Associations between climate change and mental health conditions of German university students

Abstract

As higher education students constitute a population characterized by relatively young age, limited resources, high media engagement, and likely elevated concerns regarding the future, they can be expected to be susceptible to climate-related mental health issues. Therefore, this study aimed to examine the association between climate change-related factors and mental health of German higher education students, addressing a distinct gap in existing research. From November 2024 to February 2025, an anonymous online survey was conducted among enrolled higher education students at universities across Germany. The questionnaire combined validated assessment tools for measuring mental stress/health (Patient Health Questionnaire (PHQ-4), Self-Rated Mental Health (SRMH)), the Climate Change Anxiety Scale (CCAS), and further climate change factors that may potentially influence mental health. Correlations were calculated between the PHQ-4 and CCAS, SRMH and CCAS, and between CCAS and climate change factors. 4,494 students took part in the survey. More than half (51.0%) were found to experience climate change anxiety. Climate change anxiety and measured psychological stress correlated positively, and accordingly, climate change anxiety correlated negatively with SRMH. Current mental illness, beliefs about climate change, the frequency with which students consumed information about climate change, certain information channels, the total number of information channels, motivation to engage in, as well as existing climate-friendly behavior, personal experience of extreme weather events, and female gender identity was significantly associated with higher climate change anxiety. Despite significant correlations between the relationship between climate change and deteriorating mental health, further research is needed to better understand the causal mechanisms underlying this relationship and to inform the development of targeted support measures.

1 Introduction

The World Health Organization titled climate change as the “single biggest health threat facing humanity” in the COP26 special report on climate change (WHO, 2021). With improved understanding of the risks to general physical health, including heat-related illness, respiratory and cardiovascular conditions, infectious diseases, and malnutrition, there is also growing concern about mental health conditions associated with climate change (Ebi et al., 2021; WHO, 2023; Skevaki et al., 2024).

Establishing a definitive causal relationship between climate change and specific health implications is challenging, though. Nevertheless, climate change is associated with an increase in the frequency and severity of natural disasters and extreme weather events and exposure to these has an obvious association with human health (Walinski et al., 2023).

Climate change is associated with mental health directly and indirectly. Exposure to traumatic events such as heatwaves, bushfires, and floods could be considered a direct association. These can trigger psychological distress, post-traumatic stress, depressive symptoms, anxiety, increased medication use, and, in severe cases, suicide (Fernandez et al., 2015; Cianconi et al., 2020; Charlson et al., 2021).

Pre-existing mental illnesses reduce an individual’s capacity to cope with environmental stressors such as extreme heat, floods, and wildfires. For example, high temperatures impair cognition and mood and may aggravate conditions like depression, psychosis, and cognitive impairment, especially for those who are on psychotropic medications that can interfere with thermoregulation. Climate-related disasters are associated with increased risk of severe mental health deterioration, including PTSD, substance abuse, and suicide, when combined with financial stress and displacement (Cordiner et al., 2025). Beyond direct associations, these individuals were also found more vulnerable to indirect climate-related impacts, including displacement, migration, food insecurity, malnutrition, breakdowns in health and social care systems, conflict, and broader economic and social disruptions (Cissé et al., 2022). Indirect effects can arise from broader political, social, and economic determinants of mental health, such as poverty, unemployment, and inadequate housing, that are increasingly reshaped by environmental change (Charlson et al., 2021; Walinski et al., 2023).

The association between climate change and mental health is likely to affect migrants and the displaced population as well. These populations are more vulnerable to psychological distress such as anxiety, depression, and pessimism, which can result from both migration itself and the difficulties of adjusting to a new culture (Bustamante et al., 2017). In addition, these risks are understood to be worsened by institutional and economic instability, which is associated with conflict and is associated with increased risk of displacement linked to environmental factors (Walinski et al., 2023). Therefore, in the larger context of climate-related vulnerability, migrants and displaced individuals represent a disproportionately affected group (van Daalen et al., 2024).

Moreover, individuals with lower socioeconomic status were found disproportionately affected by climate change, i.e., vulnerable, as they experience greater exposure to heat and air pollution, have a higher prevalence of pre-existing mental health conditions, and are associated with an increased vulnerability to social isolation and discrimination (Heinz and Brandt, 2024). Due to their reduced capacity to adapt to climate-related health conditions, they are less able to cope with, manage, and recover from environmental stressors, which can aggravate mental health conditions (Ingle and Mikulewicz, 2020). Moreover, a low income often implies a lack of resources and economic stability, which is associated with a higher vulnerability to mental health consequences of climate change, such as persistent stress, anxiety, and depression (Fahrudin et al., 2024).

