Enhancing climate change communication: Strategies for profiling and targeting Australian interpretive communities

TitleEnhancing climate change communication: Strategies for profiling and targeting Australian interpretive communities
Publication TypeReport
Year of Publication2013
AuthorsHine, DW, Phillips, WJ, Reser, JP, Cooksey, RW, Marks, ADG, Nunn, PD, Watt, SE, Ellul, MC
Date Published06/2013
InstitutionNational Climate Change Adaptation Research Facility
CityGold Coast
ISBN Number978-1-925039-20-7
Keywordsaudience segmentation analysis, communication, Extended Parallel Processing Model, interpretive communities, latent profile analysis, online survey, strategy, synthesis and integrative research

This research aimed to provide practical information about how to design communications on climate change adaptation and target these to the Australian population.   This was achieved by: (1) identifying and increasing awareness of different climate change audiences in Australia, and (2) evaluating how each audience responds to different types of climate change messages. 

Phase 1 of the study used audience segmentation analysis to identify the main climate change interpretive communities within Australia; that is, groups of Australians who share similar views and understandings about climate change.   A nationwide sample consisting of 3,096 Australian residents (aged 15 to 108 years, 47% male and 53% female) completed an online survey assessing a broad range of psychological and behavioural factors related to climate change.   Latent profile analysis applied to the psychological variables suggested that this Australian sample consists of five distinct interpretive communities: Alarmed (26%), Concerned (39%), Uncertain (14%), Doubtful (12%), and Dismissive (9%). Validation analyses revealed that these groups differed in terms of how they responded to perceived climate change threats, and also in their support for particular climate change mitigation and adaptation policies.   

Phase 2 of the project examined how Australian interpretive communities respond to climate change adaptation messages and identified the specific message attributes that drive these responses. 1,031 Australian residents (aged 18 to 66 years, 49.8% male, 50.2% female) completed an online survey assessing a similar set of psychological and behavioural responses to climate change to those assessed in Phase 1.   Respondents subsequently viewed six climate change adaptation messages that were randomly allocated from a pool of 60 messages sourced from the internet.   Messages were pre-coded on 10 communication cues (e.g., language complexity, normative influence), and respondents rated them on four judgement dimensions: perceived threat, perceived efficacy, fear control (message rejection), and danger control (message acceptance).   

Latent profile analysis applied to the psychological variables identified three climate change interpretive communities in this sample: Alarmed (34.4%), Uncommitted (45.2%), and Dismissive (20.3%).   Judgement analysis methodology (Cooksey, 1996) found that the three interpretive communities based their threat and efficacy evaluations on unique combinations of communication cues, and that high perceived threat and high perceived efficacy were related to message acceptance for all communities.   

  • Effective messages for Dismissive respondents used simple language and did not emphasise descriptive social norms.   
  • Uncommitted audience members responded positively to messages that focused on preventing losses and had a strong emotional component.   
  • Alarmed respondents preferred messages that focused on local issues and had a collectivist frame. 


Providing specific adaptation advice in messages was found to be effective for all communities. The results largely support the Extended Parallel Processing Model of risk communication (Witte, 1992), and suggest that message attributes should be adjusted to effectively communicate with different climate change interpretive communities within Australia.

Refereed DesignationRefereed