Using protection motivation theory to explain Australian's motivations to engage in individual and collective climate actions

Abstract Using an Australian sample, the current study investigated the usefulness of protection motivation theory (PMT) in predicting intentions for two climate actions—one individual action (limiting household heating and/or cooling) and one collective action (writing a letter to a local Member of Parliament urging them to take action to mitigate climate change). The data were analysed in two ways: (1) regression analysis, to examine the independent effects of coping and threat appraisals, and (2) latent profile analysis (LPA), to understand how the coping and threat appraisals may act in combination. The regression showed that PMT explained a significant amount of variance for both behavioural intentions. While perceived response efficacy and self‐efficacy were significant unique predictors of both behavioural intentions, perceived response costs were a significant unique predictor of heating and/or cooling intentions. Although the regression analysis suggests that people were more motivated by coping appraisals for both outcomes, the LPA indicates that the coping appraisals are unlikely to lead to stronger intentions unless individuals perceive climate change to be sufficiently threatening. PMT research could benefit from employing LPA to identify participant profiles with heightened likelihoods of reporting stronger intentions to participate in climate actions.

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Publication Details

Journal
Asian Journal Of Social Psychology
Published
2024-12-27
DOI
https://doi.org/10.1111/ajsp.12660
Citations
3
Primary Topic
Environmental Education and Sustainability
Type
article
Field-Weighted Citation Impact
2.13

Funders

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article

Using protection motivation theory to explain Australian's motivations to engage in individual and collective climate actions

Matthew Mackay, Anna Klas, Emily Kothe, Julian W. Fernando et al.
3 citations
Asian Journal Of Social Psychology
Environmental Education and Sustainability
2.13
article

Using protection motivation theory to explain Australian's motivations to engage in individual and collective climate actions

Matthew Mackay, Anna Klas, Emily Kothe, Julian W. Fernando, Mathew Ling
article en
3 citations

Abstract

Abstract Using an Australian sample, the current study investigated the usefulness of protection motivation theory (PMT) in predicting intentions for two climate actions—one individual action (limiting household heating and/or cooling) and one collective action (writing a letter to a local Member of Parliament urging them to take action to mitigate climate change). The data were analysed in two ways: (1) regression analysis, to examine the independent effects of coping and threat appraisals, and (2) latent profile analysis (LPA), to understand how the coping and threat appraisals may act in combination. The regression showed that PMT explained a significant amount of variance for both behavioural intentions. While perceived response efficacy and self‐efficacy were significant unique predictors of both behavioural intentions, perceived response costs were a significant unique predictor of heating and/or cooling intentions. Although the regression analysis suggests that people were more motivated by coping appraisals for both outcomes, the LPA indicates that the coping appraisals are unlikely to lead to stronger intentions unless individuals perceive climate change to be sufficiently threatening. PMT research could benefit from employing LPA to identify participant profiles with heightened likelihoods of reporting stronger intentions to participate in climate actions.

Asian Journal Of Social PsychologyVol. 28(1)
Deakin University (AU), Neami National (AU)
Deakin University
Climate action
Openalex Percentile: Top 11%
Environmental Education and Sustainability
2.13
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Using protection motivation theory to explain Australian's motivations to engage in individual and collective climate actions — Matthew Mackay, Anna Klas, et al. · Asian Journal Of Social Psychology (2024) | TGRS Research Map | TGRS