Study 1. Understanding the Role of Psychological Distance in Preventing the Spread of Kauri Dieback: A Path Analysis

Background: Psychological distance is a tool based on construal level theory, whereby the level of abstraction an individual imagines an event is related to the level of personal significance of the event. Interventions to reduce psychological distance have been used to increase climate change mitigation intentions. The current study extends this concept to managing kauri dieback and explores possible causal pathways for further investigation.

Methods: A survey assessing beliefs and behaviours related to kauri dieback was completed by a sample of 451 people residing in New Zealand who had visited a kauri forest in the past four years. Two path analyses were conducted to determine whether the effects of three exogenous predictor variables (pro-environmental worldview, trust in authority, and geographic distance) on self-reported boot cleaning and track use compliance behaviours were mediated by psychological distance to kauri dieback.

Results: Two path analyses indicated the predicted effects of worldviews, trust, and geographic distance on compliance were partially mediated by psychological distance. Direct paths from environmental worldview and trust to compliance remained statistically significant in both models after controlling for psychological distance.

Conclusions: Psychological distance is a reliable predictor of respondents’ boot cleaning and track use compliance. Interventions to increase psychological distance may be beneficial for increasing compliance, although the effects were modest and other potential determinants of compliance also require investigation. Direct paths from worldviews and trust on compliance, after controlling for psychological distance, suggests that other mediating mechanisms are likely operating. Future research should attempt to identify these mechanisms.

Study 2. Understanding the Drivers and Barriers to Preventing the Spread of Kauri Dieback: An Audience Segmentation Approach

Background: Audience segmentation and driver/barrier analysis provide an important foundation for behavioural change interventions. The current study used Michie et al.’s (2011) COM-B framework to assess forest users’ capabilities, opportunities, and motivations for two behaviours linked to the spread of kauri dieback: boot cleaning and responsible track use.

Methods: COM drivers and barriers linked to best-practice boot cleaning and track use were assessed using an online survey. The survey was administered to 451 New Zealand residents who had visited the Waitākere and/or the Hunua Ranges within the past four years. Stepwise regression analysis was conducted to identify the strongest COM predictors of boot cleaning and track use compliance. Audience segmentation using MPLUS was conducted to identify distinct barrier/drive profile groupings within the sample; which were used to predict degree of compliance.

Results: Stepwise regression analysis revealed forest users were significantly more likely to comply with boot cleaning guidelines if they were habitual boot cleaners; worried about spreading kauri dieback; were aware of the correct method of boot cleaning; and would not use track if there was no cleaning solution. Forest users were significantly less likely to comply with boot cleaning guidelines if they considered boot cleaning to be inconvenient and were averse to using the cleaning chemicals. A second stepwise regression found that forest users were significantly less likely to comply with track use guidelines if they felt they were unlikely to spread kauri dieback; that mitigation efforts would be unsuccessful; that it is too time consuming to use alternative routes; and if they held the forest and its tracks as part of their identity. In contrast, forest users were significantly more likely to comply with track use guidelines if they wished to protect kauri and followed rules as a habit.

Latent profile analysis of COM variables produced three-profile solutions for boot cleaning behaviours (named Conflicted, Receptive, and Engaged) and track use behaviours (named Non-Compliant Nature Lovers, Uncommitted, and Engaged). For boot cleaning, members of the Engaged segments were more likely to comply with guidelines than members of the Conflicted and Receptive segments. For track use, members of the Engaged segment were more likely to comply with track guidelines than Uncommitted respondents, who, in turn were more like to comply than the Non-Compliant Nature Lovers.

Conclusions: We employed two analysis strategies to demonstrate the utility of COM-B framework for identifying key drivers and barriers related to boot cleaning and track use compliance: two behaviours linked to the spread of kauri dieback. The results of the study can be used to tailor behaviour change interventions aimed at increasing the drivers and reducing the barriers for these two behaviours, for each of the audience segments identified.