In a global study across 10 countries, 10,000 young people aged 16 to 25 took part in a survey investigating their feelings towards climate change and governmental responses to it. The survey included 1,000 young people from each of these countries: Australia, Brazil, Finland, France, India, Nigeria, the Philippines, Portugal, the United Kingdom, and the United States. The results showed that participants across all countries were already concerned about climate change, with 84% at least moderately concerned and 59% very or extremely concerned. More than half of the participants reported feeling “afraid, sad, anxious, angry, powerless, helpless, and guilty” about climate change, and nearly half indicated that these emotions negatively affected their daily lives. Furthermore, 75% of the participants stated that they were afraid of the future due to climate change, and “83% believe that humans have failed to take care of the planet” (Hickman et al., 2021). Although a certain degree of worry or anxiety regarding climate change can be seen as an appropriate, even healthy, reaction to climate change, these negative emotions can result in a serious mental health burden as soon as their extent exceeds one’s own ability to cope with them (Clayton et al., 2021).

Climate anxiety has been linked to uncertainty about how, when, and where the effects of climate change will manifest. Additionally, increased media exposure to environmental information has been associated with stronger negative feelings and lower general well-being (Wang and Liu, 2024). Students in higher education, mostly belonging to Generation Z (born 1997–2012), appear particularly vulnerable to climate anxiety (Marcolini et al., 2025). Their stage of personal development, increased knowledge, as well as exposure to climate-related material in the media and regular usage of social media can all be associated with a persistent anxiety and sense of helplessness over climate change (Gunasiri et al., 2022; Marcolini et al., 2025).

According to Clayton (2020), experiencing a certain degree of anxiety, worry, or distress in response to climate change is a normal and psychologically understandable reaction, given the magnitude and harmful consequences of the climate crisis. Research suggests that such negative climate-related emotions are not necessarily associated with detriments to mental health. Rather, they have been associated with greater motivation for climate-friendly behavior when accompanied by a sense of hope, efficacy, or perceived agency. In this context, emotions such as concern, worry, or moral unease may motivate individuals to engage in pro-environmental actions to restore coherence between values and behavior (Clayton et al., 2021).

Empirical findings support this relationship. Wullenkord et al. (2021) reported a positive correlation between climate anxiety and stronger “expressed pro-environmental intentions,” indicating that individuals who experience stronger emotional responses to climate change are often more motivated to engage in climate-friendly behavior. Similarly, studies by Sibley and Kurz (2013) and Zawadzki et al. (2020) demonstrate that climate change beliefs and moral emotions, such as guilt or moral responsibility, predict motivation to adopt climate-friendly behaviors and to support climate-related policies. These findings suggest that moral and emotional engagement with climate change can enhance motivation to act, which may, in turn, be associated with a sense of purpose and value-based meaning.

However, the mental health effects of climate-related emotions depend strongly on whether individuals perceive viable pathways for action. When negative emotions such as anxiety or grief are experienced without hope or perceived efficacy, they are known to be associated with passivity and resignation rather than engagement and have been shown to have detrimental effects on mental health (Clayton et al., 2021). Ojala et al. (2021) similarly emphasize that while worry can promote efficacy beliefs and climate-friendly actions, unresolved climate-related negative emotions can impair well-being. Thus, motivation for climate-friendly behavior can serve as a protective psychological factor, buffering the potential adverse mental health effects of climate distress by transforming concern into meaningful action.

Importantly, the relationship between climate-friendly behavior and mental health appears to be bidirectional. Not only can climate-related emotions motivate action, but engaging in climate-friendly behavior itself can also have positive mental health effects. Clayton et al. (2021) recommend active involvement in climate-related organizations, open communication about climate anxiety, and integrating climate-friendly behaviors into everyday life as effective coping strategies. Such behaviors may enhance perceived self-efficacy, social connectedness, and a sense of agency, factors that are consistently associated with better psychological well-being (Clayton et al., 2021; Ojala et al., 2021).

Engaging in climate-friendly behavior may therefore serve not only as a response to climate anxiety but also as a mechanism for maintaining or improving mental health by reinforcing a sense of control, moral integrity, and collective efficacy.

Knowledge about climate change and its impact on humans can also affect mental health: on the one hand, it can be linked to climate change anxiety by association with concerns of the future, stress, or feelings of guilt; on the other hand, more knowledge about climate change can be associated with a higher level of motivation for activism or for implementing climate-friendly behavior, which can result in a higher degree of self-efficacy and, hence, well-being (Pihkala, 2020; Ágoston et al., 2022). Additionally, belief in climate change, combined with the belief that humans are the cause, is associated with an even higher level of environmentally friendly behavior and support for climate-friendly policies (Sibley and Kurz, 2013).

