Examining the relationships between eco-anxiety, sociodemographic factors, experience of climate events, pro-environmental behaviours, and life satisfaction in young adults

Abstract

Background

Climate change and environmental degradation pose significant threats to ecosystems and human well-being, leading to increased eco-anxiety, especially among young adults. Eco-anxiety, characterized by worry and fear about environmental issues, can affect mental health and behaviours. This study aims to explore the relationships between eco-anxiety, sociodemographic factors, experiences of climate events, pro-environmental behaviours, and life satisfaction in young adults.

Methods

A quantitative cross-sectional design was employed to examine the relationships between the variables mentioned above among young adults. The sample included university students from health science centres in Spain. Surveys were used to gather data on participants’ eco-anxiety levels, sociodemographics, experiences with climate events, pro-environmental behaviours, and life satisfaction.

Results

The study revealed eco-anxiety differences among genders, with female participants experiencing greater personal impact anxiety. However, no differences were found among education or area of upbringing and residence, except that growing up/living in rural areas was associated with more behavioural symptoms of eco-anxiety. Direct and indirect experiences with climate events significantly influenced eco-anxiety levels, with direct experiences having a stronger effect. Linear regression models showed that different eco-anxiety dimensions had distinct relationships with pro-environmental behaviours and life satisfaction, with personal impact anxiety increasing pro-environmental behaviours and reduced affective/behavioural symptoms enhancing life satisfaction. Increased personal impact anxiety predicted higher levels of pro-environmental behaviours, whereas decreased affective and behavioural symptoms of eco-anxiety predicted higher life satisfaction.

Conclusions

The findings suggest that eco-anxiety is a complex and multidimensional construct influenced by several factors, including direct and indirect psychosocial experiences related to climate events and information-seeking behaviours. Eco-anxiety is differently associated with pro-environmental behaviours and mental health variables, such as life satisfaction. Addressing eco-anxiety requires a multifaceted approach that considers its different dimensions and individual differences over time. Future research should explore these relationships longitudinally and include more diverse samples to enhance the generalizability of the findings.

Background

The world is facing an ecological crisis, with its adverse consequences becoming increasingly evident [1]. These consequences encompass a range of interconnected ecological issues, such as pollution, biodiversity loss, and climate change (e.g [2]) . Human-caused climate change represents one of the most significant threats to species, ecosystems (biodiversity loss) [3], and to the living conditions, overall well-being, and physical and mental health of present and future generations [4, 5]. Beyond its environmental and physical consequences, climate change also poses psychological challenges. As individuals witness or become aware of environmental degradation, concerns about its present and future implications can give rise to emotional distress. In response, public health experts have started to examine the psychological and social impacts of the ecological crisis [6], particularly its effects on mental well-being [7].

The literature distinguishes between different types of adverse climate change experiences and their impact on mental health. Direct exposure to weather events and environmental problems heightens the likelihood of clinical levels of distress [8]. At the same time, as public awareness of ecological concerns increases, there is a growing sense of anxiety prompted by ecological issues, even among individuals who have not been directly exposed to environmental challenges [9].

Climate change can also lead to negative psychosocial experiences, including climate-induced migration, economic instability, and social conflict linked to climate change, which are expected to affect mental health and well-being [10, 11]. In addition, people are increasingly exposed to environmental problems indirectly through media coverage [10, 12, 13]. Media-driven awareness of ecological issues heightens individuals’ perception of the deteriorating state of the planet [14], thereby contributing to feelings of concern, anxiety, and worry – a phenomenon commonly referred to as eco-anxiety [15].

Anxiety related to environmental issues can prompt individuals to seek information about environmental matters [16] and avoid this information [17, 18]. In examining the relationship between individuals’ engagement with environmental news in the media and eco-anxiety, Hogg et al. [17] found that both actively seeking and deliberately avoiding information about climate change were associated with heightened eco-anxiety. Rather than mere exposure, it was the active management of climate information—whether through seeking or avoidance—that predicted increased anxiety. These findings suggest a broader role of media in shaping climate-related distress and highlight how individuals may cope by regulating their access to information. Similarly, Ogunbode et al. [19] studied climate anxiety, which is a specific form of eco-anxiety centred on climate-related concerns [15]. They found that climate anxiety is linked to the nature of climate-related media exposure rather than its sheer volume. Specifically, attention to information about climate change impacts was a significant predictor of climate anxiety, whereas no such association was found for exposure to climate solutions. This suggests that the content and focus of climate information, rather than its quantity, play a key role in shaping climate anxiety.

Eco-anxiety is a multidimensional construct, encompassing affective symptoms, behavioural responses, ruminative eco-anxious thoughts, and anxiety about one’s contribution to environmental degradation [5]. It involves anxiety related to a wide range of environmental issues, including anthropogenic climate change [15, 20] and other concerns, such as species extinction and deforestation, which may or may not be directly attributed to climate change. The experience of eco-anxiety varies along a spectrum, ranging from mild, non-debilitating to significant and severe distress, determined by the frequency and intensity of the experienced distress [21, 22].

Evidence indicates that individuals who have been directly exposed to the impacts of climate events are more likely to report heightened levels of eco-anxiety [23], particularly in the form of elevated affective/behavioural symptoms and rumination [17]. Coffey et al. [24] systematic scoping review on eco-anxiety further supports this evidence, showing that individuals who have directly experienced physical environmental changes - such as injury or stress from extreme weather events, displacement or homelessness due to climate impacts, or the effects of rising sea levels, droughts, or unpredictable weather - tend to report higher levels of stress and vulnerability to developing eco-anxiety. Given that eco-anxiety arises as a response to serious and tangible environmental threats, the prevailing consensus is that it should not be pathologized (e.g [22, 25–28]). , . Also, there is evidence that individuals who frequently seek out or avoid environmental information further experience eco-anxiety across all its dimensions [17]. However, mere exposure to environmental or climate change-related information does not appear to be uniquely related to the dimensions of eco-anxiety [17].

Sociocultural factors seem to have a considerable impact on how individuals react to ecological crises. Eco-anxiety seems to be shaped by various social, political, and geographical influences [20, 29]. Levels of eco-anxiety appear to vary according to sociodemographic factors, although the current body of evidence remains limited. In a cross-national study with more than 50,000 participants from 25 European countries, using data from the European Social Survey, Niedzwiedz and Katikireddi [30] found that respondents in Spain recorded the second-highest levels of eco-anxiety, as measured by levels of worry about climate change. This underscores the importance of examining eco-anxiety in context, particularly to understand how its prevalence and intensity may differ across various sociodemographic groups.

