RR?
8
Descriptive statistics revision
Analysis of quantitative research
Scales of measurement
Quantitative research often presents a combination of the following
analyses. It is important to understand how they are different and where
each test or measure fits in the research process.
▪ Categorical
▪ Nominal
▪ Ordinal
▪ Continuous
▪ Interval
▪ Ratio
9
DESCRIPTIVE
ANALYTICAL
Measures of Association
ANALYTICAL
Measures of Statistical
Significance
Displays of data
Relative risk/risk ratio (RR)
p-value
histograms, polygons, tables
cohort study, RCT
< 0.05 Central tendency Odds ratio (OR) 95%CI mean, median, mode case-control study Dispersion Correlation coefficient (r) range, IQR, percentiles, SD cross-sectional study Distributions Chi-square (χ2) normal, skewed cross-sectional study 10 Correlation coefficient (r) ▪ Measures association (not causation) ▪ Variables must be continuous ▪ r values exist on a limited scale −1 Measures of association Correlations can tell us: HBS108 TOPIC 7B.2 ▪ The strength of an association 0 1 ▪ ±0.1–0.4 (Weak), ±0.4–0.7 (Moderate), ±0.7–1.0 (Strong) ▪ The direction of an association 11 HBS108 Week 08 Lecture Notes 12 2 25 June 2021 Correlation coefficient (r) Correlation coefficient (r) 170 ▪Height and weight of 30 females, 11 years of age ▪Hours spent doing physical activity and weight 80 −1 70 75 160 1 Height 0 r = 0.749 1 0 Weight −1 150 60 r = −0.938 140 65 55 130 50 25 35 45 55 0 Weight 13 5 10 15 20 Hours spent doing physical activity 14 Chi-square (χ2) Correlation coefficient (r) −1 1 0 r = 0.226 Pulse rate (resting) ▪Height and resting pulse rate 85 ▪ Measures association (not causation) 80 ▪ Measures differences between groups 75 ▪ Variables must be categorical 70 65 60 55 50 140 150 160 170 Height 15 180 190 16 Chi-square (χ2) Chi-square (χ2) “Have you been a victim of crime in 100 the past 12 months?” Yes No Total “Have you been a victim of crime in 100 the past 12 months?” 2005 (%) 2009 (%) 80 2005 (%) 2009 (%) 80 n = 204 n = 166 60 n = 204 n = 166 60 81 (39.7) 57 (34.3) 40 81 (39.7) 36 (21.7) 40 Yes 123 (60.3) 109 (65.7) 100.0 100.0 No 20 Total 123 (60.3) 130 (78.3) 100.0 0 χ2 = 1.13, df = 1 17 HBS108 Week 08 Lecture Notes 100.0 20 0 2005 Yes 2009 χ2 = 13.75, df = 1 No 2005 Yes 2009 No 18 3 25 June 2021 Null hypothesis significance testing HBS108 TOPIC 7B.3 Image credit: FreeDigital Photos 19 20 Statistical significance p-values How sure are we that the results represent a ‘real’ effect and not just a chance occurrence? Statistical significance is fundamental to the principle of generalizability [also known as external validity]. To answer this question, we need to utilise either p-values or CIs ▪ Accepted cut-off value is 0.05 [against which we compare the p-value] ** You do NOT need to calculate these yourself ** We can interpret p-values in terms of: This is called ‘null hypothesis significance testing’ [NHST] ▪ Chance ▪ Null Hypothesis: There is no difference or association ▪ Drug A results in the same recovery time as Drug B ▪ Null hypothesis vs. research/alternative hypothesis ▪ Statistical significance ▪ Alternative Hypothesis: There is a difference or association ▪ Drug A results in an improved recovery time to Drug B 21 22 Interpretation of p-values What does the p-value tell us? If p ≤ 0.05 then: 170 ▪Height and weight of 30 females, 11 years of age ▪ What we have observed is ‘real’ ▪ We can reject the null hypothesis 160 ▪ The result is deemed ‘statistically significant’ −1 0 1 Height ▪ Therefore, what happened in our study can be generalised to the wider population If p > 0.05 then:
150
▪ What we have observed is due to chance
r = 0.749
