Estimating climate change and mental health impacts in Canada: A cross-sectional survey protocol.

• Published in: PLOS ONE
• Main Authors: Sherilee L Harper, Ashlee Cunsolo, Breanne Aylward, Susan Clayton, Kelton Minor, Madison Cooper, Rachael Vriezen
• Format: Article in Journal/Newspaper
• Language: English
• Published: Public Library of Science (PLoS) 2023
• Subjects: Medicine; R; Science; Q; Canada; inuktitut
• Online Access: https://doi.org/10.1371/journal.pone.0291303; https://doaj.org/article/8f1af848e61446429419020476201e26

Climate change has severe and sweeping impacts on mental health. Although research is burgeoning on mental health impacts following climate and weather extremes, less is known about how common these impacts are outside of extreme events. Existing research exploring the prevalence of psychosocial responses to climate change primarily examines university students and uses non-random sampling methods. Herein, our protocol outlines an approach to data collection, processing, and analysis to estimate the population prevalence, magnitude, and distribution of mental health responses to climate change in Canada. A cross-sectional survey of youth and adults aged 13 years and older in Canada will be administered over the course of one year. The questionnaire will take approximately 10 minutes to complete orally and will be administered in English, French, and Inuktitut. The survey will consist of six sections: (1) self-reported past experiences of climate change; (2) self-reported climate-related emotions; (3) self-reported past and current impacts, anticipatory impacts, and vicarious experiences; (4) self-reported subclinical outcomes; (5) self-reported behavioural responses; and (6) demographics. A multi-stage, multi-stratified random probability sampling method will be used to obtain a sample representative of the Canadian population. We will use two different modes of recruitment: an addressed letter sent by postal mail or a telephone call (landlines and cellular). Population-weighted descriptive statistics, principal component analysis, and weighted multivariable regression will be used to analyse the data. The results of this survey will provide the first national prevalence estimates of subclinical mental health responses to climate change outcomes of people living in Canada.