109 collective transilience in the face of climate change Collective Transilience, Individual Transilience, and Adaptation Intentions We used the package cocor in R (Diedenhofen & Musch, 2015) to test whether collective transilience, compared to individual transilience, is more strongly associated with community-based adaptation intentions and less strongly associated with individual adaptation intentions (Hypothesis 2). Collective transilience was indeed more strongly related to the evaluation of the SensHagen initiative and to communitybased adaptation intentions, compared to individual transilience (i.e., Zou’s confidence intervals did not include zero; Zou, 2007; see Table 4.2). Yet, we did not find a significant difference in the strength of the correlations between the other adaptation intentions and individual and collective transilience, respectively (i.e., Zou’s confidence intervals included zero; see Table 4.2). Hence, we found partial support for Hypothesis 2 in the case of community-based adaptation measures, and no support for Hypothesis 2 in the case of individual adaptation intentions. We conducted a series of two-step hierarchical multiple regressions using the jmv package (Jamovi, 2021) to assess whether collective transilience predicts unique variance in community-based intentions when controlling for individual transilience. For information seeking, which is a dichotomous variable, we conducted a hierarchical binary logistic regression. We applied the Bonferroni correction to limit chances of type I error, leading to an adjusted significance level of p < .008 (i.e., .05/6). For each dependent variable, individual transilience was entered at Step 1, and collective transilience was entered at Step 2. Multicollinearity was not an issue (VIF = 1.48). Table 4.3 shows that individual transilience was significantly related to all indicators of individual and community-based adaptation. As expected, adding collective transilience to the model consistently led to a significant increase in explained variance. Interestingly, in all cases collective transilience became the only significant predictor in the model. The effect sizes for collective transilience were small-to-medium (i.e., .02 < f2 < .10; Selya et al., 2012), except for community-based adaptation intentions, where the effect was medium (i.e., around f2 = .15; Selya et al., 2012). Thus, collective transilience seems more relevant than individual transilience for predicting different types of climate change adaptation intentions. 4
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