p < 0.001 ▪ We can accept the null hypothesis ▪ The result is not ‘statistically significant’ ▪ Therefore, what happened in our study cannot be generalised to the wider population 140 130 25 35 45 55 Weight 23 HBS108 Week 08 Lecture Notes 24 4 25 June 2021 What does the p-value tell us? ▪Hours spent doing physical activity and weight 80 −1 70 85 80 Weight −1 65 60 r = −0.938 p < 0.001 1 0 r = 0.226 p = 0.229 55 Pulse rate (resting) 75 1 0 What does the p-value tell us? ▪Height and resting pulse rate 75 70 65 60 55 50 50 0 5 10 15 20 Hours spent doing physical activity 25 140 150 160 170 Height 180 190 26 What does the p-value tell us? What does the p-value tell us? “Have you been a victim of crime in 100 the past 12 months?” Yes No Total “Have you been a victim of crime in 100 the past 12 months?” 2005 (%) 2009 (%) 80 2005 (%) 2009 (%) 80 n = 204 n = 166 60 n = 204 n = 166 60 81 (39.7) 57 (34.3) 40 81 (39.7) 36 (21.7) 40 Yes 123 (60.3) 109 (65.7) 100.0 100.0 No 20 Total 123 (60.3) 130 (78.3) 100.0 100.0 0 χ2 = 1.13, df = 1, p = 0.288 20 0 2005 Yes 2009 χ2 = 13.75, df = 1, p < 0.001 No 27 2005 Yes 2009 No 28 What does the p-value tell us? P-values can also be used to test other measures of association. What do the following results mean? Are they statistically significant? ▪ RR = 1.7, p = 0.01 Confidence intervals ▪ OR = 2.6, p = 0.10 ▪ Mean for males = 5.7 seconds, p < 0.05 HBS108 TOPIC 7B.4 29 HBS108 Week 08 Lecture Notes 30 5 25 June 2021 Confidence intervals (95% CI) Confidence intervals (95% CI) ▪ CI assists in determining reliability of results Our sample recorded an r value of 0.754, therefore, we can be 95% confident that if we measured the whole population the true r value would be somewhere between 0.652 and 0.856 ▪ Most statistics relate to a sample, not a population ▪ CIs estimate the lower and uppermost values for the entire population Population Population 95% CI = 0.652–0.856 Sample Sample r = 0.754 31 32 Why only 95%? What does a 95% CI tell us? ▪ Just like p-values, there is a cut-off point for confidence intervals 170 ▪Height and weight of 30 females, 11 years of age ▪ If we wanted to be 100% certain, then we would need to measure everyone! 160 −1 0 1 Height ▪ Therefore, we leave a 5% leeway for error ▪ In other words, if you ever did measure the whole population, there is a 5% chance we might have been wrong with our estimate r = 0.749 p < 0.001 95% CI = 0.533–0.874 150 140 130 25 35 45 55 Weight 33 34 What does a 95% CI tell us? What does a 95% CI tell us? 85 ▪Height and resting pulse rate In a study looking at the association between eating takeaway for dinner 3+ times a week and CHD, the RR was found to be 1.60. The 95% CI for this relationship was 1.40–1.80. −1 0 r = 0.226 p = 0.229 95% CI = −0.146–0.542 1 Pulse rate (resting) 80 75 0 70 1 2 3 65 60 RR = 1.60 95% CI = 1.40–1.80 55 50 140 35 HBS108 Week 08 Lecture Notes 150 160 170 Height 180 190 36 6 25 June 2021 What does a 95% CI tell us? What does a 95% CI tell us? In a study looking at the association between arthritis and ‘voluntarily cracking joints’ in the past, the OR was found to be 1.20. The 95% CI for this relationship was 0.70–1.70 How confident we are about a RR, OR, r, or χ2 0 ▪ Mean = 50 kg, 95% CI 40 kg–60 kg 1 2 ▪ χ2 = 9.75, 95% CI 8.62–10.88 How confident we are about a mean 3 How confident we are that there is a ‘real’ difference between two groups OR = 1.20 95% CI = 0.70–1.70 Males: Mean = 90 kg Females: Mean = 60 kg 95% CI = 85 kg–95 kg 95% CI = 55 kg–65 kg These CIs do not include the same numbers (overlap) so we’re 95% certain that males and females are different! 37 38 Confidence intervals (95% CI) Generalisability and causality Four quantities make up and influence a confidence interval Be careful of language when discussing statistical findings! ▪ The sample statistic determines the location or middle of the confidence interval ▪ Hypotheses are never ‘proven’, they are merely ‘accepted’ or ‘rejected’ ▪ The sample size (n)—As n increases, the width of the CI gets narrower ▪ External validity: The results may be statistically significant for the study sample, but are they generalizable? ▪ The sample standard deviation (SD)—As the SD increases the width of the CI gets wider ▪ Association vs. cause and effect: You may have a statistically significant association but that doesn’t mean that the IV caused the DV ▪ The confidence level of the interval—As the CI gets larger (e.g., 99%), the width of the CI gets wider 39 40 Mixed-methods studies ▪ It is increasingly common for researchers to combine qualitative and quantitative research methods ▪ Mixing can occur at different stages of the research process [study design, data collection, analysis] ▪ Mixed-methods approaches permit a thorough investigation and understanding of research questions Activity 1 ▪ Triangulation: When a number of different methods are used in a single study INDIVIDUAL ACTIVITY (Taket 2013) 41 HBS108 Week 08 Lecture Notes 42 7 25 June 2021 Activity 2 Questions? INDIVIDUAL ACTIVITY 43 44 Reminders References Taket A (2013) ‘The use of mixed methods in health research’, in Liamputtong P (ed) Research methods in health: Foundations for evidence-based practice, 2nd edn, Oxford University Press, South Melbourne. Assignment II (30% of your final grade) ▪ This is an individual assessment task (1,200 words maximum) ▪ Based on the learning materials and concepts covered in Weeks 1–8 ▪ Due Sunday 12 September 2021 at 8.00 PM (AEST) 45 HBS108 Week 08 Lecture Notes 46 8 25 June 2021 Class schedule and exam revision Topic 1—Introduction to research Health Information and Data (HBS108) Topic 2—Searching for and evaluating online health information WEEK 10: Topic 6—Sampling, data collection & measurement Topic 3—Evaluating online health information and data Topic 4—Qualitative research Topic 5—Introduction to quantitative research MEASURING HEALTH AND DISEASE IN POPULATIONS 1 2 Class schedule and exam revision Outline for today ▪ Lecture ▪ Introduction to Epidemiology ▪ Measures of morbidity and mortality ▪ Case-fatality Topic 7 (Part 1)—Analysis and interpretation in quantitative research Topic 7 (Part 2)—Analysis and interpretation in quantitative research Revision of Topics 1–7 Topic 8—Measuring health and disease in populations ▪ Seminar ▪ Individual Activity I ▪ Individual Activity II Topic 9—Evidence based professional practice Exam Revision 3 4 Topic 8—Learning objectives By the end of Topic 8, you should be able to: ▪ Explain the purpose of collecting population health information Introduction to epidemiology ▪ Identify real-world examples of population health data collection ▪ Define the term ‘epidemiology’ ▪ Define and calculate the following epidemiology terms: Incidence, prevalence, mortality, morbidity, case-fatality HBS108 TOPIC 8.1 5 HBS108 Week 10 Lecture Notes ▪ Interpret basic epidemiological and population health data 6 1 25 June 2021 What are we talking about? The study of the health and disease of a population is called epidemiology. Epidemiology investigates: ▪ Distribution ▪ Determinants ▪ Deterrents Terminology: ▪ Epidemic—Sudden, widespread increase in cases ▪ Pandemic—A disease that is prevalent worldwide 7 8 Why? How? It all began with… ▪ John Snow and the Broad St. pump (1854) More recent examples… ▪ Cholera in Papua New Guinea (2010) ▪ Australian Foreign Minister Kevin Rudd claimed: “Australia remains concerned about cases in the hinterland around Daru Island, with potential for further spread of the disease.” Epidemiology uses measurement, for example: ▪ Hepatitis C in Melbourne (2010) ▪ Fifty-four women were infected after being treated at a Croydon Day Surgery in 2008 and 2009 ▪ Mortality ▪ How many? What percentage? What proportion? Two main types of measurement: ▪ Morbidity ▪ Middle East Respiratory Syndrome Coronavirus (MERS-CoV) WHO Emergencies—MERS Corona Virus 9 10 Morbidity Prevalence ▪ How many people currently have the illness? ▪ This can be ‘point’ prevalence: ▪ “How many people were sick on January 1 2015?” ▪ Or ‘period’ prevalence: ▪ “How many people were sick from 2000–2010?” Measures of morbidity and mortality In HBS108 we only calculate these two! Incidence ▪ How many new cases of the illness are developing? ▪ This can be ‘cumulative’ incidence: ▪ “How many people were diagnosed during January?” ▪ Or the incidence rate (person time): ▪ “How many people were diagnosed each hour?” HBS108 TOPIC 8.2 (Bonita 2006) 11 HBS108 Week 10 Lecture Notes 12 2 25 June 2021 How? Formulae Point prevalence All calculations learnt in this topic are rates: 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑒𝑥𝑖𝑠𝑡𝑖𝑛𝑔 𝑐𝑎𝑠𝑒𝑠 𝑜𝑓 𝑎 𝑑𝑖𝑠𝑒𝑎𝑠𝑒 𝑖𝑛 𝑎 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑎𝑡 𝑎 𝑝𝑜𝑖𝑛𝑡 𝑖𝑛 