Another study by Maran and Begotti (2021) found that a higher frequency of consuming climate change-related content via the media was correlated with higher levels of climate anxiety and other negative feelings. The same study revealed that the consumption of such content was also positively correlated with self-efficacy beliefs about climate change.

Finally, age appears to be an important associated factor. Young people and children have the potential to experience both direct effects, such as distress and trauma from extreme weather events, and indirect effects, including ecological grief, the sense of loss associated with environmental degradation, and the exacerbation of social and economic inequalities (Gislason et al., 2021). Perceptions of climate threats are associated with developmental age, increased media exposure, and increased social media use (Marcolini et al., 2025).

Higher education students in Germany constitute a population characterized by the above-mentioned vulnerabilities, such as relatively young age, limited socioeconomic resources, high levels of media engagement, with mental health conditions as the most common form of disability among students (Kroher et al., 2023). A mixed-methods study with 284 adult students conducted in the United States, confirmed the detrimental effects of climate change on mental health with climate anxiety inhibiting the pursue of life goals or even contributing “to a loss of meaning or purpose” (Schwartz et al., 2023). For Germany, the results of a study with 203 medical students show that their risk of suffering from stress and mental health problems as a reaction to the severity of climate change is increased (Schwaab et al., 2022). Nevertheless, there are still significant gaps in research in this field in Germany: a scoping review by Gebhardt et al. (2023) has shown that research on climate change and health in Germany is “highly insufficient.” In particular, there is a lack of knowledge about how to successfully adapt to and mitigate the negative effects of climate change on mental health. Therefore, this study aimed to examine the link between climate change and the mental health of German higher education students across all disciplines, addressing this distinct gap in existing research and providing initial insights.

2 Materials and methods

From November 2024 to February 2025, an anonymous online survey was conducted among enrolled higher education students at universities across Germany. The questionnaire was provided in German as well as in the English language to enable as many students as possible to participate. The questionnaire combined validated assessment tools for measuring mental stress/health such as the Patient Health Questionnaire (PHQ-4) with four items for the assessment of depression and anxiety with four items (Kroenke et al., 2009), a one-item measurement for self-rated mental health (SRMH) (Ahmad et al., 2014; Stubbs and Achat, 2023), the Climate Change Anxiety Scale (CCAS) in the original English version by Clayton and Karazsia (2020) and in the original German version by Wullenkord et al. (2021) to assess the emotional stress linked to climate change and further climate change factors that may potentially influence mental health. Correlations were calculated between the CCAS and the PHQ-4, the CCAS and the SRMH, and the CCAS and climate change factors.

The questionnaire assessed potentially directly and indirectly associated factors of climate change on mental health that have been identified in the literature:

• Belief in climate change (Sibley and Kurz, 2013; Milfont et al., 2015; Zawadzki et al., 2020; Ojala et al., 2021),

• Knowledge about climate change (Pihkala, 2020; Ágoston et al., 2022),

• Information frequencies and pathways (social media, social environment, news, course of study, work, informing oneself, others) regarding climate change (Maran and Begotti, 2021; Ojala et al., 2021; Verlie, 2021),

• First-hand experience of extreme weather events attributable to climate change (Clayton et al., 2017; Cissé et al., 2022),

• Diagnosed mental illness (Clayton et al., 2017; Cissé et al., 2022),

• Migration background (van Daalen et al., 2024), and

• Motivation for and existing climate-friendly behavior (Clayton, 2020; Clayton et al., 2021; Ojala et al., 2021; Wullenkord et al., 2021).

Furthermore, the questionnaire included questions about wishes for support in dealing with climate change, as well as social demographics such as age and gender.

In line with a targeted non-probability sampling approach, an internet search resulted in a total of 427 universities in Germany at that time, all of which were contacted. 79 universities responded and shared the survey with their students, whereas 26 refused to actively disseminate the student survey. The research team reached out to further higher education related networks across Germany and promoted the survey via the researchers’ home institution’s social media channel. Finally, 4,658 students from 190 universities across all subject groups¹ in Germany participated in the survey. For the first screening of the collected responses, Microsoft Excel was used. 164 cases with contradictory statements, as well as hateful or discriminatory comments, were removed, resulting in 4494 cases included in the statistical analysis.

