CEPI5312: Semester 2 Early, 2020

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Units CEPI5312 Semester 2 Early 2020 [Normal day]

Unit outline_

CEPI5312: Diagnostic and Screening Tests (1 and 2)

Semester 2 Early, 2020 [Normal day] - Camperdown/Darlington, Sydney

Overview

This unit of study introduces the student to basic concepts behind diagnostic and screening tests, including: test accuracy, sources of bias in test evaluation, critical appraisal of test evaluation studies, principles and use of evidence in making decisions about population screening, and overdiagnosis. It will then move to more advanced topics including: application of test results to individual patients, place of tests in diagnostic pathways, impact of tests on patient outcome, tests with continuous outcome, receiver-operator characteristic curves, systematic review of diagnostic tests, predictive models, and monitoring/surveillance. After completing this unit of study, the student should have a comprehensive understanding of contemporary issues and the methodology underlying, diagnostic and screening test evaluation and application.

Unit details and rules

Academic unit	Public Health
Credit points	6
Prerequisites ?	PUBH5010 or CEPI5100
Corequisites ?	None
Prohibitions ?	PUBH5208 or CEPI5202 or CEPI5311
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Katy Bell, katy.bell@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Assignment 2 Written assessment	30%	Mid-semester break	1000 words
Outcomes assessed:
Participation	Participation Contributions to tutorial discussions	10%	Multiple weeks	n/a
Outcomes assessed:
Presentation	Assignment 1 Oral presentation	15%	Week 06	5 minutes
Outcomes assessed:
Presentation	Assignment 3 Oral presentation	15%	Week 12	5 minutes
Outcomes assessed:
Assignment	Assignment 4 Written assessment	30%	Week 14 (STUVAC)	1000 words
Outcomes assessed:

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (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
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.

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 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.

Weekly schedule

WK	Topic	Learning activity	Learning outcomes

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. calculate sensitivity and specificity using 2x2 tables from various data sources, and explain how sensitivity and specificity affect the way we use and interpret a test
LO2. classify types of bias in diagnostic test evaluation, and describe how these could affect estimation of test accuracy
LO3. explain different roles a test may have in a diagnostic pathway, and how to evaluate a new diagnostic test
LO4. explain the principles and practice of population screening
LO5. explain the issues surrounding overdiagnosis and other contemporary issues in diagnostic test use
LO6. apply test results to individual patients using likelihood ratios and decision thresholds
LO7. interpret further topics in diagnostic test evaluation, including repeatability, test combinations, use of clinical information, and tests with continuous outcome
LO8. interpret receiver-operator characteristic curves and explain the principles behind systematic review and meta-analysis of diagnostic tests
LO9. describe issues surrounding use of tests for monitoring chronic disease or cancer surveillance.

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
Learning outcomes

Responding to student feedback

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

No changes have been made since this unit was last offered.

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.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

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