Recent studies indicate that younger individuals experience higher levels of eco-anxiety. A systematic review by Boluda-Verdú et al. [31] suggested a relationship between eco-anxiety and negative mental health outcomes, particularly among younger generations. Similarly, the scoping review by Coffey et al. [24] highlighted that children and young people are most affected by eco-anxiety and considered especially vulnerable. However, Hogg et al. [25] showed that the dimensions of eco-anxiety may vary with age; their study revealed that while age was linked to lower levels of personal impact anxiety, it was associated with higher levels of rumination. However, these findings are not consistently reported in the literature. For example, Rocchi et al. [32] conducted a study in Italy that found individuals aged 30 or younger reported significantly higher means than participants over 30 years old in “affective symptoms” and “personal impact anxiety” dimensions of the Hogg Eco-Anxiety Scale (HEAS).

Regarding gender, research consistently shows that women are more likely to experience higher levels of eco-anxiety compared to men (e.g [25, 30]). A narrative review by Rothschild and Haase [33] revealed that multiple systematic reviews have demonstrated greater susceptibility among women to the development of climate-related anxiety, worry, and stress than men. This aligns with the broader pattern observed in climate perception and action research, often referred to as the ‘eco-gender-gap,’ which suggests that women are generally more concerned about environmental issues than men [34–36]. Specifically, women tend to experience higher levels of affective symptoms and personal impact anxiety than men [25, 33]. However, some studies found no differences among genders in eco-anxiety [37], which may be attributed to variations of differences in data analysis methodologies.

Higher levels of education have been associated with increased awareness and subsequent eco-anxiety. For example, Niedzwiedz and Katikireddi [30] observed that participants with tertiary education or higher were more likely to experience eco-anxiety compared to those with lower educational attainment. Sampaio et al. [37] found no direct relationship between educational levels and specific dimensions of eco-anxiety; however, they observed a positive association between paternal education attainment and anxiety related to personal impact anxiety.

The impact of living conditions on eco-anxiety is significant, with urban residents sometimes exhibiting higher levels of eco-anxiety compared to rural residents. This distinction between urban and rural environments is essential, as the place of residence plays a key role in shaping environmental values, attitudes, and behaviours [38, 39]. By comparing rural populations with urban populations, the latter are more likely to face environmental challenges, such as rising sea levels, strong rainfalls or cyclones leading to storm surges and flooding, compared to rural populations, particularly because urban communities are often located near coastal regions [40]. Urban residents are often more exposed to visible environmental problems – such as air pollution and waste accumulation – which may heighten environmental concern and emotional strain [41]. Combined with greater access to education and environmental information, this exposure can increase sensitivity to ecological issues and contribute to eco-anxiety [41, 42]. In contrast, rural residents may hold strong environmental values rooted in their relationship with nature, but structural and cultural barriers often limit these attitudes from becoming action, potentially reducing the emotional impact of environmental threats [43]. Consequently, people living in urban areas may exhibit increased fear of climate change [44]. However, these effects are not consistent across all studies (e.g [37]).

Previous research has demonstrated that eco-anxiety has two concurrent and divergent effects. On the one hand, it can drive some individuals to adopt pro-environmental behaviours (PEB) [45–48]. PEB are actions to reduce adverse effects on the environment or cause it less harm and ideally benefit it [49–51]. One explanation for the association between eco-anxiety suggests that individuals experiencing eco-anxiety are more aware of the environmental consequences of their actions and, therefore, more inclined to engage in PEB, such as recycling, reducing plastic consumption, and utilizing sustainable transportation options [52]. This connection underscores the importance of individual emotions and perceptions in potentially promoting environmentally responsible behaviours. Specifically, some studies have found that rumination and personal impact anxiety are distinct predictors of PEB [25]. However, the evidence remains mixed. While certain findings support the idea that ruminative aspects of eco-anxiety foster action, other research suggests that rumination may not consistently predict pro-environmental behaviour, or may even be associated with emotional paralysis or avoidance in some individuals [53]. Recently, Hogg et al. [25] started exploring whether the relationship between eco-anxiety and PEB followed an inverted ‘U’ pattern, where moderate levels of eco-anxiety led to optimal engagement, while low and high levels resulted in lower engagement. The U-shaped pattern of eco-anxiety can be explained through psychological mechanisms related to the relationship between emotional arousal and behaviour. This pattern would resemble the ‘inverted U’ hypothesis in the relationship between arousal and performance [54], where moderate levels of arousal may drive action, but too low or too high levels may decrease proactive behaviour.

Additionally, researchers have examined the association between direct and indirect experiences of climate events and PEB. Maran et al. [55] found that individuals directly exposed to environmental problems and/or experiencing psychosocial effects were more likely to adopt PEB than those without direct exposure to climate events. The physical context can also lead to different experiences. For example, individuals living in a rural context exhibited greater environmental responsibility and consistency in expressing behavioural intentions aligned with environmental protection than those living in urban settings [56].

Both eco-anxiety and PEB are closely related to individual well-being, albeit in different ways. Specifically, eco-anxiety is associated with decreased life satisfaction [30], and climate anxiety, in particular, had a moderate negative association with psychological well-being [7]. On the other hand, PEB may positively influence well-being and affect mood or happiness. Individuals in positive emotional states tend to perceive others more favourably, which may, in turn, compel them to adopt pro-social behaviours [57, 58]. Xiao and Li [59] observed a correlation between sustainable consumption and higher levels of life satisfaction in China based on demographic variables. The transactional model of stress and coping [60] provides a useful framework: eco-anxiety arises when individuals appraise climate change as a threat and evaluate their coping resources. Those perceiving sufficient control may engage in PEB as active coping, while others may feel helpless, reducing life satisfaction [61, 62] As highlighted by Hogg et al. [25], the various dimensions of eco-anxiety have distinct effects on mental well-being and PEB, with symptomatic aspects (affective and behavioural) contributing to mental health challenges, while rumination and personal impact anxiety specifically predict pro-environmental actions. Thus, this model contributes to the explanation on how eco-anxiety influences both behaviour and well-being dynamically [63, 64].

Current study

Building on the identified gaps in the literature – particularly the limited differential analysis of eco-anxiety dimensions and the lack of integrative models considering both experiential and psychological variables – this study aims to clarify how eco-anxiety, sociodemographic factors, experiences of climate events, PEB, and life satisfaction intertwine in the lives of young adults amid the current ecological climate crisis. Given the multidimensional nature of eco-anxiety and the potential role of demographic and experiential factors, these interconnections are explored from a comprehensive and integrative perspective. These relationships raise important questions, such as: How do sociodemographic variables and direct or indirect experiences of climate events lead to variations across dimensions of eco-anxiety? Moreover, how does eco-anxiety relate to PEB and life satisfaction? To address these questions, the following hypotheses were formulated based on the reviewed literature. Specific predictions for the dimensions of eco-anxiety were made only when relevant evidence was available in the literature.