𝑡𝑖𝑚𝑒 × 10𝑛 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝒑𝒆𝒐𝒑𝒍𝒆 𝒊𝒏 𝒕𝒉𝒆 𝒑𝒐𝒑𝒖𝒍𝒂𝒕𝒊𝒐𝒏∗ 𝑎𝑡 𝑡ℎ𝑎𝑡 𝑡𝑖𝑚𝑒 𝑛𝑢𝑚𝑒𝑟𝑎𝑡𝑜𝑟 × 10𝑛 𝑑𝑒𝑛𝑜𝑚𝑖𝑛𝑎𝑡𝑜𝑟 * All people in the population Cumulative incidence 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑛𝑒𝑤 𝑐𝑎𝑠𝑒𝑠 𝑜𝑓 𝑎 𝑑𝑖𝑠𝑒𝑎𝑠𝑒 𝑖𝑛 𝑎 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑜𝑣𝑒𝑟 𝑎 𝑝𝑒𝑟𝑖𝑜𝑑 𝑜𝑓 𝑡𝑖𝑚𝑒 × 10𝑛 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝒑𝒆𝒐𝒑𝒍𝒆 𝒂𝒕 𝒓𝒊𝒔𝒌∗ 𝑎𝑡 𝑡ℎ𝑒 𝑏𝑒𝑔𝑖𝑛𝑛𝑖𝑛𝑔 𝑜𝑓 𝑡ℎ𝑎𝑡 𝑡𝑖𝑚𝑒 * People who were disease free at the beginning of the time period (Bonita 2006) 13 14 Measles outbreak! California December 2014–February 2015 Measles outbreak! California December 2014–February 2015 On February 13, 2015, a report was posted as a Morbidity and Mortality Weekly Report (MMWR) Early Release on the MMWR website (https://www.cdc.gov/mmwr/). Here is an excerpt: “On January 5, 2015, the California Department of Public Health (CDPH) was notified about a suspected measles case. The patient was a hospitalized, unvaccinated child, aged 11 years with rash onset on December 28. The only notable travel history during the exposure period was a visit to one of two adjacent Disney theme parks located in Orange County, California. On the same day, CDPH received reports of four additional suspected measles cases in California residents and two in Utah residents, all of whom reported visiting one or both Disney theme parks during December 17–20. By January 7, seven California measles cases had been confirmed, and CDPH issued a press release and an Epidemic Information Exchange (Epi-X) notification to other states regarding this outbreak. Measles transmission is ongoing (Figure).” (Zipprich et al. 2015; CDC 2015) 15 16 Measles outbreak! California December 2014–February 2015 U.S. Measles cases and outbreaks Between 28 December 2014 and 11 February 2015, 125 measles cases had been confirmed in U.S. residents connected with this outbreak. The United States Census Bureau estimates that the population of California was 38,802,500 on July 1, 2014. Therefore, over this six-week period, what was the incidence rate for measles? U.S. Measles Cases by Year 1,400 1,200 1,000 800 125 = 0.0000032214 × 1,000,000 38,802,500 = 3 𝑝𝑒𝑟 1,000,000 𝑟𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑠 600 400 125 doesn’t seem like many cases, but how does it compare to the usual rate? Or to other areas? 200 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 17 HBS108 Week 10 Lecture Notes 18 3 25 June 2021 Measles outbreak! California December 2014–February 2015 Mortality Mortality is measured in different ways: The measles virus in this outbreak (B3) turned out to be identical to the virus type that caused a large measles outbreak in the Philippines in 2014. ▪ Crude Mortality (All-Cause) ▪ Cause-Specific ▪ Group-Specific (sometimes referred to as ‘standardised’ mortality) ▪ Sex ▪ Ethnicity ▪ Socio-economic status ▪ Other demographic factors… Standardisation ensures you are comparing like with like… Image credit: CDC 19 20 Mortality formulae Crude mortality Crude mortality (all-cause) 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑑𝑒𝑎𝑡ℎ𝑠 𝑜𝑣𝑒𝑟 𝑎 𝑝𝑒𝑟𝑖𝑜𝑑 𝑜𝑓 𝑡𝑖𝑚𝑒 × 10𝑛 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑒𝑜𝑝𝑙𝑒 𝑖𝑛 𝑡ℎ𝑒 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑎𝑡 𝑡ℎ𝑎𝑡 𝑡𝑖𝑚𝑒 Cause-specific mortality 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑎𝑢𝑠𝑒 𝑠𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝑑𝑒𝑎𝑡ℎ𝑠 𝑜𝑣𝑒𝑟 𝑎 𝑝𝑒𝑟𝑖𝑜𝑑 𝑜𝑓 𝑡𝑖𝑚𝑒 × 10𝑛 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑒𝑜𝑝𝑙𝑒 𝑖𝑛 𝑡ℎ𝑒 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑎𝑡 𝑡ℎ𝑎𝑡 𝑡𝑖𝑚𝑒 Group-specific mortality (most commonly used group is age) 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑎𝑔𝑒 𝑠𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝑑𝑒𝑎𝑡ℎ𝑠 𝑜𝑣𝑒𝑟 𝑎 𝑝𝑒𝑟𝑖𝑜𝑑 𝑜𝑓 𝑡𝑖𝑚𝑒 × 10𝑛 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝒑𝒆𝒐𝒑𝒍𝒆 𝒘𝒊𝒕𝒉𝒊𝒏 𝒕𝒉𝒂𝒕 𝒂𝒈𝒆 𝒈𝒓𝒐𝒖𝒑 𝑎𝑡 𝑡ℎ𝑎𝑡 𝑡𝑖𝑚𝑒 (Bonita 2006) 21 (ABS 2016) 22 Mortality and the top 10 causes of death, USA, 1900 vs. 2010 (rates per 100,000) Cause-specific mortality 1900 Rank Cause of death All causes 1998 Number Rate Cause of death Number 343,217 1719.1 All