This article is part of the Iris Ethics Knowledge Base; you can find a directory of all articles here.
Overview
These decision trees give step-by-step guidance for the scenarios most commonly encountered when working out whether ethics review is required and which pathway applies. They are drawn from the flow charts Iris Ethics has published for the National Statement Navigator and for consent. They are not exhaustive and should be read alongside the substantive guidance in the Knowledge Base.
Decision tree 1: Do I need ethics review?
- Is the activity an investigation to gain knowledge with an intention to generalise the findings?
→ No: it is not human research, and ethics review is not required.
→ Yes: proceed to step 2. - Is it conducted with or about people, or their data or biospecimens? (NS: Purpose, scope and limits of this document)
→ No: not human research; ethics review is not required.
→ Yes: proceed to step 3. - Does it meet any of the NS 5.1.17 exemption criteria (for example, non-identifiable data, anonymous surveys with no more than discomfort, or publicly available statutory data)?
→ Yes: may be eligible for a statement of exemption from ethics review; the QA Guidance triggers also need to be checked for evaluation and QA activities.
→ No: formal ethics review is required.
Decision tree 2: Which review pathway applies?
- Is there a foreseeable risk of harm: physical, psychological, devaluation of personal worth, cultural, social, economic or legal? (NS Chapter 2.1)
→ Yes: full HREC review is required (NS 5.1.11).
→ No: proceed to step 2. - Is the only foreseeable risk discomfort, with or without burden or inconvenience?
→ Yes: lower risk review is appropriate (NS 5.1.10–5.1.14).
→ No: if there is no foreseeable risk at all, reassess whether the activity meets the exemption criteria in step 3 of decision tree 1.
Decision tree 3: Is consent required, and how should it be sought?
- Will participants provide information directly, for example through a survey, interview or focus group?
→ Yes: informed consent is required unless a waiver is granted by the review body (NS 2.3.9–2.3.12).
→ No: proceed to step 2. - Will existing data about identifiable individuals be used without their knowledge?
→ Yes: consent or a waiver is required; a waiver requires approval by the review body, and for personal information in medical research or personal health information, only an HREC may grant it (NS 2.3.9).
→ No: assess whether the data meets the NS 5.1.17 exemption criteria. - What recruitment mechanism is proposed: public/open, or selective? Each carries different risks: open recruitment raises questions about who self-selects into the sample, while selective recruitment raises questions about undue influence from whoever holds the participant list. Design the consent process to address the risks specific to the mechanism chosen.
- For self-completed surveys: has the project decided how non-completion will be treated? As a default, Iris Ethics' guidance is that non-completion of a survey should be treated as a withdrawal of consent, not simply as missing data. This matters because most survey platforms do not, by default, distinguish between a respondent who dropped out from boredom or distraction and one who has withdrawn consent; treating both as ordinary attrition risks using data from someone who has withdrawn. Mitigations include: reaffirming consent before each survey section, offering an explicit opt-out for sensitive questions (for example, income), and sending reminder emails to incomplete respondents where this is possible.
None of these decision trees address the secondary use of previously collected data; see Secondary use of data for that scenario. For more detailed guidance see What counts as research, Lower risk vs full HREC review, and General consent requirements.
This page was last updated on 16 September 2026.
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This article makes reference to the National Statement on Ethical Conduct in Human Research 2025. It is intended as practical guidance and does not constitute legal advice.
AI Disclosure: Resources in this library were prepared using Large Language Models with input from Iris Ethics staff who guided the scope and design. Subsequent revisions and final versions were developed and approved by Iris Ethics staff.