1. We hypothesised higher levels of eco-anxiety among women compared to men, particularly regarding affective symptoms and personal impact anxiety (Hypothesis 1a); among individuals with higher educational attainment compared to those with lower education levels (Hypothesis 1b); among individuals who grew up and resided in urban environments compared to those raised and living in rural environments (Hypothesis 1c); and among individuals with direct experiences of climate events compared to those with only indirect exposure (Hypothesis 1d). These effects were tested while controlling for general mental and physical health effects. No hypothesis was formulated for age because our sample comprises only young adults.

2. We hypothesised higher levels of PEB among individuals with higher levels of rumination and personal impact anxiety dimensions of eco-anxiety, compared to those presenting with lower levels of rumination and personal impact anxiety (Hypothesis 2a); and higher levels of life satisfaction among individuals with lower levels of eco-anxiety symptoms (affective and behavioural) compared to those with higher levels of eco-anxiety (Hypothesis 2b). These effects were tested while controlling for the sociodemographic variables examined in Hypothesis 1.

Methods

Participants and procedure

We employed a cross-sectional design to examine the associations between dimensions of eco-anxiety, PEB, experience of climate events, sociodemographic factors, and life satisfaction in young adults. A subset of these data was also used to validate the Hogg Eco-Anxiety Scale (HEAS) in Spain and Argentina, as reported by Rodríguez Quiroga et al. [65]. The data was collected in the second half of 2022. The study population comprised young adult university students from two health sciences faculties at two Spanish universities. Convenience sampling was used to recruit 548 participants. Based on inclusion and exclusion criteria, we limited the sample to individuals aged 18–25 (excluding 63 participants) and those who agreed to participate in the study (excluding 62 individuals who did not formally consent), resulting in a final sample of 423 participants. This age range was selected because it encompasses the most common age group of individuals pursuing higher education. University students were of particular interest, as they are frequently exposed to discussions on climate change, sustainability, and environmental issues, which are key factors in the experience of eco-anxiety. Including this specific age range allowed for a more homogeneous sample in terms of academic background and life stage, facilitating a focused analysis of eco-anxiety within this demographic. Participants did not receive any compensation for their participation, in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Bioethics Committee of the Universitat de Barcelona Ethics of Human Research (no. 00003099).

Participants were invited to participate in the study by teaching staff and via the universities’ social media channels. Data were gathered using an online form sent to the participants. Sociodemographic variables, such as age, sex, years of education, and whether the participants had been raised and lived in a rural or urban area, were collected for analysis. These areas were coded as 0 = rural area and 1 = urban area for each variable, respectively. Also, the form gathered information on direct and indirect experiences of climate events and assessed the presence of a diagnosed chronic physical and/or mental illness, coded as 0 = chronic physical or mental illness and 1 = no chronic physical or mental illness for each variable, respectively. Other variables included levels of eco-anxiety, PEB, and life satisfaction, as described below. The form and dataset were managed using REDCap electronic data capture tools [66]. The data collected were anonymized immediately after completion, preventing any further linkage to the participants. Due to this anonymization process, the data could not be withdrawn once submitted.

Measures

Eco-anxiety

The HEAS [5], recently translated and validated for use in Spanish-speaking populations (HEAS-SP) [65], was employed in this study. The scale comprised 13 items that capture the experience of eco-anxiety across four dimensions: affective symptoms of eco-anxiety (4 items, e.g., “Worrying too much”), ruminative thoughts related to environmental issues (3 items, e.g., “Unable to stop thinking about losses to the environment”), impairment in social and behavioural functioning (3 items, e.g., “Difficulty enjoying social situations with family and friends”), and anxiety about one’s contribution to ecological problems and solutions (3 items, e.g., “Feeling anxious that your personal behaviours will do little to help fix the problem”). Responses regarding how often participants were bothered by each problem over the preceding two weeks were measured on a 4-point frequency scale (0 = never, 3 = almost every day).

The scale exhibited good internal consistency across all dimensions (affective symptoms: α = 0.81; rumination: α = 0.83; behavioural symptoms: α = 0.79; personal impact anxiety: α = 0.79). Additionally, a confirmatory factor analysis (CFA) conducted in the Spanish sample supported the four-factor structure, with the following fit indices: χ²(59) = 110, p < .01, CFI = 0.98, TLI = 0.97, BBNFI = 0.97, AGFI = 0.95, RMSEA = 0.04 (90% CI: 0.02–0.05), and SRMR = 0.04, indicating a good model fit. These findings reinforce the validity of the HEAS-SP in this population (see [65] for the global psychometric analysis of the HEAS-SP psychometric properties of this sample).

Life satisfaction

We used Vázquez et al. [67] Spanish version of the Satisfaction With Life Scale (SWLS) [68]. This scale comprises 5 items that evaluate individuals’ overall perception of life satisfaction (e.g., “In most ways, my life is close to my ideal”). Responses were rated on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). The scale revealed good internal consistency, with a Cronbach’s alpha coefficient of 0.86. The SWLS was validated in a large general population sample of 2,964 Spanish adults, ensuring its robustness in the Spanish context. Given that the original validation study included a representative sample of adults within the 18–25 age range, it can be concluded that this scale is appropriate for use in our study.

Pro-environmental behaviour

We used 17 items from Whitmarsh and O’Neill [69] and 1 item from Hogg et al. [25] to assess individual-level PEB across various domains (e.g., waste reduction, energy conservation, and green shopping; with the additional item asking about minimising heating or cooling). This resulted in an 18-item instrument, participants reported how often they engaged in each behaviour over the past two weeks using a 4-point Likert-type scale coded as 0 = Never, 1 = Occasionally, 2 = Frequently, and 3 = Always. For each participant, a composite PEB score was calculated by computing the mean of the responses across all 18 items, resulting in a continuous variable ranging from 0 to 3, with higher scores indicating greater engagement in pro-environmental behaviours. A Cronbach’s α of 0.72 was obtained in our sample.

Direct and psychosocial experience

Following Hogg et al. [17] approach, we inquired about the frequency with which participants had been directly affected by climate events over the past year. Participants rated their exposure on a 5-point scale (from 0 = not at all to 4 = a great deal) in response to the prompt “Over the last year, I have personally been affected by the following climate events.,” rating: bushfires, bushfire smoke, drought, extreme weather events, flooding, increased temperatures, local environment changes, species loss, rising sea levels, pollution, and climate change-related economic decline, migration, and social conflict. Scores for all 13 items were summed to create a total score ranging from 0 to 52. The scale demonstrated obtained a Cronbach’s α of 0.87.