causes 2,337,256 Rate 864.7 1 Pneumonia 40,362 202.2 Diseases of the heart 724,859 268.2 2 Tuberculosis 38,820 194.4 Malignant neoplasms 541,532 200.3 3 Diarrhea, enteritis, ulceration 28,491 142.7 Cerebrovascular diseases 158,448 58.6 4 Diseases of the heart 27,427 137.4 COPD 112,584 41.7 5 Intracranial lesions 21,353 106.9 All accidents 97,835 36.2 6 Nephritis (all forms) 17,699 88.6 Pneumonia and influenza 91,871 34.0 7 All accidents 14,429 72.3 Diabetes mellitus 64,751 24.0 8 Malignant neoplasms 12,769 64.0 Suicide 30,575 11.3 9 Senility 10,015 50.2 Nephritis (all forms) 26,182 9.7 10 Diphtheria 8,056 40.3 Chronic liver disease 25,192 9.3 (CDC 1999) 23 HBS108 Week 10 Lecture Notes 24 4 25 June 2021 Cause-specific mortality Group-specific mortality Cardiovascular disease death rates by age and sex, 2009 Deaths per 100,000 people 8,000 7,000 6,000 5,000 4,000 Males 3,000 Females 2,000 1,000 0 < 25 25–34 35–44 25 45–54 55–64 65–74 75–84 85+ Age group (years) (ABS 2014) 26 Case fatality Case fatality combines morbidity and mortality and, therefore, estimates chance of survival 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝒑𝒆𝒐𝒑𝒍𝒆 𝒘𝒉𝒐 𝒅𝒊𝒆 𝒇𝒓𝒐𝒎 𝒂 𝒑𝒂𝒓𝒕𝒊𝒄𝒖𝒍𝒂𝒓 𝒅𝒊𝒔𝒆𝒂𝒔𝒆 𝑜𝑣𝑒𝑟 𝑎 𝑝𝑒𝑟𝑖𝑜𝑑 𝑜𝑓 𝑡𝑖𝑚𝑒 × 10𝑛 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝒑𝒆𝒐𝒑𝒍𝒆 𝒘𝒉𝒐 𝒉𝒂𝒗𝒆 𝒕𝒉𝒆 𝒅𝒊𝒔𝒆𝒂𝒔𝒆 𝑑𝑢𝑟𝑖𝑛𝑔 𝑡ℎ𝑎𝑡 𝑡𝑖𝑚𝑒 𝑝𝑒𝑟𝑖𝑜𝑑 Case-fatality Ebola virus disease Fact sheet N°103 Updated April 2014 Key facts • Ebola virus disease (EVD), formerly known as Ebola haemorrhagic fever, is a severe, often fatal illness in humans. • EVD outbreaks have a case fatality rate of up to 90%. • EVD outbreaks occur primarily in remote villages in Central Africa, near tropical rainforests. • The virus is transmitted to people from wild animals and spreads in the human population through human-to-human transmission. HBS108 TOPIC 8.3 (WHO 2016) 27 28 Measles outbreak! FYI… How deadly is measles? In 2014, the World Health Organization (WHO) announced that measles elimination had been achieved by Australia. In many countries, mortality is low as it is now a rare virus, but what about case-fatality? Case-fatality rates for four recent global pandemics: Global pandemic Use the following information to calculate case-fatality of measles for the different age groups: Deaths by age in reported measles cases, United States, 1987–2000 AGE CASES DEATHS 0–9 35,222 106 10–19 18,580 18 20–29 9,161 26 30+ 4,069 27 1.1% H5N1 (Bird flu) ~60% MERS (Middle-East Respiratory Syndrome) CASE-FATALITY Case Fatality H1N1 (Swine flu) SARS-CoV-2 (Corona virus) 34.4% 16.7% ➛ 3.6% (Perry and Halsey 2004) 29 HBS108 Week 10 Lecture Notes 30 5 25 June 2021 SARS-CoV-2 (Corona virus) WHO coronavirus disease weekly epidemiological updates https://www.who.int/emergencies/diseases/novel-coronavirus2019/situation-reports/ WHO coronavirus disease dashboard https://covid19.who.int/ 31 32 Extra information For those of you who are interested in this topic (and are a fan of Hans Rosling like we are!), here is a link to a documentary titled “Don’t Panic” that you may find fascinating: https://www.gapminder.org/videos/dont-panic-the-facts-aboutpopulation/ Activity 1 (It is one hour long so we cannot fit it in this class!) INDIVIDUAL ACTIVITY 33 34 Activity 2 Questions? INDIVIDUAL ACTIVITY 35 HBS108 Week 10 Lecture Notes 36 6 25 June 2021 Reminders References ABS (Australian Bureau of Statistics) (2014) Causes of death, Australia, 2012, catalogue number 3303.0, accessed 9 February 2021. Assignment II (30% of your final grade) ▪ This is an individual assessment task (1,200 words maximum) ▪ Based on the learning materials and concepts covered in Weeks 1–8 ▪ Due Sunday 12 September 2021 at 8.00 PM (AEST) ABS (Australian Bureau of Statistics) (2016) Deaths, Australia, 2015, catalogue number 3302.0, accessed 9 February 2021. Bonita R, Beaglehole R and Kjellstrom T (2006) Basic Epidemiology, 2nd edn, World Health Organisation Press, Geneva, Switzerland. CDC (Centers for Disease Control and Prevention) (1999) Leading causes of death, 1900– 1998, CDC, accessed 9 February 2021. CDC (Centers for Disease Control and Prevention) (2015) Measles outbreak—California, December 2014–February 2015, CDC, accessed 9 February 2021. Rosling H (8 May 2009) ‘Swine flue alert! News/Death ratio: 8176’ [video], Gapminder Foundation, YouTube, accessed 9 February 2021. 