Using the software R, (semi) metric variables were examined for frequencies and distributions. Assumptions for possible correlation tests were also tested. Spearman rank correlations were calculated between the CCAS and the SRMH, between the CCAS and PHQ4, as well as between the CCAS and potential mental health-related factors of climate change, because the assumptions required for simple linear regression or Pearson correlation, such as normality, homoscedasticity, and the absence of outliers, were not met.

Firstly, for the bivariate analysis, the correlations between the CCAS and the PHQ-4, as well as between the CCAS and the SRMH, were calculated to identify associations between climate change anxiety and psychological distress and between climate change anxiety and self-rated mental health. Afterward, correlations for the other variables potentially associated with climate change anxiety or vice versa were calculated. The Spearman rank correlation’s effect size, rho, was assessed according to Cohen’s classification (Cohen, 1988).

To assess the correlation between gender and CCAS, the eta coefficient was used. To assess the effect size, eta², Cohen’s classification was also used (Cohen, 1988). To determine the direction of this correlation, Spearman’s rank correlation was used, with gender coded as a binary variable (female as “0” and male as “1”).

To achieve a more reliable and realistic estimate of the relationship between different associated factors on climate change anxiety, a regression analysis was conducted. Due to violations of the assumptions for multiple regression analysis and outliers that did not result from incorrect entries or any other cause for exclusion, an MM robust regression analysis was chosen. Due to multicollinearity between some variables, two different MM robust regression models were carried out. From the first model, one variable that showed high multicollinearity with other independent variables was removed. From the second model, the excluded independent variable was included, whereas variables that were part of the first model, which showed high multicollinearity with this now included variable, were excluded.

3 Results

Regarding frequencies and the univariate analysis, students of all ages (≤20 years to >35 years) participated, with the majority aged between 21 and 25 years (51.3%; ≤20 years, 14.3%; 26–30 years, 21.7%; 31–35 years, 6.5%; >35 years, 6.2%); 0.1% of the participants did not state their age. The age distribution is presented in.

Almost two-thirds (60.7%) of the participants identified as female, and a good third (34.6%) as male. Few participants identified as diverse (2.6%), of another gender (0.4%), or did not specify their gender (1.6%); 19.5% of respondents had a migrant background. These distributions are presented in.

Almost all respondents (strongly) agreed that climate change was real and caused by humans (96.3%); 2.0% neither agreed nor disagreed, and only 1.7% (strongly) disagreed. The majority of the participants (69.7%) had good knowledge about climate change, and 69.9% had experienced an extreme weather event attributable to climate change. 37.6% agreed or strongly agreed that they already engaged in climate-friendly behavior in their day-to-day life, and even more students (61.1%) agreed or strongly agreed that they were motivated to do so in their day-to-day life in the future.

Concerning climate change information channels, the most prevalent were regular news channels (e.g., TV, radio; 85.6%) and social media (e.g., Instagram and TikTok, X; 74.6%), followed by social networks (e.g., family and friends; 56.7%), independent information searches (44.2%), climate related studies (36.9%), and climate change relevant work (11.9%). Most students (30.9%) used three of the mentioned information channels, 23.4% used two, and 36.7% used four or more information channels (23.1% four, 9.7% five, 3.8% six, and 0.1% seven). Only a very small number of participants (0.2%) did not use any information channels. Regarding frequency, more than half of the respondents (55.1%) received climate change information at least once a week, and 20.2% received it even more frequently (“at least once a day”). 19.2% of the students received information about climate change at least once a month, and 5.3% even less frequently.

Regarding mental health, 18.736% of the respondents stated they had a diagnosed mental illness, whereas 77.926% stated that they did not have one. Only 3.338% did not answer this question. Most students rated their mental health as “good” (41.811%) or “moderate” (32.109%); the extremes on the scale, “very good” (12.550%), “poor” (11.193%)/“very poor” (2.092%), showed lower values, and only 0.245% did not respond to this question. Frequency distributions of diagnosed mental health and self-rated mental health (SRMH). As for the PHQ-4 results, 30.3% of students showed no psychological stress, while 41.1% exhibited mild, 19.1% moderate, and 9.5% severe levels of psychological stress. With respect to climate change anxiety, according to the cut-off score recommended by Cosh et al. (2024), no to minimal climate change anxiety was prevalent in 49.0% of respondents, whereas in 8.8%, mild to moderate, and in 42.2% of the participating students, severe climate change anxiety was measured.