Indirect experience and engagement

Following Hogg et al. [17], we included three items that asked participants to report how often they see, actively seek, and avoid information about climate change in the media (including newspapers, social media, radio, television, and the Internet). These items were measured on a frequency scale from 0 = never to 6 = several times a day. Reporting the frequency of seeing climate-related information may reflect passive indirect exposure to climate change impacts, while seeking and avoiding information are conceptualised as active engagement or moderating exposure to climate information, respectively. These measures were used as three separate single-item scales aligned with the authors’ approach [17].

Data analysis

All analyses were conducted using IBM SPSS software version 27.0 (SPSS, Inc., Chicago, IL, USA) and RStudio (version 4.4.2). For data visualization, the libraries ggplot2 (version 3.5.1) [70] and dplyr (version 1.1.4) [71] were used in R. Parametric tests were employed, primarily based on the central limit theorem, which states that as the sample size increases, the distribution of sample means tends to approximate a normal distribution, regardless of the original population distribution. In this study, the sample consisted of 423 subjects, allowing for a confident assumption that the sample means of the analysed variables would follow a normal distribution [72]. Moreover, previous research has shown that parametric tests generally maintain their robustness in most cases, even when the normality assumption is not strictly met. In other words, these methods can produce accurate results even if the data does not perfectly conform to a normal distribution [73].

For descriptive statistics, categorical variables using frequencies and percentages and described continuous variables using means and standard deviations were used. We used bivariate correlations to examine group differences in eco-anxiety dimensions, PEB, direct and psychosocial experience items, indirect experiences, and engagement items in a parsimonious manner. Specifically, Pearson’s correlation was used to assess relationships between two scalar variables, while point-biserial correlation was applied for associations between a scalar and a dichotomous variable (e.g., gender, growth area). As with other analyses, normality assumptions were checked to ensure the appropriateness of the statistical tests used. The results of these correlation analyses were corrected for multiple comparisons using a false discovery rate (FDR) of 5%, based on the sequential FDR correction algorithm [74]. The correction was performed using the p.adjust function in R (version 4.4.2), with the fdr method. Multiple linear regression analyses were conducted to identify factors uniquely associated with these dimensions and behaviours, with a significance level set at p < .05. The effect sizes evaluated for the regression tests were assessed using the criteria established by Cohen [75], where an f² of 0.02 is considered a small effect, 0.15 a moderate effect, and 0.35 a large effect.

Results

The sample comprised 54 (12.8%) men and 369 (87.2%) women, reflecting the predominance of female enrolment in health sciences degrees in Spain, with a mean age of 20.8 years (SD = 1.9). Additional demographic information about the sample is provided in Table 1.

Table 1.

Sociodemographic characteristics of the sample

	M	SD
Age	20.8	1.9
Min.	18	-
Max.	25	-
Educational level (number of years)	16.7	3.3
	N	%
Gender
Male	54	12.8
Female	369	87.2
The area where participants grew up in
Rural	76	18.0
Urban	347	82.0
The area participants currently live in
Rural	46	10.9
Urban	377	89.1
Chronic mental illness
Yes	38	9.0
No	385	91.0
Chronic physical illness
Yes	45	10.6
No	378	89.4

Note. n, number of cases; M, mean; SD, standard deviation; Max., maximum value; Min, minimum value

Descriptive and correlational analyses of the study variables are presented in Table 2. Hypothesis 1a was partially corroborated: In the dimension of personal impact anxiety, women scored higher than men; however, no differences were found for affective symptoms. Hypothesis 1b was not corroborated, as education did not correlate with any dimension of eco-anxiety. Hypothesis 1c was partially corroborated, as individuals who grew up in urban environments had higher scores in behavioural symptoms, while place of residence did not yield significant scores. These individuals also reported higher scores in PEB. Finally, Hypothesis 1d was corroborated since direct or indirect experiences of climate events scored higher in eco-anxiety dimensions, with coefficients relatively higher for direct experiences than indirect experiences.

Table 2.

Correlations between sociodemographics, direct or indirect experiences of climate events, dimensions of eco-anxiety, PEB, and life satisfaction

	M (SD) / %	1.	2.	3.	4.	5.	6.	7.	8.1	8.2	8.3	9	10.1	10.2	10.3	10.4	11
1. Age (in years)	20.8 (1.9)	1.00
2. Gender (male 0; female 1)	0 = 12.8%	− 0.04	1.00
3. Educational level (in years)	16.7 (3.3)	0.37***	0.01	1.00
4. Growth area (rural 0; urban 1)	0 = 18.0%	0.01	− 0.09	− 0.02	1.00
5. Living area (rural 0; urban 1)	0 = 10.9%	− 0.04	0.00	− 0.01	0.67***	1.00
6. Chronic physical illness (yes 0; no 1)	0 = 10.6%	− 0.10	0.03	0.08	0.04	0.05	1.00
7. Chronic mental illness (yes 0; no 1)	0 = 9.0%	0.02	− 0.07	0.00	0.09	0.10	0.16**	1.00
8. Indirect experience
8.1 Information seeing	2.8 (1.5)	0.07	− 0.04	0.02	0.03	− 0.07	− 0.02	− 0.04	1.00
8.2 Information seeking	1.2 (1.2)	0.06	− 0.04	− 0.01	0.01	− 0.07	− 0.02	− 0.03	0.40***	1.00
8.3 Information avoidance	1.4 (1.7)	− 0.01	− 0.10	− 0.10	− 0.06	− 0.07	− 0.01	− 0.11	0.16**	0.17**	1.00
9. Direct experience	19.8 (8.8)	0.00	0.10	− 0.06	− 0.06	− 0.02	− 0.03	− 0.09	0.23***	0.28***	− 0.01	1.00
10. HEAS
10.1 Affective symptoms	1.0 (0.7)	− 0.07	0.09	− 0.05	− 0.08	− 0.05	0.05	− 0.22***	0.08	0.23***	0.10	0.28***	1.00
10.2 Rumination	0.7 (0.6)	0.05	0.01	0.01	− 0.01	− 0.04	− 0.02	− 0.01	0.19***	0.29***	0.03	0.37***	0.43***	1.00
10.3 Behavioural symptoms	0.6 (0.7)	− 0.05	0.05	0.00	− 0.11*	− 0.10	− 0.02	− 0.29***	0.07	0.14**	0.11**	0.30***	0.58***	0.24***	1.00
10.4 Personal impact anxiety	0.8 (0.6)	0.09	0.14**	0.04	− 0.01	− 0.04	− 0.01	− 0.02	0.16**	0.27***	0.08	0.38***	0.36***	0.59***	0.23***	1.00
11. PEB	1.4 (0.3)	0.10*	0.00	0.04	− 0.12*	− 0.10*	− 0.08	− 0.10	0.21***	0.30***	− 0.02	0.41***	0.18***	0.35***	0.18***	0.44***	1.00
12. Life satisfaction	5.1 (1.1)	0.09	− 0.03	0.08	0.10	0.07	0.02	0.31***	− 0.02	− 0.13**	− 0.09	− 0.14*	− 0.29***	− 0.08	− 0.31***	− 0.12*	− 0.02

Note. ^*p < .05. ^**p < .01. ***p < .00

When analysing each gender subgroup separately to explore differences according to residential environment (urban vs. rural), no statistically significant differences were found in direct and psychosocial experience, indirect experience, eco-anxiety dimensions, PEB, or life satisfaction. These results were consistent for both men and women (see Table 3).

