The role of trait mindfulness in moderating climate distress during wildfire season

Joanna Y. Guan; Ethan G. Dutcher; Philippe Goldin; Sarah E. Ahmadi; Elena Fromer; Sheri D. Weiser; Edward Maibach; Aric A. Prather; Elissa S. Epel

doi:10.1371/journal.pclm.0000524

Abstract

Extreme worry about climate change can lead to maladaptive climate distress, defined as avoiding negative thoughts and feelings about climate. Avoiding negative thoughts and feelings (“experiential avoidance”) is a risk factor for clinical depression and anxiety. Greater ability for mindful metacognition may lead to greater tolerance of negative feelings and thus less maladaptive climate distress. To test this hypothesis, we assessed climate distress in a community sample of adults (n = 501) from the San Francisco Bay Area, before and after the severe wildfire season in 2021. Specifically, we measured experiential avoidance of distress about climate at baseline and 6 months later after the wildfire season. At baseline, climate distress was higher in women, and among people with lower trait mindfulness, higher generalized anxiety, and more liberal political ideology. Climate distress significantly increased across the sample after the wildfire season. However, this increase occurred in individuals with low mindfulness, but not high mindfulness, at baseline. As climate disasters become more frequent and severe, the ability to face the existential threat without severe distress will be an important adaptive ability and is hypothesized to help people stay engaged in climate actions. Here, we show that mindfulness may be a useful aid in maintaining lower climate distress over time, despite wildfire exposure.

Citation: Guan JY, Dutcher EG, Goldin P, Ahmadi SE, Fromer E, Weiser SD, et al. (2024) The role of trait mindfulness in moderating climate distress during wildfire season. PLOS Clim 3(12): e0000524. https://doi.org/10.1371/journal.pclm.0000524

Editor: Kim-Pong Tam, The Hong Kong University of Science and Technology, HONG KONG

Received: December 18, 2023; Accepted: November 19, 2024; Published: December 10, 2024

Copyright: © 2024 Guan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data Availability Statement: The data described in this article are available on the Open Science Framework: https://osf.io/g2hyk/.

Funding: This work was supported by the National Institute of Aging (NIA) R24AG048024 (to ESE) and the Fisher Family Trust. Neither funders had no role in the study design, collection, analysis, or interpretation of data, writing the manuscript, or the decision to submit the paper for publication.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Wildfires and climate distress

Climate events such as heatwaves, drought, and wildfires are occurring at an accelerating pace because of global warming [1,2], and pose an immense threat to human life, health, and well-being. While the common causes of wildfires have been documented to be human-related (e.g., Wallow Fire), powerline issues (e.g., Camp Fire), or natural disasters (e.g., from lightning), the conditions due to climate change have and will continue to make containing these fires extremely difficult. Regardless of how a wildfire started, climate-related factors contribute to the challenges of managing wildfires such as warmer temperatures, shorter winters (e.g., earlier snowbelt), and increased drought [3]. As a result of climate change, wildfire frequency, size, and severity are predicted to continue to increase over the next century [3]. In California, residents are not exposed to harsh and extreme climate change, such as in the Global South, with more severe effects on health and mental health, but rather to intermittent climate events, including wildfires, heatwaves, and drought [4]. Nevertheless, these unpredictable exposures and the increasing awareness of the worsening climate crisis globally can contribute to increasing levels of climate distress including feelings of anxiety, sadness, and hopelessness. It can also contribute to maladaptive emotion regulation responses—denial and avoidance of distressing thoughts and emotions about climate change which is a form of “experiential avoidance,” reviewed in detail below [5–7]. The current study addresses predictors of maladaptive climate distress, which we define as experiential avoidance, and whether levels increase with time and exposure to a severe wildfire season.

