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Unit outline_

FMHU5001: Foundations of Health Research

Semester 1, 2023 [Online] - Camperdown/Darlington, Sydney

This unit introduces students to the principles and foundations of health research methodologies and ethics. Students will learn about the main methodologies used to conduct research that is scientifically and ethically sound and be able to critically appraise and review literature. We will introduce common study designs and research methodologies, including qualitative, epidemiologic and clinical studies, and discuss their strengths and limitations. We will introduce students to the main principles of conducting data analysis and the basis to choose amongst different statistical methods. Obtaining ethics approval is necessary for any study involving the collection or analysis of data involving humans, animals or their tissues. Hence, in this unit we will cover ethics in research and when and how to apply for ethics approval. Students will also learn about main concepts in health economics and economical evaluations of interventions and health policies.

Unit details and rules

Academic unit Public Health
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
MEDF5005 or NTDT5602
Assumed knowledge
? 

Basic knowledge in mathematics

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Christina Abdelshaheed, christina.abdelshaheed@sydney.edu.au
Guest lecturer(s) Julie Mooney-Somers, julie.mooneysomers@sydney.edu.au
Alison Hayes, alison.hayes@sydney.edu.au
Ian Kerridge, ian.kerridge@sydney.edu.au
Tim Driscoll, tim.driscoll@sydney.edu.au
Rowena Forsyth, rowena.forsyth@sydney.edu.au
Lecturer(s) Christina Abdelshaheed, christina.abdelshaheed@sydney.edu.au
Armando Teixeira-Pinto, armando.teixeira-pinto@sydney.edu.au
Type Description Weight Due Length
Assignment Ethics, Qualitative research
Ethics and Qualitative Research
45% Week 07
Due date: 07 Apr 2023 at 23:59
Up to 4500 words
Outcomes assessed: LO1 LO2
Assignment Proposal and appraisal for a quantitative study
Candidates will identify study types and appraise a quantitative study.
25% Week 10
Due date: 01 May 2023 at 23:59
Up to 2000 words or up to 5 A4 pages
Outcomes assessed: LO1 LO2 LO3
Assignment Appraisal and analysis of a Quantitative study (statistics and economic evaluation)
Students will be given a dataset and asked to conduct exploratory analysis
30% Week 13
Due date: 26 May 2023 at 23:59
Up to 1000 words
Outcomes assessed: LO3 LO4

Assessment summary

  1. Assessment 1: Candidates will be asked to identify potential risks and ethical considerations for research scenarios and consider strategies to mitigate any risks to participants, researchers and participating institutions. Candidates will develop a research proposal for a qualitative study. Candidates will be asked to consider methods in qualitative study design and analysis, and strategies to mitigate potential risks to participants, researchers and participating institutions.
  2. Assessment 2: Candidates will be asked to identify and consider appropriate study types, identify and describe biases, and scientifically critique the design of one or more quantitative studies.
  3. Assessment 3: Candidates will be given a dataset and asked to conduct an exploratory data analysis, summarise and present data and conduct a formal data analysis.

Assessment criteria

A grade of High distinction, distinction, credit, pass or fail will be awarded in accordance with University Grading Policies: https://www.sydney.edu.au/students/guide-to-grades.html

 

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late assignments of a pass or higher standard will be subject to a penalty of 5% of the total mark per day late or part thereof until a mark of 50% has been reached. Submissions greater than 10 business days late will not be accepted and will be given a mark of 0, unless prior approval has been provided.

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 Ethics in Health Research Lecture (2 hr) LO1
Week 02 Ethics in Health Research Lecture (2 hr) LO1
Ethics in Health Research Tutorial (2 hr) LO1
Week 03 Qualitative Research Lecture (1 hr) LO2
Qualitative Research Tutorial (2 hr) LO2
Week 04 Qualitative Research Lecture (1 hr) LO2
Qualitative Research Tutorial (2 hr) LO2
Week 05 EPIDEMIOLOGICAL AND CLINICAL RESEARCH Lecture (1 hr) LO2
Week 06 EPIDEMIOLOGICAL AND CLINICAL RESEARCH Lecture (1 hr) LO2
EPIDEMIOLOGICAL AND CLINICAL RESEARCH Tutorial (2 hr) LO2
Week 07 EPIDEMIOLOGICAL AND CLINICAL RESEARCH Lecture (1 hr) LO2
EPIDEMIOLOGICAL AND CLINICAL RESEARCH Tutorial (2 hr) LO2
Week 08 BIOSTATISTICS AND DATA SCIENCE Lecture (1 hr) LO2 LO3
BIOSTATISTICS AND DATA SCIENCE Tutorial (2 hr) LO3
Week 09 BIOSTATISTICS AND DATA SCIENCE Lecture (1 hr) LO3
BIOSTATISTICS AND DATA SCIENCE Tutorial (2 hr) LO3
Week 10 BIOSTATISTICS AND DATA SCIENCE Lecture (1 hr) LO3
BIOSTATISTICS AND DATA SCIENCE Tutorial (2 hr) LO3
Week 11 HEALTH ECONOMICS Lecture (1 hr) LO4
HEALTH ECONOMICS Tutorial (2 hr) LO4
Week 12 HEALTH ECONOMICS Lecture (1 hr) LO4
HEALTH ECONOMICS Tutorial (2 hr) LO4

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.

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. • LO1: Describe the importance and the principles of ethics in the context of health research (GQ6, GQ7, GQ8, GQ9)
  • LO2. • LO2: Identify the main elements and methodologies of qualitative, epidemiologic and clinical research (GQ2, GQ5, GQ7)
  • LO3. • LO3: Identify the steps of a statistical analysis and the principles used to select the appropriate statistical method(s) (GQ2, GQ4)
  • LO4. • LO4: Understand the principles of health economics, namely, resource scarcity, incentives, opportunity cost, efficiency, and equity, and their practical application in real-life examples (GQ2, GQ5)

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.

The teaching team will review the results from the USS and provide candidates with a closing the loop summary of the feedback and how these will be addressed in subsequent iterations of the unit.

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.