Table 3.

Comparison of mean scores on psychological variables by type of residence (urban vs. rural) in female and male subsamples

	Gender	Rural M (SD)	Urban M (SD)	t (df)	p
HEAS
Affective symptoms	Female	1.08 (0.69)	0.97 (0.65)	0.984 (47.686)		0.330
	Male	0.87 (0.77)	0.80 (0.61)	0.207 (5.818)		0.843
Rumination	Female	0.68 (0.46)	0.65 (0.58)	0.321 (55.493)		0.750
	Male	1.00 (1.05)	0.60 (0.55)	0.904 (5.349)		0.405
Behavioural symptoms	Female	0.77 (0.90)	0.56 (0.64)	1.456 (43.940)		0.152
	Male	0.61 (0.57)	0.47 (0.48)	0.540 (5.910)		0.609
Personal impact anxiety	Female	0.89 (0.62)	0.84 (0.63)	0.417 (49.204)		0.678
	Male	0.88 (0.68)	0.54 (0.62)	1.153 (6.061)		0.292
Direct & psychosocial experience	Female	20.52 (8.53)	20.03 (8.87)	0.338 (49.822)		0.737
	Male	18.66 (10.13)	17.35 (8.16)	0.305 (5.840)		0.771
Indirect experience
See information	Female	3.02 (1.32)	2.73 (1.49)	1.282 (51.703)		0.206
	Male	3.50 (2.07)	2.89 (1.50)	0.691 (5.678)		0.517
Seek information	Female	1.37 (1.14)	1.16 (1.13)	1.099 (48.710)		0.277
	Male	1.83 (1.60)	1.27 (1.21)	0.831 (5.743)		0.439
Avoid information	Female	1.57 (1.90)	1.24 (1.60)	1.037 (45.940)		0.305
	Male	2.33 (2.33)	1.72 (2.11)	0.603 (6.064)		0.568
Pro-environmental behaviour	Female	1.53 (0.39)	1.42 (0.32)	1.655 (45.497)		0.105
	Male	1.54 (0.34)	1.41 (0.31)	0.856 (6.075)		0.424
Satisfaction with Life	Female	4.80 (1.54)	5.10 (1.02)	-1.224 (43.292)		0.228
	Male	5.23 (0.79)	5.16 (1.15)	0.194 (7.942)		0.851

Note. M, mean; SD, standard deviation; t test, *p < .05, **p < .01, ***p < .001. Welch’s t test was used due to unequal variances between groups. The analysed variables were direct and psychosocial experience, indirect experience, eco-anxiety, PEB, and life satisfaction

Positive correlations were also found in the dimensions of eco-anxiety, PEB, and life satisfaction. Hypothesis 2a was corroborated: Participants who reported higher levels of rumination and personal impact anxiety also indicated taking more steps to reduce their ecological footprint. The symptomatic dimensions of eco-anxiety (affective and behavioural symptoms) were also related to PEB. However, the correlation between PEB and rumination/personal impact anxiety was relatively higher than the correlation between PEB and affective/behavioural symptoms. Hypothesis 2b was also corroborated, with life satisfaction inversely related to affective and behavioural symptoms, suggesting that higher scores in these dimensions of eco-anxiety were associated with lower levels of life satisfaction. Life satisfaction was also related to personal impact anxiety, but this relationship was relatively weaker, and no correlation was found to rumination.

Additionally, direct and psychosocial experiences of climate events exhibited significant and positive correlations with all dimensions of eco-anxiety and PEB, and negative correlations with life satisfaction. Both seeing and seeking information were positively correlated with direct and psychosocial experiences of climate events. Specifically, seeing information positively correlated with rumination and personal impact anxiety; however, it also directly correlated with PEB. Seeking information showed positive and significant correlations with all dimensions of eco-anxiety and PEB, and negative correlations with life satisfaction. Avoiding information positively correlated with affective symptoms and behavioural symptoms, although the strength of these associations was low, as detailed in Table 2.

Predicting the dimensions of eco-anxiety

To examine the combined effects of sociodemographic variables and experiences of climate events, these variables were entered into multiple linear regression models predicting the dimensions of eco-anxiety, detailed in Table 4; Fig. 1. All regression assumptions, including multicollinearity, were met. Consistent with the simple correlations presented and further supporting Hypothesis 1a, gender emerged as a significant predictor of personal impact anxiety, suggesting that female-identified participants experienced greater personal impact anxiety. However, no differences were found for age, education, or growth/living area in these models. Regarding experience of climate events, direct and psychosocial experiences, as well as seeking information about climate change emerged as the most relevant predictors. Direct experience of climate events was a significant positive predictor for all dimensions of eco-anxiety. Seeking information about climate change was a significant predictor of affective symptoms, rumination, and personal impact anxiety. These effects were observed while controlling for chronic physical and mental illness. Notably, participants who disclosed having a chronic mental illness exhibited significantly higher levels of affective and behavioural symptoms of eco-anxiety.

Table 4.

Regression coefficients from linear regression models for dimensions of eco-anxiety as dependent variables and sociodemographic, direct or indirect experiences of climate events as predictors (N = 423)