As reviewed by Hrabok and colleagues, the mental health impacts of wildfire exposure can be significant, including increased risk of developing PTSD, depression, suicidality, anxiety disorders, and substance use disorders, especially in those with pre-existing psychological disorders [8]. For example, among adult clients of a mental health system in San Diego in 2007, living in a wildfire evacuation area was related to more severe stress, anxiety, fear, and depression [9]. Similarly, many people exposed to the 2012 Arizona Wallow Fire were still experiencing high levels of distress (as measured on the Kessler Psychological Distress Scale) one year later, an impact that was moderated by the financial impact of the fire [10].

In 2020, the state of California experienced 5 of its largest 20 wildfires by acreage since official record-keeping began in 1932; similarly, in 2021, the state experienced 4 of its largest 20 wildfires [11]. Not surprisingly, studies in California have linked wildfire exposure to long-term mental health impacts. For example, six months after the 2018 Camp Fire, people directly exposed (vs. indirectly exposed or not exposed) to the fire’s impacts were more likely to have symptoms of PTSD and depression [12] as well as heightened frontal brain responses on electroencephalography that have been observed in PTSD [13]. Given the increasing frequency of climate events, it is essential to identify factors that may buffer against the development of climate-related mental health problems.

Climate distress and climate behaviors

Climate distress can be a driver for behavioral change and eco-engagement [14] or it can overwhelm and immobilize a person via a variety of cognitive, emotional, and functional impairments [15] that render a person ineffective and non-agentic. Specifically, high levels of climate distress can cause powerful emotional responses such as fear, hopelessness, powerlessness, and despair [16–18] that lead to recoiling, and behavioral inhibition due to emotional and experiential avoidance.

Paradoxically, those experiencing climate distress are also more likely to be engaged in environmental behaviors and climate advocacy. For example, a recent large survey in Finland found climate worry and hope correlated positively with each other and with climate action [19], and a US survey found climate distress was related to greater past engagement in collective and current intentions to engage [20]. These studies highlight the dual role of climate anxiety in enhancing climate action, adaptive coping, and also enhancing experiential avoidance. Clearly, climate distress is multifaceted and likely has complex contextual conditions and moderators. Here, we are focusing on emotion regulation of climate distress. Experiential avoidance, in general, is a robust predictor of poor mental health. In this study, we are particularly interested in understanding the relationship between trait mindfulness and maladaptive climate distress, which we define as experiential avoidance of climate-related thoughts and emotions.

Maladaptive emotion regulation (experiential avoidance) to the climate crisis

Climate change is becoming more tangible with the news and the increasing frequency of climate disasters [21]. In the face of climate change threats which are largely outside of personal control, some people use defensive and self-protective strategies such as rationalization, avoidance, and denial [22]. Similarly, perceptions of closeness to climate change events have been associated with intense emotional reactions like avoidance of distressing emotions and thoughts [23]. While avoidance and denial can be adaptive in the short run for acute crises, reliance on these strategies can lead to more anxiety and depression over time, as reported in several community-based studies [24]. A meta-analysis found that in people with clinical psychiatric conditions, high levels of experiential avoidance are associated with more severe levels of depression and anxiety [25]. Given the impact of experiential avoidance on long-term mental health, and the need for a resilient and prepared mindset to deal with the worsening crisis, it is important to understand predictors of flexible emotional responding vs. rigid maladaptive emotional responses of experiential avoidance to climate change.

Mindfulness may buffer stress responses to climate events

Many models of mindfulness include how mindfulness skills promote emotion regulation. Mindfulness is thought to promote self-regulation through reperceiving, a shift in seeing thoughts as just thoughts [26]. The Monitoring and Awareness Model of Mindfulness [27] posits that mindfulness skills can promote emotion regulation through a set of awareness and monitoring skills that improve cognitive control, and especially through a set of equanimity skills (acceptance, non-judgment) that reduces emotional reactivity [27]. The Dual Mode Model of Mindful Emotion Regulation [28] integrates the Extended Process Model of Emotion Regulation Components with the Monitoring and Awareness Model, proposing that mindfulness skills can be used for emotion regulation through cognitive processes and also that mindfulness can be a state or trait that affects emotion regulation. Trait mindfulness measures may serve as a crude proxy for the set of skills for both mindfulness and emotion regulation [28]. Trait mindfulness measures the tendency to use mindfulness skills, paying attention to inward or external cues, nonjudging of thoughts and emotions, and mindfulness interventions specifically train in these skills with mindfulness meditation and informal use of mindfulness [28].

