Outline

Overview

Cyberpsychology in Digital Health provides a workshop series into how digital technology impacts human behaviour - specifically how societal and individual health is affected by the internet and other popular technologies. The course will be based on evidence-based research and policy guidelines set by the Australian and American Medical Associations, and peak Psychological organisations such as the APS, BPS and APA regarding the use of information technology in the following areas: how types of digital tools and functions may affect human behaviour; the ethics and viability of delivering health resources online; the rise of serious games for health; social media in health; provision of therapy over the internet for general health and mental health; VR/AR and XR use in health and wellbeing; quality control, data security, and assessment of general and specific online health resources; and how AI and machine learning is being utilised in Cyberpsychology. The workshop series will conclude with a look at future directions of Cyberpsychology and its application to digital health and well being globally.

Unit details and rules

Academic unit	Public Health
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	BACH3146
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Andrew Campbell, andrew.campbell@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Presentation	Podcast Podcast on investigating the evidence-base of a Digital Health initiative.	15%	Week 05 Due date: 05 Sep 2025 at 09:00	5min audio recording	AI allowed
Outcomes assessed:
Written work	Report Report and recommendations on UX for Digital Health online information	35%	Week 10 Due date: 10 Oct 2025 at 09:00	1500 words	AI allowed
Outcomes assessed:
Presentation	Cyberpsychology Documentary Group Documentary on the Cyberpsychological impact of a Digital Technology.	40%	Week 13 Due date: 06 Nov 2025 at 12:00	Minimum 10min - Maximum 15 min	AI allowed
Outcomes assessed:
Contribution	Workshop Engagement and Discussion Board Discussion Board Contributions and attendance at Workshops.	10%	Week 13 Due date: 07 Nov 2025 at 13:00	Weekly attendance	AI allowed
Outcomes assessed:
= hurdle task ? = group assignment ?

Assessment summary

Workshop engagement + Discussion Board contribution: students will be required to attend workshops each week and engage with the dialogue posted on the Discussion board.
Podcast: Individual students will review a Digital Health tool and discuss its evidence-base via a submitted podcast.
Report: A choice of 1 of 2 topics is given to report on.

Topic 1: consists of an online e-health website resource (e.g. self-help, or peer-to-peer assisted) and how ethically it is run. Students must detemine whether it is based on quality evidence-based research.

Topic 2: consists of an online social networking health support group and how ethically it is run. Students must determine whether it is based on quality evidence-based research.
Group Work Documentary: Over the 13 weeks of the unit, students will work in groups of 2-3, to write, direct, film and present a 10 to 15min documentary on the Cyberpsychological impact of a digital device or system.

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 sydney.edu.au/students/guide-to-grades.

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 Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including 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:

Submitted work will receive a penalty of 5% deduction of total marks for the assessment, per work day. After a total of 10 working days has passed, the assignment will not be assessed and will receive 0 marks. This is in accordance with University Learning and Teaching Policies.

Academic integrity

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

Our website 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 Academic Honesty Education Module (AHEM) 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 Current Students website for more information on AI in assessments, including 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 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.

Support for students

The Support for Students Policy reflects the University’s 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	Workshop (2 hr)
Week 02	Social Networks	Workshop (2 hr)
Week 03	Smartphones and Digital Addictions	Workshop (2 hr)
Week 04	VR Training + Online Gaming and Gaming Disorder	Workshop (2 hr)
Week 05	VR unit distribution and MR/XR demonstration	Workshop (2 hr)
Week 06	Online Ethics and the Law + Report Writing Workshop #1	Workshop (2 hr)
Week 07	Information Architecture + Report Writing Workshop #2	Workshop (2 hr)
Week 08	Digital Interventions for Mental Health and Substance Use Disorders	Workshop (2 hr)
Week 09	VR UX Evaluation	Workshop (2 hr)
Week 10	Digital Privacy and Scams	Workshop (2 hr)
Week 11	Artificial intelligence	Workshop (2 hr)
Week 12	Support for Final Assessment	Project (2 hr)
Week 13	Major Work Presentations	Workshop (2 hr)

Attendance and class requirements

Attendance: This seminar series provides 2 hours of combined lectures/workshops per week. To succeed in this unit of study it is best to attend and participate in the seminar series as much as possible on a weekly basis, but students must attend 80% of scheduled classes, in accordance with the University of Sydney requirements. Penalties for under 80% of seminar attendance may be imposed by the Unit of Study Coordinator.

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

Readings will be provide through the Unit CANVAS site.

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. Apply knowledge of cyberpsychology and digital health research and interventions to effectively address consumer health issues
LO2. Understand and explain ethical issues relating to the application of cyberpsychology and digital health interventions
LO3. Critically evaluate the strengths and weaknesses of consumer e-Health communication and support tools online
LO4. Describe and critically evaluate cyberpsychology in an evolving digital health systems and consumer use

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.

This unit has been updated to include ongoing VR workshops whenever equipment is available each week the unit is taught.

Additional information

Work, health and safety

Do not attend class if you believe you may have a cold, flu or COVID-19 symptoms (i.e. runny nose, coughing, headache etc).

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

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

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

BIDH3146: Cyberpsychology in Digital Health

Semester 2, 2025 [Normal day] - 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

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links