	Affective symptoms R2 = 0.16; Adj R2 = 0.14 f² = 0.19			Rumination R2 = 0.18; Adj R2 = 0.16 f² = 0.22			Behavioural symptoms R2 = 0.18; Adj R2 = 0.16 f² = 0.22			Personal impact anxiety R2 = 0.21; Adj R2 = 0.19 f² = 0.27			VIF
	β	B	95% CI	β	B	95% CI	β	B	95% CI	β	B	95% CI
Age (in years)	− 0.06	− 0.02	[-0.05, 0.01]	0.02	0.01	[-0.02, 0.04]	0.06	− 0.02	[-0.05, 0.01]	0.07	0.02	[-0.01, 0.06]	1.205
Gender (male 0; female 1)	0.06	0.11	[-0.07, 0.29]	− 0.01	− 0.02	[-0.17, 0.14]	0.004	0.01	[-0.17, 0.18]	0.13	0.25**	[0.08, 0.42]	1.045
Educational level (in years)	− 0.01	− 0.003	[-0.02, 0.02]	0.02	0.004	[-0.01, 0.02]	0.04	0.01	[-0.01, 0.03]	0.04	0.01	[-0.01, 0.03]	1.209
Growth area (rural 0; urban 1)	− 0.05	− 0.08	[-0.29, 0.13]	0.03	0.05	[-0.13, 0.23]	− 0.05	− 0.09	[-0.29, 0.12]	0.06	0.09	[-0.10, 0.29]	1.880
Living area (rural 0; urban 1)	0.01	0.02	[-0.23, 0.28]	− 0.04	− 0.08	[-0.30, 0.15]	− 0.03	− 0.06	[-0.31, 0.20]	− 0.05	− 0.11	[-0.35, 0.13]	1.871
Chronic physical illness	0.09	0.18	[-0.01, 0.38]	− 0.01	− 0.01	[-0.18, 0.16]	0.02	0.05	[-0.15, 0.24]	0.001	− 0.001	[-0.18, 0.18]	1.058
Chronic mental illness	− 0.19	− 0.44***	[-0.65, − 0.23]	0.03	0.06	[-0.13, 0.24]	− 0.25	− 0.57***	[-0.78, − 0.37]	0.03	0.07	[-0.13, 0.27]	1.065
Indirect experience
Information seeing	− 0.05	− 0.02	[-0.07, 0.02]	0.04	0.01	[-0.02, 0.05]	− 0.04	− 0.02	[-0.06, 0.03]	0.01	0.002	[-0.04, 0.04]	1.247
Information seeking	0.18	0.10***	[0.05, 0.16]	0.19	0.09***	[0.04, 0.14]	0.06	0.04	[-0.02, 0.09]	0.16	0.09**	[0.04, 0.14]	1.273
Information avoidance	0.07	0.03	[-0.01, 0.06]	0.003	0.001	[-0.03, 0.03]	0.08	0.03	[-0.003, 0.07]	0.08	0.03	[-0.01, 0.06]	1.087
Direct experience	0.22	0.02***	[0.01, 0.02]	0.32	0.02***	[0.02, 0.03]	0.27	0.02***	[0.01, 0.03]	0.33	0.02***	[0.01, 0.03]	1.148

Note. R² = R squared, Adj R² = Adjusted R², f² = Cohen f², β = standardised regression coefficients; B = unstandardized coefficients; CI = confidence interval around the unstandardised B coefficients; *p < .05; **p < .01; ***p < .001. VIF = Variance Inflation Factor

Fig. 1.

Graphical representation of multiple linear regression models predicting dimensions of eco-anxiety based on sociodemographics and experiences of climate events. Note. The coloured lines correspond to the interval around the unstandardized B coefficients, while the points correspond to the unstandardized Beta coefficients

Predicting PEB and life satisfaction

To examine the combined effects of sociodemographic variables, experiences of climate events, and dimensions of eco-anxiety, these variables were entered into multiple linear regression models to predict PEB and life satisfaction, as depicted in Table 5; Figs. 2 and 3. All the regression assumptions, including multicollinearity, were met.

Table 5.

Regression coefficients from linear regression models for PEB and life satisfaction as dependent variables, and sociodemographics, direct or indirect experiences of climate events and dimensions of eco-anxiety as predictors (N = 423)

	PEB R2 = 0.32; Adj R2 = 0.30 f² = 0.47			Life satisfaction R2 = 0.19; Adj R2 = 0.16 f² = 0.23			VIF
	β	B	95% CI	β	B	95% CI
Age (in years)	0.05	0.01	[-0.01, 0.02]	0.05	0.03	[-0.03, 0.08]	1.221
Gender (male 0; female 1)	− 0.07	− 0.07	[-0.15, 0.01]	0.02	0.07	[-0.23, 0.37]	1.080
Educational level (in years)	0.01	0.001	[-0.01, 0.01]	0.05	0.02	[-0.02, 0.05]	1.216
Growth area (rural 0; urban 1)	− 0.12	− 0.11*	[-0.20, − 0.01]	0.06	0.18	[-0.17, 0.52]	1.891
Living area (rural 0; urban 1)	0.02	0.02	[-0.10, 0.13]	− 0.01	− 0.05	[-0.47, 0.37]	1.878
Chronic physical illness	− 0.04	− 0.05	[-0.13, 0.04]	− 0.01	− 0.04	[-0.37, 0.28]	1.070
Chronic mental illness	− 0.07	− 0.08	[-0.18, 0.02]	0.24	0.91***	[0.55, 1.27]	1.162
Indirect experience
Information seeing	0.06	0.01	[-0.01, 0.03]	0.04	0.03	[-0.04, 0.10]	1.254
Information seeking	0.14	0.04**	[0.01, 0.07]	− 0.09	− 0.08	[-0.18, 0.01]	1.338
Information avoidance	− 0.09	− 0.02*	[-0.03, − 0.002]	− 0.01	− 0.01	[-0.07, 0.05]	1.105
Direct experience	0.23	0.01***	[0.01, 0.01]	− 0.02	− 0.003	[-0.02, 0.01]	1.377
HEAS
Affective symptoms	− 0.07	− 0.04	[-0.09, 0.02]	− 0.14	− 0.24*	[-0.44, − 0.03]	1.860
Rumination	0.07	0.04	[-0.02, 0.10]	0.08	0.16	[-0.06, 0.38]	1.790
Behavioural symptoms	0.02	0.01	[-0.04, 0.06]	− 0.14	− 0.23*	[-0.42, − 0.04]	1.658
Personal impact anxiety	0.30	0.16***	[0.10, 0.21]	− 0.07	− 0.12	[-0.32, 0.08]	1.710

Note. R² = R squared, Adj R² = Adjusted R², f² = Cohen f², β = standardised regression coefficients; B = unstandardized coefficients; CI = confidence interval; *p < .05; **p < .01; ***; p < .001. VIF = Variance Inflation Factor

Fig. 2.

Graphical representation of multiple linear regression models predicting pro-environmental behaviour. Note. The coloured lines correspond to the interval around the unstandardized B coefficients, while the points correspond to the unstandardized Beta coefficients

Fig. 3.

Graphical representation of multiple linear regression models predicting life satisfaction. Note. The coloured lines correspond to the interval around the unstandardized B coefficients, while the points correspond to the unstandardized Beta coefficients

The significant predictors for PEB included growing up in a rural area, which was associated with increased PEB compared to growing up in an urban area. Direct and psychosocial experiences of climate events, along with seeking information about climate change were positive predictors of PEB while avoiding such information was a negative predictor. Additionally, personal impact anxiety was a positive predictor of PEB.

Regarding the life satisfaction model, no sociodemographic variables were significant predictors. However, the eco-anxiety dimensions of affective and behavioural symptoms were negative predictors of life satisfaction. This model also accounted for the significant effect of having a chronic mental illness.