It is well established that higher mindfulness can be protective by buffering deleterious mental health effects [29]. In response to mindfulness interventions, trauma-exposed individuals report lower depression, anxiety, and perceived stress [30,31]. There are no mindfulness-based interventions that we are aware of for climate trauma-exposed individuals, although some interventions for those exposed to climate disasters or ongoing harsh conditions have used psychological coping skill training to reduce climate distress [32].

Several studies have shown cross-sectional associations between trait mindfulness and psychological well-being following climate-related events. In a study looking at adolescent mental health six months after a severe tornado in Yancheng, China, higher trait mindfulness was associated with lower PTSD and depressive symptoms, as well as lower social functioning impairment [33]. In a sample of 2018 Camp Fire survivors, mindfulness was associated with lower levels of depression and anxiety, but not PTSD, six months after the fire [34]. A US-based study found that trait mindfulness was negatively correlated with PTSD, internalizing, and externalizing symptoms 3 months after hurricane exposure [35]. Nevertheless, the cross-sectional nature of these associations limits causal inference.

Here we pose a potential model (Fig 1) of climate event exposure, maladaptive climate distress, and the role of mindfulness. People are exposed to climate traumas by media or personal exposure which contributes to some level of negative climate emotions. Those high in trait mindfulness may habitually regulate climate emotions with more adaptive emotion regulation strategies such as reperceiving, cognitive reappraisal, and acceptance, and these may help prevent climate emotions from growing to prolonged intense emotions. Those low in trait mindfulness may tolerate negative climate emotions less effectively, and use more maladaptive climate emotion regulation strategies such as experiential avoidance. This in turn may put them more at risk of anxiety and depression, as well as make them less likely to engage in climate mitigation actions.

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Fig 1. Model of how trait mindfulness potentially moderates levels of maladaptive climate distress.

https://doi.org/10.1371/journal.pclm.0000524.g001

The current study

In this study, we sought to measure a form of climate distress–maladaptive regulation of negative emotions about the climate crisis–and examine the extent to which mindfulness may be able to buffer the distress. Maladaptive emotion regulation is a strong vulnerability factor for poor mental health, and likely an impediment to people engaging in climate action, which is one of the few ways to help mitigate existential distress about the climate crisis. To measure maladaptive climate distress, we adapted a validated measure of experiential avoidance of distressing thoughts and emotions, the Acceptance and Action Questionnaire (AAQ-2) [36] to focus on thoughts and feelings related to climate change. Leveraging our prospective measurement of baseline trait mindfulness before a fire season involving 4 of the 20 largest fires on record in California, we examined whether baseline mindfulness predicted differential trajectories of climate distress across this period. We also tested for associations between climate distress and several other individual differences, including political ideology, which has been associated with the degree of concern about climate change, adoption of climate change mitigation behaviors, and attitudes toward the environment [37,38].

Hypothesis 1: Participants with greater trait mindfulness at baseline will also report lower climate distress at baseline.
Hypothesis 2: Participants with greater trait mindfulness at baseline will report a decrease in climate distress from baseline to follow-up (i.e., 6 months later).

Methods

Study procedures

Participants mostly residing in the San Francisco Bay Area were recruited using multiple methods including outreach via social media, local radio, and local news begin early March 2021 and ended April 2021 as part of a larger study examining antibody response to the COVID-19 vaccine [39]. Eligible participants were healthy volunteers who were ≥18 years old. Participants provided written informed consent and completed a baseline survey and a follow-up survey six months after the initial vaccination, as part of the procedures for the larger parent study. The median completion dates were in March 2021 for the baseline survey and October 2021 for the follow-up survey. The five largest fires in California in 2021 (i.e., the Dixie Fire, the Monument Fire, the Caldor Fire, the River Complex Fire, and the Antelope Fire), all occurred in Northern California and together resulted in 1.8 million acres burned [40]. All five began in July or August and were declared contained in October or November [40]. Wildfire season has historically been between July and October, with its peak being in September through October. Since initial surveys took place between March and April 2021, the 6-month follow-up surveys were completed between September and October 2021, overlapping with peak wildfire season during which we would expect climate-related experiential avoidance to be heightened.