The bivariate analysis showed a positive correlation between climate change anxiety (CCAS) and psychological distress (PHQ-4) and significance at a p-level <0.01. With a value of rho = 0.46, the correlation between the two variables was of medium, almost large, effect size, whereas the CCAS and the SRMH correlated negatively with a medium effect size (p < 0.01, rho = −0.37). For climate change’s potentially associated variables on mental health, results suggest that “belief in climate change,” “knowledge about climate change,” all information channels except “other,” “sums of information channels,” “frequency of received information about climate change,” and “first-hand experienced extreme weather events” attributable to climate change correlated positively with climate change anxiety.

Additionally, motivation for climate-friendly behavior, as well as already applied climate-friendly behavior, correlated positively with climate change anxiety.

Table 1 presents the results of the bivariate analysis of CCAS as the dependent variable and the predictor variables, with corresponding significance levels, effect sizes, and sample sizes.

Gender accounted for a statistically significant proportion of the variance in CCAS scores, with a small-to-medium effect size (p < 0.01, eta² = 0.06). When coded in binary to assess the direction of the correlation between binary gender and the CCAS, the result remained significant and had a small effect size (p < 0.01; rho = −0.24).

Finally, due to high multicollinearity among the variables of the information channels for receiving climate change information and the variable for those channels totaled (VIF > 5), two different MM robust regression models were performed.

• The first multivariate analytical model contained all independent variables except the total information channels. In this model, the variables “climate change belief,” “motivation for climate-friendly behavior,” “existing climate-friendly behavior,” “existing mental illness,” “informing oneself” as an information pathway for climate change information and “frequency of received information” were positively associated with climate change anxiety, and “binary gender” was negatively associated with climate change anxiety at a significance level of p < 0.01. The variables “experienced extreme weather event” and “social environment” as information pathways and “other” information pathways (other than those provided in the survey) had a positive association, whereas “news” as an information pathway and “age” had a negative influence on climate change anxiety at a significance level of p < 0.05. “Social media,” “course of study,” and “work” as information pathways, as well as “knowledge about climate change” and “migrant background,” did not a relationship with climate change anxiety at a significance level of p < 0.05 in this model. The adjusted R² value of the first model was 0.3537 (R² = 0.3569).

• The second model included all independent variables except the various information channels. This time, the total number of information channels was included as a variable. In this model the variables “climate change belief,” “motivation for climate-friendly behavior,” “existing climate-friendly behavior,” “existing mental illness,” the “information pathways totaled” to receive information about climate change, and the “frequency of received information” had a positive association, and “binary gender” had a negative association with climate change anxiety at a significance level of p < 0.01. The variables “experienced extreme weather event” and “migrant background” were positively associated with climate change anxiety at a significance level of p < 0.05. “Knowledge about climate change” and “age” did not an association with climate change anxiety at the significance level of p < 0.05 in this model. In this second model, the adjusted R² value was 0.3459 (R² = 0.348).

Both models had 1,076 observations with missing data, which had been removed from the analysis.

4 Discussion

Climate change anxiety appears to be a relevant psychological response to climate factors among higher education students in Germany. The study conveyed that more than half (51.0%) of the study participants experienced climate change anxiety, hereof 42.2% severely; almost half reported no to minimal anxiety.

The positive correlation between CCAS and PHQ-4 confirms a clear association between climate change anxiety and general mental health. This pattern is further supported by the negative correlation between CCAS and SRMH, suggesting students who feel more burdened by climate change also tend to evaluate their overall mental health less favorably.

Regardless of climate change anxiety, many German students seem to be suffering from psychological strain: in 19.1% of the participants, moderate psychological distress was measured, which corresponds to the “yellow flag” range of the PHQ-4, and an additional 9.5% fell into the “red flag” range. PHQ-4 sum scores in the “yellow flag” and the “red flag” range indicate the presence of a depressive or an anxiety disorder in which the individual calculation of the subscale scores is advised, “to investigate if the individual predominantly suffers from anxiety, depression, or both” (Löwe et al., 2010).

In contrast to previous research in German-speaking samples, e.g., the 2021 study by Wullenkord et al. (2021) in which overall levels of climate anxiety and correlations between the CCAS and the PHQ-4 were low, our recent findings indicated a higher level of climate change anxiety and medium, almost strong, correlations between the CCAS and the PHQ-4 among university students in Germany. This may reflect emerging evidence that young people experience increasing levels of climate-related emotions and anxiety.

To further contextualize these findings, detailed statistical analyses were conducted to identify the specific factors associated with climate change anxiety. The following section summarizes the interpretation of the bivariate analysis, followed by the interpretation of the multivariate analysis.