37 38 References Perry RT and Halsey NA (2004) ‘The clinical significance of measles: A review’, The Journal of Infectious Diseases, 189(1):S4–16, doi:10.1086/377712 WHO (World Health Organisation) (2014) Ebola virus disease, fact sheet number 103, accessed 7 February 2016. Zipprich J, Winter K, Hacker J, Xia D, Watt J and Harriman K (2015) ‘Measles outbreak— California, December 2014–February 2015’, Morbidity and Mortality Weekly Report, 64(6):153–154. 39 HBS108 Week 10 Lecture Notes 7 25 June 2021 Class schedule and exam revision Topic 1—Introduction to research Health Information and Data (HBS108) Topic 2—Searching for and evaluating online health information WEEK 9: Topic 6—Sampling, data collection & measurement Topic 3—Evaluating online health information and data Topic 4—Qualitative research Topic 5—Introduction to quantitative research REVISION OF TOPICS 1 –7 1 2 Class schedule and exam revision Outline for today ▪ Lecture ▪ Summary of Topics 1–7 Topic 7 (Part 1)—Analysis and interpretation in quantitative research Topic 7 (Part 2)—Analysis and interpretation in quantitative research ▪ Seminar ▪ Individual Activity I ▪ Individual Activity II Revision of Topics 1–7 Topic 8—Measuring health and disease in populations Topic 9—Evidence based professional practice Exam Revision 3 4 Topic 1—Introduction to health research What is research? ▪ Quantitative: ▪ Experimental or observational? ▪ Qualitative: ▪ Inductive or deductive? Summary of Topics 1–7 HBS108 TOPIC REVISION 5 HBS108 Week 09 Lecture Notes 6 1 25 June 2021 Topics 2 & 3—Searching and evaluating online health information Topic 1—Introduction to health research What are ethics? Online health information ▪ Population based data ▪ ▪ ▪ Clinical and group-based research ▪ ▪ 7 8 Topics 4 to 7—Qualitative and quantitative research methods QUALITATIVE Study Design Ethnography Phenomenology Grounded Theory Sampling or Recruitment Data Collection Systematic Review/Meta-Analysis RCT Cohort Case-Control Cross-Sectional Case Study Non-probability Convenience Quota Interviews Focus groups Topics 5 and 6 Additional aspects to consider when viewing quantitative research: ▪ Bias ▪ ▪ ▪ Confounding ▪ ▪ Validity ▪ ▪ ▪ Reliability ▪ QUANTITATIVE Purposive Snowball Observation Existing data Data Analysis Transcription, immersion, and coding Thematic analysis Probability Simple Random Systematic Physiological measurements Stratified Cluster Existing records Questionnaires Descriptive statistics Measures of association Measures of statistical significance 9 10 Topic 1—Revision questions 1. Health research is important for professional practice because: a. It enables health practitioners to improve the health and wellbeing of individuals and the community by basing their practice on sound evidence. b. It provides a better knowledge base than health claims that are not based on good research. c. It informs government health policies aimed at improving public health. d. All of the above are correct. Test your understanding of Topics 1–7 HBS108 TOPIC REVISION QUIZ 11 HBS108 Week 09 Lecture Notes 12 2 25 June 2021 Topic 1—Revision questions Topic 1—Revision questions 3. Which of the following statements about research ethics is correct? a. Research studies are considered ethical if the benefits to society (as a whole) outweigh the harms caused to a small number of individuals participating in the study. b. There is no need to obtain ethics committee approval for a study if the researcher considers that the risks of participation are minimal. c. It is unethical for organisations or individuals who could potentially benefit from research findings (e.g., pharmaceutical companies, medical appliance manufacturers) to conduct or fund health research. d. Ethical principles require researchers to consider the possibility of psychological and social harm (e.g., distress, anxiety, release of private information) to study participants as well as physical harm. 2. Health research: a. Always involves quantitative measurement and statistical analysis of quantitative data. b. Employs quantitative, qualitative or mixed methods designs depending on the research question. c. Uses predominantly qualitative methods because statistics can never adequately deal with the complexity of human health. d. Uses mixed methods research when the researcher is not sure whether it is best to use quantitative or qualitative methods. 