Ethics statement

Written consent was obtained from all participants. This study was approved by the local Institutional Review Board at the University of California, San Francisco (IRB# 21–33496; Reference # 307854).

Measures

To measure anxiety and experiential avoidance in the context of climate change, we created a modified version of the Acceptance and Action Questionnaire (AAQ-II) [36]. This modified questionnaire, the Climate Acceptance and Action Questionnaire (C-AAQ), included the prompt, “How much over the past month have you had these feelings about climate distress?”, followed by 6 items rated on a 5-point Likert scale from “Never” to “Very often”. The items included: “I’m afraid of my feelings about climate change”, “I can be overwhelmed by my worries and feelings about climate change”, “Painful images and information about climate change keep me from having a fulfilling life”, “I avoid painful thoughts and feelings about climate change” “It seems like others are handling climate change better than I am”, and “Worrying about climate change is preventing me from feeling at ease and content”. Coded values were summed to create a total score with minimum and maximum possible values of 0 and 24 respectively, with higher scores indicating greater climate distress. We describe consistency of this new questionnaire in our results section below.

Generalized anxiety symptoms were measured using the Generalized Anxiety Disorder Questionnaire (GAD-7) [41], which consists of 7 items rated on a 4-point scale ranging from ‘not at all’ (0) to ‘nearly every day’ (3). The questionnaire asks respondents, over the last two weeks, how often have they been bothered by a list of 7 problems that include statements like, “feeling nervous, anxious, or on edge.” The GAD has a documented high internal consistency (Cronbach α = .92) [41].

Depressive symptoms were measured using the Patient Health Questionnaire (PHQ-8) [42], which consists of 8 items on how often the respondent has been bothered by a list of 8 problems, for example, “little interest or pleasure in doing things.” These items were rated on a 4-point scale ranging from ‘not at all’ (0) to ‘nearly every day’ (3). We omitted the final question from the original 9-item questionnaire that asks about suicidal and self-injurious thoughts. The original 9-item PHQ has a high internal consistency Cronbach α = .89) [43].

The Cognitive and Affective Mindfulness Scale–Revised (CAMS-R) [44] was used to measure trait mindfulness. This scale has 10 items rated on a 4-point scale ranging from ‘rarely/not at all’ (1) to ‘almost always’ (4). Respondents are asked to respond the degree to which they endorse statements such as, “It is easy for me to concentrate on what I am doing.”; “I try to notice my thoughts without judging them.” and “I can accept things I cannot change.” The CAMS-R has been found to have acceptable internal consistency across two tested samples (Sample 1 α = .74; Sample 2 α = .77) [44].

Other measures included basic demographics (age, gender, race/ethnicity, education, and income), political ideology, political party, and distance from wildfires. Political ideology was measured using a single-item question: “Regardless of your political registration or affiliation, where would you place yourself on the political spectrum from extremely liberal to extremely conservative?” with responses on a 9-point scale from “extremely liberal” (1), to “extremely conservative” (9). This question was drawn from the Understanding America Study [45]. In describing sample characteristics, subjects with values less than 5 were considered “liberal”, values equal to 5 were considered “moderate”, and values above 5 were considered “conservative”. The political party was measured using the question “What political party do you feel most affiliated with?”, with the ordered options: “Republican”, “Democratic”, “Libertarian”, “Green”, and “Other”. Distance from wildfires was measured using the question, “How close (in miles was your primary residence to the wildfires this year?”