4.1 Interpretation of the bivariate analysis

Overall, climate change anxiety was associated with poorer general mental health. To better understand which factors are linked to higher levels of climate change anxiety, the following section presents the interpretation of the bivariate analysis. The remaining significant and positive correlations of the predictors with the CCAS are interpreted as follows:

• The higher climate change anxiety was,

  • the stronger were the beliefs about climate change;

  • the better was the knowledge about climate change;

  • the higher was the frequency of received climate change information;

  • the more information paths were being used to receive information about climate change.

• The older the participants were, the higher the climate change anxiety was.

• Motivation for climate-protecting behavior and existing climate-protecting behavior were higher at higher levels of climate change anxiety.

• Climate change anxiety was higher in students who had experienced at least one extreme weather event compared to students who had not, as well as in students with an existing mental illness compared to students without mental illness.

• With regard to individual information channels, students who used social media, social networks, and news, studied or worked in a related field, or actively sought out information on climate change, reported higher anxiety about climate change than those who did not use any of these channels.

As the female gender was coded with zero and the male gender was coded with one, the negative correlation can be interpreted to mean that students who identified as female had a significantly higher climate change anxiety compared to students who identified as male. In the bivariate analysis, migrant background and other information pathways not listed did not appear to have a significant association with climate change anxiety at the significance level of p < 0.05. While the bivariate analysis highlights straightforward relationships between individual variables and climate change anxiety, the multivariate analysis provides a more comprehensive understanding of these patterns by examining which factors remain significant when considered simultaneously.

4.2 Interpretation of the multivariate analysis

The results of the first MM robust regression model can be interpreted as follows:

• A higher level of climate change anxiety was associated with a higher motivation for climate-friendly behavior and more practiced climate protection in day-to-day life. The coefficients of motivation for climate protection and for practiced climate protection were 2.00 and 0.81, respectively, indicating a 2.00 unit increase in climate change anxiety was associated with a one unit increase in motivation for climate-protective behavior [95% CI (1.67, 2.32)]. A 0.81 unit increase in climate change anxiety was associated with a one unit increase in climate-protective behavior [95% CI (0.50, 1.12)].

• The stronger the climate change beliefs and the higher the frequency of climate change information received, the higher the climate change anxiety.

• Climate change anxiety was higher in students who had a diagnosed mental illness and in students who had experienced an extreme weather event (attributable to climate change), compared to students who had not.

• Students who obtained information themselves and those who received information about climate change from their social environment or other channels beyond those provided in the survey experienced higher climate change anxiety than students who did not use these information channels.

• Participants who received climate change information through real news had lower climate change anxiety than those who did not use the news as an information pathway.

• Female students had a significantly higher climate change anxiety compared to students who identified as male.

• The younger the participants were, the higher was their climate change anxiety.

Table 2 presents the coefficients, their respective significances, and confidence intervals for this analysis model.

The model’s predictors explain 35.4% of the variance in climate change anxiety. The adjusted R² was used to assess how much of the variance was explained. The fact that R², with a value of 0.3569, was very close to the adjusted R² (0.3537) shows that the model does not contain predictors that do not explain any or only very few of the variance in the dependent variable.

The results of the second robust regression analysis, containing the total information pathways, rather than the various information pathways, differed slightly from those of the first model. The total number of information pathways was positively associated with climate change anxiety, meaning that the more information pathways were used to obtain climate change information, the higher was the climate change anxiety. Moreover, the results from the second model were in line with the results of the first model, except for two sociodemographic predictors: age lost its significant association with climate change anxiety, whereas a migrant background suggested a significant association, where students with a migrant background had higher climate change anxiety compared to students without a migrant background. The results of the second robust regression model are shown in Table 3.

The predictors of this second model explain 34.6% of the variance in climate change anxiety. In this model, both R² values were very similar as well (R² = 0.348 and adjusted R² = 0.3459).

Taken together, these multivariate findings provide a coherent analytical foundation for interpreting the broader patterns that emerge in this study, allowing the subsequent discussion to focus on how these statistically identified factors manifest in the mental health of German university students.

With regard to associated factors, the findings suggest a consistent pattern in the mental health of German university students: the higher the climate change anxiety, the stronger the climate change beliefs, the more actual climate-friendly behavior and the higher the motivation for climate-friendly behavior. Climate change anxiety could be interpreted here as a statistically associated variable between climate change beliefs and climate-friendly behavior. The positive effects of pro-environmental behavior on mental health, as suggested by Clayton (2020), could not be confirmed with this cross-sectional design.