13 14 Topic 4—Revision questions Topic 4—Revision questions 4. In qualitative health research: a. Data are often collected on participants’ experiences, beliefs and perspectives. b. It is important to use random sampling to select study participants. c. Ethical approval to conduct the research is not usually required because there is little harm caused to study participants. d. Data are usually analysed using descriptive statistics. 15 5. Which of the following research questions could not be answered using qualitative methods: a. Are people who own pets less likely to experience high blood pressure than people without pets? b. What factors do families with young children consider when choosing a pet? c. What role do children play in choosing a family pet? d. What are pet owners’ understandings of the concept of ‘responsible pet ownership’? 16 Topic 4—Revision questions Topic 4—Revision questions 6. In grounded theory research: a. Hypotheses (derived from theory) are tested. b. Theories emerge from the data analysis. c. Only pre-determined themes and issues are included in the analysis. d. ‘Unexpected’ findings (e.g., that question existing theories) indicate that the study design and/or methods were likely to be faulty. 17 HBS108 Week 09 Lecture Notes 7. Qualitative data can be in the form of: a. A video-recording of pedestrian behaviour at intersections. b. Notes taken during focus group discussions with carers of children with a disability. c. Transcribed audio-tapes of interviews with members of a self-help group. d. All of the above are correct. 18 3 25 June 2021 Topic 5—Revision questions Topic 5—Revision questions 8. Randomised control trials (RCTs) are considered the ‘Gold Standard’ study design because: a. They are less susceptible to measurement error. b. Study participants can choose whether or not they receive the intervention. c. They are less susceptible to the effects of bias and confounding. d. They are the most ethical quantitative study design. 19 9. In the context of the ‘hierarchy of evidence’, systematic reviews with meta-analyses of randomised controlled trials provide the most rigorous evidence. a. True. b. False. 20 Topic 5—Revision questions Topic 5—Revision questions 10. In the context of the ‘hierarchy of evidence’, cohort studies are considered to have poor ability to eliminate bias and therefore do not contribute significantly to the evidence base. a. True. b. False. 21 11. You are conducting a study to explore the nature of nurse-doctor relationships in a large hospital in rural Victoria. The most appropriate study design is: a. Cross-sectional study. b. Ethnography. c. Phenomenology. d. Cohort study. 22 Topic 5—Revision questions Topic 6—Revision questions 12. A random sample of older Australian adults is surveyed to examine whether pet ownership is associated with physical activity levels. This is a: a. Cross-sectional study. b. Randomised controlled study. c. Cohort study. d. Case-control study. 23 HBS108 Week 09 Lecture Notes 13. In quantitative health research: a. Data are recorded in the form of numbers. b. Data are recorded in the form of words. c. Data are often collected using focus group discussions. d. Data are usually collected from a non-probability sample. 24 4 25 June 2021 Topic 6—Revision questions Topic 6—Revision questions 14. Recruiting people to participate in a study of people’s perceptions of healthy food choices by approaching them as they leave a supermarket is a form of: a. Convenience sampling. b. Stratified sampling. c. Snowball sampling. d. Simple random sampling. 