Statistical analysis

All data processing, graphing, and statistical analysis were performed using R v4.2.2 [46]. For each scale, individual items were summed to create a total score. Where respondents completed at least two-thirds but not all of the items, a pro-rated score was calculated as though all items were completed. Where less than two-thirds of the items were completed for a given scale, the score was treated as missing.

Bivariate relationships were examined using Spearman’s rho or Welch two-sample t-tests. Multivariable analyses initially involved fitting a mixed-effects linear model using the lme4 package [47]. Models included a random intercept for each subject and were fitted using restricted maximum likelihood estimation. Categorical predictors were incorporated into models using deviation coding, and continuous predictors were mean-centered. The significance of model predictors was evaluated using F statistics and Kenward-Roger degrees of freedom [48] calculated using the car package [49]. F statistics used Type II sums of squares, meaning they compared the model predictions using a specific predictor but without any higher-order predictors to the model predictions without the specified predictor [49]. Visualizations and post hoc comparisons were performed via the calculation of estimated marginal means (EMMs) and associated 95% confidence intervals (CIs) using the emmeans package [50]. Thus, visualizations represent model-derived estimated climate distress for each level of any depicted predictors, assuming mean levels of continuous covariates (age, mindfulness, generalized anxiety, political ideology), and averaging across the estimates for each level of other categorical predictors with proportional weighting (gender, time point, distance from wildfires). Post-hoc testing made the same assumptions. The effectsize package v0.7.0 was used to convert t or F statistics and associated degrees of freedom to standardized effect sizes (i.e., Cohen’s d, partial correlation, or partial eta squared, η²). Visualizations were produced using ggplot2 [51] together with ggeffects for the calculation of partial residuals.

Results

Sample characteristics

A total of 501 participants who provided complete predictor data and outcome data for at least one-time point were included in the present analyses (See Table 1 for additional demographic information). Regarding climate distress, the mean (+/- SD) C-AAQ score in the sample was 5·5 (+/- 4·4) at baseline and 6·0 (+/- 4·6) at follow-up, which is a significant increase over time (See Table 2). Cronbach’s alpha was 0·83 at baseline (n = 495) and 0·84 at 6-month follow-up (n = 489). McDonald’s omega for the C-AAQ was 0·77 at baseline and 0·80 at 6-month follow-up.

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Table 1. Sample characteristics.

https://doi.org/10.1371/journal.pclm.0000524.t001

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Table 2. Model statistics.

https://doi.org/10.1371/journal.pclm.0000524.t002

Bivariate analyses

Bivariate correlations were examined between climate distress at both time points and baseline measurements of four continuous variables (mindfulness, political ideology, age, and anxiety symptoms). The correlation coefficients and significance levels are presented in Fig 2. All bivariate correlations were statistically significant except for age and political ideology. We also tested for associations between climate distress at baseline and gender, self-reported distance from wildfires (30 miles or less vs. more than 30 miles), and depressive symptoms. Females had significantly higher climate distress than males (p = 0·02), 5·83 (CI 5·34 to 6·31) vs. 4·90 (CI 4·25 to 5·56) points. Distance from wildfires was not significantly associated with climate distress (p = 0·06). Depressive symptoms were moderately correlated with climate distress measured at both baseline (r = 0·34, p < 0·001) and follow-up (r = 0·37, p < 0·001).

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Fig 2. Bivariate correlations between continuous variables.

Most variables examined were significantly related to one another. For consistency, all values represent spearman’s rho, given that while most relationships were linear, the relationship between age and political ideology was slightly non-linear.

