DOI: 10.25903/mvvk-kz75
title: Climate Change Anxiety survey data

description: <p>We collected an initial 326 survey responses that we evaluated against three criteria for data cleaning. Omitted responses included 1) participants who did not provide informed consent; 2) incomplete, inconsistent, or flatline responses; 3) participants who completed the study in &lt;180 seconds.</p>

<p>After data cleaning, a final sample of 237 valid responses included 70.0% female, 26.6% male, 2.1% non-binary, and 1.3% preferred not to say. Participants’ age ranged from 18–64 years (M = 24.34, SD = 8.26).</p>

<p><strong>Measures</strong></p>

<p><strong>Nature connectedness</strong> (Richardson et al., 2019) was measured using the 6-item Nature Connection Index (NCI). Responses are made on a 7-point Likert-type scale (1 = completely agree, 7 = completely disagree). The six items draw on five pathways to nature connectedness: emotion, beauty, contact, meaning and compassion. Responses were transformed using a weighted points index ranging from zero to 100 (Richardson et al., 2019). Richardson et al. reported high internal consistency of the measure at an alpha of 0.92.</p>

<p>Doubts regarding climate change were measured using the 12-item Climate Change Skepticism Questionnaire (CCS-Q) (de Graaf et al., 2023). Responses are made on a 7-point Likert-type scale (1 = totally disagree, 7 = totally agree); 4 items are reverse scored.</p>

<p>Perceptions about climate change were measured using the 14-item Climate Change Perceptions Scale (CCPS) (van Valkengoed et al., 2021). Responses are made on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree).</p>

<p>We followed guidance from van Valkengoed et al. by presenting the three ‘perceived reality of climate change’ items first, in random order (2 of the items are reverse scored), followed by all other climate change perceptions items (11 items) in random order. These included items relating to causes (3 items), valence of consequences (3 items), spatial distance (3 items, all reverse scored), and temporal distance (2 items).</p>

<p>For the 11 climate change perception items, the option ‘I do not believe climate change exists’ (0) was added for the benefit of those who disagreed that climate change is real in the perceived reality of climate change items. Any ‘0’ responses (after reverse scoring) were coded as ‘missing’ and excluded from analyses. Van Valkengoed et al. reported Cronbach alpha values between .89-.98 for the subscales.</p>

<p>Anxiety about climate change was measured using the 22-item Climate Change Anxiety Scale (CCAS) (Clayton & Karazsia, 2020). Responses are made on a 5-point scale (1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = Almost always) to indicate “how often the statements are true of you”.</p>

<p>The full scale includes 8 items measuring cognitive-emotional impairment, 5 items measuring functional impairment, 3 items measuring experience of climate change, and 6 items measuring behavioural engagement.</p>

<p>In the present study, we operationalised anxiety about climate change as the average of 2 subscales (cognitive-emotional impairment and functional impairment, as per Clayton and Karazsia).</p>

<p>Clayton and Karazsia also advised they did not identify clear cutoff points for anxiety in their measure, but suggested that, “if 25% of a sample report that climate change makes it difficult for them to function more often than “sometimes”, this indicates that climate change is beginning to have a significant effect on mental health” (p. 6).</p>

<p><strong>Assumptions Testing</strong></p>

<p>Prior to analysing the data, several assumptions were assessed. Firstly, Shapiro-wilk tests for all outcome variables were significant, indicating a violation in the assumption of normality. However, Bennett et al. (2022) argued that Shapiro-wilk tests often indicate departures from normality that are inconsequential because the tests are overly sensitive. Moreover, visual inspection of histograms did not show severe violations in normality, thus we kept the existing dataset.</p>

<p>Secondly, the normal probability plot of standardised residuals and scatterplots of standardised residuals against standardised predicted values implied that the assumption of normality, linearity, and homoscedasticity of residuals were met.</p>

<p>Thirdly, there was no multicollinearity between the outcome variables (i.e., r &gt; . 90); for the predictor variables, variance inflation factor (VIF) and tolerance coefficients were &lt;10 and &gt;.1 respectively.</p>

<p>Next, Box’s test was non-significant, F(10, 48690.87) = 1.59, p = .10, fulfilling the assumption of homogeneity of the variance-covariance matrix.</p>

<p>Lastly, there were no univariate outliers, as indicated by a maximum Cook’s distance of &lt; 1. However, a comparison between the maximum Malalanobis distance and the critical chi-square value suggested 4 multivariate outliers. Accordingly, we removed them, and the subsequent analyses were conducted using N = 233.</p>

<p><strong>Software/equipment used to create/collect the data:</strong> JCU Qualtrics licence</p>

<p><strong>Software/equipment used to manipulate/analyse the data:</strong> IBM SPSS Statistics version 29.01</p>