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Understanding a population: A methodology for a population-based coastal safety survey

Drowning is a global public health problem, but accurately estimating drowning risk remains a challenge. Coastal drowning comprises a significant proportion of the drowning burden in Australia and is influenced by a range of behavioural factors (e.g. risk perception, knowledge, attitudes and behavio...

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Autores principales: Lawes, Jasmin C., Uebelhoer, Lea, Koon, William, Strasiotto, Luke, Anne, Frederic, Daw, Shane, Brander, Robert W., Mulcahy, Nick, Peden, Amy E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8362993/
https://www.ncbi.nlm.nih.gov/pubmed/34388222
http://dx.doi.org/10.1371/journal.pone.0256202
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author Lawes, Jasmin C.
Uebelhoer, Lea
Koon, William
Strasiotto, Luke
Anne, Frederic
Daw, Shane
Brander, Robert W.
Mulcahy, Nick
Peden, Amy E.
author_facet Lawes, Jasmin C.
Uebelhoer, Lea
Koon, William
Strasiotto, Luke
Anne, Frederic
Daw, Shane
Brander, Robert W.
Mulcahy, Nick
Peden, Amy E.
author_sort Lawes, Jasmin C.
collection PubMed
description Drowning is a global public health problem, but accurately estimating drowning risk remains a challenge. Coastal drowning comprises a significant proportion of the drowning burden in Australia and is influenced by a range of behavioural factors (e.g. risk perception, knowledge, attitudes and behaviours) that are poorly understood. These factors, along with those that impact exposure (e.g. coastal visitation and activity participation) all impact on drowning risk. While excellent mortality and morbidity data exists in Australia, a lack of coastal participation data presents challenges to identifying high-risk groups or activities and prioritising prevention efforts. This methods paper describes the development and evolution of an ongoing, annual, nationally representative online survey as an effective tool used to capture valuable data about the Australian population’s relationship with the coast. This paper explores how the survey is structured (12–14 sections spanning multiple topics and themes), the different question types used (including open text, 4-digit responses and categorical questions), the sample size (1400–1600 respondents), sampling strategy (using demographic quota sampling which can then be post-weighted to the population if required) and how topics and themes have changed over time to enhance the quality of data collected (i.e., wording changes to enhance participant comprehension or data usability and changing issue-specific ‘feature’ topics of interest such as campaign evaluation). How the survey is implemented online is described, both practically through to third-party recruitment processes and ethically to maximise anonymity of respondents and ensure data quality. Interim analyses indicate the impact of considering exposure when calculating fatal drowning rates, especially by activity (e.g., crude boating drowning rate 0.12 per 100,000 population vs 0.95 per 100,000 exposed population [relative risk = 8.01; 95% confidence interval: 4.55–14.10]). This study highlights lessons learned in the process of conducting a nationally representative coastal participation survey as well as the strengths and limitations of adopting this approach. Data collected will provide more detailed information on the skills, behaviours, knowledge and attitudes of coastal activity participants. Analyses of this unique dataset will inform research that will underpin development and evaluation of coastal drowning prevention initiatives prioritising those most at risk. It is hoped that the methods detailed within this study may be useful for other countries to develop similar approaches to understanding their own population.
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spelling pubmed-83629932021-08-14 Understanding a population: A methodology for a population-based coastal safety survey Lawes, Jasmin C. Uebelhoer, Lea Koon, William Strasiotto, Luke Anne, Frederic Daw, Shane Brander, Robert W. Mulcahy, Nick Peden, Amy E. PLoS One Research Article Drowning is a global public health problem, but accurately estimating drowning risk remains a challenge. Coastal drowning comprises a significant proportion of the drowning burden in Australia and is influenced by a range of behavioural factors (e.g. risk perception, knowledge, attitudes and behaviours) that are poorly understood. These factors, along with those that impact exposure (e.g. coastal visitation and activity participation) all impact on drowning risk. While excellent mortality and morbidity data exists in Australia, a lack of coastal participation data presents challenges to identifying high-risk groups or activities and prioritising prevention efforts. This methods paper describes the development and evolution of an ongoing, annual, nationally representative online survey as an effective tool used to capture valuable data about the Australian population’s relationship with the coast. This paper explores how the survey is structured (12–14 sections spanning multiple topics and themes), the different question types used (including open text, 4-digit responses and categorical questions), the sample size (1400–1600 respondents), sampling strategy (using demographic quota sampling which can then be post-weighted to the population if required) and how topics and themes have changed over time to enhance the quality of data collected (i.e., wording changes to enhance participant comprehension or data usability and changing issue-specific ‘feature’ topics of interest such as campaign evaluation). How the survey is implemented online is described, both practically through to third-party recruitment processes and ethically to maximise anonymity of respondents and ensure data quality. Interim analyses indicate the impact of considering exposure when calculating fatal drowning rates, especially by activity (e.g., crude boating drowning rate 0.12 per 100,000 population vs 0.95 per 100,000 exposed population [relative risk = 8.01; 95% confidence interval: 4.55–14.10]). This study highlights lessons learned in the process of conducting a nationally representative coastal participation survey as well as the strengths and limitations of adopting this approach. Data collected will provide more detailed information on the skills, behaviours, knowledge and attitudes of coastal activity participants. Analyses of this unique dataset will inform research that will underpin development and evaluation of coastal drowning prevention initiatives prioritising those most at risk. It is hoped that the methods detailed within this study may be useful for other countries to develop similar approaches to understanding their own population. Public Library of Science 2021-08-13 /pmc/articles/PMC8362993/ /pubmed/34388222 http://dx.doi.org/10.1371/journal.pone.0256202 Text en © 2021 Lawes et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lawes, Jasmin C.
Uebelhoer, Lea
Koon, William
Strasiotto, Luke
Anne, Frederic
Daw, Shane
Brander, Robert W.
Mulcahy, Nick
Peden, Amy E.
Understanding a population: A methodology for a population-based coastal safety survey
title Understanding a population: A methodology for a population-based coastal safety survey
title_full Understanding a population: A methodology for a population-based coastal safety survey
title_fullStr Understanding a population: A methodology for a population-based coastal safety survey
title_full_unstemmed Understanding a population: A methodology for a population-based coastal safety survey
title_short Understanding a population: A methodology for a population-based coastal safety survey
title_sort understanding a population: a methodology for a population-based coastal safety survey
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8362993/
https://www.ncbi.nlm.nih.gov/pubmed/34388222
http://dx.doi.org/10.1371/journal.pone.0256202
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