https://doi.org/10.1371/journal.pclm.0000524.g002

Multivariable analyses

Results of multivariable mixed-effects linear model are provided in Table 2. Climate distress was significantly predicted by an interaction between mindfulness and time point, so pairwise comparisons were conducted to compare climate distress at baseline vs. at follow-up for two levels of mindfulness (+1 standard deviation and -1 standard deviation). Mindfulness appeared to be protective (Fig 3), given that for low-mindfulness individuals, climate distress increased over time (d = 0·43, CI 0·25 to 0·61; mean difference = 1·0, CI 0·62 to 1·5; p < 0·001), while for high-mindfulness individuals, there was no change in climate distress over time (d = 0·10, CI -0·07 to 0·27; mean difference = 0·25, CI -0·18 to 0·67; p = 0·26). Simple slopes of mindfulness at each time point were also examined. Mindfulness was negatively associated with climate distress at both baseline (partial correlation = -0·11, CI -0·18 to -0·04; slope = -0·11, CI -0·17 to -0·039; p = 0·002) and follow-up (partial correlation = -0·19, CI -0·26 to -0·12; slope = -0·18, CI -0·24 to -0·11; p < 0·001).

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Fig 3. Climate distress worsened over the study period in low-mindfulness but not high- mindfulness individuals.

A significant interaction was identified between mindfulness and time. Pairwise comparisons compared measurements in March vs. October 2021 for two levels of mindfulness (+1 and -1 standard deviation, SD), and revealed a significant increase over time (***, p < 0.001) for low-mindfulness individuals but no significant change for high-mindfulness individuals. Lines and gray bands connect model-derived estimated means +/- 95% confidence intervals for each combination of time point and mindfulness level. Each estimate assumes sample means of age, generalized anxiety, and political ideology, and averages across the levels of categorical variables (sex and distance from wildfires), weighting levels equally.

https://doi.org/10.1371/journal.pclm.0000524.g003

Other significant predictors of climate distress in the multivariable model included political ideology and generalized anxiety. For political ideology, the partial correlation was -0·22 (CI -0·30 to -0·14), indicating that political conservatism was associated with lower climate distress (Fig 4). For generalized anxiety, the partial correlation was 0·24 (CI 0·18 to 0·30), indicating that higher generalized anxiety was associated with higher climate distress (Fig 5). Age, gender, and distance from wildfires did not significantly predict climate distress after accounting for mindfulness, political ideology, and generalized anxiety.

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Fig 4. Political ideology predicted climate distress.

Participants were asked to report where they would place themselves on the political spectrum using a 9-point Likert scale. Most participants identified as “moderate” to “extremely liberal”. A significant, linear relationship was identified between political ideology and climate distress. The line and gray banding connect model-derived estimated means +/- 95% confidence intervals of climate distress for each level of political ideology. Each of these estimates assumes sample means for age, generalized anxiety, and mindfulness, and averages across the levels of categorical variables (time, sex, distance from wildfires), weighting levels equally. Red circles represent partial residuals (with horizontal jitter), with one circle per observation.

https://doi.org/10.1371/journal.pclm.0000524.g004

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Fig 5. Generalized anxiety and climate distress.

Participants completed the GAD-7 questionnaire as an index of generalized anxiety. A significant, linear relationship was identified between generalized anxiety and climate distress, adjusting for covariates. The line and gray banding represent the model- derived estimated mean +/- 95% confidence interval for each level of generalized anxiety. Each of these estimates represents the average effect across both time points, sex, and distance from wildfires, and assumes sample means for age, political ideology, and mindfulness. Red circles represent partial residuals (with horizontal jitter), with one circle per observation.

https://doi.org/10.1371/journal.pclm.0000524.g005

Two sensitivity analyses were performed relating to political ideology. In a sensitivity analysis performed with the same model structure as described but including only subjects identifying with the Democratic party (n = 381), political ideology remained a significant predictor of climate distress (F_1,375·2 = 5·49, p = 0·02). In another model using the full sample (n = 501), the timepoint by mindfulness interaction term was replaced by a timepoint by political ideology interaction term, which was not statistically significant (F_1,374·8 = 1·08, p = 0·30), while the main effect of political ideology remained significant (F_1,375·2 = 5·49, p = 0·02).