25 15. Which of the following is not a form of non-probability sampling? a. Convenience sampling. b. Purposive sampling. c. Snowball sampling. d. Cluster random sampling. 26 Topic 6—Revision questions Topic 6—Revision questions 16. A randomised controlled trial investigating the effectiveness of a GPbased child asthma management program was conducted using a sample drawn from recently-arrived families in inner-urban Melbourne living in government housing. In terms of applying the findings to the population of children in Melbourne, the study would have limited external validity. Is this true or false? a. True. b. False. c. There is not enough information provided to decide. 27 17. A quantitative study is conducted to investigate the physical activity (PA) levels of office workers aged 30–50 years. A questionnaire is developed to collect data about their PA. In checking whether the questionnaire collects consistent responses from participants, the investigator is assessing its: a. Internal validity. b. Reliability. c. External validity. d. All of the above are correct. 28 Topic 7—Revision questions Topic 7—Revision questions 18. In a randomised controlled trial (RCT) testing the effectiveness of the Atkins’ diet for weight loss (Foster et al. 2003) a chi-square test was performed to determine differences between the intervention and control groups for those who dropped out of the study. After three months’ follow-up, more participants following the control diet had dropped out (30%) than those following the Atkins diet (15%) but this difference was not statistically significant. This means: a. The conventional diet was more acceptable to participants than the Atkins’ diet hence the higher dropout rate for this group. b. The chi-square test found no statistically significant difference in dropout rates between the two groups. c. The chi-square test was not the correct statistical test. d. The authors are in error as there is clearly a significant difference in dropout rates. 29 HBS108 Week 09 Lecture Notes 19. In a study of the health impacts of contact with nature, a large company examined whether employees who had one or more potplants in their office took fewer sick days per annum than those who did not. The chi-square test could be used to test the statistical significance of this relationship. a. True. b. False. 30 5 25 June 2021 Topic 7—Revision questions Topic 7—Revision questions 20. Hughes and Jones (1985) studied the relationship between average intake of dietary fibre and the average age of menarche (first menstrual period) in girls across 46 countries. They found a correlation coefficient of r = 0.84 (p < 0.001). This means: a. Dietary fibre intake and age of menarche are strongly and significantly correlated. b. Age of menarche predicts dietary fibre intake. c. Dietary fibre intake and age of menarche are strongly but not significantly correlated. d. The relationship between dietary fibre intake and age of menarche is a chance association. 31 21. Which of the following is not a property of the correlation coefficient, r? a. r measures the strength of a linear relationship between x and y. b. If r is close to zero, there is little to no relationship between x and y. c. If r = –1 or r = +1, there is a very strong relationship between x and y. d. r measures the strength of a relationship between two categorical variables x and y. 32 Activity 1 Activity 2 INDIVIDUAL ACTIVITY INDIVIDUAL ACTIVITY 33 34 Reminders Assignment II (30% of your final grade) ▪ This is an individual assessment task (1,200 words maximum) ▪ Based on the learning materials and concepts covered in Weeks 1–8 ▪ Due Sunday 12 September 2021 at 8.00 PM (AEST) Questions? 35 HBS108 Week 09 Lecture Notes 36 6 25 June 2021 References Foster GD, Wyatt HR, Hill JO, McGuckin BG, Brill C, Mohammed BS, Szapary PO, Rader DJ, Edman JS and Klein S (2003) ‘A randomized trial of a low-carbohydrate diet for obesity’, New England Journal of Medicine, 348(21):2082–2090, doi:10.1056/NEJMoa022207 Hughes RE and Jones E (1985) ‘Intake of dietary fibre and the age of menarche’, Annals of Human Biology, 12(4):325–332, doi:10.1080/03014468500007851 37 HBS108 Week 09 Lecture Notes 7