Experiencing extreme weather events attributable to climate change was also associated with elevated anxiety, consistent with evidence that direct exposure to climate-related events can have detrimental psychological consequences (Clayton et al., 2017; Cissé et al., 2022). Gender differences were evident as well, with female students showing higher psychological strain due to climate change than male students, a pattern regularly documented in climate anxiety research (Clayton et al., 2021; Ojala et al., 2021; Wullenkord et al., 2021). Taken together, these results correspond with international literature describing climate change as a factor that may intensify existing vulnerabilities (Fahrudin et al., 2024).

One central aspect arising from the findings is the possible relationship with information pathways. Students reported receiving climate-related content through numerous channels, and many engaged with such information frequently. This suggests that indirect effects of climate change, mediated through exposure to information about it, may also be associated with shaping university students’ mental health. The bivariate analyses showed that all information pathways except “other” were significantly associated with climate change anxiety. This analysis could indicate that a broad spectrum of media and interpersonal sources may be associated with heightened emotional responses.

However, in the multivariate models, several of these pathways, specifically social media, study-related content, and work-related information, no longer showed a significant association when other factors were controlled for. At the same time, “other” information channels, which were not significant in the bivariate analysis, became significant in the first multivariate model. This pattern suggests different information pathways may overlap in their effects, and their association partly depends on the presence of other variables.

The following figure displays the variables that correlated with the CCAS on a significance level of p ≤ 0.05 throughout all statistical analysis. The line thickness represents the effect size based on the results of the Spearman rank correlations of the bivariate analysis (see Figure 1).

Figure 1

Overall, the findings support previous research highlighting the role of media environments in shaping emotional responses to climate issues. Higher attention to climate change information has been linked to increased climate anxiety in university student samples, and media coverage has been shown to be a significant associated factor of eco-anxiety in broader populations (Maran and Begotti, 2021; Gunasiri et al., 2022; Marcolini et al., 2025). One interesting, because contrasting, finding is, however, that respondents who received such information through regular, i.e., real news appeared to show lower climate change anxiety. This may be explained by the fact that “real news” channels still experience a high level of basic trust among the German population as opposed to fake news or social media sources (WDR, 2025). However, as with prior cross-sectional studies, it remains unclear whether certain information channels contribute causally to climate anxiety or whether individuals with higher anxiety are more likely to seek out climate-related information. Longitudinal studies will be needed to examine these dynamics more clearly.

Beyond interpreting individual associated factors, the present findings need to be situated within the broader international research landscape. A scoping review on climate change and mental health research suggests a strong geographical imbalance in existing research. Most original studies have been conducted in a small number of countries, particularly Australia, Canada, and the United States, while many regions remain underrepresented (Charlson et al., 2021). Germany is not among the countries contributing the most empirical studies, underscoring a gap in nationally specific evidence. In this context, the present study offers unique insights that may help to develop targeted measures to improve students’ resilience against climate anxiety. One example of how such measures could look like can be witnessed in the frame of the German research project KLIM MENT that develops measures tailored to distinct needs communicated by students during participatory focus group discussions².

As both models in the multivariate analysis account for more than one-third of the variance in climate change anxiety, these findings underscore the importance of the aforementioned associated factors and indicate that further research is advisable to identify additional associated factors. For example, the variable age showed conflicting results in this study. In the bivariate analysis, age correlated positively, although with a close to zero effect size. In the first robust regression model, age was negatively correlated with climate change anxiety, whereas in the second model, no significant correlation was found. Hence, age is not consistently associated with climate change anxiety across models.

4.3 Limitations

As this is a correlational study, further research is required to confirm any causal influences of climate change factors on the mental health of German university students. A direct demographic comparison against the official benchmarks from the German Federal Statistical Office [Statistisches Bundesamt (Destatis), 2024, 2025] for the corresponding survey period 2024/2025, which recorded a total of 2,864,122 enrolled students nationwide, revealed meaningful deviations between the present sample and the national population. Most notably, female students are significantly over-represented in the sample compared to the national average (60.7% vs. 51.2% nationally), while male students are under-represented (34.6% vs. 48.8% nationally) [Statistisches Bundesamt (Destatis), 2025, Table 21311-b01]. With respect to age, the sample more closely mirrors the national distribution; the 26–30 age bracket aligns with the national baselines within a fraction of a percentage point (21.7% vs. 21.9% nationally), Though a slight over-representation is observed in the core 21–25 age bracket (51.3% vs. 44.8% nationally) and a minor under-representation of students aged 20 or under (14.3% vs. 17.5% nationally) [Statistisches Bundesamt (Destatis), 2025, Table 21311–15].