Discussion

In this study, our aim was to measure what protects against the elevation of climate distress in a group of community-dwelling individuals who had recently been exposed to a climate disaster (i.e., large wildfires occurring in 2021). We found that climate distress in a highly exposed northern California sample increased on average after one fire season in 2021, suggesting the possibility that there may be increases as wildfire exposures increase over time rather than habituation. It is unknown how much distress will continue to increase over time with repeated exposures, or how much people will become habituated to the dangerous climate and wildfires locally and in the global news. National studies should track changes in direct exposures, climate-specific distress, and mental health responses by geographic and sociodemographic factors.

Which subgroups have high climate distress?

In line with our hypothesis, we found that those with high levels of trait mindfulness at baseline have lower levels of climate distress. Prior research has similarly shown promise for the role of mindfulness in reducing climate-related distress [33,34] and results from our study further highlight that mindfulness may prevent escalating climate distress over time. The ability to observe negative emotions without overreaction and active acceptance of emotions is an important part of mindfulness and how it protects against anxiety and depression. In this case, these same cognitive skills appear to protect from heightened reactions to negative thoughts and feelings about climate change. The ability to recognize feelings about the harsh reality of climate destruction and its impacts, without having these feelings interfere with psychological functioning and behavioral action, is a critical skill that will become even more important as climate crises increase in the near future.

Our results also revealed additional findings surrounding individual differences such as gender and political ideology. Climate distress was higher in women, similar across a large age range (18 to 88 years), and not related to self-reported proximity to wildfire. This may be because the wildfire smoke was widespread across the region. In our sample, which was mostly Democratic (77%), albeit with a range of ideologies (28% identifying as moderate to conservative), climate change distress was positively linearly associated with political ideology, regardless of political party. Thus, political ideology is an important factor influencing the level of climate distress and should be considered as we try to predict, track, and prevent extreme climate distress. While this area is relatively under-studied, one previous study found that people who identify as conservative are less worried about climate change [52]. Similarly, a study using the Climate Change in the American Mind survey highlighted that Democrats report higher worry about global warming than Republicans [53]. Conservative ideology did not, however, mitigate the increases in climate distress over time in the way that mindfulness did.

Climate distress was only moderately associated with general anxiety (less than 15% shared variance), showing, as others have [15], that climate distress and general anxiety are interrelated but distinct constructs. This provides evidence for the utility of the C-AAQ as a measure of climate distress that is separate from generalized anxiety.

Implications of mindfulness for climate-change-related distress

Our results suggest that trait mindfulness may be an important mitigating mechanism for the negative mental health sequelae as wildfires increase in frequency and intensity in the future due to climate change. Developing mindfulness skills may serve as a buffer or inoculation to reduce the incidence, intensity, and duration of climate-related negative emotions. Importantly, we found that those with high mindfulness did not experience an increase in climate distress over time while those with low trait mindfulness did. Whether trait mindfulness can be taught and trained is a future direction that additional research should address. The role of mindfulness as a tool for adapting to climate-related experiential avoidance should be further explored for those most at risk, such as those living in environments most heavily impacted by climate change and those at the front lines of climate activism.

Climate distress and potential implications for climate action

Theoretically, experiential avoidance and denial of climate-related thoughts and feelings should lead to less action. Thus, the type of maladaptive climate distress we measured may specifically have implications for lack of action, advocacy, or personal climate-engaged behaviors, but this remains to be shown empirically. High climate concern, which is related to climate distress, is important to motivate behavior change as it is a strong predictor of support for climate solutions policies [54], climate change-related political activism [55], and consumer activism [56]. Those who endorse higher climate distress are also more willing to participate in a climate campaign, take climate action, and talk to their friends and families about these important issues [57]. People involved in climate activism or environmental work tend to report higher climate distress [58,59] which can contribute to burnout and loss of engagement. In turn, it is widely thought that engaging in action is one of the ways that people can reduce climate distress. It is important in future studies to measure the level of concern, climate distress, climate change advocacy, and other engagement behaviors, over time, to provide a more comprehensive understanding of how attitudes and emotional responses affect activism.

