Impact of carbon footprint information on inhaler prescribing intentions by general practitioners: protocol for an online factorial randomised experiment
Related Experiment Video
Updated: Jan 23, 2026

Spotting Cheetahs: Identifying Individuals by Their Footprints
Published on: May 1, 2016
Luise Kazda1, Timothy E Schlub2, Michelle Guppy3
1Wiser Healthcare Research Collaboration, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; NHMRC Healthy Environments and Lives (HEAL) National Research Network, University of Canberra, Canberra, ACT, Australia.
Background:
Many asthma patients experience suboptimal disease control and are disproportionally impacted by worsening environmental risk factors due to climate change. General practitioners (GPs) are well-placed and trusted to lead conversations to improve asthma management. The resulting treatment improvements have the potential to simultaneously reduce the significant greenhouse gas emissions from inhalers as a co-benefit.
Objectives:
This study aims to explore whether adding environmental impact information for respiratory inhalers can influence clinician prescribing while improving quality of care and investigates optimal ways to communicate environmental impacts to GPs.
Methods:
We will conduct a factorial (2 × 2 plus control) randomised online hypothetical experiment with Australian GPs. Following consent and baseline information on guideline-concordant maintenance-and-reliever-therapy ("MART") prescribing, participants will be randomised 1:1:1:1:1 to five conditions: A. Emissions impact: collective action/with graphic; B. Emissions impact: single-action/with graphic; C. Emissions impact: collective action/no graphic; D. Emission impact: single-action/no graphic; E.
Control:
no further information. The required sample size is 250 GPs. The primary outcome is participant choice of inhaler type (binary choice of dry powder or pressurised metered dose). Secondary outcomes include participant level of confidence in their choice, management choice anxiety, acceptability and trustworthiness of information received (all measured on Likert scales) and reasons for inhaler choice (free text). Study duration will be less than 10 min. We will use t-tests and chi-squared tests for univariable analysis of continuous and binary outcomes respectively, and t, F or likelihood ratio tests for regression models as appropriate.
Results:
Not applicable - this is a study protocol.
Conclusion:
This study will provide evidence on whether and how environmental impact information can influence prescribing intentions among GPs. Findings will inform future interventions aimed at aligning clinical and environmental goals in respiratory care.
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