These deviations are attributable in part to the non-probability convenience sampling procedure employed; whereby participant recruitment relied on institutional networks and social media channels. Participation was dependent on the cooperation of institutional deans and student representatives and was further subjected to self-selection processes, likely amplified by participant’s pre-existing engagement with climate-related issues. Under these conditions, statistical weighting could not be applied to align the sample with the national benchmark of 2,864,122 students [Statistisches Bundesamt (Destatis), 2025, Table 21311–15]. Application of weighting would have introduced a substantial variance inflation without adequately correcting for the underlying psychological selection bias. Therefore, data was analyzed in unweighted form.

Despite these limitations, the study benefits considerably from its scale and thematic breadth. With data drawn from across almost half of all German universities, spanning all major subject areas, age groups, and gender identities, the dataset provides a broad empirical impression of how climate change is experienced within this population. Nevertheless, the possibility of self-selection bias cannot be excluded, and students with a stronger personal interest in climate-related topics may have been systematically more likely to participate, which should be considered when interpreting the findings.

The PHQ-4 and SRMH scales are validated tools for assessing mental health. However, they are very compact as they contain a maximum of four items and thus tend to measure mental distress in a general manner, failing to account for potential climate change-related stressors (Ahmad et al., 2014; Stubbs and Achat, 2023; Kroenke et al., 2009).

The CCAS scale is also a validated instrument and seeks to assess climate anxiety as depicted in its distinct name. However, after testing the scale, Wullenkord et al. (2021) are rather critical of it. They recommend revising the scale, as they were unable to replicate the factor structure. The authors tend to believe that the scale does not measure climate anxiety, but rather “climate-related emotional impairment as a consequence of climate-related distress” (Wullenkord et al., 2021). Critically, this is not an isolated observation, but a pattern found across multiple independent validation studies. Larionow et al. (2022) reach the same conclusion in their Polish validation study of the CCAS: the CCAS “seems to measure the emotional and cognitive response (not unequivocally maladaptive) related to climate change” (Larionow et al., 2022), i.e., “a general climate-related emotional impairment, rather than distinctly and comprehensively capturing climate anxiety,” as Wullenkord et al. (2021) had described it. Despite cross-cultural validity of the CCAS, results of a COSMIN systematic review revealed inconsistent results for its structural validity (Ramsay et al., 2025).

These contradictory associations of climate change anxiety with anxiety and depressive symptoms and a need for a distinct definition for climate change anxiety make it difficult to precisely define the concept of climate change anxiety and to measure it accordingly using the CCAS as it currently stands (Wullenkord et al., 2021; Larionow et al., 2022; Hempel et al., 2025).

These concerns are particularly relevant when interpreting the observed correlation between CCAS and PHQ-4 scores (rho = 0.46). If the CCAS is partly capturing general emotional impairment rather than climate anxiety as a distinct construct, some of the associations may reflect conceptual overlap with the relationship between climate anxiety and psychological distress.

However, it should be noted that in the present study the CCAS was used as a total score rather than at the subscale level. Both Wullenkord et al. (2021) and Cruz and High (2022) found that a single-factor structure, i.e., total score, provided a more coherent fit than the proposed two-factor model. This is consistent with the use of the total score in the present study, as collapsing across subscales aligns with a unidimensional conceptualization of the construct. (Wullenkord et al., 2021; Cruz and High, 2022).

5 Conclusion

Among the vulnerable groups, more and more studies provide evidence that young people are especially affected by mental health issues and need specific interventions and safeguards. The study’s findings reinforce the view that climate change can affect mental health, not only through direct environmental factors but also through psychological and social pathways. For universities and mental health services, this underscores the need to consider climate-related stress in their support structures.

The analysis identified and confirmed several associated factors, as well as vulnerabilities for associations between climate change and mental health. These include climate change beliefs, pre-existing mental illness, extreme weather experiences, motivation for and existing climate-friendly behavior, and gender. Moreover, information about the climate phenomenon is linked to university students’ mental health, namely the frequency, scope, social environment, news, and other pathways through which they received climate change information.

These findings extend existing international findings to a large student sample in Germany and provide a solid basis of knowledge for this target group in this previously under-researched area of the mental effects of climate change. As the study is correlational, it cannot determine causal relationships. Nevertheless, the results indicate that many students feel psychologically affected by climate change, and targeted support may help them cope with this burden. Universities and health services may benefit from considering integrating resources that address climate-related stress and help students navigate the emotional potential impact of global environmental change.

Larger-scale representative studies, as well as in-depth qualitative studies, could provide a clearer picture of the extent to which climate change influences university students’ mental health in Germany. Future work should also explore additional links to mental distress among university students, with the aim of developing effective strategies to reduce psychological strain and promote resilience.

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