Discussion

The current ecological crisis not only threatens the environment but also affects the mental health and psychological well-being of current and future generations. Increasing public awareness of this crisis has been linked to heightened eco-anxiety, even among individuals not directly experiencing environmental challenges. This study aimed to expand the knowledge base on eco-anxiety by analysing the relationships between eco-anxiety, sociodemographic factors, experiences of climate events, PEB, and life satisfaction among young adults. Through cross-sectional data, sociodemographic variables and experiences were found to be likely predictors of eco-anxiety, while PEB and life satisfaction were interrelated variables of eco-anxiety.

Predictors of eco-anxiety

These study results suggest that the effects of sociodemographic variables and direct/indirect experience on eco-anxiety are not straightforward and are likely shaped by additional, unmeasured factors. While the percentage of variance explained by the models was modest, the overall effect sizes were medium, indicating that the included predictors make a meaningful practical contribution. These findings highlight the importance of further research to identify other relevant influences on eco-anxiety and to deepen understanding of its underlying mechanisms.

Consistent with existing literature, differences related to gender exhibited women experiencing higher levels of personal impact anxiety, and this difference remained even after accounting for sociodemographic factors and direct or indirect experiences of climate events. Despite exhibiting higher levels of personal impact anxiety, women did not report more affective symptoms of eco-anxiety, consistent with previous studies [25, 33]. Additionally, women reported more direct and psychosocial experiences of climate events than men and expressed less avoidance of information, aligning with findings from Hogg et al. [17]. These findings corroborate previous research, indicating that women are more vulnerable to climate change and environmental problems. Women often face higher risks and greater burdens from climate change impacts due to economic dependence, less access to education, and rooted cultural norms [76, 77].

Contrary to expectations, neither education level nor living area were direct predictors of eco-anxiety in the regression models. No significant direct relationship between education and eco-anxiety emerged. However, education level was associated with a lower (non-significant) tendency to avoid climate change information, suggesting that education might have an indirect influence on eco-anxiety through factors such as personal experiences with climate change, media exposure, or psychological resilience. This aligns with Angrist et al. [78], who found that additional years of education increased pro-climate beliefs and behaviours. Future research could explore whether education shapes eco-anxiety through mediating factors such as political orientation, social norms, or perceived vulnerability to climate-related events.

Living area was correlated in an unexpected manner to experiencing more behavioural symptoms of eco-anxiety and this relationship became non-significant when entered into a regression model with the additional variables. While studies typically suggest that urban residents tend to report higher eco-anxiety, we found that growing up in rural areas was linked to greater behavioural symptoms of eco-anxiety. This could be due to the more direct exposure individuals in rural areas have to environmental changes. In rural contexts, people often rely on natural resources for their livelihoods (e.g. agriculture, and fishing) [79], which might lead to stronger behavioural responses. While this effect did not hold in the regression model, the initial association suggests that area of living may exert an indirect effect on eco-anxiety, potentially mediated by individuals’ exposure to environmental change or dependency on natural resources. People from rural areas also reported higher levels of PEB. These findings align with previous research, which claims that people from rural backgrounds have stronger environmental identity and connection to nature, which provides insight into the higher PEB of rural populations compared to urban dwellers [80, 81]. Moreover, PEB appears to be related to the proximity of neighbourhood greenspace, independent of household socio-economic status [82].

Regarding the relationship between experiencing climate events and eco-anxiety, our findings showed that, although bivariate correlations and regression models yielded different patterns, direct experience and information seeking emerged as robust predictors of eco-anxiety. Regression models revealed that directly experiencing climate events predicted all the dimensions of eco-anxiety and that information seeking predicted increased affective symptoms, rumination and personal impact anxiety. The bivariate correlations between eco-anxiety and both seeking and avoiding information did not hold when controlling for sociodemographic factors and direct or indirect experiences of climate events. Overall, these results align with several studies arguing that eco-anxiety is experienced due to direct or indirect impacts of ecological breakdown, climate change, and biodiversity loss [46, 83–85]. Seeking information allows the development of a reflective process about environmental events (even not directly experiencing them) [86], potentiating the increase in eco-anxiety. Hogg et al. [17] also reported significant positive associations between several indirect climate experiences and all dimensions of eco-anxiety when analysed as bivariate correlations. However, through path analysis, direct experience of climate events was no longer associated with personal impact anxiety, and seeing information was not related to any dimension of eco-anxiety [17]. Future research should explore the relationship between information-seeking and specific eco-anxiety dimensions, as well as how different types of climate information (e.g., alarming vs. solution-focused content) shape eco-anxiety and subsequent engagement in pro-environmental behaviour.

Relationship between eco-anxiety, PEB and life satisfaction

The regression model predicting PEB accounted for a substantial portion of the variance, with a large effect size suggesting that the combination of sociodemographic factors, direct and indirect experience, and eco-anxiety meaningfully contributes to explaining individual differences in PEB. These results indicate a strong and practically significant relationship between the predictors and PEB, reinforcing the importance of psychological and experiential variables in fostering environmentally responsible actions. In particular, people with higher personal impact anxiety, direct experience of climate events, and actively engaged in seeing and seeking information on the topic were more likely to report PEB. Therefore, PEB may represent an adaptive response to environmental challenges and protective of the environment [37]. Conversely, greater information avoidance was associated with reduced PEB. Avoidance is a coping strategy where individuals distance themselves from stressors [87], which does not align with involvement in environmental protection and mitigating environmental issues [51]. These results contribute to understanding factors that may influence PEB within the proposed U-shaped relationship between eco-anxiety and environmental engagement [25].

The regression model predicting life satisfaction explained a smaller proportion of variance but had a medium effect size, suggesting that the predictors offer a practically relevant contribution, but unmeasured variables may play a more prominent role in shaping life satisfaction. In particular, a lower level of life satisfaction was associated with direct experiences of climate events, seeking information, and higher levels of eco-anxiety affective and behavioural symptoms. These findings are corroborated by studies arguing that higher levels of eco-anxiety were associated with poorer mental health [22, 88], in particular with its symptomatic dimensions [25]. Given this, there is increasing recognition of the need for interventions that help individuals manage the psychological impacts of climate-related distress. Mindfulness-based approaches and ecotherapy have been highlighted as promising strategies to reduce affective symptoms and promote psychological resilience in the context of ecological concerns [20]. Our results also showed that individuals with chronic mental illness experienced more behavioural and affective symptoms and reported lower life satisfaction. Chronic illnesses introduce additional stressors, often amplifying negative emotional responses such as anxiety [89].

