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Unit outline_

HSBH4101: Research Design and Analysis in Health

Semester 1, 2023 [Normal day] - Camperdown/Darlington, Sydney

In this unit of study you delve deeper into the methods used in health research, building on your knowledge from previous years (see the prerequisites). You will attend lectures and interactive workshops, and complete online study modules. After the common foundations, the unit will be split in streams so that each student will learn either quantitative or qualitative data analysis in depth (not both), depending on their prior learning and interests. As part of quantitative methods, we cover experimental and observational (survey, case­control, cohort) study designs, and linear model and logistic regression for data analysis. Qualitative approaches include ethnography, grounded theory, phenomenology and narrative. Methods include interview, focus group and text based. The unit will help with your specific Honours project.

Unit details and rules

Academic unit Health Sciences
Credit points 6
Prerequisites
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None
Corequisites
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None
Prohibitions
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None
Assumed knowledge
? 

48cp of 3000 level units of study

Available to study abroad and exchange students

No

Teaching staff

Coordinator Tatjana Seizova-Cajic, tatjana.seizova-cajic@sydney.edu.au
Type Description Weight Due Length
Supervised exam
? 
hurdle task
Research methods exam
Pen-and-paper (hurdle task - must pass)
50% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
Assignment Foundations quiz
Foundations quiz on concepts in quantitative research
3% Week 03
Due date: 12 Mar 2023 at 23:59

Closing date: 19 Mar 2023
10 questions, no time limit
Outcomes assessed: LO1 LO3 LO5 LO6
Assignment My study design
Written description of basic aspects of your study design
3% Week 06
Due date: 02 Apr 2023 at 23:59

Closing date: 09 Apr 2023
300-500 words
Outcomes assessed: LO1 LO3 LO4 LO5 LO6
Assignment Mid-semester quiz
Quiz on quant and qual study design and descriptive statistics
30% Week 07
Due date: 05 Apr 2023 at 13:00

Closing date: 05 Apr 2023
50 min
Outcomes assessed: LO1 LO3 LO5 LO6
Presentation Show and tell: Methods
Describe and justify method of a published study
7% Week 08
Due date: 19 Apr 2023 at 10:00

Closing date: 19 Apr 2023
12 min (+ discussion)
Outcomes assessed: LO1 LO7 LO5
Presentation Show and tell: Results
Show and interpret published results
7% Week 13
Due date: 24 May 2023 at 10:00

Closing date: 24 May 2023
12 min (+ discussion)
Outcomes assessed: LO1 LO7 LO5
hurdle task = hurdle task ?

Assessment summary

  • Foundations quiz (3%) will refresh your memory of basic concepts in quantitative research and get you to think about bigger ideas behind your Honours project
  • My study design (3%) will get you to think through the reasons you are choosing a particular study design
  • Mid-semester in-class quiz (30%) will assess your understanding of concepts covered in Weeks 1-7
  • Show-and-tell are two short presentations worth 7% each. First you will present and justify method of a published study, and later, its results; these presentations will motivate you to carefully consider relevant sections of published papers and develop your ability to discuss research (done in pairs; 7 slides; 12 min to present + discussion)
  • Research methods exam (50%): This exam will test the understanding of concepts covered in class (including your stream) and compulsory readings. You will receive a detailed list of assessable concepts.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 L1. Introduction to Honours; meet and greet; Introduction to the unit (TSC) Lecture (2 hr) LO2
T1. Types of research; research process; role of theory (TSC) Tutorial (2 hr) LO1 LO3 LO5
IS1: Variable, the building block of quantitative research (online module) Online class (2 hr) LO1 LO5
Week 02 L2. Quantitative research: Observational study designs (TSC) Lecture (2 hr) LO1 LO3 LO5 LO6
Week 03 L3. Qualitative research: introduction and basic concepts (JMN) Lecture (2 hr) LO1 LO5 LO6
T2. Qualitative methods (JMN) Tutorial (2 hr) LO3 LO5 LO6
Week 04 L4. Quantitative research: Experiments and quasi experiments (MFS) Lecture (2 hr) LO3 LO5 LO6
Week 05 L5. Use of interviews in qualitative research (JMN) Lecture (2 hr) LO3 LO4 LO5 LO6
T5: Interviews (JMN) Tutorial (2 hr) LO1 LO5 LO6
IS2. Your study design: discuss with a peer Online class (2 hr) LO3 LO4 LO5 LO6 LO7
Week 06 L6. Descriptive statistics for continuous and categorical data; Introduction to inferential statistics (TSC) Lecture (2 hr) LO2 LO5 LO6
Week 07 L7. Use of focus groups in qualitative research (JMN) Lecture (2 hr) LO3 LO4 LO5 LO6
T3. Mid-semester QUIZ (30%); discussion (TSC) Tutorial (2 hr) LO3 LO4 LO5
Week 08 L8. Show and tell (present method of a paper) If time permits: p value; Confidence Intervals (TSC) Lecture and tutorial (2 hr) LO1 LO3 LO5 LO6 LO7
Week 09 QUANT STREAM L1: Analysis of continuous data: Correlation and regression; application in SPSS (TSC) Lecture (2 hr) LO5 LO6
QUANT STREAM T1: Data exploration in SPSS (plotting and descriptive statistics); Correlation and regression in SPSS (TSC) Tutorial (2 hr) LO5 LO6
QUANT STREAM IS1: Regression in SPSS (online module) (TSC) Online class (1 hr) LO5 LO6
QUAL STREAM L1: How we evaluate qualitative research (JMN) Lecture (2 hr) LO5 LO6
QUAL STREAM T1: Topic tba (JMN) Tutorial (2 hr) LO3 LO5 LO6
Week 10 QUANT STREAM L2: Analysis of continuous data: Comparison between the means - t-test, ANOVA (TSC) Lecture (2 hr) LO5 LO6
QUANT STREAM IS2: t-test and ANOVA in SPSS (online module) (TSC) Online class (1 hr) LO5 LO6
QUAL STREAM L2: Analysis of qualitative data, part 1 (JMN) Lecture (2 hr) LO5 LO6
QUAL STREAM IS1: Qualitative data analysis (JMN) Online class (1 hr) LO1 LO5 LO6
Week 11 QUANT STREAM, L3: Analysis of categorical data: OR, RR, Survival analysis and/or Logistic regression (TSC) Lecture and tutorial (2 hr) LO5 LO6
QUAL STREAM L3: Analysis of qualitative data, cont.; revision (JMN) Lecture and tutorial (2 hr) LO5 LO6
Week 13 L9 (both streams together): Show and tell (present results); revision of difficult concepts (TSC) Lecture and tutorial (2 hr) LO1 LO5 LO6 LO7
L9 (both streams together): Similarities and differences between quantitative and qualitative methods (TSC; JMN) Tutorial (2 hr) LO4 LO5 LO6 LO7

