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Protocol for developing a mental imagery intervention: A randomised controlled trial testing a novel implementation imagery e-health intervention to change driver behaviour during floods
Journal article   Open access   Peer reviewed

Protocol for developing a mental imagery intervention: A randomised controlled trial testing a novel implementation imagery e-health intervention to change driver behaviour during floods

K Hamilton, Jacob Keech, A E Peden and M S Hagger
BMJ Open, Vol.9(2), e025565
2019
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Published VersionPDF - Published Version (Open Access)CC BY-NC V4.0 Open Access
url
https://doi.org/10.1136/bmjopen-2018-025565View
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Abstract

driving drowning flooded waterways mental imagery social-cognitive theories water safety
Introduction Drowning due to driving into floodwater accounts for a significant proportion of all deaths by drowning. Despite awareness campaigns such as 'If it's flooded, forget it', people continue to drive into floodwater. This causes loss of life, risk to rescuers and damage to vehicles. The aim of this study was to develop and evaluate an online e-health intervention to promote safe driving behaviour during flood events. Methods and analysis The study will use a 2×3 randomised controlled trial in which participants are randomised into one of two conditions: (1) education about the risks of driving into floodwater or (2) education about the risks of driving into floodwater plus a theory-based behaviour change intervention using planning and imagery exercises. The effect of the intervention on the primary outcome, intention to drive through floodwater and the secondary outcomes will be assessed using a series of mixed-model analysis of covariances. Ethics and dissemination The study has been approved by the Griffith University Human Research Ethics Committee. Participants will review a study information sheet and provide informed consent prior to commencing participation. Results will be disseminated through peer-reviewed publications, industry reports, media releases and at academic conferences. Deidentified data will be made publicly available following publication of the results.

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