Implications for interventions

To cope effectively with climate change requires awareness, discussion, and collective action, at the community and political level. However, the common response is inaction due to avoidance and lack of tolerance over distressing feelings, which we define as maladaptive climate distress. It is critical to develop a climate-resilient mindset where one can tolerate these thoughts. As noted above, our findings suggest that mindfulness may be protective from climate crisis experiential avoidance. Those with high mindfulness had lower levels of climate distress which remained stable over the six-month period and those with low mindfulness showed a significant increase in climate distress.

Mindfulness is multifaceted and includes both awareness and monitoring skills, as well as acceptance skills, including non-reactivity to stressors and acceptance of negative experiences. In one study, acceptance skills were related to lower climate anxiety whereas awareness was related to greater climate anxiety and greater personal relevance which was linked to greater climate engagement behaviors [60]. Therefore, relationships between different mindfulness skills and climate emotions and actions can be complex. However, interventions that teach mindfulness for emotion regulation in tandem with empowerment skills of self-efficacy for collective engagement may be most effective.

Future studies could examine whether mindfulness training can be used in climate activism to promote greater emotion regulation and psychological flexibility. Mindfulness has been promoted in the UK parliament as an important resource for climate change action [61] and mindfulness has been cited as an important skill to explore in the latest IPCC report [62]. The Mindful Climate Action (MCA) Program, aimed at changing behaviors benefitting an individual’s health and the environment through mindfulness-based environmental education, appears to improve well-being although there are unknown effects on climate action such as sustainable behaviors or activism [63].

Study limitations

The current study has several limitations, including the timing of measurements. Climate distress was measured before or after peak exposure to wildfires, thus the timing did not capture acute stress responses and instead may be capturing individuals’ general distress about climate change. We measured a specific type of climate distress, (maladaptive emotion regulation about climate change). It would be useful to compare the C-AAQ scale to a validated scale of severity of symptoms of climate distress, such as the Climate Anxiety Scale by Clayton and Karazsia [15]. Measuring both types of climate distress would help us understand if avoidant emotion regulation better predicts a lack of climate action than severity of symptoms. Although our discussion suggests that our findings have important implications for those engaged in climate action to be at high risk for burnout and climate-related experiential avoidance, our study does not have a direct measure of climate action. Future studies directly measuring climate action can further elucidate the important role that mindfulness may have.

Additionally, due to the large age range (18 to 88 years old), future studies should look at differences in age groups as generational differences may contribute to varying levels of climate distress, as well as trait mindfulness. While our recruitment strategies allowed us to reach participants across the Bay Area, our sample is not representative of the demographic composition thus limiting the generalizability to the region. Eighty-four percent of our participants have at least a 4-year college degree and 56% of participants report an annual income of $100,000 or over. Because we have a limited sampling of participants from lower socioeconomic status, it is unclear whether mindfulness mitigates climate distress over time for these individuals. Further, while climate change is expected to further exacerbate wildfires in western North America [3], and our sample is restricted to an area within this region, future work should aim to address climate distress and resilience mechanisms more globally.

Conclusion

This longitudinal study contributes to a growing understanding and awareness of climate-related distress and potential resilience pathways. High climate concern and distress are natural in our current crisis and are increasing over time. Trait mindfulness appears helpful for mitigating climate distress, particularly maladaptive emotion regulation. Whether mindfulness interventions help people with particularly high distress is an ongoing research question.

Acknowledgments

We thank the research volunteers for their time and all of the emergency and essential workers who help us through the wildfires and other climate emergencies. We also thank Dylan Marchiel for her help with our study team.

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Figures

Abstract

Introduction

Wildfires and climate distress

Climate distress and climate behaviors

Maladaptive emotion regulation (experiential avoidance) to the climate crisis

Mindfulness may buffer stress responses to climate events

The current study

Methods

Study procedures

Ethics statement

Measures

Statistical analysis

Results

Sample characteristics

Bivariate analyses

Multivariable analyses

Discussion

Which subgroups have high climate distress?

Implications of mindfulness for climate-change-related distress

Climate distress and potential implications for climate action

Implications for interventions

Study limitations

Conclusion

Acknowledgments

References