Of relevance, our study findings suggest that eco-anxiety is associated with both PEB and life satisfaction, albeit through different dimensions. Personal impact anxiety was associated with increased PEB, while the symptomatic aspects of eco-anxiety (affective and behavioural symptoms) were uniquely linked to lower life satisfaction. These results generally align with those of Hogg et al. [25], with the exception of rumination. In contrast to their findings, rumination did not significantly contribute to PEB in our regression model, suggesting it does not independently explain pro-environmental behaviour when accounting for shared variance among predictors. Furthermore, this result highlights the potentially central role of personal impact anxiety in promoting PEB, in line with previous research [53]. Consistent with theoretical models of anxiety as both functional and pathological [90], our findings suggest that eco-anxiety may encompass both adaptive and maladaptive dimensions. Specifically, personal impact anxiety appears to play an adaptive role, motivating greater PEB, whereas affective and behavioural symptoms of eco-anxiety were associated with lower life satisfaction, reflecting more maladaptive aspects. This supports the idea that eco-anxiety, like general anxiety, may vary in its degree of adaptiveness depending on the psychological processes and outcomes involved. Future research should continue to differentiate these dimensions to better understand eco-anxiety’s dual role in environmental action and mental health.

Limitations

Despite the valuable insights provided by our study, several limitations must be acknowledged. Firstly, the cross-sectional design limits causal inference between eco-anxiety, sociodemographic factors, experience of climate events, PEB, and life satisfaction. Without longitudinal or experimental data, it is challenging to determine, for instance, whether eco-anxiety drives behavioural engagement or vice versa. Future studies are needed to deepen our understanding of these relationships over time. Additionally, self-reported data may introduce biases, such as social desirability or recall bias, which could influence the accuracy of the findings.

Another limitation of the study is sample representativeness. The sample was predominantly composed of university students from two health science centres in Spain, and most participants were women (87.2%), potentially limiting generalisability to the broader young adult population. Expanding the sample to include a more diverse demographic, with better gender balance, balanced age cohorts, and cross-cultural representation, would enhance the external validity of the findings.

Furthermore, this study did not account for specific contextual factors, such as local environmental policies or recent climate events, which could influence the levels of eco-anxiety and PEB. Another important limitation is that the measure of indirect experience and engagement assessed the frequency of exposure to climate change-related information but did not account for the valence of media exposure (e.g., alarmist vs. solution-oriented narratives). Prior research suggests that the emotional framing of climate information can influence psychological responses, including levels of eco-anxiety. Future studies should consider evaluating the qualitative aspects of media exposure to better understand its differential effects on eco-anxiety and engagement with pro-environmental behaviours.

Another limitation of this study is that indirect experience with climate change was assessed using three single-item measures, which may limit the reliability and depth of the construct. Future research should consider using or developing multi-item validated scales to capture this dimension more robustly.

Lastly, while various sociodemographic factors were considered, unexamined variables, including climate awareness, cultural values and norms, socioeconomic status, and local environmental policies may also play significant roles in eco-anxiety and related behaviours. Future research should consider incorporating mediation and moderation analyses to better disentangle these effects and provide a more comprehensive understanding of the relationships examined. Addressing these limitations in future research will provide a more comprehensive understanding of the factors influencing eco-anxiety and its impacts on individuals’ well-being and environmental actions.

Conclusions

This study helps elucidate the intricate relationships between eco-anxiety, sociodemographic factors, experiences of climate events, PEB, and life satisfaction among young adults.

Women, with chronic mental illnesses and with direct experience of climate events, are more likely to experience higher eco-anxiety levels. Identifying these sensitive groups highlights the need for more targeted environmental policies that prioritize psychological support and adaptation to climate change impacts. Additionally, individuals with indirect exposure to environmental events - particularly those who sought information - reported higher levels of eco-anxiety and engagement in PEB. Therefore, information can play a critical role in raising public awareness of climate change, increasing eco-anxiety related to environmental threats and promoting PEB. Information on the topic should be made available clearly and thoughtfully to promote consistent environmental behaviours.

Eco-anxiety acted as a motivator for PEB but reduced life satisfaction among young adults. Different dimensions of eco-anxiety promoted PEB (personal impact anxiety) and decreased life satisfaction (eco-anxiety affective and behavioural symptoms). However, as noted by Hogg and colleagues [17, 25], these eco-anxiety dimensions are interdependent, meaning that as individuals experience more affective and behavioural symptoms of eco-anxiety, they also experience higher levels of rumination and personal impact anxiety. Consequently, this interaction increases the likelihood of both mental health challenges and engagement in PEB. Therefore, understanding the intercorrelations between these dimensions is essential before implementing any recommendations to either treat the symptoms of eco-anxiety that decrease satisfaction with life or leverage the dimensions that promote pro-environmental behaviour.

Effectively addressing eco-anxiety requires a multifaceted approach that considers individual antecedents, direct and indirect experiences of climate events, and proactive engagement in environmental issues. Future research should explore these relationships longitudinally and include more diverse samples, such as non-student populations and individuals from different cultural contexts, to promote the generalizability of results. By understanding and addressing the various factors that contribute to eco-anxiety, we can better support young adults in managing their environmental concerns and encouraging sustainable behaviours.

This study provides concrete insights to inform interventions at both clinical and policy levels. To alleviate the distressing aspects of eco-anxiety evidence-based clinical approaches such as cognitive-behavioural therapy, mindfulness training, and ecotherapy may be useful in managing emotional distress and fostering adaptive coping. Interventions should also aim to harness motivational dimensions of eco-anxiety, such as personal impact anxiety, to promote pro-environmental engagement. Mental health services for young adults could benefit from integrating strategies that encourage active engagement with climate issues in a constructive way. On a broader scale, climate communication efforts should strike a balance between conveying environmental risks and offering actionable solutions. Overly alarmist or threat-focused messages may foster helplessness, whereas solution-oriented content can enhance individuals’ sense of agency and encourage behavioural change. Future studies should evaluate the effectiveness of such approaches and their applicability across different cultural and demographic settings.

Author contributions

FS: conceptualization, methodology, writing – review & editing, supervision, project administration. JRM, AMP: methodology, formal analysis, investigation, resources, writing – original draft, writing – review & editing, visualisation. EM, CB, AA, ARQ: formal analysis, resources, writing – original draft, writing – review & editing. TC, LGP, LTS: writing – original draft, writing – review & editing. CS: funding acquisition, writing – review & editing. SL: validation, formal analysis, resources, writing – original draft, writing – review & editing.

Funding

This article was supported by National Funds through FCT - Fundação para a Ciência e a Tecnologia, I.P., within CINTESIS, R&D Unit (reference UIDB/4255/2020 and Hei-Lab (reference UIDP/00713/2020 and reference UIDB/05380/2020).

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The authors confirm that all experiments followed the Declaration of Helsinki recommendations. Ethical approval was obtained from the Bioethics Committee of the Universitat de Barcelona Ethics of Human Research. The use of the scales was allowed by their original authors. The participants completed informed consent.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.