Attendance and class requirements

Attendance: Students are expected to attend all scheduled classes and to participate in discussions and activities. Attendance of less than 80% of the scheduled seminar classes must be supported by written documentation.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

The following recommended textbooks are available from the library (all except #3 are available online). Feel free to use other texts if you prefer them or already have them, but compare them to some of the recommended sources to ensure they are of similar depth.

  1. Bourgeault, I., Dingwall, R. and deVries, R. (2010). The SAGE handbook of qualitative research in health research. London: Sage. Available online: https://sydney.primo.exlibrisgroup.com/permalink/61USYD_INST/2rsddf/cdi_askewsholts_vlebooks_9781473971172
  2. Bruce N, Pope D & Stanistreet D (2018) Quantitative Methods for Health Research: a Practical Interactive Guide to Epidemiology and Statistics. Second edition. Hoboken, NJ: John Wiley & Sons, Inc. Available online: https://sydney.primo.exlibrisgroup.com/permalink/61USYD_INST/12rahnq/alma991005667659705106
  3. Field AP (2013) Discovering statistics using IBM SPSS statistics: and sex and drugs and rock 'n' roll. (4th ed.) London, SAGE Publications. Not available online – for hard copy, see: https://sydney.primo.exlibrisgroup.com/permalink/61USYD_INST/12rahnq/alma991005642139705106 An excellent introduction to statistics, with very detailed instructions on SPSS. It’s a big volume, because Andy Field makes many jokes.
  4. Portney LG (2020) Foundations of Clinical Research: Applications to Evidence-Based Practice. Fourth edition. Philadelphia, PA: F.A. Davis Company. Available online  https://sydney.primo.exlibrisgroup.com/permalink/61USYD_INST/1c0ug48/alma99103174078740510
  5. Saks M. & Allsop J. (2013) Researching health: Qualitative, quantitative and mixed methods. London: Sage.  Available online: https://sydney.primo.exlibrisgroup.com/permalink/61USYD_INST/12rahnq/alma991014514489705106 

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. study and work independently and in teams
  • LO2. manage schedules and resources
  • LO3. propose research that will increase knowledge in the area of interest
  • LO4. know the ethical principles of research and adhere to them
  • LO5. understand quantitative and qualitative approaches to research
  • LO6. investigate a topic under supervision, including data collection and analysis
  • LO7. demonstrate the ability to orally present ideas and research findings and respond to questions.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

Some students feel rather overwhelmed with the amount of coursework in Honours - there is a lot to learn. We have reduced some assessments in another unit of study to reduce the overall load, but it is important also to be realistic and allocate enough time to your studies from the very beginning. Also, we used to have classes on Wednesdays and Fridays and now all our classes are on Wednesdays to reduce travel time and free days for your other activities (primarily work on the project) Lecturers are usually described as very helpful, so please use us! Don't hesitate to ask questions and to seek help.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.