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Unit outline_

BIDH3146: Cyberpsychology in Digital Health

Semester 2, 2023 [Normal day] - Camperdown/Darlington, Sydney

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 Department of Medical Sciences
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
Lecturer(s) Andrew Campbell, andrew.campbell@sydney.edu.au
Type Description Weight Due Length
Assignment Podcast
Podcast on investigating the evidence-base of a Digital Health initiative.
15% Week 05
Due date: 01 Sep 2023 at 23:59

Closing date: 08 Sep 2023
5min audio recording
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment Report
Report and recommendations on UX for Digital Health online information
35% Week 10
Due date: 13 Oct 2023 at 23:59

Closing date: 20 Oct 2023
1500 words
Outcomes assessed: LO1 LO2 LO3 LO4
Presentation group assignment Cyberpsychology Documentary
Group Documentary on the Cyberpsychological impact of a Digital Technology.
40% Week 13
Due date: 01 Nov 2023 at 11:59

Closing date: 10 Nov 2023
Minimum 15 min - Maximum 20min video
Outcomes assessed: LO1 LO2 LO3 LO4
Online task Workshop Engagement and Discussion Board
Workshop Group work + Discussion Board Contributions
10% Week 13
Due date: 03 Nov 2023 at 23:59

Closing date: 10 Nov 2023
Weekly attendance
Outcomes assessed: LO1 LO4 LO3 LO2
group assignment = 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 20min 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 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:

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 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 Introduction Workshop (2 hr) LO1 LO4
Week 02 Online identity formation Workshop (2 hr) LO1 LO4
Week 03 Social networks Workshop (2 hr) LO1 LO2 LO3 LO4
Week 04 Smartphones and digital addictions Workshop (2 hr) LO1 LO2 LO3 LO4
Week 05 Online ethics and the law + Project workshop Workshop (2 hr) LO1 LO2 LO3
Week 07 Information architecture + Report writing workshop Workshop (2 hr) LO1 LO2 LO3 LO4
Week 08 Cyber-therapies Workshop (2 hr) LO1 LO2 LO3 LO4
Week 10 Online gaming and gaming disorder Workshop (2 hr) LO1 LO4
Week 11 VR/MR/XR Workshop (2 hr) LO1 LO3 LO4
Week 12 Artificial intelligence Workshop (2 hr) LO1 LO2 LO3 LO4
Week 13 Major Work Presentations Workshop (2 hr) LO1 LO2 LO3 LO4

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 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. 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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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 taught.

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.