Outline

Overview

This unit introduces the principles underpinning the design and conduct of high quality controlled clinical trials to generate good evidence for health care decision making. The topics include clinical trial design, randomisation, sample size, measures of treatment effect, methodological issues, trial protocols, and ethical principles.

Unit details and rules

Academic unit	Public Health
Credit points	6
Prerequisites ?	PUBH5018 or FMHU5002
Corequisites ?	None
Prohibitions ?	PUBH5206 - Controlled trials (2CP)
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Armando Teixeira-Pinto, armando.teixeira-pinto@sydney.edu.au

Assessment

The census date for this unit availability is 31 August 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Out-of-class quiz	Online quizzes Online quizzes	10%	Week 03 Due date: 17 Aug 2026 at 11:25	Each quiz - 30 mins	AI allowed
Outcomes assessed:
Written work	Assignment Scenario-based written assignment	45%	Week 08 Due date: 21 Sep 2026 at 23:59	4 x A4 pages	AI allowed
Outcomes assessed:
Out-of-class quiz	End of semester Quiz Online quiz	20%	Week 12 Due date: 26 Oct 2026 at 23:59	1 hour	AI allowed
Outcomes assessed:
Written work	End of Semester Assignment Scenario-based written assignment	25%	Week 13 Due date: 02 Nov 2026 at 23:59	3 x A4 pages	AI allowed
Outcomes assessed:

Assessment summary

Short quizzes: Each quiz covers two modules. The quizzes are open book.
Mid-Semester assignment:听Students will be required听read a number of scenarios and respond to structured questions designed to evaluate their understanding of the material in the course.
End of semester quiz:听Longer quiz covering the whole unit.听
End of semester assignment:听Students will be required to read a number of scenarios and respond to structured questions designed to evaluate their understanding of the material in the course.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	听
Distinction	75 - 84	听
Credit	65 - 74	听
Pass	50 - 64	听
Fail	0 - 49	When you don鈥檛 meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the听Academic Integrity Policy.

Visit the听Current Students website听for more information on AI in assessments, including听details on how to acknowledge its use.

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:

鈥� Late submissions that have not been granted extensions and are of a standard to receive a pass or higher mark will attract a penalty of 5% of the maximum mark per day late including weekend days (e.g. if the assignment is worth 40 marks, the penalty is 2 marks per day late) until the mark reaches 50% of the maximum mark (e.g. 20 marks if the maximum is 40 marks). 鈥� Submissions that are not of a pass standard will not have marks deducted and will fail regardless 鈥� Submissions more than 10 days late without prior approval from the unit of study coordinator will not be accepted and will be given a zero (0) mark

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website听provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the听Academic Honesty Education Module (AHEM)听which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the听Current Students website听for more information on AI in assessments, including听details on how to acknowledge its use.

Learning support

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听simple extension.鈥� 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鈥檛 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听special consideration or special arrangements.

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

Using AI responsibly

Co-created with students,听听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.

Support for students

The Support for Students Policy听reflects the University鈥檚 commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to Controlled Clinical Trials and Trial Designs	Lecture (60 hr)
	Introduction to Controlled Clinical Trials and Trial Designs	Self-directed learning (60 hr)
	Introduction to Controlled Clinical Trials and Trial Designs	Self-directed learning (1 hr)

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

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.

Outcomes
Graduate qualities

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

LO1. describe the features of high quality controlled clinical trials and determine the applicability of common designs for randomised controlled trials to a particular research question
LO2. demonstrate an understanding of the purpose of random treatment allocation and implementing common randomisation methods
LO3. demonstrate an understanding of the key issues in determining an adequate sample size for a randomised control trial
LO4. demonstrate awareness of the ethical principles of relevance to clinical trials
LO5. describe the main sections of a trial protocol
LO6. recognise, correctly interpret, and adequately manage key methodological and practical issues arising in the design, conduct, analysis, and interpretation of a randomised controlled trial.

Graduate qualities

The graduate qualities are the qualities and skills that all 爆料王 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鈥檚 personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

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

We will promote discussion online for all students about tutorial activities.

Disclaimer

Important: the 爆料王 regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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

爆料王

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

爆料王

PUBH5216: Controlled Clinical Trials

Semester 2, 2026 [Online] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links